Living Standards in British Africa

in a Comparative Perspective, 1880-1945 Is Poverty Destiny?

Student: Supervisor:

M.F.M. van Waijenburg Dr. E.H.P. Frankema

Student number: 0338990 Assistant Professor Economic History

Faculty of the Humanities

Utrecht University

MA Thesis Comparative History

March 2010 Second Supervisor:

Faculty of the Humanities Prof. Dr. M. Prak

Utrecht University Professor Socio-Economic History

Faculty of the Humanities

Utrecht University

CONTENTS

ACKNOWLEDGEMENTS

CONTENTS

1 INTRODUCTION 1

2 GEOGRAPHICAL, TECHNOLOGICAL OR INSTITUTIONAL IMPEDIMENTS 7

2.1 Introduction 7

2.2 Input-Orientated Approaches: Human Capital and Geographical Endowments 7

2.2.1 Solow Growth and the Human Capital Stock

2.2.2 Geographical Endowments

2.3 Socio-Political Structures – Institutional Barriers 13

2.4 New Empirical Evidence – Implications for the Current Academic Debate 18

2.4.1 Compilation and Validity of the Dataset

2.4.2 The ‘Missing’ Numbers – GDP per Capita Performance in Colonial Africa

2.4.3 Income Growth and Distribution – A Revision of Colonialism’s Extractive

Nature?

2.5 The African Colonial Economy – A New Research Agenda 25

3 COMPILATION DATA 28

3.1 Introduction 28

3.2 Data and Methodology 32

3.2.1 Sample Selection

3.2.2 Compilation of the Wage Data

3.2.3 Compilation of the Price Data

3.3 Results 44

3.3.1 The Development of Real Wages – Long-run Trends and Levels

3.3.2 Periodical Changes in Nominal Wage, Price and Real Wage Levels

3.3.3 African Real Wages in a Comparative Perspective

3.3.4 Real Wages and Taxation Pressure

3.4 Conclusion 73

4 CONCLUSION – REFLECTIONS ON THE AFRICAN GROWTH TRAGEDY 75

BIBLIOGRAPHY 80

APPENDICES

I. Wage and Price Indices

II. Figures and Tables

1

1. INTRODUCTION

The unprecedented global income disparities that characterize the modern world, both among

and within nations, remain one of today’s most profound concerns. Ever since the economic

‘take-off’ of several prime movers in the course of the nineteenth century, a number of

regions have witnessed an astonishing steady transformation in terms of living standards. For

most individuals in the developed world, per capita income and purchasing power has

rocketed, and the spectrum of available and affordable consumer goods has widened.

Moreover, on the physiological plane, unparalleled levels have been reached, with average

body size increasing over fifty percent and human life expectancy even doubling. This trend

of taller and healthier humans has, in turn, further accelerated the process of economic

growth.1 However, this remarkable rise in living standards and prosperity, in particular its

long-term sustainable variant, has unfortunately not yet been attained globally. Although all

world regions took part in the economic boom of the early post-WWII decades, for many of

them this epoch of economic convergence was soon reversed again.2 More than 168 countries

experienced economic stagnation or even deterioration after the mid-1970s, and a pattern of

increasing global divergence vis-à-vis the OECD countries set in. In particular the former

USSR states, the African continent and Latin America have not been able to maintain their

earlier steady development achievements, and nearly all of them have relapsed into a state of

comparative economic stagnation, political instability, poverty, and low standards of living.

Ranking consistently at the bottom of almost all of the general development indices,

Sub-Saharan Africa (SSA) has become a rewarding focal point for scholars who seek to

explain dismal economic growth performance.3 This trend contrasts sharply with the pre-

1970s literature on Africa’s economy, when it was believed that the continent – with its low

population density and rich natural resource endowments – had ample opportunities for

economic expansion. Influential publications at the time, therefore, perceived Africa’s growth

potential as much stronger than that of East Asia.4 Evidently, these optimistic visions were far

1 For an elaborate discussion of the synergetic relationship between physiological and economic progress, see for

example: Robert Fogel, The Escape from Hunger and Premature Death, 1700-2100: Europe, America and the

Third World, (Cambridge: Cambridge University Press, 2004). 2 As has been pointed out by Angus Maddison, the global economy grew at a historically unique rate between

1950 and 1973 (when the oil shocks set in). World per capita income increased by nearly 3 per cent annually, and

global trade by close to 8 per cent. Although all regions took part in this economic upheaval in these decades,

Europe and East Asia had the fasted growth records. See: Angus Maddison, The World Economy: A Millennial

Perspective. Paris: Development Centre of the Organisation for Economic Co-operation and Development, 2002. 3 Any reference to ‘SSA’ or more generally ‘Africa’ in this paper will hereafter refer to the countries south of the

Sahara, except for South Africa. 4 See: Gunner Myrdal, Asian Drama: An Inquiry into the Poverty of Nations (3 Vols.), (Harmondsworth,

Middlesex: Penguin Books, 1968); Andrew M. Kamarck, The Economics of African Development, (New York:

2

from realized. As can be derived from graph 1.1, depicting SSA’s per capita income trajectory

from 1950-2006, Africa is an ultimate exemplar of a region whose ‘growth tragedy’ became

established during the 1970s, when the per capita income growth trend stagnated, or even fell

below previously attained levels.5 Interestingly, conventional contemporary studies on the

underlying causes of Africa’s dismal performance have frequently ignored the two decades of

growth preceding it, or have simply dismissed it as a form of ‘catching-up’ growth. Let alone

have any systematic analyses been conducted about the economy’s functioning during the first

part of the twentieth century, when the continent was under colonial rule. Consequently, the

theoretical arguments that have been postulated about SSA’s structural growth impediments –

whether technological, geographical, or institutional in nature – have traits of deterministic

disaster-proneness, suggesting that poverty is destiny, and have too often been based on

speculative premises without a solid empirical basis.

Figure 1.1: GDP per capita Performance Sub-Saharan Africa, 1950-2006

(In 1990 International Geary-Khamis dollars)

Source: Maddison, “Statistics on World Population, GDP and Per Capita GDP, 1-2006 AD”

Praeger, 1967). References partially derived from: Easterly, W. and Levine, R. "Africa’s Growth Tragedy:

Policies and Ethnic Divisions", Quarterly Journal of Economics 112, 1997: 1203. 5 The figures used for graph 1.1 are based on an average of the GDP per capita estimates for all countries south

of the Sahara, thereby excluding Algeria, Egypt, Libya, Morocco and Tunisia from this aggregate trend. For data

observations of individual countries see: Angus Maddison, “Statistics on World Population, GDP and Per Capita

GDP, 1-2006 AD”, http://www.ggdc.net/maddison/.

0

200

400

600

800

1000

1200

1400

1600

1800

1950 1955 1960 1965 1970 1975 1980 1985 1990 1995

Average GDP per capita for SSA

3

Not until recently though, have serious efforts been made to reconstruct Africa’s

colonial growth record. Moreover, first insights have even been presented into the

development of living standards in the late nineteenth and early twentieth century. These

valuable contributions, albeit somewhat preliminary, allow for a revision of SSA’s long-term

economic development pattern, based on actual quantitative empirical evidence from this

early period. From these new research projects, it appears that Africa’s growth record before

WWII has been widely underestimated. The agenda-setting GDP time-series from 1910-1950,

as presented by Jan Pieter Smits, suggests a respectable and even comparatively good

performance of the African colonial economy. Additionally, a growing body of literature

seems to support this image of the emergence of a fairly dynamic economy under colonial

rule. Moreover, such studies, in part responding to popular allegations about the inherent

‘extractive nature’ of colonial institutions, even point towards increases in living standards for

the average (British) colonial subject.6

Building on this new research agenda, this economic historical study sets out to

contribute to our understanding of the performance of the British African colonial economy in

general, and the development of living standards in particular. First, in chapter 2, an in-depth

discussion will be provided of the existing body of growth literature, and, following from this,

some reflections will be presented on the reigning paradigm that ‘poverty is – either

geographical or institutional – destiny’. For the latter evaluation, some of the most recent

empirical evidence will be presented on both the colonial growth record and the development

of living standards in this period. From here, the central questions of this study will follow. If

the economy under colonial rule was indeed fairly dynamic, then, were the economic rents

resulting from such commercial expansion mainly extracted by colonial authorities and local

elite representatives, or did living conditions improve as well for the average African subject?

In chapter 3, the empirical results of this study on living standards will be presented,

compared and analyzed. To examine the development of standards of living, two empirical

6 Jan-Pieter Smits, “Economic Growth and Structural Change in Sub Saharan Africa during the Twentieth

Century: New Empirical Evidence and Outlook to 2030,” Groningen Growth and Development Centre.

Presented at the Conference World Economic Performance; Past, present and future, Groningen, 2006. See for

the other works referred to here: Gareth Austin, “The ‘Reversal of Fortune’ Thesis and the Compression of

History: Perspectives from African and Comparative Economic History”, Journal of International Development

20, 2008: 996-1027; Gareth Austin, Jörg Baten, and Alexander Moradi, “Exploring the evolution of living

standards in Ghana, 1880-2000: An anthropometric approach”, presented at the Annual Conference of the

Economic History Society, University of Exeter, 2007; Moradi, “Towards an Objective Account of Nutrition and

Health in Colonial Kenya: A Study of Stature in African Army Recruits and Civilians, 1880-1980.” Centre for

the Study of African Economies, Working Paper No. 284, 2008; and Ewout Frankema, “Raising Revenue in the

British Empire, 1870-1940: How ‘extractive’ were colonial taxes?”, presented at the WEHC, University of

Utrecht, 2009.

4

indicators have been created for eight different colonies or protectorates in British Africa: (1)

a time-series of absolute real wage levels for urban and rural unskilled labour, indicating the

development of purchasing power for an as large as possible share of the population over

time; and (2) a time-series for total and direct per capita taxation incidence, allowing for some

insights on overall the taxability of the population, and on the impact of colonial economic

policy on real wage levels. The British African colonies that have been included in this real

wage study are respectively: The Gambia, The Gold Coast (current Ghana), Kenya (former

East Africa Protectorate), Mauritius, Nigeria, Nyasaland (former Central Africa Protectorate

and current Malawi), Sierra Leone, and Uganda. The temporal scope of this analysis, ranging

from 1880-1945, entails that for the first time nearly the entire period under effective British

rule has been included.

By placing the empirical findings in various dia-chronological and intra-spatial

comparative frameworks, this study sets out to transcend some of the limitations that have

characterized previous contributions on the advancement of living standards in colonial

Africa. The benefits for social scientists of conducting comparative analyses are multiple. As

explicated by Charles Tilly, scholars embark on such studies to distil the ‘individualizing’,

‘universalizing’, ‘variation-finding’ or ‘encompassing’ causal patterns of macro-social

phenomena.7 This comparative study on living standards in British Africa is based on both

universalizing and variation-finding components. The global comparative perspective, the

core of this study, has a clear variation-finding objective, seeking to reveal whether living

standards, both in terms of trend and level, differed from other parts of the world.

Additionally, by incorporating a large set of countries into the analysis and not aggregating

them into one unit, it becomes possible to make intra-African comparisons as well. These

intra-African comparisons are both nationally and regionally-based; the former highlighting

variation between the individual African colonies; the latter emphasizing common patterns

within the regions (West and East Africa) when contrasted with each other.

Nonetheless, it has to be mentioned here that carrying out a solid and systematic

comparative study, especially when posing historical questions, is not without pitfalls. As a

result of the objective to make generalizations about causal patterns of complex historical

7 Individualizing comparisons attempt to distinguish “a small number of cases in order to grasp the peculiarities

of each case”. Universalizing comparisons seek to “establish that every instance of a phenomenon follows

essentially the same rule.” Variation-finding comparisons aim to ascertain a “principle of variation in the

character or intensity of a phenomenon by examining systematic differences between instances.” And finally,

encompassing comparisons seek to place “different instance at various locations within the same system on the

way to explaining their characteristics as a function of the varying relationships to the system as a whole.” See:

Tilly Charles Tilly, Big Structures, Large Processes, Huge Comparisons, (New York: Russell Sage, 1984): 82-3.

5

phenomena, such comparative analyses are bound to find themselves caught in the tension

field between qualitative and quantitative approaches. Qualitative, or case-oriented, studies

generally take on a holistic form, where each single case is treated as a ‘whole’, embedding

the examined phenomena fully in a historical context. One of the main weaknesses of the

case-oriented method, though, is that it is incapacitated to deal with a large number of cases as

a result of causal complexity. In order to substantiate general patterns, the empirical basis of

the researcher’s analysis should be based on as large as possible a sample size. However, the

exponential nature of causal complexity makes it particularly difficult for researchers to take

on even more than two or three cases.

The variable-oriented method, on the other hand, relying upon statistical techniques, can

take on a large number of cases by establishing controls over the conditions and causes of

variation. By simplifying assumptions about causes and their interrelation, the researcher can

reduce the complexity of the data structure artificially. Yet, as a result of such simplifications,

the variable-oriented method has to give way to the holistic nature of the individual cases.

Cases in these types of studies are not viewed as wholes, but as collections of parts, and are

thus no longer understood within the context of the whole, which in turn can lead to such a

de-contextualization that the study produces meaningless results that have little connection to

actual historical processes. In other words, the objective of generality here is achieved at the

expense of causal complexity.8

This comparative study is neither purely case- nor variable-oriented. First and foremost,

the nature of the main research inquiry, placing the development of British African living

standards in a global perspective, concerns the question of causality in an indirect manner. As

will be explicated more elaborately in chapter 2, this comparative analysis aims to contribute

to our understanding of the Sub-Saharan growth potential by using the empirical results on

living standards to assess the validity of other hypothesized causal relationships, such as

geographical and institutional impediments, that have become well-established in the body of

growth literature. More specifically, we set out to examine whether the African real wage

trends and levels lend more support to hypotheses of a persistently stagnant economy, or to

that of a dynamic colonial economy in which attained rents were dispersed at all levels of

society. As such, this study is not as much caught in the methodological tension field between

qualitative and quantitative strategies, allowing for comparisons that can both treat cases

8 See for an excellent discussion of the methodological divide in comparative studies: Charles Ragin, The

Comparative Method. Moving Beyond Qualitative and Quantitative Strategies, (Berkeley: University of

California Press, 1989).

6

holistically and take on a large number of cases.

Finally, in the concluding part of this study, a summary of the main findings will be

presented, followed by some brief reflections on broader thematic questions that follow from

the results found in this empirical analysis. If most of these countries were able to perform

relatively well in the first part of the twentieth century, and can therefore not be considered

structurally disaster-prone or destined for poverty, why, then, did their economic growth

trajectory collapse so dramatically in the closing decades of the century? Why, if the root

causes of the current economic stagnation cannot rigidly be attributed to geographical

impediments or poor colonial institutions, does most of SSA up until today seem to have such

great difficulties in creating a relatively stable, well-functioning economy again? Evidently,

these questions have significant implications for the configuration of a future research agenda

on what causes growth and what impedes it. Moreover, as research agendas could intersect

with and complement the domain of the deep-seated problems that characterize current

development strategies, it is important to evaluate what the core areas are that we still know

relatively little about. It will be argued that economic historical research on Africa’s colonial

political-economy is such an essential research area, one that will matter for the way in which

we will interpret SSA’s development past, its present and its future outlook; and how such

scholarly contributions could go beyond the deterministic approaches that have dominated the

debate on Africa’s development trajectory so far.

7

2. TECHNOLOGICAL, GEOGRAPHICAL AND INSTITUTIONAL IMPEDIMENTS

2.1 Introduction

The sum of economic literature that is concerned with unequal growth achievements is

extensive, reflecting clear patterns of the different approaches that have been taken towards

this end. In line of Adam Smith, they ask themselves, why, and how, did the wealth of certain

nations come about? Why is economic development still far from a universal phenomenon?

What impedes developing countries in attaining higher per capita income levels? And why,

more specifically, does SSA seem to have the greatest development problems? In economics,

albeit diverging somewhat in methodological approaches, traditionally the fields of

development economics and economic history have been preoccupied with these profound

questions.9 This chapter will start out with a general overview of the various explanations that

have been promulgated for Africa’s poor growth record, focussing both on their strengths and

on their limitations. It will become evident that the rather deterministic variants of these

approaches fall short in their explanatory power to account for SSA’s recent path of economic

stagnation. In order to interpret the African growth tragedy in a more convincingly manner, it

is indispensable to gain deeper insight in the actual performance of its economy over a longer

time frame; a time frame longer than the five to six decades following WWII. This chapter

will, therefore, finish with a brief discussion of such recent pioneering answers – in which

general trends about SSA’s performance under colonial rule are being revealed – and their

implications for the broader economic growth debate.

2.2 Input-oriented approaches: Technology, Human Capital and Geographical Endowments

2.2.1 Solow Growth and the Human Capital Stock

Classical economic theory, with its emphasis on output levels, has proven an inspirational

starting point for both development economists and economic historians alike. Following

these theoretical lines of thought, the economy is perceived as a sort of transformative

apparatus, through which input quantities, the labour (L) and capital stock (K), are being

converted into output quantities. Ever since Robert Solow has demonstrated that the physical

amount of inputs can only account for a small share of realized output levels, and that, instead,

it is the technology level (A) that allows a society’s economy to progress towards a higher

9 Apart from specialized fields in economics, in the political science department, the field of political economy

has increasingly turned towards these questions as well. Additionally, economic history has been a discipline

located in both economics and history departments.

8

steady-state (k*) growth level, researchers have increasingly turned towards such arguments

of ‘technological’ change.10

A particularly popular variation of this neo-classical kind of

national income theory, also referred to as the augmented Solow growth model, has been

presented by N.G. Mankiw, David Romer and David Weil. Alongside investment rates in

physical capital, they incorporate investment rates in human capital into the production

function – both in terms of skills and knowledge – which accordingly also come to affect the

equilibrium income.11

For SSA, the implications of these, as termed by Dani Rodrik,

‘proximate cause oriented’ frameworks affects the manner in which its growth problems are

perceived; it being largely the result of the low technological standards in labour and capital,

thereby failing to realize “(a) physical capital deepening; (b) human capital accumulation, and

(c) productivity growth.”12

Albeit recognizing that technology levels in capital forms matter, both material and

human, this quantitative strategy is still severely hampered in its ability to establish causality.

The most problematic effect, in this respect, is that of reverse causality: is the independent

variable, the income level (Y) caused by the independent variables, low investment levels in

technology, or vice versa? Although statistical techniques do exist to control for such wide-

ranging econometric problems, in terms of growth analysis, they remain difficult to utilize.

Moreover, as generally put in question by economic historians, even if these correlations

reflect causality, they still fail to explain why economies fail to realize their full growth

potential.13

This more ‘ultimate cause’ or ‘deep cause oriented’ outlook on economic

development, in which structural patterns are central to the question of dismal growth

10

Robert M. Solow, “Technical Change and the Aggregate Production Function,” Review of Economics and

Statistics 39, (1957): 312-320. 11

N.G. Mankiw, David Romer, and David Weil, “A Contribution to the Empirics of Economic Growth,”

Quarterly Journal of Economics 107, (1992): 407–437. Other significant contributions made along these lines to

account for SSA’s failure to attain higher growth rates are for example: R.J. Barro, “Economic growth in a cross

section of countries”, Quarterly Journal of Economics 106, 1991: 407–444. 12

See: Dani Rodrik (ed.), In Search of Prosperity. Analytic Narratives on Economic Growth, (Princeton:

Princeton University Press, 2003): 4. For a more elaborate discussion of ‘proximate’ versus ‘ultimate’ causes

and how they interrelate see p. 3-9. 13

This does not entail that economic historians have not made any, more qualitative, attempts to account for

long-term economic growth patterns, or ‘the rise of the West’, predominantly in terms of technology arguments.

See in this respect: David S. Landes, The Unbound Prometheus: Technological Change and Industrial

Development in Western Europe from 1750 to the Present, (Cambridge: Cambridge University Press, 1969); and

The Wealth and Poverty of Nations: Why Some Are So Rich and Some So Poor, (New York: Norton, 1998), or

Joel Mokyr, The Gifts of Athena: Historical Origins of the Knowledge Economy, (Princeton: Princeton

University Press, 1983). And a more recent account: Gregory Clark, A Farewell to Alms: A Brief Economic

History of the World, (Princeton: Princeton University Press, 2007).

9

performance, seems to be one of the greatest methodological divides between the fields of

development economics and economic history.14

In recent decades, it appears as if the emphasis on structural growth patterns has

gained territory over ‘proximate cause’ modelling, and that the quest to locate development

problems in semi-exogenous or even fully exogenous factors is a more fruitful endeavour. In

particular, the contributions made by development economics, traditionally the more

pragmatic-oriented of the two fields, has come to be regarded as one of suggestive results

obtained through econometric research and mathematical modelling; as one that establishes

correlation rather than causation; and one that, even if successful in reflecting a degree of

causality, still fails to uncover the underlying, structural impediments to economic

development. In these terms, such academic efforts have become increasingly constrained in

explanatory power. Especially the long track record of development economists in advocating

stringent policies for the Third World, that would allegedly correct for their technological

input deficiencies, have by now not only become outdated, but even motivation for a new

form of apologetic discourse of economist’s ‘adventures and misadventures in the tropics’.15

In economic history, the central area of interest for explaining the global divergent

development trajectories in terms of long-run, or ‘deep cause’, input barriers, has found its

main expression in the ‘geography school’, which will be discussed in the next section.

2.2.2 Geographical Impediments

Accounting for economic performance in terms of geographical endowments is not at all a

recent phenomenon. When Adam Smith wrote his famous Inquiry into the Nature and Causes

of the Wealth of Nations, notions of the universality of human nature dominated, and hence he

did not perceive economic disparities to be the result of any cultural differences between

societies. Consequently, with such cultural factors dismissed as irrelevant variables for a

nation’s ability to attain economic growth, geographical factors were believed to explain

14

It has been correctly pointed out by Gareth Austin that until AJR, to whose contributions this chapter will turn

later, most economist’s studies on Africa “were written as if economic history had begun only with the recovery

of political independence from Europe.” Hence, little attention was given by development economists to the

‘ultimate causes’ of Africa’s growth tragedy. See: Gareth Austin, “The ‘Reversal of Fortune’ Thesis and the

Compression of History: Perspectives from African and Comparative Economic History.” Journal of

International Development 20, 2008: 998. 15

See for example: William Easterly, The Elusive Quest for Growth: Economists’ Adventures and Misadventures

in the Tropics, (Cambridge, MA: MIT Press, 2001); and The White Man’s Burden: Why the West’s Efforts to Aid

the Rest Have Done So Much Ill and So Little Good, (Oxford and New York: Oxford University Press, 2006).

10

development differences. Smith maintained that – with the division of labour being limited by

the extent of the market – regions with access to sea-coasts and navigable water ways, had a

distinct advantage over other regions in terms of benefiting from the gains of exchange and

specialization. Hence, his outlook for the African, Russian and Central Asian land masses,

having large ‘locked- in’ inland parts, was somewhat pessimistic.16

Among geography-

oriented scholars, such claims still find great resonance. Their main premise, therefore, is that

the contemporary economic performance of SSA is rooted in its geographical endowments.

Building on and extending Smithian notions, this school reasons that, whether directly or

indirectly, geographical location and climate determine the opportunities for agricultural

productivity, transportation facilities, and even disease environment. Consequently, they

imply, these structural impediments had, have and will continue to have, a negative effect on

the opportunities for Africa’s long-term GDP performance.

As highlighted by Daron Acemoglu, Simon Johnson and James Robinson (hereafter:

AJR), the geography school of thought can be subdivided into two main branches. The first

has stressed the more fixed and direct relationship between geographical location and

economic potential, also referred to as the “time-invariant” geographic variables.17

An

interesting interdisciplinary argument in this respect – applying biological evolutionary theory

to economic development trajectories – has been postulated by ecologist Jared Diamond. In

Guns, Germs and Steel he maintains that Eurasia had a structural comparative advantage over

other parts of the world for development as a result of its geographical and ecological

endowments. The Eurasian continent, in contrast to Australia, the Americas and Africa, is

characterized by a large landmass with an east-west axis that is situated in a ‘temperate

ecological zone’. Consequently, Eurasia benefited from environmental differences, such as the

presence of a large natural selection of plant and animal species suitable for domestication,

and a relatively homogeneous disease climate. This, in time, led to the rise of sedentary

agriculture. Moreover, he argues, the use of domesticated animals strengthened the immune

system of the Eurasian population. This evolutionary advantage was of vital importance, and

is most notably highlighted by the ravaging consequences the absence of such a well

developed immune system had for the more epidemically susceptible indigenous populations

of the Americas in the sixteenth and seventeenth centuries. Additionally, the geographical

east-west axis facilitated the diffusion of technological advances on the Eurasian continent.

16

Adam Smith, An Inquiry into the Nature and Causes of the Wealth of Nations, 1776. 17

Daron Acemoglu,, S. Johnson, J.A. Robinson, “Reversal of Fortune: Geography and Institutions in the Making

of the Modern World Income Distribution”, Quarterly Journal of Economics 117, 2002: 1233.

11

Hence, Australia, Africa and the Americas, neither profited from such diversity of potentially

domesticable plants or animals, nor from a large east-west land axis. In the long-run,

therefore, Eurasia had a structural and fixed advantage for economic development over to the

rest of the world.18

Apart from such rigorous accounts, the geography school also knows somewhat more

refined variants of hypotheses along this line, also referred to as the “time-varying effects of

geography.”19

This group recognizes that certain geographical endowments may have been

conducive for economic growth may at a certain point in history, but not automatically as well

at another. Some scholars – most notably Jeffrey Sachs, John Gallup and Andrew Mellinger

(hereafter: SGM) – have gradually moved away from rigid geographical accounts towards

more ‘sophisticated’ versions.20

A well-known adaptation of such ‘sophisticated’ geography

reasoning is the ‘temperate drift hypothesis’. Whereas the tropical areas may have had a

comparative advantage in terms of agricultural output earlier on, it is argued, the subsequent

technological devices developed to raise agricultural production – such as the plough, rotation

systems and domesticated animals – were more beneficial at a later point in time to nations

located in the temperate zone. Additionally, scholars such as Kenneth Pomeranz – who argued

that ‘the West’ had economically diverged from China by escaping from a Malthusian “proto-

industrial cul-de-sac” through easily accessible coal deposits and greater access to caloric-rich

products in the New World – could also be considered adherents of time-varying geographical

reasoning.21

Despite the fact that many of its arguments appear plausible at first sight, there are

some problems with the geography model. With regards to the ‘time-invariant’ explanations,

these seem to suggest that the economic development of nations is inescapably determined by

its geographical location. Bluntly stated: once situated in an unfavourable area, chances for

economic progress are limited to non-existent. ‘You can’t fight nature’, so they seem to argue.

