PED401. Applications and Cases in International Development

Teaching Notes1

The Big Push: what does it mean, and does it make sense for Ethiopia? The idea of the Big Push is one of the earliest in development economics, coined by Rosenstein-Rodan over 60 years ago in the context of a classic work on “the problem of industrialization of eastern and south-eastern Europe”. The core argument is that coordination problems, in the context of increasing returns, create the possibility of multiple equilibria. A poor country can be caught in a low-equilibrium “poverty trap”, government intervention can potentially solve the coordination problem, and “push” the economic into the better equilibrium allowing a “take-off” into sustained growth.

The Big Push idea has returned to the center of development policy in the recent past. William Easterly (2006) described 2005 as the Year of the Big Push. It has done so in particular in the context of debates over Africa: the compelling normative case to transform development possibilities of Africans, has been associated with renewed emphasis on the positive case for a Big Push. This has been linked to the case for a major expansion in aid, notably in the work of the Commission for Africa and the Millennium Development Goals; Jeffrey Sachs has been a vigorous exponent of this linkage.

This case concerns the analytics of the Big Push, the evidence and its applicability to a poor African country. It bridges issues of growth (from macro) and general equilibrium (from micro). There are three parts. The first outlines the analytics: it uses the prism of the Solow growth model to look at three possible cases for multiple equilibria, and focuses on the coordination problem as one account. The second looks at approaches to evidence from cross-country patterns, and from country experiences. The third poses the question of Big Push ideas are applicable to Ethiopia.

Analytics of the Big Push

Poverty traps try to explain, within a growth model, why some countries exhibit stagnant growth at low levels of income per capita while others race ahead. In the 1940s, scholars conjectured that underdeveloped countries might be caught in a “poverty trap”, a vicious

1 These notes were prepared by Alexander Culiuc and Michael Walton and are solely for teaching purposes.

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circle of low savings and unattractive investment opportunities. How can this be explained?

We’ll answer this question within the framework of the Solow model, using three “classical” sources of poverty traps discussed by Easterly (2006): low savings at low income levels, non-convexities in the production function, and a Malthusian trap. All three involve multiple equilibria, driven, respectively, by the shape of the savings function, the production function and the depreciation schedule.

Low savings at very low incomes

In this story, poverty traps are due to low saving rates among poor people, so that physical capital accumulation fails to keep up with depreciation and population growth. Similar stories could apply to human capital, but we lump the two forms of capital into one for simplicity. This may be due to a subsistence constraint—below a certain level of income, people have to consume almost all of their income simply to stay alive. The savings of the poor in this case are just big enough to make sure the same subsistence constraint is met in future periods also.2 So the Solow model breaks in this model at the low end of capital.

Output cannot go below some level that covers both subsistence consumption cmin + “subsistence” savings smin, i.e. f(0) is not defined. Instead, we have f(kmin), where kmin is the amount of capital required to maintain the household at this subsistence level of consumption. As output increases, this constraint will be relaxed, and we are back in the standard Solow world, where savings represent a constant share of output. See Figure 1.

As shown in the graph, there are three steady state equilibria: k*low, k*mid and k*high. Of these, only the extreme ones are stable equilibria. However, the k*mid defines the critical threshold. If the economy is located below this point, it will converge to the low capital-low-output equilibrium k*low. If it is above this threshold – it will converge to the “good” equilibrium k*high.

2 PED-101 inspired example: an Indian farmer does not consume all of his crop, a small portion of output being “invested” in (fed to) the bullock, to ensure that the animal can work the land next year.

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Figure 1. A poverty trap in an economy with a subsistence constraint

kmin

f(kmin)

smin

cmin

k*low k*high

Poverty trap A world w/o poverty

f(k)

(n+δ)k

Savings

Output Savings

k k*mid

In this context, aid that is fully invested in new capital will raise the savings curve and will temporarily remove the low equilibrium, as shown in Figure 2: the depreciation line (n+δ)k no longer touches the savings schedule at the lower end of the k axis. To escape the poverty trap, what is needed is to supply sufficient aid for long enough until the economy passes the k*mid threshold, after which aid can be discontinued.

