Measuring outward orientation in LDCs: Can it be done?

Journal of Development Economics Vol. 49 (1996) 307-335

ELSEVIER

JOURNAL OF Development ECONOMICS

Measuring outward orientation in LDCs: Can it be done? Lant Pritchett World Bank, 1818 H St, NW, Washington DC, 20433, USA

Received 15 July 1991; revised 15 August 1994

Abstract In recent years abundant evidence has been put forth to show that something about a country's trade policy stance improves economic performance. However, less examined is the question of what exactly that trade policy something that matters for performance is. Examination of the link between various empirical indicators used in the literature to measure trade policy stance reveals that, with minor exceptions, they are pairwise uncorrelated. This finding raises obvious questions about the their reliability in capturing some common aspect of trade policy and the interpretation of the empirical evidence on economic performance. JEL classification: F 13; 01 Keywords: Outward orientation; Trade liberalization

1. Introduction

The pressure for trade reform as an integral component of adjustment programs has intensified the ongoing debate about the growth and productivity benefits of liberalization of trade regimes in the less-developed countries (LDCs) (Havrylyshyn, 1990; Tybout, 1992; Rodrik, 1990; Rodrik, 1996). This heightened interest has in turn generated continued empirical study of the relationship between economic performance and trade policy orientation. One branch of this overall policy-performance literature uses cross-country regressions relating eco0304-3878/96/$15.00 © 1996 Elsevier Science B.V. All rights reserved SSDI 0 3 0 4 - 3 8 7 8 ( 9 5 ) 0 0 0 6 4 - X

308

L. Pritchett / Journal of Development Economics 49 (1996) 307-335

nomic performance and some measure of trade policy stance to investigate this relationship, l This paper attempts to move the debate on the empirical cross-country relationship between trade policy and economic performance backward one step by asking the question, can the economist's intuitive notion of policy outward orientation be captured empirically? Different authors have used different measures to serve as proxy for overall trade policy stance (Balassa, 1985; Edwards, 1992; Dollar, 1992) and generally have come to similar conclusions; that outward-oriented countries perform better. If these different empirical proxies for policy stance were strongly correlated, this would create confidence that some significant, well-understood aspect of countries' trade policy is being captured. This paper examines cross-country data for a number of variables that can plausibly claim to be a summary measure of trade policy orientation. The empirical evidence presented below is easily summarized: the alternative objective measures of trade policy examined are completely uncorrelated across countries. 2 This result has serious implications for empirical research that attempts to assess the effects of liberalization on economic performance using comparisons across countries; it also highlights the difficulties of interpretation in these types of empirical studies. This paper is divided into three sections. The first reviews broadly and briefly some principles of the measurement of trade barriers. The second section examines the relationship between four types of empirical measures of policy orientation across countries. These are (a) the share of trade (or imports) in GDP (adjusted for country structural characteristics or factor endowments), (b) the average tariff and coverage ratio of nontariff barriers (NTBs), (c) measures of the deviation of countries' actual trade pattern from the pattern predicted from a model of resource-based comparative advantage and (d) a measure of price distortions. The third section of this paper discusses the interpretation and implications of the lack of association between the various measures and draws conclusions.

2. Measuring trade policy stance in LDCs Baldwin (1989) suggested that there are two types of measures of trade barriers: incidence and outcome. Each of these have their strengths and weaknesses. Incidence-based measures of attempt to measure the trade policies by direct observation of the policy instruments. The level (or dispersion) of tariffs or the

i A large literature connects exports (export performance) and economic growth (Feder, 1983; Jung and Marshall, 1985). However, as these studies relate export outcomes to economic performance and address policy orientation, at best indirectly, they will not be discussed. 2 Several studies have undertaken a subjective assessment of trade policy stance (e.g., World Bank, 1987; Choksi et al., 1989). These subjective measures, although not without interest, will not be treated.

L. Pritchett / Journal of DeL~elopment Economics 49 (1996) 307-335

309

frequency of the various types of nontariff barriers are the two most common. Incidence measures are generally atheoretic. For instance, counting the frequency of NTBs is a (relatively) straightforward empirical exercise. However, measurement problems are created by the fact that the less-developed countries (LDCs) tend to deploy a host of tariff and NTBs to imports. 3 The mere count of NTBs cannot assess the severity of the distortions as, unlike ad vah)rem tariffs, where the barrier itself has a natural price metric, NTBs and foreign exchange rationing are generally not transparent in their operation. 4 This is a severe limitation for cross-country comparisons. Moreover, with a few exceptions LDCs do not have convertible currencies and often resort to implicit rationing of imports through foreign exchange allocations and pursue policies that sustain overvalued exchange rates that discourage exports. Outcome-based measures of trade policy assess the deviation of the actual outcome from what the outcome would have been without the trade barriers. Outcome measures can be either price based (such as effective rates of protection based on price comparisons) or trade flow based. Table 1 summarizes the outcome based measures of trade policy based on whether they examine the let:el of prices or of trade (whether this be imports, exports, or net exports) or distortions in the pattern of trade. How do these conceptual measures of trade policy stance correspond to the usual notions of openness, liberality and the two flavors of outward orientation: liberal and interventionist. 5 I define 'openness' as simply an economy's trade intensity. Openness thus defined is not a policy measure at all as trade intensity varies across countries for reasons having nothing to do with policy, for instance, the 1985 trade intensity ratio of the United States, at 14 percent, was less than half that of the Philippines (31 percent) although no one would propose that the Philippines was either more 'liberal' or 'outward oriented' than the US. A measure of policy openness must adjust for nonpolicy determinants of trade intensity., the magnitude of traded output relative to all output (or on the import openness side, import penetration). 6

3 The literature often refers to LDC trade restrictions as quantitative restrictions (QRs), which in many cases is a misnomer, as LDC import restrictions are rarely imposed on quantities. Much more common is to separate the universe of imports into those goods that are banned, those goods that are freely importable and those goods that require a license. For those goods that require a license, the apprnval process is typically discretionary, not based on preannounced quantity allocations. 4 See Pritchett (1988) or Narasimhan and Pritchen (1993) for attempts to measure at the aggregate level the impact of otherwise unobservable non-tariff and foreign exchange based restrictions. The idea that trade policy stance is in a multidimensional and ambiguous concept is not original and this section has been informed by the literature (Balassa, 1982; Helleiner, 1990; Krishna, 1991). ~' Although in fact trade (a gross measure) is always compared to value-added, not gross output. This creates problems in cross-country comparisons when the ratio of value added in traded activities to trade differs, as with assembly operations.

f(tJ(Y, A ) - 7J(Y, A0)) An aggregation of the deviation of trade flow of An aggregation of the impact on the ith commodity of policy set A in country j versus country j of the ith commodity under policy set A from the level predicted by factors Y. policy set A 0

h( A¢ - A¢o)

Pattern

PJ(X, A ) - PJ(x, A o)

TJ(w j, A j ) - 7'(W j, A~)

An aggregation of the deviation of prices of the ith commodity under policy set A24 from levels predicted by factors Z and policy set A 0.

g( p/(Z, A ) - fiiJ(Z, Ao))

Deviation of total trade flow (T) of country j Deviation of the price level of country j under when policy set is A from level predicted based policy set A from that predicted by factors X on factors W and policy set A 0. under policies AO.