18

Jared Diamond, Guns, Germs and Steel: the Fates of Human Societies, (New York: Norton and Company Inc.,

1997). 19

AJR, “Reversal of Fortune: Geography and Institutions in the Making of the Modern World Income

Distribution.” Quarterly Journal of Economics 117, (2002): 1233. 20

See for example: John Luke Gallup, Agricultural productivity and geography. (Cambridge, MA: Harvard

Institute for International Development, 1998); Jeffrey Sachs, “Natural resource abundance and economic

growth”, HIID discussion paper 517a, (Cambridge, MA: Harvard Institute for International Development, 1995);

David Bloom and Jeffrey Sachs, “Geography, Demography, and Economic Growth in Africa.” (Cambridge, MA:

Center for International Development, 1998); and “Tropical Underdevelopment,” NBER Working Paper No.

8119, 2001. Or, for combined efforts: SGM, “Climate, Water Navigability, and Economic Development”, CID

Working Paper No. 24 , (Cambridge, MA: Harvard Institute for International Development, 1999).

“Geography and Economic Development”, International Regional Science Review, 22 (1999): 179-232. 21

Pomeranz, Kenneth. The Great Divergence: China, Europe and the Making of the Modern World Economy,

(New Jersey: Princeton University Press, 2000), 207.

12

That such reasoning is too rigid is exemplified by the number of nations that have developed

remarkably well, despite their unfortunate geographical location. A good illustration of a

nation that has been able to realize steady economic growth, in spite of difficult conditions, is

Botswana. This nation’s geographical situation as a landlocked country in the tropics, having

a low population density and barely any cultivable soil, would categorize as a structurally

disadvantaged nation according to economists such as SGM. However, in particular when

compared to the majority of its Sub-Saharan African counterparts – including those in more

‘favourable’ geographical environments – Botswana’s economic performance can duly be

called impressive. Even though some might reduce Botswana’s development achievements

exclusively to its diamond bequest, the fact that for many African nations natural-resource

abundance has proven to be a curse rather than a blessing, seems to suggest that not

geographically fortunate mineral endowments are the key to economic success, but rather the

management of its proceeds.22

As pointed out by Joseph Stiglitz, such resources have more

than often been “the object of conflict and the source of financial wherewithal that enables the

conflict to go on”23

than a straightforward ticket to broad-based prosperity. Evidently,

examples such as Botswana demonstrate that geographical determinism is strongly limited in

its overall theoretical capacity to account for long-term economic growth patterns.

Even the more sophisticated versions of the geography model are characterized by a

number of causal inaccuracies as well. As has been demonstrated by AJR, there has been a

clear ‘reversal of fortune’ among nations during the past five centuries. Looking at data on

urbanization levels and population density, AJR point out how nations that were

comparatively rich around 1500 have now descended into relatively poverty.24

Such a

prosperity U-turn cannot be explained by the temperate drift hypothesis, since the implications

of this theory hold that the reversal should have been set in motion with the arrival of

European agricultural technology in the colonies. However, the reversal only took place at a

much later stage – at the time of industrialization in the course of the late eighteenth and early

nineteenth centuries – and shows, thus, no significant correlation with the perceived

geographical variables. Moreover, other sophisticated geography arguments, that emphasize

the relationship between geographical endowments (such as coal deposits or easy coastal or

waterway access) and industrialization, still lack clear empirical evidence for such causality.

22

Daron Acemoglu, S. Johnson and J. Robinson. “An African Success Story: Botswana”. In: Dani Rodrik (ed.),

In Search of Prosperity: Analytic Narratives on Economic Growth, (Princeton and Oxford: Princeton University

Press, 2003), 83. 23

Joseph E. Stiglitz, Making Globalization Work, (New York: Norton and Company Inc, 2006) 135. 24

AJR, “Reversal of Fortune,” 1231.

13

Although the various studies conducted by the geography school have provided for some

meaningful insights on the effects of site and ecology on economic development patterns, they

remain inherently limited in establishing causality in a consistent manner.

2.3 Socio-Political Structures – Institutional Barriers

If barriers for economic development can neither consistently nor empirically be explained by

deficiencies in technological or geographical endowments, why, then, are economies, such as

the SSA ones, unable to reach their full potential? The inherent limitations in the explanatory

power of input-oriented arguments has increasingly shifted attention towards socio-political

conditions; or, in other words, towards the institutional domain in which the allocation and

exploitation of technology and resource endowments are determined. Being more micro-

oriented and theoretical in nature, this revival of interest in institutional economics was

pioneered by economic historians, most notably by Douglass C. North and Robert Thomas.25

Building on the theoretical foundations of, amongst others, Thorstein Veblen and Ronald

Coase, this ‘new’ school of institutions – also known as New Institutional Economics, or NIE

– emphasizes the impact of ‘secure property rights’ and ‘transaction costs’ on long-term

growth potential.26

Albeit diverse theoretical implementations of NIE exist – mainly evolving

around the extent to which neo-classical elements are incorporated – for the purpose of this

study, we will restrict ourselves here to the general outlook of adherents of this school.

Defined, in its broadest sense, by Nobel Laureate Douglass C. North, institutions are

considered the “humanly devised constraints that structure human interaction.” These consist

both of “formal constraints (e.g. rules, laws, constitutions)” and “informal constraints (e.g.

norms of behavior, conventions, self-imposed codes of conduct)”, and the mode in which

these constraints will be enforced. Consequently, institutions are the “rules of the game”,

which delineate the incentive structure of societies, and economies in particular.27

In particular

the clear specification and enforcement of private property rights, which characterized the

‘rise of the West’, figures in this argument as a central prerequisite for attaining long-term

economic growth. Culminating in the last decade, both economic historians and development

25

Douglass C. North and Robert P. Thomas, “An Economic Theory of the Growth of the Western World”, The

Economic History Review 23 (1970): 1-17; and The Rise of the Western World: A New Economic History,

(Cambridge: Cambridge University Press: 1973) 26

For theoretical foundations see: Thorstein Veblen, “Why is economics not an evolutionary science?”

Cambridge Journal of Economics 22 (1998). Originally published in The Quarterly Journal of Economics

(1898), 373-397; Ronald Coase, “The Nature of the Firm”, Economica 4, (1937): 386-405; and “The Problem of

Social Cost”, Journal of Law and Economics 3 (1960): 1-44. 27

North, Douglass C., “Economic Performance through Time”, The American Economic Review, 84 (1994): 360.

14

economists have increasingly taken an interest in the manner in which institutional

frameworks shape economic performance. What institutions are growth-conducive? How

exactly do they affect economic development? Why did they emerge in certain regions, and

not in others? Are ‘bad’ institutions persistent? In the literature on SSA, the main question

seems to be whether the current growth malaise is the result of poor institutions, especially

those believed to have been exported to the continent by the colonizing powers.

Three of the most prominent contemporary scholars of the ‘institutions school of

thought’ are indisputably AJR. In their numerous – and much cited – contributions, wedding

development-economics-style econometric techniques to more economic historic natured

inquiries, they seek to establish a causal relationship between secure “institutions of property

rights”28

on the one hand, and long-term GDP performance on the other. In many respects,

they aim to push the Northian notion that ‘institutions matter’, to the next level. Firstly, by

testing this not easily quantifiable concept empirically, and, secondly, by providing for an

account of the even more profound question why growth-promoting institutions were not

exported universally by the colonial empires.

A closer look at one of their seminal works, “The Colonial Origins of Comparative

Development”, will highlight some of the problems that characterize such quantitative

attempts of establishing institutionally deterministic claims. In “The Colonial Origins”, AJR

go about this by correlating settler mortality levels among colonizing subjects in a specific

region, with economic performance of that particular region in the long run. Their claim is

straightforward: if Europeans faced high mortality rates in their colonial territories, they

would refrain from broad-based settlement and hence, they reason, be more likely to set up

extractive, aka ‘bad’, institutions there. On the contrary, AJR maintain, areas with lower

mortality rates would have been deemed more suitable for settlement, and hence came to

benefit from the “set up of institutions that enforced the rule of law.”29

Accordingly, colonies

of settlement, or the so-called “Neo-Europes,” became much more favourable for investment

than those fraught by extractive institutions, and, hence, were able to realize a more stable and

positive economic growth record over time. A significant assumption made by AJR, is that

“[t]he colonial state and institutions persisted even after independence.”30

The implication of

this deterministic assumption is that the disease prevalent areas in close proximity of the

28

Which are defined as “effective property rights for a large segment of the society, against state expropriation

and predation by private agents”, AJR, “An African Success Story,” 86. 29

Daron Acemoglu, S. Johnson and J. Robinson. "The Colonial Origins of Comparative Development: An

Empirical Investigation." American Economic Review 91, 2001: 1375. 30

Ibid., 1370.

15

equator became as good as institutionally doomed upon colonial arrival. Although this

analysis emphasizes the central role of institutional factors on development paths, it also

incorporates the impact of geographical aspects. In the end, the absence or presence of high

settler mortality rates reflects different geographical locations – or mainly their corresponding

disease regimes – and are in this sense an interrelated determinant of the emergence of a

growth-promoting institutional framework.

The validity of AJR’s claim, as with all attempts to establish causal relationships

between institutional arrangements and long-run economic performance, stands or falls above

all with the extent to which they can establish a clear correlation between settler mortality

rates and long-term GDP per capita performance. As such, much depends on the validity of

the statistical evidence on which AJR’s argument is based. Interesting, therefore, is an

evaluation of the settler mortality data by economist David Albouy. His assessment of AJR’s

empirical basis reveals that if certain ‘mistakes’ would be controlled for, then the supposed

causal relationship between the dependent and independent variable “loses robustness.”31

More specifically, Albouy criticizes AJR for having attributed inappropriate settler mortality

numbers to more than half of their sample size, basing themselves on unsuitable rates from

neighbouring countries. Moreover, Albouy continues, their regression analysis is build upon

inconsistent measurements of mortality rates – some being derived from missionary bishops,

others from soldiers in war situations – therefore making the dataset highly inconsistent.

Another example of such meagre empirical foundations is illustrated by their study on

the ‘reversal of fortune’. Here, AJR postulate that there is a clear correlation between

countries that were prosperous around 1500 and those that are currently poor. The causal

factor, again, that can account for this development is the type of institutional framework that

had been imposed on the colonized countries by the imperial powers. It was European

intervention, they maintain, that overturned the attained growth records through “institutional

reversal”.32

Once more, AJR imply that current economically unfortunate countries, such as

the African ones, can thank their previous colonizer for entrenching them with a persistently

hampering institutional structure. In some respects, this ‘reversal of fortune’ hypothesis –

especially to historians – is reminiscent of the Dependency theory that had gained popularity

in the 1970s, which stressed the manner in which Europe had ‘underdeveloped Africa’, albeit

31

David Albouy, “The Colonial Origins of Comparative Development: An Investigation of the Settler Mortality

Data”, University of Michigan, revised version, February 1, 2008: 1. 32

‘Institutional reversal’ refers, again, to the extractive nature of the institutional framework that was imposed on

regions that were ‘better off’ (where more could be extracted in the first place), as opposed to the institutions that

were created in poorer, scarcely population areas. AJR, “Reversal of Fortune,” 1279.

16

that being a more “rational-choice, optimistically quantified version.”33

AJR’s supporting

regression analysis indeed displays a striking statistical correlation between the two variables.

However, the fact that the data sample is solely based on former colonies weakens the validity

of their wider claim. Including the entire world into this regression analysis would most likely

provide for a different outcome. Unmistakably, there are a great number of non-colonial

countries that were relatively prosperous half a millennium ago and that are still so nowadays,

most notably in this respect the prime movers. Such examples clearly demonstrate that

economic development can be persistent. Another methodological weakness, as pointed out

by Gareth Austin, is that the data observations used by AJR for the level of GDP in 1500 – for

which obviously no figures are available – rely solely on highly disputable accounts of

population size. Moreover, Austin continues, these backward projected data points, or

“guesstimates”, are further destabilized by the Atlantic slave trade and the introduction of new

food crops from the Americas, which shifted the production possibility frontier outwards. 34

Albeit both being appealing assertions, AJR-like hypotheses, emphasizing the long-

term impeding consequences of poorly specified property right regimes and, as such,

institutional path-dependency, suffer from even deeper problems than mere empirical

questionability. First of all –very similar to the methodological shortcomings of the rigid

statistical technology and geography approaches – the Achilles heel for scholars adhering to

the ‘institutions school’, aiming to establish institutional deterministic patterns through such

techniques, is to effectively establish causality. Do good institutions really cause economic

growth, or does economic development produce ‘better’ institutions? Again, the possibility of

reverse causality remains a fundamental problem, and maybe even more so for regression

analysis of institutions, as these do not lend themselves that easily to quantification. The

quality of such data, as we have seen with the settler mortality data and pre-colonial

population estimates, poses severe limitations for what can be done with it.

Moreover, at a more abstract level, the problem with this type of literature is that, in

the end, it does not demonstrate how various institutions affect development patterns, or how

the evolution of an institutional framework accompanies growth. From a more theoretical

perspective, therefore, these approaches tell us little about the dynamic interaction between

the economy, socio-political structures, and the “rules of the game”. One good example of

33

Austin, “The ‘Reversal of Fortune’ Thesis and the Compression of History”, 1002. See also: Walter Rodney,

How Europe Underdeveloped Africa, (London: Bogle-L’Ouverture, 1972); and Immanuel Wallerstein, The

Modern World System, Vol I-III, (New York and San Diego: Academic Press, 1974, 1980, 1989). 34

Austin, “The ‘Reversal of Fortune’ Thesis and the Compression of History”, 998. For the population figures

Austin refers to, see: C. McEvedy and R. Jones, Atlas of World Population History, (Harmondsworth, UK:

Penguin Books, 1978).

17

such a limitation can be illustrated by the growing emphasis of this strand of literature on the

importance of ‘well-specified’ private property rights. As has recently been demonstrated by

Steven Chueng, the absence of such full-fledged property rights has clearly not been a

significant barrier in the Chinese economic development path of the last two decades. Rather,

as Chueng demonstrates, it was in the complex politico-institutional context of a specific

Chinese administrative district, the xian, that competition was able to rise and flourish.35

Examples such as these suggest that insights about the real mechanisms that are at work in the

social, political and economic domains; about the manner in which they interact; and, more

particularly, about how they have been shaped by both formal and informal constraints,

remain intrinsically difficult to isolate through econometric analysis.

Both the input-oriented geography/technology schools and the institutions school have

attempted to account for the divergent global growth patterns. Both have made important

contributions to our understanding of international income disparities. Both, however, in

particular in their pursuit of deterministic explanatory arguments, have severe limitations in

clarifying why the majority of the Sub-Saharan African nations have failed to secure a stable

pattern of national income growth. The most remarkable trend in the debate – in particular

among scholars that emphasize the role of European-imposed extractive institutions – is that

there seems to be a growing consensus that the African economy performed poorly under

colonial rule. The astonishing aspect of this premise is that in reality, we still know very little

about the actual performance of the African colonial economy, and that, as such, these types

of hypothesized causal relationships may very likely be oversimplifications of the actual

patterns of causation at work. With respect to the hypotheses postulated about the African

growth tragedy and its alleged colonial roots, it seems, therefore, that any evocative validation

should, first of all, start with an in-depth examination of the colonial economy.

Only recently have such initial steps been taken. As already briefly alluded to in

previous sections, the construction of a unique pre-WWII GDP time-series for SSA has

opened up a window through which we can now capture some first glimpses of the continent’s

actual colonial economic performance. Moreover, even more recently, evidence has been

presented, by amongst others, Gareth Austin, Jörg Baten and Alexander Moradi, that overall

living standards for the average African subject improved rather than deteriorated under

35

Steven Chueng, “The Economic System of China”, May, 2008, fourth draft. Forthcoming.

18

colonial rule.36

Additionally, a cross-colonial comparison of fiscal policies in the British

Empire, as carried out by Ewout Frankema, suggests that taxation pressure in the African

colonies was relatively mild, and that, hence, the term ‘extractive colonial institution’ is in

need of further scholarly decomposition.37

In the section below, these new empirical insights

into the African colonial economy will be presented. The propositions of these studies – that

Africa’s economy performed much better under colonial rule than was previously assumed,

that living standards appear to have risen in this era, and that there is little quantitative

evidence for any claims of extractive fiscal institutions – will undoubtedly have some broader

implications for the academic debate on growth determinants and impediments.

2.4 New Empirical Evidence – Implications for the Current Academic Debate

As has been highlighted in the introduction, the Maddison dataset suggests that the African

economy performed relatively well between 1950 and 1973. The ensuing growth collapse has,

following AJR, frequently been interpreted as the persistence of the continent’s poor

economic performance under colonial rule; the period in which it had become imbedded with

‘hampering’ institutions. Jan Pieter Smits, though, points out correctly that this interpretation,

which still lacks solid empirical evidence, has led to easy dismissals of the African economic

growth achievements during the period 1950-1973; these accomplishments merely being signs

of ‘catching-up growth’. However, in order to understand the post-WWII growth upheaval

and its subsequent collapse, Smits points out that it is important to look at the long-term

economic pattern of Africa, one that also includes the pre-WWII period. In his paper

“Economic Growth and Structural Change in Sub Saharan Africa during the Twentieth

Century: New Empirical Evidence and Outlook to 2030,” Smits tries to elucidate parts of this

long-run growth record by presenting a new dataset for the African economy1910-1970.

2.4.1 Compilation and Validity of the Colonial Dataset

Evidently, the compilation of such a dataset is a difficult undertaking, and this is undoubtedly

one of the main reasons that such endeavours have not been carried out at an earlier point in

36

Gareth Austin, Jörg Baten, and Alexander Moradi, “Exploring the evolution of living standards in Ghana,

1880-2000: An anthropometric approach”, presented at the Annual Conference of the Economic History Society,

University of Exeter, 2007; and Alexander Moradi, “Towards an Objective Account of Nutrition and Health in

Colonial Kenya: A Study of Stature in African Army Recruits and Civilians, 1880-1980”, Centre for the Study of

African Economies, Working Paper No. 284, 2008. 37

Ewout Frankema, “Raising Revenue in the British Empire, 1870-1940: How ‘extractive’ were colonial taxes?”,

presented at the WEHC, University of Utrecht, 2009.

19

time – not even by Maddison himself.38

Therefore, the significance of these new GDP figures

stands or falls with the quality and reliability of the data observations used to construct them.

The assumption that has prevailed for many decades is that official statistical records of the

colonial powers can neither be adequate nor trustworthy, and should, hence, not be relied

upon for empirical analysis. The premise here is that these records would reflect either the

incompetent documentation skills of local administrators or, perhaps even worse, manipulated

numbers that mirror politically desired outcomes rather than actual economic performance.

Smits maintains, however, discarding such widely held views, that practically all colonial

administrations ensured that information on relevant aspects of the economy was

systematically gathered and processed, as accurate numbers allowed them to maximize

taxation revenues. Having visited various archives for this project myself, and having

scrutinized a great amount of the colonial sources Smits utilized, I believe that it is necessary

to add two things here to the discussion about the validity of these statistical records.39

Firstly, there is great variety in the quality of the figures documented in the annual

statistical reports from the colonial territories, also known as the ‘Blue Books’. It has to be

taken into account that most of the colonial administrations in British Africa were unequipped

to conduct certain types of data collection. The most notable examples of such ‘guesstimates’

are the gross underestimations that characterize the decade-by-decade population censuses,

which frequently failed to incorporate all of the groups or tribes living in the hinterlands.40

These regions were both hard to reach and lacked the sophisticated administrative system

necessary to conduct accurate census taking. As pointed out by Frankema, “[c]ensus-

committees were chronically understaffed and native authorities were not always prepared to

cooperate voluntarily, if they disposed of the skills to produce an accurate head count in the

first place.”41

Apart from the standardized lay-out of the Blue Books, London provided little

to no guidelines on how to collect the requested statistical records. Consequently, information

on wage and price rates, for example, is inherently biased towards the urban centres.

38

Note that Maddison’s extended database does not include any GDP estimates for Africa before 1950.

Additionally, it should be mentioned that some early estimates have been made for national income growth in

Africa under colonial rule, but such attempts have always been limited to a small regions, and for relatively short

time-spans. See for example estimates of the GDP levels in Gold Coast (current Ghana) for the period 1891-

1911: R. Szereszewski, Structural Changes in the Economy of Ghana, 1891-1911, (London: Weidenfeld &

Nicolson: 1965). 39

It must be mentioned here, that this refers predominantly to the British Colonial Blue Books. 40

Overall the error boundary is assumed to be somewhere in between 0 and 20%. See: R.R. Kuczynski,

Demographic Survey of the British Colonial Empire, Vol. I, West Africa, (London: Oxford University Press,

1948); and Demographic Survey of the British Colonial Empire, Vol. II, East Africa, (London: Oxford University

Press, 1949). 41

Frankema, “Raising Revenue in the British Empire”, 15.

20

Secondly, something more optimistic should be said about the alleged inadequacy of

the local administrators. Creating a time-series dataset reveals much about the consistency of

such records, and nothing points towards systematic forms of ineptness on the part of local

colonial officials in gathering and processing the figures. The pervasive use in the Blue Books

of terms as, ‘no information available (nil)’ or, ‘no reliable figures can be presented for

Colony X’, tells us there was at least no systematic reliance upon ‘guesstimates’ by the

administrators, and hence, indicates transparency rather than ambiguity. This is not to say that

no occasional mistakes have been made, and that for some years, especially in the pre-WWI

period, statistical estimates relied to a certain extent upon the previous year. And surely, these

data observations reflect the limitations discussed in the previous paragraph under which the

staff in the colonies had to work. However, with respect to the problem of occasional annual

shortcomings in the statistical figures, one can argue that this is of minor significance for a

research focus on the long-run trend. The second problem does not necessarily entail that the

colonial statistics are useless for all purposes. It does emphasize, though, that one needs to

treat these figures with great care. With respect to the dataset as presented by Smits, therefore,

the following can be said. At this point in time the evidence for his hypothesis remains thin

and preliminary, and still has to withstand the test of peer review. However, already before

publication, it can be considered an agenda-setting study. It not only opens up the discussion

about the performance of the African colonial economy, but also encourages a greater effort

of academic peers to see what can be distilled from the extant British statistics.

2.4.2 The ‘Missing’ Numbers – GDP per Capita Performance in Colonial Africa

The foremost significant constituent presented in Smits’ new dataset, are the estimates of

GDP per capita levels for the period 1910-1950, a period for which no figures had previously

been available.42

In figure 2.1 below, these per capita income estimates are depicted. The

graph reveals that, contrary to prevalent premises about Africa’s malperformance, its

economy functioned remarkably well during the colonial period.43

With the exception of the

years surrounding WWI and WWII, the per capita growth rates can be considered relatively

high. After WWI’s associated negative growth years, the African economy grew at an annual

rate of 3.8% between 1922 and 1938. Smits points out that the high growth rates during the

42

The per capita GDP levels have been estimated on the basis of a variety of agricultural and industrial products

and output data on transport, the public sector and trade. 43

It must be mentioned that the discussion of Smits’ GDP series in this section is limited to its contributions, and

that some problems of the dataset will be addressed in Chapter 3. In order to avoid repetition I have chosen to

restrict myself here to the overall findings and their implications for the wider growth debate.

21

1930s are “rather surprising”, given the fact that by comparison most regions in the world

suffered strongly from the “globalization backlash of the 1930s.” Adding this upward trend to

the two and a half decades of the post-WWII growth44

, Smits concludes that, from a long-run

perspective, it is not the strong growth pattern of earlier periods that should be considered as

the “exceptional phenomenon”45

, but rather the more recent growth collapse. Moreover,

opposing AJR-style interpretations, he suggests that the strong growth record of the Sub

Saharan economies in the first two decades after independence should be considered as “a

continuation of the growth pattern that had been realized in the colonial era.”46

Figure 2.1: Levels of GDP per capita in Sub-Saharan Africa, (1820) 1910-2000

(at constant prices in American Dollars of 1990)

Source: Smits, "Economic Growth and Structural Change,” 5.

As mentioned before, in the early 1960s the economic prospects for Africa were

perceived to be more optimistic than for East Asia. In graph 2.2, depicting the long-term

economic growth patterns for both Africa and East Asia, such notions may in retrospect not

seem that far off. The GDP trends of the two regions unmistakably illustrate that before WWI,

per capita income levels in Africa were above those in East Asia. The onset of WWI, though,

44

In which the African economy grew at an annual rate of 2%. 45

Smits, “Economic Growth and Structural Change,” 5. 46

Ibid., 7. To support his argument, Smits presents a more detailed, segment-based composition of the Africa’s

national income performance during the twentieth century, reproduced in table 1, ‘Average growth rate of

African GDP (in %)’, p. 7. These findings reveal a significant pattern. Not only did the African economy do

fairly well until the 1970s, but also the foundations of national output levels were extraordinarily well balanced

over all sectors. Moreover, these figures emphasize again that it was not until after the 1970s that the economy

started to perform poorly and that growth in industry and agriculture became heavily disrupted.

22

seems to have had greater negative consequences for the African economy than for the East

Asian. Nonetheless, the rapid economic recovery of the African continent during the inter-war

years ensured that income levels overtook those of East Asia once more. It was not until after

the mid-1950s that the East Asian economic trend clearly started to diverge from its African

counterpart. Again, Smits points out, such a comparative perspective seems to support the

image of a resilient and dynamic African economy rather than that of a rigid and stagnant one.

