Shadow Economies around the World: Model
Based Estimates∗
Ceyhun Elgin†
Bogazici University
Oguz Oztunalı‡
Bogazici University
Abstract
In this paper, relying on a two-sector dynamic general equilibrium model, we propose and
then use a new methodology to construct a novel shadow economy dataset. We calibrate
our model to match various reported macroeconomic variables and then back out the
size of the shadow economy from the calibrated model. This allows us to construct an
unbalanced 161-country panel dataset over the period 1950 and 2009. This aims to be
the largest dataset in the literature, particularly with its time-series dimension. We also
present certain features of the data along with various descriptive statistics.
JEL codes:. E26, H26, O17, O41.
Keywords: shadow economy; informal sector; two-sector dynamic general equi-
librium models; panel data.
∗We thank Friedrich Schneider for helpful comments and suggestions.†Address: Bogazici University, Department of Economics, Natuk Birkan Building, 34342 Bebek, Istanbul,
(Turkey). e-mail: [email protected].‡Address: Bogazici University, Department of Economics, Natuk Birkan Building, 34342 Bebek, Istanbul,
(Turkey). e-mail: [email protected].
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1 Introduction
Shadow economy, sometimes also titled informal, hidden, black, parallel, sec-ond or underground economy (or sector) is defined by Hart (2008) as a setof economic activities that takes place outside the framework of bureaucraticpublic and private sector establishments. Another paper by Ihrig and Moe(2004) defines it as a sector which produces legal goods, but does not com-ply with government regulations. Additionally, Frey and Pommerehne (1984),Loayza (1996), Johnson, Kaufmann and Shleifer (1997), Johnson, Kaufmannand Zoido-Lobaton (1998a, 1998b), Thomas (1999), Fleming, Roman and Far-rell (2000) Schneider and Enste (2000, 2002), Dell’Anno and Schneider (2004),Schneider (2005) provide or use similar definitions and descriptions among manyothers.
Even though informality is a widespread phenomenon and poses serious so-cial, economic, cultural and political challenges across the world, many issuesabout its nature and consequences still remain largely under-explored or un-resolved. For example, the evidence presented in the existing literature, hasfailed to generate a consensus around the measurement of the informal sectoramong researchers. There are also many other open questions regarding thedeterminants and/or effects of informality including even such basic ones suchas whether informal sector size would be larger in low income or high incomenations (see Dreher and Schneider, 2010); whether taxes are positively corre-lated with informal sector size or not (See Schneider and Enste, 2000, Friedmanet. al. 2000, Elgin, 2010 among many others.) or whether shadow economyand corruption are substitutes or complements (Dreher and Schneider, 2010).
Still, there is a significant amount of empirical research that looks into thecauses and effects of the shadow economy. The existing studies typically con-sider variables like income per capita (or worker), unemployment, tax burden,government spending, regulatory costs, openness to international trade, andvarious other institutional and cultural characteristics as possible determinantsof the shadow economy (see Johnson et. al 1997, 1998; Friedman et al. 2000;Torgler and Schneider, 2007; Elgin, 2010 and much more recently Elgin andSolis-Garcia, 2011 among many others.) Frequently used institutional factorsinclude corruption levels, quality of the bureaucratic establishment, law andorder enforced by the government. Common cultural and social factors, in-cluded in empirical studies are tax morale, religious factors, trust, ethnic unityor polarization. Surely, whether certain factors affect informal sector size or
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not depends on the group of countries and periods being made subjected toempirical analysis.
There are also many studies in the existing literature that explore effectsof the shadow economy. By these studies, presence of the shadow economyaffects both the level and the cyclicality of fiscal policy (Cicek and Elgin, 2011);provision of social security, labor force participation behavior (Schneider andEnste, 2000); income distribution (Hatipoglu and Ozbek, 2011); magnitudeof business cycles (Elgin, 2012); monetary base (Tanzi,1983) and total factorproductivity.(D’Erasmo and Moscoso Boedo, 2012)
As the number of papers in the growing literature on informality indicates,there is an increasing attention on the economic analysis of the shadow econ-omy. However, one particular setback which, despite the development of variousmethods, still persists in the literature is the lack of significantly large datasetsthat would make informality subject to robust (applied) policy analysis. Eventhough, there are various methodologies suggested for its measurement, thisissue mostly arises due to the fact that the size of the shadow economy, bydefinition, is hard to measure and make it subject to empirical analysis. Mostof the suggested methodologies (See the next section for a longer review.) areusually used for a particular country or even a region and could not be general-ized to cross-country panel frameworks. One particular exception is the datasetpresented by Schneider, Buehn and Montenegro (2010) which reports shadoweconomy size (as % of GDP) for 162 countries in an annual basis for the 9 yearsbetween 1999 and 2007. In this study, the authors rely on the MIMIC (MultipleIndicators and Multiple Causes) approach to estimate the size of the shadoweconomy, which according the Breusch (2005) is largely unfit for the purpose.
In this paper, contributing to this literature, we aim to address two issues:First, using a two-sector dynamic general equilibrium we present a new approachto estimate the size of the shadow economy. We believe that this approach hasvarious advantages over the existing methodologies. Second, we use this newmethodology to construct a new unbalanced 161-country panel dataset over theperiod 1950 and 2009. This aims to be the largest dataset in the literature,particularly with its time-series dimension. Among many possible advantagesregarding its use, the construction of such a dataset would allow for variouspolicy analysis that require a significantly large time dimension.
The rest of the paper is organized as follows: In the next section, we pro-vide a short review of the existing methodologies used to estimate the size ofthe shadow economy economy. Then in the third section, we describe a new
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methodology to construct shadow economy estimates. Next, in section four,we apply this methodology to obtain shadow economy size estimates in a panelof 161 countries. In section five, we make some robustness checks to establishrobustness of our estimates. Finally, in the last section we provide concludingremarks.
2 Estimating the Size of the Shadow Economy
2.1 Existing Methodologies
As mentioned above, by its definition estimating the size of the shadow economyis difficult and daunting. Nevertheless, various approaches and methodologieshave been suggested and to some extent used in the literature to come up withestimates. Schneider (2005) and more recently Orsi, Raggi and Turino (2012)provide an excellent survey and comparison of different ways of estimating theshadow economy size. We critically review these below, however we refer thereader to these two papers for a longer survey of these approaches.
Schneider (2005) classifies shadow economy estimation methods under threecategories. They differ in various dimensions but they are all based on the useseveral different econometric estimation methods. These are direct approaches,indirect approaches and the MIMIC approach, respectively.
2.1.1 Direct Approaches
Direct approaches are generally based on the use of surveys, questionnaires, in-terviews and tax auditions of firms and/or households, the results of which arethen used to constructs estimates of shadow economy size employing microeco-nomic or microeconometric methods. (See Schneider, 2005 for a list of papersusing these approaches.) Difficulties regarding the sample choice, possible exis-tence of a selection bias, measurement errors regarding interviews and surveysare among the disadvantages of these approaches. Moreover, these approachesare mostly used at some specific point in time and it is usually very difficult tocreate a time dimension and therefore a time-varying estimate of the shadoweconomy size.
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2.1.2 Indirect Approaches
Methods under this category usually try to obtain estimates exploiting variousdifferent macroeconomic relationships under certain assumptions. Estimatescan be obtained for example from differences between i) national income andexpenditures, ii) official and actual labor force participation, iii) transactionsand national income, iv) electricity consumption and GDP. Yet another heavilyused method is the currency demand approach which is based on the use of acurrency demand function to estimate the size of the shadow economy.1
These methods are generally criticized for being based on various simplifyingand limiting assumptions. Moreover, they generally focus on one specific aspector indicator of the shadow economy and neglect many others. (See Schneider,2005 for a more extensive review and critic of these approaches.)
2.1.3 MIMIC Approach
This approach builds upon the works of Frey and Weck-Hannemann (1983) andis essentially based on the use of a specific structural equation model, titledthe MIMIC approach.2 This approach treats the size of the shadow economyas an unobserved latent variable and essentially consists of two steps: In thefirst step, one determines the causes and the indicators of the shadow economy.Then in the second step, given the causes and the indicators and the specifiedrelationship among them through the unobserved latent variable, one runs astructural equation model to estimate the coefficients of the causes and theindicators. However, similar to the methods outlined above, this approach isbased on the use of ad-hoc econometric specifications thereby making it subjectto statistical errors. Moreover, another shortcoming of this approach is thatit does not rely on any micro-foundations. Breusch (2005) is one of the heavycritics of using the MIMIC approach for this purpose.
2.2 Towards A New Approach
Currently used approaches aiming to estimate the size of the shadow economymight be criticized from three different points of view. First, all these methodsare based ad-hoc econometric specifications and assumptions. Second, heavy
1See Feige (1979), Tanzi (1983), Kaufman and Kaliberda (1996), Johnson Kaufman and Zoido-Lobaton(1998a) Thomas (1999) for different applications and comparison of these different methods.
2There is also a dynamic version of the MIMIC model which does not differ from the static model in anessential way.
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use of econometric estimations make them prone to measurement errors. Fi-nally, even though they specify various macroeconomic variables in their econo-metric specifications, they don’t have any microeconomic foundations whichmakes them open to the Lucas Critique. (See Lucas, 1976.)
To overcome these shortcomings, in this paper we propose and then use anew methodology to estimate size of the shadow economy. We present anddescribe this in the next section.
3 Constructing a New Shadow Economy Dataset
3.1 Procedure
As shortly outlined above the main motivation in constructing a new method-ology is to form a new approach which relies on microfoundations and which isnot based on ad-hoc econometric specifications and assumptions. To this end,we will rely on a two-sector (official and the shadow economies) dynamic generalequilibrium model. In what follows, we will first solve this model and charac-terize it in the steady state. Then we will calibrate the model’s key parametersto match various observables in the data and finally we’ll use the model to backout the unobservable size of the shadow economy. As the observables we plugin to the model vary over time for every country, we will have both time-seriesand cross-sectional variation in the size of the shadow economy.
3.2 Methodology
We will rely on a simple deterministic dynamic general equilibrium model3
which is mostly adapted from Roca, Moreno and Sanchez (2001), Ihrig andMoe (2004), and Busato and Chiarini (2004).
In our model environment, there is an infinitely-lived representative house-hold endowed with K0 units of productive capital and a total of Ht > 0 unitsof time. The household has access to two productive technologies, denoted for-mal and shadow, and maximizes its lifetime utility by solving the the following
3Since we want to run the model for as many countries as possible, as opposed to Busato and Chiarini (2004)or Orsi, Raggi and Turino (2012), we do not introduce uncertainty, as this would require more observables tocalibrate the model.
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program:
max{Ct,Xt,NSt,NFt}∞t=0
∞∑t=0
βtU(Ct)
s.t. Ct +Xt = (1− τt)θFtKαt N
1−αFt + θStN
γSt (1)
Kt+1 = Xt + (1− δ)Kt (2)
NSt +NFt = Ht. (3)
In the program above, β < 1 is a discount factor. We assume that theinstantaneous utility function U(·) is strictly increasing and strictly concave.Equation (1) is the household’s resource feasibility constraint: The amount ofconsumption Ct and investment Xt should equal the amount produced usingthe formal and informal technologies.
The right-hand side of equation (1) shows that the formal technology followsa standard Cobb-Douglas specification, where θFt is the level of productivityexclusive to the formal sector, Kt is the household’s capital stock, and NFt
is the amount of hours the household devotes to the formal technology. Inaddition, formal output gets taxed at a rate τt ∈ [0, 1].
The shadow economy technology depends on labor input only and has formθStN
γSt, where θFt is the level of productivity exclusive to the informal technology
and NSt is the amount of time that the household devotes to the informaltechnology. At a cost of zero, the household can attempt to hide the incomereceived from the informal technology. The government cannot enforce paymentof taxes on informal output.
The rest of the household’s problem is standard: Equation (2) is the house-hold’s law of motion for capital, where δ ∈ [0, 1] is a depreciation rate. Equation(3) is the household’s time constraint.
In this simple model, we assume that the government’s policy τt is exoge-nously determined and the tax revenue is used to finance an exogenous streamof government spending Gt. An equilibrium is easy to define:
Definition 1. Given the government policy variable tax burden {τ}, a competi-tive equilibrium of the two-sector model is a set of sequences {Ct, Xt, Kt+1, NSt, NFt, Gt}∞t=0
such that
1. The household’s problem is solved by {Ct, Xt, Kt+1, NSt, NFt}∞t=0.
2. Gt equals τtθFtKαt N
1−αFt .
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3.3 Solving the model
Assuming logarithmic utility of consumption, household’s maximization prob-lem yields the following first order conditions:
Ct+1
Ct= β[(1− τt)α
YFt+1
Kt+1+ 1− δ] (4)
,where YFt = θFtKαt N
1−αFt and
θStγNγ−1St = (1− τt)θFt(1− α)Kα
t N−αFt . (5)
By rearranging the Euler equation (4), one can obtain Kt in terms of NFt:
Kt = NFt
[(1− τt)θFtα
(1 + gc)/β − 1 + δ
] 11−α
. (6)
where gc is the growth rate of consumption in period t, i.e. 1 + gc = CtCt−1
Moreover, informal labor can be obtained now using (5) as follows:
NSt =
{γθSt
(1− τ)(1− α)θFt
[(1 + gc)/β − 1 + δ
α(1− τt)θFt
] α1−α} 1
1−γ
(7)
Given the characterization of the model, we now can turn to the calibrationand how we back out the size of the shadow economy using the model.
3.4 Calibration and Data Construction
Our ultimate purpose in this section is to back out time-varying estimates ofthe size of the shadow economy as % of official GDP in every country for any
year t. In our model’s terms, that is given byθStN
γSt
θFtKαt N
1−αFt
.
To back out the shadow economy size in a specific country for a specific yeart we proceed as follows:
First, as standard in the real business cycle literature we assume that α =0.36, δ = 0.08. Moreover, we take γ = 0.425 following Ihrig and Moe (2004).Next, we construct the capital stock series {Kt} relying on the widely used
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perpetual inventory method.4
Once the capital stock series is constructed we can calibrate β for everycountry using the Euler equation (4). Here we obtain the aggregate consumptiondata Ct from PWT.
Moreover, we obtain (formal) employment (NFt) from PWT as well. Finally,as we assume a balanced budget for the government τt is obtained as the shareof government spending in GDP similarly from the same source.
Next, using the specified values for α and δ, the calibrated value of β andyear specific τt, NFt and Kt, we use the equation (6) to back out θFt for anyyear t.
Now, the only thing remains to be calculated is θSt. Here we assume thatθSt grows at a rate which is the average of the growth rate of Kt and θFt.
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Having made this assumption regarding the growth rate of θSt, we choose θS2007
to match the shadow economy size in 2007 of the series reported in Schneider et.al. (2010) and construct the rest of the θSt series using the calculated growthrates.
Finally, we calculate NSt using (7). Once NSt is obtained, the size of the
shadow economy in a specific year can easily be computed usingθStN
γSt
θFtKαN1−α
Ft
forevery year.
4 Results
Our procedure allows us to have a dataset with 7395 observations for 161 coun-tries6 in an unbalanced panel framework running from 1950 to 2009. The com-
4We obtain the capital-stock using the following formulae:
Kt+1 = Kt(1− δ) + It
K1950
Y1950=
∑2009i=1950
IiYi
δ + gY
The first equation is the standard law of motion for capital, where Kt stands for the aggregate capital stock inyear t, δ for the depreciation rate of physical capital, and It for the amount of investment in year t. Here weset δ = 0.08 and obtain the data on investment from Penn World Tables 7.0 (PWT). The second equation isbased on the assumption that the economy is at the steady state in the initial period of analysis which we takeas 1950 here. Once the capital stock in 1950 is calculated using the second equation, the first equation allowsus to create a capital stock series for the years between 1950 and 2009.
5Notice that the shadow economy production function is only a function of the productivity parameter θSand labor NS . This does not necessarily mean that the shadow economy doesn’t employ capital in production asone can interpret the function so that a fixed amount of capital is incorporated in θSt . Therefore, the assumptionwe make regarding the growth of θSt is not unrealistic.
6The country list is provided in the appendix. The only country we exclude from Schneider, Buehn andMontenegro (2010) is Myanmar.
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Table 1: Unweighted Shadow Economy Size
Region Mean Median Minimum Maximum Std. Dev.
OECD-EU 23.53 21.06 8.07 72.08 11.34Latin 45.47 44.33 22.64 74.30 12.79Post-Socialist 34.94 33.95 14.15 80.33 12.08MENA 29.01 27.80 15.09 63.12 11.36Sub-saharan 43.92 41.70 21.85 78.41 10.48Asia 38.40 37.65 10.65 78.09 14.76World 36.54 35.91 8.07 80.33 14.78
plete dataset is reported in a country by country and year by year basis inthe appendix. Nevertheless, we report various descriptive statistics and presentillustrative figures in this section.
