metadata: authors: 0: author: Azam, Jean-Paul
1: author: Guillaumont, Sylviane
docna: 0: docna: Methodological problems in cross-country
            analyses of economic growth
docty: Policy Research Working Paper
subtopic: Economic Theory & Research,Economic Conditions and Volatility,Industrial Economics,Economic Growth,Inflation,Global Environment
teratopic: Poverty Reduction
abstracts: cdata!: Many cross country studies have been
            conducted over the last twenty years to explain how various
            factors affect economic growth rates in the developing
            countries. The data in these studies - which underlie
            international economic comparisons and serve as the basis
            for economic policy recommendations - give researchers the
            systematic and scientific information required for their
            investigations. But the conclusions are often fragile and
            sometimes contradictory. This paper finds that research
            results are sensitive to the choices of components, the aim
            of the investigation, and the type of model used. In
            general, researchers need to have better statistical data,
            particularly on economic policy indicators, and must subject
            the selected sample to careful tests. Cross-country studies
            are particularly unreliable when it comes to estimating the
            economic impact of government budgetary and regulatory
            policies. These studies thus provide only a weak basis for
            developing country economic policies.
repnme: repnme: Methodological problems in cross-country
            analyses of economic growth
display_title: Methodological problems in
            cross-country analyses of economic growth
listing_relative_url: /research/1988/06/700697/methodological-problems-cross-country-analyses-economic-growth
topicv3: Macroeconomic Vulnerability and Debt
            m1326057 1104,Economic Growth m1326241 471,Inflation m1326709 0870F4727ACED1CF8525815C00471347,Environment, Natural Resources and Blue
            Economy m1327391 566,Population, Aging and Health m1327736 640
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: Poverty Reduction
origu: Policy Plan & Prog Review Dept
no_of_pages: 66
model_extractions: <!-- Start of picture text --> Polay nning, and Rewh<br>Soc10oocnonW10 Data<br><!-- End of picture text --> Many cross-country studies have been conducted over the last 20 years to explain how various factors affect economic growth rates in the developing economies. The data in these studies - which underlie intemational economic comparisons and serve as the basis for - economic policy recommendations give researchers the systematic and scientific information required for their investigations. But the conclusions are often fragile and sometimes contradictory.

Research results are ser.sitive to the choices of components, the aim of the investigation, and the type of model used. In general, researchers need to have better statistical data, particularly on economic policy indicators, and must subject the selected sample to careful tests.

Cross-country studies are particularly unreliable when it comes to estimating the economic impact of government budgetary and regulatory policies. These studies thus provide only a weak basis for developing country economic policies.

This paper is a product of the Socioeconomic Data Division, Intemational Economics Department. Copies are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Estela Zamora, room S7136 extension 33706.

The PPR Working Paper Series disseminates the findings of work under way in the Bank's Policy, Planning, and Research Complex. An objective of the series is to get these rmdings out quickly, even if presentations are less than fully polished. The findings, interpretations, and conclusions in these papers do not necessarily represent official policy of the Bank.

Copyright / 1988 by the International Bank for Reconstruction and i>elopmentmThe World Bank
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# Table of Contents

# 1. Choices Concerning the Dependent Variable: Characteristics of the Sample

- 1.1 Choice of aggregate used to measure growth

- 1.1.1 Domestic or national product

- 1.1.2 Data sources

- 1.1.3 The choice of the base year

- 1.2 Choice of countries and periods

- 1.2.1 Country sets Sets and subsets Aberrant data points and weighting

- 1.2.2 Choice of period

- 1.2.3 Data pooling

2. Choice of Independent Variables: Characteristics of the Model

- 2.1 Choices concerning definition of variables

- 2.1.1 Classification and nature of variables 2.1.2 Measurement and international comparability of variables

- 2.2 Combination of variables

- 2.2.1 Relative impact of economic policy variables and environmental variables

- 2.2.2 Transmission mechanisms and levels of analysis Productive factor models Upstream models Reduced equations or structural models

Conclusions Bibliography List of Tables

# ACKNOWLEDGMENTS

The authors wish to thank J. Baneth, D. Cies ;kowsky, J. de Melo, A. Kundu and J. O'Connor for their assistance in the preparation of this work and Mr. Bouchut for his help in processing the data. They are particularly grateful to Bela Balassa for having taken the trouble to help improve the English version of this paper.
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# Crosi-sectional Analysis of Factors Affecting Growth in Developing Countries: Examination of Methodological Problems

A large number of studies of international cross-sectional data have been conducted during the lost 20 years in an attempt to explain the growth rate or other variabies in the developing economies. The purpose of these studies is to permit scientific comparison of national experiences, as the basis for policy recommerdations. In the absence of systematic and scientific international comparisons, judgments are likely to be based only on partial comparisons and subjective evaluations. Moreover, if international cross-sectional studies are to serve for economic policy, their conclusions must be solidly established. Yet it seems that, in the present state of the literature, these conclusions are relatively fragile and sometimes contradictory.

The conclusions depend on the methodological choices made. What definition is used for economic growth? Is it measured over a long or a short period? Does the investigation concern all countries or a homogeneous subset? Does it seek to evaluate all factors affecting growth or, on the contrary, to bring out the impact of some particular factor? Is the aim to measure the overall impact of one or another factor or to identify the mechanisms through which it affects growth? Is this done using a reduced form model or a structural model?

The purpose of the present work is obviously not to resolve all the methodology problems posed by cross-sectional studies. Nor is it to present an exhaustive balance sheet of the cross-sectional analyses that contribute to knowledge of factors affecting growth and of the efficacy of economic policies. Our analysis is based on some 30 cross-sectional studies selected using various criteria. The reference studies used here are recent studies (since 1982), written in English or French, that directly explain growth (excluded are studies designed solely to explain certain factors affecting growth, such as the saving rate, the investment rate, the rate of export growth, etc.). The reference studies, moreover, either use a large range of independent variables or display originality in the choice of factors affecting growth or in the way they have analyzed them (cf. table 1).

The methodological questions posed by cross-sectional analysis have been grouped into two categories. The first series of questions concern the choice of the dependent variable (i.e. the growth indicator adopted), the countries and the period over which it is measured, that is, the characteristics of the sample. The second series of questions concern the independent variables, i.e. their selection, their
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measurement and the way in which they have been introduced into the explanatory model, that is, the characteristics of the model.

1. Choices Concerning the Dependent Variable: Characteristics of the Sample

The literature is characterized by a wide variety of choices with respect to the aggregate whose growth is studied, the set of countries and the period for which the estimate is made. The justification for these choices is not always clearly stated. Yet they can affect the econometric results and the conclusions of the analysis. Some aspects of this sensitivity will be illustrated with the help of a simple model applied to different measures of the dependent variable.

This model, without any claim to originality, adopts five independent variables from among those currently used in the literature. Three of them reflect economic policies (inflation rate, public expenditure share of GDP, and rate of es 7 .h of goods and services exports weighted by the share of these i l in GDP). The other two (initial GDP per capita and populaL.. correspond to fundamental economic data that are independent of lh.1 economic policy followed during the period. We therefore estimated as follows: in which the dot over the variable represents the time-derived variable, N - population, P **=** general price level, C - public expenditure, X - goods and services exports, and u - a random disturbance. Y represents product, defined differently depending on the case.

# 1.1 Choice of aggregate used to measure growth

# 1.1.1 Domestic or national

Most of the studies use GDP. A few, however, prefer GNP (Balassa 1986, Devarajan and de Melo 1987, Kavoussi 1984, Moran 1983, Ram 1985, Venieris and Cupta 1983). One study uses both aggregates together (Kormendi and Meguire 1985). (Cf. table 1, column 2). The choice of one or the other aggregate is justified by the purpose of the study. If the purpose is to study the growth of economic activity, GDP is appropriate; if, on the contrary, it is rather to ascertain what affects the trend in living standards, GNP seems appropriate. In the latter case, moreover, the choice of another aggregate may be justified (e.g. national expenditure, or perhaps national product, corrected for.' evolution of the terms of trade, etc.).
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The difference between CDP and GNP consists of net factor income payments. Consequently, the greater the change in share of factor income payments in the product, -he greater the difference in growth rate of the two aggregates for a given councry. It is probable that in the late 1970s and early 1980s the gap was appreciable and varied with the evolution of interest payments (and of income remittances of migrant workers who had remained residents of their country of origin).

Table 2 compares average annual growth rates of CDP and GNP calculated on the basis of the World Bank's World Tables. The absolute gap between the two rates exceeds 0.52 in only 9 cases out of 85 during the period 1970-81, and 15 cases out of 86 in 1974-81; it exceeds 1% in t.nly 3 cases and 5 cases, respectively, over these two periods. The difference is therefore less important than might have been supposed. This result is perhaps due to poor estimation of the trend of factor income payments.

The illustrative model was estimated using' the two definitions of product (cf. results, table 3, equations 1 and 2). The model explaining GDP growth is seen to be a little better than the model explaining GNP growth. This may result from the greater risk of error in GNP estimates due to poor knowledge of international factor income payments or to the fact that the independent variables are less well adapted to explanation of CNP growth than of CDP growth.

# 1.1.2 Data sources

Most of the studies use World Bank data to measure product. However, a few use IMF data (Fry and Lilien 1986, Kormendi and Meguire 1985, Landau 1986, Lanyi and Saracoglu 1983, Rana 1987) and others, United Nations data (Venieris and Gupta 1983). Some authors have also used the data of the project of international comparison of products on the basis of purchasing power parities (Landau 1983, based on Kravis 1979, and Ram 1986, based on Summers and Heston 1984). Finally, some studies do not specify the data source (cf. table 1, column 2).

The choice of source is not without importance for the measurement of growth, as is evident in various studies. This is shown by Ahmad and Kwon (1981) for the difference between IMF and World bank data, and Plane (1986) for the difference between World Bank and UNCTAD data. We have tried to assess the magnitude of the difference between the two rates calculated using World Bank and IMF statistics for GDP at market prices over the period 1970-81 (see table 2). The differences between these two rates are found to be greater and more frequent than the differences previously observed between GDP and GNP growth rates: over the period 1970-81 the absolute gap exceeds 0.5 in 14 cases out of 55 and 1Z in 9 cases; over the period 1974-81 it exceeds 0.52 in 18 cases out of 37 and 12 in 11 cases; in some countries (Honduras, Malaysia), it is substantial.
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The difference between World Bank and other statistics seems to result chiefly from the fact that adjustments are effected at the World Bank. Some of these adjustments are intended to correct for the fact that the method of preparing the accounts does not always conform to the United Nations standard system or for inconsistencies in the accounts. Other, more delicate, adjustments take account of country economists' opinions concerning the reliability of the official data. Subject to the quality of these adjustments and uniformity of the principles underlying them, it seems preferable to work with the World Bank statistics. The advantage of the other series is that they are available more rapidly and more regularly.

As the illustrative model shows (cf. table 3, equations 3 and 4), the coefficient of determination is in fact a little better using the World Bank data.

The use, still rare, of the statistics of the international comparison project, perfectly justified for comparing standard of living leveis and trends, is much less justified for measuring economic efficiency through growth of product. This efficiency cannot be judged in each country without taking into account the structure of costs and scarcities, which is reflected in the country's price system.

# 1.1.3 The choice of the base year

The growth rates are calculated on CDP series measured at constant prices. The base year in which these series were originally established naturally varies from country te country. The series of aggregates published by the international agencies, including the World Bank, have used a base year varying with the country, which nevertheless, as we have seen, ensured a certain harmonization of the statistics. The next edition of the World Tables will present aggregates on a uniform base year for all countries, the year 1980. These data could not be used up till now and all the cross-sectional analyses of growth studied here use series established on base years varying from country to country. This practice raises a problem that has been ignored by all of the studies examined.

For example, ths price system that can be used to aggregate the various branches of activity differs greatly, depending on whether we are dealing with the pre- or post-oil shock period. In an oil-producing country, the weight given to growth of the mining sector differs widely according to whether the base is prior to or subsequent to the oil shock. If the growth of the mining sector differs from that of the rest of the economy, this results in a difference of evaluation of overall growth, depending on the base adopted. 1/ The problem arises when a country's growth is relatively highly conce-trated in a sector whose production is subject to wide variations in relative prices and grows at a different rate from the rest of the economy. This was true of the mineral producing countries, particularly those that were new producers or, on the contrary, declining producers during the period.
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In order to assess the practical importance of the choice of base year, we proceeded to carry out 12 partial rebasings, recalculating CDP series at constant prices on the basis of value added series at constant prices, broken to n into 12 sectors, derived from the World Tables 1984. For tha* rpose we established a deflator for each sector, the prices of a~, year serving in turn for calculation of a global product series whose base was the correspondi-g year. 2/ In this way we were able to calculate for the period 1970-81 and for 73 countries, by regression, average annual growth rates on the basis of each of the years (i.e. 12 average growth rates per country). In more than half the cases (39 countries) tne gap between the maximum and minimum rates exceeds 0.5%. For 22 countries it exceeds 1%. In some cases, most of them oil-exporting countries, it is substantial (Nigeria 7.2%, Iran 4.2%, Congo 2.9%, etc.).

The illustrative model was estimated using the growth rates calculated for various base years for a sample of 40 countries. It was found first of all that the coefficient of determination varies between 0.54 and 0.62, the best estimates according to this criterion being obtained, curiously, by using as bases the years following the two oil shocks (1975, 1976, 1980, 1981). We next note that the value of the coefficients estimated hardly changes with the base year (with the exception of the constant) but that the "Student's" value for t changes appreciably. For example, the share of public expenditure in GDP, which is practically never significant, becomes so (at the 10% threshold) in base 1980. Thus, if the choice of the base year does not seem to entail any bias in estimating the coefficients, it can skew the selection of independent variables.

In brief, it is found that growth measurements differ substantially, depending on the base year adopted and the source used and, to a lesser degree, on the nature of the aggregate adopted. But, in conformity with the econometric theory of measurement errors (for example, Stewart and Wallis, 1981), the differences in the measurement of the dependent variable have little effect on the results of the econometric estimates of the factors affecting growth.

# 1.2 Choice of countries and periods

The cross-sectional analyses of economic growth are based on a wide variety of country sets and a wide variety of periods (cf. table 1, columns 2 and 3). The choices made result logically frm the nature of the question posed; however, they are very often constrained by availability of statistics.
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# 1.2.1 Country set

The estimation of an econometric equation using the data for a set of countries assumes that the relationship studied does not differ significantly between the countries of the sample. In other words, as far as we are concerned here, it assumes that the differences between the observed growth rates are explained by the different values assumed by the independent variables for the various countries.

This implicit hypothesis of structural homogeneity of economic relationships would call for systematic tests. But the econometric studies using cross-sectional data are generally accompanied by a much more limited number of diagnostic tests than the studies done using time data. Most of the customary software produces, for example, the Durbin and Watson statistic, which has no clear significance in cross-sectionul analysis. However, the pertinent tests for this type of research, such as the coefficient stability test between two subsamples due to Chow (1960), or the homos- 'sticity tests that bring out the variability of the residual variances between the different observation points -- and therefore that of the coefficients, according to Breush and Pagan (1979) -- generally call for supplemental work by the investigators. They would therefore be very helpful for justifying econometric analysis using cross-sectional e3ta by means of a given model or, on the contrary, for excluding .ertain countries from the sample.

Whereas including a country in a sample implies the hypothesis of homogeneity, the fact of excluding a country does not necessarily imply a hypothesis of structural heterogeneity. It may simply reflect the investigator's tastes or limits on the availability of data. To be tested, the homogeneity hypothesis requires that the model be estimated with and without the countries in question.

Howe;er, the econometrician is tempted to include the largest possible number of observations in the sample in order to have sufficient degrees of freedom to apply statistical tests under satisfactory conditions. The temptation to do 3o can sometimes conflict with the homogeneity requirement stressed earlier. It can also be pointed out that the exclusion of a country from the sample used (taking into account the cost in terms of degrees of freedom that that implies) might reveal an implicit heterogeneity hypothzsis. Cenerally speaking, however, the literature does not contain detailed justification of the choice of the sample analyzed, and a wide variety of criteria have been applied.

# Sets and subsets

Cross-sectional analyses of growth are generally based on a sample composed exclusively of developing countries (cf. table 1, column 3). However, some studies include industrialized countries in the sample (Fry and Lilien 1986, Genberg and Swoboda 1987, Hwa 1983,
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Kormendi and Meguire 1985, Landau 1983, Marsden 1983, Ram 1986, Venieris and Cupta 1983). This implies a homogeneity hypothesis whose significance can be 'ariously interpreted, ecg. according to the nature of the independent variables concerned. For example, the impact of initial per capita product on growth rate can vary with level of development: whereas the catch-up hypothesis, implying a negative impact, may be more apt when a certain level of development is attained; below that levei a lower per capita income can mean a handicap, associated tor example with a lower human capital, and hence a positive impact. The literature in fact contains both positive and negative results, depending on the composition of the sample: a negative impact when the developed countries are included (Kormendi and Meguire 1985), positive with only the developing countries (Singh 1985) but also negative with only the developing countries (Landau 1986). An econometric solution to this problem can be sought in the estimation of ..onlinear relationships, following Chenery and Syrquin. This alternative makes it possible to measure the respective weight of the two but not to define the way in which each influences the results.

The same problem arises, but to a lesser degree, within the set of developing countries. A number of cross-sectional studies relate to only some of the developing countries, either the middle-income or semiindustrialized countries (Feder 1983, 1986) or the low-income countries (Helleiner 1984), while some estimate the relationship for different incomes-(Demeocq and Guillaumont 1985, Kavoussi 1984). The distinction between subsets of countries at different incorme levels can also be used to test the hypothesis that the transmission mechanisms differ accordin3 to income (Peder 1986, Kavoussi 1984).

The distinction between sets of countries at different income level partially overlaps the distinction between geographical subsets (Africa, Latin America, Asia). Some studies relate only to the countries of a given continent (e.g. Africa, Wheeler 1984 or Helleiner 1984; Asia, Rana 1987). Others estimate the relationship for several geographical subsets (Paini, Annez and Taylor 1984, Demeocq and Guillaumont 1985). In still others the African countries are de facto eliminated (e.g. Kormendi and Meguire 1985).

Examining the factors affecting growth separately for a regional subset comes down to making the hypothesis that these factors operate differently in different regions of the world. These hypotheses may be based on historical or geographical considerations but the latter do not always emerge clearly. It is true that the results obtained can vary appreciably from one regional subset to another, as is evident from our illustrative model (table 3, equations 18 through 21). Some studies have sought to take account of regional specificity by introducing a dummy variable corresponding to each regional subset (Singh 1985); however, this method does not capture a possible regional specificity of the impact of the various independent variables affecting the regression coefficients.
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An important problem arises when one seeks to explain the causes of growth or stagnation in a given region of the world, aF Wheeler does with respect to Africa. It consists of determining whether, in order to identify the causes of the stagnation observed in these countries more than elsewhere in the world, it is appropriate tL reasoni solely from the African subset or from all the developing countries. If the homogeneity hypothesis can apply to all the developing countries, including the African countries, the causes of African stagnation can be sought in the level of the variables affecting growth. But if these causes stem from a certain specificity of the model applicable to Africa, it is preferable to work on a sample limited to that region. However, this specificity hypothesis must itself be tested by reference to a larger sample.