Figure 2. The effect of aid on savings

f(kmin)

k*high

Poverty trap A world w/o poverty

f(k)

(n+δ)k

Savings

Output Savings

k k*mid

Aid

Savings + Aid

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Production function non-convexities

The same general result can be achieved by assuming a different shape of the production function. The key is increasing returns to scale, at least for a range of capital-labor ratios.

Let us revert to the assumption of a constant savings rate. However, assume that the production function does not satisfy the Inada conditions, but instead has the following properties:

00

00)('' 0' 0)0(

⎪⎩

⎪⎨

⎧

><<<><<<

=>=

b

ba

a

kkkkk

kkkfff

The conditions imposed on the 2nd derivative is what makes this function non-convex.3 In this case the Solow graph will look as follows (inflexion points ka and kb are omitted):

Figure 3. Poverty trap

k*min k*high

Poverty trap A world w/o poverty

(n+δ)k

Savings = s .f(k)

Savings

k k*mid

f(k)

Again, we obtain two stable equilibria, k*low and k*high, and the non-stable “threshold” equilibrium k*mid. Foreign aid has the same impact on the economy as in the “poor save too little” story: it will temporarily raise the savings schedule so that the economy can pass the threshold. The Murphy-Shleifer-Vishny account (discussed below) provides the underpinnings for increasing returns.

3 The terminology is somewhat confusing in this case. When we talk about a non-convex production function, we actually mean that it has convex regions where f''>0. A well-behaved production function is concave.

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A basic version of the Malthusian trap

The third obvious modification to the Solow model that can create multiple equilibria is the assumption of an abnormal depreciation schedule. Instead of assuming a constant population growth, we make n a function of output. For low levels of income, the system behaves like a Malthusian economy, in which all increases in productivity are offset by increases in population. Only when returns to human capital become high enough do people shift from making more babies to investing more in their children, which results in the escape from the poverty trap.

Figure 4 Malthusian poverty trap in the Solow model

k*low k*high

Poverty trap A world w/o poverty

y=f(k)

(n(y)+δ)k

s.f(k)

Output Savings

k k*mid

We will return to this type of poverty trap and its implications in a future session.

The Big Push in a general equilibrium setting

When discussing the poverty trap due to a non-convex production function, we simply assume that such a production function can exist. Murphy, Shleifer, Vishny (1989) develop several models that explain why such non-convexities arise in the real world.

The basic idea of their approach is that demand for a manufacturing activity depends on whether other manufacturing activities are already in place. These demand spillovers can result in lack of industrialization in the absence of investment coordination (a “Big Push”). It requires increasing returns to scale interacting with other features of the economy, in particular pecuniary externalities between firms.

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Demand spillovers and a factory wage premium

The economy produces a continuum of goods over the unit interval. Each good is produced by a firm. The only factor of production is labor, with L being the representative worker’s endowment. Any good can be produced either with a traditional or a modern technology, with n being the fraction of firms using modern technology. Firms using traditional technology transform one unit of labor into one unit of output (CRS). If we normalize the wage (price of a unit of labor) to 1, we obtain that the price of any good is also 1. The wage is spent by the worker/consumer equally among all the goods, with y being the per-good spending. Since the total number of goods is 1, the output of each good in a purely traditional economy (n=0) is:

yn=0= L

“Modernization” makes the firm more productive, i.e. one unit of output requires only 1/α units of labor (α>1). However, modernization entails two costs:

Higher wages (1 + ν), where ν is the factory premium.4 A sunk cost of F units of labor in order to upgrade the technology. Notice that the

labor used in the modernization of the firm is of the productive type, but it also has to be paid the high wage, so the cost of the upgrade is F(1+ ν)

Total output if all firms modernize is:

yn=1= α(L – F)

Modernization is welfare improving if α(L – F) > L.