Table 2: GDP-weighted Shadow Economy Size
Region Mean Median Minimum Maximum Std. Dev.
OECD-EU 20.38 19.65 16.02 25.66 2.99Latin 43.27 40.56 35.19 56.78 5.75Post-Socialist 35.64 32.28 26.20 55.67 8.58MENA 28.89 23.65 19.30 60.89 10.29Sub-saharan 42.94 41.62 34.10 51.97 4.69Asia 38.47 37.24 20.82 65.56 13.32World 27.88 28.14 21.59 36.09 3.91
The first thing we notice is that the 1999-2007 part of our dataset has a cor-relation of 0.987 with the shadow economy data reported by Schneider, Buehnand Montenegro (2010).
Next, in order to observe the variation of the shadow economy size in differ-ent group of countries over time, we divided the world into 6 different groups.These are OECD-EU, Latin American and Caribbean, Post-Socialist (Transi-tion), Middle East and North African, Sub-Saharan African and Asia-Oceaniacountries.7 We also report descriptive statistics for the whole dataset (denotedby the row titled World) as well.
In Table 1, we report the descriptive statistics of the shadow economy sizein these 6 different groups of countries. These group statistics in Table 1 areunweighted, that is we simply treated every country in a specific group equal.
7See the Appendix for the countries included in specific groups.
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These are group statistics for the 1950-2009 period, except for Post-Socialistcountries in which case the period covered is 1990-2009.
Table 3: Regional Trends (GDP-Weighted Data)
Region 1960-1970 1971-1980 1981-1990 1991-2000 2001-2009
OECD-EU 22.92 20.26 18.92 17.81 16.53Latin 47.43 41.88 40.02 39.09 36.28Post-Socialist - - - 31.56 31.55MENA 33.77 24.58 22.89 22.35 21.06Sub-saharan 50.36 44.58 40.40 39.81 36.16Asia 42.92 37.63 33.08 26.16 26.45World 31.51 28.571 25.70 23.99 23.95
Figure 1: Shadow Economy Over Time: Unweighted Regional Averages
As looking at unweighted series might be a misleading way of calculating theshadow economy size in a group, in Table 2 we report the descriptive statistics
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of weighted series in different groups of countries.8 Investigating Tables 1 and2 indicate a couple of crucial points: First, as ceteris paribus, richer countriestend to have a smaller shadow economy (tough the relationship is not totallylinear) once we weight the shadow economy size with GDP, the world averageis significantly reduced. Second, judging from the standard deviations, the sizeof the shadow economy experienced a significant variation both across groupsand within groups. Third, Latin American and Sub-saharan economies do havesignificantly larger shadow economies than the other group of countries wherethe OECD-EU group does have a significantly smaller shadow economy size.Post-socialist transition economies also have a significant shadow economy size.
Figure 2: Shadow Economy Over Time: GDP-weighted Regional Averages
Next, in Table 3, we report the evolution of the shadow economy size indifferent groups over time in approximately 10-year intervals. In line with Table
8We calculated the weighted series for a group using the following formula:∑N
i=1 SiYi∑Ni=1 Yi
, where Si is the size
of the shadow economy (as % GDP) Yi is the GDP in the country i, and N is the number of countries in thegroup.
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3, Figures 1 and 2 present unweighted and GDP-weighted shadow economysize in an annual basis. For almost all country groups (except for the Post-Socialist one) we observe a declining trend over time. However, the pace of thereduction seems to loose some momentum in the last decade. Also, somewhatmore interestingly we observe a spike starting in 2007 for the OECD-EU group.Considering the emergence of the global economic crisis especially shaking thedeveloped economies, this could give further support for the hypothesis that thesize of the shadow economy is countercyclical as suggested by Roca, Moreno andSanchez (2001) and Elgin (2012).
Figure 3: Shadow Economy in a Cross-Section
As mentioned above, richer countries tend to have a smaller shadow economysize. We illustrate this in Figure 3, where we plot shadow economy size as % ofGDP vs. GDP per-capita. Here we plot average values for every country from1950 to 2009.
Even though Figure 3 suggest the existence of a highly negative (and lin-ear) relationship between GDP per-capita and shadow economy size in a cross-section, there is also evidence leading us to suspect that this relationship might
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Figure 4: Evolution of the Shadow Economy in Different Income Groups
be non-linear. In Figure 4, we aim illustrate this. Here, we group countrieswith respect to the GDP per-capita and then report the average GDP-weightedshadow economy size in each group for every year from 1960 to 2009. To dothis, we divide the countries into five categories: poorest, second, third, fourthand the richest 20 %. Not surprisingly, richer countries tend to have a smallershadow economy; however what Figure 3 shows that this relationship mightnot be exactly linear, especially in the process of development. Even tough,further research is required on this, this might be considered as a support forinformality dimension of the Kuznets Curve hypothesis.
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5 Robustness Checks
In this section we present several robustness checks of the methodology wepropose to construct shadow economy estimates.
5.1 Tax Burden vs. Government Spending
Table 4: Tax Burden vs. Government Spending: 1960-2009
With Taxes Region Mean Median Minimum Maximum Std. Dev.
OECD-EU 22.80 21.02 8.76 72.11 10.47Latin 45.07 43.01 22.65 72.14 12.63Asia 38.10 36.97 10.69 79.12 14.03
With Gov. Sp. Region Mean Median Minimum Maximum Std. Dev.
OECD-EU 22.20 20.09 8.07 72.08 10.17Latin 44.09 42.71 22.64 71.79 12.31Asia 37.26 36.79 10.65 78.09 13.96
One potential criticism of the simple methodology we propose could be thespecific balanced budget assumption we make for the government. Specifically,we assumed that for any government revenues equal spending. This allowed usto use share of government spending as a proxy for the level of tax burden in acountry. We made this simplifying assumption to construct the largest datasetpossible, as data for government spending is available in PWT for a very largenumber of countries whereas tax burden data (for example from GovernmentFinance Statistics of the IMF or from World Development Indicators) is muchmore limited. Nevertheless, in one of the robustness checks, instead of usinggovernment spending share from PWT as the measure τt, we directly obtain thetax burden (tax revenue as % of GDP). In that case we can only construct datafor 98 countries and lose data for most of the subsaharan and post-socialisttransition economies. Moreover, the time-series dimension of our dataset isnow reduced to the period from 1960 to 2009. We present descriptive statisticsfor this exercise (for unweighted data) in Table 4. Observe that there is nosignificant difference between two panels in the table. Moreover, we should alsomention that the correlation between unweighted shadow economy series is 0.92for the OECD-EU group, 0.84 for Latin American and Caribbean economies and0.90 for Asian-Australian countries.
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5.2 Sensitivity Analysis
Remember that In the data construction stage of the benchmark case we haveassumed that γ = 0.425, δ = 0.08 and α = 0.36. In this subsection we will firstrelax these three assumptions one-by-one and present descriptive statistics forunweighted data.
Table 5: Descriptive Statistics with Different γ
γ = 0.35 Region Mean Median Minimum Maximum Std. Dev.
OECD-EU 23.61 21.10 8.12 72.18 11.25Latin 45.50 44.35 22.67 74.38 12.76Post-Socialist 34.94 33.98 14.16 80.35 12.10MENA 29.08 27.85 15.16 64.14 11.82Sub-saharan 44.01 41.79 22.03 79.14 10.58Asia 38.45 37.71 10.77 78.19 12.21World 36.59 35.95 8.12 80.35 14.75
γ = 0.50 Region Mean Median Minimum Maximum Std. Dev.
OECD-EU 23.43 21.01 7.99 71.15 11.45Latin 45.06 44.04 22.33 73.30 13.03Post-Socialist 34.21 33.57 13.82 79.12 11.08MENA 28.22 26.98 14.97 62.87 11.38Sub-saharan 43.10 39.98 21.11 78.02 10.55Asia 37.45 36.28 10.11 77.18 14.77World 35.51 34.79 7.99 79.12 15.20
To this end, first we relax the assumption that γ = 0.425. In this case, welet γ to vary between 0.35 and 0.5. In Table 5 we report descriptive statistics ofunweighted shadow economy estimates (similar to Table 1) for different regionsusing these two different values for γ. As we can see from Table 1, results arenot significantly different from the benchmark case. Especially, we note that thecross-country (or cross-regional) and time-series correlations do not significantlychange when we let γ to take different values than the benchmark.
In similar exercises, we change the values of δ and α in tables 6 and 7. Inall cases, we end with descriptive statistics which are not significantly differentthan the those in the benchmark case.
The final robustness check we perform is regarding the construction of the{θSt} series. Remember that in the benchmark case, we have choosen θS2007
to match the shadow economy size in 2007 for any country with the shadoweconomy estimates reported in Schneider et al. (2010) and then constructed
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Table 6: Descriptive Statistics with Different δ
δ = 0.06 Region Mean Median Minimum Maximum Std. Dev.
OECD-EU 23.40 21.09 8.05 71.86 11.30Latin 44.72 43.76 22.32 73.40 11.88Post-Socialist 33.99 33.42 14.01 78.42 11.82MENA 28.89 27.45 15.01 63.01 11.04Sub-saharan 43.78 41.65 21.72 78.37 10.46Asia 37.92 37.49 10.55 77.86 13.12World 35.97 35.55 8.05 78.42 13.80
γ = 0.10 Region Mean Median Minimum Maximum Std. Dev.
OECD-EU 23.83 21.16 8.14 72.20 11.22Latin 45.98 45.02 23.02 74.98 12.75Post-Socialist 35.25 34.03 15.18 82.01 12.08MENA 29.20 27.82 15.32 63.77 11.40Sub-saharan 43.97 42.01 21.99 78.74 10.59Asia 39.01 38.14 11.03 79.02 13.77World 36.98 36.15 8.14 82.01 13.98
Table 7: Descriptive Statistics with Different α
α = 0.42 Region Mean Median Minimum Maximum Std. Dev.
OECD-EU 22.15 20.02 7.18 71.80 10.98Latin 44.90 43.78 22.00 73.80 12.77Post-Socialist 34.15 33.25 14.00 79.75 12.07MENA 28.50 27.41 14.63 62.52 11.00Sub-saharan 43.61 41.56 21.45 78.00 10.45Asia 38.01 37.12 10.42 77.27 14.37World 35.39 35.00 7.18 79.75 14.07
α = 0.30 Region Mean Median Minimum Maximum Std. Dev.
OECD-EU 24.00 21.12 8.32 72.12 11.42Latin 45.55 44.49 22.75 74.89 12.56Post-Socialist 35.02 34.04 14.19 80.56 12.00MENA 29.11 27.82 15.13 63.17 11.30Sub-saharan 44.00 42.20 22.05 79.17 10.65Asia 38.47 37.80 11.01 78.23 14.56World 37.20 35.90 8.32 80.56 14.70
the rest of the θSt series using the calculated growth rates. Now, an alternativeis not to match the shadow economy size in 2007 from Schneider et al. (2010)
but instead share of informal employment (NStNFt
in model’s terms.) Using data
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from Charmes (2009) we now match share of self-employment as % of non-agricultural employment in 2000.9 for various economies. Since this data isonly available for 111 countries, such an exercise again reduces the size of ourdataset compared to the benchmark. Nevertheless, Table 8 reports descriptivestatistics of our model’s estimates with this exercise.
Table 8: Descriptive Statistics with Different Data Matching
Region Mean Median Minimum Maximum Std. Dev.
OECD-EU 24.10 22.19 8.30 71.45 9.87Latin 46.51 45.20 23.29 74.31 12.77Post-Socialist 35.16 34.30 13.99 82.44 14.17MENA 30.00 28.08 16.01 64.15 10.89Sub-saharan 44.94 43.21 22.93 80.19 11.56Asia 38.59 37.98 10.64 78.97 15.01World 37.15 36.29 8.30 82.44 14.88
6 Conclusion
In this paper, using a two-sector dynamic general equilibrium model, we de-veloped a approach to estimate the size of the shadow economy. Compared tothe methods used in the current literature, this approach overcomes three mainissues: First, it does not rely on ad-hoc econometric specifications and assump-tions. Second, as it does not estimate the size of the shadow economy usingstatistical methods, it does not include statistical errors. Finally, as opposed tothe currently existing methods, it does not lack micro-foundations.
In addition to presenting the new approach we also used it to estimate thesize of the shadow economy in a 161-country panel data framework. Withsignificantly larger time-dimension than the currently existing ones, this aimsto be the largest dataset in the literature. Thanks to this, future research cannow utilize various tools of panel data econometrics with a relatively closer focusto time-series dimension.
9This is a widely used proxy for informal employment in the empirical literature on informality.
18
References
1. Breusch, T. 2005. Estimating the Underground economy using MIMICmodels, Econometrics 0507003, Econ WPA.
2. Busato, F., Chiarini, B. 2004. Market and underground activities in a two-sector dynamic equilibrium model, Economic Theory, 234, pages 863-861.
3. Charmes, J. 2009. Concepts, measurement and trends. In P. Jutting & J.R. de Laiglesia (Eds.) Is informal normal? Towards more and better jobsin developing countries. An OECD Development Centre Perspective.
4. Cicek, D., Elgin, C. 2011. Cyclicality of fiscal policy and the shadoweconomy, Empirical Economics, 413, pages 725-737.
5. Dell’Anno, R., Schneider, F. 2004. The Shadow Economy of Italy andother OECD Countries: What Do We Know? Linz: University of Linz,Department of Economics. Discussion Paper. Published in Journal ofPublic Finance and Public Choice, 2005.
6. D’Erasmo, P. N., Moscoso Boedo, H. J. 2012. Financial Structure, Infor-mality and Development, Journal of Monetary Economics, forthcoming.
7. Dreher, A., Schneider, F., 2010. Corruption and the Shadow Economy:An Empirical Analysis, Public Choice, 144, 215-238.
8. Elgin, C. 2010. Political Turnover, Taxes, and the Shadow Economy,WorkingPapers 2010/08, Bogazici University, Department of Economics.
9. Elgin, C., Solis-Garcia, M. 2011. Public Trust, Taxes and the InformalSector, Working Papers 2011/04, Bogazici University, Department of Eco-nomics.
10. Elgin, C. 2012. Cyclicality of the Informal Economy, Working Papers2012/02, Bogazici University, Department of Economics.
11. Feige, Edgar L. 1979. How Big is the Irregular Economy?, Challenge 22:1,pp. 5-13.
12. Fleming, M.H., Roman, J., Farrel, G. 2000. The Shadow Economy. Journalof International Affairs, Spring 2000, No. 532: 64-89.
19
13. Frey, B. S., Weck-Hannemann, H. 1983. Estimating the Shadow Economy:A Naive Approach, Oxford Economic Papers, 35, pp. 23-44.
14. Frey, B. S., Pommerehne, W. W. 1984. The Hidden Economy: State andProspect for Measurement, Review of Income and Wealth 30 3: 1-23.
15. Friedman, E., Johnson, S., Kaufman, D., Zoldo-Lobaton, P. 2000. Dodg-ing the Grabbing Hand: The Determinants of Unofficial Activity in 69Countries, Journal of Public Economics 76 3: 459-493.
16. Hatipoglu, O., Ozbek, G. 2007. On the Political Economy of the Infor-mal Sector and Income Redistribution, Working Papers 2007/11, BogaziciUniversity, Department of Economics.
17. Hart, K., 2008. Informal Economy, The New Palgrave Dictionary of Eco-nomics. Second Edition, Eds.Steven N. Durlauf and Lawrence E. Blume.Palgrave Macmillan
18. Ihrig, J., Moe, K., 2004. Lurking in the shadows: The informal sector andgovernment policy. Journal of Development Economics, 73, 541-77.
19. Johnson, S., Kaufman, D., Shleifer, A. 1997. The Unofficial Economy inTransition, Brookings Papers on Economic Activity, 2, 159-221.
20. Johnson, S., Kaufman, D., Zoido-Lobaton, P. 1998. Regulatory Discretionand the Unofficial Economy, American Economic Review 88,. 387-392.
21. Kaufman, D., Kaliberda, A. 1996. Integrating the unofficial economy intothe dynamics of post-socialist economies: A framework of analysis andevidence, World Bank Policy Research Working Paper No. 1691.
22. Loayza, N.V., 1996. The economics of the informal sector: A simple modeland some empirical evidence from Latin America. Carnegie-RochesterConference Series on Public Policy 45 1: 129-162.
23. Lucas, R. 1976. Econometric Policy Evaluation: A Critique”, in Brun-ner, K.; Meltzer, A., The Phillips Curve and Labor Markets, Carnegie-Rochester Conference Series on Public Policy, 1, New York: AmericanElsevier, pp. 19-46.
24. Orsi, R., Raggi, D., Turino F. 2012. Estimating the Size of the Under-ground Economy: A DSGE Approach, Working Papers wp818, Diparti-mento Scienze Economiche, Universita di Bologna.
20
25. Roca, J. C. C., Moreno, C. D., Sanchez, J. E.G. 2001. Underground econ-omy and aggregate fluctuations, Spanish Economic Review, 31, 41-53.