# Aberrant data points and weighting

Finally, the heterogeneity of a sample is sometimes due es3entially to a single country or a small number of countries. This is the problem of "outliers," which involves two questions: how to detect aberrant data points that affect the estimate, and how to take them into account.

Heterogeneous data points can exist in the sample that do not significantly affect the estimate; in that case they do not reed to be eliminated. Unfortunately, the outliers that have the greatest impact on the results are those that are both the most useful and the most difficult to detect. Detecting them cannot be done solely on the basis of the size of the residuals since it is possible that an aberrant data point will not lie far from the regression line. On the contrary, the countries characterized by "high" residuals (in absolute value) are in a way "disregarded in the estimate." With our illustrative model we show (table 3, equations 22 through 25) how successive elimination of the four data points with the largest residuals has little impact on the values assumed by the estimated coefficients. It is noted, however, that the public expenditure ratio becomes significant at lOx when Botswana and Syria are eliminated and that per capita income also becomes significant.

When economic considerations cause a country to be singled out, its exclusion can sometimes have a particularly significant impact. For example, in Kormendi and Meguire (1985), the exclusion of Brazil sharply reduces the significance of the variable "average rate of growth of money supply" and the value _ji_ its coefficient. In our illustrative model the exclueion of Singa,pore, suspect because of its exceptional export share, causes a substantial change in the coefficient estimated for impact of exports on economic growth (equation 25). This leads to a second important observation concerning aberrant data points: their presence is often detected by economic reasoning, which sometimes, by the same token, justifies eliminating them from the sample. It is true that more formal methods also exist for detecting them and testing their heterogeneity on the basis of "Studentized residuals" (Barnett and Lewis
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1978, Cook and Weisberr 1982). But they do not appear to be in very common use yet. Once the aberrance of an observation is recognized, by one means or Another, eliminating it is not the only way to resolve the problems it poses. It can also be weighted in order to conserve the information it contributes wh.le reducing its impact.

The technique of weighting the different variables can be applied in a completely different spirit, as does Landau (1983). He considers that it is appropriate to weight the various observations by the size o; the country's population. The econometric rationality of this procedure is not very clear since there are two possible causes: either the sample is homogeneous, and changing the weighting of the countries does not have much effect, or it is not, in which case the very justification for the use of a cross-sectional sample in the estimation is in question.

But the very concept of weighting has to be examined in light of the purposes of the study. If the aim is to test the impact of certain variables in order to assess the efficacy of certain economic policies, there is no reason a priori to give greater weight to some national experience, than to others. But the purpose of the study may be different. It might be felt that in a certain sense it is more "important" to understaid the growth of India than that of countries witlh very small populations. But in a similar spirit it could be argued that weighting the observations by the inverse of per capita income would be more justified since in a certain sense it is more "important" to understand the growth of the poor countries than that of the rich countries. The number of the weighting criteria could be multiplied in this way.

# 1.2.2 Choice of period

The length of the period over which the growth rate is calculated normally depends on the purpose of the study. Most of the studies are concerned with long-term growth. It is exceptional for authors of cross-sectional growth analysis to aim at explaining both fluctuations (or cycle) and growth; this applies to Fry and Lilien 1986. It is normal in this latter case for the dependent variable to be an annual growth rate calculated over a short period (mobile two-year average); the interest of Fry and Lilier. in product fluctuations is closely linked to the purpose of the study, i.e. an examination of the impact of anticyclical monetary policy on growth. The purpose can also be to explain medium-term growth performance, for example in response to the oil shock, as does Balassa (1985) in introducing ways of adjusting to the oil shock as independent variables.

The long or medium period over which most of the authors calculate the growth rate in fact varies in length. Our sample of articles includes (in roughly equal proportions) studies covering 20 years, often divided into two subperiods, others that work on 10 years (apparently the commonest length) and still others that are limited to
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less than 7 years. There are even that seek to capture<sup>long-term</sup> characteristics by calculating growth over a single year (cf. table 1, column 4).

All in all, authors show a certain preference for ten<sup>years as</sup> the appropriate unit of time. This preference appears to reflect<sup>a</sup> compromise between two aims. One aim is to investigate the<sup>longest</sup> possible period in order to erase short-term fluctuations and also to capture the impact of the variablas even if they take<sup>a long time to</sup> act. The other leads to shortening of the calculation period so that the broad orientations of economic oolicy, which can change over the course of time, can be expressed in a significant way. For example, countries like Brazil and South Korea have experienced<sup>contrasting</sup> economic policy phases over the course of the last<sup>thirty years. To</sup> then take an average rats over the entire period<sup>to characterize</sup> economic or budgetary policy or openness to the outside<sup>world rather</sup> poorly characterizes the policy fillowed and consequently<sup>does not</sup> capture tbe impact of a given policy. The technique of introducing a variable representin, 'D instability of the economic policy in question only partially resoL eo the problem since this variable makes it possible to measure the impact of the variability of the policy but not to assess the relative efficacy of the various types<sup>of policies</sup> successively applied. In brief, the length of the calculation period is a fundamental factor in interpreting regressions.

The homogeneity of the period covered is sometimes sought<sup>by</sup> choosing a historically defined period. For example, some studies (e.g. Rana 1987) distinguish between the period preceding and<sup>the period</sup> following the first oil shock. The distinction often drawn between the 1950s, the 1960s, and the 19709 itself demarcates notably<sup>different</sup> phases of economic history: the late 19509 marks the end of<sup>the dollar</sup> scarcity and the return to convertibility of European currencies; in contrast, the late 1960s marks the onset of international<sup>monetary</sup> instability, of world inflation and of the rise in unemployment in the industrialized countries; the end of the 1970s and the beginning of the 1980s ushers in a new phase of tbi international economy characterized by disinflation and reduction in the availability of<sup>international</sup> capital.

The studies that compared the equations estimated over<sup>two</sup> periods usually stress the difference in results, particularly those of Genberg and Swoboda (who distinguish between 1970-77 and<sup>1977-83) and</sup> Singh (1985); in contrast, others find that they are<sup>similar (Hwa</sup> 1983). The fact that a difference is found can be interpreted differently, depending on the purpose of the study: the problem is to know whether the observed instability of the model estimated, depending on the period, is a failure of the underlying theory or its<sup>modelization</sup> or whether, on the contrary, it brings out the role<sup>of factors placed in</sup> their historic&l context.
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# 1.2.3 Data tooling

A number of studies combine cross-sectional observations with time series. This practice of "pooling" has been used by various authors, though in different ways. Some have simply combined the observations relating to two multiannual subperiods (Genberg and Swoboda 1987, Singh 1985); it is then a matter of a stability test of the relationships estimated for each of the subperiods, a problem evoked earlier. The other studies introduce a series of observations for each country, usually calculated for a small number of years (one year, Devarajan and de Melo 1986, Rana 1987, Faini et alia 1984; an average of two years, Fry and Lilien 1986; successively 1, 4 or 7 years, Landau 1986). The purpose of pooling is usually to increase the number of observations; more rarely it is to capture both short-term and long-term effects (Fry and Lilien 1986).

But when pooling is done using a short-period growth rate as dependent variable, it is necessary to define the structure of the time lags for the impact of the different independent variables on the growth rate. For example, if the investment rate is introduced to explain the growth rate of the same year, the Keynesian effect on demand is likely to be captured rather than the long-term effect on productive capacity. But pooling analyses of growth, although referring generally to a long-term model which implies long time lags of the independent variables, often pay little attention to the appropriate impact of the lag structure. The problem of time lags also arises logically for cross-sectional analysis but its practical importance is less, the longer the period of calculation of the growth rate.

Moreover, pooling poses the problem of sample homogeneity particularly acutely. To the problem posed by heterogeneity of the data in space is added that of possible heterogeneity in time, i.e. that of instability of relationships over time. In this case, even more than in that of purely cross-sectional analysis, certain diagnostic tests would appear to be necessary (Chow test, heteroscedasticity test, Breush and Pagan test, etc.). To capture any country heterogeneity one can use the "fixed effect" method (dummy country-variable) Devarajan and de Melo 1987 and Faini et alia 1984); in cross-sectional analyses, dummy variables can obviously only be used to characterize groups of countries. To capture heterogeneity over time, some authors introduce a trend variable (Devarajan and de Melo 1986).

Whatever the precautions that have to be taken in using pooling, the estimation of our illustrative model using this technique (transition from 40 to 280 observations) indicates that the results are not fundamentally changed (see table 3, equations 28 and 29).

x x x
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The illustrative model used to test the impact of the various choices concerning the dependent variable revealed that the choice pertaining to the composition of the sample is essential and the other choices less significant. This does not mean that another model would not have led to different evaluations. It also emerges that most of the others who tested the homogeneity of relationships over time, rejected it.

# 2. Choice of Independent Variables: Characteristics of the Model

Cross-sectional analyses of growth seek to answer a wide range of questions (see table 1, column 1). They do not, as a rule, aim to provide a general or exhaustive overview of factors affecting economic growth in the developing countries, but to highlight the particular role of one or another variable and derive implications for economic policy from it. The independent variable whose impact is chiefly analyzed is then either a variable directly representing economic policy (tax ratio, budgetary expenditure ratio, growth of money supply, overvaluation of exchange rate, etc.) or some oth'r variable that affects growth and can be influenced by economic policy (growth of exports, their instability, external capital inflows, population growth, education, health, growth of agricultural production, etc.). Moreover, some studies seek to apportion economic growth between the part attributable to constraints imposed by the environment (external or internal) and the part determined by economic policy choices.

The purpose of the study influences not only the nature of the independent variables but also the way in which they are combined in a model. The interpretation of economic results is conditioned by these two methodological choices, which we shall now consider in turn.

# 2.1 Choices concerning definition of variables

Examination of the literature on cross-sectional analysis of growth reveals that the choice of independent variables is affected by two major kinds of problems:

- the variables are difficult to classify and their nature is sometimes uncertain;

- they are measured in different ways and their international

- comparability is not always ensured.

# 2.1.1 Classification and nature of variables

A number of classifications of independent variables affecting growth can be found in the literature (production and productivity factors, short-term and long-term factors, external and internal factors, etc.). To be able to extract lessons from cross-sectional studies concerning the economic policy most favorable to growth, we need
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to distinguish between economic policy variables and "fundamental" or environmental variables. As used here, environment means the entirety of the factors that are independent of discretionary economic policy choices (or "exogenous" factors in relation to economic policy). This distinction is not the same as that between international and domestic factors: the environmental variables group together not only international factors, such as evolution of terms of trade, but also certain domestic factors, such as climate, dimension, natural resources, etc.. The distinction between international factors and domestic factors, often used in global studies of the impact of North-South relations, is hardly used at all in cross-sectional analysis of factors affecting growth. The main reason is that the purely international factu,rs affect all countries and it is often impossible to differentiate their impact according to country (growth of world demand, world inflation, and so on).

Although the distinction between country-specific environmental variables and economic policy variables is an essential one, it is rarely made explicitly (it is found in Wheeler 1984, Plane 1986, Guillaumont P. and S. 1986 and, to some extent, Genberg and Swoboda 1987).

Thus, the distribution of the variables between these two categories is not obvious. This presents hardly any problem in the case of the environmental variables representing initial conditions, such as initial product per capita, initial population size, initial school enrollment rate, initial structure of production or exports, etc.. While these variables are influenced by economic policy, they are not affected by the policy followed during the period considered.

A problem arises in regard to the environmental variables measured over the ssne period as economic growth. Examples are population growth and instability of exports. These variables are not totally independent of economic policy. Population growth can be affected not only by birth control policy but also, in the shorter term, by migration flows, which depend on economic growth and therefore on economic policy. In that connection, natural population growth is a better environmental variable than total growth; however, it is rarely used (it occurs in Plane 1986). Similarly, while the instability of exports undoubtedly results mainly from international factors (price and demand fluctuations) or climatic hazards, it is also affected in the long term by diversification policy and in the short term by producer pcice policy -- itself linked to monetary and budgetary policy.

Conversely, the economic policy variables are usually influenced by the environment. Thus, in cross-sectional analysis the economic policy instruments used, which vary from country to country, cannot be introduced directly; indicators are then used that result from the use of various instruments and from the environment. Examples are the customary monetary and budgetary policy indicators (e.g. rate of growth of money supply or inflation rate, which depends in part on the
- 19 -

evolution of international prices, or tax ratio, which depends in part on the initial structure of production). This effect of the environment is even more obvious in the case of indicators meant to represent a strategy, for example in favor of agriculture, through rate of growth of agricultural production, or a strategy of openness to the outside world, through rate of growth of exports. It is not enough to establish a positive relationship between the rate of growth of CDP and that of agricultural production or that of exports in order to justify a policy favorable to agriculture or an openness policy. That entails the risk that a situation will be regarded as resulting from a policy when in ' ct it results in part from the starting condition4.

Moreover, certain environmental variables that significantly affect the growth rate undoubtedly do so by reason of the economic policy reactions that they usually -- even though avoidably - generate. This is true of the instability of export receipts in particular (Demeocq and Guillaumont 1985).

Separate treatment has to be given to the purely political factors, whether that of the more or less democratic nature of the political regime (taken into account by, for example, Venieris and Gupta 1983 and Kormendi and Meguire 1985) or that of political instability (coups d'etat, war, violence, etc.) (Wheeler 1984, Venieris and Gupta 1983). These factors can be regarded as either environmental variables or economic policy variables, depending on the purpose of the analysis: in an analysis of the efficacy of economic policy as an intervention technique, they form part of the environment (Wheeler); in an analysis of development strategies they can be deemed to result from human choices and must therefore be treated as policy variables.

Generally speaking, it seems that the political conclusions to be drawn from cross-sectional analyses would be more reliable if greater attention were paid to the nature of the environmental variables and their linkage with autonomous economic policy decisions.

# 2.1.2 Measurement and international comparability of variables

Regardless of the nature of the independent variables, the cross-sectional studies reveal substantial difficulties in measuring them on a comparable basis in different countries. These difficulties have been overcome in a variety of ways and more or less well.

The variable measured is very often no more than an approximation ("'roxy") of the initial concept. A good approximate variable has to be correlated with the variable it replaces yet in such a way that the percentage of error is not itself a function of the growth of the product one seeks to explain. Many approximate variables no doubt fall victim to this risk. Thus, gross investment is often used in place of variation in capital for lack of a measurement of capital: the error introduced concerns the depreciation rate which can itself be a function of the CDP growth rate (thus, a period of rapid growth can
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lead to accelerated depreciation of capital). The solution of using growth of investment as "proxy" (Tyler 1981, Marsden 1983, Hwa 1983) is even less satisfactory since it assumes that the sum of capital growth rate and capital depreciation rate is constant. 3/ The problem is just as great when rate of growth of employment is replaced by rate of growth of active population or (even more commonly) of total population: the faster the growth, the more the unemployment rate normally declines, so that employment rises faster than population.

The choice of an approximate variable can present a problem that is not just econometric but has to do with the very significance of what it is sought to represent. To express the full natural and human resource endowment of a country (natural resources, infrastructure, educatiorn, health, etc.), the yardstick of per capita product is used. Now the relationship between these various conditions and per capita product can be fairly remote (in 1960 South Korea had a low per capita product but a high school-enrollment rate whiciL no doubt contributed to its development); moreover, per capita product depends both on the environment and on the policy followed previously: the growth capacity for a given low initial per capita product differs according to whether this initial level is due to naturdl conditions or to poor policy (for example, Niger and Madagascar had the same per capita product in 1985).

To capture qualitative factors that are difficult to measure, a number of authors use dummy variables. These are often sociopolitical or institutional variables: vio ence, democratic situation, climatic zone, membership of a geographical area, etc.. More rarely, it is a question of representing a threshold effect for variables that are in fact measurable (for example, evolution of terms of trade, Wheeler 1984, or per capita income, Ram 1985): the approximation is then that of a logistical transformation of the variables. The dummy variables sometimes have a very significant impact, to the detriment of other variables (for example, in explaining investment rate in Kormendi and Meguire 1985). In brief, the dummy variables not only are by definition imprecise but also they often substantially affect the estimation results. They reveal in fact a heterogeneity of the sample without making it possible to capture any relationship that may exist in homogeneous subsets of the sample.

A specific difficulty arises in comparing variables meant to represent a deviation from a normal or equilibrium position. This applies in particular to price distortion indicators. Some studies have sought to take account of the impact of overvaluation of currencies on growth (Wheeler 1984, Agarwala 1983). In view of the difficulty of defining the country-specific base year it may be tempting to adopt the variation in the real effective exchange rate as an approximation (Wheeler 1984); however, this approximation is itself disputable since it no longer corresponds to the underlying theory, which considers not the variation in the exchange rate but its level in relation to an optimum. The problem would be analogous if one desired to introduce a variable representing deviation in agricultural producer prices from an
- 21 -

optimum: using the variation in prices would then be an unreliable approximation. For that reason, nominal rates of protection of agricultural products are sometimes introduced (relationship between producer price and farmgate equivalent of world price) (Agarwala 1983); however, a difficulty then arises because the available data usually relate to different years, depending on the country concerned, and therefore to different international price levels, which alters the significance of the protection rate.

The difficulty of measuring price policies on a comparable basis explains why cross-sectional analyses of growth have paid little attention to this essential field of economic policy. More generally, this difficulty applies to the entire regulatory domain of economic policy (control of prices, of wages, of imports, regulation, etc.); very exceptionally, t "government intervention" variable is introduced (Singh 1983 uses an indicator of Bornshier and Heintz 1979, established in the form of a scale that takes into account both the "general role of government in industry" and nationalization policy).

A final type of measurement difficulty needs to be stressed. It stems from the fact that the significance of certain economic policy variables is closely linked to a country's specific institutions and sociopolitical structures. For example, the public expenditure ratio is generally measured by reference to the central government account, which covers different categories of public expenditures depending on whether the state is unitary or federal; including when the expenditures of the federated states means taking into account expenditures that are included elsewhere in local authority expenses. Similarly, the value of using a particular interest rate (the Central Bank discount rate or a bank deposit interest rate) varies with the countries' financial structures; that is no doubt why a variable of this type is not usually introduced into cross-sectional growth studies (an exception is provided by Lanyi and Saracoglu 1983), although it has often been attempted, not without difficulty, to use it to explain the saving rate.

In sum, it is important to take economic policy into account in cross-sectional analysis of growth, and such analysis benefits from the progress made in the measurement of pertinent comparable indicators; but it is unrealistic to hope to be able to capture all aspects of economic policy in a comparable way. For that reason many studies use variables that do not correspond directly to economic policy instruments but derive from the use of multiple instruments. The drawback of these intermediate policy variables (such as export ratio or rate of export growth or of agricultural growth) is that, as we saw earlier, they are also influenced by the environment and do not represent only discretionary economic policy decisions. It has also sometimes been considered that the residual of a growth-rate equation in which most of the environmental variables capable of influencing growth are introduced, would be an indicator (admittedly very approximate) of the effects of
- 22 -

economic policy as a whole in each country of the sample (Plane 1986, Guillaumont P. and S., Plane 1987). More precisely, the residual relating to each country represents the impact of the country's economic policy to the extent that it differs from the average policy followed in the sample as a whole. The drawback of this indicator is that its validity is based on the hypothesis that the environmental variables introduced into the function are exhaustive (cf. Azam 1986).