A - A0 Average impact of policies in country j.

Prices

Trade flow

Level

Policy incidence

Table 1 Classification of trade policy indicators

I

i

L. Pritchett / Journal of Development Economics 49 (1996) 307-335

31 I

Trade policy liberality is best described as the set of policies such that the level a n d pattern of trade (and prices) are near what they would have been under free

trade. 7 Liberality is not synonymous with 'outward oriented' in two senses. Countries can be outward oriented while the government plays a large role in determining economic incentives. Two kinds of 'outward orientation' can be distinguished. The first, 'liberal outward orientation' is characterized as the lack of bias against exports and neutrality within imports and exports. Although the government may pursue some policies that raise the price of importables, export policies offset those incentives in such a way that the trade regime creates no bias on average in favor of import substitutes and that the trade regime does not create price distortions between various import and export goods. A second, 'interventionist outward orientation' applies to those countries that have no bias against exports, but in which the government intervenes to alter relative prices within importable and exportable activities. Korea and Taiwan (China) are often used as examples of outward-oriented countries, and yet their trade policies have certainly not been liberal in the sense that, say, Hong Kong has been liberal. 8 Attempting a summary measure of the total impact of these barriers for a single country is a formidable project, and attempting to construct such a measure that would be comparable across countries is even more forbidding. Nevertheless, given the importance of the subject, measures of various kinds have been proposed. In the face of these seemingly insurmountable difficulties, intuition (and hope) suggests that outward-oriented countries will tend to be simultaneously more open and more liberal; the actual relationships among the various components is an empirical question to which we turn.

3. Comparison of alternative outward-orientation measures Empirical research into the effects of outward orientation on economic performance has generally not untangled the various dimensions of trade policy stance. This section examines the relationships between six trade policy stance measures, summarized in Table 1. NTB frequency and the average tariff level are two incidence measures of trade barriers, Two measures, structure-adjusted trade intensity and L e a m e r ' s openness index, are trade flow outcome measures of policy openness. Two other outcome measures are a price distortion measure, based on comparisons of price levels across countries and Learner's trade-distortion index.

7 Although governments can easily be liberal in trade policy without being laissez faire. Industrial, credit, employment, regulatory and social transfer policies can all affect the determination of relative prices and output and hence influence trade even when all these policies are trade 'neutral' in the sense of treating domestic and foreign firms and products similarly. There is a large debate about whether Korea is a 'liberal outward oriented' or "interventionist outward oriented' country (Wade, 1990).

312

L. Pritchett / Journal o f Development Economics 49 (1996) 3 0 7 - 3 3 5

3.1. Description As is clear from Table l, all outcome measures are sensitive to the model used in constructing the counterfactual of what would have happened under an alternative policy, usually assumed to be free trade. Empirically this means picking a set of variables and a functional form to estimate the relationship. Structure adjusted trade intensity (SATI). Intuitively, highly protectionist policies and a large anti-export bias tend to reduce the fraction of economic activity that is internationally traded. This adjustment has been done in two ways: accounting for obvious structural features of the economy (such as size and transport costs) and using some more theoretic model for predicting trade intensity differences (e.g. factor endowments). A straightforward indicator of policy openness is the magnitude of trade flows relative to GDP, corrected for certain structural characteristics of the Chenery and Syrquin (1975) and Chenery and Syrquin (1989) type, such as level of per capita GDP, size (both area and population), transport costs and obvious resource endowment characteristics. 9 This measure, which I call 'structure-adjusted trade intensity' is simply the residuals from a trade intensity regression which indicate the amount by which a country's trade intensity exceeds (or falls short) of that expected for a country with similar characteristics. 10, ~ The residuals from the equation are taken as a measure of policy openness, as they indicate the amount by which a country's openness exceeds or falls short of that expected for a country of its type. Adjusted trade-intensity ratios are computed for total trade (exports plus imports), total imports and various import subcategories to make direct comparisons with the other trade measures discussed below easier. 12

9 These trade intensity (or a subset, import penetration) regressions have been used as an outwardorientation measure by Balassa (1985) and Balassa and Noland (1988). 10 The variables in this paper's measure of adjusted trade intensity were: Trade Intensity = 0;0 + a l * Population + c~2 * In(Area) + 0;3 * C I F / F O B + ol4 * G D P p e r capita + % * ( G D P p e r capita) 2 + 0;6 * Oil d u m m y . (1) All included variables were significant (at the 10 percent level) except for the CIF/FOB ratio and population. The regressions give the usual results - that trade intensity increases at a decreasing rate in GDP per capita (an inverse U), declines with area and increases with population. The goodness of fit for these trade-intensity regressions (R 2 of 0.47 for total trade) is quite good for cross-country regressions of this type (full regression results are presented in the appendix). ~ This procedure is slightly incorrect as ideally the country whose openness is being measured should be excluded from the estimation of the parameters. If a separate regression is estimated excluding each country to calculate its deviation (equivalent to estimating a dummy for each country individually), the simple (rank) correlation is 0.95 (0.99). The only countries for which the ranking is altered are those that are outliers in the independent variables. Canada (area), India (population) and Malawi (CIF/FOB ratio) are the only countries whose openness ranking changes by more than five places. 12 The correlation between trade intensity ((exports plus imports)/GDP) and import penetration is quite high. The simple (rank) correlation before adjustment is 0.90 (0.83); after adjustment the correlations are 0.88 (0.82).