26. Schneider F., Enste, D. H., 2000. Shadow Economies: Sizes, Causes andConsequences. Journal of Economic Perspectives, 38: 77-114.
27. Schneider, F., 2005. Shadow Economies Around the World: What do WeReally Know?, European Journal of Political Economy, 21, 598-642
28. Schneider, F., Buehn, A., Montenegro, C. E. 2010. Shadow Economies allover the World, World Bank Policy Research Working Paper, 5356.
29. Thomas, J. J. 1999. Quantifying the Black Economy: Measurement with-out Theory Yet Again? The Economic Journal 109456: 381-389.
30. Torgler, B., Schneider, F. 2007. Shadow Economy, Tax Morale, Governanceand Institutional Quality: A Panel Analysis, IZA Discussion Papers, no.2563.
31. Tanzi, V. 1983 The underground economy in the United States: annualestimates, 1930-80, IMF Staff Papers, 30 (2), 283-305.
21
Appendix
Group Compositions:OECD-EU: Australia, Austria, Belgium, Canada, Chile, Cyprus, Denmark,
Finland, France, Germany, Greece, Iceland, Ireland, Israel, Italy, Japan, Korea(South), Luxemburg, Malta, Mexico, Netherlands, New Zealand, Norway, Por-tugal, Spain, Sweden, Switzerland, Turkey, UK, USA
Latin American and Caribbean: Argentina, Bahamas, Belize, Bolivia,Brazil, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala,Guyana, Haiti, Honduras, Jamaica, Nicaragua, Panama, Paraguay, Peru, Suri-name, Trinidad and Tobago, Uruguay, Venezuela,
Post-Socialist: Albania, Armenia, Azerbaijan, Belarus, Bosnia and Herze-govina, Bulgaria, Croatia, Czech Republic, Estonia, Georgia, Hungary, Kaza-khstan, Kyrgyzstan, Latvia, Lithuania, FYR Macedonia, Moldova, Mongolia,Poland, Romania, Russia, Slovakia, Slovenia, Tajikistan, Ukraine,
MENA: Algeria, Bahrain, Egypt, Iran, Jordan, Kuwait, Lebanon, Libya,Morocco, Oman, Qatar, Saudi Arabia, Syria, Tunisia, UAE, Yemen,
Sub-saharan Africa: Angola, Benin,Botswana, Burkina Faso, Burundi,Cameroon, Cape Verde, Central African Republic, Chad, Democratic Republicof Congo, Republic of Congo, Equatorial Guinea, Eritrea, Ethiopia, Gabon,Gambia, Ghana, Guinea, Guinea-Bissau, Ivory Coast, Kenya, Lesotho, Liberia,Madagascar, Malawi, Mali, Mauritania, Mauritius, Mozambique, Namibia, Niger,Nigeria, Rwanda, Senegal, Sierra Leone, South Africa, Sudan, Swaziland, Tan-zania, Togo, Uganda, Zambia, Zimbabwe.
Asia - Oceania: Bangladesh, Bhutan, Brunei, Cambodia, China, Comoros,Fiji, Hong Kong, India, Indonesia, Laos, Macao, Malaysia, Maldives, Nepal,Pakistan, Papua New Guinea, Philippines, Singapore, Solomon Islands, SriLanka, Taiwan, Thailand, Vietnam,
22
Shadow
Eco
nom
yE
stim
ate
s1950-1
980
XX
XX
XXX
XXX
XX
Year
Cou
ntr
yA
lban
iaA
lger
iaA
ngo
laA
rgen
tina
Aust
ralia
Aust
ria
Bah
amas
Bah
rain
Ban
glad
esh
Bel
gium
Bel
ize
Ben
in
1950
29.6
922
.07
17.2
034
.96
1951
29.8
221
.88
17.1
034
.70
1952
29.5
321
.51
16.8
934
.48
1953
29.5
121
.66
16.8
434
.24
1954
29.3
821
.61
16.9
034
.06
1955
29.3
421
.44
16.8
933
.78
1956
29.1
021
.26
16.6
533
.54
1957
29.0
821
.18
16.5
133
.17
1958
28.9
521
.07
16.3
432
.74
1959
28.6
820
.89
16.1
548
.23
32.5
966
.65
1960
36.6
128
.56
20.7
315
.98
49.0
832
.41
65.8
2
1961
36.3
528
.15
20.4
715
.66
49.8
532
.14
65.0
5
1962
35.7
527
.68
20.3
715
.32
50.5
231
.75
64.3
6
1963
35.9
127
.36
20.1
915
.06
50.6
231
.28
63.9
4
1964
36.1
027
.32
19.9
814
.83
51.0
531
.02
63.5
2
1965
36.4
427
.10
19.6
814
.52
51.1
530
.48
63.2
8
1966
36.7
526
.82
19.5
114
.23
51.1
530
.02
63.2
4
1967
37.2
426
.62
19.2
513
.89
51.1
129
.50
63.0
5
1968
37.4
126
.37
19.0
713
.64
50.9
529
.08
62.3
4
1969
37.3
826
.16
18.7
813
.35
50.2
228
.76
61.5
5
1970
39.4
937
.09
41.8
525
.76
18.6
013
.10
32.7
617
.12
49.8
228
.21
54.0
960
.62
1971
38.9
136
.58
41.5
125
.38
18.2
912
.83
33.2
317
.19
49.6
527
.77
53.3
060
.15
1972
38.3
836
.46
41.0
025
.01
18.1
112
.61
33.6
817
.21
49.7
927
.39
52.5
759
.82
1973
37.8
136
.17
40.6
424
.67
17.9
812
.36
34.1
317
.23
50.8
227
.13
51.7
358
.79
1974
37.3
535
.58
39.9
724
.45
17.6
912
.10
34.5
017
.20
50.9
226
.83
51.1
458
.28
1975
36.9
334
.68
39.3
224
.22
17.5
811
.82
34.9
716
.79
51.1
626
.35
50.6
957
.20
1976
36.5
233
.77
38.9
824
.01
17.5
111
.69
35.5
717
.51
51.3
426
.16
49.8
156
.18
1977
36.1
433
.11
38.8
823
.77
17.4
411
.55
36.0
917
.22
51.3
125
.88
48.8
455
.83
1978
35.7
832
.25
38.6
823
.38
17.3
511
.38
36.5
217
.31
50.8
525
.63
48.1
755
.63
1979
35.4
231
.27
38.5
023
.20
17.2
311
.30
37.0
817
.15
50.3
325
.43
47.4
155
.59
1980
35.0
730
.62
39.2
622
.99
17.1
511
.13
37.2
716
.81
49.4
025
.26
46.3
154
.74
23
Shadow
Eco
nom
yE
stim
ate
s1950-1
980
XX
XX
XXX
XXX
XX
Year
Cou
ntr
yB
huta
nB
oliv
iaB
otsw
ana
Bra
zil
Bru
nei
Bulg
aria
Burk
ina
Fas
oB
uru
ndi
Cam
bodia
Cam
eroon
Can
ada
Cap
eV
erde
1950
72.3
963
.86
24.2
4
1951
72.6
563
.05
24.0
1
1952
72.0
761
.93
23.8
2
1953
71.9
160
.25
23.6
7
1954
72.4
359
.98
23.4
9
1955
72.2
959
.14
23.4
7
1956
71.1
958
.30
23.3
3
1957
70.4
157
.99
23.0
6
1958
70.1
056
.99
22.8
0
1959
70.1
556
.26
52.9
722
.66
1960
70.3
455
.01
53.8
252
.82
42.4
522
.53
49.7
3
1961
70.1
954
.35
54.5
953
.06
42.8
022
.38
48.7
7
1962
70.0
653
.60
55.3
253
.26
43.1
022
.28
47.4
1
1963
69.1
452
.83
56.0
253
.14
43.3
522
.16
46.6
4
1964
68.4
952
.54
56.7
353
.44
43.5
522
.05
46.9
9
1965
67.8
352
.25
57.7
353
.68
43.5
721
.91
47.4
4
1966
67.4
551
.68
58.0
553
.90
43.2
521
.74
47.7
0
1967
67.1
151
.05
58.3
453
.85
42.6
721
.46
47.1
3
1968
66.7
750
.76
58.4
253
.52
42.4
121
.27
47.3
5
1969
66.5
850
.18
58.6
752
.95
42.1
321
.12
47.2
3
1970
50.3
666
.39
48.9
635
.90
47.1
658
.47
52.3
455
.93
41.9
720
.87
46.5
0
1971
50.0
366
.35
48.0
637
.14
46.2
758
.16
52.4
855
.90
41.4
620
.70
45.5
1
1972
49.7
265
.99
47.0
538
.11
45.3
856
.43
51.2
856
.04
40.6
320
.56
44.7
2
1973
49.4
765
.32
45.9
238
.95
44.4
955
.50
52.0
356
.29
39.8
520
.46
44.0
9
1974
49.2
465
.13
44.5
839
.90
43.6
254
.54
51.9
956
.77
39.1
320
.27
43.5
6
1975
49.0
065
.00
60.0
243
.30
40.7
542
.74
52.8
251
.17
57.0
338
.73
20.0
243
.14
1976
48.8
864
.00
57.7
642
.06
41.4
441
.83
52.4
350
.91
57.0
838
.06
19.9
142
.51
1977
48.6
363
.72
55.8
440
.95
41.8
940
.98
51.8
750
.24
57.1
337
.78
19.6
942
.03
1978
48.3
663
.16
55.8
840
.12
42.4
240
.11
51.6
448
.66
57.3
436
.95
19.5
441
.54
1979
48.0
362
.19
55.2
339
.38
42.8
639
.28
51.1
047
.42
57.8
035
.62
19.4
241
.27
1980
47.5
961
.92
54.0
738
.76
43.0
938
.57
49.5
046
.39
58.6
634
.64
19.2
141
.14
24
Shadow
Eco
nom
yE
stim
ate
s1950-1
980
XX
XX
XX
XXX
XXX
Year
Cou
ntr
yC
entr
alA
fric
anR
ep.
Chad
Chile
Chin
aC
olom
bia
Com
oros
Con
go,
Dem
.R
ep.
Con
go,
Rep
.C
osta
Ric
aC
ote
d’I
voir
eC
ypru
s
1950
55.0
543
.70
42.5
547
.17
1951
29.2
354
.36
43.7
042
.58
46.7
7
1952
28.4
534
.06
53.9
143
.39
42.4
946
.00
1953
27.9
534
.12
53.3
842
.66
42.1
145
.30
1954
27.0
934
.00
52.7
441
.73
41.5
644
.65
1955
26.9
133
.62
51.7
141
.05
41.2
743
.06
1956
26.5
133
.47
50.7
840
.39
40.7
841
.14
1957
26.0
533
.16
50.0
439
.82
40.3
139
.49
1958
25.6
832
.90
49.5
539
.36
39.7
638
.18
1959
25.3
532
.05
49.4
139
.23
39.4
738
.02
1960
40.9
859
.59
25.2
530
.48
49.2
145
.39
39.2
768
.19
38.9
259
.37
38.3
6
1961
40.7
060
.06
24.8
329
.29
48.8
645
.03
39.7
263
.95
38.5
458
.46
38.3
8
1962
40.1
060
.52
24.5
829
.33
48.3
945
.57
40.2
361
.16
38.1
857
.45
38.0
8
1963
39.7
660
.99
24.1
629
.77
48.1
144
.66
41.2
760
.48
37.7
157
.05
37.4
1
1964
39.1
661
.36
23.5
729
.97
47.9
944
.45
41.2
860
.53
37.2
855
.84
36.7
0
1965
38.9
261
.98
23.2
829
.91
47.6
443
.85
41.1
460
.56
37.1
454
.13
36.8
8
1966
38.7
462
.58
23.0
629
.60
47.4
442
.81
41.0
159
.95
36.6
453
.01
36.4
4
1967
38.9
462
.95
23.1
929
.06
47.1
041
.20
41.0
958
.66
36.1
551
.96
36.0
5
1968
38.5
463
.20
23.1
828
.95
46.8
140
.13
41.3
357
.42
35.6
751
.28
35.5
3
1969
38.5
463
.17
23.0
928
.85
46.2
939
.68
41.5
856
.64
35.2
750
.57
35.0
9
1970
38.3
763
.35
22.9
928
.74
45.8
039
.47
41.3
156
.03
34.7
449
.56
34.3
7
1971
38.2
763
.38
22.9
328
.14
45.2
138
.59
41.0
455
.47
34.2
048
.43
33.8
0
1972
38.0
763
.49
22.8
627
.54
44.7
437
.80
40.8
354
.78
33.4
647
.49
33.2
5
1973
37.8
163
.37
23.0
427
.18
44.3
537
.14
40.5
954
.27
33.0
246
.58
32.7
7
1974
38.0
863
.55
23.3
626
.66
43.9
536
.50
40.4
953
.77
32.3
945
.66
32.1
6
1975
38.4
862
.84
23.1
326
.23
43.2
635
.92
40.4
053
.42
31.7
844
.88
31.7
4
1976
39.0
261
.51
23.4
725
.69
43.0
435
.36
40.3
853
.17
31.4
444
.08
31.9
1
1977
39.4
960
.38
23.8
025
.35
42.7
235
.30
40.3
352
.89
30.8
843
.19
32.2
0
1978
39.7
259
.88
24.0
524
.99
42.2
034
.82
40.2
952
.98
30.2
141
.69
32.0
0
1979
40.0
159
.48
24.1
824
.38
41.6
634
.47
40.3
052
.86
29.6
540
.27
31.6
6
1980
40.5
359
.32
24.2
123
.90
41.2
334
.15
40.3
052
.18
29.0
339
.52
31.1
5
25
Shadow
Eco
nom
yE
stim
ate
s1950-1
980
XX
XX
XX
XXX
XXX
Year
Cou
ntr
yD
enm
ark
Dom
ini-
can
Rep
.E
cuad
orE
gypt
El
Sal
vador
Eth
iopia
Fij
iF
inla
nd
Fra
nce
Gab
onG
ambia
1950
27.4
062
.28
64.9
351
.16
29.1
823
.68
1951
27.2
758
.40
45.7
762
.66
65.2
152
.25
29.1
323
.61
1952
27.3
758
.48
45.2
163
.02
65.2
353
.04
28.8
023
.48
1953
27.4
957
.39
45.0
763
.12
65.1
753
.68
28.3
223
.44
1954
27.4
556
.90
44.5
062
.85
65.0
253
.59
28.2
023
.50
1955
27.3
556
.52
43.5
762
.49
65.0
452
.96
27.8
223
.47
1956
27.4
055
.73
42.6
562
.14
64.9
952
.24
27.3
823
.48
1957
27.3
554
.87
41.8
962
.27
64.2
451
.87
27.0
023
.26
1958
27.2
054
.02
41.2
662
.30
63.4
151
.24
26.6
923
.05
1959
27.2
653
.29
40.8
162
.02
63.0
949
.54
26.2
422
.77
1960
27.0
253
.27
40.2
961
.51
63.3
349
.12
44.1
326
.04
22.5
976
.76
55.0
8
1961
26.6
453
.67
39.7
261
.16
62.3
247
.95
43.9
425
.58
22.2
775
.18
56.0
8
1962
26.2
754
.32
39.2
160
.41
61.7
946
.84
43.7
825
.05
21.9
472
.83
56.8
7
1963
25.8
454
.27
38.9
259
.39
61.3
445
.79
43.8
224
.58
21.5
970
.57
58.5
8
1964
25.6
353
.63
38.5
858
.32
60.7
844
.84
43.7
224
.36
21.2
369
.50
59.0
2
1965
25.2
052
.56
38.2
457
.08
59.3
944
.09
43.5
824
.04
20.8
068
.90
60.3
1
1966
24.7
453
.17
37.9