# 2.2 Combination of variables

It is undoubtedly important to define each independent variable properly. But the interpretation of the estimated coefficients and the policy conclusions that can be drawn from them depend on the way in which these variables are combined in the model. On this combination depend both the judgment that can be made concerning the place of economic policy in relation to the environment factors, and the assessment of the mechanisms by which their effects on growth are transmitted.
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# 2.2.1 Relative impact of economic policy variables and environmental variables

If economic policy variables representing the various decisions of gove-nment were available, there would be hardly any problem in assessing government responsibility with respect to growth, taking into account the environmental constraints. But, as we have seen, these (multiple) decisions are difficult to represent in a comparable way. For this reason the variables used are usually intermediate economic policy indicators. The problem, discussed above (2.1.1), is then that these variables are not pure economic policy variables; they are affected in part by environmental factors which, moreover, help to explain economic growth.

To try to distinguish clearly between the respective effects of the two types of variables, the impact of economic policy decisions can be isolated by purging the policy indicators of the effect of the environmental factors. To that end the intermediate economic policy indicator is regressed on the environmental variables that affect it and the regression residual is used as the indicator of economic policy choice. The residual is assumed to represent the discretionary element in economic policy, which is equivalent to considering that a "normal" policy in relation to the totality of the countries of the sample (zero residual) contains no discretionary element. A measurement thus purged of the policy followed has been made by Chenery and Syrquin (1975) for openness to the outside world (residual of an equation explaining the export ratio as a function of per capita income and of population) in order to characterize the development mode, but without estimating a growth equation. It has been possible to extend this measurement to a large number of variables representing economic policy (tax ratio, public expenditure, growth of money supply, investment rate, etc.) by introducing environmental factors chosen specifically for each indicator (CERDI 1986).

These types of indicators can be introduced as independent variables explaining the growth rate (Balassa 1985 for the residual of per capita exports; Guillaumont P. and S. 1986 for the residual of the export ratio and of the investment rate). The coefficient estimated for this variable represents approp'iately the impact of the economic policy choices made. In contrast, the coefficients estimated for the environmental variables express both their direct impact on growth and the impact exerted through the intermediate economic policy variable. Thus, this transformation of the growth rate equation generates a change in the environmental variables coefficient but not in the economic policy coefficient. 4/ The part of a country's rate of growth of product that is attributable to the economic policy choice-in other words to economic policy to the extent it is discretionary or differs from the norm-is represented for the country by the product of the value of the new variable (the residual) and its coefficient.
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# 2.2.2 Transmission mech&nisms and levels of analysis.

Most cross-sectional studies of growth factors are concerned with supply determinants. Here again, the reason is not always clearly explained. Some authors consider that demand factors act on the world level and affect the various developing countries indiscriminately, others that demand variations affect production only in the short term, thereby explaining deviations from trend (cf. Genberg and Swoboda 1987, pp. 24-25). An exception is furnished by the study of Faini, Annez and Taylor (1984), based explicitly on demand factors.

The most commonly used reference -- explicit or implicit -- is a production function. But this reference takes very diverse forms. Two broad types of models can be distinguished. The first group introduces supply of production factors (as control variables) in order to isolate the productivity growth factors. The others are concerned, more upstream, with the variables that affect both productive factors and productivity growth. For the sake of brevity, we shall designate the two groups "productive factor models" and "upstream models," respectively.

# Productive factor models

Let us consider first the first group of models, which is the most frequent case. The coefficients estimated for the growth of the two productive factors, capital and labor, do not only express the direct impact of these factors on production in a pure way but also incorporate any indirect impact they have on productivity gains.

The difficulty does not seem to be an important one as far as the interpretation of the capital coefficient is concerned. Generally speaking, the variable is the investment rate. Its coefficient then measures marginal capital productivity if its effects on technical progress are negligible. The coefficiints estimated in the literature show rather little dispersion and are of the order to be expected for a profit rate (for example, 0.13-0.16, Ram 1985; 0.11-0.13, Ram 1986; 0.18-0.20, Feder 1983; 0.05-0.15, varying with development level, Feder 1986; 0.15-0.16, Venieris and Gupta 1983.

In contrast, the coefficients estimated for labor growth vary substantially from one study to another: the coefficient may be significant, ranging from 0.4 in Kavoussi 1984 and Ram 1986 to 1.1 in Ram 1985, via intermediate levels such as, for example, 0.61 in Kormendi and Meguire 1985, 0.6-0.7 in Feder 1986, etc.) or insignificant (Balassa 1985, Cenberg and Swoboda 1987, Marsden 1986 and, for low-income countries, Helleiner 1984). This reflects not only the fact that, as already noted, a very approximate variable frequently replaces growth of employment but also the existence of varying impacts of employment growth (or population growth, taken as "proxy") on productivity growth. In a number of studies a higher coefficient is estimated for the low-income countries than for the medium-income or semi-
- 25 -

industrialized countries (Feder 1986, Kavoussi 1984, Ram 1985, Rana 1987). This result, which is noc obviously explained by a relatively larger share of labor income in the low-income countries, can be interpreted as the manifestation in those councries of a greater positive impact of population growth on productivity growth. (Conversely, when the coefficient is not significant, the result can be interpreted as reflecting a negative impact on productivity gains which cancels out the direct impact on production.) 5/ Sometimes the dependent variable is growth of per capita product (Landau 1983, 1986, Venieris and Gupta 1983). In these studies the population growth rate continues to be included among the independent variables and its coefficient is negative -- significantly in two cases (Landau, -0.5 to -0.1, Venieris and Gupta 1983, -0.2). In addition to the growth of productive factors, various other independent variables are introduced into the models with the aim of explaining productivity growth. It appears that the impact of the fundamental or environmental variables, such as size, initial per capita income, or oil resources, is not usually the focus of interest of the investigations and that they are introduced as control variables and not as test variables.

The test variables can be divided into two groups. The first group of variables deals with the impact of a sector on the whole economy. They a e represented by growth of the manufacturing sector (Feder 1986), of the agriculture sector (Hwa 1983, Genberg and Swoboda 1987), of the export sector (Feder 1983, 1986, Genberg and Swoboda 1987, Kavoussi 1984, Lal and Rajapatirana 1987, Moran 1983, Ram 1985, Rana 1987) or again of the public sector (Ram 1986). The expected impact of this sectoral growth is of two kinds, as emerges clearly from the model of Feder (1983). First, if the sector in question is more efficient than the rest of the economy, the reallocation of resources in its favor increases overall factor productivity; this hypothesis is sometimes described as disequilibrium growth (Chenery 1986, Feder 1986): it assumes differing marginal factor productivity from sector to sector and therefore segmentation of factor markets. Second, the most dynamic sector can generate external economies: for example, the export sector causes the other sectors to benefit from a better trained labor force, more modern management techniques, foreign exchange, etc. The impact of these variables is usually positive. It is reassuring to note that no sector was seen to exert a negative influence on economic growth (agriculture and industry, exports and public expenditures). Attention is drawn, however, to a certain discord in the literature concerning the impact of exports on the growth of the low-income countries (Helleiner 1986, Goncalves and Richtering 1986). 6/ The second group of variables, whose impact is estimated on the growth of productivity, comprises economic policy variables. These variables are distinct from the sectoral variables, although the latter are also linked to economic policy. The link is particularly evident
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where exports are concerned. Thus, export growth prior to the period of analysis is often adopted to express openness as a choice (Lal and Rajapatirana 1987). But openness can be measured by means other than growth of exports and can be introduced alongside it (Balassa 1985). Another aspect of openness is represented by external aid or private foreign investment, which generally have a positive impact (Faini et al 1984, Singh 1983, Rana 1987) or an insignificant one (Balassa 1985). The monetary policy variables are introduced into a few studies and their coefficient has the expected sign: negative for inflation (Landau 1983, 1986, Hwa 1983), its variability (Genberg and Swoboda 1987) or its acceleration (Kormendi and Meguire 1985), or again for rate of growth of money supply or its standard deviation (ibid).

The results of the impact of the role and size of the government on productivity are less uniform: while the impact of taxes appears to be negative (Marsden 1983), as does that of government intetvention (Singh 1985), contradictory results are noted for public expenditure. Thus, Landau (1983, 1986) finds a negative impact for various public expenditure/GDP ratios, including public investment expenditure; Genberg and Swoboda (1987), in contrast, obtain for these same public investment expenditures a positive impact (but negative for the overall rate of public expenditure); Ram (1986), as we saw earlier, obtains a positive impact for public expenditure growth rate whether or not it is weighted by public expenditure ratio. This apparent contradiction can no doubt be explained in part by the definition of the variables, which obeys two different hypotheses. Ram, through variation in public expenditure, is concerned with a "Feder-type" sectoral impact, described earlier, whereas Landau, through the average level of the ratio, investigates the impact of various categories of expenditures on economic efficiency. But when Kormendi and Meguire introduce the rate of growth of the public expenditure ratio, the impact appears to be negative: the authors interpret this variable as reflecting the negative impact of the taxes on the level of production.

Widely varying results are also found when sociopolitical variables are introduced: while "civil liberty" is a positive factor for Kormendi and Meguire (1985), "democracy" is a negative factor for Landau (1986), as is political instability for Venieris and Gupta (1983). These results must not be cited without recalling the uncertainty that besets the definition and measurement of these variables (cf. section 2.1.2 above).

# Upstream models

A second category of models, designated above "upstream models," is characterized by the absence of variables representing productive factors. In these models the coefficient of the independent variables is meant to represent the impact exerted by these variables on the growth of productive factors as well as on productivity. A given independent variable can therefore logically have a different coefficient in the two types of models. For example, the inflation rate
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used as independent variable in a sample that includes the developed countries in both cases has a coefficient four times as high in absolute value (-0.08) in the itudy of Pry and Lilien (1986), in which factors of production are not introduced, as in the analysis of Hwa (1983) (-0.02), in which the independent variables include the growth of capital and labor. This difference can be interpreted as denoting a negative impact of inflation on the investment rate. Similarly, the weighted growth of exports appears, by reason of its impact on saving and investment, to have a more favorable impact on growth when it is introduced without the investment rate (coefficient of 1.2 to 1.4 in Demeocq and Guillaumont 1984 but less than unity in the studies combining this variable with the investment rate, for example Feder 1983, 1986). Conversely, the instability of exports, which has a positive impact on the investment rate and a negative impact on capital productivity, entails in total a diminished negative impact on growth (Demeocq and Guillaumont 1986).

A second characteristic of this group of models is that it allows the global impact of the economic policy variables on economic growth to be distinguished from that of the environmental variables, both groups acting on growth of productive factors and on productivity. In this perspective the environmental variables receive more attention than in the first category of models and are more diverse: in addition to population, per capita product or existence of oil resources, variables may be introduced representing climate (Landau 1983, Plane 1986), human capital (Agarwala 1984, Guillaumont P. and S. 1986, Landau 1983, Plane 1986), terms of trade (Plane 1983, Wheeler 1983), political instability (Wheeler) and so on.

The significance of population growth in this context needs to be clearly defined: it is no longer a variable regarded as an approximation of growth of employment but one capable of affecting employment, investment rate and productivity simultaneously. It is, moreover, sometimes replaced by natural population growth to the extent that immigration is in part induced by growth or by economic policy (Plane 1986). It should be noted that the population growth rate does not always turn out to be significant, either because its wide-ranging impact can mutually compensate or because the presence of per capita product, with which it is linked, captures part of its impact on economic growth. Similarly, human capital, measured by literacy or school enrollment level, life expectancy or child mortality rate, reflects a certain state of initial conditions or development level: it is then very much a matter of an environmental variable and not of the variation in a productive factor, human capital, which in the case at hand would be difficult to measure. Through these variables analysts seek to identify an explanation of growth that is located more "upstream" in the hierarchy of causes and thereby more qualitative than the analyses that focus on production factors. The limitation on this type of explanation lies, of course, in the impossibility of quantifying the impact of variables that are perhaps more fundamental, such as value systems and motivations.
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The economic policy variables are themselves more diversified in this second category of models than in the productive factor models. Some authors, such as Fry and Lilien (1986), use many different monetary policy variables (seven variables representing monetary policy which turn out to be simultaneously significant). Agarwala (1984) uses a price distortion variable which is a synthesis of seven special indicators. As we have seen, the impact of price distortions on growth has rarely been estimated doe to the difficulty of measuring them properly; when they are introduced, their impact is perhaps better captured in a model in which the investment rate does not figure, since these distortions can affect investment rate as well as productivity.

To obtain an approximate idea of the impact exerted by economic policy choices on growth through investment and productivity, respectively, it is possible to use among the intermediate variables, stripped of the effect of the environmental variables, the residual of the investment rate. Thus, there have been introduced, alongside environment factors, the residual of the export ratio, an indicator of openness policy, and the residual of the investment rate, .ndicator of "accumulation effort" (P. and S. Guillaumont 1986). When the openness indicator is introduced by itself, alongside the environment factors, its coefficient (0.10) expresses the impact of the openness policy both on productive factors and on productivity. When it is introduced jointly with the investment rate residual, its coefficient (0.6-0.8, depending on the sample) no longer reflects the impact of the openness policy on productivity.

The upstream models or "environment, policy and growth" type models moreover offer the advantage that they avoid the problem posed in the productive factors models by the possible endogeneity of the growth of these factors in relation to that of product. A solution to this problem has however been sought in time-shifting of the independent variables (Landau 1986).

Alongside these advantages, the environment, policy and growth models have the drawback that they mask the mechanisms of transmission of the impact of both environment and economic policy on growth, a traditional criticism of the black box of reduced equations.

# Reduced equations or structural models

For that reason, some recent studies have analyzed factors affecting growth cross-sectionally on the basis of simultaneous equations based on a structural model. (This can be a single indirect least-squares procedure (Rana 1987), double least-squares (Genberg and Swoboda 1987, Gupta and Islam 1983, Venieris and Gupta 1983) or triple least-squares (Moran 1983)). The advantage of a structural model is of course that it allows capture both of the entirety of the effects of the variables examined and of the way in which those effects are transmitted. Unfortunately, however, the results obtained with crosssectional analysis using this procedure are statistically insignificant
- 29 -

# (Gev"-erg and Swoboda 1987, Gupta and Islam 1983, Moran 1983). 7/

The reasons for tS.e discrepancy between the apparent quality of the results obtained using the ordinary least-squares method and those obtained using a structural model do not appear to have been explained clearly. One reason is perhaps the following: if the sample of countries is heterogeneous for certain relationships, there is a good chance that the estimation of the simultaneous model will detect it and that the quality of the adjustment will be affected thereby; in contrast, in the reduced form equation the effects of the heterogeneity of the sample on various underlying relationships may tend to compensate each other. Moreover, the fact that cross-sectional series analyses probably give rise to special heteroscedasticity problems (cf. supra) raises the question of whether the resulting loss of efficiency of the estimation is not greater in the double least-squares than the ordinary least-squares method.

# Conclusions

Four principal conclusions can be drawn from the foregoing analysis of the main methodological problems that arise in a crosssectional study of factors affecting growth.

The quality of the available statistical data appears to have a greater impact on the results when it affects the independent variables than when it affects the growth rate itself. The studies examined clearly brought out the need for better statistical knowledge of developing economies. This need is particularly important in the case of the economic policy indicators.

The results obtained appear to be very sensitive to the choice of periods and samples. However, the choice of periods seems to open the door less to arbitrary subdivision. Interpretation of the results of a cross-sectional study of factors affecting growth should be based on an analytical description of the composition of the sample (taking into account not only the number of countries but also their geographic location, development level, political system, etc.). The hypothesis of sample homogeneity must be suitably tested (coefficient stability and homoscedasticity tests).

Interpretation of the results must, moreover, be accompanied by close attention to the way in which the variables are combined in the equation, which reflects the structure of the underlying explanatory model. This attention is crucial to the validity of the economic policy conclusions that can be drawn from examination of the regression coefficients. It is therefore appropriate to explain the theoretical model used, particularly since a number of different growth models can be conceived. The use of a reduced form equation -- currently the commonest practice - in preference to a structural model involves an
- 30 -

obvious danger in this connection. However, it has to be recognized that simultaneous equation models have not so far yielded satisfactory econometric results.

The policy conclusions that can be drawn from the examination of cross-sectional studies are particularly unreliable as regards the role exercised by government through budgetary and regulatory policy. This unreliability is no doubt attributable simultaneously to lack of suitable indicators, government intervdntion, heterogeneity of the samples in terms of the countries' reactions to this intervention, and the diversity of the modes of transmission that can be envisaged.
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# Notes

I/ The problem has been raised by J. Baneth (1986).

2/ A sectoral deflator is defined for each country: pib Xib Pib a - pij Xib in which: i - sector index j - base year of data in **the** initial document, appropriate to each country b - (1970, .. , 1981), year adopted as new base year Xib - production volume of sector i in base year b.

CDP at constant prices in base b is then calculated for each **year** t **_as:_** Ytb - Ei Pib pij Xit 3/ We write the increase in capital stock as followst K a I - 8K in which: K - capital stock I - gross investment 8 - depreciation rate It is 6 K that introduces a measurement error when we replace K by I.

In addition, we can write: K i I _a K_ (- + 6) K In these circumstances, the equality between I and K growth rates implies that **the** sum [(K/K) + _6_ 1 is constant.
-32 -

# 4/ Given the model:

Y - a * Eb + Pc + y, in which H and P are the vectors of the variables representing environment and economic policy, respectively, and if there also exist relationships such **as:** P = 8 + Eh + p, we obtain: Y - (a + gc) = E (b + hc) + pc + y.

In this expression, (b + hc) is the list of the coefficients of the environmental variables, in which the effect of the variables P acts through the medium of the coefficients c. In contrast, the coefficients for economic policy, "purged" of the effects of the environment, represented by the vector p, remain unchanged by this manipulation of the variables.

- 5/ One author (Singh 1985) introduces investment rate but not population growth. This omission may be due to the fact that per capita income is introduced elsewhere part in the model and captures this influence.

- 6/ Helleiner's study is criticized by D. Lal and Rajapatirana (1987).

- 7/ In the case of the indirect least-squares method there is no significance test.
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- 34 -

- DEMEOCQ, M. and GUILLAUMONT, P., 1986, "Risk and Ratchet Effects of Export Earnings Instability: a Cross-Section Analysis," Etudes et Documents Provisoires, CERDI, Clermont-Fd.

- DEVARAJAN, S. and de MELO, J., 1987, "Evaluating Participation in African Monetary Unions: A Statistical Analysis of the CFA Zones," World Development, vol. 15, no. 4, April, p. 483-496.

- FAINI, R., ANNEZ, P. and TAYLOR, L., 1984, "Defense Spending, Economic Structure, and Growth: Evidence Among Countries and Over Time," Economic Development and Cultural Change, 32 (April 1984), 487-498.

- FEDER, G., 1983, "On Exports and Economic Growth," Journal of Development Economics, vol. 12, , p. 59-73.