Consequently, he maintains, it seems that “from a long-run perspective slow growth is not a

fundamental, structural characteristic.”47

Figure 2.2: Levels of GDP per capita in Sub-Saharan Africa and East Asia, 1910-2000

(in American Dollars of 1990, logarithmic scale)

Source: Smits, "Economic Growth and Structural Change,” 6.

2.4.3 Income Growth and Distribution – A Revision of Colonialism’s Extractive Nature?

From these new GDP figures it clearly follows that the African economy performed much

better during the colonial period than had previously been assumed. Consequently, these new

estimates have some significant implications for hypotheses that attribute the economic

collapse of the 1970s-present to structural, deterministic factors, such as geographical

bottlenecks or unproductive and importunate institutions. Nonetheless, building upon these

new insights, we need to examine as well to what extent the colonial economic growth

47

Smits, “Economic Growth and Structural Change,” 6.

23

achievements where beneficial to society as a whole, and not exclusively to the alleged

‘extractive’ colonizers. The growing body of literature dealing with this question is more

diverse than Smits’s aggregate account on its own, and holds great promise for a clearer

delineation of the ‘extractive’ features of colonial political economies. Based on estimates of

daily caloric intake, Smits makes a first attempt in the same paper to gain some insights into

the development of living standards for the ‘average’ African subject between 1910 and 1970,

as is depicted in graph 2.3 below.48

It appears as if the overall level of food consumption

before the outburst of WWI was remarkably high. Moreover, the estimates highlight the

destructive impact of WWI on the African economy, in particular on its colonial subjects.

During the early 1920s, it seems that the critical consumption level – less than 1600 Kcal per

day – was closely approximated.49

However, with the recovery of the economy in the late

1920s and 1930s, living standards, expressed in terms of caloric consumption, seem to have

improved again for the African population.

Figure 2.3: Average daily caloric intake in Sub Saharan Africa, 1910-1970 (in Kcal per caput per day)

Source: Smits, "Economic Growth and Structural Change,” 9.

Analogous to the GDP time-series, one of the main problems with the aggregate

picture this graph presents for caloric intake levels, is that it does not tell us much about

national or even regional differences within SSA. Can it be assumed that this average trend is

48

This estimation rests upon a comparison between agricultural output and the import-export ratio of food

products. 49

Taking into account that 1600 Kcal is only an average level, the absolute minimum must have been even more

disparaging.

24

a good approximation for the experience of each of the SSA colonies, or do we find great

intra-African disparities when we further decompose this pattern? Moreover, the level of

caloric intake may give us an idea about the overall quantity of native food consumption, but

it fails to tell us anything about its quality. Do the periods with high caloric intake levels also

reflect more well-balanced diets, with the corresponding implications for overall health

conditions? Evidently, there is a need for further differentiation here too.

An attention-grabbing case-study on the development of living standards in British

Gold Coast has recently been presented by Austin, Baten and Moradi (hereafter: ABM), and

provides further insights into these types of questions. Taking an ‘anthropometric’ approach,

and thereby aiming to overcome the constraint of a “limited amount of good data” and the

problem of a “need for a consistent measure of well-being”50

, ABM examine the development

of human stature in pre-colonial and colonial Gold Coast, and after its independence. They

reason, analogous to Fogel’s account on the positive correlation between economic growth,

human well-being, and physiological traits, that adult height, as a product of a high-quality

nutritious diet in childhood – reflecting a greater degree of human well-being –, is a good

indicator of living standards. Relying upon a careful selection of army recruitment records,

they demonstrate that living standards improved both rapidly and significantly under early-

and mid-twentieth century colonial rule. Especially, when contrasting the upward trend in

height values with the stagnation and decline of the post 1970s era, they argue that, in terms of

living standards, the colonial period for the Gold Coast cannot straightforwardly be

considered ‘bad’. Moreover, they conclude, that there is little basis in the case of the Gold

Coast to assume that colonial institutions, which, if we follow the literature, should have been

highly extractive in this marginally settled tropical area, would have “‘prevented’

improvements in living standards.” In contrast, in the case of the Gold Coast, ABM maintain,

colonial institutions appear to have even been “pro-growth.”51

Moradi, building upon this

combined endeavour, has conducted a similar study on the evolvement of mean heights in

colonial Kenya. His findings, that the average height increased from the 1920s onwards under

colonial rule, suggests that, here too, a similar conclusion is in order.52

In another recent attempt to gain deeper insights into the ‘extractive’ nature of colonial

institutions, Frankema assesses the comparative taxation burden in 34 settler, and non-settler

societies within the British Empire. Separating the share of fiscal revenue from the overall

50

ABM, “Exploring the evolution of living standards in Ghana”, 4. 51

Ibid., 20. 52

Moradi, “Towards an Objective Account of Nutrition and Health in Colonial Kenya”.

25

gross public revenue (hereafter: GPR), divided by the total recorded population size53

, he

calculates and compares, how many days an unskilled urban labourer had to work across the

empire to meet his annual taxation obligation. This cross-colonial examination of per capita

tax incidence yields little evidence that the low-settled peripheral territories suffered from a

more excessive taxation burden than their ‘Neo-European’ counterparts. Even more surprising

is his preliminary finding – one that deserves further scrutiny – that there appears to be a

statistically significant relationship between the higher end of the taxation incidence range on

the one hand, and long-run economic growth on the other. With respect to the debate on the

Sub-Saharan growth tragedy, this study reveals as well that the hypothesis of colonial

extractive institutions falls short in its ambition to consistently account for long-term dismal

growth performance. Moreover, if there indeed exists a causal relationship between stronger

taxation incidence under colonial rule and post-independence national income growth, this

would point out the necessity to further nuance the notion of what constitutes an ‘extractive

institution’ as such.

2.5 The African Colonial Economy – A New Research Agenda

All of these findings on the African colonial economy and the development of living

standards in this period should capture our interest. Counter to dominant assumptions about

the colonial and post-colonial African economies, these new figures reveal some interesting

patterns with respect to national income growth, living standards and the extent that the

colonial tax systems can be considered ‘extractive’. With respect to GDP performance, it now

appears that SSA had been performing comparatively well during the first seven decades of

the twentieth century. Apart from the periods surrounding the two World Wars, which

highlighted the vulnerability of the African economy vis-à-vis external political shocks, SSA

on the whole seems to have enjoyed strong per capita growth rates under colonial rule.

Evidently, such findings of a dynamically growing colonial economy undermine deterministic

assertions that the African continent, through its geographical or institutional inheritance, is

destined to remain poor. Additionally, taking the analysis one step further, ABM present

evidence that, in the cases of the Gold Coast and Kenya, living standards for the native

colonized population even improved over time. These findings are complemented by the

53

Evidently, the estimated population figures of the colonial empire are far from adequate. However, as will be

elaborated upon more thoroughly in Chapter 3, there are ways in which these figures can be allocated to suit the

purpose of constructing a per capita taxation incidence.

26

aggregate account on average daily caloric intake of the native population, which suggests

that the positive effects of economic expansion were not solely confined to the colonizer.

Finally, the comparative taxation incidence as presented by Frankema, and especially the

moderate levels that were found for most of the British African colonies, points towards a

need to further differentiate the, so widely perceived, colonial ‘extractive’ institutions.

These new findings on the African colonial performance, both in terms of growth

records and the development of living standards, thus suggest that there are profound

implications for the extent that we can perceive colonial rule as intrinsically extractive in

nature, and, on an even broader plane, for the debate on SSA’s dismal growth as a whole.

However, the picture that has been painted remains far from complete. Smits’ account on

national income growth and caloric intake is, ironically, limited by its main strength. By

sketching a trend for such a large region it truly highlights the ‘bigger’ picture. However, as a

consequence of not presenting any nationally decomposed figures, it leaves room for

speculation about gross regional differences, and hence for doubts about the overall

applicability of this aggregate economic growth record to individual units of analysis. ABM’s

account, in contrast, seems to suffer from the complete opposite constraints in terms of

explanatory power. The exclusive focus on living standards in the Gold Coast and Kenya have

all the benefits of good case-studies: they are holistic in nature and, therefore, allow for a

more sophisticated treatment of particularities and causal complexity. However, with these

studies addressing this question for only two cases, little applicability can be derived for the

overall development of human well-being under colonial rule. Moreover, the small amount of

available cases, also complicate efforts to embark on intra-African and international

comparisons on the development of living standards in this period. Frankema’s study seems to

be the most encompassing in that respect; it addresses the per capita taxation burden in a large

sample of individual countries, and is able to distil some general patterns and variations

through an economic historical comparison. Nonetheless, the reliance upon nominal wage

rates still allows us to ask the question of how much of a burden the fiscal obligations were

for the native population if one would take the overall price level into account, and hence

deflate these nominal wage rates. Moreover, the reliance upon benchmark years – albeit far

from arbitrary – begs the question of how well these years fit into the year-to-year pattern, as

would be revealed by a time-series.

It is on these components that this study sets out to build. In order to gain some deeper

insights in the development of living standards for a large set of British African colonies, a

full time-series for real wages has been constructed, both for unskilled industrial and

27

agricultural labour. Through this, it aims to provide for a broad-based picture of the

development of living standards in terms of purchasing power. As will be further elaborated

upon in the next chapter, real wages are widely considered as a solid tool to examine trends in

living standards.54

Moreover, taking a relatively homogenous set of units of analysis and

methodological tools, it will allow for inter-temporal and spatial comparisons, through which

general similarities and variations can be distilled. Additionally, the wage and price

observations allow us to estimate how close these rates placed the native population to a bare

subsistence income, and how this trend developed over time. Finally, following from this set

of real wages, a first attempt can be made to place per capita taxation incidence in the context

of overall purchasing power.

54

The literature on real wages is abundant. See for example: C.H. Feinstein, “Pessimism Perpetuated: real wages

and the standard of living in Britain during and after the Industrial Revolution”, Journal of Economic History,

58, 1998: 625-58; L. Noordegraaf and J.L. van Zanden, “Early Modern Economic Growth and the Standard of

Living: did labour benefit from Holland's Golden Age?” In: C.A. Davids and J. Lucassen (eds.) A miracle

mirrored. The Dutch Republic in European perspective, (Cambridge: Cambridge University Press, 1995): 410-

38; J. de Vries and A. van der Woude, The First Modern Economy, Cambridge: Cambridge University Press,

1997; and J.L. van Zanden, “Wages and the Standard of Living in Europe, 1500-1800”, European Review of

Economic History, 3, 1999: 175-198.

28

3. THE DEVELOPMENT OF REAL WAGES - RESULTS

3.1 Introduction

The preliminary empirical evidence on the performance of the Sub-Saharan colonial economy

is at the core of this study. I aim to shed some further light on this topic by presenting a

dataset on the development of living standards for the average native population in this period.

Examining the historical evolvement of living standards, however, is far from a

straightforward undertaking. First of all, how does one measure ‘well-being’, or make

assertions about people being ‘better’ or ‘worse’ off? A broader, more philosophical,

approach towards such profound questions would include ‘intangible’ elements as well, such

as cultural, religious and social group notions. As has been emphasized by the immense array

of post-colonial literature, the negative effects of colonial rule on matters of identity, pride,

sense of autonomy and historical continuity, have undoubtedly had a detrimental impact on

more encompassing interpretations of ‘living standards’ or ‘quality of life’.55

Evidently,

making assertions about the development of living standards in colonial Africa, let alone

interpreting them in normative terms of ‘progress’, is a highly controversial undertaking. In

order to avoid any ambiguity in this respect on what this study sets out to do, I will start out

by making the assumptions and focal areas explicit here. This study sets out to distil the

development of living standards in terms of more narrowly, quantifiable, economic indicators;

thereby not focusing on the more ‘qualitative’ – or psychological – effects of colonial

domination.

A particularly popular measure for economic historians indicating improved standards

of living, are data figures on height.56

Such physiological statistical figures, however, are alas

still only scarcely available for the epoch under investigation, and require access to archival

documents less easily available than those for price and wage observations. Nonetheless, this

approach remains a worthwhile undertaking for further research on living standards in

colonial Africa. For this initial broad-based empirical analysis, though, the question of the

55

See for a broader critique of colonialism the classic works of Edward W. Said, Orientalism, (New York:

Random House, 1978); and Frantz Fanon, Les Damnés de la Terre, (Paris: F. Maspero, 1961) and Peau Noire,

Masques Blancs, (Paris: Editions du Seuil, 1952); and Albert Memmi, Portrait du Colonisé, Précédé Par

Portrait du Colonisateur, (Corrêa: Editions Buchet/Chastel, 1957). Or for later works on Africa see: V. Y.

Mudimbe, The Invention of Africa: Gnosis, Philosophy, and the Order of Knowledge (African Systems of

Thought), (Bloomington: Indiana University Press, 1988); Ng!g" wa Thiongo, Weep Not, Child, (New York:

Collier Books, 1964). 56

It has widely been agreed upon that economic development goes hand in hand with increases in physical

height. See: J. Komlos, Nutrition and Economic Development in the Eighteenth-Century Habsburg Monarchy:

An Anthropometric History, (Princeton: Princeton University Press), 1989; and R. Martorell and J.-P. Habicht,

“Growth in Early Childhood in Developing Countries.” In: F. Falkner and J. M. Tanner, Human Growth: A

Comprehensive Treatise, Vol. 3. New York: Plenum, 1986, pp. 241-262.

29

native population’s economic well-being will be approached through other well-established

measurements; most notably through the reconstruction of a real wage time-series for British

Africa.

Research into real wage development has proven to be a rewarding undertaking for

economic historians. The early real wage literature, originating in the mid-nineteenth century,

was predominantly Eurocentric in outlook, and has, as was recently pointed out by Allen et.

al., made our understanding of European living standards from the early modern period

onwards both “broad and deep”.57

Nonetheless, more recently a new trend in this strand of

literature has become discernable. Especially in the last decade, the wage and price figures

that have become available reflect the heightened interest in a more comprehensive approach

towards real wages. Increasingly, a greater variety can be observed in terms of the spatio-

temporal scope of the research projects embarked upon.58

Even so, remaining the great

exception to this trend, real wage studies on Sub-Saharan Africa have up until today

consistently been avoided. Partially, this ‘neglect’ should be attributed to the fact that Africa,

unlike large parts of Asia or Latin America, has a comparatively limited tradition of

commodified labour. As pointed out by Austin, labour was tied various institutions, such as

slavery or communal labour, and was, hence, not predominantly allocated through the

‘invisible hand’ of the market.59

Additionally, the strong oral tradition of most African

societies limited the extent to which any available price or wage figures were gathered in a

systematic manner. Finally, as has already been addressed in the previous chapter, those data

figures that are available, mainly dating from the colonial period, are anything but

unproblematic and may have further discouraged research into the historical living standards

of SSA.

57

R.C. Allen, J.-P. Bassino, et al., "Wages, prices, and living standards in China, 1738-1925: in comparison with

Europe, Japan, and India," Economic History Review, 2009 (forthcoming). 58

See for example: R. C. Allen, “The Great Divergence in European Wages and Prices from the Middle Ages to

the First World War.” Explorations in Economic History 38, 2001: 411-447; The British Industrial Revolution in

Global Perspective, (Cambridge: Cambridge University Press, 2009); S. Broadberry and G. Bishnupriya, “The

Early Modern Great Divergence: Wages, Prices and Economic Development in Europe and Asia, 1500-1800,”

Economic History Review 59, 2006: 2-31; !. Pamuk and S. Ozmucur, “Real wages and standards of living in the

Ottoman empire, 1489–1914. 62: 292–321.” The Journal of Economic History 62, 2002: 292-321; Jeffrey G.

Williamson, “Real Wages and Relative Factor Prices in the Third World 1820-1940: The Mediterranean Basin.”

HIER Discussion Paper, Department of Economics, Harvard University, 1998 (forthcoming); “Real Wages and

Relative Factor Prices in the Third World 1820-1940: Asia.” HIER Discussion Paper, Department of Economics,

Harvard University, 1998 (forthcoming); “Real Wages and Relative Factor Prices in the Third World 1820-1940:

Latin America.” HIER Discussion Paper, Department of Economics, Harvard University, 1998 (forthcoming);

and J.L. van Zanden, “Rich and poor before the Industrial Revolution: a comparison between Java and the

Netherlands at the beginning of the nineteenth century.” Explorations in Economic History 40, 2003: 1-23. 59

Austin, “Land and labour Ghana”, 1.

30

In general, the advantages of studies on real wage development are numerous. Firstly,

data on nominal wage and price levels can for certain types of research questions be more

suitable than the general GDP estimates. Notwithstanding the tremendous contribution that

has been made by Angus Maddison, documenting in a systematic manner the development of

world real output levels, these wide-ranging figures also have their limitations. The sample of

historical GDP numbers, especially those for the period before WWII, are not evenly available

for the various world regions, thereby complicating inter-regional comparisons. Moreover, as

pointed out by Jeffrey Williamson, the gaps in these time-series are much larger than those for

real wage data. Consequently, the near annual presence of documented records for wage and

price levels allows for much greater precision in identifying epochal trends and socio-

economic turning points.60

Secondly, by analyzing real wage trajectories, one can uncover

significant information on matters of income distribution. Moreover, ordinary citizens

generate an income by earning wages, profits or economic rents, and not by earning the

statistically created figure of GDP per capita. Such averaging of all incomes, even in the form

of GDP per worker hour, fails to capture much of the valuable information on economic well-

being of ‘real people’ as can be accomplished through real wages. Finally, it has to be taken

into account that over time an increasing share of the population became employed as a wage

labourer, a trend that is particularly applicable to the period and region under consideration in

this study.

For colonial SSA, little data was available on average income levels until recently. The

new figures presented by Smits are, in this respect, a huge leap forward for our understanding

of the African colonial economy. However, these new numbers still remain very general in

their explanatory power, telling us that Africa on the whole did relatively well, as Smits does

not offer a breakdown of these figures. By looking at the trajectory of real wages for a large

sample of different colonial territories, the empirical results presented in this section aim to

shed some light on elements that these GDP series are not able to expound. Not only can

differences or similarities in purchasing power between specific African regions be distilled,

but their unit form as nationally-based figures allows us to compare them to those of other

nations in the world as well. Moreover, this time-series of real wages will reveal significant

trends in terms of income dispersion and the socio-economic development of the average

African subject.

60

Williamson, “The Mediterranean Basin”, 6-7.

31

This chapter will start out by presenting our empirical results for the development of

real wages in the form of a subsistence ratio. It will become evident that in five out of our

eight selected British African colonies (Gambia, Gold Coast, Sierra Leone, Nigeria and

Uganda), purchasing power of average native subjects improved significantly over the time-

span covered in this study. Two of the remaining cases showed little to no upward movement

in real wages (Kenya and Mauritius), and only for one case an actual decline was observed

(Nyasaland). Moreover, on the basis of our subsistence ratio, reflecting whether the wage of

an unskilled adult male was sufficient to sustain a family of five, we can say something about

the purchasing power of the native population in absolute terms. Only in Nyasaland the

subsistence ratio remained smaller than 1.0, indicating that the population could barely make

ends meet purely on the basis of the nominal wage rates. The subsistence ratio in all of the

other colonies, in contrast, was well above the bare minimum of 1.0.

Additionally, we will place these new results for British colonial Africa in an

international comparative perspective. For this purpose it is useful to first decompose the

overall real wage trend, allowing for a closer look at specific periodic episodes. Doing so will

corroborate Smits’ observation of the vulnerability of the African economy to “external,

political shocks”, such as both World Wars.61

When comparing these real wage trends for

Africa subsequently with those of Jeffrey Williamson for Asia and Latin America, it will

become evident that, in terms of purchasing power, most of the African colonial citizens

suffered less from the 1930s economic contraction than their international counterparts.

Moreover, the expression of our real wage time-series in terms of a subsistence ratio allows

for even further global comparisons. Plotting the average subsistence ratio in one graph with

Robert C. Allen’s ratio’s for pre-industrial Europe and Asia highlights the relative high real

wage level in British Africa.

Finally, taking the examination of the African’s socio-economic position one step

further, an analysis will be presented on the extent to which the colonial administrations were

able to extract tax revenue from this group. First, following the lines of Frankema, a time-

series will be presented for the development of taxation incidence for agricultural and

industrial unskilled labourers. Second, a further breakdown will be presented of the fiscal

pressure on the native population. Through our real wage series, and by separating indirect

from direct taxation revenues, we can make a first inference of what the taxation burden was

on the average unskilled labourer. This allows for some insights on how big of an impact

61

Smits, “Economic Growth and Structural Change”, 10.

32

native hut or poll taxes were on overall purchasing power. It will be demonstrated that, on the

whole, the overall taxation pressure on the native population can be considered relatively low.

3.2. Data and Methodology

3.2.1. Sample Selection

For this empirical study, a sample of eight former British colonies has been selected, covering

roughly fifteen percent of Africa’s geographical territory, and – more importantly – an even

larger share of its total population size.62

The selection of exclusively British colonies for this

empirical study on living standards in colonial Africa is based on two main arguments. Firstly,

with respect to the quality of data employed, the British data can be considered both the most

systematic and the most reliable compared to other colonial powers, such as France and

Belgium. As more elaborately discussed in chapter 2, we assume that the statistical figures

used for this study, as documented by the colonial administration, are sufficiently trustworthy

and competent when treated with the necessary caution. Secondly, in order to distil general

patterns or find regional differences with respect to the position of the native population, it is

essential that our units of analysis are comparable, and are, hence, part of the same ‘Empire’.

For further comparative reasons, the eight selected countries are located in diverse regions in

SSA. Four of them are situated in West Africa (Gambia, Gold Coast, Nigeria, and Sierra

Leone); another three in East Africa (Kenya, Nyasaland, and Uganda). Additionally, one case

stands out, having had a longer history of colonial rule and a different post-independence

growth trajectory (Mauritius). Such spatio-temporal particularities will serve as valuable tools

to examine developmental similarities and variations between the different colonial territories.

Before embarking on the analysis of the colonial period, it is useful to gain some

insights in the post-colonial performance of the selected countries, and examine whether they

reflect the previously discussed patterns of relative steady growth up until the mid-1970s, and

the ensuing decay in terms of economic development and living standards. In table 3.1 below,

a schematic overview is presented for these eight selected counties, for (1) their period of

being under British colonial rule, (2) their post-colonial economic performance record, and (3)

indicators of current standards of living. From the table clearly follows that for most of these

countries the negative growth records start in the course of the 1970s. Moreover, the

62

Initially, Bechuanaland, Northern Rhodesia and Somaliland were included in this study as well. However, as a

result of concerns about the quality of the wage data, I decided to exclude these colonies from this analysis.

33

schematic overview highlights the exceptional position of Mauritius in this sample, it being

the only country in the list with consistent positive growth rates and high scores on the Human

Development Index.63

Finally, apart from the question of how well the development trajectory

of each of these selected countries matches up or contrasts with the overall post-colonial

growth tragedy in SSA, one more aspect of our sample should be examined. Because this

study is examining the process of change over time, we need to ensure that our units of

analysis – the colonial or post-colonial states – do not change significantly for the decades

under consideration. Figures 3.1 and 3.2 in appendix II demonstrate that, in contrast to other

former African colonies, little to no changes occurred for these political entities in terms of

territorial properties.

Table 3.1: Schematic overview of the post-colonial growth rates and living standard

indicators for the selected countries in this study

1 2 3

British

colonial

rule

GDP/capita

growth rate

1960-1975

GDP/capita

growth rate

1975-1990

GDP/capita

growth rate

1990-2006

Human

Development

Index (2006)

Life expectancy

at birth (2006)

Gambia 1816-1965 2.84% -1.02% 0.68% 0.471

(low) –160th

59.0

(medium) – 140th

Gold Coast

(current Ghana) 1821-1957 -0.59% -0.93% 2.20%

0.533

(medium) – 142nd

59.4

(medium) – 139th

Kenya/EAP

1890-1963 1.86% 1.16% -0.31%

0.532

(medium) – 144th

52.7

(low) – 154th

Mauritius 1810-1968 2.68% 5.01% 3.81% 0.802

(high) – 74th

72.6

(high) – 72nd

Nigeria 1901-1960 3.56% -0.85% 1.51% 0.499

(low) – 154th

46.5

(low) – 168th

Nyasaland/CAP

(current Malawi) 1891-1964 3.05% -0.50% 1.22%

0.457

(low) – 162nd

47.0

(low) – 167th

Sierra Leone 1808-1961 1.96% -0.56% -2.80% 0.329

(low) – 179th

42.1

(low) – 176th

Uganda 1888-1962 0.59% -1.56% 2.57% 0.493

(low) – 156th

50.5

(low) – 160th

Benchmark 2.31% (UK)

2.73% (US)

2.42% (UK)

2.65% (US)

2.11% (UK)

1.82% (US)

0.968

Iceland (high)

– 1st

82.4

Japan (high)

– 1st

Sources: GDP growth rates – Maddison, “Statistics on World Population”; HDI and life expectancy –

Human Development Reports from United Nations Development Programme

63

Mauritius is widely recognized in the literature as an example of a ‘growth miracle’ in SSA. See for example:

James E. Meade, Economic and Social Structure of Mauritius, (London: Frank Cass and Company Ltd., 1961); J.

Sachs and A. Warner, “Sources of Slow Growth in African Economies,” Journal of African Economies, 6, 1997:

335-76; D. Rodrik, “Where Did All the Growth Go? External Shocks, Social Conflict, and Growth Collapses,”

Journal Of Economic Growth, 4, 1999: 385-412; and Arvind Subramanian and Devesh Roy, “Who Can Explain

The Mauritian Miracle: Meade, Romer, Sachs or Rodrik?”, IMF Working Paper, African Department, July 2001,

http://www.iie.com/publications/papers/subramanian0701imf.pdf, also published in: D. Rodrik, (ed.). In Search of

Prosperity. Analytic Narratives on Economic Growth. (Princeton: Princeton University Press, 2003).