855
.91
58.5
043
.32
43.1
923
.60
20.4
268
.87
60.8
2
1967
24.3
852
.87
37.7
455
.02
57.3
642
.46
42.9
223
.16
20.0
267
.27
60.8
8
1968
24.0
052
.49
37.2
554
.64
56.8
241
.47
42.7
222
.82
19.6
467
.14
61.2
8
1969
23.6
452
.23
36.7
354
.50
56.8
440
.61
41.7
822
.58
19.2
866
.98
61.0
7
1970
23.2
151
.46
36.4
054
.22
56.7
339
.99
41.1
522
.30
18.7
766
.76
60.6
5
1971
22.8
550
.44
36.2
153
.90
56.4
639
.77
40.6
721
.84
18.4
466
.30
61.6
1
1972
22.5
449
.26
35.5
753
.73
55.7
239
.46
40.0
421
.44
18.1
765
.59
60.9
4
1973
22.2
448
.04
35.3
353
.10
55.2
639
.08
39.3
821
.20
17.9
164
.87
60.3
3
1974
21.8
746
.36
34.9
051
.56
54.4
138
.90
38.5
820
.96
17.6
465
.25
60.8
6
1975
21.5
944
.79
34.1
249
.96
53.1
638
.80
38.1
520
.51
17.3
460
.89
61.9
8
1976
21.5
143
.44
33.2
047
.84
52.3
638
.73
37.5
920
.26
17.2
657
.11
62.5
3
1977
21.3
342
.47
32.5
846
.09
51.5
238
.88
37.2
420
.07
17.2
052
.17
62.1
6
1978
21.1
741
.55
31.8
844
.68
50.0
038
.94
36.9
619
.92
17.0
649
.24
60.6
6
1979
21.0
840
.75
31.0
643
.02
48.7
339
.21
36.6
519
.93
16.8
949
.29
59.8
7
1980
20.9
439
.94
30.4
741
.23
48.1
739
.14
35.9
819
.84
16.7
448
.79
59.2
1
26
Shadow
Eco
nom
yE
stim
ate
s1950-1
980
XX
XX
XX
XXX
XXX
Year
Cou
ntr
yG
erm
any
Ghan
aG
reec
eG
uat
emal
aG
uin
eaG
uin
ea-
Bis
sau
Guya
na
Hai
tiH
ondura
sH
ong
Kon
gH
unga
ry
1950
74.3
066
.24
1951
49.2
973
.85
66.5
9
1952
49.1
673
.52
66.4
2
1953
49.6
373
.80
65.9
9
1954
49.4
173
.86
65.4
5
1955
48.0
349
.74
74.0
365
.78
1956
45.8
549
.76
73.0
865
.88
1957
43.8
649
.38
71.1
765
.90
1958
42.8
748
.92
69.5
065
.80
1959
41.9
348
.19
68.6
449
.15
66.1
5
1960
40.3
847
.37
68.1
949
.73
52.4
563
.21
66.3
233
.53
1961
38.8
346
.49
68.0
950
.09
51.1
864
.09
66.4
332
.81
1962
38.1
144
.96
68.2
950
.10
50.3
565
.08
66.7
832
.32
1963
37.4
843
.82
68.4
749
.88
49.5
165
.93
66.5
031
.35
1964
36.8
442
.59
67.9
650
.16
48.5
166
.76
66.0
030
.33
1965
35.5
741
.12
66.9
950
.33
47.6
667
.66
65.8
729
.21
1966
35.2
039
.58
66.1
650
.25
47.2
368
.54
65.4
027
.88
1967
34.9
838
.50
65.7
250
.03
46.9
969
.51
64.7
527
.05
1968
35.3
237
.60
64.9
850
.07
46.6
670
.45
63.5
926
.63
1969
35.5
836
.69
63.6
650
.15
46.4
071
.27
62.5
526
.39
1970
18.5
735
.30
35.5
063
.22
50.2
645
.93
34.8
671
.29
61.5
326
.24
32.4
4
1971
18.3
435
.25
34.4
162
.48
50.3
344
.27
34.6
071
.44
61.0
726
.09
32.0
8
1972
18.1
535
.01
33.2
861
.52
50.3
443
.24
34.5
771
.09
61.0
225
.69
31.7
9
1973
17.9
535
.51
32.2
161
.11
50.3
342
.72
34.4
970
.47
61.0
525
.29
31.5
5
1974
17.7
435
.62
30.9
460
.39
50.3
242
.67
34.2
669
.40
58.8
724
.85
31.3
2
1975
17.6
135
.31
30.3
859
.04
50.2
543
.57
33.8
167
.85
57.8
924
.46
30.9
4
1976
17.5
535
.24
29.9
758
.33
50.1
744
.30
32.7
366
.39
57.4
824
.28
30.4
5
1977
17.4
535
.31
29.4
856
.98
49.9
944
.75
31.7
564
.79
57.0
123
.82
30.0
0
1978
17.3
535
.02
29.1
955
.60
49.9
044
.70
31.3
763
.19
56.2
723
.26
29.4
8
1979
17.2
635
.41
28.8
954
.28
49.7
344
.46
31.4
561
.77
55.1
022
.91
28.8
7
1980
17.1
135
.34
28.7
853
.53
49.6
343
.58
31.0
560
.05
53.8
922
.39
28.5
2
27
Shadow
Eco
nom
yE
stim
ate
s1950-1
980
XX
XX
XX
XXX
XXX
Year
Cou
ntr
yIc
elan
dIn
dia
Indon
esia
Iran
Irel
and
Isra
elIt
aly
Jam
aica
Jap
anJor
dan
Ken
ya
1950
26.3
640
.39
27.8
740
.68
50.4
823
.68
38.3
2
1951
26.2
240
.64
27.7
640
.15
50.2
524
.12
37.8
8
1952
26.1
240
.77
27.5
238
.96
49.8
423
.99
37.3
9
1953
26.0
041
.05
27.4
537
.93
49.5
348
.40
24.0
736
.98
1954
25.7
841
.16
27.2
937
.43
48.9
947
.89
24.1
628
.02
36.5
7
1955
25.5
840
.96
31.0
627
.16
36.9
548
.46
47.2
024
.21
28.1
436
.03
1956
24.9
140
.61
31.0
726
.90
35.9
047
.60
46.4
524
.14
28.6
835
.37
1957
24.4
940
.12
30.8
226
.80
35.8
546
.70
45.6
423
.99
28.7
734
.87
1958
24.1
839
.84
30.3
326
.85
35.2
945
.76
44.4
823
.55
28.7
734
.48
1959
23.6
939
.59
29.6
826
.91
34.6
845
.05
43.5
923
.29
29.2
634
.35
1960
23.2
439
.31
32.7
829
.06
26.7
533
.99
44.1
643
.01
23.0
129
.37
34.3
3
1961
22.9
538
.66
33.0
828
.34
26.6
933
.45
43.2
642
.34
22.4
729
.19
34.3
0
1962
22.6
738
.08
33.0
827
.86
26.4
832
.82
42.1
641
.87
21.7
228
.88
34.6
5
1963
22.6
337
.45
33.1
327
.51
26.2
532
.16
41.0
141
.63
21.0
528
.38
34.9
9
1964
22.3
336
.84
33.3
727
.08
25.9
231
.72
40.0
341
.50
20.4
428
.35
35.2
2
1965
21.9
536
.15
33.5
926
.57
25.5
030
.93
39.2
541
.17
19.7
827
.83
35.6
1
1966
21.4
735
.56
33.6
625
.83
25.1
230
.13
38.7
340
.77
19.2
727
.24
35.8
8
1967
20.9
335
.09
33.7
125
.20
24.7
529
.43
38.3
340
.26
18.7
527
.32
35.7
9
1968
20.3
834
.69
33.9
024
.42
24.4
629
.57
37.7
839
.68
18.1
427
.27
35.5
0
1969
20.1
334
.41
33.9
423
.68
24.0
329
.20
37.1
938
.81
17.4
426
.99
34.9
5
1970
20.0
334
.02
33.7
223
.08
23.4
428
.45
36.5
737
.90
16.7
725
.64
34.3
5
1971
20.1
833
.64
33.2
522
.67
23.0
728
.01
35.8
637
.23
16.0
325
.62
33.5
2
1972
19.6
233
.23
32.6
122
.34
22.5
727
.41
35.3
236
.62
15.4
424
.99
32.8
8
1973
19.5
432
.97
31.8
021
.83
22.1
226
.38
34.9
726
.23
14.9
824
.12
32.4
2
1974
19.2
932
.62
30.9
721
.32
21.6
125
.72
34.4
435
.67
14.4
423
.99
31.9
3
1975
18.7
932
.28
29.9
620
.37
21.2
925
.16
33.7
535
.65
14.0
323
.38
31.5
9
1976
18.4
231
.93
29.0
219
.40
21.0
524
.75
33.6
335
.47
13.7
822
.95
31.6
7
1977
18.3
131
.59
28.1
818
.43
20.8
824
.60
33.2
935
.79
13.5
522
.32
31.6
5
1978
18.0
431
.25
27.3
017
.71
20.5
324
.43
33.0
236
.40
13.3
521
.00
31.3
6
1979
17.8
830
.79
26.4
117
.47
20.2
624
.44
32.8
836
.88
13.1
520
.05
30.9
5
1980
17.8
430
.25
25.6
617
.29
19.7
724
.15
32.6
637
.07
12.9
319
.66
30.8
6
28
Shadow
Eco
nom
yE
stim
ate
s1950-1
980
XX
XX
XX
XXX
XXX
Year
Cou
ntr
yK
orea
Rep
.L
aos
Leb
anon
Les
otho
Lib
eria
Luxem
-b
ourg
Mac
aoM
adag
as-
car
Mal
awi
Mal
aysi
aM
aldiv
es
1950
14.7
5
1951
14.4
5
1952
14.3
8
1953
65.5
914
.21
1954
66.0
413
.94
59.8
4
1955
66.7
713
.74
60.5
467
.35
1956
67.2
813
.61
59.8
267
.92
1957
68.3
413
.46
59.4
968
.23
1958
68.3
113
.22
58.1
768
.28
1959
68.6
713
.06
56.0
468
.42
1960
69.5
053
.20
12.9
341
.96
57.6
068
.85
1961
70.6
354
.50
12.7
941
.37
57.3
268
.30
1962
71.1
255
.74
12.6
341
.07
55.0
167
.70
1963
72.0
856
.67
12.4
240
.93
54.9
966
.65
1964
70.5
557
.27
12.3
040
.59
53.9
765
.56
1965
70.4
857
.52
12.1
240
.19
55.1
364
.71
1966
70.3
657
.86
11.9
839
.97
54.2
063
.71
1967
68.4
358
.01
11.8
339
.73
51.7
862
.81
1968
66.8
457
.92
11.8
039
.32
51.3
561
.92
1969
64.1
657
.88
11.8
238
.74
50.1
160
.98
1970
62.0
344
.84
29.3
857
.93
30.8
911
.91
17.2
538
.24
49.3
460
.46
56.2
3
1971
60.5
645
.35
29.6
857
.74
30.7
611
.86
17.0
537
.76
46.2
959
.41
55.2
7
1972
59.1
045
.69
29.8
657
.34
30.6
211
.79
16.8
037
.45
44.6
557
.79
54.3
3
1973
58.4
646
.34
29.6
856
.60
30.6
611
.71
16.5
537
.38
42.1
856
.49
53.4
4
1974
57.1
546
.53
29.6
255
.18
30.7
111
.61
16.3
137
.23
41.8
654
.75
52.6
8
1975
54.9
446
.94
29.6
054
.06
30.2
511
.54
16.0
737
.07
41.2
652
.29
51.9
9
1976
53.9
546
.97
29.3
552
.41
29.5
811
.51
15.8
337
.03
39.5
551
.31
51.5
9
1977
52.5
046
.55
29.6
049
.73
29.0
211
.47
15.5
937
.18
38.7
350
.30
51.2
5
1978
50.8
446
.40
29.6
746
.72
28.6
211
.50
15.3
937
.30
38.9
148
.98
50.7
8
1979
48.5
845
.98
29.7
444
.74
28.2
211
.44
15.2
237
.27
36.8
847
.84
50.1
1
1980
46.0
846
.68
29.7
742
.98
27.9
211
.45
15.0
736
.84
35.9
146
.55
49.3
6
29
Shadow
Eco
nom
yE
stim
ate
s1950-1
980
XX
XX
XX
XXX
XXX
Year
Cou
ntr
yM
ali
Mal
taM
auri
ta-
nia
Mau
ritu
sM
exic
oM
ongo
lia
Mor
occ
oM
ozam
-biq
ue
Nam
ibia
Nep
alN
ether
-la
nds
1950
33.2
148
.01
59.4
220
.27
1951
33.1
047
.98
58.4
720
.03
1952
32.9
647
.67
57.0
219
.82
1953
33.1
147
.25
56.0
619
.83
1954
32.8
546
.94
54.7
519
.73
1955
32.8
946
.49
53.5
819
.49
1956
32.7
845
.90
53.4
919
.24
1957
32.8
145
.05
53.5
718
.97
1958
32.7
244
.25
54.5
718
.70
1959
32.4
443
.71
54.2
618
.60
1960
53.8
544
.74
32.3
443
.24
54.9
649
.69
37.8
853
.69
18.4
5
1961
54.4
843
.58
31.5
442
.73
55.0
949
.86
37.7
354
.69
18.1
6
1962
55.0
141
.75
31.2
242
.24
55.5
049
.78
37.6
655
.65
17.9
5
1963
55.5
439
.75
31.0
541
.85
55.2
549
.99
37.4
456
.61
17.7
3
1964
55.7
540
.43
30.8
441
.31
54.6
750
.22
37.1
857
.43
17.5
9
1965
55.5
640
.71
31.0
340
.55
54.4
550
.35
36.9
157
.71
17.2
7
1966
55.5
840
.94
30.8
339
.72
53.9
750
.48
36.4
958
.19
16.9
9
1967
55.3
041
.35
31.1
838
.93
54.1
350
.31
35.8
458
.86
16.7
1
1968
54.9
041
.14
31.1
838
.22
53.5
850
.13
35.1
859
.40
16.4
4
1969
54.5
940
.07
31.4
737
.44
53.4
549
.65
34.5
259
.83
16.1
4
1970
54.4
142
.36
39.6
231
.43
36.9
319
.50
52.6
148
.92
33.9
060
.44
15.8
7
1971
54.3
040
.00
39.0
631
.82
37.4
919
.04
51.0
848
.17
33.0
860
.69
15.5
8
1972
54.9
638
.59
38.4
732
.13
37.1
918
.64
49.8
047
.47
32.3
560
.49
15.3
4
1973
54.1
337
.97
37.1
932
.52
36.8
318
.29
49.4
746
.74
31.7
260
.39
15.1
7
1974
53.5
937
.51
36.8
832
.10
36.3
217
.94
48.7
146
.01
31.1
859
.86
15.0
0
1975
53.2
737
.41
35.2
131
.84
35.6
717
.63
48.5
845
.43
30.6
559
.49
14.8
6
1976
52.6
837
.12
33.6
231
.00
35.0
817
.36
46.0
544
.92
30.1
858
.11
14.7
7
1977
52.0
436
.85
32.0
930
.25
34.6
617
.09
43.8
744
.38
29.7
956
.77
14.6
7
1978
51.0
536
.58
31.1
229
.65
34.3
116
.78
41.4
743
.97
29.3
555
.44
14.5
7
1979
50.0
336
.45
31.4
929
.09
33.8
716
.49
40.6
743
.74
28.9
653
.93
14.4
9
1980
49.3
135
.85
31.7
828
.40
33.2
816
.25
40.1
843
.39
28.8
753
.07
14.4
9
30
Shadow
Eco
nom
yE
stim
ate
s1950-1
980
XX
XX
XX
XXX
XXX
Year
Cou
ntr
yN
ewZ
eala
nd
Nic
arag
ua
Nig
erN
iger
iaN
orw
ayO
man
Pak
ista
nP
anam
aP
apua
New
Guin
eaP
arag
uay
Per
u
1950
16.6
455
.23
67.8
129
.56
57.3
872
.81
1951
16.4
555
.82
68.8
629
.10
58.3
256
.13
71.2
2
1952
16.3
555
.82
69.4
228
.73
59.0
256
.91
68.5
9
1953
16.3
255
.23
69.7
628
.36
59.5
657
.29
65.9
5
1954
16.3
754
.50
70.0
227
.93
59.8
657
.29
63.7
9
1955
16.1
753
.50
70.1
727
.53
60.1
257
.60
63.0
0
1956
16.0
252
.67
69.8
627
.11
60.2
658
.07
61.8
4
1957
15.9
452
.16
69.7
226
.74
60.4
758
.63
60.3
7
1958
15.8
351
.76
69.2
926
.36
60.4
258
.27
58.7
4
1959
15.7
451
.54