L. Pritchett / Journal of Development Economics 49 (1996) 307-335

313

Leamer's Openness Index (LOPX). A major weakness of structure-adjusted trade intensity is that the regression adjustment is ad hoc and atheoretic. A theoretically more sophisticated openness, or trade intensity, measure has been constructed by Leamer (1988). He creates a measure of openness from the estimation of a modified Heckscher-Ohlin-Vanek (HOV) model of trade flows. Using data from 1982 the model predicts the net exports for each country for each of the 182 three-digit SITC commodity classes as a function of the country's endowment of capital, land, labor, oil, coal and minerals; the distance to its markets; and the trade balance. The openness measure for total trade for a country (and for three subaggregates: manufacturing, agriculture and resources) is computed as the sum of the deviations of the predicted from the actual level of net exports across all commodities (see data appendix). 13 I call this the 'endowmentadjusted trade intensity ratio', or Leamer's openness index (LOPX). The empirical importance of adjusting the simple openness or trade intensity to derive an outward-orientation measure depends on how much the countries' rankings by simple openness differ from the rankings by adjusted openness. Interestingly the (rank) correlation of trade intensity with SATI was 0.53 (n = 94) and for LOPX was 0.65 ( n - - 4 4 ) . The adjustment for structural factors substantially alters the rankings of countries by openness. 14 However, the impact on the openness ranking of countries made by the 'structure' versus the 'endowment' adjustment is quite different as the rank correlation of SATI with LOPX is only 0.04. J5 This weak correlation between two plausible adjustments should be kept in mind as these two measures of policy openness are compared with other policy stance measures. Average tariffs'. Data on the level of tariffs and frequency of NTBs for eighty-nine LDCs for a single year have been collected at the S1TC five-digit commodity level from country sources by UNCTAD (see UNCTAD, 1988; Erzan

~3 Leamer's 'intervention' indices discussed below measure the deviation of the actual from predicted trade pattern, while the openness index measures the deviation of the actual from predicted trade level. 14 Of course, the correlation between y and the residuals of regressing v on x is simply p = ~/1- Ry. To the extent the model of the determination of trade intensity had no explanatory power the correlation would be perfect. This will not hold because the reported correlations are rank not simple and the simple correlations are much higher than the rank correlations. The difference in the simple and rank correlations suggests that the rankings of the most open countries (e.g., Singapore) are not much affected while the rankings for many countries in the middle of the distribution are re-ordered. If the five countries with the highest unadjusted trade-intensity ratios are excluded, the simple correlations between the adjusted and unadjusted ratios falls from 0.73 to 0.45. ~5 The sample for comparison is limited by the number of countries in Learner's paper, although the larger sample is used in computing the trade-intensity regressions. The sample used in the trade-intensity regression does not affect the basic result.

314

L. Pritchett/ Journal of Development Economics 49 (1996) 307-335

et al., 1989). 16 Weighted average total import charges were computed for total imports and three subaggregates - manufacturing, agriculture and resources using world imports as weights (see the data appendix). ~7 The data largely agree with other available sources on tariffs (Kostecki and Tymoski, 1985; Pritchett and Sethi, 1993). Non-tariff barrier frequency (NTBF). While tariffs are often high, the predominant form of import control in LDCs is the discretionary licensing of imports. The coverage ratio of NTBs for each is the import weighted percent of tariff code lines covered by various types of NTBs (licenses, quotas, prohibitions) as a percentage of all tariff code lines within the aggregate. ~8 Overall measures that affect all imports, such as comprehensive foreign exchange licensing and general import licensing, are also recorded. The data appear to be very carefully constructed to capture as best as possible the fraction of goods subject to nontariff import constraints. Price distortion. Another indicator used for 'outward orientation' used the price comparisons undertaken as part of research into international comparisons of real national product (ICP). The ICP project used surveys to measure the prices of a basket of goods in a large number of countries. These detailed price comparisons were then used to construct a purchasing power parity (PPP) exchange rate used to convert local currency values for output (GDP) into internationally comparable levels. The PPP exchange rate divided by the official exchange rate produces an internationally comparable index of price levels. If one assumes that trade restrictions result in a higher price level, all else being equal, then the inverse of the price level, adjusted for the level of G D P per capita, could be used as an outward-orientation index. J9 A number of new empirical studies on growth have found a significant negative correlation between growth and the black market premium. While some have used the black market premium as an indicator of trade policy (Harrison, 1991), others have used the black market premium as an indicator of macroeconomic instability, exchange rate overvaluation, or even economic freedom (Bhalla, 1994). Price outcome measures, which measure directly the difference between domes-

16The data is a rolling cross section, with each country giving the most up-to-date information possible. The actual dates for each country range from 1985 to early 1988. Again, this raises the issue of changes over time in policy stance. J7 The variable is referred to for convenience as tariffs although it includes all import charges, such as duties and customs fees. 18Frequency-type measures of the incidence of nontariff barriers for the industrialized countries (Nogues et al., 1986; Laird and Yeats, 1988) also exist but are not comparable to the LDC data. 19There are analytic difficulties with using this indicator for 'outward orientation' as it is not entirely clear why the 'level' of prices and not relative prices should be affected by trade barriers, see Rodrik (1994).

L. Pritchett / Journal of Det~elopment Economics 49 (1996) 307-335

315

tic and world prices, are generally feasible only for products in which the quality adjustments are not overwhelming. 20 Moreover, even if a set of price distortions could be constructed, they would be extraordinarily difficult to aggregate into an economy-wide summary measure (Anderson and Neary, 1992). Learner's trade distortion indices. The two adjusted openness measures can also be compared with a measure of trade distortion also constructed by Learner from using the HOV model, trade intervention indices. The difficulties of constructing an adequate measure of trade liberality based on the incidence of legal restrictions has led some to measure liberality in terms of actual trade flows. 2~ Learner's (1988) cross-section estimation, the HOV model, provides measures of trade distortion for each country that compare the actual trade pattern to that predicted from the HOV factor endowment model of comparative advantage. Learner uses the deviations of the pattern of trade from the predicted pattern to form an 'intervention' index for total trade as well as for manufacturing, agricultural and resource aggregates (see the data appendix). 22 This intervention index is a trade flow outcome-based measure of trade liberality. As the appropriate normalization of the residuals (because countries with large trade would tend to have large absolute deviations) is not clear, Learner constructed three separate indices of intervention from the residuals of the estimated HOV trade model, each using a different weight for the same residuals. Two measures were calculated from the sum of the absolute value of the residuals, scaling the total either by predicted trade or by GDP. A third measure was the c o u n t r y R 2 (the proportion of the country trade pattern predicted by the model). 2~ Higher levels of the trade intervention indices indicate greater distortions. Table 2 presents on overview of indicators of trade policy stance. One difficulty in evaluating trade policy stance is that no measure has ever been proposed that can compare policies both across countries and over time. Each of the cross-country measures examined here was constructed to compare countries during a different time period. Nonetheless, comparisons remain interesting for two reasons. The measures cover roughly the same period (mid-1980s). Also, in any case, the cross-country measures of trade policy stance at a point in time can be linked

20 Aitken (1992) has used the disaggregated price data from the ICP to construct a measure of relative price dispersion, examining the dispersion of prices within a country as opposed to the levels across countries 21 A body of literature has grown up around the question of whether Japan is or is not more protectionist than other nations. Japan scores relatively low by the incidence measures, but has very low trade intensity. Saxonhouse (1985) argues that for Japan, a low import penetration ratio for manufactures simply indicates a comparative advantage in production of manufactures. Balassa and Noland (1988), on the other hand, find Japan very closed, even after accounting for endowments. 22 This intervention index differs from the adjusted trade intensity in that both positive and negative deviations of actual trade from the prediction increase the intervention indices. ,,3 The sign is reversed so that it is an intervention index.