The presence of a sunk cost leads to increasing returns to scale, since average cost will be decreasing as output increases (the sunk cost is spread among more units of output). Clearly, if 1+ν>α then modernization will not happen regardless of the sunk cost – the marginal cost under new technology will be higher than under the traditional one, so we only consider 1+ν<α. The modernized firm will sell its goods at the same price as the traditional ones5, which means that it charges a per-unit markup (1–1/α). However, the existence of a markup does not make modernization necessarily a profitable investment from the point of view of the firm, since we need to subtract the upgrade cost. The profit from modernization is:

( )νανπ +−⎟⎠⎞

⎜⎝⎛ +−= 111 Fy

If no other firms have yet modernized, the profit of a “pioneer” from modernization is:

4 Authors argue that modern firms (factories) have to pay higher wages, whether to offset harder working and living conditions in the city (pollution, long commute, etc.), or on efficiency wage grounds. The urban-rural wage gap is empirically robust, even when accounting for differences in productivity. 5 This stems from the particular form of the utility function assumed by the authors.

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( )νανπ +−⎟⎠⎞

⎜⎝⎛ +−== 1110 FLn

If all other firms have already modernized, the profit of a “late-comer” from modernization is:

( ) ( ναανπ +−−⎟⎠⎞

⎜⎝⎛ +−== 1111 FFLn )

So under our assumptions it may be possible that 00 <=nπ and 00 >=nπ . In such a situation, there must be a threshold fraction of firms n* that need to modernize before modernization becomes profitable for subsequent firm.

Figure 5. Multiple equilibria in the presence of a factory wage premium

The intuition: if nobody has yet modernized, total income in the economy is low, so the first firm to modernize might not reach the scale where average cost is low enough (remember average cost goes down with output) and its profits will be negative. The “late-comer” benefits from the fact that everyone has already modernized, so that the income in the economy is high enough to drive average costs below unit price. However, this n* cannot be reached, since no firm will want to be the first to modernize. And the market economy offers no mechanism for firms to coordinate their efforts. Therefore, there is a role for the state to step in and make all (or at least n*) firms modernize at the same time.

Infrastructure investment

Let’s now assume that the wage in the modern sector is the same as in the traditional one (so ν=0) and explore a different source of coordination failures. Modern technologies/activities require an investment in infrastructure (“railroad”), with sunk cost R and zero maintenance costs. Now industrialization is welfare-enhancing if:

α(L – F – R) > L

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Since the firm operating the infrastructure is a monopolist, it will be able to extract from modern firms a share λ of the profits from modernization by charging a non-zero price for using the infrastructure. Since ν=0, profits from modernization are now:

( ) FRFLFy −−−⎟⎠⎞

⎜⎝⎛ −=−⎟

⎠⎞

⎜⎝⎛ −= α

ααπ 1111

Profits from undertaking the infrastructure investment depend on whether goods are produced with modern technology or not:

( ) FRFLR nn −−−⎟⎠⎞

⎜⎝⎛ −=Π−=Π == α

αλ 11 10

If λ is sufficiently high, we have multiple equilibria (industrialization and no-industrialization).

Figure 6. Profits of the infrastructure owner as a function of the modernization level of the economy

Unless the investor is guaranteed at least n* modern activities, the infrastructure investment will not take place. And unless the infrastructure is expected to be in place, no entrepreneurs will choose to operate with modern technology. The state can step in by financing the infrastructure, with modernization following on its own.

Some empirical evidence

Cross-country patterns

The logical sequence stemming from the aggregate models is the following:

Poverty traps exist A “big push” can move the economy into a good equilibrium Aid can finance the big push

This is what Easterly (2006) calls the classic narrative, and he looks at evidence for this from cross-country patterns. His findings are as follows:

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Malthusian poverty traps clearly exist, as shown by the historical experience of Western countries, that experience long periods in which increased national income was translated into increased population, and not rising income per capita, until the transition to modern growth. However, escaping such traps is a prolonged process.

There is no macro-level evidence supporting low savings rate at low levels of income.

Africa has indeed experienced near-zero growth rates since the mid-1980s, but it was growing over the period if 1950-1985 at around 1% a year (Europe was growing at this rate in mid-nineteen century), and such slowdowns are hard to motivate in the framework of poverty traps.

There is less than ten cases throughout history that fit the story of a big push, in which countries jump from near-zero to sustained, significant positive growth levels (>1.5% a year). Growth rates in the West picked up gradually, so there was no big push in the sense advocated by Sachs and others. Japan and Korea are the clearest examples.