69.1
625
.98
60.2
958
.14
57.7
4
1960
15.6
651
.18
39.4
068
.74
25.7
259
.63
58.9
358
.14
57.7
5
1961
15.5
851
.11
39.6
968
.39
25.5
258
.19
59.4
458
.03
57.0
9
1962
15.4
550
.95
40.1
067
.78
25.2
255
.66
59.7
357
.93
56.6
0
1963
15.3
850
.43
40.1
067
.40
24.9
453
.48
59.8
958
.16
56.0
4
1964
15.3
049
.77
39.6
166
.86
24.7
251
.27
59.6
158
.35
55.6
7
1965
15.1
648
.57
39.4
866
.04
24.4
849
.42
58.8
058
.55
55.2
5
1966
14.9
547
.30
39.4
764
.50
24.1
747
.44
57.3
958
.05
54.7
6
1967
14.7
245
.99
39.5
363
.41
23.8
646
.63
55.8
657
.54
53.8
5
1968
14.5
845
.03
39.4
662
.94
23.4
445
.72
54.5
356
.77
52.9
7
1969
14.6
144
.53
39.3
762
.83
23.1
644
.79
53.2
756
.18
53.0
3
1970
14.5
443
.83
39.6
962
.53
23.0
428
.05
44.3
351
.25
55.6
152
.83
1971
14.4
543
.33
39.6
760
.57
22.7
528
.54
43.7
148
.29
55.2
553
.55
1972
14.3
542
.84
39.7
858
.94
22.6
628
.23
43.3
646
.95
54.7
054
.02
1973
14.2
943
.01
39.4
557
.34
22.3
827
.76
43.0
346
.96
53.8
554
.79
1974
14.1
242
.12
38.8
655
.55
22.0
427
.89
42.6
146
.97
52.4
354
.95
1975
13.8
140
.77
38.2
454
.55
21.7
827
.77
42.0
770
.17
46.7
850
.92
54.3
6
1976
13.7
640
.62
38.0
153
.08
21.5
727
.11
41.4
169
.11
47.1
149
.66
53.9
8
1977
13.6
840
.45
37.8
350
.86
21.2
526
.28
40.7
368
.43
45.9
248
.19
53.8
3
1978
13.6
439
.24
37.8
148
.66
20.9
525
.72
40.1
768
.44
45.0
446
.65
54.1
7
1979
13.6
939
.42
37.3
947
.12
20.8
425
.20
39.7
868
.08
44.1
944
.97
54.6
4
1980
13.6
641
.13
36.9
046
.25
20.6
924
.74
39.4
567
.97
43.0
943
.24
54.7
5
31
Shadow
Eco
nom
yE
stim
ate
s1950-1
980
XX
XX
XX
XXX
XXX
Year
Cou
ntr
yP
hilip
-pin
esP
olan
dP
ortu
gal
Rom
ania
Rw
anda
Sen
egal
Sie
rra
Leo
ne
Sin
gap
ore
Sol
omon
Isla
nds
Sou
thA
fric
aSpai
n
1950
65.1
346
.80
35.8
945
.71
1951
64.5
146
.71
35.7
645
.67
1952
64.0
746
.67
35.1
945
.59
1953
63.8
046
.54
35.0
545
.29
1954
63.1
446
.15
34.7
844
.90
1955
62.4
045
.78
34.3
844
.31
1956
61.7
045
.63
34.0
243
.66
1957
60.7
845
.47
33.7
643
.00
1958
59.6
244
.93
33.4
642
.33
1959
58.6
944
.50
33.1
341
.79
1960
57.6
144
.15
55.6
746
.22
53.0
125
.12
33.0
441
.35
1961
57.0
643
.28
55.6
746
.70
53.7
850
.16
24.6
432
.74
40.6
1
1962
56.3
042
.16
54.6
646
.95
54.3
250
.51
24.3
132
.70
39.6
8
1963
55.6
941
.53
53.8
447
.21
55.0
050
.46
23.9
932
.81
38.7
1
1964
54.8
540
.70
52.6
147
.67
55.4
549
.93
23.5
932
.68
37.7
3
1965
53.9
539
.84
51.6
747
.81
55.7
449
.34
23.3
132
.17
36.6
9
1966
53.1
238
.84
50.6
747
.89
55.9
848
.70
22.9
931
.45
35.6
7
1967
52.3
838
.01
49.6
348
.67
56.3
947
.53
22.6
931
.11
34.7
9
1968
51.5
837
.30
48.4
249
.30
56.8
647
.15
22.3
730
.39
33.9
8
1969
50.9
036
.58
47.2
349
.56
57.1
246
.85
21.9
829
.97
33.1
1
1970
50.2
335
.02
36.2
746
.18
49.9
357
.20
46.1
421
.58
38.4
829
.44
32.3
5
1971
49.7
934
.79
35.1
844
.92
50.2
256
.97
45.0
021
.10
38.8
128
.82
31.7
3
1972
49.2
934
.55
34.3
743
.57
50.1
756
.71
44.5
820
.56
38.2
628
.11
31.1
3
1973
48.8
634
.29
33.5
042
.25
50.6
956
.18
44.1
920
.07
37.7
527
.86
30.5
2
1974
48.2
633
.99
33.1
541
.01
51.0
855
.84
43.2
119
.69
37.5
027
.47
29.8
0
1975
47.4
833
.62
32.3
339
.60
50.3
455
.63
42.4
119
.09
36.6
126
.88
29.1
2
1976
46.4
833
.14
32.4
838
.07
49.4
755
.25
42.2
018
.75
36.4
226
.38
28.5
2
1977
45.3
132
.68
32.3
236
.91
48.5
255
.16
41.8
818
.39
36.1
726
.14
28.1
5
1978
44.3
732
.35
31.7
935
.45
47.1
054
.96
41.8
218
.19
35.7
126
.00
27.8
5
1979
43.4
731
.91
31.3
633
.95
46.2
455
.03
41.4
417
.96
35.4
025
.94
27.6
1
1980
42.5
531
.53
30.9
132
.87
45.3
854
.83
40.8
117
.63
34.6
725
.85
27.3
9
32
Shadow
Eco
nom
yE
stim
ate
s1950-1
980
XX
XX
XX
XXX
XXX
Year
Cou
ntr
ySri
Lan
kaSudan
Suri
nam
eSw
azilan
dSw
eden
Sw
itze
r-la
nd
Syri
aT
aiw
anT
anza
nia
Thai
land
Tog
o
1950
71.8
211
.83
1951
71.3
826
.24
11.9
075
.43
1952
70.5
326
.06
11.8
476
.26
1953
69.7
025
.91
11.8
776
.64
1954
69.3
625
.80
11.9
076
.37
1955
68.9
725
.59
11.8
776
.04
1956
67.6
125
.35
11.8
175
.88
1957
67.1
425
.17
11.6
875
.75
1958
66.6
624
.99
11.4
675
.61
1959
66.1
724
.83
11.4
375
.28
1960
65.6
424
.63
11.4
028
.41
74.5
538
.91
1961
65.3
324
.33
11.3
028
.39
73.2
939
.14
1962
65.6
524
.02
11.1
228
.21
72.0
339
.46
1963
64.2
623
.69
10.9
127
.66
71.1
939
.44
1964
63.5
723
.39
10.7
327
.40
69.9
839
.09
1965
63.0
823
.03
10.4
727
.07
68.6
937
.99
1966
62.9
622
.70
10.2
926
.98
66.7
036
.72
1967
62.6
122
.35
10.1
526
.70
64.9
236
.07
1968
62.1
622
.08
10.0
126
.50
62.5
735
.81
1969
61.5
121
.85
9.91
26.1
960
.13
35.7
2
1970
60.4
033
.12
40.6
059
.68
21.6
29.
8225
.46
58.0
578
.41
35.6
0
1971
59.1
333
.49
41.2
758
.73
21.3
39.
6825
.39
56.0
476
.41
35.0
5
1972
58.4
133
.92
41.8
958
.13
21.1
09.
5425
.28
53.9
774
.24
34.2
7
1973
57.6
434
.38
42.4
657
.16
20.9
39.
4124
.84
51.9
872
.83
33.5
5
1974
57.7
834
.55
42.5
956
.28
20.8
29.
2724
.61
50.0
771
.68
32.8
7
1975
57.2
834
.41
42.1
254
.41
20.6
89.
0224
.16
47.5
570
.57
32.1
3
1976
56.7
133
.98
41.6
453
.29
20.4
68.
9523
.43
46.1
369
.67
78.0
931
.01
1977
55.7
133
.50
41.7
351
.72
20.2
68.
9522
.44
44.6
068
.89
76.9
930
.40
1978
55.1
933
.31
41.4
949
.82
20.2
18.
9621
.50
43.3
967
.75
75.3
429
.26
1979
53.6
333
.29
41.4
247
.01
20.2
68.
9720
.89
42.0
966
.98
73.3
027
.95
1980
53.0
333
.35
41.4
945
.30
20.2
38.
9720
.54
40.6
066
.30
71.9
927
.15
33
Shadow
Eco
nom
yE
stim
ate
s1950-1
980
XX
XX
XX
XXX
XXX
Year
Cou
ntr
yT
rinid
adan
dT
obag
oT
unis
iaT
urk
eyU
ganda
Unit
edK
ingd
omU
nit
edSta
tes
Uru
guay
Ven
ezuel
aV
ietn
amZ
ambia
Zim
bab
we
1950
56.2
265
.26
60.4
818
.38
13.3
860
.67
39.3
0
1951
55.4
265
.85
60.7
318
.49
13.1
659
.67
38.3
5
1952
54.4
466
.27
60.6
118
.44
12.9
958
.25
37.4
0
1953
53.5
966
.12
59.9
618
.52
12.9
457
.31
36.2
3
1954
53.1
565
.67
59.3
518
.54
12.9
256
.99
35.2
8
1955
52.8
365
.20
58.9
218
.55
12.9
356
.03
34.3
749
.37
1956
52.0
565
.05
58.3
518
.49
12.8
255
.52
33.6
948
.23
1957
51.3
564
.54
57.9
318
.42
12.7
055
.29
33.0
046
.99
1958
50.0
263
.52
57.8
818
.30
12.6
454
.79
32.2
345
.88
1959
48.7
161
.86
57.9
018
.23
12.6
255
.03
31.7
845
.80
1960
47.3
260
.98
58.1
018
.16
12.5
855
.09
31.4
545
.60
74.2
9
1961
46.0
353
.12
60.1
258
.33
17.9
812
.50
54.9
531
.54
45.3
473
.87
1962
45.3
252
.45
59.3
058
.11
17.8
112
.44
54.6
231
.65
45.2
173
.04
1963
44.3
650
.95
58.4
357
.97
17.6
712
.37
54.5
531
.65
45.2
173
.31
1964
43.8
849
.45
57.3
957
.33
17.5
312
.29
54.6
131
.65
45.5
373
.89
1965
43.4
347
.95
56.5
156
.14
17.2
712
.20
54.8
531
.38
45.8
474
.71
1966
42.7
946
.66
55.7
855
.34
17.0
312
.04
55.1
531
.17
45.1
175
.10
1967
42.3
645
.74
54.4
454
.65
16.7
811
.87
55.4
231
.10
44.2
475
.51
1968
42.3
544
.76
53.3
253
.70
16.5
411
.76
55.5
030
.98
43.1
975
.75
1969
42.0
644
.02
52.1
552
.92
16.3
011
.67
55.8
630
.64
42.2
873
.98
1970
42.0
743
.35
50.8
051
.97
16.0
811
.56
55.8
130
.29
26.1
341
.80
73.3
8
1971
41.7
743
.19
49.7
751
.35
15.8
711
.50
55.5
329
.82
26.1
740
.30
72.5
8
1972
40.8
242
.87
49.1
350
.67
15.7
011
.44
55.2
329
.41
26.1
939
.06
71.3
2
1973
40.2
841
.95
48.3
450
.72
15.6
111
.35
55.0
629
.07
26.2
037
.90
70.2
4
1974
40.0
441
.81
47.4
650
.99
15.3
911
.22
55.0
728
.98
26.2
437
.30
69.2
9
1975
39.1
341
.18
45.5
051
.11
15.2
411
.11
55.1
528
.92
26.2
736
.24
66.7
7
1976
38.1
340
.81
44.0
351
.67
15.2
011
.11
54.8
228
.66
26.2
935
.70
64.8
8
1977
37.1
340
.30
42.8
852
.45
15.1
011
.07
54.2
528
.23
26.2
435
.98
64.4
3
1978
36.2
939
.93
42.3
153
.33
15.0
111
.01
53.3
627
.66
26.0
836
.32
63.9
3
1979
35.0
539
.48
42.0
954
.27
14.9
310
.90
52.3
427
.27
25.9
336
.75
64.6
4
1980
34.2
038
.95
41.9
954
.89
14.8
410
.77
51.0
227
.19
25.7
537
.33
66.0
4
34
Shadow
Eco
nom
yE
stim
ate
s1981-2
009
XX
XX
XXX
XXX
XX
Year
Cou
ntr
yA
lban
iaA
lger
iaA
ngo
laA
rgen
tina
Arm
enia
Aust
ralia
Aust
ria
Aze
rbai
-ja
nB
aham
asB
ahra
inB
angl
ades
hB
elar
us
1981
34.7
930
.10
39.0
422
.80
17.0
311
.01
36.9
416
.34
48.5
5
1982
34.4
229
.62
38.8
322
.77
16.8
211
.00
36.8
215
.87
48.1
1
1983
34.0
429
.20
38.8
522
.86
16.7
510
.93
36.4
016
.05
47.7
0
1984
33.7
828
.83
38.5
822
.91
16.6
510
.93
36.0
916
.03
47.2
8
1985
33.6
628
.51
38.9
422
.97
16.5
310
.86
35.9
915
.60
46.9
3
1986
33.5
628
.32
39.2
123
.22
16.4
610
.81
35.5
715
.68
45.8
1
1987
33.4
528
.36
39.6
223
.34
16.3
910
.77
35.2
315
.82
45.3
6
1988
33.4
028
.55
39.8
323
.43
16.3
010
.71
34.8
616
.01
45.0
9
1989
33.3
728
.72
40.4
223
.43
16.1
610
.63
34.6
516
.11
44.8
8
1990
33.1
128
.84
40.8
923
.92
16.0
010
.57
33.8
416
.18
44.6
9
1991
32.8
528
.99
41.3
124
.20
15.9
110
.50
32.9
816
.56
44.6
6
1992
33.3
029
.21
41.3
324
.24
15.8
810
.44
32.5
116
.46
44.4
0
1993
34.0
529
.53
41.6
224
.14
57.5
615
.80
10.3
565
.75
32.2
016
.19
43.8
8
1994
34.6
229
.86
40.5
523
.95
56.8
315
.73
10.3
565
.58
32.1
116
.56
43.3
353
.79
1995
34.9
930
.18
39.9
123
.71
55.3
515
.62
10.2
766
.08
32.0
116
.47
42.7
252
.45
1996
35.2
430
.52
42.5
123
.63
54.4
715
.51
10.1
666
.12
31.7
416
.69
42.0
851
.91
1997
35.4
230
.85
39.6
223
.49
53.5
915
.36
10.0
865
.33
31.3
316
.83
41.3
951
.32
1998
35.7
931
.18
41.5
123
.24
52.7
715
.19
10.0
164
.84
30.7
016
.89
40.6
350
.52
1999
36.0
431
.37
39.0
322
.98
51.9
814
.99
9.93
64.1
830
.03
16.6
039
.84
49.8
9
2000
36.9
731
.57
39.2
722
.92
51.4
114
.80
9.86
63.8
229
.29
16.8
239
.01
49.5
6
2001
35.7
831
.82
39.7
722
.90
50.7
414
.68
9.98
63.8
228
.58
16.8
838
.28
49.2
3
2002
35.4
431
.92
40.0
622
.96
49.8
914
.55
9.71
63.2
728
.11
17.2
637
.58
48.8
7
2003
35.1
631
.91
40.4
323
.26
48.5
914
.37
9.68
60.9
527
.68
17.3
036
.89
48.3
4
2004
34.7
531
.84
40.7
823
.41
46.9
814
.14
9.96
57.5
627
.39
17.3
236
.21
47.4
6
2005
34.2
731
.67
41.5
123
.39
45.2
413
.98
9.57
54.8
627
.21
17.1
635
.53
46.3
3
2006
33.6
431
.45
42.3
123
.28
43.2
413
.74
9.54
53.2
826
.76
17.0
434
.81
44.9
4
2007
32.9
031
.20
42.1
023
.00
41.1
013
.50
9.50
52.0
026
.20
16.8
034
.10
43.3
0
2008
32.0
630
.87
41.0
922
.64
39.0
013
.23
9.42
51.2
125
.75
16.3
233
.40
41.6
7
2009
12.9
99.