- FEDER, G., 1986, "Growth in Semi-Industrial Countries: A Statistical Analysis," Chapter 9 in Chenery, H, Robinson, S, and Syrquin, M, (ed.), Industrialization and Growth, 263-282.

- FISCHER, S., 1987, "Economic Growth and Economic Policy," Symposium on GrowthOriented Adjustment Programs, World Bank and International Monetary Fund, Washington, 25-27 February.

- FRY, M.J. and LILIEN, D.M., 1986, "Monetary Policy Responses to Exogenous Shocks," American Economic Review (A.E.A. Papers and Proceedings), vol. 76, no. 7, May 1986, p. 79-83.

- GASTIL, R.D., 1979, Freedom in the World, Transaction Books, New Brunswick N.J.

- GENDBERG, H. and SWODOBA, K., 1987, "The Medium-term Relationship between Performance Indicators and Policy: A Cross-Section Approach," World Bank, E.P.D. Discussion Papers, Report no. EPD-01, March 1987, 96 pages.

- GONCALVES, M. and RICHTERING, J., 1986, "Export Performance and Output Growth in Developing Countries," Discussion paper no. 17, UNCTAD, Geneva.

- GUILLAUMONT, P. and GUILLAUMONT, S., 1986, "Strategies de developpement comparees: methode d'analyse et resultats generaux", in CERDI, 1986.

- GUILLAUMONT, P., GUILLAUMONT, S. and PLANE, P., 1987, "Participating in African Monetary Unions: An Alternative Evaluation", CERDI, March.

- GUPTA, K.L. and ISLAM, N.A., 1983, Foreign Capital, Savings and Growth. An International Cross-Section Study, Reidel Publishing Company.
- 35 -

- HELLEINER, G., 1984, "Outward Orientation, Import Instability and African Economic Development," Working Paper no. A.13, University of Toronto, Development Studies Program.

- HWA, H.C., 1983, "The Contribution of Agriculture to Economic Growth. Some Empirical Evidence," World Bank Staff Working Papers, no. 619, 23 pages.

- KAVOUSSI, R.M., 1984, "Export Expansion and Economic Growth: Further Empirical Evidence," Journal of Development Economics, vol. 14, no. 1-2, p. 241-250.

- KORMENDI, R.C. and MEGUIRE, P., 1985, "Macroeconomic Determinants of Growth Cross-Country Evidence," Journal of Monetary Economics, vol. 16, no. 2, Sept. 1985, p. 141-163.

- KRAVIS, I.P., 1979, "International Comparisons of Real Product and Its Composition 1950-77," Review of Income and Wealth, 19-66.

- LAL, D. and RAJAPATIRANA, S., 1987, "Foreign Trade Regimes and Economic Growth in Developing Countries," The World Bank Research Observer, vol. 2, no. 2, July, p. 189-218.

- LANDAU, D., 1983, "Government Expenditure and Economic Growth: A Cross-Country Study," Southern Economic Journal, no. 49 (January), p. 783-92.

- LANDAU, D. 1986, "Government and Economic Growth in Less Developed Countries: An Empirical Study for 1960-1980," Economic Development and Cultural Change, no. 35 (October), 35-76.

- LANYI, A. and SARACOGLU, R., 1983, "Interest Rate Policies in Developing Countries. Appendix III, Interest Rate Policies, Financial Growth and Economic Growth: Some Cross-Section Evidence," FMI, Occasional Paper. no. 22, October.

- MARSDEN, K., 1983, "Links between Taxes and Economic Growth," World Bank, Staff Working Papers, no. 605, The World Bank, Washington, D.C.

- MORAN, C., 1983, "Export Fluctuations and Economic Growth. An Empirical Analysis," Journal of Development Economics, p. 195-218.

- PLANE, P., 1986, "Performances comparees en matiere de croissance economique," in CERDI, 1986.

- RAM, R., 1985, "Exports and Economic Growth: Some Additional Evidence," Economic Development and Cultural Change, vol. 23, no. 2, January, p. 415-425.
- 36 -

- RAM, R., 1986, "Government Size and Economic Growth: A New Framework and Some Evidence from Cross-Section and Time-Series Data," American Economic Review, 76 (March), p. 191-203.

- RANA, P.B., 1987, "Foreign Capital, Exports, Savings and Growth in Asian Region," Savings and Development, no. 1.

- SINGH, R.D., 1985, "State Intervention, Foreign Economic Aid, Saving and Growth in LDCs: Some Recent Evidence," Kyklos, 2, p. 216-232.

- STEWART, M.B. and WALLIS, K.F., 1981, Introductory Econometrics, 2nd ed., Basil Blackwell, Oxford.

- SUMMERS, R. and HESTON, A., 1984, "Improved International Comparisons of Real Product and its Composition: 1950-80," Review of Income and Wealth, June, no. 30, p. 207-262.

- TYLER, W.G., 1981, "Growth and Export Expansion in Developing Countries," Journal of Development Economics, vol. 9. August, p. 121-130.

- VENIERIS, Y.P. and GUPTA, D.K., 1983, "Sociopolitical and Economic Dimensions of Development: A Cross-Section Model," Economic Development and Cultural Change, , 727-756.

- WHEELER, D., 1984, "Sources of Stagnation in Sub-Saharan Africa," World Development, vol. 12, no. 1, p. 1-23.
- 37 -

# LIST OF TABLES

- Table la List of Principal Reference Studies, Showing Chief Purpose

- Table lb Analytical Summary of Thirty Recent Works

- Table 2 Average Annual Growth Rates (GDP/GNP and World Bank/IMF Comparison)

- Table 3 Illustrative Model: Comparison of the Various Regressions Table 4. Average Annual GDP Growth Rates (Sensitivity to Quasi Changes of Base)
- 38 -

Tabe 1 a

# LISr OF IUNCWAL REIUE SUDS, SMM _GM KW3R_

# (Se suiiry of ach study in table I b)

|TYpes of<br>T f|?dle|||lFa|ctors<br>Ex__|ud||
|---|---|---|---|---|---|---|---|
|ype o<br>wal aid<br>princpal<br>Productin<br>factors<br>factor<br>exm.zd<br>IdJl|Upltrem<br>mdels<br>(wlrrt<br>ad polic)|ka!y<br>polic<br>ad role<br>of gDvt.|bWtarM<br>Polley<br>_ad_<br>systm|<br>Externl<br>finmgir|Oo_rcl<br>'sau|Exterul<br>**smck**ad<br>amport<br>ImstaKlity|_Stcture_<br>Of<br>pradctiac|
|ApavaU 1983<br>Balus<br>1985<br>x<br>Rnzy 1966<br>x|x||||x|x||
|QilJaint<br>1986<br>Davarujui and<br>de Hlo 1987|x<br>x||x||x|x||
|Falin A im aid<br>Taylor 1964<br>x<br>Fedw 1983<br>x<br>F:ae 1966<br>x<br>Fry ad Llies<br>1966<br>Gber<br>ad|||x<br>x||x<br>x||x|
|g<br><br>9mboda<br>19B7|x|||||||
|Gcaiwaz ad<br>Rdt.ering<br>1966<br>Qdll.U<br>P.|||||x|||
|an S. 1986<br>Gi dIST|x||x||x|||
|pta aa<br>1983<br>x<br>IIel,le.izr 1964<br>x<br>He 1994<br>x||||x|**X**<br>x|**K**||
|Kswoul 1984<br>x<br>_VmuwAi_aid|||||x|||
|<br>KdUl 1985<br>|x||x|||||
|1.1 and Sajaper-<br>tirem 1987<br>x<br>_LwAds_1983<br>xx<br>Laidau 1986<br>x||x|||x|||
|**Lmm1**<br>WAi<br>SwaccVu 1983<br>Nscl<br>1983<br>x<br>1r<br>1983<br>x<br>Plm<br>1966<br>Dm 1985<br>x|x<br>xs|x<br>x||x|x|||
|Rm1986<br>x<br>a<br>1967<br>x<br>SP_l98S<br>x<br>Vaereris<br>_sA_||x||a|x<br>x|||
|Qpta 1983<br>x<br>Whee<br>1964|x|||||||
Table 1 b

# MILITICAL lRY OF THIRfY EIIT SIDIES

<!-- Start of picture text --> IWEIET VUInES<br>CNARACFER- CALDATIW RIITAL UECT CAUl WI<br>UCT mIlCS OF PERIOD NO AS EONC- r. r.Ia socio<br>imR El AM I soE I_ YSIS EYIUIIUITL POtICY rUcTlI POLITICAL<br>OF ST S IY UtEIES I P3I0E I S VABAIRAB 1M11 FACIAS WIMLE mUm<br>.AGU Ealwte MP 31 aCm II yams Ol t reawr Price PpAstlon wouth R-ac a 0.46<br>(1a) effes of (Wortd C* 15 of C9l9I-l0) distortion +<br>price Bwt) piplatim litawy ra (omapite<br>distortion of DC&. lshm)<br>act. Cina)<br>................................................... ........................................................................................................ ...................................................... .....................<br>MuAM CMlmnd World 43 OC 6 ya Initial per Cr lraL PopAetion gromth It-S * 0.43<br>(1915) offscts of - Meral sud) (Clomlncme mI-in*str. (19I3-W) capita ncom - a t(wiml u of Sawre rate nus. Otlc awln<br>atp u mMr1ls) an a rt rat. r<br>- pol0cls f Licn) +<br>odjhtmc to 4 Extwral aWfv<br>baltce of _q2ome to raft<br>pwts dI dodas 4 ns.<br>. ....................................................................................... ..... ........ .......... .................. .. ...................... .......................... .....................<br>QR eC rm diffaFs UP 57 cauentrie Avwq dO.*nsd CpIn 0.59' R-iq 4 08<br>(19" ) onus of (vwris dividcd Into rat w ctb kti n MnoSF ratlw<br>uq n dation of sours) sAta: priod wrylq of bbor Nd Inelfficlicy of<br>vedi of pro t 19 d tlapd with comtsy, capital fators gr>Ah proc_4<br>aI prd tlvlty 7 intratzad 5-2D yas, to 1owth in in<br>(grAth In 31 daetIrg, owri wars e<br>dllhIku, of hfdh: 1949 to 19 7<br>umiarid hre, 9 hIig prfoi (coefficlet of<br>rd in 22 a ap or wlriabl * 0.68<br>dls ilbrfu :pc l bat 1.2 for the<br>a" F br 19t6) ntliw sple)<br>............................ ........................................................ .................... .......................................... .... ...... ................................ ........... .............<br><!-- End of picture text -->
MfYTICAL m_YW OF TN3131 EIT StIDIES

||IUWOBE<br>OF SUm|POT<br>TYPE AM<br>uSME|_CNoRACIER-_<br>ISTICS OF<br>**_SMU_**<br>**_WE_**<br>CM<br>IaEmS|O_NH_RATE<br>DCAWTIOU<br>PRIODAO<br>ANALYSIS<br>Ms|---------------------<br>UNTAL<br>_AD_<br>IUITMAL<br>MPEu|INEEDN<br><br>-----<br>------<br>SWTOML U<br>ECfC-<br>POLICY<br>VIABLES|MAKlHES<br>--------------------------<br>VWIES<br>WIOMhING<br>PETIW<br>WIFCOS<br>f|-----<br>SOC1o-<br>POLITICL<br>MMLES|S|
|---|---|---|---|---|---|---|---|---|---|
|DEluct<br>ahd<br>WILILAWT<br>(1966)|ofGMrt<br>nstebitityanm<br>paid<br>0<br>fteto<br>(ewlre<br>itel<br>Cala<br>ifl<br>, clapital<br>pr atrivty)|MP<br>(orld<br>s13*)|56 gutoil-<br>apartei<br>OC..<br>Serl<br>inbeaptes:<br>25 Afrlc<br>22 lew-mPr<br>23 madisa-Iom<br>43 warfAtual<br>arters|Avrqp<br>aal<br>_~at_<br>wr22<br>>ys 19<br>l<br>ad two<br>_sndbprods:_<br>1960-70<br>(11yam)<br>Iat -I<br>4(12ywa)|Export<br> imtbility<br>wasuredin<br>Importor<br>dmmtfk<br>Pwd.slu<br>puNr<br>or<br>eapat<br>price<br>instaility<br>nas.<br>midSONrt<br>Velum<br>irsthbi1ity<br>wigatudby<br>pa<br>**rate)**|Eport pOd<br>rt<br>at<br>Caotat<br>price<br>,ighted<br>bV<br>aprt<br>rate|||0.30 <I-sw q<br>0.67<br>Vinylu<br>with<br>s_pb,.<br>period<br>erdfndim<br>uw.<br>eauts<br>intepr<br>,<br>w<br>uitht<br>su'tuWal<br>mxst,<br>in light<br>of dSwwd<br>reLateiuhfpa<br>hetiam<br>iI3tiity<br>mnd<br>prcztimn<br>factars<br>(swinto<br>cpitatl:<br>**wri**<br>**le**iquct)<br>ad I bhtin<br>0<br>proitity<br>(nateiw|
|DEIUM<br>0d<br>deHiU<br>(1W?)|cere<br>gram of<br>fru<br>MO<br>**Cesgtf**<br>With<br>that of<br>CMr-I<br>deeAln<br>**casatria**|**_UP_**<br>(Wbold<br>**_inow_**|15 nn DCO,<br>dlvidid ito<br>abat<br>using<br>fouoiirg<br>cWri:<br>- **size**<br>- irct<br>(hfgh,low)<br>- oiL-sporting<br>or -i2mrting<br>-<br>W-iinxtr.<br>- Africen<br>(11 saplie<br>In<br>ill)|Pootlru smusI<br>ra<br>r<br>period 1960Z<br>ad tmo<br>ssharlas<br>**1960-73**nd<br>1973-||Silent<br>vrile<br>for<br>**frnc arm**<br>catries<br>and<br>siltnt<br>**VaIle**<br>**for**<br>adscos,tay|||frisum aLt a<br>e<br>hr<br>pid<br>_omth_<br>of frenca-n<br>cantria<br>then<br>of<br>_dele<br>**caiawrie bit**<br>**les**rWid then<br>of DC's aa<br>de.<br>Perfowue<br>better in 2nd<br>_akpriod_|

... .. . . . ...................
MLYTWIAL 9MRY OF THIITY EET SDtIES <!-- Start of picture text --> INwEmur VMIAlES<br>NTH RATE ----------------------------------------------------------------<br>tNIC- CALOAATIN RMSTSAL SECTOA R VIALES<br>PRDUCT ISTICS OF PERID AM AND ECDlC- _EPT IS soCio<br>FINCPh TYPE AM AN AMLYSIS MEIN ITIAL POLICY IETIu FOLITICAL<br>OF STI MC W RllXIES PERIOD WRAILES VAIALES UWIN FACTOS WVtAUIfr<br>FAIlN, eimpet of GP 69 eaitries 1 VOWr Per eqilta Exprfi 9rcmth Popiatein puirth R-s r emt)Ule<br>ANiEZ edlitoy (World (r amtl (polirg ino + + for *ll r qasnl<br>ad -p-dIF Pir) orc ep etIF 1952-70) n. a Vriatihn in (but Africa -) afsu s. btu<br>TAYLO prsented, Silent eilitry Coital 9cuth 40.31. Nobda<br>(1981) or by dmlep- weriables by apandiuta n.s. widthut eqplicit<br>Mnt Leel) coutry pro-tien<br>(fixed f ect) (but n.m. for functien<br>irdLtrial<br>cantries)<br>ExtwmL aid<br>(+ or ns.)<br>MFR ShN that OaWt GDP Smi-ln*ktr. 10 Ets EJIort gradt lint rate i-sr 0.69<br>(193) MGh he a (World cmaitries in Avuag ratrte wighted +<br>favrdbte Iqiact Ra) broed m16-13 by apart Popastien pwmh<br>en pr It g th (31), strIt aef ra<br>be spt MM (19), pract 4<br>matar ha hidhr act. 4<br>a_gmt oil-mqxertiru<br>acktlvlty then countrie<br>ret of ecoy<br>wd beam<br>Latter miju<br>acea mnp<br>_eertd by<br>00rt -11b<br><!-- End of picture text --> <!-- Start of picture text --> FER Test iqucta of DP 30 emi-indstr. 10 yers Vaighted Inveetamt dhre R-sqr t 0.75<br>(1986) - ifaturi.g World contrie. (19-73) grwth of of prct N l of _m<br>ad pWrt Ot Tet With othr mfemcwtur i* type m fEO<br>tmactar duatis" (lets Test en sector Populatfn growth (195):<br>dr#Lcped 1955-3 + rate reallocatfen of<br>caitrim) ad eighted + factors taumd<br>grath of mt efficient<br>apart sectors ard<br>+ extemrality<br>.__.. .. _........................... ....................................................... ... . ...... ........ . ...........................<br><!-- End of picture text -->
NLYTICL UMY OF TIV T SWIES

||||C1iAru-|ClialHPATE<br>CALATICI|.....................-<br>MUTAL|INDEET<br>VA<br>.......-<br>SECTOIL Q|RILES<br> <br>...............--<br>RABLE|-.. --...||
|---|---|---|---|---|---|---|---|---|---|
||RNE<br>OFS1?|PWJNCT<br>TYPEAM<br>ISICE|<br>ISTICS OF<br>SPE<br>WEARIES|<br>PERICD<br>AND<br>AMLYSIS<br>PUIOD|<br>_AM_<br>EVIWI<br>L<br>VARIAIES|<br>EXONIC-<br>POICT<br>VAIABLES|EUUTEING<br>PRUUCT<br>UWIN FACRS|IOCIO-<br>POLITICAL|CIASS|
|FRY<br>m1<br>LILIES<br>(19k)|Stu* iquct of<br>anticyclical<br>inary<br>pdicy<br>an dot-w0<br>**ltu-tuu**<br>.carmiC gruth|GDP<br>(INF)|55 dmwlcd<br>and d1cqpIr.<br>inms<br>of Nw<br>with papArs<br>or<br>2 dtllian|1yar<br>w period<br>190-3<br>Amat grath<br>**rat**of**a**<br>binl<br>praijt<br>aworap<br>Pooiru|Si (t<br>**vrimle**<br>rqpritq,<br>irntriltizd<br>cowtrim<br>Si lt<br>v wridite<br>paing<br>oI lrtirw<br>coidtrle<br>Iate of<br>wriatien<br>of<br>oil price<br>Oit<br>,ali_r<br>**ceitrim**<br>Oil-iprptiru<br>comtries<br>GP<br>rate of two<br>Prw~<br>wars<br>*|Avwap of<br>saNt<br>reti<br>of wriation<br>of_mw_<br>ty<br>Std<br>dwiation of<br>antwy<br>Aod<br>iictor<br>Silent<br>**wriable yr**<br>1914-77<br>Awmop<br>lat<br>inftatin<br>**rate**<br>RateofuraAth<br>of law to<br>dos<br>d<br>tic<br>credit ratio<br>Umptay sbcho<br>(runial<br>of<br>vamt rate<br>timteda a<br>fuwctin of<br>**tim**_ud_of<br>dw detye<br>**wriable)**<br>correted_bV_<br>its vuiuie|||R-Wu0.31|
# ANJ.YTICAL 5ISMY OF TNIRTY FANT STWIBS