34

3.2.2. Compilation of the Wage Data

The compilation of a real w\age time-series for British colonial Africa has been conducted so

that it presents as adequate a picture as possible. Evidently, this study on real wage

development aims to distil the minimum living standard for a large share of the native

occupational population. Focusing on purchasing power for the lower bound of British

Africa’s income distribution requires that we base ourselves on wage rates for unskilled

labour, as these figures correspond with minimum wage levels. Additionally, this category of

wage observations is accommodating in another respect. What is classified as unskilled labour

consisted mainly of physical tasks and was carried out by a large part of the native wage

workers. Unskilled labour tasks required neither a high degree of skills, expert knowledge nor

responsibilities. These aspects make unskilled wage observations exceedingly suitable for

comparative analysis, as we can assume that the tasks that were performed in all of the

colonies included in this study were relatively homogeneous. Moreover, the existence of

unskilled real wage data for non-African territories allows for even broader cross-national

comparisons, as will be conducted later in this chapter with Williamson’s real wage series and

Allen’s subsistence ratio.

Most real wage projects, ranging from medieval Europe to twentieth century Latin

America or Asia, are exclusively based on records for urban unskilled labour. The emphasis

of this study will mainly be on this category as well. The reasons for this preference are

straightforward. On the whole, working with urban wage and price figures safeguards

researchers from various problems that they would inevitably encounter if they would be

working with rural wages. The main apprehensions that hamper systematic research into

agricultural real wage development surround the non-quantifiable income sources of rural

wage-labourers. First of all, there is the problem of ‘payments in kind’. What additional non-

monetary resources, such as rations, clothes or lodgings, did land workers receive from their

employers next to their wage? Secondly, working outside the city had the advantage of little

to no expenses on housing, and offered ample opportunity to complement the nominal wage

income with yields from a vegetable garden or a small plot of land. Evidently, the size of such

financial benefits of living in the countryside is nearly impossible to estimate. Thirdly, with

rural prices barely available, one is forced to deflate the nominal agricultural wages rates with

urban prices. As prices are generally higher in the cities or large towns than on the

countryside, such rural real wage series are as good as certain underestimations. Finally, there

is the problem of seasonal employment. Did people in the countryside work for the stated

daily wage practically year-round? Or did they generate a large part of the annual income in

35

the harvest months when demand for rural wage labour was high? This question too

complicates working with agricultural wage figures.

Evidently, there is an endless array of reasons to exclude agricultural wages from a

study on real wage development. However, there is also a very good reason for not

immediately discarding such wage observations. In most of the non-industrialized world the

great majority of the labour force is employed in the agricultural sector. As such, the

construction of a real wage series for rural labourers would capture a much larger share of the

population than one for urban workers. In British Africa too, most of the population was

working in the countryside. In certain cases, the colonial administrators have even

documented clearly what share of the employed population was employed as ‘preadial’

labourers. For Kenya and Nigeria, for example, it has been recorded that, on average, between

50 and 60 percent of the wage-labouring population was occupied in agriculture, and the

majority of them as unskilled labourers. For Mauritius these numbers augment to 70 percent,

and in Nyasaland even to 85 percent. For Uganda, the documentation of nominal wage rates

was conducted exclusively for the native population, revealing almost 90 percent of the

occupational labour force in agriculture. This does not entail that these figures can be

translated into an assumption that, in the case of Uganda for example, 90 percent of the total

population was working as rural wage labourers. Unquestionably, the vast majority of the

native population generated income through subsistence farming. Nonetheless, basic

economic principles allow us to make the following supposition for those areas where rural

wage labour existed. If the income of agricultural labourers would have been far above that of

subsistence farmers, we can expect that many of the latter would have substituted their mode

of occupation to that of the former, and vice versa. As a result, we could still capture a large

share of the population in an indirect manner. Thus, in order not to throw out the child with

the bath water, I have incorporated the figures for rural labour into this real wage study as

well. Despite their inherent limitations, agricultural wage observations can still serve as useful

tools for two purposes.

Firstly, through rural wages, it is possible to estimate – albeit very roughly – a lower

bound of living standards. The purpose of this study is to distil the development of the

minimum living standard for a large share of the native population. This objective entails that

an underestimation of the living standard would not hamper the results of the analysis, but

would rather strengthen it. Having no rural price observations available for our selected

African colonies, there is thus strong reason to assume that estimations of a subsistence ratio

for agricultural workers reflect ‘the worst case scenario’, or, in less normative terms, the

36

minimum or the lower bound. Both to enable making careful estimations about the minimum

living standard, and to capture a large share of the native population, it thus seems wise to

incorporate agricultural wages into our analysis. However, even though our rural real wage

estimations will be underrated rather than overrated, one question remains. If we take these

rural wage rates with urban prices as a proxi for the minimum living standard, how far off

would this calculation to be from the actual living standard?

This question is not one that can be answered in any precise terms. However, there are

good reasons to believe that the gap between the underestimated living standard and the actual

one is not so big that the results from this empirical analysis could be considered practically

futile. With respect to the size of in kind payments, we are fortunate to have some quantitative

insights in this matter. In British Africa, such supplementary income sources have been

relatively well documented in the Blue Books. For each occupational sector – generally

agriculture, domestic services, government and trades – colonial administrators were required

to state the wage rate “including the value of any payments in kind.”64

For some countries, the

value of the rations has even been specified separately, giving us an indication how large this

share of in kind payments was vis-à-vis the monetary part of the nominal wage. Additionally,

regarding the rural-wage-urban-price disparity, we have good reason to believe that the

overall price level in the rural regions did not diverge too drastically from that in the urban

centres. It has to be taken into account that the observations for rural wage labour do not refer

to completely remote regions that were located far from the urban centres. Most large-scale

farms or plantations, where the demand for agricultural wage labour mainly came from, were

situated either around the administrative capital, or in other strategic locations for trade, in

close proximity of the transportation network. As such, in these rural enclaves, especially in

those sprouting up around the main cities, one can speak of a certain degree of market

integration with the urban economy. It is therefore very likely that rural, or ‘semi-rural’,

prices, did not differ exceedingly from the urban prices we have available. Evidently, there are

still some problems with the rural real wage series we will present for British Africa.

However, the benefits of incorporating such a time-series for this study are large, and we

believe that the overall error margin of our calculations remains acceptable, As such, these

rural data figures will serve in this study as a lower bound benchmark for the results found for

urban unskilled labour.

64

All of the Blue Books used for this study require this, and the rations are either mentioned separately as ‘on

top’ of the nominal wages, or as a value included in these.

37

Secondly, having both rural and urban wage figures to our disposal is advantageous in

the sense that these contain valuable information with respect to the plausibility of the

colonial statistical records in general. One can build in another check on the soundness of the

numbers provided in the Blue Books by comparing the levels of the nominal agricultural

wages, including the value of the in kind payments, with the levels of urban unskilled

labourers (which rarely included rations). If these figures are indeed reliable enough to work

with, we would expect to find that nominal wage rates for industrial labourers are slightly

above those for agricultural labourers. Generally, agricultural wages fluctuate in between 50

to 100 percent of the level of their industrial counterparts. Table 3.2 below, depicting the ratio

of these nominal wages levels for six different periods, reveals that for all of the African

colonies these numbers are in between the expected boundaries, hence strengthening our

confidence in the solidity of the empirical basis used for this comparative study.

Table 3.2 Periodical ratios of nominal agricultural wages levels vis-à-vis

industrial wage levels for British Colonial Africa

COUNTRY PRE-1900 1900-1914 WWI 1920-1929 1930-1939 WWII

WAG/WIN WAG/WIN WAG/WIN WAG/WIN WAG/WIN WAG/WIN

Gambia 0.85 0.87 0.81 0.75 0.75

Gold Coast 0.71 0.94 0.91

Kenya 0.78 0.91 0.75 0.58

Mauritius 0.43 0.68 0.75 0.57 0.71

Nigeria 0.87 0.98 0.83 0.52 0.63 0.88

Nyasaland 0.69 0.82 0.69 0.57

Sierra Leone 0.59 0.83 1.01 0.83 0.72 0.77

Uganda 0.5 0.5 0.6 0.5

Sources: Colonial Blue Books

A few cases in this table, however, require further elaboration. For the Gold Coast, we

have excluded the rural-urban wage ratio for the periods 1900-1914, WWI, and 1920-1929 as

we had no separate data available for the category agricultural labour in these years. The Blue

Books indicate that the price for unskilled labour in the countryside more or less equalled that

of the urban centres. In some respects, it can be argues that such a trend is not that remarkable.

The small territory of the Gold Coast was already a comparatively well-integrated economy,

and as such, it is not so surprising that the difference between rural and urban wages was quite

small. Moreover, as pointed out by Austin, the exponential increase in cocoa cultivation in the

first two decades of the twentieth century, combined with the growth of the infrastructural

network, altered the dynamics of the land-labour ratio and the market of land use rights. He

points out that “cocoa made it possible for farmers to offer labourers pay at or above

38

reservation wage rates.”65

Nonetheless, we believe that for the purpose of creating a rural-

urban ratio, these agricultural wage figures are too speculative, and hence we have excluded

them from this part of the analysis. Additionally, it should be mentioned that the wage ratios

for Mauritius are based on rural unskilled labour on the one hand and urban skilled labour on

the other. Evidently, this inflates the rural-urban wage gap for this colony. Unfortunately, no

consistent wage figures were available for urban unskilled labour in the Blue Books for

Mauritius. However, one has to take into account that the far majority of the employed

population performing unskilled labour tasks was occupied in the sugar industry. Considering

the small size of the island, and the relatively high level of market integration, we can

reasonably assume that wages paid to, for example, carriers of sugar on plantations must not

have differed too much from those paid to carriers of sugar in the harbour. Consequently, the

real wage series in this study will also be based upon rural unskilled labour.

The nominal wage levels have both been provided as single average rates and as areas

in between minimum and maximum rates in the Blue Books. For this study the average rates

have been maintained, meaning that this figure had to be derived from the figures available.

The most common way to derive such an average rate on the basis of minimum and maximum

information, is by taking a lognormal distribution, assuming that the distribution is skewed to

the lower bound. This approach has been taken and years derived on this basis are italicized in

the appendix. Taking into account that minimum wage rates, when provided, at times

indicated the amounts paid to women or children, this calculation of the average wage level

for male native labour can be considered relatively accurate. However, there is another way of

going about this; one that can be used to estimate the validity of our average estimates. In

some cases, both of these categories – an average rate and a minimum and maximum – were

present at the same time. This allowed for an inference of how much the average nominal

wage rate was above its minimum counterpart. I derived that the average level equalled:

WAVERAGE = WMIN + ((WMAX – WMIN) ! 0.301)

Applying this equation to all of the years for which no average value was available yields

nearly the same result as taking a lognormal distribution. At most, the difference between the

lognormal average and the average based on this latter equation was 1 or 2 percent, making

65

Gareth Austin, “Land and labour Ghana, 1874-1939: A shifting ration and an institutional revolution,”

Australian Economic History Review, 47, 2007: 1.

39

the difference as good as negligible. Therefore, we can assume that the lognormal averages as

calculated for this study, are relatively solid estimates.

In some cases our wage figures for unskilled labour had to be derived from rates

provided for skilled labour. Especially in the early colonial Blue Books, no separate figures

were available in some of the colonial Blue Books for ‘ordinary’ labourers or carriers in the

category ‘trades’. In such cases, the daily unskilled urban wage rates have been estimated on

the basis of those for skilled labour (carpenters, masons or blacksmiths). According to

Frankema, a simple linear regression analysis suggests that the average skill-premium in all

British colonies was around 113 percent.66

This yields an equation of:

WSKILLED = 2.13 ! WUNSKILLED + 2.11

This equation has been applied to practically all years for which only skilled urban labour

rates were available. However, in case a later colonial Blue Book (with nominal wage rates

for both unskilled and skilled labour) strongly indicated that unskilled rates of the previous

years were most likely the same as the year in which these were first explicitly documented,

these earlier years have been extrapolated on the basis of the value for the later year.67

For most of the cases in this study, the units in which nominal wage rates were

measured changed over time; these being either on a daily, monthly or annual basis. In order

to convert these records into consistent and workable figures, all have been expressed in daily

wages. I assumed that the average African agricultural an industrial labourer worked

approximately 26 days per month – reflecting a six-day workweek – and, hence, 312 days

annually. For some years, where both monthly or annual and daily wages were available, we

see that these figures correspond well to this assumption. Where there was any discrepancy

between the values of the daily and yearly rates, such incongruities can be attributed to the

fact that next to the annual rate the labourer received, as for example in the case of Mauritius,

“rations, lodging and medical care.”68

66

Frankema, “Raising Revenue in the British Empire”, 13. Frankema does, for various reasons, exclude South

Africa, Southern Rhodesia, Australia, Canada and New Zealand from this regression analysis. 67

Such extrapolation could of course only be used if there was no movement in the nominal wage rates for

skilled labour between the early years and the year for which unskilled labour rates became available. See for

example the years 1897-1912 for Sierra Leone, which have been based upon the wage rate for unskilled

labourers of 1915, rather than on the figures for carpenters that were available for this period. 68

See for example Mauritius, in the early Blue Books (1899-1917) both annual and daily wage rates are available

for urban and rural labourers. The rates paid to labourers that had an annual or monthly-based contract on one of

the estates also received rations, medical care and lodgings when occupied in agriculture, and lodgings and

medical care when working in the trades sector. In later years, one can derive how large the value of the rations,

lodging and medical attendance were for agricultural labourers when under a monthly contract. The monthly

40

As our real wages will be presented in the form of a subsistence ratio, for which the

daily wages will be converted back to annual ones, and will be compared to those of Allen, it

is important to explain here the latter’s approach with respect to the compilation of the annual

income levels. He argues as follows:

In Europe, most of the wage information refers to daily wages, and we assume that a full year

was 250 days - the balance was accounted for by Sundays, religious holidays, illness and slack

time. In India, many of the wage contracts we know were monthly, so we take annual earnings

to be twelve times the monthly figure.69

Clearly, Allen tries to make as accurate an estimate of the annual wage earnings as

possible, and relies upon differentiation in terms of days worked per year for his cases rather

than a uniform theoretical supposition that should be universally applicable. The implication

for this study is that we can – and should – apply a comparable case-particular approach to our

wage data for British Africa. On the basis of the corresponding levels we found for daily,

monthly and annual wages, we will base the African yearly income rates on 312 work-days.70

3.2.3. Compilation of the Price Data

In order to deflate the nominal wage rates, a basket of goods has been created – or a simple

form of a ‘Consumer Price Index’ (hereafter CPI) – with each component having a particular

weight. For further international comparative reasons, the CPI that has been chosen for this

empirical analysis is based on Robert C. Allen’s ‘bare bones’ subsistence basket. In his latest

work, The British Industrial Revolution in a Global Perspective, Allen traces the development

of purchasing power for different places in pre-industrial Europe and Asia by calculating “the

reward for this kind of labour was “Rs. 10 with rations, free lodging, and medical attendance, all in equivalent to

about Rs. 50 per month” (Blue Book, 1923, Section X 3), which makes a total of Rs. 60 per month, or converted

in a daily wage Rs. 2.3, based upon our assumed 26 work-days per month. Day labourers received Rs. 2.00-3.00

per day, yielding a lognormal average of Rs. 2.45 per day. This difference is about 6% in total and can be

considered negligible. Evidently such margins differ from year to year, as the value of the contract-based

earnings does not fluctuate at par with those of day labourers. However, the daily wage rates of day labourers

provide for a better input figures for our real wage series, as the purchasing power of this category was much

more dependent upon changes in the overall price level, and its nominal wage levels were to a greater extent a

product of the market. 69

Robert C. Allen, The British Revolution in a Global Perspective. (Cambridge: Cambridge University Press,

2009), 38. 70

Statistical tables relating to British self-governing dominions, crown colonies, possessions and protectorates

(London): issue of 1911, Kenya, No. 23, “Average Rates of Wages for Various Descriptions of Labour in each of

the Years ended 31st March, 1910, 1911, 1912”, p. 414. Evidently, we considered the wage rate provided for the

year ended on March 31st 1910 as the value for 1909, and so onwards. In this table one can see for the years 1910

and 1911 how great the equivalence is between daily and annual wages based on the 312 work-days per year.

41

ratio of full-time annual income to annual subsistence cost.”71

To derive the annual

subsistence cost, he assumes that a male adult needs to consume about 1950 calories per day

for survival. As can be seen in figure 3.1 below, Allen’s ‘subsistence basket’ for Indian

unskilled labour, is based on the assumption that about 85% of the daily calories are obtained

through the consumption of a carbohydrate-rich staple crop. Additionally, Allen assumes that

about 3 meters of cotton were consumed annually. For the subsistence ratio, he translates this

basket for a single adult male into a spending pattern for an average household. On average,

the daily caloric needs for women is lower than that for men, and even fewer for children. As

such, he estimates that about three baskets of goods were needed to support a household

consisting of a father, a mother and some children. Taking into account that rent needs to be

deducted from the salary as well, he estimates that the total amount of expenditure to sustain a

small household was about 3.15 times the amount of the subsistence basket.72

Figure 3.1: Caloric decomposition for various products in Allen’s subsistence basket

for unskilled labourers in pre-industrial India

Sources: Allen, 2009.

71

Robert C. Allen, The British Revolution in a Global Perspective. (Cambridge: Cambridge University Press,

2009), 38. Note that Allen creates comparative real wage series for pre-industrial Europe and Asia to shed new

light upon the (related) debates of the ‘great divergence’ and that of ‘why the industrial revolution occurred in

Britain’. 72

Although we do not know what the amount of rent was, that was paid by the native African population, we will

for reasons of consistency apply the same percentage for British colonial Africa. Nonetheless, as people in

subsistence economies spend about 90% of their income on food, we can assume that the 5% as suggested by

Allen is a fairly good estimate.

!"#$

%&#$

%#$

'#$

%#$

rice

beans/

peas

meat

butter

sugar

42

For our African subsistence basket, we have also set the amount of calories needed to sustain

a male adult at 1950Kcal per day. We assume here that the average African native may not

have been much taller than his Asian counterparts, and hence that the 1950 Kcal is a good

approximation of the level of caloric intake required for subsistence. It is reasonable to

assume that the diet of the average native inhabitant in British Africa also consisted to a large

extent of ‘basic’ food crops. As can be derived from Donald Mitchell’s World Food Outlook,

for example, the dietary composition of current developing economies consists on average of

about 60 percent on cereals, another 30 percent on vegetables, and a small 10 percent on

animal products.73

There are only two ways in which the African subsistence basket differs from Allen’s

for India. The first is that the pre-industrial Indian basket includes beans and peas. For British

Africa little to no such price information was available for these carbohydrate-rich vegetables.

Therefore, these products have been substituted for an amount of the main staple crop that

yields an equal amount of calories. Secondly, we had to replace butter for a percentage share

of the basket that consisted of local substitutes such as palm oil or ghee. The prices

documented in the Blue Books for butter referred mostly to imported butter, which was most

likely consumed by British administrators and not by the local population. As information on

palm oil of ghee was only sparsely available, we have assumed, on the basis of the years we

did have, that these products amounted to about 10 percent of the cost of the total basket.

Hence, the calculation of the annual African subsistence cost constitutes:

PSUBSISTENCE = (((PSTAPLE CROP + PMEAT + PSUGAR)/90)*100)) ! 3.15

Evidently, the explanatory power of our subsistence basket for British Africa is first of

all dependent upon the selection of the ‘most appropriate’ staple crop. Depending upon

location and purchasing power of the population, rice, maize, millet, sweet potatoes, cassava

and yams constitute Africa’s main staple crops. The selection of the most important crop for

our country-based subsistence baskets has been based upon Brian Mitchell’s International

Historical Statistics, complemented by information on native consumption patterns found in

the colonial Blue Books and Sessional Papers.74

Ideally, price information for these selected

73

Donald O. Mitchell, M.D. Ingco and R.C. Duncan, The World Food Outlook, (Cambridge: Cambridge

University Press, 1997), 24. 74

Unfortunately, Mitchell’s statistical records on the output of main arable food crops for Africa are to a large

degree limited to the post-colonial period. B. R. Mitchell, International Historical Statistics: Africa, Asia and

Oceania, 1750-2000, (Basingstoke and New York: Palgrave Macmillan, 4th

ed., 2003). Where available in the

43

food crops would be available for the full period under consideration in this study. However,

the colonial statistical records only provide near-complete time-series for wheaten flour and

rice, which were consumed by the British administrators, and no constant price observations

are available for the native staple crops. Moreover, constructing a time-series of the latter

category was further complicated by changes over time in units of measurement. The

Sessional Papers for Nigeria, 1938, illustrate such common measurement problems:

Food is not sold by weight, but by arbitrary measures or by number; butchers in Lagos are

required by law to use scales, but in practice most of their customer know nothing about such

measurement and prefer to buy meat by the piece.75

Evidently, price information that is expressed in terms of “per bunch” or “per basket” clearly

poses problems for the incorporation of such commodities into a continuous CPI.

Table 3.3: Correlation coefficient between prices for main native food

crop and rice and wheat, British Colonial Africa

R2

Rice Wheat

Gambia maize -0.37 0.49

Gold Coast maize 0.53 0.72

maize 0.46 0.56 Kenya

potatoes 0.56 0.35

Mauritius maize 0.96 0.69

maize 0.67 0.62 Nigeria

cassava 0.82 0.93

Nyasaland76

maize

Sierra Leone maize 0.58 0.70

cassava 0.33 0.24

millet 0.01 0.02

Uganda

sweet potatoes77

-0.38 -0.43

Sources: Colonial Blue Books

Nonetheless, it is possible to overcome such data limitations. As can be seen in table

3.3 above, we have assessed the correlation between the price movements of wheat or rice on

Blue Books and Sessional Papers, information on native consumption patterns has been used. See: name Blue

Books and Sessional Papers (Nigeria, 1934, Nyasaland, 1948, Sierra Leone, 1932, Uganda all Blue Books after

1925) 75

Nigeria, Annual Report on the Social and Economic Progress of the People of Nigeria for 1938, “IX Wages

and Cost of Living”, 59. 76

Unfortunately, no price observations on maize were available for Nyasaland for the years in this study.

However, in the Sessional Papers of 1948, both maize and rice prices were available, indicating that rice prices

per lb. were nearly twice as high as that of maize. Consequently, the subsistence ratio for maize for Nyasaland

has been estimated upon the price figures for 1948. See: Nyasaland Protectorate, Annual Report of the Labour

Department for the year ended 31st December, 1949, Table VII, Prices of Commodities at Local Markets, 18.

77 The series of sweet potatoes has been extrapolated on the basis of 6 simultaneous price observations for beans.

44

the one hand and, the incomplete native food crop on the other. Unless indicated in bold, all

R2 values in the graph have been based upon a minimum of 10 price observations.

78 The high

level of the R2 values we have obtained for these correlation assessments allowed to expand

the time-series of the incomplete crop through extrapolation, and demonstrates that this

technique can be considered a relatively solid alternative. The selected dietary products for the

subsistence baskets are therefore a plausible reflection of both the general price movement

and its level. The subsistence ratios and indices have been documented in tables 1.1.1.-1.1.16.

in appendix I. Additionally, the caloric and nutritional composition of the different

subsistence baskets can be found tables 3.1-3.3 in appendix II.

3.3 Results

3.3.1. The Development of Real Wages – Long-run Trends and Levels

On the basis of the time-series for nominal wages and the CPI, as conducted along the lines

described above, we can now derive a real wage series, or ‘subsistence ratio’. The advantage

of expressing our real wages series in the form of a subsistence ratio is that it allows us to not

only get an impression of the overall fluctuations in purchasing power, as an index would do,

but also to gain some insights in the actual amount of food that could be purchased. On the

next four pages, individual graphs (figures 3.2-3.9) are presented for the development of

purchasing power in each of the colonies selected for this study. Before embarking upon a

discussion of the results found for the different subsistence ratios, it is necessary to mention a

couple of technical aspects of the graphs.

First, for some colonies, where price information on various native food crops was

abundant, it was possible to construct multiple subsistence ratios through extrapolation. In

some cases, where only a few years with such native staple crops were available, the

extrapolated ratio can tell us something about the relative standard of living that could be

obtained by consuming commodity X versus consuming commodity Y. When near complete

time-series were available, as for example for Gold Coast and Uganda, one can not only get

an impression of relative living standard with respect to consuming different food crops, but it

can also be observed how the overall living standard could be maintained by substituting one

78

The foodcrops for which we had less than 10 years available that are presented in this table should not cause

any significant problems for our analysis. For the colonies concerned here, Gambia and Mauritius, maize was not

the main food crop in that colony (rice was), and serves mainly in our sample as a potential upper bound of the

subsistence ratio. In case we only had one or two years of price information available, such as millet in Sierra

Leone, no full time-series has been created for these food crops, and they have been represented in the graph in

the next section only for the years we do have information.

45

crop for another in times of a bad harvest or high world food prices. Second, it should be

emphasized that these subsistence ratios are applicable to the administrative capitals, as this is

where most of the price information has been taken from. As such, the subsistence ratio of, for

example, Nigeria, regards Lagos, and not the economically more peripheral hinterlands.

Thirdly, it is important to point out, that one should focus on the long-run trend in these

graphs, and not on the year-to-year fluctuations. Especially the strongest outlying values are

predominantly reflections of harvest yields or price-wage time-lags in data reporting in

periods of high inflation, rather than solid indications of the level of purchasing power.

Finally, the WWII years, unlike in the real wages tables in the appendices, have not been

included in these graphs, as changes in the subsistence ratio in this period do not reflect the

effects of colonial rule, but rather that of extreme external conditions.

A first look at the overall trend tells us that purchasing power for urban unskilled

labourers appears to have increased in most countries since 1910. In Gambia, Gold Coast,

Sierra Leone, Nigeria and Uganda, the subsistence ratio augmented indisputably in the course

of the colonial period. This picture of a more economically developed West than East Africa

is not surprising, and is supported by the literature. Maddison’s earliest GDP per capita

figures for SSA highlight the exceptional position of Ghana and Mauritius in terms of per

capita income levels. Comparing an aggregate average of the 1950 GDP per capita levels for

West Africa (Gambia, Gold Coast, Nigeria, and Sierra Leone) with those for East Africa

(Kenya, Uganda, Nyasaland), reveals a relative West-East income ratio of 1:0.71. Also,

Frankema’s studies on taxation and public spending patterns in British Africa point towards

much higher per capita trade and GPR rates for West versus East part of the continent.79

Moreover, with respect to the absolute values of the subsistence ratios, the average levels of

around 2.0 and 3.0 suggest that the native population did not live on the verge of starvation. In

the graphs for Gambia, Gold Coast and Sierra Leone is can be seen that the average wage

worker was able to substitute maize for rice, the latter of which we assume was higher in the

order of consumption preferences.