Fraction of imports subject no NTBs (each category of world trade in that category). Average tariff rates (each import category weighted by fraction of world trade in that category). Deviation of trade share of GDP from its expected value based on structural characteristics. Ranking of deviation of trade volumes from values predicted by implementation of HOV theory. Deviation of price levels from value expected by purchasing power parity (PPP), adjusted for income level. Deviation of trade pattern from values predicted by theory

Policy incidence (level) Policy incidence (level) Outcome (trade flow, level) Outcome (trade flow, level) Outcome (trade flow, level) Outcome (trade flow, distortion)

NTB frequency (NTBF)

Average tariffs (AVGT)

Structure-adjusted trade intensity (SAT1)

Learner's openness index (LOPX)

Price distortion (PRDS)

Learner' s trade-distortion index (LTDI)

Source." See data appendix for complete description of original sources, methods.

Description

Type

Name

Table 2 Indicators of trade policy stance

t_n

4~

z~

g~

2.

L. Pritehett / Journal o f Det,elopment Economics 49 (1996) 3 0 7 - 3 3 5

317

Table 3 Matrix of correlations or partial correlations between the various indicators of trade policy stance in less-developed countries a SATI(+) SATI ( + ) LOPX(+)

LOPX(+)

NTBF(-)

AVGT(-)

PRDS(

r:0.06 (0.76) -

b: 0.041 (0.70) b: - 0 . 1 3 (0.53)

b:

b: 0.006 (0.96) r: 0.051 ((I.82) b: 0.208 (0.11 ) b: -0.221 (0.09)

NTBF (-)

-

AVGT (-)

0.16 (0.22) b: - 0 . 5 3 (0.01) * r: 0.38 (0.001) * -

PRDS ( - ) LTDI ( - )

)

LTDI(-)

b: - 0 . 2 5 (0.16) r: 0.21 (0.08) b: - 0 . 1 4 (I).541 b: 0.05 (0.811 r: (/.06(/I.79)

Variable names: SATI - structure-adjusted trade intensity; L O P X - L e a m e r ' s openness index; N T B F - NTB frequency; A V G T - average tariffs; PRDS price-distortion index; LTDI - Learner's

trade pattern distortion index. Expected signs: a + ( - ) indicates an increase (decrease) in the variable, which represents a more (less) open/liberal/outward-oriented policy. Hence the expected sign of the correlation is positive if two variables have the same sign, negative if the signs differ (e.g., higher tariffs [ A V G T ] and a larger price distortion [ PRDS] indicate less liberality and hence should be positively correlated while higher tarif[\s should be negatively correlated with trade intensity [SAT1]). Statistics reported: The top entry is either b: standardized beta coefficient or r: rank correlation. The number in parentheses is the P-level of the test; the reported statistic is zero.

to

economic

performance

r e l a t i v e l y s t a b l e in a n y c a s e .

3.2. Basic

over 24

time

were

if the

pattern

across

countries

is

results

The overall results are summarized Reported

only

in t h e c o r r e l a t i o n s p r e s e n t e d

in T a b l e 3.

is e i t h e r t h e r a n k c o r r e l a t i o n b e t w e e n t w o v a r i a b l e s or, i f t h e v a r i a b l e s

related by a regression,

the standardized

b e t a . 25 A l s o r e p o r t e d

for each

24 That is, all existing regressions relate trade policy at a point in time (or a period average) to a growth rate over a period of time. To the extent that countries' trade policies were volatile enough that cross-country rankings were affected by slight changes in the time period, this also affected the regression results. 25 The standardized beta scales the regression beta coefficients so that they are comparable across variables, in the sense that it indicates how many standard deviations the dependent variable would shift for a one standard deviation shift in an independent variable.

318

L. Pritchett / Journal of Development Economics 49 (1996) 307-335

statistic is the P-level. 26 A positive (negative) sign signals that the variable indicates a more (less) liberal/open/outward-oriented trade policy. Hence, if the signs are the same, one could expect a positive correlation and conversely, if variables have opposite signs, a negative correlation (e.g., a priori trade distortions should be positively correlated with price distortions, or NTB frequency should be negatively correlated with trade intensity). The results suggest disappointingly low correlations between the various measures. The only two 'right' signed and significant relationships are between Leamer's openness measure and the average level of tariffs and between the level of tariffs and NTBs. For the rest of the variables, the relationships are weak, often perversely signed and statistically insignificant. Adjusted trade intensity is not correlated with any of the other variables, including Learner's openness index, which measures trade intensity using a more sophisticated model to gauge deviations from trade intensity. Neither is higher NTBs, higher tariffs, larger price distortions, nor more distorted trade associated with lower adjusted trade intensity. Similarly, Learner's openness variable is uncorrelated with any other variable, except average tariffs. The two incidence indicators of trade policy, NTBs and tariffs, are correlated with each other, but they are not correlated with the other indicators of policy distortion. Neither is the price-based measure of distortion strongly correlated with the trade flow distortions as measured by Learner). To verify the robustness of these results the next subsections examine the empirical relationships between each of these measures in more depth, along three dimensions. First, the construction of the variables and their intrinsic limitations and sensitivity are examined. Second, many of the trade flow and policy indicator variables can be disaggregated by functional classification (e.g., manufactures versus agriculture) and these disaggregated measures are examined. Finally, as the negative results may be driven by outliers or particular regions, the effect of the sample choice on the results is also examined. These robustness characteristics are examined first, for the relationship of two policy openness measures to each other. Next, the relationship between these two trade-based indicators of policy openness with four others: NTB frequency, average tariffs, price distortion and trade pattern distortion, is examined. 3.3. Results variable by variable NTBs and trade intensity. If nontariff barriers (NTBs) and tariffs reduce the level of imports and if the NTB coverage ratios and statutory tariff levels capture this effect, then NTB coverage and mean tariffs should be empirically important

26 The P-level is the smallest significance level at w h i c h one c a n reject the hypothesis that the reported coefficient is zero.