34
35
Shadow
Eco
nom
yE
stim
ate
s1981-2
009
XX
XX
XXX
XXX
XX
Year
Cou
ntr
yB
elgi
um
Bel
ize
Ben
inB
huta
nB
oliv
iaB
osnia
Bot
swan
aB
razi
lB
runei
Bulg
aria
Burk
ina
Fas
oB
uru
ndi
1981
24.9
046
.39
53.9
047
.29
62.0
352
.24
38.0
443
.65
37.7
348
.58
45.6
4
1982
24.8
146
.23
53.4
546
.77
62.2
250
.69
37.6
243
.49
36.9
147
.58
44.3
8
1983
24.7
546
.50
51.7
646
.16
63.0
448
.90
37.3
942
.19
36.2
446
.84
43.3
0
1984
24.8
046
.90
51.6
445
.24
63.7
248
.45
37.4
141
.53
35.6
846
.51
42.2
5
1985
24.7
147
.02
51.9
744
.49
64.0
448
.22
37.4
141
.71
35.1
246
.66
41.3
3
1986
24.6
947
.36
51.7
843
.69
64.1
246
.85
37.3
641
.80
34.5
045
.14
40.6
4
1987
24.6
447
.79
51.7
243
.11
64.2
246
.99
37.1
941
.81
33.8
544
.06
40.0
7
1988
24.5
847
.89
51.9
641
.90
64.4
445
.66
36.9
641
.62
33.2
443
.43
39.5
9
1989
24.4
047
.64
51.8
840
.71
65.0
248
.02
37.0
041
.26
32.5
842
.96
38.9
9
1990
24.1
746
.86
52.0
939
.81
65.7
347
.35
45.7
436
.80
40.7
532
.05
42.2
438
.63
1991
23.8
646
.25
52.3
338
.97
66.1
245
.75
43.4
737
.11
40.0
431
.40
41.6
938
.19
1992
23.6
445
.43
52.4
137
.75
66.1
644
.22
41.6
737
.37
39.1
131
.87
41.1
037
.73
1993
23.4
444
.97
52.7
436
.28
66.1
243
.00
40.8
737
.47
38.1
632
.32
40.5
637
.22
1994
23.2
844
.32
53.1
135
.35
66.1
742
.12
40.1
837
.50
37.1
432
.91
40.2
037
.04
1995
23.1
244
.36
52.9
834
.03
66.3
541
.58
39.6
137
.39
36.0
733
.42
40.2
437
.72
1996
22.9
344
.15
52.4
433
.05
66.3
341
.66
39.3
137
.08
34.9
333
.88
40.2
037
.94
1997
22.7
844
.07
52.3
932
.45
65.9
239
.39
39.4
236
.98
33.7
434
.40
40.0
138
.34
1998
22.5
744
.02
52.0
732
.30
64.9
437
.23
38.9
736
.68
32.5
334
.80
39.5
938
.72
1999
22.4
344
.10
52.0
032
.16
63.6
735
.49
37.4
636
.52
31.9
334
.98
39.5
639
.20
2000
22.2
543
.76
51.6
631
.68
63.1
134
.54
36.7
036
.50
31.7
035
.05
39.4
339
.54
2001
21.9
542
.76
51.4
531
.27
62.9
334
.11
35.6
336
.35
31.7
735
.02
39.4
339
.88
2002
21.8
142
.33
50.9
630
.37
62.9
933
.89
34.7
736
.33
31.8
834
.90
39.5
640
.35
2003
21.7
142
.01
50.7
029
.47
62.9
133
.83
34.0
136
.39
31.6
134
.63
39.8
740
.42
2004
21.6
842
.00
50.2
828
.86
63.1
133
.81
33.4
136
.57
31.5
534
.45
39.5
640
.50
2005
21.6
241
.96
49.7
428
.06
63.3
933
.43
32.2
536
.61
31.5
133
.92
39.5
340
.41
2006
21.4
442
.05
49.6
627
.73
63.4
033
.05
32.1
736
.71
31.4
233
.43
39.4
239
.95
2007
21.3
042
.00
49.1
027
.70
63.5
032
.80
31.9
036
.60
31.2
032
.70
39.6
039
.60
2008
21.0
841
.97
48.4
927
.65
63.3
432
.03
31.8
536
.42
30.8
631
.91
39.7
939
.41
2009
20.8
2
36
Shadow
Eco
nom
yE
stim
ate
s1981-2
009
XX
XX
XXX
XXX
XX
Year
Cou
ntr
yC
amb
odia
Cam
eroon
Can
ada
Cap
eV
erde
Cen
tral
Afr
ican
Rep
.C
had
Chile
Chin
aC
olom
bia
Com
oros
Con
go,
Dem
.R
ep.
Con
go,
Rep
.
1981
59.5
334
.11
19.0
741
.17
41.2
959
.25
23.9
323
.47
40.8
333
.33
40.3
750
.36
1982
60.3
933
.15
18.8
041
.06
42.1
159
.66
23.4
023
.14
40.3
133
.10
40.3
847
.33
1983
61.2
232
.35
18.7
840
.62
42.4
559
.99
23.6
722
.80
39.8
232
.69
40.4
645
.00
1984
61.8
531
.60
18.7
340
.25
42.4
059
.70
24.1
422
.38
39.4
632
.51
40.4
944
.00
1985
62.4
230
.96
18.6
139
.99
42.1
959
.30
24.3
021
.92
39.2
431
.70
40.6
043
.32
1986
63.0
630
.28
18.4
739
.73
41.9
258
.94
24.4
521
.28
39.2
331
.38
40.6
743
.17
1987
63.7
429
.71
18.3
339
.43
41.6
158
.74
24.7
020
.74
39.1
731
.43
40.7
343
.72
1988
63.3
829
.41
18.1
438
.95
41.4
758
.56
24.7
620
.24
39.0
031
.36
40.8
644
.44
1989
63.4
229
.38
17.9
338
.93
41.4
358
.21
24.7
419
.67
38.7
831
.43
41.0
845
.21
1990
64.0
429
.47
17.6
638
.77
41.3
857
.67
24.4
519
.22
38.7
031
.84
41.5
746
.00
1991
64.4
729
.63
17.4
638
.16
41.3
457
.60
24.1
518
.81
38.6
932
.06
40.5
046
.43
1992
64.3
729
.93
17.3
438
.18
41.4
657
.43
24.0
118
.40
38.7
833
.07
40.6
446
.87
1993
64.3
430
.38
17.2
837
.98
41.7
556
.55
23.7
418
.01
38.4
433
.01
41.0
347
.12
1994
63.3
530
.59
17.2
438
.08
41.8
857
.00
23.2
117
.40
37.7
233
.26
41.4
847
.35
1995
62.5
630
.84
17.1
437
.31
41.9
556
.46
22.7
416
.83
36.9
833
.39
42.5
147
.58
1996
60.8
831
.12
17.0
337
.21
42.0
657
.64
22.0
716
.21
36.1
933
.88
42.5
147
.69
1997
59.5
231
.44
16.9
736
.71
42.6
457
.49
21.5
015
.65
35.8
734
.06
42.3
147
.29
1998
58.1
531
.67
16.8
036
.41
43.0
556
.19
20.9
615
.21
35.2
534
.78
42.6
046
.86
1999
57.7
531
.85
16.6
836
.33
42.9
854
.93
20.4
514
.82
34.8
135
.07
43.3
946
.27
2000
56.1
931
.98
16.5
235
.66
43.0
055
.32
20.1
814
.42
34.8
835
.42
43.7
446
.32
2001
54.8
632
.01
16.3
235
.62
43.2
554
.83
19.9
114
.09
34.9
335
.99
45.6
546
.29
2002
53.1
531
.88
16.2
335
.45
43.4
550
.93
19.6
513
.76
34.9
336
.69
45.8
846
.07
2003
51.8
531
.81
16.1
234
.92
43.8
547
.18
19.4
813
.42
34.9
337
.29
46.2
546
.12
2004
50.3
431
.72
15.9
434
.76
44.4
646
.20
19.3
513
.04
34.7
937
.78
46.5
146
.15
2005
49.2
331
.61
15.7
434
.15
44.9
644
.69
19.0
912
.66
34.5
438
.35
46.7
146
.06
2006
47.7
531
.51
15.5
233
.79
45.2
742
.97
18.7
612
.28
34.1
138
.86
46.7
845
.52
2007
46.0
031
.40
15.3
033
.40
45.1
042
.20
18.5
011
.90
33.5
039
.40
46.7
044
.60
2008
44.3
631
.29
15.0
832
.35
45.0
341
.62
18.3
111
.53
32.8
439
.83
46.5
644
.39
2009
14.8
5
37
Shadow
Eco
nom
yE
stim
ate
s1981-2
009
XX
XX
XXX
XXX
XX
Year
Cou
ntr
yC
osta
Ric
aC
ote
d’I
voir
eC
roat
iaC
ypru
sC
zech
Rep
ublic
Den
mar
kD
omin
i-ca
nR
ep.
Ecu
ador
Egy
pt
El
Sal
vador
Equat
oria
lG
uin
eaE
ritr
ea
1981
28.4
839
.03
30.5
620
.84
39.1
929
.85
39.9
547
.98
1982
28.5
038
.75
30.2
720
.91
38.8
229
.61
38.6
447
.90
1983
28.7
139
.07
29.9
520
.92
38.7
729
.16
37.6
548
.10
1984
28.6
539
.55
29.7
020
.89
38.6
629
.26
37.0
048
.46
1985
28.7
640
.40
29.2
920
.79
38.4
829
.39
36.4
248
.79
1986
28.6
540
.88
28.9
920
.70
38.3
929
.43
36.0
949
.21
1987
28.6
741
.30
28.7
020
.39
38.3
429
.42
35.7
849
.42
1988
28.3
541
.86
28.4
120
.21
37.9
629
.49
36.0
949
.69
1989
28.1
442
.75
28.1
920
.04
37.5
329
.62
36.3
549
.73
1990
27.9
544
.12
32.6
727
.80
18.1
319
.89
37.0
429
.68
36.6
249
.44
1991
27.6
545
.23
33.0
328
.02
18.0
919
.73
36.8
429
.94
36.6
249
.71
1992
27.5
445
.69
33.2
527
.83
18.2
119
.62
36.8
029
.95
36.8
549
.77
46.9
7
1993
27.3
646
.38
33.6
127
.62
18.3
219
.46
36.5
430
.01
36.9
349
.54
47.2
6
1994
27.0
946
.58
33.8
027
.51
18.4
319
.29
36.1
730
.16
36.8
849
.17
46.5
5
1995
26.9
046
.32
33.9
927
.36
18.4
519
.21
35.7
430
.17
36.8
048
.39
44.6
7
1996
26.5
746
.07
34.1
327
.24
18.3
519
.04
35.4
030
.24
36.6
747
.36
74.4
545
.20
1997
26.7
746
.14
33.9
927
.08
18.1
718
.92
34.9
930
.39
36.5
047
.10
61.3
145
.08
1998
26.6
845
.98
33.4
927
.05
18.0
818
.66
34.4
530
.48
36.1
947
.03
52.7
742
.39
1999
26.2
345
.74
33.1
426
.97
18.0
018
.41
33.4
730
.32
35.8
746
.39
47.4
840
.71
2000
25.9
546
.27
32.9
927
.04
17.9
218
.21
32.7
730
.76
35.5
245
.85
43.4
338
.93
2001
26.0
247
.05
32.9
627
.03
17.8
217
.96
32.0
231
.11
35.2
945
.30
40.0
839
.73
2002
25.6
346
.75
32.7
526
.99
17.6
717
.75
31.4
731
.08
35.0
344
.73
36.4
639
.43
2003
25.2
347
.05
32.3
926
.95
17.4
917
.57
31.0
130
.83
34.7
844
.55
35.5
438
.80
2004
24.8
747
.23
32.0
427
.01
17.4
117
.46
30.9
530
.84
34.5
143
.93
33.4
539
.30
2005
24.7
047
.14
31.5
726
.79
17.2
817
.31
30.9
230
.75
34.1
843
.71
31.9
639
.51
2006
24.3
647
.02
30.9
626
.63
17.1
717
.15
30.8
030
.57
33.7
943
.45
31.1
440
.47
2007
24.0
047
.00
30.4
026
.50
17.0
016
.90
30.5
030
.40
33.1
043
.00
30.1
041
.40
2008
23.6
746
.93
29.7
726
.19
16.7
916
.70
30.1
130
.18
32.3
642
.71
28.8
042
.32
2009
16.6
316
.47
38
Shadow
Eco
nom
yE
stim
ate
s1981-2
009
XX
XX
XXX
XXX
XX
Year
Cou
ntr
yE
ston
iaE
thio
pia
Fij
iF
inla
nd
Fra
nce
Gab
onG
ambia
Geo
rgia
Ger
man
yG
han
aG
reec
eG
uat
emal
a19
8139
.15
35.2
519
.63
16.5
248
.78
58.3
916
.98
35.4
628
.86
53.1
9
1982
39.0
934
.49
19.5
216
.46
47.9
658
.24
16.9
635
.98
28.8
152
.65
1983
38.7
734
.27
19.3
616
.39
47.5
458
.62
16.9
636
.77
28.8
952
.64
1984
38.5
134
.31
19.2
216
.37
47.1
458
.66
16.9
237
.72
28.9
252
.86
1985
37.9
934
.49
19.0
916
.33
47.2
058
.88
16.9
038
.15
28.9
753
.07
1986
37.7
734
.55
18.9
416
.35
46.4
859
.47
16.8
738
.39
28.9
353
.57
1987
37.4
534
.51
18.7
916
.34
46.1
559
.71
16.8
238
.79
28.7
854
.14
1988
37.1
834
.84
18.6
616
.30
46.5
759
.67
16.7
839
.30
29.0
254
.36
1989
36.5
835
.32
18.5
216
.25
46.4
857
.87
16.7
239
.60
28.9
854
.48
1990
34.0
436
.08
35.7
318
.20
16.1
246
.74
56.0
016
.69
39.7
029
.00
54.6
0
1991
33.4
836
.23
34.9
917
.92
16.0
747
.08
54.9
916
.58
39.7
428
.85
54.7
5
1992
33.0
936
.63
34.5
917
.82
15.9
747
.08
53.8
216
.38
39.3
628
.84
54.4
3
1993
32.8
536
.91
34.5
417
.85
15.7
347
.38
52.2
279
.69
16.2
039
.44
28.8
553
.70
1994
32.8
336
.94
34.2
017
.95
15.9
247
.67
50.9
980
.33
16.0
839
.66
28.9
253
.31
1995
32.8
036
.91
34.0
618
.05
15.9
147
.98
50.3
079
.44
15.9
439
.66
28.9
452
.97
1996
33.0
036
.84
33.8
518
.06
15.8
948
.23
49.2
279
.06
15.8
239
.78
28.9
752
.75
1997
33.1
236
.85
33.8
018
.08
15.8
548
.52
48.4
378
.42
15.7
539
.61
28.8
252
.76
1998
32.8
936
.88
33.8
518
.07
15.8
847
.57
48.1
677
.16
15.6
939
.24
28.9
452
.45
1999
32.6
236
.81
33.2
818
.01
15.8
346
.35
47.9
775
.42
15.5
539
.05
28.7
951
.63
2000
32.6
336
.80
32.9
017
.96
15.6
146
.74
47.7
973
.75
15.4
438
.87
28.5
050
.97
2001
32.4
736
.87
32.9
217
.84
15.5
146
.74
47.2
772
.60
15.3
439
.00
28.1
350
.34
2002
32.1
136
.69
33.0
617
.69
15.4
046
.78
46.6
770
.82
15.2
738
.97
27.9
049
.77
2003
31.9
036
.32
32.9
517
.56
15.2
846
.89
46.4
369
.85
15.2
439
.08
27.7
249
.13
2004
31.3
636
.57
32.6
817
.43
15.2
647
.04
46.1
067
.90
15.2
638
.85
27.3
948
.65
2005
30.7
936
.28
32.5
717
.33
15.1
847
.16
45.0
465
.91
15.3
139
.34
26.9
248
.46
2006
30.3
635
.77
32.5
117
.15
15.0
747
.28
42.7
964
.40
15.3
338
.93
26.7
648
.35
2007
29.5
035
.10
32.6
017
.00
14.7
047
.30
40.9
062
.10
15.3
038
.30
26.5
047
.90
2008
28.7
034
.26
32.8
616
.79
14.6
347
.37
39.2
659
.93
15.2
337
.42
26.1
647
.39
2009
16.5
314
.26
15.1
425
.85
39
Shadow
Eco
nom
yE
stim
ate
s1981-2
009
XX
XX
XXX
XXX
XX
Year
Cou
ntr
yG
uin
eaG
uin
ea-
Bis
sau
Guya
na
Hai
tiH
ondura
sH
ong
Kon
gH
unga
ryIc
elan
dIn
dia
Indon
esia
Iran
Irel
and
1981
49.5
443
.62
30.7
458
.67
53.5
121
.84
28.2
517
.74
30.2
524
.82
17.3
319
.62
1982
49.4
043
.64
30.6
457
.54
53.5
021
.09
28.0
317
.59
29.8
624
.04
17.5
419
.33
1983
49.3
043
.47
30.7
856
.80
54.0