The trend we see for British Uganda is consistent with the literature as well. Uganda

was in some respects an exceptional case in colonial East Africa. Reid points out how within a

few years after the trade in ivory and slaves had ended in the late nineteenth century, “Uganda

79

Frankema, “Raising Revenue in the British Empire,” 2009; and Frankema, “Toiling for Prisons or Hospitals?

A comparative study of colonial taxation and public spending in British Africa,” Preliminary version. March

2010.

46

Figure 3.2: Subsistence ratio for urban unskilled labourers, Gambia (Bathurst), 1880-1939

Sources: Colonial Blue Books; subsistence basket based on Allen, 2009

Figure 3.3: Subsistence ratio for urban unskilled labourers, Gold Coast (Accra), 1880-1939

Sources: Colonial Blue Books; subsistence basket based on Allen, 2009

0

1

2

3

4

5

6

7

8 1880

1882

1884

1886

1888

1890

1892

1894

1896

1898

1900

1902

1904

1906

1908

1910

1912

1914

1916

1918

1920

1922

1924

1926

1928

1930

1932

1934

1936

1938

subsistence ratio urban - rice subsistence ratio urban - maize

0

1

2

3

4

5

6

7

8

1880

1882

1884

1886

1888

1890

1892

1894

1896

1898

1900

1902

1904

1906

1908

1910

1912

1914

1916

1918

1920

1922

1924

1926

1928

1930

1932

1934

1936

1938

subsistence ratio urban - maize subsistence ratio urban - rice

47

Figure 3.4: Subsistence ratio for urban unskilled labourers, Kenya (Nairobi), 1905-1938

Sources: Colonial Blue Books; subsistence basket based on Allen, 2009

Figure 3.5: Subsistence ratio for urban unskilled labourers, Mauritius (Port Louis), 1900-1939

Sources: Colonial Blue Books; subsistence basket based on Allen, 2009

0

1

2

3

4

5

6

7

8 1905

1907

1909

1911

1913

1915

1917

1919

1921

1923

1925

1927

1929

1931

1933

1935

1937

urban subsistence ratio - maize urban subsistence ratio - potatoes

0

1

2

3

4

5

6

7

8

1900

1902

1904

1906

1908

1910

1912

1914

1916

1918

1920

1922

1924

1926

1928

1930

1932

1934

1936

1938

subsistence ratio unskilled rural - rice subsistence ratio skilled urban - rice

48

Figure 3.6: Subsistence ratio for urban unskilled labourers, Nigeria (Lagos), 1880-1939

Sources: Colonial Blue Books; subsistence basket based on Allen, 2009

Figure 3.7: Subsistence ratio for urban unskilled labourers, Nyasaland (Zomba), 1904-1938

Sources: Colonial Blue Books; subsistence basket based on Allen, 2009

0

1

2

3

4

5

6

7

8 1880

1882

1884

1886

1888

1890

1892

1894

1896

1898

1900

1902

1904

1906

1908

1910

1912

1914

1916

1918

1920

1922

1924

1926

1928

1930

1932

1934

1936

1938

subsistence ratio urban - maize subsistence ratio urban - cassava

subsistence ratio - rice

0

1

2

3

4

5

6

7

8

1904

1905

1906

1907

1908

1909

1910

1911

1912

1913

1914

1915

1916

1917

1918

1919

1920

1921

1922

1923

1924

1925

1926

1927

1928

1929

1930

1931

1932

1933

1934

1935

1936

1937

1938

urban subsistence ratio - rice urban subsistence ratio - maize

49

Figure 3.8: Subsistence ratio for urban unskilled labourers, Sierra Leone (Freetown), 1880-1939

Sources: Colonial Blue Books; subsistence basket based on Allen, 2009

Figure 3.9: Subsistence ratio for urban unskilled labourers, Uganda (Kampala), 1906-1939

Sources: Colonial Blue Books; subsistence basket based on Allen, 2009

0

1

2

3

4

5

6

7

8

1880

1882

1884

1886

1888

1890

1892

1894

1896

1898

1900

1902

1904

1906

1908

1910

1912

1914

1916

1918

1920

1922

1924

1926

1928

1930

1932

1934

1936

1938

subsistence ratio urban - maize subsistence ratio urban - rice

subsistence ratio urban - millet

!"

#"

$"

%"

&"

'"

("

)"

*"

1906

1907

1908

1909

1910

1911

1912

1913

1914

1915

1916

1917

1918

1919

1920

1921

1922

1923

1924

1925

1926

1927

1928

1929

1930

1931

1932

1933

1934

1935

1936

1937

1938

1939

urban subsistence ratio - millet urban subsistence ratio - cassava

urban subsistence ratio - sw. pots

50

had become a major producer of cotton and unlike in the Gold Coast, the colonial state can be

seen to have been instrumental in bringing about change.”80

Evidently, the rise of a dynamic

economy in Uganda led to economic gains from which it seems that also the average native

population could profit. The fluctuations in cassava prices that can be observed for the years

1929-1930 and 1937-1938, were the result of the cassava mosaic virus disease, which

occasionally destroyed a large share of this crop’s harvest in East Africa.81

Again, the

reflection of such harvest fluctuations in our price data supports the reliability of these figures.

For Kenya we do not observe similar significant increases or declines in purchasing

power at first sight. The Kenyan case stands out from the other colonies selected for this study

in various ways. Firstly, it is the only colonial territory for which we have no information

available for the period of WWI until the end of the 1920s, as no colonial Blue Books

appeared in these years. Consequently, we have a relatively large data gap in our subsistence

ratio. It is important here to recognize some of the limitations of our dataset for this colony.

The years before WWI have been based upon figures for (skilled) Swahili carpenters, whereas

the years from the mid-1920s onwards are from observations for unskilled industrial

labourers. The long-run trend of our real wages series, and the comparability of the early years

with the later years, depends thus on the extent that the skill-premium is a good reflection of

the skilled-unskilled nominal wage gap. Unfortunately, in none of the early Blue Books we

have found any observation for unskilled urban labour, which we could have used to check

the assumed skill-premium. In the other colonies in this study, we were able to observe that a

transition from skilled labour figures (converted to unskilled wage rates) did not cause any

significant break in the long-run nominal wage trend. For Kenya, in contrast, with a data-gap

of nearly 15 years, it was impossible to make such an assessment.82

Another reason why this

skill-premium could have been slightly problematic for this British colony, is the fact that the

colonial population was one that was based upon a relatively high degree of European

settlement and Indian immigration. As such, differentiation in the wage rates may be as much

a reflection of different skill-levels as of racial variety. Therefore, we need to be cautious

when drawing conclusions on the basis of the long-term real wage trend.

80

Reid, A History of Modern Africa, 178. 81

J. P. Legg and J. M. Tresh, “Cassava mosaic virus disease in East Africa: a dynamic disease in a changing

environment,” Virus Research 71 (2000): 135-149. 82

As such it is difficult as well to support a claim of a slight rise between the pre-WWI years, with an average

subsistence ratio of 1.0, and the post-WWI years, with an average of 1.5-2.0. If the period from the mid-1920s to

WWII would stand on its own, then hardly any increases in the subsistence ratio are discernable, a trend we do

observe in the West African colonies and Uganda.

51

We do, however, have good reasons to believe that the figures used for the second part

of the real wage series, are reliable. The collapse of the real wage level for unskilled urban

labour in the year 1929 is supported by reports from that year’s Annual Report of the Native

Affairs Department:

10. Economically speaking, the year, with its visitation of locusts, drought and famine was

disastrous in certain areas. The Meru and Embu districts of the Kikuyu Province and the Kitui

District of the Ukamba Province suffered actually from famine which necessitated extensive

measures of relief. (…) On the Coast and in the native reserves of the Rift Valley Province a

food shortage occurred which, however, was relieved by the measures taken and never reached

the extremity of famine.

24. Generally speaking, the year has been a difficult one. Owing to drought and locusts a food

shortage occurred in all districts, necessitating the importation of food. In the Digo and Kilifi

districts maize was purchased from money voted by the Local Native Council and sold at cost

price. 83

Evidently, the low subsistence ratio for this year was a direct consequence of a failed harvest.

The ensuing food shortages, and even famines in certain parts of the colony, led to the

importation of maize on behalf of the colonial administration, hence driving up the prices of

the main staple crop and pushing down the real wage level in that year.

An interesting pattern can be distilled when comparing the subsistence level of Kenya

to that of the West-African colonies and Uganda. Kenya’s subsistence ratio, with an average

absolute value of around 1.5-2.0 in the mid-1920s and 1930s, contrasts sharply with the nearly

twice as high values that can be observed for the latter ones. This in itself is not so surprising,

and certainly not inconsistent with the image of the colony that we find in the literature.

Kenya is widely regarded as a colonial territory where the native population suffered heavily

under British rule; something this real wage graph seems to underwrite both in terms of the

trend and the overall subsistence level. In contrast to the other territories included in this

study, Kenya was a ‘settler economy’, where European settlers were allowed to appropriate

agricultural land. According to Bowden and Mosley “settler-type political systems tended to

produce highly unequal income distributions and, as a consequence, patterns of public

expenditure and investment in human capital which were strongly biased against smallholder

83

Kenya Colony and Protectorate, Native Affairs Department, Annual Report, 1929, (London: His Majesty’s

Stationary Office, 1931), 6, 8.

52

agriculture and thence against poverty reduction.”84

Reid too, emphasizes that the European-

centric political-economic equilibrium of the settler colonies had greater disadvantageous

implications for the native population, the latter which became “politically and economically

marginalized”, as “the settler economy relied on their labour.”85

The comparatively low level

of nominal wage rates in Kenya seems to support this statement.

Finally, our real wage graphs display Mauritius’ divergent economic trajectory vis-à-

vis the rest of the SSA countries incorporated in this analysis. Not only is this sugar-island the

only one with a steady post-colonial growth record, it also had the by far highest GDP per

capita figures in 1950 – more than twice the level of the second highest in our sample (Gold

Coast) – and it had the highest nominal trade and government revenue values per head of the

population while under colonial rule. Although the average unskilled rural wage labourer in

Mauritius may not have experienced a strong rise in purchasing power in these early

twentieth-century decades, the high level of the subsistence ratio at the start of the period

highlights the substantial amount of growth had already been realized and distributed in this

colonial society before 1900.86

If one looks at the subsistence ratio for urban skilled labour, it

seems that this category of wage workers did experience an increase of purchasing power over

the time-span covered.

Lastly, the results for Nyasaland seem plausible, as they confirm the image of this

colony as a marginally developed, peripheral region within the British Empire. Although

cotton growing and tobacco cultivation were industries that developed in Nyasaland under

colonial rule, no comparable economic dynamism was found to that of West Africa. The

subsistence ratio, the lowest in our sample, is stagnant for years in a row and seems to have

declined over time. The Annual Report of the Labour Department from the end of the colonial

period point out that famines still occurred frequently, that the administration was forced to

import staple crops to provide for famine relief, and that the younger population looked for

opportunities in neighbouring territories:

35. In Nyasaland the main source of employment is found in agriculture: the bulk of the

population maintain themselves by subsistence agriculture, normally growing food crops and a

84

Sue Bowden and Paul Mosley, “Politics, public expenditure and the evolution of poverty in Africa 1920-

2007,” version derived from XVth World Economic History Congress,

http://www.wehc2009.org/programme.asp?find=jerven 85

Reid, A History of Modern Africa, 181. 86

One has to take into account that when comparing the average of 2.5-3.0 subsistence ratio for Mauritius in the

early colonial years to that of other colonies with relatively high subsistence ratios (as found for Gambia, Gold

Coast and Nigeria) that this ratio is not only based upon figures for rural labour, but also for the more expensive

staple crop rice.

53

few cash crops, chiefly tobacco, and by working at intervals at the estates. The cost of living is

therefore regulated generally speaking, rather by climatic conditions and the abundance or

scarcity of food crops than by any change in world prices. (…) The standard of life is also still

rather primitive. The boredom and the general lack of amenities and amusements of village life

are often cited as contributory causes of the annual migration of such numbers of the younger

members of the population to South Africa and Southern Rhodesia.87

3.3.2. Periodical Changes in Nominal Wage, Price and Real Wage Levels

In order to gain some deeper insights into the development of purchasing power, the nominal

wage, price and real wage indices have been decomposed for each country for a number of

specific periods, as can be found in table 3.4 below. For each of these periods an average

annual percentage change in nominal wages, prices and real wages has been calculated. In

order not to disrupt the long-run pattern, the last year of period 2 (for example the values for

1929 in the period 1920-1929) also serves as the first year for period 3 (1930-1938).

Similarly, the last year of period 3, also serves as the first year for period 4. There is only one

exception in this manner of calculating the average annual percentage changes. As little data

was available for the WWI years, only the pre-WWI period stands on its own for some

colonies. Nonetheless, this should not be problematic, as little changes occurred in this period

and our main interests goes out to the interbellum years.

Table 3.4: Average annual percentage changes in nominal wages, prices and real wages for industrial

unskilled labour in British Colonial Africa

Sources: Colonial Blue Books

There are certain advantages of treating our data in such manner. Firstly, by breaking

down the long-run pattern into smaller units it becomes easier to conduct intertemporal

comparisons. One can now compare the trends of wage and price changes for one epoch with

that of another. Secondly, such a decomposition will reveal information about the reasons why

87

Nyasaland Protectorate, Annual Report of the Labour Department for the year ended 31st December, 1949, “VI

– Living Conditions”, 6.

COUNTRY PRE-WWI WWI 1920s 1930s WWII

Average

WN

P

WR WN

P

WR WN

P

WR WN

P

WR WN

P

WR

Gambia 0 -1.8 1.8 -1.7 -3.6 1.9 -3.7 -1.0 -2.7 12.5 27.7 -15.2

Gold Coast -0.1 -0.4 0.3 -3.4 -6.6 3.3 4.3 -0.8 5.0 0 18.5 -18.5

Kenya 0 3.6 -3.6 -0.2 -1.3 1.1 16.7 3.3 13.4

Mauritius 3.0 0.6 2.3 16.5 8.6 8.0 -5.4 -4.8 -0.6 0.9 -3.9 4.7

Nigeria -0.3 -1.5 1.2 -2.5 -4.3 1.8 0.4 -2.2 2.6 4.0 6.6 -2.6

Nyasaland 0.0 -0.2 0.2 -1.8 -0.8 -1.0 1.3 -3.9 5.3

Sierra Leone -0.5 -1.6 1.1 10.0 6.4 3.6 -1.6 -4.7 3.1 -0.3 -4.1 3.8 5.3 29.8 -24.5

Uganda 0.4 -3.9 4.3 24.1 20.4 3.7 0.7 -2.9 3.6 -3.5 -4.9 1.5 3.6 14.3 -10.7

54

real wages rose or declined. Did prices, for example, increase faster than nominal wages, or

vice versa? Taking a closer look at table 3.4 some interesting patterns. Starting at the pre-

WWI period, it appears that for all the colonies in this study but Kenya, the average annual

percentage change in real wages was positive. This generally rising trend can mainly be

attributed to the decline in the overall price level, a phenomenon that did not occur

exclusively in SSA.88

Moreover, it seems to support Smits’ hypothesis that already before

1910 a fair amount of per capita income growth was realized and that the native population

profited from this as well. In the 1920s we see an increase in real wage levels for all our

countries, with the exception of Nyasaland and Mauritius, as well. Partially, this trend should

be attributed to the fact that real wages suffered much during the WWI-years, as can be

derived from the long-run trends depicted in figures 3.2 to 3.9 above. Hence, the increase in

purchasing power in the 1920s should to some extent be interpreted as a sign of a recovery of

purchasing power. Nonetheless, the graphs also depict that by the end of the 1920s, real wages

had augmented, for all countries but Nyasaland, to levels above that of 1910.

In the course of the 1930s, the upward trend continued in most of the colonies, albeit

not with a magnitude comparable to the previous decade. Both nominal wage and price levels

declined in these years, but any gains in purchasing power were minimal. However, in

Gambia, real wages went down in the 1930s. Interesting to note here for Gambia is that there

are indications that in Gambia there was some form of wage-politics by the colonizing powers

in this decade. If we take a close look at the price observations in the Blue Books we indeed

find supporting evidence for this hypothesis. In the statistical records of the early 1930s for

Gambia, for example, it is stated that for the main food crops consumed by the African

population, the “maximum retail price was controlled by Proclamation.”89

Moreover, the overall moderate trend for this decade seems to corroborate Smits’

observation that, in terms of per capita income, the African continent suffered only marginally

from 1930s backlash compared to many other parts of the world. These figures reveal that in

sum, there was little volatility in the real income of the employed part of the population as

well. In the Sessional Papers of Gold Coast, one of the colonies in British Africa that was

more integrated in the global economy, one finds the following report on the impact of the

depression on the native population:

88

See for example the discussion of global fluctuations in the overall price level in Milton Friedman and Anna

Jacobson Schwartz, A Monetary History of the United States, 1867-1960, (Princeton: Princeton University Press,

1963). 89

Maximum retail prices were controlled for wheaten bread, beef, mutton and rice from 1930 onwards. See the

section for the “average retail prices of the chief staple articles of use or consumption, Bathurst”, in Blue Book

for the Colony of The Gambia (Government Printing Office): issues of 1930-1945.

55

205. The trade depression has resulted in a decrease in the spending power of the population

generally but this the main has caused little hardship in a country where land for farming is

plentiful and the essentials of life are obtainable with the minimum of labour. The decrease in

spending power has been largely set off by decrease in the price of native foodstuffs. While it

may be said that the standard of living has not been noticeably affected by the general

depression, the amount of money in circulation and the buried resources of the family unit has

shrunk almost below pre-war level.90

This goes against the widely held view that the African population suffered greatly from the

global economic crisis. Richard J. Reid, for example, maintains that:

The 1930s witnessed a collapse in wages all across the continent, too; wage labour suffered in

the mining economy, on white-owned plantations, and in the urban centres, to which Africans

increasingly drifted in search of work. (…) The impact of declining wages was to some extent

offset by a corresponding fall in the cost of living, but this was hardly significant in real terms.

In reality, the 1930s was a period of genuine hardship for millions of Africans and large

numbers of poor whites, and the fall in living standards was not reversed until the second half of

the 1940s.91

Indisputably, the 1930s were a period in which a part of the native population

experienced economic hardship. These real wage figures, for example, do not tell us whether a

large part of the African wage-workers might have suffered from the economic crisis through

unemployment. However, the problem with Reid’s perspective on this period in colonial

Africa is that he offers no empirical evidence to support this claim. Moreover, he seems to fall

into the pitfall of generalizing trends that may count for certain African regions to the entire

continent. Our empirical analysis, in contrast, shows that intra-African differentiation and

further nuance are necessary when making such wide-ranging claims.

Nonetheless, the different real wage trajectories we have observed for British Africa, and most

notably the contrast between the East and West colonies, do beg the question of what general

causal factors we should attribute to these divergent outcomes. Why did purchasing power

increase significantly, and to levels far above subsistence level, for wage labourers in West

Africa and Uganda? And why do we not see a similar development for their counterparts in

90

Gold Coast, Annual Report on the Social and Economic Progress of the People of the Gold Coast, 1931-1932,

“VIII Wages and Cost of Living”, (London: His Majesty’s Stationary Office, 1933): 44. 91

Reid, A History of Modern Africa, 225.

56

Kenya and Nyasaland? Partially, this ‘East-West’ real wage disparity is a reflection of

different degrees of economic dynamism. The comparative per capita figures for government

revenue and exports, underline that Nyasaland is indubitably the poorest colony in our

selected sample.92

However, a similar argument of a stagnant economy cannot explain the real

wage gap between Kenya and the other colonies. The Kenyan per capita trade value and fiscal

revenue level greatly exceeded that of Nigeria, Sierra Leone and Uganda.93

As such, the

comparatively low real wage levels and stagnant trend vis-à-vis West Africa and Uganda must

have been the outcome of certain distributive arrangements.

The most compelling argument about these real wage discrepancies points towards

different types of labour market institutions that operated in Kenya and the West African

colonies, these being more coercive in the former and more liberal in the latter. Two elements

contributed to these differences in labour market institutions. First, and as will also be

addressed more elaborately in de last section of this chapter, concerns the fiscal arrangements

of the colonies. Direct native taxation played a more important role in Kenyan colonial fiscal

policy than in the West African ones. A more coercive form of head or hut taxes could impact

labour market relations by ‘pushing’ the native population on the wage labour market, which

in turn, artificially reduced the equilibrium price of labour by enlarging its supply. However,

the fiscal system of Uganda shows much greater resemblance to that of Kenya than to those of

the West African colonies, and, as such, the ‘coercive taxes argument’ cannot account for the

Kenyan-Ugandan real wage disparity.

The second, and maybe even more important, factor shaping labour market institutions

is that of land tenure regimes. As pointed out by Austin, in the Gold Coast, the envisioned

reforms that would commercialize land tenure rules were never implemented by the colonial

administration, and as such left the indigenous system fairly intact.94

Similarly, Bowden and

Mosley demonstrate that the native Ugandan land tenure regime, in contrast to the Kenyan

one, remained fairly unaltered in the colonial period. No land was reserved in the ‘peasant

export colonies’, such as Uganda, Ghana and Nigeria, for European settlers. In the British

‘settler colonies’ of Kenya, in contrast, 7 percent of the highest quality of land was allocated

to Europeans.95

The high level of land alienation in Kenya entailed that a comparatively large

share of the native population was pushed of their land and became dependent on the (wage)

92

See: Frankema “Raising Revenue in the British Empire” 2009; and “Toiling for Prisons or Hospitals?”, 2010 93

Ibid. 94

See: Gareth Austin, Labour, Land and Capital in Ghana: From Slavery to Free Labour in Asante, 1807–

1956. (University of Rochester Press: Rochester, NY. 2005), and “The Reversal of Fortune Thesis”, 2008: 1020. 95

Bowden and Mosley, see Table 1, p. 19

57

labour market for subsistence, driving down the wage levels again as a result of excess supply.

Therefore, the combination of a coercive fiscal system with a land tenure regime that was

strongly biased in favour of the colonizer, contributed to the development of much more

‘extractive’ labour market institutions in Kenya than in the other colonies selected in this

study.

3.3.3. African Real Wages in a Comparative Perspective

On the basis of the time-series we have constructed for British Africa, it would be interesting

to examine how these real wage movements and levels compare to other parts of the world.

We can embark on such cross-continental comparative endeavours in two ways. First, by

comparing our real wage indices with those of Williamson for Asia and Latin America.

Second, by placing the African subsistence ratios next to those of Allen for pre-industrial

Europe and Asia. For the first objective it is necessary to translate our subsistence ratio into an

index, as Williamson, unfortunately, does not offer any nominal data figures. For a number of

reasons, all of the indices, including those of Williamson, have been set at 100 for the year

1910. First, we want our indexical year both to fall in a period of relative political-economic

stability, and to reflect a certain routine in data reporting in the Blue Books. At the close of

the first decade of the twentieth century, we can clearly observe that the statistical records

have become fairly systematic for all of the colonies incorporated in this study. From the full

time-series it was possible to derive that 1910 was a relatively representative year; one in

which nominal wage and price levels did not reflect any outlier-type of behaviour. Only for

Gambia and Gold Coast information was lacking for 1910, and the real wage indices were

accordingly set at 100 for the year closest to it, which was 1904. This, however, should not

pose any severe problems for the overall comparability of the real wage indices, as, for most

countries, wages and prices did not fluctuate much in this period.

In figures 3.10 and 3.11 above, next to our African colonies, the comparative annual

percentage changes in real wages are depicted for eight Asian, and six Latin American

countries. Graph 3.10 illustrates that both in Latin America and SSA, the 1920s marked a

decade in which the average labourer experienced a significant increase in purchasing power.

As seen for Africa, part of the economic gains of the 1920s made up for the real wage losses

of the WWI period. The Williamson data reveal that, with the exception of Cuba, the war-

years had been a period of financial setback for Latin American labourers as well, and that

hence, the strongly rising real wages of the post-WWI years can be explained as a form of

58

catching-up growth. The labouring class in Asia, in contrast, seems on the one hand to have

suffered less from the economic mayhem surrounding the war, but on the other, not have

shared in the gains of the 1920s either. The only exceptions to this trend are the British and

Dutch colonies.

Figure 3.11 shows that, in terms of purchasing power, all of Latin America was hit

hard by the economic collapse of the 1930s. For most labourers on this continent, some of the

gains of the 1920s were lost again in the ensuing decade. This declining trend contrasts

sharply with the rising one of British Africa and some of the Asian colonies. There are some

possible explanations – or combinations thereof – that could account for this comparatively

strong performance of Africa in the 1930s. One clarification could be that these parts of the

world were less integrated in the world economy than Latin America, and that they were,

hence, less hit by the global economic backlash. Another explanation might be that Africa,

where in most colonies prices continued to decline at a faster pace than the nominal wage

rates in the 1930s, reaped the benefits of long-term investments by the colonial administration

to increase agricultural yields. Annual Reports on the Social and Economic Progress of the

People of various colonies indeed point towards such pro-active agricultural meddling by the

administration:

134. The Agricultural Department is working to increase both acreage and yield of all crops in

the Northern Provinces, including food stuffs, cotton and groundnuts by the use of cattle for

ploughing and the making of farm-yard manure. This system is known as ‘mixed farming’. A

family with a pair of cattle and a plough can cultivate four or five times the area of crops that

they can cultivate by hand. At the same time, owing to the fact that a very little manure greatly

increases the yield in that part of the country, the man who uses farm-yard manure gets much

heavier yields than the man who tills the soil by hand and, keeping no cattle, has manure.96

Instructional work and the improvement of crops and produce continue successfully through the

efforts of the Agricultural Officers and produce inspectorate served closely by the advisory

work (economics, entomology, and mycology) under guidance from the Headquarters of the

Department of Agriculture. Among the more important features of the work were included the

extension of the growing swamp of rice in inland swamps, especially in the Southern Province,

oil palm and coffee planting, improvement and increased production of piassava, raffia

production, and cultivation with the plough (in the Northern Province).97

96

The Colony and Protectorate of Nigeria, Annual Report on the Social and Economic Progress of the People of

Nigeria for 1938, “VI Natural Resources”, (London: His Majesty’s Stationary Office, 1939): 43. 97

Sierra Leone, Annual Report on the Social and Economic Progress of the People of Sierra Leone, 1932, “VI

Production”, (London: His Majesty’s Stationary Office, 1933): 24.