L. Pritchett / Journal of Deuelopment Economics 49 (1996) 307-335

319

determinants in reducing import penetration ratios. 27, 28 The impact of NTB coverage on import-penetration ratios was estimated for each of four aggregates (total, manufactures, agriculture and resources), controlling for total tariff charges and the structural determinants of trade intensity used in Eq. (1) for the sample of 72 LDCs for which data was available. 29 The results for NTBs are easily summarized: the estimated impact of NTB coverage on trade intensity for each import aggregate was nearly uniformly of the wrong sign (if higher NTB coverage leads to lower import penetration, the sign should be negative), very small ~°and always statistically insignificant. 31 Fig. 1 depicts the relationship between structure-adjusted total import penetration (vertical axis) and the NTB coverage ratio for the full sample. For instance, Jordan's (JOR) import penetration is roughly 40 percentage points higher than that predicted from the regression. If countries with low NTB coverage were more open, a general downward sloping relationship should be evident. Visual inspection confirms the regression results that no clear relationship exists. Learner's openness measure was also regressed on mean tariffs and NTB coverage ratios for the four import aggregates. While the coefficients on NTB coverage are at least of the expected sign, they are small and insignificant for total, manufacturing and resources trade. Only for agriculture is there a hint of a relationship. Endowment-adjusted openness and the NTB coverage ratio are, at best, weakly correlated. Hence, no relationship exists between NTB coverage and openness measures based either on adjusted import penetration ratios or on a more sophisticated trade intensity that adjusts for factor endowments. Tari~ and trade intensity. While NTB coverage is completely unrelated to

27 The tariffs are the legal levels, not amounts actually collected, which tend to be substantially lower. 28 Import penetration ratios are used instead of total trade intensity because information is available only on barriers to and taxes on imports. However, the correlation between overall import penetration and trade intensity in 1985 was 0.89, so that this is not likely to be an empirically crucial difference. Also, 1985 was the latest year that trade data were generally available, while the trade barrier data are more up to date. Again, this is not a major problem as the cross-country correlation over time is quite high. 29 This procedure is nearly identical to constructing an index of openness Ii'om the residuals of the estimated Eq. (1) and taking the correlation with NTBs and tariffs. Using the regression approach allows separate assessment of the impact of tarif and nontariff measures. 30 The ratio of the variables (NTB/penetration) at the medians are as follows: 1.10, 1.37, 9.67 and 7.3 for overall, manufacturing, agriculture and resources. The elasticities for the full sample in levels at the medians therefore are -0.047, 0.041, 0.022 and 0.074, respectively. 3~ As cross-country regressions are notoriously sensitive to the influence of exceptional observations, the robustness of the regression results were verified by dividing the overall sample of countries in many ways and performing the same regression on these different subsets of countries. In regressions which deleted outliers, or extreme observations (Singapore, Hong Kong, India), or those countries with t00 percent NTB coverage, or dividing the sample by income, by NTB coverage and by import penetration, or excluding oil exporters, NTB coverage was never significant.

L. Pritchett / Journal of Deueloprnent Economics 49 (1996) 307-335

320

50

!

1

JOR BHR

40

BLZ i

30

"=i

!

EGY

! i

20 ~

BRA

A!E 10 "I~NG i 0 ~

-10 ~

! l I I

i

JAM $DN MYS

LKA

SEhl

CMR ....

TTO

HVO i PAK IDN S~R ~D IN MWI TU, ZWE

TUN ECU

CAF"1~!( HTI GHA NPL PRY MIC BOL L~'V KOR ARqbIEX

BGD PER MDG

CYP VEN

DZA KEN

COL

I~

PHL

ZAR

I !

TUR

-20 B~]~MNKttV.I" GTI~HL -30

URY

"COG i

-4O

I 0

I 20

4D

eO

80

100

NTB aDvJtagl ratio

Fig. 1. N T B coverage and import penetration.

either openness measure, Table 4 reports the coefficients of mean tariffs (AVGT) on Leamer's openness index (LOPX). Tariff levels have a strong impact on both aggregate import penetration and that of manufactures. The structural import penetration regressions, which also provide some (though much weaker) evidence that the level of tariff charges does have an impact on import penetration levels, especially with overall imports and manufactures (Appendix, Table A.2). Given the usual view that tariff protection is not serious in LDCs relative to NTBs and that legal tariffs are often a poor proxy for actual import charges, the correlation of tariffs with openness is quite surprising.

Table 4

Relationship of average tariffs ( A V G T ) to Leamer's (1988) openness index ( L O P X ) for various trade aggregates in L D C s a Total

Full(n=26)

Outlier restricted (n = 23)

Manufacturing

Agriculture

Resource

Std. b

Sig. lvl,

Std. b

Sig. lvl,

Std. b

Sig, lvl.

Std. b

Sig. lvl.

-0,53 -0.51

0.01 ** 0.02 **

-0.41 -0.47

0.08 * 0.05 *

-0.25 -0.16

021 0.46

-0.28 -0.52

0.20 0.02 **

a The 'outlier restricted' sample eliminates sequentially the largest three residuals from the full sample

regression. * * ( * ) - Significant at the 5 (10) percent level,

L. Pritchett / Journal of Development Economics 49 (1996) 307-335

321

100 i

GUY

gO I B0 70

i

! HKG

60

50

i COG

40 MYS

30

20

JOR

GMB

TGO

EGY

BRA IDN

10

CRI

LKA 0

JAM

PNG

MLT

[

ClV ~

CMR MW.I. eKl...

!

T ~X R

-10

T u ~ O R - - ~ ' ~ LV -C~.. ~ ICBRB O~pL ~

'/E~ AK PHLcHLVEN B PER AR(bIDG NPL URY GTM ~

-20

ZAR ~u.

b,-N

DZA~ ....

"-

$DN

NER

CAFZV~ED'

$LE PRY

GHA TZA

RWA

i

COL

-30

i

IRN -40

....

I

I

80

40

~-~

I

t20

I

I

~eO

-1--

-F

200

I ....

240

I

i

i 280

Pd©l) distortion

F i g . 2.

Structure-adjusted openness and price-distortion index.

Price distortions and trade intensity. Fig. 2 is a graph of structure-adjusted trade intensity and the price-distortion measure. It is difficult to discern any pattern or relation. If the price distortion measure is added to a trade intensity regression the small and statistically insignificant coefficients indicate that this measure is also empirically unrelated to trade intensity.an increase in price distortion is actually estimated to increase openness (Appendix, Table A.3). 32 This weak result is also robust across a variety of sub-samples. Table 5 presents the ten most and least outward oriented of 72 LDCs, as ranked either by openness or by price distortion. In the upper left quadrant are the ten least price-distorted countries. Seven of the ten least price distorted were less open than average and two (Nepal and Colombia) were among the ten least open. Similarly, of the top ten most-open countries when ranked by adjusted trade intensity, four (Congo, Jamaica, Togo and Zambia) were in the bottom third ranked by price distortion. Leamer's openness measure is also roughly unrelated to price distortions. The unexplained deviations of countries' price levels produces

32 From the time series on price distortions a measure of the variability of price distortions was also constructed, which was also included in the regression. The outward-orientation measure used in some regressions in the Dollar (1992) paper is a weighted average of the average price distortion level and price-distortion variability. Interestingly, variability of price distortions actually had some significance in the trade intensity regressions.