INDUEPET VAMIMES GR0fW N RATE -------------------------------CPIMRArCALUtJLATION RMWMUIAL SECTORAI. CU VAtRLES PRMLET ISTICS OF PERIOD AND AND EOMIICREPRESETN i smoCRioE TYPE AND SMMWL ANALYSIS BMRhIITAL POLICY pEUmtWlc POUTICAL OF 5113? UMIC CifUTIE PUIOD waMIAis VARMANES _Omar FACTUS_ VAhIALES 03M inicator Crasd.a1 of credfit to doustic credit ratio, **tin** _wd_ af the detaysd vutwe) <!-- Start of picture text --> QEiG Stu*/ tio factors GDP 35 &wnLqmd 8 oWi 7 yams Agricutuat PiMic Population growh StnucturaL mdi<br>Rd ~in mndkumton (Wo~rld ad swqlg Avvrs wrnmt proigtfan inmstwmn rat mtltlon bVt<br>Sum= prodet grailh In Ban) omattles ard rafte 19T0-77 uih rate rate, * n.s. dpte teawt<br>(19Wcm odu to aloe 14 dswLclrls ad 197-U 4 + Iiwsntm rate Ord<br>tim eulbtllty oun~tries Ezqor grwth<br>Of the atnctawal Cross- rate Pooling ramAts<br>adjwi sectiamuli ar e poor Cowin<br>powm pooling stu* Inf lotlio todimngi<br>vwridA(fty between the tmo<br>psri od)<br>PiMic<br>m IF -pi ture ~~~~The ramAts for<br>raft the DCa atam fn<br>doMe least<br>Variousaw othr mra we Mich<br>lrdircators,~o<br>triad b* not slwtlf lot 4<br>sipdfflcat thin with single<br>ltas 0AMa<br><!-- End of picture text --> . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..... . . . . . . . . . . . . . . . . . . . . . . - - - - - - - - - - - - - -
1 s113 maNYTICL aWJY OF TNRIl

||It6E<br>OF SW?|_MDT_<br>TYPE<br>AM|ONIRC-<br>ITICSOF<br> SIPE<br>WTEs<br>al<br>IES|OWIRATE<br>CALOLUTI<br>P1WD AND<br>AALYSIS<br>P31eW|--------------<br>RNIITAL<br>m<br>EIVIITAL<br>vtm,s|HEiML OR<br>1DllC-<br>ffLIC)T<br>rIES|1l_B<br>1P1ITII1G<br>IUT1I<br>_U_FACTORS|sOCIO-<br>POLITIC<br>WA<br>BS|AL|
|---|---|---|---|---|---|---|---|---|---|
|OGINICAE<br>nd<br>IIOfITIUs<br>(1"6)|3Disam s<br>sigiffsenicu of<br>theqx<br>s<br>t<br>g<br>raitam,ac<br>acud<br>relatuhip,<br>diffe-tlating<br>wccadirto<br>aRx|orP<br>OMtad<br>atian)|70C<br>distribUd<br>scm.siwly<br>nto:<br>:- I P<br>Was<br>- clwters<br>dffimd bl<br>position In<br>relation to_m_<br>of amg<br>ndAthof GP|22Zar<br>Awaq snnul<br>rat iWOl-S||EWort Orath<br>raft|||0.14'R-a c O0<br>macrdirs to<br>nme_iit_<br>(0.25 for toal<br>**e)**<br>0.01<R-a0.09<br>bccrdif* to<br>cltster|

|.......................................<br>WLIUA T<br>P. md S.<br>(10)|.....................................................<br>DistfryAsh,<br>in gmth<br>diffaws,<br>bI<br>a mio<br>ts<br>facto<br>anouic policy<br>fc tos<br>lhraultatter<br>spain Puruth<br>p"fI<br>dNfindn<br>luil<br>of<br>paids raft<br>titd<br>on<br>bsts of<br>factors<br>y|WP<br>(orld<br>kl)|(a) 31 or<br>(b)47 OCs<br>selected<br>aerdn.r to<br>tistics<br>sailtobiity,<br>the badt<br>$AQle<br>wi,g<br>_NA_ios.<br>'IIm<br>mlfle|Awraga am<br>ra<br>20 ar<br>1W2-81|........<br>ml PopAation<br>t<br>Initiat<br>prmr ychool<br>s<br>vuotmu rat<br>+|...............................................................................................<br>Crcil<br>pxrnu<br>icdicym<br>(si<Al<br>of a<br>fusictin of<br>theq *rt<br>rte<br>Acnmuatfon<br> <br>effort<br>Iwdicator<br>(raidal<br>of a<br>fuetion of<br>dthe sarau<br>ftwtunt<br>rat)<br>(Te onty<br>mw]AU of<br>the f"unio,<br>frn witic the<br>residuls<br>derive are<br>factors)|............................<br>The..<br>t<br>introticn Io<br>of the>ue<br>p<br>si ICY<br>_wrabts<br>(reijals)<br>into<br>a add In<br>dhich<br>orly the<br>nvirnstal<br>swridls<br>_aar<br>**raim I-SW**frm<br>0.36 to 0.55 in<br>saple(a)rd<br>0.47 to 0.6f in<br>smpte_0)_|
|---|---|---|---|---|---|---|---|

, .. . . . . . . . . . . . . . . . . . . .. . . ..... **.** . . . .. . . . . . . . . . . . . . . . . .
MLYTICAL UMY OF THIRTY ECElt SIDIES <!-- Start of picture text --> IN1EPI0 WAVLJES<br>ard (133) SPTA ISm nd OF SD intenal cpftat inf ta Iquct of C6 W=eU an unrq Umu*) GNP (lorld F1X= T ME YPE MNo period cored ORIAIES 40 or 52 DC., pliop $mut CMME- ISTICS OF I n md FP5I 9 196a-7I PEt MRLSIS CAWUTICS 10 M Per cqita proiet (Srvirg to M BMVIIITMML POLICY WR RNAUIAL VMm1mLS E6N SETC.rg C C- mom Sawir MIS PUULTIW MARIARES + ITlU rate FACTGIM WRWBESS=CIOPOLITICL 0.4" c 2-* 0.53<br>- Alto sheple: - br bq amntm regin um tnaom svldidiarily 1950-60 (11 yes) varf,l es) asigt other * or ns. ft Ohr Direct freign Infl Fwrig aid rate frNtumu + or n.s. + cqpitsl rat rate growd, rate re"ts Ato usa dmM*with futimn Last wng aqAe rot of bit rate<br>sfu,ffient<br>Lbor fae o rAdh<br>.............................................................................<br>..........................................................................................................................<br><!-- End of picture text --> ("a) ElEIE* q miterior is nrt a slunificant Show that to 0P (WorLd () m*) 2 ample l1ina# 25 Av _rag 21 as 1980 rate Inbbitity of Variation in fport wiws ert rate (aw 1ffO adIn _eatm ret., countries _lowInm_ nor_ African cmutriies bt* t iqcit-tet iratbfiity _rath ftcor_ t ir an In in 4680 (b) 24 c tries with flo (4410 193) _Afrfa_ n.s. in of posWr or 1rstdbility beween 1960 1960)i - in alte _aport_ no (a) uple ,iwort Varition In P*pAL tf on _ai 19O Qr,_ n.r.rae rate **(a)** (a) r.s. + or (b) n.s.or (b). rath **uafeveL** (b) factor in Africa _din_ to _tak_ of ltqidity .................................................................................................................................................................

.......... **.** ............ ................ ............
AJLYTICAL IBY OF THIRTY ET STWIES C INDEPDET VMIAMES GRTH RATE --------------------------------------------------------------NARACECALCILATIW RIMUIAL SECTO (it VMIAR ES RUCT ItICS OF PERIOD MAD 0 D EMIIICITIUS SOCIORP 6E TYPE AM SPE ANLYSIS VNWUUTAL POLICY PU1IETIOI FOLITICAL OF SIUY S3U WETRIES PERIMD V RUIAE VAlARLES OirN FCTS VSAlES R _ES NA_ Show the GDP Dinlcd wd 11 yrm furicAturl Inwestnt rate 1st period (1W53) **detaulrmt** role (World drwti'w 10 was pkdxction + R-q **u 0.46** of qrfc. _raft_ u) coitrie Averae _anal rwth rat_ PopAlaticn guith in listrial gram rte + rato ad period gra ad 1st period 56 1960-70 E rt grwth R-9u **_*_** 0.61 ca"_ tly the 2d period: 81 1970-79 rat ntire aon= + To ealiate the DCs Inflation rate strauth of the 1at period: 41 -stinte, the and period: a8 residal of the furtian of the grwt rate estinted without the agricultural ewiabt* wa thisasm verible . .... ...... .... .......... ... ............ .. . ..................................... .. ...... .. KAIUSI Stu4 Vh w 73 mket19 wrs Rate of Irtsnt grcth R-sqr - 0.66 (1W" ) ralettiiihip (Word cmc DCs Averg rat growth of **rat at** corotat total Ile bet n agpot BWt) dividd into 1960-78 godo sct price growth am tw mapes: at cnt + The iqet proiet gor - 37 lowprices Poptabtion growth stidid is acoordir to - 36 md-i + rate dciefly that deve1opat levet Ditto, + carted by of the DC. ad The oltweighted by Wgrwth of the mat ee of uspotliw Irv reof eap art an their cquntr cmtries ad _*maifactwilrg_ factor those with 1960 Iq2orts in prodctivity pqpAru below total uqots 1 fillion for the _coustrias_ **amle** for the modiu_-ir countries ................ .............................. ....... .......... ............ ...................... ..................................................................
-s

# ANLYTICAL YM OF TNIRIY EM S1DIES

INDEPEMT VMAKES OWIN RATE ----------------------------------.-.------aWTERCNA.ATION RNUTAL U OCR. WuMes PRMLCT IRICS OF PEIW **_m_** MI ElOMCEPUUINI SOCIOE TYPE AM SA **_UE_** AULISIS 0MIIITAL POLICY PTlclC POLITICAL Of V SMlCE MIXIMnIES MPD VAIBESt VMUAU Ou e FACTfS WUIAES IEIS rIIXel Tet the chief or GOP 46 devloped **Nexhem** Initial per Rate of Invst rate Civil 3-eq **a** 0.64 and '(prtiaulty (acmb to wd dwevcping 28 v_s capita inee s hvath of librty IIIE the nt _ea*rv)_ otris (in Cyrvirs bt - public pm-, indicator R-e a 0.59 (195) coersal) ,eee1 s (INF) p _Afo_ ice no contry) Avarage rat PopAstion WUIUh **rat*** ditlO rate - n.e. (slentwridlt The effect of rative to coatrie lass 1950-77 Rat of growth taken fro erg rnic policy wo fhct Souh Africa) Stdrad of t rate GASIIL _1979)we_ deaud to Ecltulen of dwiation of + act tuWuh BiLm rate*of Ruofgrath factor atier veriation In of Inflatien proctivity L pict **rate** Stufrd dwistion of rate of _dwue_ in w aeof g9itof _-Wo afA_ + n.

UAL nd COnfi ad (Wbrld 18 lwoirfcome 12 as RAPATIRM criticia crtain lwi) **untr"i** Avera raft (11W) tests Of 1973-1 uqmorts/'owh raationip .................................................................................................................................................................

Growth of UP Investam rate **R-eq** - 0.30 ,1.% of + orts frm Growth of ldbor t~19 to 1973 force (irdicator of + qm prior to 173)
co

# ANALYTICAL mUWXm OF THIRT ET STWIES

||RSPE<br>CFSRUW|ORmtlR-<br>PRIICT<br>ISTICS OF<br>TYE ANDSLE<br>SMJCE<br>WMTRIES|GK NRATE<br>CAAJLATIU<br>PtIDAND<br>ANALYSIS<br>PERIOD|-<br>RTW TAL<br>AM<br>IOlITAL<br>VRIAES|I11DPW9ENT<br>V<br>SECTOR<br>ECONMC-<br>POLICY<br>VMIALKES|<br>MIALE3<br>tMES<br>REP11BIIG<br>PRUTIIN<br>5KU1 FACITRS|1ci0-<br>POLITICiL<br>VMIAlES|_IwEs_|
|---|---|---|---|---|---|---|---|---|
|LJANDA<br>c196)|lpct<br>of ptlfc<br>aipudtw<br>(CcAmtifa|Per<br>10W<br>cpite<br>- aoil<br>Itc<br>eparters<br>prI<br>t<br>96<br>(Krwls,<br>19W9)|9 w.rs<br>(1961-70)<br>11 wr<br>(1961-72)<br>13 was<br>(1961-74)<br>15 was<br>1961-76)|Per capta<br>1nc<br>-<br>Oft<br>ci let<br>wrlver-<br>n.s.<br>PopqaAtion<br>n.s.<br>Cliastic zoe<br>silent<br>wriables|oweof<br>plAe<br>cAu tfOn<br>In n titl<br>provct<br>**Shre**of<br>aricultare<br>n.s.|"n<br>'tal<br>(4 w:ras)<br>*<br>Papulation groth<br>rate<br>n.s.|Yeas<br>since<br>in<br>dp<br>du<br>n.s.|0.7 0 R-o q<br>0.86<br>DaA*le leat<br>s*ne<br>for<br>pbAilc<br>expaiture|
|LWDIUi<br>(19"a)|Ioat<br>of pAlic<br>eNniture<br>(separated into<br>S t"M)|Per cAta 65 DCs (clit.<br>utl<br>*W-instr.)<br>pvrdt<br>(INF)<br>**(aWil.**<br>by<br>Wrld Eat)|Aral<br>date<br>* 4-yar<br>Wra<br>* 7-yer<br>b<br>aWes<br>(pooliin)|Per capIta<br>Inca<br>-<br>Oil silent<br>wrfrae<br>+<br>PqoAatfhn<br>TeM of<br>trad<br>n.s.<br>wbrtd wth<br>n.e.<br>Wrlid<br>inflation<br>n.s.|_Shre_of<br>agriculture<br>n.s.<br>andshae of<br> wufatwriq<br>n.s..<br>p.<br>other<br>indstrin<br>n.s.<br>foreign aid<br>n.s.<br>5 t"e<br>of<br>pblic<br>"diare<br>- or n.r.<br>In thfdh<br>pAbic<br>Intnt<br>- or n.s.<br>Inflatien rat|Inntmt<br>aare<br>*<br>PopuAtion<br>growd<br>-<br>e|Colotn<br>n.s.<br>DOracy<br>-<br>Years<br>**since**<br>Indc,pn-<br>dcnce<br>ns.|0.47' R-eps' 0.72<br>vry larg<br>nutr<br>of<br>wiahle<br>tried|
I J=

# ANALYTICAL SAIR OF THIRTY REEIT STUOIS

||||CWRATER-|6OHH<br>RATE<br>CALCJLATIlW|------------<br>RNTAL|IIWNIEPNDTV<br>-<br>....<br>C<br>O|ARIASU'S<br>...............<br>VARUIES|...........|...|
|---|---|---|---|---|---|---|---|---|---|
||RJW'OIE<br>OFSl11Y|_PRMtCT_<br>TYPEAND<br>SOLM|_ISTICS_OF<br>S<br>E<br>OTMIRIES|PERICAND<br>ANLYSIS<br>PERICD|N<br>EMKUSITAL<br>VARIABLES|EWONIC-<br>POLICY<br>VAMIADLES|IEF*IING<br>PRIETIU<br>mWN FAS|s9Cio-<br>POLITICAL<br>VARIABLE|S<br>MSk|
|LmUII<br>od<br>_SARAWO_<br>(Om)|Antfly.Ipet<br>of<br>Intest-rate<br>poliey an<br>fiwciat<br>_th_<br>_ud_ecR<br>ic<br>growth|DP<br>(INF)|21 ICe|C<br>=al<br>groth<br>rateZ<br>191-80||_Vwfabte_<br>rVeut<br>poicr.<br>eqAl<br>to 1:<br>positiw<br>resl<br>interest-rate<br>contrile<br>eqAt to 0:<br>moderately<br>nhptiw<br>ruL<br>Interest-rate<br>cantri<br>eqalto-1:<br>highly<br>negmtiw rel<br>Interest-rat<br>countries<br>Reickat<br>of<br>ooth rat<br>of<br>restmetwry<br>ard casi-<br>eratary<br>-In<br>rvoiptr,|||R-SW<br>0.62|

.................................................................................................................................................................
Am TICAL 9W OF Tulllrt CT S1wIIS 0 lNEEW EIJT VRtUALES GNrH RTE --------w **-** -----------------------------------------------------CIWRA - CALaIATION REPTAL SECTOAL OR wiMtAs PET ISTICS Of P31W AMD _AD_ ECONUCTIUII sOCIoPURPW TYPE AD S1M ANLYSIS MOIUUTAL POICY PRDUCTIO POLITICAL OF SWr tfCE OMltIB PERIOD UIAES VAILES Mol FACTS VRMILES _tS ixpct of to OP 20 csitries 10 Vas Tamtion rate Poapittion 0.78 **(** R-aqr 4 0.88 (190) du cn (Wrld aC" pt1 (197X-9) -v th ram of 1_ O o rs), n.s. Sib ple pr t nad of exclicnr 0PEC Irctnt regraealian prodictivity nd ccmtriee PoUUY plus sAtiple with Nbrkettru + regresaion 10 high-tax costlasf **-v-** 10 lowta cantries 10 low inom castria **-V.** 10 hlsh-incoI . ... ........... .................. .. ..... .... ..... ........ ..... ..... .................................................. NMAiN Iqpct of NP aid 30 Cs Av. anal Export Export growth Foreign arou Exasnoa first (1) _OpWt_ orP nwt itcluirHg rate in tobility in rats rate the ipmct of ir tobility an of sparta 18 Latin An. 22 12. 10 coatnt WI (current a/c apart sawing **rate** wd (scic. not I Africn yaMc n.s. deficit) inst bilIty on arcuth **rat** pcff lobd 8 Asian 1954-75 or + prodictivity 1954-6 Inntobillty of Dom0etic graith (function 1%6-75 _apart_ pricea ,wrl **rate** of productlin) ad volum + than the gltbal * cr -or ns. Lobar force Iqats, inla. (different grcwth rate those s fartad muareonmts) + thrcush the avIg _rate (bV_ triple least )qam ............. ....................... .. .. .. ...... ....... .............................................................
AILYTICAL miNt OF TNiRTY NT m SiIES

||OF SO|pRmicr<br>TYRE AM<br>I|CHARACTE<br>ISTIM OF<br>SOIE<br>IMINYElRI|cOEM<br>RRTE<br>R- UCALaIAT<br>PERIOD<br>A<br>AALYSIS<br>ES PERIOD|-------------------------<br>IO RI<br>TAI<br>S<br>_INIITAL_<br>mRULB|INDEPSEN<br>V<br>-----------------------<br>OC .<br>I<br>A<br>EUCONNIC<br>POLICY<br>WIALES|T<br>MIALES<br>--------<br>WO<br>RIALES<br> <br>TEPIINIG<br>WMCTION<br>UOA FATSBLE|soCIO<br>POLITICA<br>S|L<br>BWIS|
|---|---|---|---|---|---|---|---|---|---|
|KLAE<br>(O9MP|_N_<br>_ar<br>gruth<br>pmrfoice<br>b<br>thersidal<br>of<br>a groh-rate<br>fumotion<br>estid<br>an<br>bais solely of<br>the factors<br>_Indo_rnt of<br>.cm ic policy<br>_ud_maltmte the<br>lmpt of<br>m~beruhi<br>of<br>fron<br>rn by<br>oxoprh<br>the<br>rmidals of the<br>"**catrim**<br>With ths<br>of<br>other**o**<br>**"itri**|CDP<br>(Wrold<br>BE*)<br>p|54-61 DCA,<br>dtharig<br>an<br>aitblbLe<br>dots|Av.mutL<br>rate_ow_<br>20**>_s**<br>(1962-81)<br>9yms<br>(1962-70)<br>rd 12ya<br>(1970-81)|For 12-81<br>- initiaL per<br>c"ite or<br>r midel<br>of<br>initial<br>jusenIte<br>mirtaLity<br>rat (sti-<br>stdan<br>bsis of pr<br>cqA toGN)<br>- inital<br>pqpuLation<br>+<br>-<br>tural<br>popiuation<br>rowth raft<br>- ta<br>of<br>trad trad||||0.40<R-qr < 0.55<br>The<br>r<br>-of<br>thef<br>r<br>(mhatadan<br>bsis of<br>reuidals)<br>asrsto be<br>cle<br>to tht of<br>the oteOc<br>id better then<br>that ofthe<br>other African ca izs|