59

Figure 3.10: Comparative Annual Percentage Changes in Real Wages Development for

Asia, Latin America and British Africa, 1920s

Sources: Williamson, 1998; Blue Books.

Figure 3.11: Comparative Annual Percentage Changes in Real Wages Development for

Asia, Latin America and British Africa, 1930s

Source: Williamson, 1998; Blue Books.

-4

-2

0

2

4

6

8

10 B

urm

a

India

Java

Phil

lipin

es

Tai

wan

Japan

Kore

a

Th

aila

nd

Arg

enti

na

Bra

zil

Colo

mbia

Cuba

Mex

ico

Uru

guay

The

Gam

bia

The

Gold

Coas

t

Ken

ya

Mau

riti

us

Nig

eria

Nyas

alan

d

Sie

rra

Leo

ne

Ugan

da

-4

-2

0

2

4

6

8

10

Burm

a

India

Java

Phil

lipin

es

Tai

wan

Japan

Kore

a

Thai

land

Arg

enti

na

Bra

zil

Colo

mbia

Cuba

Mex

ico

Uru

guay

The

Gam

bia

The

Gold

Coas

t

Ken

ya

Mau

riti

us

Nig

eria

Nyas

alan

d

Sie

rra

Leo

ne

Ugan

da

60

Alternatively, it may have been the case that contemporary government policy aimed at

safeguarding the real wage level, and that through market intervention either prices were kept

at an artificially low level, or, vice-versa, nominal wages at a non-equilibrium high rate.

Looking at the price observations in the Blue Books generates indeed some supporting

evidence for this last hypothesis. In the statistical records of the early 1930s for Gambia it is

stated that for the main food crops consumed by the African population, the “maximum retail

price was controlled by Proclamation.”98

One other element is interesting to observe here as well. It appears as if real wage

levels of labourers in the colonial territories of the more ‘advanced’ economic powers, Burma

(U.K.), India (U.K.), Java (NL), and the Phillipines (U.S.), was much better ‘protected’ than

that of the Japanese colony Taiwan, and the far majority of the Asian and Latin American

non-colonial states. The only exceptions to this pattern are Thailand and Argentina. Evidently,

our sample is somewhat limited in size to derive strong general conclusions from this.

Unfortunately, similar wage and price time-series are not yet available for all world regions to

see whether this observed pattern is consistent throughout the world. Evidently, it is beyond

the scope of this study to provide for a sound causal explanation for this phenomenon. As

such, we will have to content ourselves with merely highlighting these general differences in

real wage fluctuations between the different continents. Nonetheless, such observations do

point out again that we are still in a very initial stage when it comes to unravelling, comparing

and interpreting economic phenomena in the colonial period.

For the second objective, the subsistence ratios for British West and East Africa have been

plotted in graphs 3.12 and 3.13, which can be found on the next two pages, together with the

ratios by Allen et. al. for four pre-industrial European cities, (London, Amsterdam, Leipzig,

and Milan in figure 3.12) and four Asian cities Suzhou, Beijing, Canton and Kyoto/Tokyo in

figure 3.13).99

Such schematic representations facilitate comparative observations on the

global evolution of living standards. Regarding the European capitals incorporated in these

graphs, the most remarkable trend that can be observed is the comparatively low real wage

level in Milan vis-à-vis London, Amsterdam and Leipzig. As pointed out by Allen, by the end

of the nineteenth century, these low wage rates were “barely enough to purchase the

98

Maximum retail prices were controlled for wheaten bread, beef, mutton and rice from 1930 onwards. See the

section for the “average retail prices of the chief staple articles of use or consumption, Bathurst”, in Blue Book

for the Colony of The Gambia (Government Printing Office): issues of 1930-1945. 99

R. C. Allen, J.-P. Bassino, et al., “Wages, prices, and living standards in China, 1738-1925: in comparison

with Europe, Japan, and India,” Economic History Review, 2009 (forthcoming).

Fig

ure

3.1

2:

Su

bsi

sten

ce r

ati

o f

or

ind

ust

ria

l la

bo

ure

rs i

n v

ari

ou

s E

uro

pea

n c

itie

s, M

au

riti

us,

Sie

rra

Leo

ne,

Ug

an

da

an

d N

ya

sala

nd

, 1

73

7-1

93

8

S

ou

rce:

No

n-A

fric

an

ra

tio

s d

eriv

ed f

rom

All

en,

20

09

; A

fric

an

ra

tio

s fr

om

Co

lon

ial

Blu

e B

oo

ks

0

1

2

3

4

5

6

7

8

9

1737

1747

1757

1767

1777

1787

1797

1807

1817

1827

1837

1847

1857

1867

1877

1887

1897

1907

1917

1927

1937

London

Am

ster

dam

L

eipzi

g

Mil

an

Port

St.

Louis

(M

auri

tius)

F

reet

ow

n (

Sie

rra

Leo

ne)

K

ampal

a (U

gan

da)

Z

om

ba

(Nyas

alan

d)

Fig

ure

3.1

3:

Su

bsi

sten

ce r

ati

o f

or

ind

ust

ria

l la

bo

ure

rs i

n v

ari

ou

s A

sia

n c

itie

s, G

old

Co

ast

, N

iger

ia,

Ken

ya

, a

nd

Ga

mb

ia,

17

37

-19

38

S

ou

rce:

No

n-A

fric

an

ra

tio

s d

eriv

ed f

rom

All

en,

20

09

; A

fric

an

ra

tio

s fr

om

Co

lon

ial

Blu

e B

oo

ks

0

1

2

3

4

5

6

7

8

9

1737

1747

1757

1767

1777

1787

1797

1807

1817

1827

1837

1847

1857

1867

1877

1887

1897

1907

1917

1927

1937

Suzh

ou

Bej

ing

Can

ton

Kyoto

/Tokyo

Acc

ra (

Gold

Coas

t)

Lag

os

(Nig

eria

) N

airo

bi

(Ken

ya)

B

athurs

t (G

amb

ia)

63

physiological minimum” or, at worst, “not even quite enough to buy that – the meager

earnings of the wife or the garden produce of a scrap of land were necessary for family

survival.”100

With respect to Asia, one has to conclude that from the mid-eighteenth century

onwards absolute purchasing power was more or less at a similar level as that of their Italian

counterparts.

The results obtained for British Africa can now be embedded in the long-run pattern

that is available for Europe and Asia. From the graphs above it becomes evident that the

subsistence ratio in late nineteenth- and early twentieth-century British Africa, with the

exception of Nyasaland, was well above that of Asia and certain parts of Europe a century

earlier. From a long-run perspective the results found for British Africa are not exceptionally

high. It is not implausible that the subsistence ratio in these colonies was at a similar level of

Early Modern Europe and Asia, when these parts of the world experienced a period of

enormous economic dynamism.101

Additionally, displaying the ratios in such a comparative

manner highlights again the rapid increase in living standards in colonial West Africa and

Uganda. Additionally, on the basis of the rural-urban wage gap of table 3.2, we can even draw

an inference that, apart for Nyasaland, if we would have substituted the industrial wages for

agricultural ones, we still would not have found a subsistence ratio smaller than 1.0.

Moreover, nominal wage rates between the urban and rural wages seem to converge over the

time-span covered, suggesting that any increases in purchasing power must have been even

stronger for agricultural wage labourers.

Nonetheless, in some respect, such conclusions are slightly premature, as the taxation

burden has not yet been taken into account. In light of AJR’s (disputed) claim that coercive

colonial fiscal policies were highly ‘extractive’ in the non-settler societies, one can wonder

how much of the nominal wage income the native population had to hand over to the state.

And, the important implication of that for this study, how did this affect the living standards in

the colonial era? In order to create as complete a picture as possible for the development of

purchasing power in British colonial Africa, it is thus necessary to incorporate the impact of

‘native taxes’ in our analysis. If AJR are right that colonial taxes were indeed excessively high

– or even extractive – with respect to the real wage level of the population, this should be

reflected in the outcome of such an empirical examination. We will turn to this question in the

next section.

100

Allen, The British Industrial Revolution, 40. 101

Note that figures 3.12 and 3.13, for graphical reasons, only depict the period 1737-1938. We do have some

insights in the levels of the subsistence ratios before 1737, however, and these suggest that ratios around 3.0 and

4.0 were reached in various European and Asian cities. See: Allen, The British Industrial Revolution, 34.

64

3.3.4. Real Wages and Taxation Pressure

All states depend on the collection of taxation revenues for their existence. Taxes are

necessary to secure domestic law and order, to defend the integrity of the territorial

boundaries in the international arena, to finance investments in long-term economic goods,

such as infrastructure and education, and to build and maintain the overall institutional

framework of the state, including the specification and protection of property rights regimes.

British colonial African states were no exception in this matter. However, this does not entail

that the manner or extent to which the British were able to raise fiscal revenues was identical

for each of the territories. In contrast, there was great cross-colonial variation in terms of the

taxation system in SSA, as these were mainly shaped by local circumstances. This section sets

out to do two interrelated things. First, a closer look will be taken at the different levels of

taxation incidence as presented by Frankema, which we can complement with a full time-

series. As Frankema to a certain extent also extends his findings to rural wage labourers, this

section will have a more explicit incorporation of our complete series for agricultural labour

as well. Second, we will extend this analysis by decomposing the category of ‘fiscal revenue’

into ‘direct’ and ‘indirect’ revenues. Combining these observations with the wage and price

levels as presented in the previous section, allows for an even more detailed picture of the

actual standards of living under colonial rule. On the basis of these insights, we will try to

further specify the degree to which the native population actually carried the taxation burden,

and what impact this had on their overall purchasing power.

The African colonial tax systems have frequently been perceived as highly extractive

in nature; as mechanisms through which unconstrained colonial powers could squeeze

revenues out of the native population; and as ones that had little regard for the consequences

of such fiscal extraction on living standards for these groups. Increasingly, such allegations

have been considered devoid of strong empirical foundations. As has been discussed already

in chapter 2, recent research into the comparative tax burden in the British Empire suggests

that there is no evidence that the African states were taxed more ‘excessively’ than other

British colonial territories. Moreover, from a more theoretical perspective, such perceptions

are problematic as well. Extractive fiscal institutions assume a near perfect control on behalf

of the colonial power over the territory and its inhabitants. This was certainly not the case for

the sparsely inhabited colonies in tropical Africa. Frankema draws attention to the fact that

levying taxes required taking the population’s response into account. As such, a lower tax

burden, for example, could provide for a “more stable political economic equilibrium” which

65

in turn prevented colonial administrations from having to deal with social upheavals and

political turmoil.102

Clearly, there are a multitude of reasons that make further research into the actual

workings and diversity of colonial tax systems a worthwhile undertaking. With respect to the

countries selected for this study it makes sense to first distinguish between different types of

government income. As this work partially builds upon and complements Frankema’s study, a

similar distinction between ‘fiscal’ and ‘non-fiscal’ revenues will be maintained in the first

part of this section. The Blue Books facilitate such a distinction, as detailed accounts of the

various types of government resources are provided in the annual revenue and expenditure

reports. Moreover, the standardized manner in which these types of resources have been

categorized, make these statistical records very suitable for cross-colonial comparisons. A

wide selection of revenues has been incorporated in the category of ‘fiscal’ revenues, such as

direct taxes – the hut and poll taxes, income taxes, and taxation of landownership – and

indirect taxes – the custom duties, excises and sale taxes.

Following from this, Frankema has been able to calculate both the levels for per capita

Gross Public Revenue (GPR) and per capita taxation incidence.103

Subsequently, by taking the

nominal wage rates of unskilled urban labour, he provided a cross-colonial comparison of

how many days of labour it took across the Empire to meet the per capita taxation obligation.

Evidently, to derive per capita levels, one has to rely upon records for population size. As has

already been discussed in the previous chapter, this is by no means an unproblematic

undertaking. It has been widely agreed upon that the population estimates for British colonial

Africa are probably underestimations of the actual population size. Nonetheless, despite the

inherent shortcomings of the population data, there is a good reason to believe that these

figures can be used for the purpose of examining per capita taxation incidence. The share of

the population that is not reflected in the census is most likely also not reflected in any of the

accounts of taxation revenues either. In fact, one of the main reasons to have a population

count was to ascertain the potential tax base in the colonies. Therefore, the incomplete

population estimates as reported in the Blue Books can even be considered as a better

alternative than the actual population size. In order to be as accurate as possible though, only

the census years have been taken from the Blue Books, and the years in between have been

derived through interpolation.

102

Frankema, “Raising Revenue in the British Empire”, 6. 103

Note that GPR is the total amount of government revenue, excluding imperial grants.

66

There are two aspects in which this study aims complement the findings established by

Frankema. The first one, which will be discussed in this sub-section, regards the fact that he

has based himself on three benchmark years; 1911, 1925 and 1937 respectively. On the whole,

the use of a number of representative benchmark years is widely considered as a reasonably

solid method to establish general trends. The years that were selected by Frankema are in

many respects well chosen. Evidently, the years of WWI, the economic instability of the early

1920s and 1930s would not have been very suitable for such an endeavour. Nonetheless,

having full time-series to our disposal now, we can do four things. First, the year-to-year

nominal wage data can tell us something about the suitability of both the years and the

categories of unskilled labour as chosen by Frankema. It is not unusual that the manner of

documenting changed over time in the Blue Books, and hence, that, not having all years to

one’s disposal, the category for 1911 does not match up that well with that of 1925. Secondly,

even if these nominal wage data fit well into the longer patterns, we would like to know

whether the level of taxation incidence of that year does not stand out too much from the

overall pattern of that decade. As custom revenues are included in the total amount of fiscal

revenue, it can very well be that in a trade-opportune year, the level of taxation incidence was

slightly on the high side and, therefore, not the best representation for the overall trend of that

decade. Thirdly, by looking at the complete time-series one can easily detect strong

fluctuations, and the impact of economically harder years can be observed. Finally, with the

new wage series for agricultural unskilled labour, which are generally lower than that for

industrial labour, the levels of taxation incidence can be compared more systematically to

both that for industrial labour and throughout the Empire as a whole.

As can be derived from figures 3.3 and 3.4 in appendix II, depicting the per capita

taxation incidence time-series, the fiscal pressure for unskilled labourers augmented in the

course of the colonial period. This in itself is not that surprising, and certainly not inconsistent

with the findings of Frankema. In most of British Africa, the institutional infrastructure

through which the state could levy and collect taxes in a relatively effective manner, was not

in place until after WWI and grew over the time-span covered. Moreover, as real wages

increased, there was a stronger basis for an increase in fiscal demands. However what is

remarkable, is that the level of taxation incidence was decidedly the highest for Mauritian

agricultural unskilled labourers. In many respects, Mauritius, with its long colonial history,

and its ‘miraculous’ post-colonial growth record, has been considered an absolute outlier in

British Africa. This trend is certainly discernable in the rural sector, but when one takes a look

67

at the taxation incidence for industrial unskilled labour, the Gambia, the Gold Coast and

Kenya seem to have the highest rates.

Frankema does take into account that there may be some disparities in terms of fiscal

pressure between rural and urban labourers. After taking a random sample, he does not find

any evidence that this may impede the overall argument. Hence, he concludes that “[W]hen

drawing up the balance it seems that substituting urban for rural wage estimates would not lift

average tax incidence in the peripheral colonies to levels exceeding the imperial average, safe

for a few exceptions.”104

At first sight, this indeed seems to be the case for most of the

countries in our sample, for both rural and urban wage labourers. However, apart from the

Mauritian case, a few exceptions are indeed there, that can now be distilled. Agricultural

labourers in Kenya suffered from a higher level of taxation incidence. Table 3.5 below shows

the average level of taxation incidence per period and may shed more light on this. From this

table it follows that this difference is in itself not that profound, but if we would look for all of

the period 1930-1938, the fiscal pressure on rural labourers is more than 25 percent higher

than the imperial average. Gambia too, comes close to this pattern. As we do not know what

the imperial average for that entire period is, no strong conclusions can yet be drawn from

this. However, it seems that compared to the other colonies in this sample, these countries do

diverge from the overall trend in that decade. On the whole the table and the graphic time-

series demonstrate that at least for a couple of countries, the fiscal pressure for rural labourers

comes close to the imperial average.

Table 3.5: Average per capita taxation incidence per period for agricultural and industrial unskilled labour

in British Africa (expressed in days of work per year)

COUNTRY 1900-10 1920-30 1930-1940

Rural Urban 1911 Rural Urban 1925 Rural Urban 1937

Gambia 6.9 6.0 7.8 11.6 9.5 9.5 18.5 13.2 15.7

Gold Coast 6,8 6.8 10.3 13.4 13.7 21.8 13.6 11.8 19.6

Kenya 4.5 4.6 5.6 19.8 18.3 13.3 25.5 16.9 15.4

Mauritius105

21.8 9.0 13.9 25.0 13.1 21.4 40.1 13.6 25.6

Nigeria 3.1 5.7 2.5 3.7 7.4 4.4 6.3

Nyasaland 7.6 5.3 7.2 10.5 8.8 13.9 16.1 7.8 15.4

Sierra Leone 5.4 4.2 4.0 7.3 6.2 8.0 9.9 6.8 10.2

Uganda 4.2 1.6 4.8 9.8 5.2 9.4 17.3 9.7 22.3

Imperial Av. 13.6 18.9 21.2

Sources: Colonial Blue Books; observations for 1911, 1925,

1937 and the imperial average have been taken from Frankema, 2009.

104

The imperial average for the year 1911 is 13.6, for 1925 18.9 and for 1937 21.2. These numbers have been

based on the taxation incidence for the United Kingdom, the Dominions, British Asia and the Pacific, the British

West Indies, the Mediterranean, and British Africa. See: Frankema, “Raising Revenue in the British Empire”, 18. 105

It has to be kept in mind that the industrial wages refer to skilled labour.

68

With respect to Kenya, a possible explanation is that, in contrast to other East African

countries, this colony developed a dynamic economy over the time-span covered, one that

both drew on, and was further stimulated by a significant amount of ‘skilled’ Asian and

British settlers. Evidently, with a higher level of income at the disposal of these groups, their

relative share in the fiscal revenue pot was larger, and could, hence, slightly raise the overall

estimations for the native taxation burden. As pointed out by Frankema, colonial

administrations often maintained different taxation rates for a variety of native groups, taking

their income position into account, a policy that was particularly applied in colonial Kenya.106

Nonetheless, the fact remains, that this manner of looking at taxation incidence does not allow

further differentiation between levels of fiscal obligations. For the purpose of conducting a

widespread cross-Empire comparative study, this is not that much of a problem. However, as

will be discussed more elaborately in the next section, if one wants to examine the impact of

the taxation obligation on the overall income and living standards of the native population,

other approaches may be required.

Apart from the incorporation of the taxation incidence for rural wage labourers and the

presentation of a full time-series, this study sets out to complement Frankema’s work in

another respect. As pointed out before, what constitutes ‘fiscal’ revenue in the latter’s

approach includes both custom revenues and direct forms of taxation. The implicit

assumption, here, is that either way, through direct or indirect forms of taxation (such as the

customs duties levied on consumer goods), it was in the end the African colonial population

that paid them. This assumption is useful when one wants to make a large cross-colonial

comparison between different levels of taxation incidence in the British Empire, as conducted

by Frankema. However, if one wants to make assessments about the impact of taxation on

overall living standards, this is slightly more problematic. How much of these custom

revenues were in the end paid by native unskilled wage-labourers? Evidently, the total amount

of custom revenues entails a wide variety of duties laid upon ‘luxury’ consumer goods as

well, goods that were only purchased by a (often non-native) more wealthy urban middle- and

upper class. Similarly, the export duties were to a great extent levied upon entrepreneurs, and

on the foreign consumers (mainly British). It is therefore incredibly difficult to ascertain what

the total amount of taxes was that the majority of the native wageworkers had to pay. How

then, can we make solid estimations about the impact of the government’s fiscal demands on

the purchasing power of the average wage labourer?

106

Frankema, “Raising Revenue in the British Empire”, 23.

69

The extent to which the administration’s budget was dependent on direct or indirect

forms of taxation resources, reveals strongly divergent patterns between the differently

located British colonies. As can be seen in figure 3.14 below, at the turn of the twentieth

century, the colonial territories in West Africa were able to rely to a great extent on revenues

resulting from trade, whereas the government’s budget of their East African counterparts was

more based on direct forms of taxation. In the coastal regions of Gambia, Sierra Leone and

Gold Coast, a near 80 to 90 percent of the total government revenues came from custom

duties, whereas in the landlocked countries of Kenya, Nyasaland and Uganda, this component

constituted less than 40 percent. Evidently, geographical endowments, and the opportunities

for commerce play an important role in this divergent pattern. However, as will be discussed

later in this section, the ability of the colonial administration to levy and collect other forms of

taxation also explains an important part here. Nonetheless, what can be derived from graph

3.5 as well is that, over time, there seems to be some convergence in the role that custom

revenues play in the overall government budget.

Figure 3.14: Customs revenue as share of GPR for British Colonial Africa, 1882-1945

Sources: Colonial Blue Books

0

10

20

30

40

50

60

70

80

90

100

1882

1885

1888

1891

1894

1897

1900

1903

1906

1909

1912

1915

1918

1921

1924

1927

1930

1933

1936

1939

1942

1945

Per

cen

tage

Year

Gambia

Gold Coast

Kenya

Mauritius

Nigeria

Nyasaland

Sierra Leone

Uganda

70

Indisputably, the native population paid a share of these trade tariffs through the

purchase of, for example, imported grains. However, as can be derived from the import and

export balance, such food crops only made up a small share of the total amount of imported

merchandise. A significant amount of ‘luxury’ goods was imported – raw materials, liquor,

tobacco, and manufactured items – which were mainly consumed by the European settlers.107

It would, therefore, be interesting to get an impression of what the relative share of the duties

on imported grain were vis-à-vis the total amount of import revenues. For the year 1920 in the

Gold Coast, for example, the total amount of custom revenue received from the import of rice,

beef and pork, flour and sugar together, was less than 1 percent of the total amount of the total

amount of import duties.108

Even in Mauritius, this share did not exceed 7 percent for the year

1921.109

Even if we would include duties paid on textiles, by the far the largest export product

of Britain to its colonies, this percentage does not change significantly. In the cases mentioned

above, the share would augment to 2 and 9.5 percent respectively.110

It should also be taken

into account that the imported textiles could not be taxed too heavily either, as an indigenous

market would be able to compete with these products. After all, a large part of the raw

materials for the British cotton industry were produced in Africa.111

All in all, these numbers

give us very little reason to believe that most of the fiscal revenue came from the native

population. It makes sense to take a closer look at the direct forms of taxation that were levied

upon the indigenous colonial inhabitants, such as the ‘hut’, ‘head’ or ‘poll’ taxes.

Generally, these taxes applied to all native adult males. The implementation of the so-

called ‘native’ taxes were indispensible for the British to display the legitimacy of their rule,

to monetize the colonial subsistence economy rapidly, and, hence, spur the provision of wage

107

In the Blue Books, a distinction is made between different classes of imported merchandise. Class I consists

of ‘Food, Drink and Tobacco”; Class II of ‘Raw Materials and Articles mainly Unmanufactured’; Class III of

‘Articles wholly or mainly Manufactured’; and Class IV of ‘Miscellaneous and Unclassified’. 108

Colonial Blue Book for the Colony of the Gold Coast, 1920, section 22, p. 44. See table No. 8: ‘Summary of

the Amount of Customs Revenue received during the Five Years ended 31st December 1916-1920, distinguishing

the Amounts derived from Principle Classes of Merchandise’. 109

Colonial Blue Book for the Colony of Mauritius, 1925, section V8. See table No. 8: ‘Summary of the Amount

of Customs Revenue received during the Five Years 1921-1925 distinguishing the Amounts derived from

Principle Classes of Merchandise’. 110

These values have been derived from the annual trade reports of the United Kingdom. The absolute value of

the export value of cotton has been taken, to which an additional 20 percent has been added to account for

transportation costs. Based on a 5 percent custom duty rate, it was possible to derive how large the share of

duties on cotton must have been vis-à-vis total custom revenues. See: Annual Statement of the Trade of the

United Kingdom with Foreign Countries and British Possesions for the Years 1920 and 1921. London: Her

Majesty’s Stationary Office. 111

Steve Onyeiwu, “Deceived by African Cotton: The British Cotton Growing Association and the Demise of the

Lancashire Textile Industry”, African Economic History 28 (2000), 89-121.

71

labour in the land-abundant, but labour-scarce African continent.112

In British West Africa,

native taxes never came to play a significant role in the total colonial budget. Partially, this

can be attributed to the large sums of custom revenues, which provided a viable alternative to

the ‘hut’ or ‘head’ taxes. However, there were also political-strategic considerations that

played a role in West Africa. The resistance to colonial rule was much greater in the Western

colonies of British Africa than in the Eastern parts. In Sierra Leone, the introduction of a

native tax triggered the outbreak of the ‘Hut Tax War’ in 1898, and it took the military

intervention of the British imperial army to restore political order. Clearly, the cost of

imposing a native tax was high here. In the end, it could only be implemented by allowing

local chiefs both a great say in the taxation levels and by placing them in charge of collecting

the revenues.113

One of the results of the ‘Hut Tax War’ was that the imposition of a head tax

was never introduced, or only at a very late stage, in the Gold Coast and southern Nigeria,

since the “anticipated African hostility was especially strong” in these regions.114

Variation in importance and in the level of native taxes for the colonial budget aside, it

is of interest for this study how these native taxes impacted the development of living

standards in British Africa. At first sight, this may appear like a straightforward undertaking.