322

L. Pritchett/ Journal of Development Economics 49 (1996) 307-335

Table 5 Comparisons of the ten most- and least-outward-oriented countries of 72 LDCs, ranked by structure adjusted trade intensity and price distortion Ranks by

Ranks by

Distortion

Openness

SATI

Distortion

Ten least price distorted Sri Lanka 1 Hong Kong 2 Bangladesh 3 Mexico 4 Nepal 5 Thailand 6 Pakistan 7 Syria 8 Malta 9 Colombia 10

34 2 65 45 60 30 36 55 13 57

Ten most open Guyana Hong Kong Congo Papua New Guinea Jordan Malaysia Togo Jamaica Mali Zambia

1 2 3 4 5 6 7 8 9 l0

38 2 65 28 36 12 51 50 43 69

Ten most price distorted Cameroon 63 Algeria 64 Congo 65 Sierra Leone 66 Zaire 67 Niger 68 Zambia 69 Tanzania 70 Ghana 71 Nigeria 72

19 27 3 68 18 23 10 58 66 40

Ten least open Uganda El Salvador Bangladesh Ghana Haiti Sierra Leone Iran Guatemala Burundi Rwanda

63 64 65 66 67 68 69 70 71 72

55 49 3 71 35 66 25 30 60 59

rankings completely unrelated to openness measured by either adjusted trade-intensity ranking. Trade intervention and trade intensity. When these trade intervention indices to the basic trade-intensity regressions the only results of unambiguous statistical significance are those for the GDP-weighted intervention index, which is perversely signed (greater intervention leads to greater openness). However, the sign and significance of the intervention index depend critically on the particular sample and which of the intervention measures is used. For instance the R 2 intervention measure is consistently of the expected sign, but is never statistically significant. This puzzling relationship between openness and intervention is also true if we compare the openness and intervention measures from Learner's paper. Leamer's policy openness measure (the endowment-adjusted trade intensity) is positively (and significantly) correlated with two of the three intervention indices based on the absolute residuals (both GDP and total trade weighted), implying that countries

L. Pritchett / Journal of Development Economics 49 (1996) 307-335

323

that are more interventionist are also more open. Openness is only weakly negatively correlated with the R 2 measure of intervention, weakly for overall. 33 Trade intensity: Summary. This sub-section has compared the results from comparisons of two policy openness measures based on trade flows with four different liberality measures: NTB coverage, tariffs, price distortions and trade intervention indices. Although the structure and endowment adjustments to trade intensity produced significantly different indices of openness, neither of them was related convincingly to any of the liberality measures, except for the relation between average tariffs and Leamer's openness. Liberali~' measures. If the measures of liberality, or lack of trade distortion, were to agree among themselves on the ranking of countries by outward orientation, this might indicate that trade intensity calculated from trade flows (however adjusted) is not an appropriate proxy for outward orientation. The next paragraphs compare Learner's intervention indices first to NTB coverage and mean tariffs and then to price distortions. Finally, the relation between NTB coverage and tariffs and price distortions is explored. Learner's trade intervention and NTBs. Each of the Leamer intervention measures was regressed against NTB coverage and mean tariffs. One would expect that the higher the NTB coverage or the mean tariff, the higher the trade intervention index. However, the estimates on NTB coverage for aggregate trade is consistently of the wrong sign (higher NTB coverage implies less intervention) for each of the measures and this is actually statistically significant for the GDPweighted measure. The same pattern of generally wrong-signed, but insignificant, results also appears for tariffs. These negative results on the relationship between measured trade intervention with trade flows and incidence of import barriers perhaps could be expected for three reasons. First, only 26 countries have data on both NTBs and the Learner indices. Second, the Leamer index uses trade data from 1982, whereas the NTB and tariff data are from more recent years. Third, Learner's indices are calculated from the prediction of net exports, whereas the trade barrier data cover only imports. Learner trade intervention and price distortion. The comparison of the pricedistortion measure with the Leamer intervention indices reveals similar conclusions. If the price-distortion variable were capturing the effect of interventions that altered the pattern of trade, then one would expect that a higher distortion index would be associated with a higher level of trade intervention, both indicating a lower level of liberality or outward orientation. The simple and rank correlations for the sample of the price-distortion index with each of the intervention measures is of the wrong sign, that is, higher intervention associated with lower price distortion. The rank correlations are slightly better in the overall sample, but they

33 For the LDC sample the critical level for the correlation coefficient to reject at the 5 percent level is the hypothesis that p = 0 is 0.382, which none of the correctly signed correlations achieves.

324

L. Pritchett / Journal of Development Economics 49 (1996) 307-335

Table 6 Developing countries ranked from least to most price distorted with ranks by Learner's intervention indices Sri Lanka Hong Kong Bangladesh Thailand Pakistan Colombia Peru Singapore Malaysia Costa Rica Cyprus Portugal Philippines Fiji

Brazil Turkey Nicaragua Argentina Morocco Dom. Republic El Salvador

Ivory Coast

Price distortion

GDP weight

Trade weight

R2

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

13 21 1 11 7 9 14 22 17 20 18 19 6 2 5 3 8 10 15 4 12 16

3 22 2 15 18 9 5 7 21 19 8 16 6 1 13 17 4 14 11 12 10 20

2 18 5 10 17 20 22 4 7 13 16 19 12 1 14 3 6 21 9 15 11 8

are mostly perverse for LDCs considered separately. Table 6 lists the countries ranked from most - to least - outward oriented, the price determined by distortion measure and it shows the rankings of those countries by the (inverse) of each of the Leamer intervention indices (rank 1 is least and 22 most interventionist). The most obvious anomaly is that, while Hong Kong is ranked second by price distortion, it is consistently low on the ranking by Learner's intervention indices. Even though the lack of internal coherence of Leamer' s intervention indices makes it difficult to assess their reliability (see below), none of the indices is associated in the expected way with either administrative measures of trade barriers (NTBs and tariffs) or price distortions. Price distortions and NTBs and tariffs. The last comparison is price distortions with the tariff and nontariff barriers. If the price-distortion index is capturing the effect of interventions to trade, in particular to imports, and if that effect also is captured by the coverage ratio of nontariff barriers or the height of tariff barriers, then one would expect that NTB coverage and mean tariffs would have a significant positive effect in explaining cross-country variation in price level. Table 7 presents the output from regressions of the price-level distortions on the NTB coverage ratio and on mean tariff charges. In the full-sample regressions,

L. Pritchett / Journal of Development Economics 49 (1996) 307-335

325

Table 7 Impact of nontariff coverage and tariffs on price-leveldistortion index NTB Full W/n 3 outliers W/o 10 outliers W/o S - H = D data W/o African W/Africa dummy W/GDP per capita W/o NTB = 100 * (* *)

Tariffs

Std. b

p lvl.