There appears to be no relationship between success stories of rapid sustained growth and aid, although the number of cases fitting the big push story is too small to draw any statistical conclusions on this.

There appears to be a much more robust correlation between the quality of institutions and growth than between aid and growth. This would suggest that development is primarily a political economy problem, not a coordination failure, as argued by Sachs.

What would Jeff Sachs respond to all this evidence? One possible argument against Easterly’s findings can be read off the graph in Figure 2. Notice that if aid is small, the savings schedule will not be lifted up sufficiently to push the economy above the depreciation line. Or, if the aid is short lived, the economy might not reach k*mid by the time aid is discontinued and the economy rolls back to the original state. In other words, all the aid to date was either not sufficiently large or was not sustained at high enough levels for a sufficiently long time. But that is still inconsistent with earlier experiences of steady growth in poor (African or other) countries.

Country narratives

Easterly’s cross-country analysis is a test of an aggregate, systematic relationship at the country level—of the classic narrative. His rejection of this is consistent with his vision of successful development, that has at its core a much more decentralized, experimental approach. But he does not directly test for the specific mechanisms described in Murphy, Shleifer and Vishny. As discussed in PED101, there is a plausible case to be made that some of the East Asian countries did actively intervene in ways that helped solve coordination problems across industries. (This is perhaps most compelling for Japan, Korea and Taiwan—and Murphy, Shleifer and Vishny speculate that the Korean experience exemplifies their models.) More broadly, a central feature of East Asian

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development has been a high priority to large-scale infrastructure development, with this often leading, rather than, lagging, productive demand. Unfortunately, there are also classic failures in government attempts to coordinate industrial policy or use big infrastructure to foster development. Table 1 provides a heuristic summary.

Table 1 Coordination: stylized implications and good and bad examples

Models Implications for development policy

Heuristic/stylized example

Negative examples

Pecuniary externalities through demand linkages

“Coordinate” Subsidize industry

Japanese, Korean and Taiwanese industrial policy

Soviet industrialization; industrial policy in Latin American and India

Infrastructure and industry profits

Finance big infrastructure Coordinate with industrial or other users

Chinese infrastructure policy (put infrastructure in place, get demand later)

“White elephant” dams and other major projects

So the world seems more demanding. At a minimum there are countervailing factors to offset the coordination gains implied by Murphy, Shleifer and Vishny. How do we interpret this? One prism is through the nature and relative importance of market failures versus “government failures”. By the latter we mean that governments either lack the capacities or the incentives to undertake the coordinatory role implied by the models. They may lack the information, or be driven by rent-seeking, corruption and clientelism rather than the maximization of social welfare. More subtly, coordination of industrial investment or big infrastructure depends on the credibility of the investment environment, at macro and micro levels—if investors do not believe the government will sustain its policies it will not invest. This is an issue we’ll discuss later in the semester.

With respect to East Asia, some scholars have sought to interpret not only what they did, but how this related to the underlying political and institutional context. A seminal example is the work of Peter Evans (1995). He argues that Korea indeed did have a developmental state, that was effective in promoting industrial transformation, but that this involved a combination of coherent internal organization, and close links to society that he called “embedded autonomy”, that in turn had historical roots in processes of social and political evolution. The strength, and partial independence, of the Korean and Japanese bureaucracies is a manifestation of this. The strategic choice to make exporting a central performance criterion was critical, but this had to be complemented by the capacity of the state to respond to failures (as emphasized in PED101.)

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Does a Big Push make sense for Ethiopia? I believe in a strong developmental state and developmental states do not intervene in the market in a wanton fashion. They intervene in the market to address pervasive market failures and let the markets work where they work well. So it is a combination of market instruments and non-market instruments to optimise the outcome. That’s been the model lets say in Korea, and Taiwan.

...while the neo-liberal model was right in identifying the central problem in Africa as being pervasive rent seeking on the part of the state, its solution was to remove the state from the economic equation. The neo-liberal reforms did not transform the rent-seeking state into a non-rent seeking one. It has no capacity to do it. All it did was reduce the influence of the state without changing its nature and therefore was inherently incapable of generating the type of growth it sought.