One could simply divide the total amount of revenue resulting from direct taxation by the total

native adult male population (about 40 percent). However, this approach assumes that all

native adult males would pay exactly the same amount of taxes, whereas it is very unlikely

that this was the case. As mentioned before, it was not unusual that the colonial administration

differentiated in the level of taxes that had to be paid by the various native tribes. Such

reduced fiscal rates took into account the variation in income distribution among natives, and

hence ensured a better political economic equilibrium. Moreover, as native chiefs were

frequently in charge of collecting these taxes, the amount received by the government does

not reveal any amounts that tribe leaders might have put in their own pockets. There is thus

reason to believe that the overall taxation pressure was higher for urban wageworkers than for

people that lived in the more secluded hinterlands.

112

See for example: J. Herbst, States and Power in Africa. Comparative Lessons in Authority and Control,

(Princeton: Princeton University Press, 2000); Frankema, “Raising Revenue in the British Empire”, especially

pp. 22-23; and Gareth Austin, “Resources, Techniques, and Strategies South of the Sahara: Revising the Factor

Endowments Perspective on African Economic Development History”, Economic History Review 61, 2008: 587-

624. 113

See: M. Crowder and Laray Denzer, “Bai Bureh and the Sierra Leone Hut Tax War of 1898”, pp. 61-103. In:

M. Crowder, Colonial West Africa, (London: Frank Cass and Company Ltd, 1978); and Frankema, “Raising

Revenue in the British Empire”, 23. 114

Young, The African Colonial State in Comparative Perspective, 126.

72

Table 3.7: Percentage Impact of Direct per capita Taxation Pressure

on Nominal Wage Income in British Africa

COUNTRY 1900-1910 1920-1930 1930-1940

Rural Urban Rural Urban Rural Urban

Gambia -1.3% -1.1% -1.9% -1.5% -3.1% -2.3%

Gold Coast -2.0% -2.0% -1.2% -1.6% -2.3% -2.1%

Kenya -4.0% -3.9% -19.5% -18.3% -29.8% -18.1%

Mauritius -16.2% -6.2% -16.7% -8.3% -54.0% -13.0%

Nigeria -1.9% -0.9% -2.4% -1.4%

Nyasaland -9.6% -6.5% -12.1% -9.4% -12.6% -6.6%

Sierra Leone -2.2% -1.7% -2.4% -1.9% -5.2% -3.6%

Uganda -5.4% -2.1% -9.7% -4.7% -18.1% -9.2%

Sources: Colonial Blue Books

Evidently, there is no manner in which one can derive the exact impact of the fiscal

burden on the real wages. This, however, is no reason to refrain from any such undertaking.

Albeit a rough estimate, such results can still provide us with a general impression of the

overall taxation burden. Table 3.7 above shows how much one would have to correct both the

rural and urban real wage levels if taxation is taken into account. On the whole, it seems that

the impact of native hut and head taxes was rather small in West Africa. For these colonies the

amount that needed to be paid to the colonial administration remained smaller then 5 percent

until the end of the 1930s. From the Sessional Papers of Sierra Leone in 1932, we know that

increases in taxation had little impact on the standard of living for the native population:

While the cost of living for officials rose slightly under increased taxation, that of the labourers

fell substantially.115

Mauritius, and the East African colonies seem to diverge from this overall trend, these

percentages amounting up to 13.0 in Mauritius, 18.1 in Kenya, 9.4 in Nyasaland and 9.2 in

Uganda for urban labour, and even higher percentages for rural labour. In the cases of

Mauritius and Uganda, where the absolute level of the subsistence ratios was already far

above 1.0, the native population did at least have the financial carrying capacity to pay these

taxes, without facing extreme economic hardship. In Kenya and Nyasaland, however, one can

imagine that the relatively high taxation burden was at times problematic to maintain a decent

standard of living. Again, such results emphasize that comparative socio-economic research

into British Africa can reveal important intra-African variety. Most notably they seem to

115

Sierra Leone, Annual Report on the Social and Economic Progress of the People of Sierra Leone, 1932, “VIII

Wages and Cost of Living”, (London: His Majesty’s Stationary Office, 1933), 33.

73

support the idea that the native population suffered from much more ‘extractive’ labour

market institutions in the settler economies than in the peasant export economies.

3.4 Conclusion

On a general plane, new empirical research seems to point towards a better performance of the

Sub-Saharan colonial economy than scholars had previously assumed. The GDP dataset as

presented by Smits, suggests that both in terms of national and per capita output levels a

substantial degree of growth was realized during the period of colonial rule. Nonetheless,

these findings in themselves do not tell us anything about the manner in which such economic

achievements were distributed among society as a whole, and among the average native

population in particular. In order to make any general assertions about the – so frequently

alleged – ‘extractive’ nature of colonial domination, and its ensuing detrimental impact on the

continent’s long-run development trajectory, we need to know more about income distribution

and how standards of living evolved for the different native populations in this period. Did the

indigenous groups also come to benefit from these gains in national wealth? Or did standards

of living exclusively improve for the colonial rulers and their local representatives? This study

has set out to contribute to these research objectives.

Some first insights into the development of living standards in colonial Africa had

already become available. ABM presented convincing accounts of the increase in human well-

being for colonial Gold Coast and Kenya, but did not (yet) provide such information for other

regions. Smits’ aggregate average trends for SSA as a whole, both in the GDP and the caloric

intake time-series, did not reveal anything about any possible intra-African regional

differences. Frankema’s contribution gave us an impression of the taxation burden for African

(and non-African) unskilled industrial labourers in a wide selection of British colonies, and

hence allowed for comparisons both within and outside of the continent. However, albeit

suiting the purpose of this endeavour, he relied upon the nominal wage rates for three

benchmark years (1911, 1925, and 1937), thereby neither providing the benefits of a time-

series nor insights into the relative impact of the taxation incidence for deflated wages – the

real wages.

In this chapter some additions have been made to this emerging body of literature on

living standards in colonial Africa. A real wage series for both rural and urban unskilled

labour has been presented for eight countries in British Africa. These time-series

demonstrated that purchasing power in West Africa and Uganda, increased for a substantial

74

part of the native population in the course of the colonial period. Moreover, the subsistence

ratio of Allen allowed us to get an impression of the absolute level of the real wages. Through

international comparisons, it was shown that, with the exception of Nyasaland, living

standards in British Africa were well above those in pre-industrial Asia. Moreover, in terms of

real wage trends, the economic crisis of the 1930s seems to have had less of an impact in

Africa than in Latin America. Finally, a first attempt has been made to estimate the impact of

per capita taxation incidence on real income levels. From this analysis, it followed that in

most of the colonies, the taxation burden on the African population was, up until WWII,

moderate at the least. However, the lower levels of real income and the decline of these over

time in other territories, also emphasize the need to recognize intra-African variety. It seems

that different types of labour market institutions can explain, at least in part, the divergent

outcomes we have observed for the development of living standards in British Africa.

75

4. SOME REFLECTIONS ON AFRICA’S GROWTH TRAGEDY

This study has set out to contribute to our understanding of the African colonial economy,

and, on a larger plane, to its impact on the long-run growth potential of the continent. For a

long time, the literature on Africa’s poor economic growth record remained rather limited in

outlook. The more ‘proximate cause oriented’ economists focused solely on the post-colonial

economy, and perceived African growth stagnation mainly in terms of technological

shortcomings in the human and physical capital stock, impeding in turn physical capital

deepening, human capital accumulation, and productivity growth. The causal accounts that

aimed to distil the more structural barriers to growth, on the other hand, have, amongst others,

emphasized the encumbering effects of the continent’s geographical endowments, causing a

permanent comparative disadvantage in international trade. Additionally, among these ‘deep

cause’ analyses, the negative effect of the colonial period on Africa’s long-run growth

trajectory also found expression in the literature, first in the form of Dependency theory, and,

more recently, through institutional path-dependency.

Indisputably, all of these studies on the Sub Saharan development path have made

important contributions to our understanding of the proximate and ultimate causes of poverty.

However, because of the research emphasis of the former on the post-WWII period, and the

attempt of the latter to establish deeper historical roots through rather rigid forms of

econometric regression analysis, little is revealed about the actual performance of the African

economy over a medium-long term. In these respects, more in-depth, empirical economic

historical research on the performance of both the colonial and post-colonial economy has two

advantages. Firstly, such long-run analyses allow for better insights into the historical

continuity and discontinuity of African political-economies. Secondly, by neither reducing the

continent nor the time-span covered to aggregate variables, the often more case-based

economic historical approaches allow for greater scrutiny in making spatio-temporal

differentiations.

Especially in the last decade, when the ‘institutions school’ gained influence following

AJR’s agenda-setting articles, the functioning of the African colonial economy has figured

prominently in the research endeavours of economic historians. In response to the new

paradigm, dictating that in most of the non-settler societies, the colonial period was one in

which extractive, growth-impeding institutions became imbedded in the political-economy,

scholars in the field of economic history have challenged this hypothesis by presenting new

insights in matters of general and per capita GDP performance, living standards, fiscal

76

pressure, and public investment patterns. In this study, I aimed to complement this emerging

strand of literature by constructing and comparing the development of real wage levels and

taxation pressure in eight British African colonies. The contribution of this comparative

analysis with respect to the existing body of scholarly works on the colonial economy finds its

expression in the following aspects.

Firstly, apart from two case-studies and an aggregate account on caloric intake levels

in colonial SSA, little was still known about the development of living standards for a wide

array of African colonies. The full time-series that have been presented for urban and rural

real wage levels, covering the entire period of effective British hegemony, therefore, are an

important addition to the already existing literature on this topic. These real wage series,

expressed in the form of a subsistence ratio, revealed that purchasing power was well above

the critical subsistence minimum and increased in most parts of British Africa. Additionally,

even when correcting these absolute real wage levels for per capita taxation incidence, the

observed trend and level in purchasing power remained practically unaffected. This generally

rising trend, even after taking into account the small amount that was creamed off by the state,

suggests, for one, that the term ‘extractive colonial institution’ is in need of further scholarly

decomposition.

Secondly, the large number of cases selected for this study allowed for intra-African

comparisons, and, as such, room for colony-based differentiation. Such a variation-finding

comparative approach breaks with the tradition of looking at SSA as a single-entity unit, while

still taking a large share of the continent into account. Most notably, the difference in living

standards, both in trend and levels, between the colonies in West and East Africa stood out.

Gambia, the Gold Coast, Nigeria and Sierra Leone, all showed increases in the real wage

levels in the course of the colonial period. Moreover, absolute purchasing power in these

British territories was well above the minimum subsistence ratio. The East African-situated

territory of Uganda, though, showed greater resemblance to this West African pattern than to

that of its regional counterparts. The latter, Kenya and Nyasaland, seem to have suffered

rather than profited from colonial rule in terms of real wage development. Nyasaland, the

indisputable negative outlier in our sample, did not only show a declining trend, but also a

subsistence level smaller than 1.0 for most of the time-span covered. Mauritius, in contrast,

the positively outlying ‘miracle economy’ in this study, revealed little fluctuations in the real

wage level, but the comparatively high subsistence level suggests that a substantial amount of

growth was already realized before the twentieth century, and that the benefits of such an

economic expansion were felt at different levels in society. An initial causal analysis of these

77

divergent African outcomes in terms of living standards, suggests that the type of labour

market institutions in the colonies shaped the extent to which the native population was able

to profit from any economic dynamism.

Finally, this study contributed by embedding Sub Saharan Africa in the increasingly

global real wage literature. As such, it was possible to compare the development of African

purchasing power on an international plane as well. First, comparative trend analysis with the

Williamson data for Asia and Latin America showed that, after a decomposition of these time-

series in decade-based units, that real income levels of the African urban labouring class were

much more sheltered from the economic downturn of the 1930s than those of their selected

international counterparts. Additionally, through Allen’s subsistence ratio for pre-industrial

European and Asian capitals, it was possible to make global comparisons in terms of absolute

real wage levels. It was demonstrated that, notwithstanding certain intra-African variety, with

Mauritius as the high-end and Nyasaland as the low-end exceptions, the overall real wage

level in British Africa was substantially above that of Asia and increased significantly in the

colonial period. This picture of rising living standards for the average African population

British Africa, point out that there is more support for hypotheses that stress a dynamic

economy under colonial rule. The findings of this study, therefore, undermine the institutional

and geographical deterministic arguments that portray the African economy as persistently

disaster-prone. And as such, we should conclude, that from a long-run perspective, poverty is

not destiny.

The picture of the performance of the African economy over time, from the colonial period to

the present, is still far from complete. The economic growth debate could benefit greatly from

deeper insights into the years of colonial rule. The array of research questions that could give

us a better understanding on the African colonial economy seems inexhaustible. It would, for

example, be incredibly useful to distinguish what particular colonial institutions can be

considered ‘extractive’ in the first place, and, second, which ones have actually proved to be

persistent. Additionally, we still know very little the impact of the colonial period on

structural income inequality that characterizes SSA. How do, for example, long-run patterns

of wage differentiation, public investment and revenue allocation relate to this phenomenon?

Finally, the current body of literature has mainly treated Africa as a single entity. Evidently,

as pointed out by this study as well, there is a long historical legacy of intra-African regional

variation, both within one empire, and possibly between different colonial powers. In this

respect too, a research agenda that incorporates studying the colonial economy could render

78

important new insights into the structural origins of the current global economic development

gap.

The results of this comparative study thus not only contribute to an emerging body of

literature on this topic, but, also give rise to further questions, which in turn highlight that our

knowledge on the socio-economic conditions in colonial Africa is still in an exploratory stage.

This research status-quo could be considered problematic when such a ‘blind spot’ does not

merely concern the domain of scholarly debate, but also that of global economic development

strategies, one that is indisputably shaped by the research efforts of political economists,

development economists and economic historians alike. The influential publications that have

equated the colonial institutional inheritance with Africa’s poor post-colonial growth record,

have not only been highly agenda-setting within academia, but also in global policy-making

bodies such as the IMF and the World Bank. Both scholars and policy advisors have

increasingly shown an interest in the relationship between long-run economic performance

and different types of property rights regimes, with Sub-Saharan Africa being the ultimate

embodiment of an institutional growth tragedy.

From the perspective of the vast amount of research that is conducted on dismal

economic performance, it is slightly paradoxical that, in an era where we believe to know

what policies or institution are growth-conducive, sustained global economic development

remains the exception rather than the rule. In the last decades, political-economic reforms,

from democratization to market liberalization, have more often than not failed to bring about

the desired objective of long-term prosperity in the Third world. In contrast, well-intended

political or financial aid from the developed to the developing world, have at times even been

counter-productive.116

Increasingly, though, a greater awareness can be observed among

development institutions about the limitations of our understanding of the root causes of

poverty, and the ways in which hasty implementations these can cause ‘misadventures in the

tropics’. A recent study by Douglass C. North, John J. Wallis and Barry R. Weingast, in part

conducted for, and financed by the World Bank, argues that our failure to understand the

political-economic logic that operates in different types of social orders, is at the root of futile

and even disastrous development policies.117

In more basic terms, they seem to warn against a

116

Most notably here is the structural adjustment ‘shock-therapy’ of the IMF in the 1980s. Moreover, financial

aid has frequently ended up in the hands of rent-seeking elites, rather than being allocated for broad-based

growth-promoting projects. 117

According to NWW, understanding the shortcomings of development strategies requires taking into account

the role of violence. The management of violence by elite groups determines the underlying structures of a

society and, hence, its potential for political-economic development. For NWW, throughout most of (recorded)

human history, powerful individuals were able to solve the problem of violence by politically manipulating the

79

new round of exporting growth-promoting policies – or, more specifically, ‘fixing’ poor

(colonial) institutions – without a thorough comprehension of the historical trajectory of the

political-economies concerned. Economic historical research on the political-economic

continuity and discontinuity of different colonial and post-colonial African countries, could in

this respect be of great value for more effective development strategies in the future.

economy to create personal rent-based incentives that ensured a modicum of stability. In this ‘natural state’, as

they call it, the nature of a society’s social order is foremost defined by the extent to which elites can make

credible commitment to controlling violence by controlling rents. The manner in which order is produced in a

society is, therefore, at the nucleus of their analysis and distinguishes ‘natural states’ from ‘open access

societies’. Contesting the Weberian notion that the main organization in society – the state – has a monopoly on

the legitimate use of violence, NWW emphasize the dispersion of violence among elite members in the natural

state. Controlling violence, they argue, is achieved through a cooperative exertion on the part of individual

members of the ruling class, backed by exclusive economic incentives. Limiting access to economic rents is the

‘glue’ that keeps the elite coalition in equilibrium. To secure intra-elite trust, the human relationships governing

this interest-based organizational mode are inherently personal in nature. In open access societies, by contrast,

order is sustained through widespread entry into the political and economic arena, ensuring a system of ‘double

balance’ by mutually reinforcing competition. Human interaction in this social order is, moreover, characterized

by ‘impersonality’. These notions of economic-political ‘double balance’ and ‘impersonality’ have significant

implications for contemporary development strategies. NWW show how long-term development cannot merely

be attained by implementing just one of these two interdependent elements. See: Douglass C. North, J.J. Wallis

and B.R. Weingast. Violence and Social Orders: A Conceptual Framework for Interpreting Recorded Human

History. (New York: Cambridge University Press, 2009).

80

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APPENDIX I – WAGES, PRICES AND SUBSISTENCE RATIOS

18

80

1.31

53.93

19

13

18

81

1.31

53.94

19

14

18

82

1.31

54.21

19

15

18

83

1.31

54.23

19

16

18

84

1.56

64.27

19

17

18

85

1.56

64.29

19

18

18

86

1.57

64.71

19

19

18

87

1.57

64.73

19

20

18

88

1.57

64.72

19

21

1.25

51.69

18

89

1.57

64.74

19

22

1.43

59.09

18

90

1.57

64.73

19

23

2.00

82.59

18

91

1.56

64.64

19

24

1.97

81.28

18

92

1.57

64.66

19

25

1.98

81.99

18

93

1.51

62.45

19

26

1.97

81.48

18

94

1.51

62.48

19

27

1.99

82.32

18

95

1.54

63.59

19

28

2.82

116.42

18

96

1.54

63.62

19

29

2.83

116.97

18

97

1.54

63.62

19

30

3.64

150.35

18

98

1.54

63.63

19

31

3.11

128.38

18

99

2.42

100.07

19

32

1.88

77.84

19

00

2.42

100.06

19

33

19

01

2.42

100.06

19

34

1.90

78.49

19

02

2.42

100.12

19

35

2.12

87.57

19

03

2.42

100.09

19

36

2.72

112.53

19

04

2.42

100.00

19

37

2.77

114.48

19

05

19

38

2.68

110.75

19

06

19

39

2.66

109.98

19

07

19

40

2.02

83.41

19

08

19

41

19

09

19

42

2.34

96.86

19

10

19

43

1.76

72.52

19

11

19

44

1.75

72.34

19

12

19

45

1.1

.1.

No

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day w

ag

es u

rba

n l

ab

ou

r, p

rice

s of

dail

y f

am

ily

su

bsi

sten

ce b

ask

et, p

urc

ha

sin

g p

ow

er a

nd

rea

l w

ag

e in

dex

Bri

tish

Ga

mb

ia, 1

88

0-1

94

5

Pu

rch

asi

ng

po

wer

,

no

. o

f b

ask

ets

Rea

l w

ag

e in

dex

,

19

04

= 1

00

Pu

rch

asi

ng

po

wer

,

no

. of

ba

sket

s

Rea

l w

age

ind

ex,

190

4 =

100

18

80

1.03

49.23

19

13

18

81

1.03

49.24

19

14

18

82

1.04

49.49

19

15

18

83

1.04

49.50

19

16

18

84

1.35

64.27

19

17

18

85

1.35

64.29

19

18

18

86

1.36

64.71

19

19

18

87

1.36

64.73

19

20

18

88

1.36

64.72

19

21

18

89

1.36

64.74

19

22

18

90

1.36

64.73

19

23

18

91

1.36

64.64

19

24

1.61

76.63

18

92

1.36

64.66

19

25

18

93

1.31

62.45

19

26

18

94

1.31

62.48

19

27

1.99

95.05

18

95

1.33

63.59

19

28

1.99

95.06

18

96

1.33

63.62

19

29

2.00

95.50

18

97

1.33

63.62

19

30

2.57

122.76

18

98

1.33

63.63

19

31

2.64

125.79

18

99

2.10

100.07

19

32

1.78

84.75

19

00

2.10

100.06

19

33

19

01

2.10

100.06

19

34

1.55

74.00

19

02

2.10

100.12

19

35

1.73

82.56

19

03

2.10

100.09

19

36

1.67

79.57

19

04

2.10

100.00

19

37

1.96

93.47

19

05

19

38

1.90

90.42

19

06

19

39

1.88

89.80

19

07

19

40

1.43

68.11

19

08

19

41

19

09

19

42

19

10

19

43

19

11

19

44

19

12

19

45

Pu

rch

asi

ng

po

wer

,

no

. of

ba

sket

s

Rea

l w

age

ind

ex,

190

4 =

100

1.1

.2.

No

min

al

day

wa

ges

ru

ral

lab

ou

r, p

rice

s of

dail

y f

am

ily

su

bsi

sten

ce b

ask

et, p

urc

hasi

ng p

ow

er a

nd

rea

l w

ag

e in

dex

Bri

tish

Gam

bia

, 1

88

0-1

94

5

Pu

rch

asi

ng

po

wer

,

no

. o

f b

ask

ets

Rea

l w

ag

e in

dex

,

19

04

= 1

00

18

80

3.95

103.84

19

13

5.48

144.07

18

81

3.95

103.89

19

14

18

82

3.95

103.95

19

15

18

83

3.43

90.14

19

16

18

84

3.43

90.17

19

17

18

85

3.43

90.27

19

18

18

86

3.44

90.49

19

19

18

87

3.45

90.61

19

20

2.95

18

88

3.52

92.51

19

21

4.45

116.87

18

89

3.52

92.61

19

22

4.35

114.36

18

90

3.52

92.53

19

23

4.90

128.68

18

91

4.16

109.25

19

24

4.90

128.87

18

92

3.58

94.17

19

25

4.96

130.26

18

93

3.58

94.10

19

26

4.99

131.26

18

94

3.79

99.69

19

27

5.91

155.35

18

95

3.80

99.90

19

28

3.64

95.64

18

96

3.81

100.12

19

29

6.84

179.81

18

97

3.81

100.13

19

30

6.90

181.27

18

98

3.81

100.15

19

31

6.45

169.43

18

99

3.80

99.96

19

32

4.31

113.16

19

00

3.80

99.94

19

33

4.30

113.09

19

01

3.80

99.92

19

34

4.30

112.97

19

02

3.81

100.09

19

35

4.30

113.10

19

03

3.80

100.00

19

36

5.69

149.50

19

04

4.24

111.55

19

37

4.28

112.56

19

05

4.24

111.42

19

38

4.33

113.79

19

06

4.24

111.47

19

39

6.16

161.85

19

07

4.23

111.10

19

40

5.27

138.52

19

08

4.23

111.18

19

41

3.22

84.66

19

09

2.02

53.06

19

42

3.38

88.83

19

10

2.02

52.96

19

43

2.51

66.08

19

11

3.30

86.73

19

44

3.02

79.43

19

12

19

45

2.69

70.57

Pu

rch

asi

ng

po

wer

,

no

. of

ba

sket

s

Rea

l w

age

ind

ex,

190

4 =

100

1.1

.3.

No

min

al

day w

ag

es u

rba

n l

ab

ou

r, p

rice

s of

dail

y f

am

ily

su

bsi

sten

ce b

ask

et, p

urc

ha

sin

g p

ow

er a

nd

rea

l w

ag

e in

dex

Bri

tish

Go

ld C

oast

, 1

88

0-1

94

5

Pu

rch

asi

ng

po

wer

,

no

. o

f b

ask

ets

Rea

l w

ag

e in

dex

,

19

03

= 1

00

18

80

2.42

63.59

19

13

5.48

144.07

18

81

2.42

63.62

19

14

18

82

2.42

63.65

19

15

18

83

2.97

78.07

19

16

18

84

2.97

78.09

19

17

18

85

19

18

18

86

19

19

18

87

19

20

2.95

77.42

18

88

19

21

4.45

116.87

18

89

19

22

4.35

114.36

18

90

19

23

4.90

128.68

18

91

19

24

4.90

128.87

18

92

19

25

4.96

130.26

18

93

19

26

4.99

131.26

18

94

19

27

5.91

155.35

18

95

19

28

4.37

114.77

18

96

19

29

6.84

179.81

18

97

19

30

7.36

193.35

18

98

19

31

6.73

176.80

18

99

19

32

4.49

118.08

19

00

3.80

99.94

19

33

3.85

101.15

19

01

3.80

99.92

19

34

3.20

84.20

19

02

3.81

100.09

19

35

3.85

101.16

19

03

3.80

100.00

19

36

4.17

109.50

19

04

4.24

111.55

19

37

4.69

123.30

19

05

4.24

111.42

19

38

4.74

124.65

19

06

4.24

111.47

19

39

5.12

134.57

19

07

4.23

111.10

19

40

4.97

130.59

19

08

4.23

111.18

19

41

2.84

74.66

19

09

2.02

53.06

19

42

2.63

69.09

19

10

2.02

52.96

19

43

2.37

62.30

19

11

3.30

86.73

19

44

2.85

74.89

19

12

19

45

2.58

67.91

1.1

.4.