<!-- Start of picture text --> StU* the role of 0l 73 DC. 11 ars ad Sitlnt Export growt Active R-q r 0.53<br>(195) h fort In (Wrd 8 yvrs vwrile for rate population (1960-70)<br>roth; plify so*) Av. growth ltowl o gr-oth rat<br>the pinwl rate cwtris + R-sqr a 0.51<br>stis hr. 190-70 - Intm (197r)<br>- mnlarumt df 1910-77 rate<br>the lwe U deOf<br>- 1PcCil uite tet<br>arilys of to -<br>the sitUation heteo-<br>of the ltw wedticity<br>noom risk<br>cantria<br>- Oxcison of<br>the iquct of<br>wort wh<br>r Nd<br>after 19<br>...............................................................................................................................................................<br><!-- End of picture text -->
_t_ AELYTICAL SMNUIR OF _tNJRJT WENR_ SiDIES

||POE<br>CF SITD|RUtCLT<br>TYR_AM_<br>SMF|auMRAt-<br> ISTICSOF<br>SNE<br>0MIIRIES|INTH ItATE<br>CAATIS<br>PERWD<br>AND<br>ANALYSIS<br>Pf1|---------------......<br>_WUTAL_<br>A<br>IEIMIMSTD<br>VARIAES|INDEPEBW V<br>..........-------<br>SI<br>E=0llC-<br>l POLICY<br>VMIALES|AIAILS<br>"<br>RS<br>_111INS<br>RCT0I1<br>SWEllFA|SOCO-<br>FOLITICA<br>VAIRLES|L<br>ENAS|
|---|---|---|---|---|---|---|---|---|---|
|Rl<br>(19t6)|lw<br>tofgt.<br>**an**tle<br>of<br>pedttfvlty<br>(udnot on<br>its g)w)|GDP<br>.<br>(Smere<br>ad<br>Nsta<br>19U)|94 OCs<br>+ 21 dralqped<br>*115<br>(OC$ then<br>aparted)|11 yam<br>1960-70<br>197WD80||PeAic<br>espeur<br>grith<br>rate<br>+<br>_wor_<br>ditto<br>weighted|PapAltion<br>oresh rate<br>+<br>Shereof<br>hnwtam<br>infim<br>+||0.<br>4-aq'<br>0.45<br>Nhl<br>Irnpired<br>by FE<br>dME):<br>reallocatfin<br>offfct pleu<br>a<br>Lity|
|RM<br>(dI)<br>..................................|Exaine the<br>iqu<br>of<br>eetrml<br>aid<br>NW priwte<br>capital inftlA<br>cn g<br>r<br>.....................................................................|UP<br>(IMF,<br>IFS) plus<br>secific<br>soe<br>for Tain<br>nd Hoe<br>Keg<br>....................................|14Aian<br>catries.<br>9hsaples for<br>l<br>1o<br>ira<br>wd<br>indlwircam<br>cl<br>trein<br>......................|I wer<br>poolin<br>_or_<br>18 yms<br>195-12<br>Diffewentiated<br>pre-_ud_<br>post-1973|Per cpita<br>MPforswil,<br>atifticn<br>+<br>|_Chage_in<br>WV"<br>-<br>z ofGDP<br>+|Labo force growth<br>n.s.<br>Svirn rate itelf<br>estimeted<br>OLS<br>+<br>Extwel aid<br>aXofGP<br>+ or ns.<br>PrivAto<br>foreign<br>Ia<br>X of GP)|<br>n<br>d|0.13<R-se<0.37<br>indirct<br>lint aqA|

<!-- Start of picture text --> SIlN (19) Ipact of foreign ad oP (orld 37 Afrfcan) 73 DCs (ict. 1l0-7D 11 Yor Per cepta nam Formign aid + sarig rate + R-qr (1-71D) - 0.52<br>inwiIor Of gwt. 1101*) 190-60 G otrnmt<br>intsvutifa<br>PopAltfon interwetcn (1970-80)<br>Hasgnity + (in a Scd<br>of the 2 Regfionl aIl) The riable<br>perioc si lnt - ".rt<br>tested aid ns. but to interveuticP<br>rejected Ol Silent detriont confiscates ali<br>(pool tg n.s. of ote But it can<br>test rejected)<br>replace fomeign<br>aid<br><!-- End of picture text -->
# MLYTICAL 5~ OF THIRTY ENT SiWIES

IINDEPBD VMIMULES GRnrH RATE ----------------;;;;;W W ................................... CHARACTERCALOUTATIN RU BITAL SECTO. CF v.MI*LES PRMtJCT ISTICS OF PERICD AmI A EIONICIERSITIIG ;cioPIIIIIPISE TYPE AID SlM ANALYSIS IOIVITAL POLICY PUCITION POLITICAL _OF SMY_ SXJ NTRIES PBIRIl VBLARL4 S UUI FACTRS ARIA RS VEIERIS lqmct of Per capita 10K 1 ar: 19S7 Invwstt SocoR-qr - 0.25 wnd UPTA sociqol itial insataility GNP (tMited bsre + political inmt tility DhAOle qFAres leot (C193) (si **Adtuneu** Naticns) PopAction apatio) gh, .................... ...................................... .................................................................... ................................................................................................. HEElfR StuW r*eaos CDP 25 SurSdahren 10 yers SiLent Av. arnul S lent (1964) for Africa's (World Africen Av. growth varidtbe rate of groith variable poor growth San) countries rate eoqAl to I if of real cq.uL to 1 performean , 1970-80 v. wenal effective if cartry distinwgishing term of trait exdhuan rate has had lees betwueen growth rate calculated by then 4 fuduent l or exceeds 1 .5X _IW_ stete wrs umiro,mntL - (no cap vfriahas wd Silent Indicator of d'etat or acroic policy variable oqul weight of narfd vrieblas to 1 if total cutomry violence) abesnc of practices in out of 11 minifg wpmorts foreign-exch. (MM"e of in 1970 alLoention for political + copital goods irstability) Export ard nm-food diverifficn. cauaer gooCd indicators iaports **I.** uaarow other Difference of nonsignif. rwgir l vwriable ieaort (rainfall, prap nitiec extarnul aid, in period of migrcnt rising nd workers falling export remittane, receipts export price (_maure of instability) inoapacity to wuae trade balence qlilbrius) ..... ..

w ........... ...................... .. .. . .. . .. .. . .. .. . .. .. . .. .. . .. . .. .. . .. .. . .. .. . .. . .. .. . .. .. . .. .. . .. .
- 54 -

Table 2 AMUM MAl. GROW RATES (CDP/GNP AND WORM **_UhKIUW_** COMPARISON)

||G<br>**GDP**|DP Grow<br>**_GNP_**|th Rate<br>GDP|1970-81<br>GDPWB|GDPWB||GDP|GDP G<br>**_GNP_**|rowth Ra<br>**GDP**|te 1974-8<br>**GDPWB**|1<br>GOPWB|
|---|---|---|---|---|---|---|---|---|---|---|---|
||<br>WB|<br>WI|<br>IFS|<br>**-GNP**<br>-|<br> GDPIFS|::|<br>WB|<br>WB|<br>IFS<br>-G|<br>NPWB<br>-|GDPIFS|
|Benin|3.40|3.94|-|-0.54|-|::|4.67|4.89|-|-0.22|-|
|Cameroon|6.30|6.31|-|-0.01|-||7.82|8.04|-|-0.22|-|
|Central Afr. Rep.|1.57|1.70|<br>-|-0.13|-|::|<br>0.37|0.53|<br>-|-0.16|<br>-|
|Congo|5.52|<br>4.65|-|0.87|-|::|5.33<br>|<br>4.04<br>|-|1.29|-|
|Cote d'lvoire|6.16|6.44|-|-0.28|-|::|<br>6.21|<br>6.32|-|-0.11|-|
|Gabon|4.21|2.93|-|1.28|-|::|-5.24|-7.32|-|2.08|-|
|Burkino Faso|3.60|3.69|-|-0.09|-||3.30|<br>3.90|-|-0.60|-|
|Mall|4.60|4.78|-|-0.19|-|::|5.33|5.69|-|-0.36|-|
|Niger|3.13|2.99|-|0.14|-||6.74|<br>6.97|-|-0.23|-|
|Senegal|1.97|1.76|-|0.21|-|::|1.08|0.66|-|0.42|-|
|Chad|-2.55|-2.64|-|0.09|-||-6.03|-6.04|-|0.01|-|
|Togo|3.20|3.18|2.68|<br>0.02|0.52|::|<br>2.66|<br>2.40|3.65|0.26|-0.99|
|Angola|-5.66|-5.66|-|0.00|-|::|-3.32|-3.32|-|0.00|-|
|Botewana|12.57|12.59|13.92|<br>-0.02|-1.35||9.09|8.20|10.64|<br>0.89|-1.55|
|Burundi|3,51|3.78|<br>3.68|<br>-0.27|-0.17|::|<br>4.79|5.04|4.82|-0.25|-0.03|
|Ethiopia|2.59|2.66|2.27|<br>-0.07|0.32|::|<br>2.65|<br>2.74|2.45|-0.09|0.20|
|<br>Gambia|4.48|4.70|-|-0.22|-|::|1.57|1.17|-|0.40|-|
|Ghana|-0.25|-0.24|0.42|<br>-0.01|-0.67|::|<br>-0.42|-0.57|-0.43|0.15|0.01|
|Guinea<br>|3.08<br>|2.99<br>|-|0.09<br>|-|::|2.25<br>|2.02<br>|-|0.23<br>|-|
|Guinea-Bissau|3.08|2.65|-|0.43|-|::|2.68|2.73|-|-0.05|-|
|Kenya|6.21|6.27|5.53|<br>-0.06|0.68||5.27|<br>5.51|5.36|-0.24|-0.09|
|Lesotho|8.58|10.44|-|-1.86|-|::|7.65|<br>7.09|-|0.56|-|
|Liberia|1.65|3.06|-0.29|<br>-1.41|1.94|<br>::|1.41|<br>3.10|-0.52|-1.69|1.93|
|Kadagascor|0.35|0.60|-|-0.25|-|::|0.55|0.49|-|0.06|-|
|Malawi|5.58|5.37|<br>4.49|<br>0.21|1.09|<br>::|5.11|<br>4.42|3.74|0.69|1.37|
|Mauritius|6.02|5.83|6.47|<br>0.19|-0.45|::|4.16|3.90|4.78|0.26|-0.62|
|Mauritania|1.63|1.83|<br>-|-0.20|-||1.41|<br>1.42|<br>-|-0.01|-|
|Mozambique|-2.06|-2.06|-|0.00|-||-1.08|-1.08|-|0.00|-|
|Nigeria|4.46|4.83|3.55|-0.37|0.91|::|1.92|2.04|1.78|-0.12|0.14|
|Uganda|-1.69|-1.61|-1.66|-0.08|-0.03|::|<br>-2.99|-2.92|-3.08|-0.07|0.09|
|Rwanda|5.30|5.28|-|0.02|-|::|5.52|5.70|-|-0.18|-|
|Sierra Leone|1.77|1.58|<br>2.04|<br>0.19|-0.27|ss|<br>1.71|<br>1.46|2.35|0.25|-0.64|
|<br>Somalia|<br>3.87|<br>3.90|<br> <br>-|<br> <br>-0.03|<br>-|<br>ss|<br> <br> <br>6.14|<br> <br>6.15|<br>-|<br>-0.01|-|
|Sudan|6.15|6.10|-|0.05|-|:s|6.47|6.45|-|0.02|-|
|Swaziland|6.09|6.67|-|-0.58|-|::|5:<br>5.60|<br>5.72|<br>-|-0.12|-|
|Tanzania|4.23|4.24|5.47|<br>-0.01|-1.24|<br>::|<br>3.60|<br>3.64|4.91|-0.04|-1.31|
|**Zaire**|-0.23|**0.05**|-0.22|-0.28|-0.01|ss|<br>-1.51|<br>-1.30|-1.48|-0.21|-0.03|
|Zambia<br>Zimbabwe|0.39<br>1.76|0.39<br>1.83|1.21<br> <br>2.0S|<br>0.00<br> <br>-0.07|-0.82<br>-0.29|ss<br>::|<br>-1.56<br> <br>-0.21|-1.54<br> <br>-0.11|0.09<br>1.40|-0.02<br>-0.10|-1.65<br>-1.61|
|<br>Afghanistan|<br>-|<br>-|<br> <br>-|<br> <br>-|<br>-|<br>ss|<br> <br> <br>-|<br> <br>-|<br>-|<br>-|-|
|Algeria|6.90|6.38|-|0.52|-|ss|<br>7.28|6.46|-|0.82|-|
|<br>Argentina|1.94|1.82|<br>2.01|<br>0.12|-0.07|ss|<br>1.13|<br>0.81|1.30|0.32|-0.17|
|<br>Bangladesh<br>Bht|4.12|4.20<br>206|-<br>|-0.08|-|ss<br>ss|<br>5.46|5.66<br>204|5.02|-0.20|0.44|
|uan<br>Surma|-<br>4.83|.<br>4.77|<br>-<br>4.57|-<br> <br>0.06|-<br>0.26|<br>ss|-<br> <br>6.11|.<br>6.06|-<br>6.11|-<br>0.05|-<br>0.00|
- 55 -