Meles Zenawi, Prime Minister of Ethiopia, Interview with the Financial Times. 6th February, 2007.

Clearly, the Prime Minister believes in an active role for the Ethiopian state, inspired by Korea and Taiwan. As discussed in the introductory case in the first semester, Ethiopia is extraordinarily poor with respect to income per capita, social outcomes, human capital, and physical capital. Figure 7 superficially looks like a poverty trap—Ethiopia’s income has, to first order, stagnated, while other very poor countries have taken off. As the Tables at the end of these notes indicate, Ethiopia has a very low level of industrialization, and very low levels of manufactures in her exports.

Figure 7. Ethiopia’s income in comparative perspective

0

1000

2000

3000

4000

5000

6000

1975197

7197

9198

1198

3198

5198

7198

9199

1199

3199

5199

7199

9200

1200

3

GD

P Pe

r C

apita

(PPP

)

EthiopiaIndonesiaChinaVietnam

There is thus a compelling ethical case for a big push—but is this intellectually coherent and politically and administrative feasible? We should be cautious about the growth numbers being evidence for a poverty trap—as indicated in Easterly’s analysis. But it is highly plausible that issues of coordination are salient: that complementarities between infrastructure and other investment matter and that inter-industry linkages will be central to any growth process. We don’t have the information for a rigorous test of the Murphy, Shleifer and Vishny models, and so a policy assessment and proposal would have to be

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undertaken based on incomplete information and a judgment of what kind of policy process makes sense. In particular, even if it could be shown that the models applied, there remains the question of government capability to undertake the interventions to effect the coordination.

So this case is to think through the applicability of coordination issues based on what you know about Ethiopia. These notes also summarize some of the conclusions from recent World Bank analysis—that itself is a synthesis of a range of existing work.

Industrial policy

The World Bank’s diagnosis of constraints for private sector industrial (and agro-industrial) growth falls loosely within the growth diagnostics framework (Hausmann, Rodrik and Velasco, 2005). With respect to the focus of this case, there are two categories of constraint identified:

Constraints associated with general costs of doing business (e.g. land registration costs) and determinants of expected profits, influenced by uncertainties over government behavior.

Problems of constructing functioning value chains, whether for domestic or export production.

The concept of a value chain is a version of inter-industry pecuniary externalities—the profits of any firm along the chain will be a function of the level of capital (physical and organizational) in other parts of the chain. The analysis does not assess the relative importance of the two categories of constraint, but argues that government policy needs to work on both fronts.

Two contrasting examples of value chains are given. The first is the case of rose production for export. This has taken off in recent years (Table 2). It started with an investment by a foreign producer with experience in Kenya to explore if rose production was profitable in Ethiopia. There followed a process of “discovery”, organization, and tackling of obstacles. Ethiopia is climatically well-suited, and has low cost labor suitable for horticulture. However, there are number of steps in the value chain from production to delivery in Europe—sharing of information on growing practices, internal transport, refrigeration, shipping in air cargo. Logistics account for three-quarters of the delivered costs of flowers. Obstacles have been partially resolved, including in land zoning and use of cargo, and incentives provided, including tax-exempt fertilizers and pesticides, duty-free privileges on technology and government funding of projects. Two factors facilitated resolution. First, there was the creation of an effective private sector organization with an unusual level or trust and cooperation—the Horticulture Association (that set up the EthioHorticulture Share Company to negotiate with other parts of the chain). This helped solve the collective action problem. Second, the government was quite responsive to the demands, adapting policies and regulations to the specific conditions of the sector.

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Table 2 A success: Ethiopia's Flower Exports (US$) Year Flower Export

Revenue Year-on-Year

Growth 2001 660,038 N/A 2002 1,212,968 84% 2003 2,904,000 139% 2004 5,050,000 74%

2005 (August) 12,645,000 >150% Source: Ethiopian Customs Authority

A contrasting example is that of leather, traditionally much larger than horticulture (Figure 8). Here however there has been a failure to solve the organizational and processing problems in the sector. The quality premium that Ethiopian leather used to hold has effectively gone. A small fraction of the total slaughter is undertaken in commercial abattoirs, there is enormous waste and damage (some 90 percent of total production ends with a low grade), there is no system for tracing higher quality final products back through the value chain to provide incentives for better production and processing. Overall, neither government nor producer associations have been able to solve the coordination problems in an area of significant potential comparative advantage. The result has been stagnation of export revenues and of producer and agro-processing incomes. In this case there is a much more dispersed initial producer base—and so a larger initial collective action problem, weak producer organization, and the government has not found interventions to solve the problems along the value chain.