Std. b

p lvl.

0.208 0.311 0.325 0.096 0.071 - 0.037 -0.009 - 0.045

0.11 I 0.019 * * 0.020 * * 0.609 0.680 0.713 0.934 0.782

- 0.221 -0.265 - 0.301 - 0.133 - 0.193 - 0.122 -0.240 - 0.125

0.092 * 0.045 * * 0.031 * * 0.477 0.265 0.206 0.028 ~ * 0.447

significantat the 5 (10) percent level.

NTBs are almost significantly positively related to price distortion, but tariffs are negatively related. The second and third rows of Table 7 show that the procedure of (arbitrarily) eliminating outliers improves the statistical significance of this finding. Even these mildly encouraging results are rather fragile, however, as reasonable sorts of variations in the sample or the model will change the sign and significance of the NTB variable as well as, fortunately, the tariff variable. Three variations are especially significant because the source of the data on price distortions was Summers' and Heston's ICP project price levels. One variation in the sample eliminates those countries for which the data were graded a ' D ' by Summers and Heston (1988), which were generally those countries for which no benchmark survey had ever been done and the price levels were based on extrapolations. This reduces the estimated impact of NTBs by half and raises the P-level to 0.61, well above statistical significance. Second, adding GDP per capita to the equation reverses the sign and eliminates the significance of the NTB variable (although tariffs are still perverse and significant). Third, either adding an African dummy variable or eliminating the African countries completely changes the results of NTBs. The sample sensitivity of the results indicates that the relationship between price-level distortion and NTBs depends critically on the price-level information for Africa (which tends to have the lowest GDP and highest NTBs), which is the most unreliable. In any case, the promising results for NTBs are tempered by the uniformly perverse results for tariffs.

4. Interpretation, caveats and implications The empirical results of this paper show that a number of promising candidates for a summary measure of outward orientation in LDCs (adjusted trade intensity, NTB coverage, tariff levels, price distortions and trade pattern distortion) are

326

L. Pritchett / Journal of Development Economics 49 (1996) 307-335

nearly completely unrelated in a cross-country data set. The two questions that need to be asked are: " w h y is this so?" and "what are the implications for future research?". The interpretation of the validity of any one of the particular measures of outward orientation is complicated by the fact that they are individually and collectively uncorrelated. The only thing that can be asserted with any confidence is that all of the measures are n o t successfully measuring some country-specific, time-persistent aspect of policy. If it had been the case that several of the indicators were strongly correlated and one had disagreed with the rest, then this partial consensus would have strengthened the claims of those that agreed and indicted the loner. Unfortunately, even this partial agreement was not found. Each outward-orientation measure must stand on its own merits, with the distinct possibility that none of them deserves even moderate confidence. The next paragraphs review the claims for each of the measures. Leamer's intervention indices probably have the least intrinsic plausibility for three reasons. The first drawback is the inherent incredibility of the model used in creating the predicted pattern of trade. Although for empirically predicting trade composition from an economic theory the HOV model is the best game in town, the assumptions that need to be imposed to estimate trade patterns as a linear function of a few crudely measured endowments strain credibility. 34 Second, although each of the intervention indices are based on exactly the same notion of intervention, that is, the deviation of the pattern of net exports from the model's prediction, seemingly minor details of the construction of the summary measures (such as whether the squared residuals or absolute values are used) actually make a huge difference in the country ordering (compare the rankings in Table 6). 35 Finally, the country ranking by intervention (scaled either by GDP or predicted trade) are intuitively unappealing. For instance, the GDP-scaled intervention rate indicates that in 1982 Singapore and Hong Kong were the m o s t interventionist countries, and Bangladesh and Turkey the least. Using price-level distortions as a measure of outward orientation raises two questions: first, how valid is the price-level data and second, how valid is their interpretation as an (inverse) outward-orientation measure? Summers and Heston (1988) present the results of Phase IV of the ICP project and review the continuing limitations of the data. The most important limitation for the comparisons among LDCs is that, to date, very few of the African countries have had the benchmark survey of price collection that is the basis of the ICP project. Price levels for the nonbenchmark countries are simply extrapolated from the data of the benchmark countries. Summers and

34 This basically agrees with Leamer's conclusion: "It seems highly unlikely that these large residuals should be attributed completely to trade barriers" (Leamer, 1988, p. 189). 35 Wolf (1993) has attacked the problem of the Leamer measures producing distortions by predicting trade flows at a more aggregated level. This may reduce the sensitivity induced by predicting imports at the three digit SITC level.

L. Pritchett / Journal of Development Economics 49 (1996) 307-335

327

Heston grade the data reliability from A (most reliable) to D (unreliable), and all but seven of the African countries are graded D. Even if we accept the price-level data, are the country deviations from that level (adjusted for income level) an adequate indicator of outward orientation? It is a fundamental measure of the overvaluation of the currency relative to its PPP level. Although generally the support of an overvalued currency entails import controls, overvaluation can be caused by factors (such as foreign aid availability) other than import controls. 36 The price-distortion measure also produces some counterintuitive outwardorientation rankings. The top five least price distorted countries over the 1973-85 period by this measure are Sri Lanka, Hong Kong, Bangladesh, Mexico and Nepal. Among the non-African LDCs, South Korea is in the bottom third in outward orientation, ranked 33rd of 44. The incidence-frequency measures of nontariff barriers are solid in one sense: they depend directly on legal and administrative facts. However, NTB coverage may not be an adequate indicator of openness across countries for several reasons. First, the NTB coverage ratios must group very different types of nontariff barriers (quotas, licenses, health regulations, and so forth) that may have very different effects on imports. Second, even for a single type of import barrier, a coverage ratio cannot capture the variations in how import policy is implemented across countries. The requirement of a discretionary import license can result in distortions of differing severity. These differences will be impossible to capture with incidence data. 37 Structure-adjusted openness has two major weaknesses as an outward-orientation measure. First, the overall flow of trade relative to domestic activity says nothing about the distortion of trade. For instance, a country could have both barriers to imports that protect the domestic production of goods in which the country has no natural comparative advantage with subsidies for export production of goods for which the country also has no comparative advantage. This country could be simultaneously more open but more distorted than another country with completely liberal trade policies. The second problem is the atheoretic nature of the adjustment of actual openness. While the structural characteristics of size and GDP per capita are empirically important in determining trade flows, these account for less than half of the total variation in openness across countries. It is difficult to believe that the unexplained variation is due entirely, or even primarily, to trade barriers. Finally, this measure throws up its own conundrums. Of 72

36 See Van Wijnbergen (1985) for empirical evidence from Africa. 37 Even if the barrier data could be augmented by administrative information (such as the percentage of license applications granted), this would likely be of little help in cross-country comparisons as the administrative procedures produce different incentives. For instance, some import licensing mechanisms encourage redundant applications much more than others.