Table 2

**A*ehE ADaL GWN SAWS (,u/=P AND** **_1OW SWA/W_ oaARISU )**

||<br>**GDP**|GDP Grow<br>**GNP**|th Rate<br>GDP|1970-81<br>GDPWF|GDPI|:3<br>3:|<br>GDP|GDP G<br>CON|rowth**Ra**<br>GDP|**te**1974-<br>GDPWS|81<br>GDPWB|
|---|---|---|---|---|---|---|---|---|---|---|---|
||<br>Ws|<br>W8|<br>IFS|<br>- GNP -G|<br>DPIFS|<br>:|<br>WB|<br>Ws|<br>IFS_-_|<br>_GNP8_<br>-|GDPI?S|
|Bolivia|4.36|<br>4.03|4.16|0.33|0.20|::|<br>3.00|<br>2.32|<br>2.63|<br>0.68|<br>0.37|
|Bratil|7.72|<br>7.45|<br>7.76|<br>0.27|-0.04|:|5.71|<br>5.32|<br>5.84|0.39|<br>-0.13|
|Chile<br>|2.07|<br>1.81|<br>2.09|0.26|-0.02|<br>::|<br>5.57|<br>5.35|<br>5.62|<br>0.22|<br>-0.05|
|China<br>|-<br>|-<br> <br>|-<br> <br>|-<br>|-<br>|s:|<br>-<br>|-<br>|-|-|-|
|Cyprus|5.82|<br>5.86|<br>2.56|-0.04|3.26|:<br>|8.17|<br>7.9e|<br>7.33|0.21|<br>0.84|
|Colombia|5.61|<br>5.78|<br>5.24|-0.17|0.37|::<br>::|<br>5.25|<br>5.36|<br>4.94|-0.11|<br>0.31|
|Cost& Rica<br>Cb|5.22<br>|<br>4.78|5.32|0.44|-0.10|::|<br>4.29|<br>3.59|<br>4.50|0.70|<br>-0.21|
|ua<br>Egypt|-<br>7.54|-<br> <br>8.21|-|-<br>-0.67|-|::|<br>9.95|-<br> 10.15|-<br> <br>-|-<br>-0.20|<br>-|
|El Salvador|3.18|<br>3.21|<br>3.20|-0.03|-0.02|::|<br>0.89|<br>0.91|<br>0.92|-0.02|<br>-0.03|
|Ecuador|8.58|<br>8.23|8.59|0.35|-0.01|::|<br>6.15|<br>5.6S|<br>6.17|O.S0|<br>-0.02|
|Fiji|4.54|<br>4.86|-|-0.32|-|::|<br>3.87|<br>3.81|<br>-|0.06|<br>-|
|Guatemala<br>|5.49<br>|<br>5.67<br> <br>|<br>5.48<br> <br>|-0.18<br> <br>|0.01<br>|5:|4.99<br>|<br>5.13<br> <br>|<br>4.97<br> <br>|-0.14<br>|<br>0.02<br> <br>|
|Guyana<br>Haiti|1.50<br>3.36|<br>1.71<br> <br>3.37|<br>1.93<br> <br>4.29|<br>-0.21<br>-0.01|-0.43<br>-0.93|:<br>::<br>|0.12<br> <br>3.43|<br>-0.29<br> <br>3.38|<br>0.56<br> <br>4.41|0.41<br>0.05|<br>-0.ai<br> <br>-0.98|
|Ronduras|4.39|<br>4.13|13.92|<br>0.26|-9.53|;:<br>s:|<br>5.86|<br>5.24|<br>12.15|<br>0.62|<br>-6.29|
|Hong Kong|9.96|<br>9.96|-|0.00|-|:s|11.45|<br>11.45|<br>-|0.00|<br>-|
|India<br>|3.63<br>|<br>3.73<br> <br>|<br>3.67<br> <br>|-0.10<br>|-0.04<br>|s:|<br>4.15<br>|<br>4.22<br> <br>|<br>4.21<br> <br>|-0.07<br>|<br>-0.06<br> <br>|
|Indonesia<br>Iran|7.82<br>-|<br>7.33<br>-|<br>7.85<br>2.66|0.49<br>-|-0.03<br>-|ss<br>|<br>7.61<br>-|<br>7.29<br>-|<br>7.64<br>-3.26|0.32<br>-|<br>-0.03<br>-|
|Iraq|-|-|-|-|-|3::|-|-|-|-|-|
|<br>i|11|<br>130|12|01|||<br>2||||<br>|
|Jamaca<br>Jordan<br>|-.5<br>-|<br>-.<br>-|-.5<br>7.56|.5<br>-|0.10<br>-|ss<br>:c|<br>-.17<br> 10.53|-3.19<br> <br>11.27|-2.24<br>12.03|1.02<br> <br>-0.74|<br>0.07<br> <br>-1.50|
|Libya|-||||||-|-|-|-|-|
|Macao|-|-|-|-|_|-||-|-|-|-|
|Malaysta|7.80|<br>7.72|14*.|0.08|-6.64|::|<br>7.6e|<br>7.71|<br>19.12|<br>-0.03|-11.44|
|<br>Morocco<br>|5.24<br>|<br>5.47<br> <br>|<br>5.45<br>|-0.23<br>|-0.21<br>|::|<br>4.90<br>|<br>4.57<br> <br>|<br>4.32<br> <br>|0.33<br>|<br>0.58<br> <br>|
|Mxleco<br>Monolia|6.53<br>-|<br>6.38<br>-|6.53<br>-|0.15<br>-|0.00<br>-|::|<br>6.72<br>-|<br>6.49<br>-|<br>6.72<br>|0.23<br>|<br>0.00|
|g<br>_Nepal_|2.12|<br>2.15|2.71|-0.03|-0.59<br>"|:|1.60|<br>1.64|-<br> <br>2.83|-<br>-0.04|-<br> <br>-1.23|
|Nicaragu|0.79|0.72|1.15|0.07|-0.36|za|-3.11|-3.26|<br>-3.04|0.15|<br>-0.07|
|Pakistan|495|526|504|-031|-009|:s|570|<br>613|<br>592|-043|<br>-022|
|<br>PanaM|.<br>4.55|.<br>4.55|.<br>4.69|.<br>0.00|.<br>-0.14|<br>s:|.<br> <br>5.35|<br>.<br> <br>5.17|<br>.<br> <br>5.65|.<br>0.18|<br>.<br> <br>-0.30|
|_PapuaNow Guinea_|207|<br>207|328|000|-121|a:|<br>126|<br>127|<br>104|<br>-001|<br>022|
|<br>Paraguay|.<br>8.80|<br>.<br> <br>8.90|.<br>8.80|.<br>-0.10|.<br>0.00|<br>::|<br>.<br> <br>10.10|<br>.<br> <br>10.14|<br>.<br>10.11|<br>.<br> <br>-0.04|<br>.<br> <br>-0.01|
|Peru|3.08|<br>2.82|3.13|0.26|-0.05|s:|<br>2.15|<br>1.68|<br>1.70|<br>0.47|<br>0.45|
|Philipplnes|6.23|<br>6.37|-|-0.14|-|ss|<br>6.12|<br>6.04|<br>-|0.08|<br>-|
|<br>Puerto<br>Rico|-|-|-|<br>-|-|<br>s:|<br> <br> <br>-|<br> <br>-|<br>-|<br>-|<br>-|
|Korea|9.02|<br>8.68|8.71|0.34|0.31|:3|7.83|<br>7.38|<br>7.84|0.45|<br>-0.01|
|Dominican lap.|<br>6.30|<br> <br> <br>6.08|<br>6.33|<br>0.22|<br>-0.03|<br>a:|<br> <br>4.63|<br> <br> <br>4.38|<br> <br> <br>4.69|<br>0.25|<br><br> <br>-0.06|
|Singapore|8.5S|<br>8.31|8.55|0.24|0.00|:s|<br>8.43|<br>8.31|<br>8.44|0.12|<br>-0.01|
|Sri Laka|4.68|<br>4.72|4.92|-0.04|-0.24|:t|<br>5.95|<br>5.90|<br>5.48|0.05|<br>0.47|
|Syria<br>|9.43|9.35|9.26|0.08|0.17|::<br>|<br>6.72|<br>6.59|<br>6.89|0.13|<br>-0.17|
|Taiwan<br>|-<br>|-<br> <br>|-<br>|-<br>|-<br>|:3|-<br>|-<br> <br>|-<br> <br>|-<br>|-<br> <br>|
|Thailand|7.22|<br>6.84|7.20|0.38|0.02|ss|7.52|<br>6.83|<br>7.46|0.69|<br>0.06|
|Trinidad and Tobago|505|<br>540|456|-035|049|st|<br>678|<br>823|<br>508|-145|<br>170|
|<br>Tunitia<br>Turke|.<br>7.40<br>519|<br>.<br>7.59<br>501|.<br>6.38<br>|.<br>-0.19<br>018|.<br>1.02<br>|<br>s:<br>|<br>.<br> <br>6.60<br> <br>334|<br>.<br>6.86<br> <br>311|<br>.<br>6.03<br> <br>|.<br>-0.26<br>023|<br>.<br>0.57<br> <br>|
|y<br>Uruguay|.<br>3.13|.<br>3.14|-<br>3.28|.<br>-0.0'|-<br>-0.15|:s|<br>.<br>4:<br>4.06|<br>.<br>4.19|<br>-<br>4.37|.<br>-0.13|<br>-<br>-0.31|
|<br>Venezuela|4*.54|5.19|4.41|-0.65|0.13|:|3.47|3.81|3.23|-0.34|0.24|
|Ymenn|880|869|882|011|-002|3|740|<br>69"|<br>744|041|<br>-004|
|<br>Yugoslavia|.<br>5.82|.<br>5.71|.<br>5.56|.<br>0.11|.<br>0.26|:<br>:3|.<br>5.20|<br>.<br>4.96|<br>.<br>5.27|.<br>0.24|<br>.<br>-0.07|
# Table 3

# ILLUSTRATIVE IOOEL: COWARISON OF THE DIFFEfENT REGSSINS

||_MNsber_of|||P|6|X|||||
|---|---|---|---|---|---|---|---|---|---|---|
||:countrles:Constan|t<br>y|:<br>N|--|--|-||R<sup>2</sup>|F|RSS|
||*|||:<br>~~~P|Y|rY|||||
|1.<br>6PAW<br>c.palson:|||||||||||
|(source:<br>VorldBank)|||||||||||
|Growthrate|||||||||||
|1970-1|69||||||||||
|O1)GDP|1,96ff|0,422<br>0(1,133)|: 0,373<br>:<br>1,837)0**|-0,034<br> <br> <br>(2,712)0<br>|: -0,012<br>:<br>(0,378)|: 0,5<br>: (4,485)*|:|<br>0,34|6,538|307,904|
|_(2)_6NP|2,390|:0,350|:0,335|-0,036<br>|:-0,004|0,4||0,30|5,473|326,658|
|||* (0,909)|: (1,594)|(2,733)**|:<br>(0,130)|: (4,04 )**|:||:||
|2<br>World ank/W:|||:|:|:||||||
|GOPC4=wIson<br>GVPC:a:ls:n:|||:||:::::||||||
|.<br>Growth rate|||||||||||
|197041|49||||||||||
|(3<br>Wrd<br>lak:|:||-|<br>|||||||
|<br> <br> <br>_(3)_<br>_Ibold IBook_||:|:|:<br>|::::||||||
|World Tables 1964|1,766|0,558|0,387|-0,036<br>|: -0,039|: 0,4||0,39|5,601|236,553|
|||_(1,181)_|: (1,394)*|(2,601)6*|(0,066)|(3,821)|||||
|_(4)_<br>_IW_IFS|0,577|: 0,424|: 0,238|-0,038<br>|: -,05|0,5||0,33-|4,290|375,646|
|||*(0,712)|:(2,205)§*|(0,600)<br>|:<br>(0,66)|(3,448)"|||||
-2-

||Nsmbr|of:|||P|G|X||||
|---|---|---|---|---|---|---|---|---|---|---|
||.count|rias:Con|stantv|N|--|||2-|F|i<br>RSS|
|||*|||~P|Y|Y||||
|3. Pmgresslons|||||||||||
|comparlson,|||||||||||
|b0 baO|40||||||||||
|(5) Calculation<br>bse 1970||1,78|0,678<br>(1,500)|0,023<br>' (0,078)|-0,036<br> :<br>(2,208)"*|0,052<br>(1,023|: 1,0<br>):(5,458)**<br>"|0,55<br>|<br>8,22|: 146,44|
|(6) CaIculation<br>bas 1971|<br>:|1,69|:<br>0,646<br>(1,445)|0,018<br>* : (0,064)|:<br>-0,036<br> <br>(2,231)*"|-0,04<br>(0,955|1,0<br>)<br>(5,45)-|0,54|<br>8,14|<br>144,74|
|(7) Calculation<br>bas 1972||1,56|0,671<br>: (1,529)|0,020<br>r (0,072)|-0,037<br> <br>(2,278)"|-0,043<br>(o,862|<br>1,0<br>)<br>(5,568)"|0,55|<br>8,38|<br>139,72|
|(8) Calculation<br>bas 1973|:|: 0,69|0,608<br>:(1,832)|0,195<br>"0 (0.684)|-0,039<br>:<br> <br>(2,#13)0|-0,046<br>(0,958|<br>1,0<br>)<br>(5,549)|0,56|<br>8,57|<br>141,07|
|(9) Calculation<br>bas 1974||1,38|0,682<br>(1-629)|0,196<br>9 (0,723)|-0,036<br> :<br>((2,36)"|-0,058<br>(1,222|<br>1,0<br>)<br>(6,026)-*|0,60<br>|<br>10,04|<br>126,90|
|(10) Calculatlon<br>bse 1975||1,05|0,719<br>(1,756)|0,21<br>* (0,789)|-0,037<br> <br>(2,473)"|-0,052)<br>(1,123|1,0<br>)<br>(6,227)*|0,61<br>|<br>10,56<br>:|:<br>121,70<br>-.|
|(11) Calculation<br>base 1976||1,11<br>:|0,720<br>:<(1,756)|0,193<br>*" (0,726)|-0,038<br> <br>(2,522)*"|-0,054<br>(1,163|<br>1,0<br>)<br>(6,161)":|0,61<br>|: 10,48|<br>121,82|
|(12) Calculation<br>base 1977|:|:.1,06|:<br>0,729<br>:.(1,769)"*|0,114<br>(0,729)|-0,037<br> <br>(2,466)"|-0,057<br>(1,228|1,0<br>)<br>(6,130)"|0,61|10,44|<br>123,00|
|(13) CalculatIon<br>base 1978||0,60|0,796<br>(I,866)|0,220<br>"* (0,603)|-0,036<br> <br>(2,471)":|-0,057<br>(1,187)|1,0<br>(5,66)"*|0,59|<br>9,74|129,62|
|(14)Calculation<br>bse1979||0,96|0,748<br>(1,724)**|0,186<br> <br>(0,661)|-0,038<br>(2,366)**|-0,061<br>(1,244|<br>1,1<br>)(6,135)**|0,60|<br>10,36|<br>136,49|
|(15) Calculation<br>bse 1960||1,53|0,603<br>(1,572)|0,133<br>"* (0,474)|-0,038<br> <br>(2,363)*"|-0,064<br>(1,315|1,1<br>)' (6,426)"*|0,62<br>|11,23|<br>136,82|
|(16) Calculation base 1961||0,72|0,810<br>"|0,187<br> <br>|-0,041<br>"*|-0,062<br>|1,1<br> <br>|0,62|11,14|139,53|
||||(1,645)§|<br>(0,658)|(2,537)|(1,251)|<br>(6,347)||||
|(17) World TeOblas<br>data||0,85|0,604|0,155|:-0,041|-0,051|1,0|0,58|9,44|129,42|
||||(1,902)"|:(0,566)|(2,665)**|(1,072)|(5,736)*||||
-3

||Number|of:||P|G|X||||
|---|---|---|---|---|---|---|---|---|---|
||:countrlo|s:Constant<br>y|N||||R-2|F|RSS|
||:|:<br>: .|:|:<br>F|Y|Y||||
|4.<br>Regressions||||||||||
|comparison,||||||||||
|forvarious||:||:||||||
|samples|:|||||||||
|GOPgrowth rat*<br>(1970-81)||:||||||||
|source World Bank||||||||||
|(a)<br>Bygeographic<br>areas||||||||||
|Cf. total<br>sample||||||||||
|(equatlon<br>1)|69|||||||||
|(18) Total sample minus||||||||||
|Latin America|47|3,023<br>0,174|:<br>0,338|:-0,077<br>|:<br>0,027|:0,4|0,35|4,498|215,4:1<br>00|
|||;*(0,299)|<br>(1,402)*|<br>(1,705)**|(0,604)|:(3,325)*|*|||
|(19)<br>Latin America alone|:<br>22|-0,855<br>1,114|0,448|:<br>-0,034|-0,097|0,5|0,50|3,258|64,066|
|||:(1,318)|(1,067)|-2,228)"<br>|:<br>(1,438)'|(1,409)*||||
|(20) Asia alon|14|-12,204 1,985|0,848|0,209<br>|:<br>0,096|0,1|0,53|:1,833(1)|31,018|
|||:(1,687)*|(1,729)*|<br>(1,336)|(1,036)|<br>(0,738)||||
|(21)<br>Africa alone|28|5,580:-0,34|0,132|-0,042|-0,013|1,3|0,64|8,014|75,779|
|||:(0,465)|(0,354)|(0,963)|(0,246)|(5,243)*||||
-4-

||Number of:|||P|G|X||||
|---|---|---|---|---|---|---|---|---|---|
||:countries:Con|stanty|N||:2|:||F|RSS|
||:<br>:|||P<br>|:<br>Y|V||||
|(b) Elimination<br>of outliers||||||||||
|or aberrant<br>countries||||||||||
|Cf. total sape (eq. 1)|69<br>:|||||||||
|(22) Total sample mInus||||||||||
|th country with|:|||||||||
|the largest<br>residual||||||||||
|In equatIon 1|68<br>0,937|: 0,611|: 0,,464 :|-0,037<br>|: -0,019|0.4|0,33|<br>6,165|<br>219,977|
|(without botiwona)||:(1,707)|: (2,385)**<br>:|<br>(3,07 )<br>|: (0,614)|(3,52 )*|:|||
|(23) Total sample ainus||||||||||
|the two countrls|:<br>:|||||||||
|with tho largest|:|:|:|||||||
|residuals in equatio|n :<br>::|||||||||
|1 (without<br>Syria and|: 67<br>1,826|: 0,534|: 0,404<br>:|-0,034<br>|: -0,04|: 0,4|0,36|<br>6,961|<br>190,509|
|Botswana)||: (1,557)|: (2,160)**<br>:|<br>(2,964)*|: (1,29M)|* (3,73)**||||
|(24) Total**sample**minus||:|||:|||||
|the thr _ countries|<br>:|||||||||
|with the largest|:|||||||||
|residuals In equatio|n:||:||:|||||
|1 (without<br>Jamalca,|: 66<br>1,064|: 0,65|: 0,395<br>:|-0,036<br>|: -0,03|: 0,4|: 0,37|<br>7,011|<br>246,669|
|Syria and Botswana)||: (1,955)*|*<br>: (2,199)**<br>:|<br>(3,216)*"<br>|<br>: (1,000)|: (3,695)*"||||
|(25)Totel**sample**minus|:<br>:|:||||||||
|the 4 countries wIth|:|||||||||
|the largest<br>residual|s ::|||||||||
|In equationI(with-|:<br>:||:|||||||
|out Lesotho,<br>Jamalca|, : 65<br>0,064|: 0,820|: 0,473<br>:|-0,037<br>|: -0,337|: 0,3|: 0,43|: 8,790|<br>270,422|
||<br>|256**|2774*|359*"|<br>(1311|(3790)*|:|||
|Syria and Botswana)|:<br>:|:,)|: (,) :|(,)|<br>,|: ,||||
|(26) Total**sample**minus|**:**<br>68<br>0,374|: 0,623|: 0,416<br>:|-0,03J<br>|: -0,007|0,9|0,45|: 10,337|: 242,638|
|Slngapor:||: (1,833|: (2,265)"*<br>:|<br>(3,354)*"<br>|<br>: (0,243)|: (5,172)*|:|||
||:Nmber|of:||:|<br>:||X|||||
|---|---|---|---|---|---|---|---|---|---|---|---|
||:countrle|s:Constant|<br>y|N<br>:|<br>-<br>|i|||2|F|RSS|
||S. PAM|SP||||Y|Y|||||
|5.Regressions::::::::::||||||||||||
|cmperlson||||||||||||
|by perlod.||||||||||||
|GOPgrowth rate.||||||||||||
|Source wrld<br>Bank||||||||||||
|1970-61:<br>cf.eq.1|69|||||||||||
|(27) 1974-41|69|2,663|:<br>0,216|0,473<br>:|<br>-0,032<br>:|<br>-0,016|0,4||0,32|5,942|376,01|
||||;(O,S49)|<br>(2,009)*s|(2,461)|(0,467)|(4,n221)ss|||||
|6.<br>Cross-sectIonal<br>analysis/||||||||||||
|pooling<br>comparison||||||||||||
|(28)<br>Cross-sectional||||||||||||
|regression:||||||||||||
|averae<br>GOPgrowth|||||||||||I|
|rate<br>(1974-81).|:|||||||||||
|Source:<br>World Bonk|40|3,623|:<br>0,110|:<br>0,456<br>:|<br>-0,026<br>:|<br>-0,034|:<br>0,4|:|0,40|4,600|190,37<br>0|
||||1<br>(0,210)|: (1,634)*<br>:|<br>(1,029)|(0,639)|: (3,478)"|:|||I|
|(29)Pooling||||||||||||
|regression:|:|:|:|:||||||||
|annualGOPgrowth||||||||||||
|rate (197541).||||||||||||
|Source: World Benk|40|2,729|:<br>0,192|:0,547<br>:|<br>-0,043<br>:|<br>-0,016|0,473||0,27|20,790|5345,35|
|(280 observations)|||: (0,599)|: (2,907)*|(4,665)ss :|(0,470)|<br>(7,627)*"|||||

Meaning nd sourc of the Independent variables:

- y: Per capita 6NP In USS In Initial **year** ) Source:

- N: Number of Inhabitants In initial year ) World Bank

- _Y:_ Gross doestic product In national currency ) World Tables, 1964

- P: Consume price Index (sourco: _IW,_ IFS)

- 6: Total public expenditure of central government (source: IF, _Government_ Finance Statistics Yearbook - 1906