Figure 8. A failure in upgrading: the value chain for leather

Sheep Population 25.5 million

Slaughter 10.2 million off take/ year (40% of sheep population)

Live Animal Export: 0.03 million (18% of sheep population)

Urban Dweller 7.52-million/year (74% of off take)

Rural Farmer 2.68-million/year (26% of off take)

Collector 9.4 million/ year

Merchant 9.4 million/ year

Tannery 9.4 million/ year

Local Market 2.68 million/year (30% of processed finished skin)

Export Market 6.25 million/year (70% of processed skin): Pickled= 84.6% Wet blue= 5.3% Crust = 2.7%

Finished= 7.4%

Waste & Damage 0.8 million pieces due to quality problems and traditional use as seat cover (30% of raw skin from farmer)

Waste & Damage Pre-process rejection: 0.47% In-process damage: 5.0%

Abattoir 1% of total slaughter Waste & Damage

89.5% downgraded to below Grade III quality

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Infrastructure

There is almost universal agreement that Ethiopia has a massive infrastructure deficit. This is illustrated in Table 3, while Table 4 gives some indicators of the complementary effects on factors affecting firm profitability. There are deficits in almost every area. Two illustrate: the poor quality of the rail to the principal port, in Djibouti (See Map); and the contrast between the great potential in water, and the tiny fraction of irrigable land actually under irrigation

Table 3 Indicators of Ethiopia’s infrastructure deficit (unless otherwise indicated; 2000, latest available for Ethiopia)

Low income average

Africa Ethiopia

Access to safe water source 78 54 24 Access to improved sanitation water - 44 15 Fixed and mobile telephones (per 1,000 population) 40 58 8 Within 2 km of an all-season road (rural population) 64 40 27 Access to electricity (%households) 55 24 6 Rely on solid fuels (%households) 78 90 95

Source: IDA 14 Results Measurement System, World Bank, 2004 and Estache (2005) for roads; Ethiopia sources: World Bank (2004c) for water and sanitation; WDI for telephones; Estache (2005) for roads and MDG NA for electricity; ESMAP for solid fuels

Table 4 The impact of unreliable infrastructure services on firms Africa Developing

Country Average

Ethiopia 2002

Electricity Delay in obtaining electricity connection (days)

57.4 32.2 115.8

Value of lost output due to electrical outages (% turnover)

6.1 4.2 5.4

Firms that share/own generator (% of total) 47.9 33.9 17.1 Telecom Delay in obtaining telephone line (days) 73.6 37.2 154.9 Source: World Bank Investment Climate Assessment Database, latest available survey (years vary). Note: Data for Africa is average from 9 countries; developing country average for 45 countries.

There has been substantial growth in spending on infrastructure since the early 1990s, with investment accounting for over 4 percent of GDP (of which almost 3 percent in roads).

For infrastructure that supports productive activities, this has the structure of the last model in Murphy, Shleifer and Vishny. Profits from transport, dams, irrigation etc. depend on other firms investing. Given the low incomes and uncertain growth prospects

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of Ethiopia, private firms are highly unlikely to invest in infrastructure outside areas that have a well-defined markets, for which telecoms is the clearest example. (There is a more complex story around private infrastructure finance with partial guarantees that we return to later in the semester.) For major transport and water development, there is a prima facie case for public funding, that also means donor finance. About 20 percent of ODA already goes to finance infrastructure. However, this does not resolve the coordination problem, for there are further rounds of organizational and inter-firm challenges on the production side. Either smallholder or commercial farm production in major irrigation sites will require solving a series of other constraints, including health related (in the lowlands), organization of water management, and input and marketing services. Even more challenging is solving the international coordination problems under the Nile Basin Initiative, if Ethiopia is to undertake major water development and export electricity from hydropower to the Sudan and Egypt.