120
.56
27.8
517
.34
29.5
823
.31
17.5
719
.11
1984
49.4
343
.31
31.2
456
.05
54.3
820
.23
27.7
517
.37
29.3
722
.71
17.5
718
.94
1985
49.7
143
.43
31.5
755
.30
54.5
819
.77
27.6
617
.31
29.1
322
.17
17.6
618
.81
1986
49.7
643
.30
31.7
554
.55
54.5
919
.56
27.6
017
.27
28.7
721
.94
17.8
918
.71
1987
49.4
143
.45
32.1
254
.09
55.0
119
.29
27.5
117
.38
28.4
621
.48
18.0
018
.68
1988
48.9
543
.31
32.3
853
.72
54.9
318
.92
27.2
817
.13
28.1
721
.12
18.0
318
.65
1989
48.3
542
.83
32.9
253
.66
54.5
318
.45
27.2
016
.91
27.7
620
.79
18.1
618
.58
1990
47.9
942
.57
33.1
753
.50
54.3
618
.15
27.1
016
.81
27.3
920
.47
18.2
518
.53
1991
47.1
142
.35
33.9
254
.32
54.1
317
.86
27.0
117
.00
26.9
620
.12
18.2
518
.36
1992
46.3
742
.57
33.6
354
.28
53.6
517
.50
27.1
516
.90
26.7
219
.76
18.0
618
.25
1993
45.7
040
.39
33.5
355
.00
53.0
717
.16
27.1
316
.87
26.4
119
.44
17.8
918
.27
1994
45.0
839
.79
33.1
855
.67
51.9
216
.96
27.0
716
.91
26.1
919
.13
17.9
518
.29
1995
44.5
739
.67
33.3
356
.47
51.0
116
.68
26.9
416
.98
25.8
118
.79
18.1
118
.26
1996
44.0
739
.63
33.2
356
.52
50.3
016
.32
26.8
116
.98
25.3
318
.42
18.2
018
.15
1997
43.4
139
.35
33.0
156
.71
49.8
216
.04
26.5
816
.91
24.9
918
.05
18.2
017
.92
1998
42.8
939
.31
33.0
956
.92
49.1
315
.64
26.3
416
.93
24.6
117
.66
18.1
917
.73
1999
42.6
239
.38
33.2
357
.02
48.5
015
.37
26.0
516
.70
24.2
617
.81
18.2
117
.45
2000
42.2
639
.22
33.1
057
.03
47.7
415
.33
25.6
816
.56
23.8
317
.90
18.1
617
.11
2001
41.8
439
.64
33.6
557
.00
47.1
515
.17
25.2
116
.32
23.5
317
.96
18.1
116
.74
2002
41.7
939
.61
33.7
257
.01
46.8
215
.07
24.8
816
.09
23.2
517
.98
18.0
716
.46
2003
41.8
140
.16
33.7
657
.05
46.6
014
.98
24.6
516
.03
22.9
318
.05
18.0
016
.20
2004
41.4
040
.53
33.9
557
.07
46.3
414
.89
24.3
615
.91
22.5
318
.07
17.8
615
.98
2005
40.8
540
.90
34.0
457
.07
45.8
714
.81
24.1
115
.78
22.0
618
.05
17.6
815
.85
2006
39.9
741
.26
34.2
157
.14
45.4
914
.75
23.8
915
.49
21.3
917
.97
17.4
915
.63
2007
39.2
041
.60
34.0
057
.10
45.1
014
.70
23.7
015
.00
20.7
017
.90
17.3
015
.40
2008
38.5
141
.44
33.8
857
.05
44.4
414
.55
23.5
114
.60
20.0
017
.82
16.9
515
.12
2009
23.3
114
.34
14.9
4
40
Shadow
Eco
nom
yE
stim
ate
s1981-2
009
XX
XX
XXX
XXX
XX
Year
Cou
ntr
yIs
rael
Ital
yJam
aica
Jap
anJor
dan
Kaz
a-khst
anK
enya
Kor
eaR
epublic
Kuw
ait
Kyrg
yzs
-ta
nL
aos
Lat
via
1981
24.0
632
.25
37.5
212
.74
18.9
730
.53
44.8
847
.59
1982
24.1
031
.98
37.7
612
.58
18.0
230
.35
44.0
247
.67
1983
24.0
331
.80
37.8
512
.46
17.5
430
.41
43.0
647
.51
1984
23.8
531
.73
37.9
212
.35
17.2
230
.65
41.8
947
.69
1985
23.7
131
.54
37.8
512
.26
16.8
630
.79
40.9
548
.58
1986
23.9
131
.38
37.7
612
.14
16.9
230
.82
40.1
217
.10
48.0
9
1987
23.7
831
.17
37.9
512
.02
16.9
330
.96
39.4
316
.95
47.7
9
1988
23.8
430
.93
37.8
511
.91
16.8
230
.98
38.4
316
.73
46.8
8
1989
23.9
030
.63
37.6
411
.76
16.7
930
.94
37.4
516
.72
45.9
2
1990
23.8
930
.39
37.2
211
.60
17.1
930
.86
36.3
416
.51
46.5
0
1991
23.9
230
.07
36.8
911
.43
17.3
930
.87
35.1
815
.09
47.6
2
1992
23.5
929
.72
36.7
711
.26
17.9
031
.00
33.8
417
.35
47.1
6
1993
23.2
929
.21
36.1
411
.11
18.0
243
.78
31.2
232
.80
18.4
139
.48
46.3
835
.17
1994
23.0
529
.08
35.6
611
.00
17.8
943
.06
31.3
332
.04
18.3
539
.64
45.7
135
.07
1995
22.7
528
.98
35.2
110
.90
17.7
142
.05
31.3
931
.15
18.4
339
.61
44.8
234
.85
1996
22.3
728
.80
34.7
810
.82
17.6
042
.11
31.3
730
.28
18.7
939
.33
43.6
734
.77
1997
21.9
428
.67
34.4
110
.74
17.4
242
.38
31.3
129
.36
18.8
439
.19
43.5
834
.65
1998
21.6
528
.54
34.0
810
.64
17.2
842
.59
31.1
828
.42
18.9
939
.23
42.1
334
.26
1999
21.4
528
.38
34.0
310
.57
17.3
842
.75
30.9
428
.35
19.0
039
.29
39.2
533
.48
2000
21.2
728
.19
33.9
610
.53
17.2
942
.84
30.8
028
.09
19.0
839
.09
37.2
632
.78
2001
21.0
127
.96
33.8
410
.47
17.2
842
.82
30.5
927
.64
19.2
338
.93
36.0
332
.27
2002
20.7
727
.75
33.5
610
.41
17.3
242
.54
30.3
527
.33
19.2
438
.84
34.4
631
.66
2003
20.7
327
.53
33.3
010
.39
17.3
742
.13
30.3
426
.89
19.2
039
.10
32.6
630
.80
2004
20.7
827
.36
33.1
310
.37
17.4
341
.58
30.2
626
.57
19.0
239
.30
31.1
229
.92
2005
20.7
927
.13
32.9
210
.35
17.2
740
.90
30.1
526
.25
18.6
639
.51
29.8
428
.90
2006
20.7
427
.00
32.7
710
.33
17.2
439
.84
29.9
225
.92
18.2
639
.37
28.5
828
.11
2007
20.7
026
.80
32.5
010
.30
17.2
038
.40
29.5
025
.60
17.8
038
.80
28.0
027
.20
2008
20.6
826
.65
32.3
010
.26
17.1
337
.01
28.9
525
.26
17.0
438
.18
26.4
826
.36
2009
26.4
310
.22
24.9
0
41
Shadow
Eco
nom
yE
stim
ate
s1981-2
009
XX
XX
XX
XXX
XXX
Year
Cou
ntr
yL
eban
onL
esot
ho
Lib
eria
Lib
yaL
ithuan
iaL
uxem
-b
ourg
Mac
aoM
aced
o-nia
Mad
agas
-ca
rM
alaw
iM
alay
sia
1981
30.0
442
.14
27.6
811
.41
14.8
536
.69
35.0
945
.13
1982
29.4
341
.30
27.6
811
.36
14.6
836
.96
35.1
643
.66
1983
29.5
840
.80
27.8
011
.30
14.6
037
.37
35.2
542
.20
1984
29.6
440
.70
28.0
011
.29
14.3
937
.76
35.2
330
.97
1985
30.0
740
.29
28.3
011
.27
14.1
838
.10
35.0
439
.78
1986
29.6
839
.72
28.6
127
.68
11.3
013
.98
38.7
134
.77
39.2
9
1987
28.9
439
.56
29.1
327
.20
11.2
513
.78
39.1
135
.16
39.1
1
1988
27.9
539
.41
29.6
427
.27
11.1
713
.55
39.3
935
.87
39.0
7
1989
27.7
938
.72
30.1
227
.48
11.0
413
.26
39.3
836
.42
38.8
6
1990
27.7
937
.57
29.8
327
.58
10.9
313
.03
34.4
839
.32
36.6
038
.45
1991
28.6
936
.14
29.7
927
.69
10.8
212
.83
34.4
739
.23
37.4
037
.97
1992
30.0
234
.60
30.6
128
.14
10.6
412
.57
34.6
539
.75
37.1
136
.91
1993
30.4
233
.51
31.5
428
.63
36.3
310
.54
12.0
934
.97
40.0
037
.00
36.0
8
1994
30.4
332
.68
32.2
628
.85
36.3
010
.45
11.6
935
.19
40.2
336
.37
35.0
6
1995
30.4
231
.98
33.0
629
.10
36.3
810
.36
11.4
335
.36
40.5
436
.74
34.0
0
1996
30.1
031
.37
34.0
229
.41
36.3
510
.32
11.5
035
.31
40.8
437
.07
32.8
2
1997
29.9
830
.72
35.3
829
.76
36.0
910
.27
11.3
935
.28
40.9
637
.42
31.8
5
1998
29.9
530
.13
36.8
629
.96
35.5
110
.22
11.3
135
.15
41.0
637
.77
30.7
0
1999
30.0
429
.79
37.9
930
.45
34.9
510
.14
11.2
835
.06
41.0
138
.12
30.6
1
2000
30.3
629
.48
38.6
330
.91
34.4
410
.05
11.2
835
.10
40.9
438
.47
30.8
0
2001
30.6
829
.27
39.4
930
.86
33.9
99.
9611
.44
34.8
640
.62
38.7
230
.50
2002
30.9
829
.11
40.4
731
.14
33.4
99.
8411
.52
34.9
740
.34
38.6
130
.38
2003
31.2
228
.95
41.5
331
.21
33.1
79.
7411
.58
35.0
640
.40
38.8
930
.20
2004
31.4
328
.84
42.0
931
.28
32.1
09.
6511
.67
34.8
040
.16
39.0
430
.10
2005
31.6
428
.55
42.6
931
.27
31.1
29.
5711
.63
34.8
939
.61
39.4
729
.90
2006
31.7
028
.74
43.4
731
.08
30.3
89.
4711
.45
34.9
739
.20
39.4
229
.80
2007
32.0
028
.80
44.2
030
.90
29.7
09.
4011
.10
34.9
038
.50
39.4
029
.60
2008
32.3
628
.71
43.9
530
.69
28.8
29.
1310
.65
34.4
937
.47
39.6
929
.34
2009
9.96
42
Shadow
Eco
nom
yE
stim
ate
s1981-2
009
XX
XX
XX
XXX
XXX
Year
Cou
ntr
yM
aldiv
esM
ali
Mal
taM
auri
ta-
nia
Mau
ritu
sM
exic
oM
oldov
aM
ongo
lia
Mor
occ
oM
ozam
-biq
ue
Nam
ibia
1981
48.3
948
.62
35.8
531
.91
28.5
331
.38
16.2
339
.57
43.0
528
.19
1982
47.3
847
.78
34.9
231
.46
28.3
930
.63
15.7
939
.03
42.8
227
.74
1983
46.6
647
.42
33.6
131
.08
28.5
230
.33
15.4
138
.52
42.5
827
.78
1984
45.7
747
.47
32.8
530
.70
28.7
130
.44
15.1
538
.37
43.3
527
.96
1985
44.5
647
.07
32.1
830
.62
28.7
530
.51
15.0
138
.16
43.8
728
.14
1986
43.4
446
.91
31.7
230
.93
28.7
530
.46
14.8
237
.85
44.6
428
.63
1987
42.3
746
.19
31.4
431
.16
28.5
730
.65
14.5
937
.70
45.0
329
.58
1988
41.3
845
.72
31.1
631
.38
28.1
830
.78
14.4
737
.62
45.1
930
.10
1989
40.4
245
.05
30.6
631
.78
27.5
730
.84
14.3
537
.62
45.0
330
.55
1990
39.5
144
.48
30.2
631
.89
27.1
630
.88
14.1
537
.41
44.9
431
.07
1991
38.6
143
.89
29.6
232
.17
26.5
632
.09
14.6
536
.81
44.8
330
.31
1992
37.7
343
.76
29.0
632
.28
26.2
132
.00
44.2
514
.89
36.6
144
.73
30.5
8
1993
36.8
943
.06
28.8
633
.20
25.8
131
.80
43.3
615
.12
36.4
044
.77
30.3
7
1994
36.0
442
.74
28.4
733
.73
25.4
331
.67
42.8
715
.26
36.3
244
.61
30.8
3
1995
35.3
942
.23
28.1
334
.32
25.0
031
.42
43.1
115
.45
36.3
644
.92
30.7
9
1996
35.1
541
.80
27.7
434
.85
24.8
031
.59
43.5
715
.79
36.3
244
.54
30.8
7
1997
34.4
441
.59
27.3
935
.04
24.6
731
.68
43.8
016
.02
36.3
344
.35
30.6
8
1998
33.7
441
.38
27.0
335
.44
24.2
631
.43
44.2
416
.13
36.2
344
.02
30.8
3
1999
33.1
041
.13
26.7
835
.33
23.8
730
.97
44.8
716
.28
35.9
843
.32
30.6
0
2000
32.5
741
.50
26.5
835
.44
23.5
030
.67
45.3
516
.43
35.6
441
.69
30.5
0
2001
32.4
041
.83
26.3
535
.74
23.0
630
.19
45.6
516
.54
35.1
840
.69
30.5
3
2002
32.2
441
.50
26.4
035
.06
22.9
229
.96
45.7
616
.75
34.8
940
.14
30.2
3
2003
32.3
641
.38
26.5
634
.61
22.6
229
.69
45.7
617
.03
34.8
439
.55
30.0
4
2004
31.8
640
.80
26.5
534
.88
22.3
229
.68
45.6
117
.19
34.5
139
.18
29.4
1
2005
30.8
440
.82
26.7
133
.11
22.0
329
.44
45.2
017
.20
33.9
238
.99
29.0
8
2006
29.4
740
.37
26.6
031
.44
21.9
729
.16
44.9
816
.89
33.5
138
.69
28.9
2
2007
28.6
039
.90
26.5
031
.10
21.9
028
.80
44.5
016
.40
33.1
038
.40
28.5
0
2008
27.6
239
.41
26.3
231
.39
21.8
528
.49
43.9
415
.81
32.5
838
.13
28.0
2
2009
28.1
09
43
Shadow
Eco
nom
yE
stim
ate
s1981-2
009
XX
XX
XX
XXX
XXX
Year
Cou
ntr
yN
epal
Net
her
-la
nds
New
Zea
land
Nic
arag
ua
Nig
erN
iger
iaN
orw
ayO
man
Pak
ista
nP
anam
aP
apua
New
Guin
ea19
8152
.05
14.5
013
.69
41.1
936
.07
45.4
320
.57
24.0
539
.17
67.2
742
.01
1982
51.1
114
.50
13.6
640
.48
35.8
044
.46
20.4
523
.33
38.7
066
.45
41.3
2
1983
50.3
414
.47
13.5
939
.99
35.6
244
.16
20.3
122
.53
38.0
765
.77
40.5
8
1984
49.5
914
.46
13.5
239
.49
36.0
544
.37
20.2
621
.87
37.5
966
.34
39.9
6
1985
48.9
014
.41
13.4
339
.08
36.8
645
.07
20.1
521
.38
37.0
467
.17
39.6
4
1986
47.8
514
.35
13.8
838
.92
37.2
145
.70
20.1
220
.62
36.5
567
.42
39.8
1
1987
47.2
314
.52
13.7
938
.77
37.5
546
.36
19.9
320
.12
36.1
767
.57
39.8
7
1988
46.5
714
.50
13.6
839
.50
37.6
047
.25
19.7
520
.14
35.7
468
.04
39.8
2
1989
45.9
314
.43
13.5
740
.21
36.1
848
.24
19.5
720
.27
35.4
169
.69
39.3
6
1990
45.2
014
.36
13.5
040
.56
35.7
549
.04
19.4
720
.43
35.0
871
.32
39.4
1
1991
44.8
214
.28
13.4
141
.99
36.2
749
.57
19.4
020
.70
35.0
671
.16
39.3
9
1992
44.2
514
.20
13.4
342
.60
36.4
650
.09
19.4
120
.85
34.5
371
.14
39.0
7
1993
43.6
614
.06
13.4
543
.03
37.0
750
.65
19.4
320
.94
34.1
170
.23
39.1
2
1994
43.0
014
.03
13.4
443
.64
37.5
551