No

min

al

day

wa

ges

ru

ral

lab

ou

r, p

rice

s of

dail

y f

am

ily

su

bsi

sten

ce b

ask

et, p

urc

hasi

ng p

ow

er a

nd

rea

l w

ag

e in

dex

Bri

tish

Go

ld C

oast

, 18

80-1

94

5

Pu

rch

asi

ng

po

wer

,

no

. o

f b

ask

ets

Rea

l w

ag

e in

dex

,

19

03

= 1

00

Pu

rch

asi

ng

po

wer

,

no

. of

ba

sket

s

Rea

l w

age

ind

ex,

190

4 =

100

18

80

19

13

18

81

19

14

18

82

19

15

18

83

19

16

18

84

19

17

18

85

19

18

18

86

19

19

18

87

19

20

18

88

19

21

18

89

19

22

18

90

19

23

18

91

19

24

18

92

19

25

18

93

19

26

18

94

19

27

2.19

208.15

18

95

19

28

1.44

136.35

18

96

19

29

1.38

130.60

18

97

19

30

1.96

185.94

18

98

19

31

2.03

192.64

18

99

19

32

2.13

202.14

19

00

19

33

2.49

236.49

19

01

19

34

1.94

183.80

19

02

19

35

1.70

161.09

19

03

19

36

2.50

237.18

19

04

1.56

148.22

19

37

1.89

179.16

19

05

1.10

103.99

19

38

2.17

206.13

19

06

1.28

121.46

19

39

1.79

169.33

19

07

1.05

99.32

19

40

2.59

245.52

19

08

1.29

122.23

19

41

1.96

186.21

19

09

1.05

99.92

19

42

3.29

312.45

19

10

1.05

100.00

19

43

1.50

142.09

19

11

1.22

115.32

19

44

2.98

282.79

19

12

1.14

108.60

19

45

Pu

rch

asi

ng

po

wer

,

no

. of

ba

sket

s

Rea

l w

age

ind

ex,

191

0 =

100

1.1

.5.

No

min

al

day w

ag

es u

rba

n l

ab

ou

r, p

rice

s of

dail

y f

am

ily

su

bsi

sten

ce b

ask

et, p

urc

ha

sin

g p

ow

er a

nd

rea

l w

ag

e in

dex

Bri

tish

Ken

ya

, 19

04-1

94

4

Pu

rch

asi

ng

po

wer

,

no

. o

f b

ask

ets

Rea

l w

ag

e in

dex

,

19

10

= 1

00

18

80

19

13

2.13

162.10

18

81

19

14

1.65

125.86

18

82

19

15

1.61

122.18

18

83

19

16

18

84

19

17

18

85

19

18

18

86

19

19

18

87

19

20

18

88

19

21

18

89

19

22

18

90

19

23

18

91

19

24

18

92

19

25

18

93

19

26

18

94

19

27

1.86

141.62

18

95

19

28

1.22

92.77

18

96

19

29

1.33

101.39

18

97

19

30

1.98

150.96

18

98

19

31

1.60

121.45

18

99

19

32

1.68

127.44

19

00

19

33

1.96

149.09

19

01

19

34

1.16

88.42

19

02

19

35

1.02

77.50

19

03

19

36

1.50

114.10

19

04

19

37

1.45

110.13

19

05

1.07

81.20

19

38

1.67

126.71

19

06

1.25

94.84

19

39

1.37

104.09

19

07

1.02

77.55

19

40

1.16

88.59

19

08

1.27

96.56

19

41

1.18

89.58

19

09

1.04

78.93

19

42

1.71

130.27

19

10

1.31

100.00

19

43

0.90

68.36

19

11

1.47

111.66

19

44

1.79

136.04

19

12

1.35

102.80

19

45

Pu

rch

asi

ng

po

wer

,

no

. of

ba

sket

s

Rea

l w

age

ind

ex,

191

0 =

100

1.1

.6.

No

min

al

day

wa

ges

ru

ral

lab

ou

r, p

rice

s of

dail

y f

am

ily

su

bsi

sten

ce b

ask

et, p

urc

hasi

ng p

ow

er a

nd

rea

l w

ag

e in

dex

Bri

tish

Ken

ya

, 19

04-1

94

4

Pu

rch

asi

ng

po

wer

,

no

. o

f b

ask

ets

Rea

l w

ag

e in

dex

,

19

10

= 1

00

18

80

19

13

18

81

19

14

4.12

84.32

18

82

19

15

3.46

70.84

18

83

19

16

18

84

19

17

3.22

65.86

18

85

19

18

2.62

53.66

18

86

19

19

4.96

101.54

18

87

19

20

5.82

119.11

18

88

19

21

5.88

120.42

18

89

19

22

5.98

122.43

18

90

19

23

5.98

122.39

18

91

19

24

5.98

122.40

18

92

19

25

8.14

166.65

18

93

19

26

8.16

167.21

18

94

19

27

7.27

148.95

18

95

19

28

7.94

162.61

18

96

19

29

6.39

130.91

18

97

19

30

6.27

128.41

18

98

19

31

7.74

158.55

18

99

19

32

7.41

151.85

19

00

4.50

92.25

19

33

7.94

162.54

19

01

6.49

132.94

19

34

7.60

155.66

19

02

6.36

130.23

19

35

7.71

157.88

19

03

6.61

135.47

19

36

7.97

163.31

19

04

5.40

110.54

19

37

8.18

167.63

19

05

6.86

140.41

19

38

8.21

168.06

19

06

5.02

102.89

19

39

8.53

174.76

19

07

4.24

86.84

19

40

6.56

134.28

19

08

4.61

94.35

19

41

19

09

4.88

99.89

19

42

4.43

90.75

19

10

4.88

100.00

19

43

19

11

5.40

110.53

19

44

19

12

5.35

109.63

19

45

1.1

.7.

No

min

al

day w

ag

es u

rba

n l

ab

ou

r, p

rice

s of

dail

y f

am

ily

su

bsi

sten

ce b

ask

et, p

urc

ha

sin

g p

ow

er a

nd

rea

l w

ag

e in

dex

Bri

tish

Ma

uri

tiu

s, 1

89

9-1

94

3

Pu

rch

asi

ng

po

wer

,

no

. o

f b

ask

ets

Rea

l w

ag

e in

dex

,

19

10

= 1

00

Pu

rch

asi

ng

po

wer

,

no

. of

ba

sket

s

Rea

l w

age

ind

ex,

191

0 =

100

18

80

19

13

18

81

19

14

2.25

119.24

18

82

19

15

2.32

122.70

18

83

19

16

3.65

192.93

18

84

19

17

1.97

104.13

18

85

19

18

1.85

97.98

18

86

19

19

3.53

186.69

18

87

19

20

4.06

214.56

18

88

19

21

4.10

216.91

18

89

19

22

4.17

220.55

18

90

19

23

4.17

220.47

18

91

19

24

2.69

142.32

18

92

19

25

3.66

193.78

18

93

19

26

3.68

194.42

18

94

19

27

3.66

193.63

18

95

19

28

3.65

192.98

18

96

19

29

2.94

155.35

18

97

19

30

2.27

120.21

18

98

19

31

2.58

136.33

18

99

19

32

2.02

107.02

19

00

2.25

119.09

19

33

2.17

114.55

19

01

2.66

140.69

19

34

2.07

109.70

19

02

2.61

137.82

19

35

3.53

186.47

19

03

3.28

173.54

19

36

3.36

177.43

19

04

2.56

135.38

19

37

3.60

190.22

19

05

3.00

158.86

19

38

3.75

198.49

19

06

1.95

102.89

19

39

3.46

182.83

19

07

1.64

86.84

19

40

2.66

140.48

19

08

1.78

94.35

19

41

19

09

1.89

99.89

19

42

1.55

81.86

19

10

1.89

100.00

19

43

19

11

1.32

69.90

19

44

19

12

2.93

155.04

19

45

Pu

rch

asi

ng

po

wer

,

no

. of

ba

sket

s

Rea

l w

age

ind

ex,

191

0 =

100

1.1

.8.

No

min

al

day

wa

ges

ru

ral

lab

ou

r, p

rice

s of

dail

y f

am

ily

su

bsi

sten

ce b

ask

et, p

urc

hasi

ng p

ow

er a

nd

rea

l w

ag

e in

dex

Bri

tish

Ma

uri

tiu

s, 1

89

9-1

94

3

Pu

rch

asi

ng

po

wer

,

no

. o

f b

ask

ets

Rea

l w

ag

e in

dex

,

19

10

= 1

00

18

80

1.51

55.91

19

13

18

81

1.52

56.19

19

14

2.60

96.42

18

82

19

15

2.22

82.35

18

83

1.93

71.40

19

16

18

84

1.93

71.40

19

17

18

85

1.94

71.77

19

18

18

86

1.95

72.14

19

19

1.11

40.98

18

87

1.97

72.90

19

20

5.61

207.51

18

88

1.97

72.90

19

21

2.41

89.38

18

89

4.68

173.15

19

22

2.14

79.23

18

90

1.97

72.90

19

23

1.40

51.76

18

91

1.36

50.48

19

24

1.95

72.23

18

92

1.36

50.48

19

25

2.06

76.15

18

93

1.36

50.45

19

26

3.00

110.89

18

94

1.58

58.34

19

27

2.18

80.71

18

95

1.37

50.60

19

28

3.27

121.22

18

96

1.37

50.53

19

29

3.06

113.45

18

97

1.95

72.07

19

30

4.42

163.66

18

98

1.96

72.55

19

31

2.62

97.06

18

99

2.27

83.98

19

32

19

00

2.27

83.88

19

33

3.03

112.25

19

01

2.23

82.46

19

34

3.15

116.52

19

02

2.23

82.37

19

35

3.14

116.36

19

03

2.26

83.83

19

36

3.13

115.89

19

04

2.27

83.93

19

37

3.27

121.15

19

05

2.42

89.61

19

38

3.28

121.48

19

06

2.98

110.41

19

39

3.07

113.80

19

07

2.90

107.36

19

40

2.19

81.19

19

08

2.89

106.95

19

41

2.25

83.22

19

09

1.89

69.82

19

42

19

10

2.70

100.00

19

43

2.01

74.57

19

11

2.68

99.16

19

44

19

12

2.68

99.34

19

45

Pu

rch

asi

ng

po

wer

,

no

. of

ba

sket

s

Rea

l w

age

ind

ex,

191

0 =

100

1.1

.9.

No

min

al

day w

ag

es u

rba

n l

ab

ou

r, p

rice

s of

dail

y f

am

ily

su

bsi

sten

ce b

ask

et, p

urc

ha

sin

g p

ow

er a

nd

rea

l w

ag

e in

dex

Bri

tish

Nig

eria

, 1

880

-19

43

Pu

rch

asi

ng

po

wer

,

no

. o

f b

ask

ets

Rea

l w

ag

e in

dex

,

19

10

= 1

00

18

80

1.94

72.42

19

13

18

81

1.95

72.79

19

14

2.60

97.24

18

82

19

15

2.22

83.05

18

83

1.95

72.79

19

16

18

84

1.84

68.58

19

17

18

85

1.85

68.93

19

18

18

86

1.86

69.29

19

19

0.78

29.23

18

87

1.62

60.64

19

20

1.44

53.81

18

88

1.62

60.64

19

21

1.14

42.49

18

89

3.86

144.03

19

22

1.14

42.38

18

90

1.62

60.64

19

23

0.99

36.91

18

91

1.57

58.73

19

24

1.03

38.63

18

92

1.57

58.74

19

25

1.03

38.33

18

93

1.57

58.70

19

26

1.47

54.78

18

94

1.71

64.00

19

27

1.89

70.49

18

95

1.72

64.10

19

28

2.08

77.60

18

96

1.71

64.01

19

29

1.63

60.83

18

97

2.45

91.30

19

30

1.46

54.50

18

98

2.46

91.91

19

31

2.21

82.53

18

99

2.39

89.27

19

32

19

00

2.93

109.20

19

33

1.70

63.40

19

01

2.88

107.36

19

34

1.90

70.79

19

02

2.87

107.24

19

35

2.27

84.84

19

03

2.92

109.14

19

36

2.26

84.49

19

04

19

37

1.77

66.25

19

05

3.13

116.67

19

38

1.78

66.42

19

06

19

39

1.67

62.23

19

07

19

40

1.62

60.42

19

08

19

41

2.29

85.66

19

09

19

42

19

10

19

43

19

11

2.68

100.00

19

44

19

12

2.68

100.18

19

45

1.1

.10

. N

om

ina

l d

ay w

ag

es r

ura

l la

bou

r, p

rice

s o

f d

ail

y f

am

ily

su

bsi

sten

ce b

ask

et,

pu

rch

asi

ng p

ow

er a

nd

rea

l w

age

ind

ex

Bri

tish

Nig

eria

, 1

884

-19

43

Pu

rch

asi

ng

po

wer

,

no

. o

f b

ask

ets

Rea

l w

ag

e in

dex

,

19

11

= 1

00

Pu

rch

asi

ng

po

wer

,

no

. of

ba

sket

s

Rea

l w

age

ind

ex,

19

11

= 1

00

18

80

19

13

18

81

19

14

18

82

19

15

18

83

19

16

18

84

19

17

18

85

19

18

18

86

19

19

18

87

19

20

18

88

19

21

0.85

64.42

18

89

19

22

0.91

69.25

18

90

19

23

0.91

69.31

18

91

19

24

1.28

97.30

18

92

19

25

0.76

57.56

18

93

19

26

0.76

57.86

18

94

19

27

0.76

57.65

18

95

19

28

18

96

19

29

0.77

58.04

18

97

19

30

0.78

58.87

18

98

19

31

0.64

48.68

18

99

19

32

0.71

53.81

19

00

19

33

0.71

53.78

19

01

0.29

22.14

19

34

0.71

53.97

19

02

0.58

44.10

19

35

0.71

54.06

19

03

19

36

0.71

54.03

19

04

1.34

102.03

19

37

1.03

78.22

19

05

1.30

98.81

19

38

1.04

78.57

19

06

1.30

98.59

19

39

19

07

1.30

98.26

19

40

1.09

82.42

19

08

1.30

98.77

19

41

1.09

82.42

19

09

1.32

100.06

19

42

19

10

1.32

100.00

19

43

19

11

19

44

19

12

19

45

Pu

rch

asi

ng

po

wer

,

no

. of

ba

sket

s

Rea

l w

age

ind

ex,

191

0 =

100

1.1

.11

. N

om

inal

da

y w

ages

urb

an

la

bo

ur,

pri

ces

of

da

ily

fa

mil

y s

ub

sist

ence

bask

et,

pu

rch

asi

ng

po

wer

an

d r

eal

wage

ind

ex

Bri

tish

Ny

asa

lan

d, 1

901

-19

41

Pu

rch

asi

ng

po

wer

,

no

. o

f b

ask

ets

Rea

l w

ag

e in

dex

,

19

10

= 1

00

18

80

19

13

18

81

19

14

18

82

19

15

18

83

19

16

18

84

19

17

18

85

19

18

18

86

19

19

18

87

19

20

18

88

19

21

0.66

72.55

18

89

19

22

0.71

77.99

18

90

19

23

0.71

78.06

18

91

19

24

0.71

77.83

18

92

19

25

0.66

71.96

18

93

19

26

0.66

72.33

18

94

19

27

0.76

83.22

18

95

19

28

18

96

19

29

0.77

83.78

18

97

19

30

0.78

84.97

18

98

19

31

18

99

19

32

19

00

19

33

19

01

0.21

22.60

19

34

19

02

0.41

45.01

19

35

19

03

19

36

19

04

0.93

102.03

19

37

0.59

64.52

19

05

0.90

98.81

19

38

0.59

64.80

19

06

0.90

98.59

19

39

19

07

0.90

98.26

19

40

0.62

67.98

19

08

0.90

98.77

19

41

19

09

0.91

100.06

19

42

19

10

0.91

100.00

19

43

19

11

19

44

19

12

19

45

Pu

rch

asi

ng

po

wer

,

no

. of

ba

sket

s

Rea

l w

age

ind

ex,

191

0 =

100

1.1

.12

. N

om

ina

l d

ay w

ag

es u

rban

la

bou

r, p

rice

s o

f d

ail

y f

am

ily

su

bsi

sten

ce b

ask

et,

pu

rch

asi

ng

po

wer

an

d r

eal

wage

ind

ex

Bri

tish

Ny

asa

lan

d,

190

1-1

94

1

Pu

rch

asi

ng

po

wer

,

no

. o

f b

ask

ets

Rea

l w

ag

e in

dex

,

19

10

= 1

00

18

80

1.03

59.70

19

13

18

81

1.04

60.04

19

14

18

82

1.04

60.05

19

15

0.54

31.02

18

83

1.03

59.74

19

16

0.53

30.71

18

84

1.03

59.74

19

17

0.78

45.21

18

85

1.19

69.00

19

18

0.61

35.45

18

86

1.47

84.82

19

19

0.61

35.30

18

87

1.47

84.85

19

20

1.07

61.78

18

88

1.47

84.84

19

21

1.15

66.25

18

89

1.63

94.34

19

22

18

90

1.48

85.61

19

23

1.61

93.24

18

91

2.05

118.49

19

24

1.72

99.65

18

92

2.05

118.41

19

25

1.69

97.82

18

93

2.05

118.43

19

26

1.40

80.95

18

94

1.63

94.39

19

27

1.75

101.03

18

95

1.63

94.43

19

28

1.74

100.79

18

96

1.63

94.37

19

29

1.70

98.30

18

97

1.18

68.31

19

30

2.07

119.42

18

98

1.70

98.11

19

31

3.27

189.10

18

99

1.70

98.10

19

32

3.48

200.99

19

00

1.70

98.03

19

33

3.61

208.69

19

01

1.70

97.96

19

34

19

02

1.69

97.84

19

35

3.48

201.13

19

03

1.69

97.85

19

36

2.56

148.12

19

04

1.71

98.79

19

37

2.49

143.80

19

05

1.71

98.84

19

38

3.33

192.30

19

06

1.71

98.81

19

39

3.39

195.77

19

07

1.71

98.83

19

40

2.75

159.07

19

08

1.74

100.29

19

41

2.82

162.80

19

09

1.74

100.34

19

42

2.36

136.63

19

10

1.73

100.00

19

43

1.72

99.55

19

11

1.73

99.84

19

44

19

12

1.73

99.89

19

45

1.1

.13

. N

om

ina

l d

ay w

ag

es u

rban

la

bou

r, p

rice

s o

f d

ail

y f

am

ily

su

bsi

sten

ce b

ask

et,

pu

rch

asi

ng

po

wer

an

d r

eal

wage

ind

ex

Bri

tish

Sie

rra

Leo

ne,

19

80

-19

43

Pu

rch

asi

ng

po

wer

,

no

. o

f b

ask

ets

Rea

l w

ag

e in

dex

,

19

10

= 1

00

Pu

rch

asi

ng

po

wer

,

no

. of

ba

sket

s

Rea

l w

age

ind

ex,

191

0 =

100

18

80

0.85

52.27

19

13

18

81

0.85

52.56

19

14

18

82

0.85

52.57

19

15

0.66

40.59

18

83

0.85

52.30

19

16

0.65

40.19

18

84

0.85

52.30

19

17

0.64

39.44

18

85

0.85

52.72

19

18

0.59

36.47

18

86

0.92

56.70

19

19

0.59

36.32

18

87

0.92

56.72

19

20

0.85

52.29

18

88

0.92

56.71

19

21

0.91

56.08

18

89

0.96

59.46

19

22

18

90

0.93

57.23

19

23

1.18

72.86

18

91

1.06

65.60

19

24

1.26

77.86

18

92

1.06

65.56

19

25

18

93

1.06

65.57

19

26

18

94

0.85

52.26

19

27

1.61

99.29

18

95

0.85

52.28

19

28

1.60

99.05

18

96

0.85

52.25

19

29

1.56

96.61

18

97

0.85

52.29

19

30

1.90

117.37

18

98

1.10

67.83

19

31

2.28

140.88

18

99

0.94

58.13

19

32

2.28

140.89

19

00

1.25

77.45

19

33

2.29

141.71

19

01

1.25

77.40

19

34

19

02

1.25

77.31

19

35

2.30

142.16

19

03

1.25

77.31

19

36

1.74

107.41

19

04

1.26

78.05

19

37

2.00

123.71

19

05

1.26

78.10

19

38

2.43

150.26

19

06

1.26

78.07

19

39

2.47

152.97

19

07

1.26

78.09

19

40

2.01

124.29

19

08

1.62

100.29

19

41

2.22

137.40

19

09

1.62

100.34

19

42

19

10

1.62

100.00

19

43

1.34

83.12

19

11

1.71

106.00

19

44

19

12

1.81

112.22

19

45

Pu

rch

asi

ng

po

wer

,

no

. of

ba

sket

s

Rea

l w

age

ind

ex,

191

0 =

100

1.1

.14

. N

om

ina

l d

ay w

ag

es r

ura

l la

bou

r, p

rice

s o

f d

ail

y f

am

ily

su

bsi

sten

ce b

ask

et,

pu

rch

asi

ng p

ow

er a

nd

rea

l w

age

ind

ex

Bri

tish

Sie

rra

Leo

ne,

198

0-1

94

3

Pu

rch

asi

ng

po

wer

,

no

. o

f b

ask

ets

Rea

l w

ag

e in

dex

,

19

10

= 1

00

18

80

19

13

1.54

100.79

18

81

19

14

1.47

95.87

18

82

19

15

0.80

52.10

18

83

19

16

1.13

73.97

18

84

19

17

18

85

19

18

18

86

19

19

1.60

104.67

18

87

19

20

18

88

19

21

18

89

19

22

2.55

166.94

18

90

19

23

2.22

144.74

18

91

19

24

2.17

142.10

18

92

19

25

18

93

19

26

3.30

215.54

18

94

19

27

3.08

201.07

18

95

19

28

3.50

228.45

18

96

19

29

2.52

164.80

18

97

19

30

1.26

82.35

18

98

19

31

2.71

176.83

18

99

19

32

2.97

194.32

19

00

19

33

2.75

179.74

19

01

19

34

2.97

194.20

19

02

19

35

2.11

137.66

19

03

19

36

2.39

156.23

19

04

19

37

2.61

170.66

19

05

19

38

1.02

66.95

19

06

0.92

59.86

19

39

1.47

96.26

19

07

0.89

58.29

19

40

19

08

0.89

58.46

19

41

0.90

58.99

19

09

19

42

1.27

82.90

19

10

1.53

100.00

19

43

1.27

82.96

19

11

1.66

108.52

19

44

1.27

82.96

19

12

1.54

100.42

19

45

1.57

102.78

Pu

rch

asi

ng

po

wer

,

no

. of

ba

sket

s

Rea

l w

age

ind

ex,

191

0 =

100

1.1

.15

. N

om

ina

l d

ay w

ag

es u

rban

la

bou

r, p

rice

s o

f d

ail

y f

am

ily

su

bsi

sten

ce b

ask

et,

pu

rch

asi

ng

po

wer

an

d r

eal

wage

ind

ex

Bri

tish

Ug

an

da

, 19

06

-19

45

Pu

rch

asi

ng

po

wer

,

no

. o

f b

ask

ets

Rea

l w

ag

e in

dex

,

19

10

= 1

00

18

80

19

13

0.88

123.45

18

81

19

14

0.91

126.83

18

82

19

15

0.50

69.90

18

83

19

16

0.75

104.61

18

84

19

17

0.60

84.15

18

85

19

18

0.65

90.76

18

86

19

19

0.53

73.48

18

87

19

20

18

88

19

21

18

89

19

22

1.69

236.98

18

90

19

23

1.71

238.56

18

91

19

24

2.17

304.25

18

92

19

25

1.46

204.12

18

93

19

26

1.30

182.50

18

94

19

27

1.25

174.38

18

95

19

28

1.44

201.17

18

96

19

29

1.00

139.64

18

97

19

30

0.57

80.27

18

98

19

31

1.37

191.27

18

99

19

32

1.61

224.69

19

00

19

33

1.67

233.24

19

01

19

34

1.87

261.89

19

02

19

35

1.31

183.80

19

03

19

36

1.28

178.80

19

04

19

37

1.26

176.41

19

05

19

38

0.49

69.21

19

06

19

39

0.51

71.74

19

07

0.34

47.32

19

40

19

08

0.34

47.46

19

41

0.31

43.96

19

09

0.30

41.91

19

42

19

10

0.71

100.00

19

43

19

11

0.92

129.33

19

44

19

12

0.88

122.99

19

45

1.1

.16

. N

om

ina

l d

ay w

ag

es r

ura

l la

bou

r, p

rice

s o

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, 1

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3-1

94

5

Pu

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Rea

l w

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dex

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= 1

00

Pu

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. of

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ind

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191

0 =

100

APPENDIX II – FIGURES AND TABLES

Figure 3.1: Political boundaries in colonial Africa, 1914

Source: Richard Reid, A History of Modern Africa, 200.

Figure 3.2: Political boundaries in colonial Africa, 1939

Source: Richard Reid, A History of Modern Africa, 201.

Table 3.1: Caloric and Nutritional Composition Subsistence Basket Based on Rice

Unit

Quantity per person

per year Nutrients per kg

Nutrients per person

per day

Calories Protein (gr.) Calories Protein (gr.)

Rice kg 190 3,510 75 1,827 39

Meat kg 3 2,500 200 21 2

Butter kg 3 7,286 7 60 0

Sugar kg 2 3,750 0 21 0

Cotton m 3

Total 1,928 41

Source: Allen, 2009.

Table 3.2: Caloric and Nutritional Composition Subsistence Basket Based on Maize

Unit

Quantity per person

per year Nutrients per kg

Nutrients per person

per day

Calories Protein (gr.) Calories Protein (gr.)

Maize kg 180 3,750 80 1,849 42

Meat kg 3 2,500 200 21 2

Butter kg 3 7,286 7 60 0

Sugar kg 2 3,750 0 21 0

Cotton m 3

Total 1,950 43

Source: Allen, 2009.

Table 3.3: Caloric and Nutritional Composition Subsistence Basket Based on Millet

Unit

Quantity per person

per year Nutrients per kg

Nutrients per person

per day

Calories Protein (gr.) Calories Protein (gr.)

Millet kg 220 3,025 110 1,823 66

Meat kg 3 2,500 200 21 2

Butter kg 3 7,286 7 60 0

Sugar kg 2 3,750 0 21 0

Cotton m 3

Total 1,924 68

Source: Allen, 2009.

Figure 3.3: Taxation incidence for urban unskilled labour in British colonial Africa, 1901-1937

Source: Colonial Blue Books

Figure 3.4: Taxation incidence for rural unskilled labour in British colonial Africa, 1901-1937

Source: Colonial Blue Books