A note on Dutch Disease

Since large scale infrastructure will require upfront government spending—with significant donor finance—there is also a risk of Dutch Disease, that is a reduction in the relative price of tradables as an equilibrating mechanism for the relative expansion of demand for nontradable goods (in fact a further example of a general equilibrium interaction.) This will tend to reduce profits in tradable goods production, and this needs to be balanced against the increased profits from scale, infrastructure and inter-firm linkages do not offset this.

Politics and government capability

Even if there is a prima facie case for government intervention, there is a question of government capabilities. Here there are a number of factors to consider.

While the Ethiopian administration is relatively effective—especially for its income level—it is far from independent. It has also been developed more to effect political control than to coordinate and respond—whether across small-scale producers (leather, smallholders that would produce in irrigated areas) or firms.

The society is emerging from a history of hierarchical control and conflict. The recent elections displayed continuing underlying polarization. There is significant mistrust between the private sector and the government.

Both state enterprises and party-controlled enterprises dominate the large-scale firm sector. This raises questions of whether the playing field will be level for other private firms, or new entrants. It is also likely to make it more difficult for the state to impose hard performance constraints (that were important to the East Asian experience.)

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The policy question

The question concerns policy design, but you have a choice of vantage point.

You are a newly appointed World Bank country director for Ethiopia. In your previous experience, mainly outside the World Bank, you developed a rich understanding of the industrialization dynamics in East Asia, focusing especially on the experiences of Japan and Korea. There is tremendous interest in the question of how Ethiopia can take off into rapid growth, and the government is interested in following what they interpret as an East Asia path, of government playing a leading role in the coordination of industrialization and big infrastructure investment. The donors took fright after the 2005 elections, but there is now rising interest in coming back in—the donors are desperate for an African success, and, in geopolitical terms, Ethiopia is increasingly seen as an island of stability in a volatile neighborhood. But you are worried that conditions in Ethiopia are very different from the East Asia exemplars: the political and social situation is polarized, there is widespread concern over political biases in support of party-affiliated firms, and the bureaucracy, while reasonably effective for its income level, is hardly independent. You have a strategic planning meeting with the decision group in the World Bank’s Vice Presidency for Africa. What do you recommend?

You are an economic advisor in the Prime Minister’s Office in Ethiopia. The government faces a major policy challenge. Even before the 2005 elections, the government had a clear vision of effecting an economic transformation of the country, subject to the constraint of maintaining political control. After the elections, there is an overwhelming political imperative—rapid, medium-term growth is seen as essential to manage the current unpopularity of the government and indeed to hold the nation together. With donors (including China) showing renewed interest, the government wants to effect a Big Push. You have been asked to lead the team designing the strategy. You have had study tours of East Asia, and see both economic and political parallels. But you are also aware that a country such as Korea had important checks on performance, including a powerful bureaucracy and the export drive. It is not clear that these are politically and practically feasible for Ethiopia. You have to sketch your approach to the Prime Minister. What do you recommend?

References

Easterly, William. 2006. “Reliving the 1950s: the Big Push, Poverty Traps, and Takeoffs in Economic Development.” Forthcoming, Journal of Economic Growth.

Evans, Peter. 1995. Embedded Autonomy: States and Industrial Transformation. Princeton University Press.

Hausmann, Ricardo, Dani Rodrik, and Andres Velasco. 2005. “Growth Diagnostics.” Harvard University. Cambridge, Mass.: Processed.

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Murphy, Kevin, Andrei Shleifer, and Robert Vishny. 1989. “Industrialization and the Big Push.” The Journal of Political Economy, 97,5.

Rodrik, Dani. 2006. Lecture notes on industrialization, PED101.

Rosenstein-Rodan, P. 1943. “The problem of industrialization of eastern and south-eastern Europe.” Economic Journal, 53, 202-211.

Sachs, Jeffrey. The End of Poverty: Economic Possibilities for Our Time. New York: the Penguin Press.

The Commission for Africa. Our Common Interest. Penguin Books.

World Bank. 2006. Draft country economic memorandum on Ethiopia.

Map of Ethiopia

Figure 7

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