# Betwoen parenthebss student T:

* Significant at 5S a: Significant at 10%.
- 61 -

lhbl 4

# AVEAE A .L 03 CDP iI RAES (umnTi-m 10 **P'tML** in493sm)

**aW** mm a **z WRm** DoU"If **BS**

|WB|170|71|72|73|74|75|76|77|78|79|s)|81|KaN|Px|DSP|WAH|s|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Bonin<br>3.31<br>6.30<br>oKCM<br>Afrim<br>bP<br>157|-<br>6.32<br>-|-<br>6.34<br>-|3.77<br>6.31<br>-|3.77<br>6.29<br>-|3.82<br>6.28<br>I()|5.03<br>6.32<br>165|4.96<br>6.33<br>161|5.01<br>6.44<br>167|4.86<br>6.57<br>16|4.90<br>6.34<br>-|4.98<br>6.37<br>-|4.94<br>6.28<br>-|3.77<br>6.28<br>161|5.03<br>6.57<br>169|1.26<br>0.29<br>008|<br>4.60<br> <br>6.35<br>166|0.57<br>o.as<br>003|
|<br> <br>.<br>.<br>Cam<br>5.52|4.80|4.57|4.70|4.80|.,<br>4.88|.<br>5.33|.<br>5.62|.<br>5.30|.<br>5.36|5.68|6.76|7.48|.<br>4.:|.<br>7.48|.<br>2.91|.<br> <br>5.44|.<br>0.88|
|Cate d'StU<br>6.16|6.76|6.90|6.83|6.65|6.43|6.56|6.35|6.16|6.3D|6.16|6.19|6.21|6.16|6.90|0.74|<br>6.46|0.27|
|GihM<br>-<br>_budm_<br>raw<br>3.55|-<br>3.55|-<br>3.55|-<br>3.43|-<br>3.45|-<br>3.42|-<br>3.49|-<br>3.33|-<br>3.33|-<br>3.27|-<br>3.29|-<br>3.29|-<br>3.3D|-<br>3.27|-<br>3.55|-<br>0.28|3.39|_<br>.10|
|NW<br>4.60|-|-|-|-|_|_|_||_|_||||_|_|||
|NLW<br>3.U||-|-|-|-|-|-<br>_|-<br>_<br>_|-|-|-|-|-|||||
|_-ed<br>1.97|1.72|1.76|1.;9|_1.77_|1.69|2.03|<br>2.05|<br><br>1.87|1.62|1.97|2.27|2.26|1.62|2.27|0.65|1.91|0.21|
|Chad<br>-2.55|-2.76|-2.n|--2.79|-2.74|-2.58|-2.42|-2.54<br>|-2.55|-2.55|-0.38|-0.17|-0.20|-2.79|-0.17|2.62|-2.03|1.08|
|1bIP<br>3.20|-|-|-|-|-|-|20|4.33|3.43|2.83|4.13|4.07|2.83|4.33|1.50|3.66|0.60|
|A0102k<br>-7.3<br> <br>|-7.3<br>|-7.43<br>|-7.48<br>|-6.97<br>|-5.93<br>|-6.32<br>|-6.98<br>|-7.09<br>|-7.23<br>|-7.17<br>|-6.57<br>|-6.53<br>|-7.48<br>|-5.93<br>|1.55<br>|-6.91<br>|0.48<br>|
|_10ComwA_<br>12.57|12.82|12.92|12.88|12.90|12.40|U.42|.30|12.40|12.08|u2.88|13.09|12.52|_12U0_|13.09|1.01|12.61|0.32|
|3.19|-|-|-|-||-|-|-||-|-|4.5|4.15|4.15|0.00|4.1U|-|
|Ethopg<br>2.16<br>44|2.16<br>-|2.15<br>-|2.21<br>-|2.18<br>-|2.14<br>-|2.19<br>-|2.13<br>-|2.05|1.99<br>-|2.00<br>-|2.00<br>-|2.01|1.99<br>-|2.21<br>-|0.22<br>-|<br>2.10<br>-|0.08<br>-|
|.<br>(Almas<br>-0.25|0.26|0.19|0.08|-0.03|-0.10|-0.25|-0.34|-0.24|-0.37|-0.47|-0.46|-1.07|-1.07|0.26|1.33|-0.23|0.36|
|<br>_OAVM_<br>3.31|-|-|-|2.92|3.11|3.41|3.63|3.66|3.63|3.64|-|-|2.92|3.64|o.n|3.43|0.30|
|QdAtinLmm<br>3.08|4.04|3.97|3.99|4.07|4.10|-|-|-|-|-|-|-|3.97|4.10|0.13|4.03|0.05|
|5.76|6.21|6.23|5S|5.8D|5.74|5.76|5.67|5.58|5.67|5.69|5.71|5.73|5.58|6.23|0.65|5.8D|0.21|
|1A.athO<br>7.84<br> <br>|2.43<br>|2.57<br>|3.28<br>|3.80<br>|3.70<br>|3.18<br>|3.79<br>|3.95<br>|4.50<br>|4.71<br>|7.64<br>|-|2.43<br>|7.64<br>|5.21<br>|<br>3.96<br>|1.41<br>|
|LUia<br>1.23<br>035|1.16<br>-|1.21<br>035|1.14<br>035|1.37<br>034|1.3S<br>03D|_0A_<br>03D|1.04<br>028|1.05<br>025|1.33<br>025|1.58<br>022|1.68<br>022|-<br>029|0.81<br>022|1.68<br>035|0.87<br>013|1.25<br>029|0.25<br>005|
|.<br>Molad<br>6.23|6.26|.<br>6.27|.<br>6.26|.<br>6.26|.<br>6.26|.<br>6.26|.<br>6.32|.<br>6.26|.<br>6.26|.<br>6.26|.<br>-|.<br>-|.<br>6.26|.<br>6.321|.<br>0.06|.<br>6.27|.<br>0.02|
|_?bwitda_<br>6.20|7.05|7.01|6.96|6.71|5.14|5.27|5.18|5.27|5.42|5.31|5.62|5.59|5.14|7.05|1.9t|5.88|0.80|
|lbwitaia<br>t.72|-|-|-|5.97|5.82|5.23|5.3S|6.L5|6.23|6.97|5.89|6.14|5.38|6.97|1.69|<br>5.98|0.50|
|Ima*Lqn<br>-2.12<br>|-2.12<br>|-2.11<br>|-2.10<br>|-2.17<br>|-2.09<br>|-2.18<br>|-2.21<br>|-2.25<br>|-2.27<br>|-2.28<br>|-2.27<br>|-2.27<br>|-2.28<br>|-2.09<br>|0.19<br>|-2.19<br> <br>|0.07<br>|
|4.56<br>_1~ussa_<br>-1.57|1.1l<br>-3.02|1.02<br>-2.75|0.93<br>-2.97|8.09<br>-3.M|7.00<br>-2.87|7.28<br>-2.34|7.19<br>-2.21|7.01<br>-|6.92<br>-|6.82<br>-|6.75<br>-|6.70<br>-|0.93<br>-3.02|8.09<br>-2.21|7.16<br>0.81|<br>5.57<br>-2.74|2.77<br>0.33|
|drAs<br>5.87|-|-|5.76|5*.69|<br>5,70|4.19|6.23|6.36|6.34|6.29|6.31|6.31|5.69|6.34|0.65|6.12|0.28|
|_<br>_s1a!m_tam<br>1.87<br> <br>|2.02|2.14|2.11|1.87|1.52|1.82|2.06|1.78|1.00|0.42|0.79|0.85|0.42|2.14|1.72|<br>1.53|0.60|
|Sis<br>3.39<br>10dm<br>656|-<br>594|-<br>59|-<br>594|-<br>655|655|655|655|654|654|-<br>652|-<br>656|-<br>655|-<br>594|-<br>656|-<br>062|-<br>639|-<br>027|
|<br>.<br>4.49|.<br>1.48|.<br>1.48|.<br>-|.<br>-|.<br>-|.<br>-|.<br>-|.<br>-|.<br>-|.<br>-|.<br>-|.<br>-|.<br>1.48|.<br>1.4S|.<br>o.ao|.<br>1.48|.<br>0.00|
|_T?m..Ua_<br>_3.96_|<br>3.90|3.91|3.82|3.73|3.69|_3A._|3.55|_3.3_|3.42|3.39|3.34|3.31|3.31|3.91|0.60|3.59|0.22|
|<br>Zd=<br>_-O3_|<br>0.23|.0.11|0.06|-0.24|-0.38|-0.52|-0.85|-1.03|-1.04|-1.6|-1.68|-1.84|-1.84|0.06|I.90|_-0.77_|0.63|
|Za<br>0.39|0.41|0.62|0.61|0.37|0.25|0.62|0.57|0.70|0.61|0.31|0.27|0.33|0.25|0.70|0.45|0.47<br>|0.16<br>|
|Z2-d-<br>1.80<br>AfItdft<br>3S6|1.61<br>|1.61|1.61|1.61|1.61|1.61|1.61|1.61|1.61|1.55|-|-|1.55|1.61|0.06|1.60|0.02|
|m<br>.|<br>-|-|-|-|-|-|-|-|_|_|-|_|_|_|_|_|_|
|AllarIa<br>6.9D<br>194|-<br>196|-<br>195|-<br>19|-<br>203|-<br>204|-<br>196|-<br>186|-<br>_195_|-<br>If|-<br>198|-<br>203|-|-<br>186|-<br>204|-<br>048|-<br>196|-<br>005|
|.|.|.|.|.|.<br>|.<br>|.<br>|_._<br>|.|.<br>|.<br>|-<br>|.<br>|.<br>|.<br>|.<br> <br>|.<br>|
|4.12|4.64|4.61|4.12|4.12|3.96|3.65|3.76|3.75|3.70|3.65|3.56|3.70|3.56|4.64|1.08|<br>3.93|0.37|
|4.83|4.8|4.83|4.8|4.8D|4.62|4.54|4.53|_4.54_|4.55|4.54|_4.54_|4.55|4.53|4.83|0.3D|<br>4.64|0.13|
|bIivI*<br>4.36<br>|4.36<br>|4.45|4.3D|4.21|3.97|4.12|4.19|4.18|-|4.02|4.02|4.16|3.97<br>|4.45<br>|0.48<br>|<br>4.18<br> <br>|0.15|
|8.35|8.63|-|-|-|-|-|-|-|-|-|-|-|8.63|8.63|0.00|<br>8.63|-|
|_Ohis_<br>2.07<br>|2.46|2.41|2.43|2.44|2.33|2.48|2.39|2.38|2.34|2.40|2.38|2.33|2.33|2.48|0.15|<br>2.40|0.05|
|adn,<br>-|-|-|-|-|-|-|_|-|_|_|_|_|_|_|_|||
|_Cnm_<br>5.52|5.61|5.73|5.82|5.51|5.65|5.70|5.59|5.65|5.79|5.87|5.97|5.98|5.51|5.98|0.47|5.74|0.15|
- 62 -

Thble 6

||aP GE|WtRAU|VtlHO|WE=1t|MM Y||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
||*|70|71|72|73|74|75|76|77|78|79|OD|6I|%a|1X|Dv|.f*|s|
|COIOW.|5.68|-|-|-|-|-|-|-|-|-|-|-|5.42|5.42|5.42|<br>0.0D|5.42|-|
|nta&_>cz_|5.22|5.26|5.3D|<br>5.31|5.28|5.21|5.17|5.14|5.00|5.04|5.03|5.05|4.94|4.9|5.31|<br>0.37|5.14|<br>0.13|
|Olbs<br>FpC|-<br>8.10|-<br>8.75|-<br>8.70|-<br>8.64|-<br>-<br>8.48|----<br>-|-|-|7.78|7.92|8.04|7.87|-|7.78|_<br>8.75|0.97|8.27|0.41|
|<br>I saI,r|3.13|3.12|3.11|3.09|3.09|3.a9|3.09|3.06|3.06|3.10|3.06|3.07|3.04|3.04|3.12|0.08|3.08|0.02|
|eCUMN|8.58|8.22|8.21|8.06|8.26|8.86|8.56|8.39|8.41|8.16|8.69|9.11|8.93|8.08|9.11|1.03|8.49|0.34|
|<br>Fiji|<br>4.63|<br>5.03|<br>4.91|<br>4.81|<br>4.65|<br>4.56|<br>4.50|<br>4.44|<br>4.63|<br>-|<br>-|<br>-|<br>-|<br>4.44|<br>5.03|<br>0.59|<br>4.69|0.2D|
|<br>oata|5.49|-|-|-|-|-|-|-|-|-|-||||||||
|QM<br>Hidtl|1.59<br>3.36|1.93<br>-|1.98<br>-|1.98<br>-|2.22<br>-|1.93<br>-|1.79<br>-|1.69<br>_|1.59<br>_|1.49|1.41<br>_|1.24|1.36|1.24|_<br>2.22|<br>0.9|_<br>1.72|_<br>D.30|
|Rxd~wm<br>It Km~|4.37<br>|<br>4.45|4.47|4.46|<br>4.44|4.42|4.41|4.38|4.29|4.34|4.41|4J.4|4.47|4.2|4.47|0.19|4.41|0.06|
|q<br>hM4,<br>1Idi*|10.05<br>3.68<br>|-<br>3.66|-<br>3.68|-<br>3.60|-<br>3.52|-<br>3.62|-<br>3.78|-<br>3.72|-<br>3.72|-<br>3.73|-<br>3.69|-<br>3.70|-<br>3.71|-<br>3.52|-<br>3.7m|-<br> <br>0.26|-<br>3.6S|-<br> <br>0.07|
|mor<br>1rum|7.82<br>7.36|-<br>11.57|-<br>11.09|-<br>11.09|-<br> <br>9.64|-<br>7.35|-<br>7.48|-<br>7.57|-<br>7.91|-<br> <br>-|-<br>-|-<br>-|-<br>-|-<br>7.36|-<br>11.57|-<br> 4.21|-<br>9.22|-<br>1.83|
|tram|10.45|10.32|10.19|10.10|9.97|9.4|9.83|9.75|-||-|-|*|9.44|10.32|0.88|9.94|0.30|
|jinlm|-1.15|-1.13|-1.02|-092|-109|-115|-109|-106|-113|-138|-157|-174|-191|-191|-092|099|-12|031|
|<br>Jord.|<br>6.33|<br>-|<br>-|.<br>-|.<br>-|.<br>-|.<br>-|.<br>-|.<br>-|.<br>-|.<br>|.<br>|.<br>|.<br>|.<br>|.<br>|.<br>|.|
|LUbys|-|-|-|-|-|-|-|-|-|-|_<br>-|_<br>-|_<br>-|_<br>-|_<br>-|_<br>-|_<br>-|_<br>-|
|30ayl&a|78D|78D|<br>784|786|784|769|771|773|769|766|769|768|-|768|786|018|775|007|
|.|.<br>5.24|.<br> <br>-|<br>.<br>-|.<br>-|.<br>-|.<br>-|.<br>-|.<br>-|.<br>-|.<br>-|.<br>-|.<br>-||.<br>-|.<br>-|.<br>-|.<br>-|.<br>-|
|Npal|<br>6.53<br>21|<br>6.53<br>-|6.32<br>-|6.52<br>-|6.47<br>-|6.49<br>-|6.sD<br>-|6.5D<br>-|6.56<br>-|6.55<br>-|6.56<br>-|6.64<br>-|6.60<br>-|6.47<br>-|6.64<br>-|0.17<br>-|6.54<br>-|0.05<br>-|
|<br>N^l|<br>2.12|-|-|-|-|-|-|-|-|-|-|-|-|-|-|-|-|-|
|N1atLM|079|133|134|129|119|14|115|111|096|090|082|079|06|079|134|055|107|020|
|.<br>Pdkstoi<br>|.<br>_4.85_|.<br>4.85|.<br>4.85|.<br>4.86|.<br>4.D|.<br>4.75|.<br>4.72|.<br>4.78|.<br>4.73|.<br>4.73|.<br>4.66|.<br> <br>4.71|<br>4.72|.<br> <br>4.68|.<br> <br>4.86|.<br>0.18|.<br>4.76<br>|.<br> <br>0.06<br>|
|P<br>~|4.55|_4.77_|4.79|4.76|4.71|4.52|4.48|4.61|4.60|4.64|4.62|4.62|-|4.48|4.79|0.31|4.65|0.10|
|<br> <br>PapaNuub<br>.<br>_M_|<br>2.07|<br>-|<br>-|<br>-|<br>-|<br>-|<br>-|<br>-|<br>-|<br>-|<br>-|<br>3.26|3.26|<br>3.26|<br>3.26|<br>-|<br>3.26|<br>O.O0|
|<br>ParsiaY|8.80|9.13|9.03|892|8.82|8.90|8.91|8.93|8.80|8.81|8.80|8.85|6.67|s.80|9.13|0.33|8.90|0.10|
|Peru|3.08|3.15|3.15|3.13|3.13|3.10|3.04|3.0a|3.08|3.06|3.18|3.12|3.13|3.04|3.16|0.14|3.11|0^.0|
|NUippt<br>|6.23|6.26|6.23|6.23|6.20|6.26|6.22|6.20|6.23|6.2D|6.23|6.29|6.30|6.20|6.30|0.10|6.24|0.03|
|Pumarto i|-<br>902|-<br>969|-<br>943|-<br>936|-<br>930|-<br>916|-<br>902|-<br>886|-<br>866|-<br>838|_<br>42|_<br>847|-<br>853|_<br>3B|_<br>969|_<br>131|_<br>894|_<br>045|
|nminim<br>pi.|.<br>6.3D|.<br>6.3D|.<br>6.31|.<br>6.3D|.<br>6.19|.<br>6.06|.<br>6.04|.<br>6.14|.<br>6.09|.<br>6.17|.<br>6.19|.<br>6.18|.<br>-|.<br>6.04|.<br>6.31|.<br>0.27|.<br>6.18|.<br>0.09|
||L<br>65n|848|839|840|-|846|846|956|955|955|949|941|937|639|956|117|901|055|
|SrilAdi|<br>.<br>4.29|.<br>4.29|.<br>4.32|.<br>4.33|4.16|.<br>3.96|.<br>3.92|.<br>3.98|.<br>3.80|.<br>3.89|.<br>3.95|.<br>3.95|.<br>3.96|.<br>3.80|.<br>4.33|.<br>0.53|.<br>4.04|.<br>0.18|
|Syia|10.01|10.35|10.16|10.28|10.15|9.94|9.99|10.05|10.02|10.02|_9.86_|10.87|<br>-|9.86|W.35|0.49|10.06|<br>0.14|
|nhutlud|7.22|7.34|7.36|7.22|7.09|7.15|7.17|7.16|7.13|7.15|7.12|7.12|7.19|7.09|7.36|0.27|7.18|0.06|
|firMdU.<br>d<br>_u_<br>odbp|5.54|5.54|5.51|5.52|5.32|4.66|4.54|4.63|4.55|4.74|4.54|4.25|4.34|4.25|5.54|1.29|4.85|0.48|
|<br>Tlmit|7.26|7.33|7.27|7.26|7.22|7.09|7.13|7.16|7.16|7.23|7.17|6.93|6J33|6.63|?.33|0.50|7.15|0.14|
|lbiIW<br>U8Y|5.37<br>306|5.39<br>-|5.36|5.39|5.31|5.31|5.30|5.28|5.28|5.28|5.34|5.39|5.44|5.28|5.4|0.16|5.34|0.05|
|--<br>Vmugla|.<br>4.54|<br>4.66|-<br>4.5D|-<br>4.43|-<br>4.04|-<br>2.50|-<br>2.60|-<br>2.63|2.62|-<br>2.95|-<br>2.56|-<br>2.01|-<br>2.0|-<br>2.C0|-<br>4.66|-<br>2.66|-<br>3.12|-<br>0.99|
|YOM|80|846|L76|903|927||||||||||||||
|<br>Y3SSli|.<br>5.6S|.<br>4.90|.<br>4.95|.<br>4.S9|.<br>4.95|9.20<br>4.95|9.29<br>5.20|9.3D<br>4.93|9.30<br>4.95|9.31<br>_4.98_|9.52<br>4.74|9.57<br>4.75|9.66<br>6.56|8.46<br>4.74|9.86<br>6.56|1.40<br>1.82|9.24<br>5.06|0.36<br>0.49|

_am_ b _nm_ to old Wa1d km _srim_ with diffdt bt yam= aig w _aaurm._