.06
19.4
620
.85
33.8
569
.01
39.5
2
1995
42.3
414
.02
13.3
743
.96
37.9
851
.56
19.4
820
.90
33.4
267
.82
39.4
8
1996
41.5
613
.97
13.2
844
.18
38.5
652
.33
19.4
720
.95
33.2
966
.27
39.2
6
1997
40.6
913
.90
13.1
544
.27
38.8
352
.98
19.4
621
.14
33.2
064
.93
38.5
4
1998
40.0
213
.79
13.0
244
.09
39.1
753
.51
19.3
220
.69
33.1
963
.82
38.4
2
1999
39.4
713
.67
12.9
343
.87
39.2
654
.07
19.0
620
.00
33.3
062
.47
38.3
8
2000
39.2
613
.56
12.8
143
.27
39.6
854
.66
18.9
119
.63
33.4
661
.37
38.3
6
2001
38.7
113
.43
12.7
343
.07
40.1
755
.01
18.7
419
.46
33.5
760
.62
37.9
2
2002
38.3
913
.32
12.6
743
.00
40.2
356
.51
18.6
519
.23
33.5
660
.50
37.4
1
2003
38.0
413
.23
12.5
543
.04
39.9
457
.91
18.5
419
.01
33.6
460
.59
37.1
9
2004
37.4
613
.18
12.4
243
.13
39.7
358
.83
18.4
818
.66
33.7
260
.53
36.9
8
2005
36.8
113
.13
12.2
743
.07
39.8
557
.72
18.3
617
.89
33.9
160
.23
36.7
9
2006
36.3
913
.06
12.1
243
.09
39.1
656
.14
18.2
017
.64
33.8
159
.77
36.5
8
2007
36.0
013
.00
12.0
043
.10
38.5
052
.80
18.0
017
.30
33.6
059
.40
36.5
0
2008
35.6
312
.91
11.8
543
.00
37.1
449
.64
17.8
116
.80
33.1
058
.65
36.0
9
2009
12.7
911
.75
17.5
1
44
Shadow
Eco
nom
yE
stim
ate
s1981-2
009
XX
XX
XX
XXX
XXX
Year
Cou
ntr
yP
arag
uay
Per
uP
hilip
-pin
esP
olan
dP
ortu
gal
Quat
arR
oman
iaR
uss
ian
Fed
era-
tion
Rw
anda
Sau
di
Ara
bia
Sen
egal
1981
41.4
354
.45
41.9
131
.10
30.2
731
.86
44.1
254
.79
1982
39.9
653
.69
41.2
930
.75
29.6
931
.23
43.6
955
.02
1983
39.2
253
.30
40.7
230
.66
29.4
030
.68
42.8
954
.75
1984
38.9
353
.77
40.1
030
.54
29.1
030
.16
41.9
854
.35
1985
38.6
454
.29
40.1
530
.41
29.0
529
.67
40.7
054
.20
1986
38.3
955
.00
40.7
730
.23
29.0
922
.73
29.2
839
.71
18.4
454
.37
1987
38.1
255
.15
41.2
429
.99
29.0
922
.75
28.9
139
.27
18.4
054
.07
1988
37.8
655
.12
41.3
629
.74
28.8
523
.03
28.6
438
.51
18.5
653
.77
1989
37.5
555
.13
41.3
129
.49
28.4
123
.18
28.4
837
.96
18.4
653
.36
1990
37.2
155
.94
41.1
429
.29
28.3
023
.36
28.4
337
.85
38.0
518
.37
53.3
9
1991
36.7
456
.48
40.8
029
.29
27.6
523
.21
28.3
636
.55
38.2
118
.33
53.0
0
1992
36.3
556
.86
40.8
429
.43
27.1
123
.23
28.5
435
.45
38.2
518
.33
52.8
7
1993
36.1
257
.22
40.6
729
.60
26.6
922
.97
28.7
935
.27
38.2
818
.28
52.4
4
1994
35.9
157
.41
40.4
929
.74
26.5
223
.01
29.0
335
.41
36.7
418
.08
51.3
8
1995
35.7
257
.10
40.3
829
.78
26.1
822
.80
29.3
535
.70
37.2
218
.09
51.4
7
1996
35.5
456
.39
40.1
529
.69
25.8
722
.16
29.6
536
.03
38.9
418
.02
51.2
2
1997
35.3
955
.96
39.8
129
.46
25.6
321
.59
29.9
736
.55
40.4
918
.01
50.6
7
1998
35.2
655
.33
39.4
329
.07
25.4
820
.84
30.2
037
.11
41.0
818
.07
49.6
6
1999
35.4
254
.78
39.2
628
.57
25.0
520
.50
30.5
537
.79
41.2
718
.07
48.7
7
2000
35.4
654
.52
39.0
928
.13
24.6
320
.61
30.8
338
.53
41.5
317
.67
47.5
9
2001
35.7
454
.46
38.9
927
.68
24.2
720
.52
31.0
039
.09
41.4
617
.57
46.3
7
2002
35.9
354
.55
38.8
527
.37
23.9
120
.08
30.6
739
.55
41.3
417
.56
45.2
7
2003
36.2
554
.59
38.7
727
.12
23.6
319
.91
30.6
539
.95
41.1
417
.54
44.8
0
2004
36.5
154
.56
38.6
826
.97
23.4
519
.05
30.7
640
.25
40.8
717
.39
43.9
3
2005
36.7
554
.43
38.4
226
.72
23.3
018
.40
30.5
340
.48
40.5
117
.27
43.2
3
2006
36.9
554
.26
38.3
426
.39
23.1
417
.14
30.5
540
.62
39.8
217
.03
42.3
4
2007
37.1
053
.70
38.3
026
.00
23.0
016
.74
30.2
040
.60
39.0
016
.80
41.7
0
2008
37.1
952
.76
38.1
725
.50
22.8
416
.11
29.6
040
.25
37.9
716
.61
40.8
5
2009
25.9
622
.62
45
Shadow
Eco
nom
yE
stim
ate
s1981-2
009
XX
XX
XX
XXX
XXX
Year
Cou
ntr
ySie
rra
Leo
ne
Sin
gap
ore
Slo
vakia
Slo
venia
Sol
omon
Isla
nds
Sou
thA
fric
aSpai
nSri
Lan
kaSudan
Suri
nam
eSw
azilan
d
1981
39.9
217
.31
34.0
125
.54
27.2
552
.25
33.9
841
.76
44.3
8
1982
39.6
617
.03
33.4
025
.05
27.1
651
.44
33.3
941
.98
43.6
1
1983
39.4
216
.59
32.7
525
.03
27.1
250
.78
33.2
842
.80
42.9
7
1984
39.3
016
.16
32.8
124
.93
27.0
750
.16
33.4
143
.50
42.5
7
1985
39.4
515
.54
32.3
624
.84
26.9
849
.67
33.7
744
.28
41.9
6
1986
39.4
815
.22
31.5
624
.90
26.8
549
.20
34.1
444
.73
41.6
7
1987
39.5
115
.10
19.0
231
.23
25.0
726
.79
49.0
134
.34
44.8
241
.90
1988
39.8
514
.98
18.7
531
.34
25.3
126
.59
48.7
734
.37
45.2
442
.34
1989
39.5
814
.96
18.4
830
.53
25.4
426
.22
48.7
134
.49
45.9
141
.95
1990
39.3
214
.87
18.2
527
.68
30.6
325
.48
25.8
548
.70
34.6
846
.38
41.3
2
1991
39.2
214
.68
17.7
627
.76
30.9
325
.68
25.4
848
.58
34.8
546
.39
41.1
3
1992
39.0
914
.54
17.6
127
.92
30.6
525
.85
25.1
648
.41
35.0
646
.53
41.0
1
1993
38.6
114
.31
17.6
528
.13
30.8
026
.11
24.9
948
.29
35.1
146
.37
40.0
8
1994
39.4
014
.04
17.7
428
.79
31.3
926
.40
24.8
747
.95
35.3
146
.13
39.5
3
1995
38.7
213
.80
17.8
628
.85
31.0
426
.51
24.6
947
.37
35.4
945
.14
39.2
8
1996
39.0
713
.63
17.9
228
.54
31.1
326
.44
24.5
647
.13
35.1
545
.31
39.1
2
1997
39.2
113
.37
17.8
028
.40
31.2
626
.39
24.4
246
.82
35.3
145
.04
38.7
2
1998
39.9
312
.93
17.6
428
.17
31.2
326
.38
24.2
046
.99
35.2
145
.10
38.5
9
1999
40.5
712
.80
17.5
427
.72
31.3
226
.33
23.9
446
.26
34.1
044
.61
38.4
0
2000
41.4
812
.66
17.5
127
.17
31.5
726
.30
23.7
745
.57
33.6
842
.95
38.6
0
2001
41.9
012
.35
17.5
226
.74
31.8
926
.25
23.4
345
.09
33.1
941
.81
38.5
4
2002
47.8
412
.25
17.3
926
.45
32.2
426
.21
23.2
544
.93
31.9
240
.65
38.2
3
2003
52.4
512
.16
17.3
026
.01
32.3
926
.13
23.0
844
.70
28.9
439
.45
38.2
0
2004
51.0
812
.32
17.3
025
.86
32.5
425
.96
22.8
744
.25
27.7
438
.25
38.1
6
2005
48.4
212
.28
17.1
625
.45
32.2
625
.73
22.6
743
.62
26.7
037
.06
37.9
3
2006
47.4
612
.26
16.9
825
.08
32.4
625
.50
22.4
543
.11
25.1
735
.86
38.2
0
2007
42.9
012
.20
16.8
024
.70
32.7
025
.20
22.2
042
.20
23.9
935
.10
38.5
0
2008
39.1
512
.13
16.5
724
.11
31.6
724
.87
22.0
141
.31
22.9
734
.25
38.8
9
2009
16.3
421
.87
46
Shadow
Eco
nom
yE
stim
ate
s1981-2
009
XX
XX
XX
XXX
XXX
Year
Cou
ntr
ySw
eden
Sw
itze
r-la
nd
Syri
aT
aiw
anT
aji
kis
tan
Tan
zania
Thai
land
Tog
oT
rinid
adan
dT
obag
oT
unis
iaT
urk
ey
1981
20.1
18.
9119
.99
39.2
965
.95
70.9
726
.66
33.0
338
.56
41.6
1
1982
20.1
18.
8619
.55
38.2
465
.85
70.0
426
.64
32.1
237
.88
41.1
4
1983
20.1
18.
8319
.19
37.7
265
.85
69.3
226
.86
31.5
337
.30
40.8
8
1984
20.1
18.
8218
.84
37.1
866
.49
68.1
827
.18
31.0
637
.14
40.7
2
1985
20.0
68.
7918
.65
36.5
467
.00
67.1
727
.72
30.7
536
.59
40.4
6
1986
19.9
18.
7718
.46
36.3
367
.04
66.4
527
.92
30.5
836
.30
40.2
0
1987
19.8
38.
7318
.43
36.0
166
.96
65.9
728
.18
30.5
636
.28
39.8
6
1988
19.7
48.
7018
.64
35.1
966
.25
65.1
728
.70
30.7
536
.43
38.9
6
1989
19.6
28.
6618
.76
34.2
365
.31
63.8
928
.98
31.1
536
.80
38.4
3
1990
19.4
38.
6219
.05
33.2
264
.19
62.1
828
.97
31.7
237
.11
37.7
7
1991
19.1
88.
6319
.24
32.4
562
.35
59.7
828
.98
31.8
437
.15
37.1
1
1992
19.0
38.
5519
.46
31.7
461
.28
57.4
829
.48
32.1
737
.32
36.5
6
1993
18.9
08.
5119
.51
30.8
537
.58
60.5
155
.46
29.7
632
.26
37.1
835
.54
1994
18.9
58.
4819
.58
30.0
735
.77
60.2
853
.58
30.4
833
.00
37.0
535
.02
1995
18.9
78.
4219
.52
29.2
735
.02
60.0
352
.08
31.0
033
.40
37.1
734
.77
1996
18.9
18.
3719
.41
28.5
034
.68
60.1
450
.50
31.4
034
.03
37.2
834
.20
1997
18.8
38.
3219
.33
27.8
734
.87
60.1
649
.10
31.8
133
.93
37.2
433
.58
1998
18.7
58.
3019
.30
27.1
835
.74
60.2
348
.33
32.0
633
.54
37.1
433
.02
1999
18.6
88.
2419
.27
26.5
536
.30
60.1
048
.62
32.2
733
.17
36.9
932
.53
2000
18.6
18.
2119
.26
26.0
237
.24
59.9
648
.98
32.5
633
.31
36.7
831
.96
2001
18.4
88.
1919
.27
25.4
538
.01
59.7
649
.18
32.8
333
.29
36.5
531
.56
2002
18.3
58.
1719
.22
25.3
338
.75
59.3
049
.32
33.2
033
.06
36.1
931
.61
2003
18.2
78.
1519
.08
25.0
139
.40
58.5
249
.37
33.4
433
.12
36.0
231
.36
2004
18.1
88.
1318
.90
24.7
839
.93
57.7
649
.28
33.8
033
.09
35.8
031
.20
2005
18.1
58.
1118
.74
24.4
540
.42
56.3
948
.98
33.9
933
.18
35.5
530
.82
2006
18.0
18.
1118
.41
24.1
440
.79
55.1
148
.49
34.2
231
.94
35.5
830
.26
2007
17.9
08.
1018
.50
23.9
041
.00
53.7
048
.20
34.5
031
.50
35.4
029
.10
2008
17.6
58.
0818
.40
23.6
540
.97
52.5
247
.90
34.7
131
.27
35.2
728
.63
2009
17.3
88.
0723
.51
27.6
8
47
Shadow
Eco
nom
yE
stim
ate
s1981-2
009
XX
XX
XX
XXX
XXX
Year
Cou
ntr
yU
ganda
Ukra
ine
Unit
edA
rab
Em
irat
es
Unit
edK
ingd
omU
nit
edSta
tes
Uru
guay
Ven
ezuel
aV
ietn
amY
emen
Zam
bia
Zim
bab
we
1981
55.4
814
.80
10.7
049
.72
27.2
725
.66
37.6
366
.51
1982
55.3
114
.81
10.6
048
.90
27.3
325
.54
38.1
765
.39
1983
54.9
914
.78
10.5
748
.53
27.4
225
.39
39.1
364
.66
1984
54.7
514
.78
10.5
548
.77
27.8
925
.22
39.9
265
.46
1985
54.8
014
.72
10.4
249
.13
28.2
025
.00
40.8
865
.99
1986
54.7
126
.04
14.6
310
.32
49.6
228
.48
24.7
741
.62
66.1
5
1987
54.4
325
.56
14.5
810
.23
49.9
628
.71
24.5
942
.47
65.9
8
1988
53.7
025
.34
14.5
110
.14
50.1
228
.84
24.3
543
.43
66.7
4
1989
53.0
325
.27
14.3
510
.07
50.3
528
.98
24.1
434
.38
43.9
766
.01
1990
52.4
425
.23
14.1
79.
9950
.67
29.5
124
.06
34.0
044
.57
66.1
8
1991
51.9
225
.12
13.9
99.
9050
.89
29.9
823
.66
33.6
944
.88
65.8
4
1992
51.4
625
.04
13.9
09.
8750
.89
30.1
323
.42
33.8
145
.99
65.1
6
1993
51.1
445
.05
24.9
613
.82
9.81
50.5
530
.08
22.8
833
.21
47.7
464
.75
1994
50.8
443
.89
24.9
313
.74
9.76
50.0
630
.25
21.9
832
.97
48.2
565
.60
1995
49.8
143
.18
24.7
813
.64
9.66
49.4
830
.58
21.1
532
.69
49.0
663
.38
1996
48.6
343
.54
24.6
113
.55
9.57
48.8
830
.74
20.3
332
.07
49.5
162
.25
1997
47.7
043
.91
24.4
413
.46
9.49
48.4
230
.92
19.5
031
.09
50.1
462
.22
1998
46.8
244
.81
24.2
213
.33
9.36
47.9
030
.90
18.8
030
.00
50.7
962
.14
1999
45.9
645
.55
24.1
013
.19
9.22
47.1
830
.86
18.1
729
.31
51.3
361
.36
2000
45.2
246
.26
23.9
913
.04
9.10
46.7
531
.00
17.6
129
.08
51.8
661
.32
2001
44.6
846
.76
23.9
212
.89
8.94
46.5
931
.00
17.1
628
.73
51.7
160
.59
2002
44.1
546
.88
23.8
512
.76
8.83
46.5
030
.96
16.6
728
.37
51.6
860
.31
2003
43.5
746
.77
23.8
012
.63
8.75
47.0
031
.25
16.1
828
.25
51.2
261
.49
2004
42.8
746
.75
23.6
912
.50
8.67
47.3
531
.70
15.7
127
.96
50.6
562
.61
2005
42.1
046
.90
23.5
612
.43
8.59
47.4
531
.74
15.2
727
.81
47.6
561
.21
2006
41.1
946
.97
23.3
312
.34
8.50
46.8
131
.52
14.8
427
.17
45.4
762
.38
2007
40.3
046
.80
23.0
012
.20
8.40
46.1
030
.90
14.4
026
.80
43.9
062
.70
2008
39.3
846
.18
21.8
612
.02
8.32
45.2
530
.19
13.8
926
.47
42.0
862
.75
2009
11.9
48.
24
48