328

L. Pritchett / Journal of Development Economics 49 (1996) 307-335

LDCs, the top six most open countries in 1985 were Singapore, Jordan, Benin, Belize, Guyana and Brazil. Hong Kong was the 32nd most open, Korea the 57th and Chile the 65th. The strength of Leamer's adjusted trade-intensity ratio is that it is derived from an empirical application of a theory which predicts the pattern of trade. The weakness is that the measure of openness inherits the defects of the theory as well as the inherent limitations in measuring the endowment of factors (such as skilled labor) that determine the trade pattern. The two major empirical concerns are that the structure-adjusted and endowment-adjusted trade-intensity ratios are less highly correlated with each other than either is with the unadjusted trade ratio, implying that the adjustments move the openness rankings in opposite directions. However, the rankings of the LDCs by openness are quite intuitively satisfying, with Singapore, Hong Kong and Malaysia as the most open countries and Peru, Cameroon and Argentina as the least open. Unfortunately I cannot conclude the interpretation of the empirical results with a glowing recommendation for any particular potential measure of outward orientation. Nor, given the lack of an adequate standard, can any of the candidates be rejected outright. The complete absence of correlation among them is skeptically interpreted as an indictment of each. However, that one (but again, only one) of the measures captures outward orientation cannot be rejected. This paper has no direct implications for overall conclusions on outward orientation and performance. Even if one accepted the validity of the various outward-orientation measures, the evidence from cross-country performance regressions is the least persuasive element of the case for the positive effect on performance outward orientation. The reviews of multicountry studies, such as Little et al. (1970), Krueger (1978) and Balassa (1982) are much more convincing. Morever, the reported regression results in studies using these measures are of course not called into question, only their interpretation. The fact that these various trade policy indicators are uncorrelated suggests that different dimensions of trade policy may have different effects on growth. Outward orientation is not a simple, undifferentiated concept and different elements (e.g., trade liberality, low anti-export bias) may have empirically identifiable impacts that can be pinpointed in the growth literature. Harrison (1991), for instance, examines the growth effect of a number of separate indicators of policy stance and finds an empirically identifiable effect of many of them, but even this does not distinguish which element of trade policy each may be capturing. The growth literature to date has shown there is something about trade policy that has an important effect on growth. Was that something maintaining a liberal trade policy? Was that something picking and promoting specific export industries (and doing it successfully)? Was that something achieving outward orientation and a balance between export incentives and import incentives with no special discrimination amongst imports and exports? Was that something maintaining a reasonable stable external environment and avoiding massive overvaluation

L. Pritchett / Journal of Development Economics 49 (1996) 307-335

329

episodes and payments crises? If all these policies went together this wouldn't matter - but empirically, as best it has been measured they don't. There are two principal implications of the empirical results in this paper. First, no reliable, robust estimate of the impact of outward policy orientation on economic performance (i.e., economic growth or export performance) is likely to be possible from cross-country data. For instance, the regressions in Edwards (1992) rely on L e a m e r ' s intervention measure in a regression explaining crosscountry growth. Using a measure equally valid a priori, such as Learner's openness (adjusted trade intensity), import penetration ratios, or some combination of tariff and nontariff barriers data, would have almost certainly produced different results. 38 This is not to say that particular variables, such as the price-distortion variable, w o n ' t perform well (i.e., have a high t-statistic) in explaining cross-country variation in economic performance. 39 However, inferring that that type of empirical result is due to effects of outward-oriented policy stance requires additional evidence establishing a link between the measure and policy. The conclusion of this paper, that alternative objective summary measures of policy outward orientation produce entirely different country rankings, is probably not an astounding revelation. Those who have worked on trade policy in LDCs know that trade regulations and barriers are generally complex legally and even more opaque in their actual administration. The hope that a reasonably straightforward (although not therefore cheap or easy, as the NTB, price distortion and Learner's measures are each the result of a massive empirical effort) measure can produce a 'correct' ranking of countries has always been treated skeptically, and, disappointingly, rightly so.

Acknowledgements I would like to thank the referee, Susan Collins, Jaime de Melo, Sebastian Edwards, Ann Harrison, Edward Leamer, Dani Rodrik and W e n d y Takacs for helpful comments. Judy Baker provided superb research assistance. The opinions and views expressed are those of the author alone and are not to be attributed to the World Bank or its member governments.

38 As noted above, the openness and intervention ratios are negatively correlated. Even more striking, the correlation between the intervention measures (measures of fit of the model to a country's trade) is surprisingly low, the correlation between the intervention (the sum of the absolute values of the residuals) scaled by GDP and scaled by predicted trade only 0.16 and between GDP scaled intervention and R 2 (which squares the residuals) -0.02 (it should be negative as a lower R2 implies a worse fit whereas a higher intervention is a worse fit) but here it is essentially zero. 39 It should be pointed out that Dollar's growth regressions do not use the price distortion variable directly. Rather, he combines the price distortion variable with a variability of the price distortion to derive what is used in growth regressions (Dollar, 1992).

330

L. Pritchett / Journal of Development Economics 49 (1996) 307-335

Appendix A A.1. Data

The data appendix describes the source and methods for the data used in the paper. The actual data are available from the author on request. A. 1.1. Tariffs and nontariff barriers

The information for each country on the tariffs and nontariff barriers to trade was taken from country pages in UNCTAD (1988). For each country the tradeweighted averages of total charges and frequency of nontariff measures for food (SITC 0 + 1 + 22 + 4), agricultural raw materials (SITC 2 less 22, 27, 28), crude fertilizers (SITC 27 + 28), mineral fuels (SITC 3), nonferrous metals (SITC 68) and manufactures (SITC 5 through 8 less 68) were entered. Weighted averages for Agriculture and Resources categories were formed from the subaggregates reported using the 1985 world trade weights. A.1.2. Leamer's measures o f openness

Measures of openness and trade intervention for each of the four aggregates: overall, manufactures (SITC 51 to 96, less 63, 64, 68, 94), agriculture (SITC 1-26, 29, 41-43) and resources (SITC 27, 28, 32 to 35 and 68) were taken from Leamer (1988). The estimates used were from the model estimated after scaling by GDP, which tends to fit the smaller LDC countries better. 40 The openness measure is from table 6.8: Openness measures: adjusted trade intensity ratios, regression model; table 6.10: Country R 2, regression model; table 6.11: Intervention rates, regression model, scaled by GNP; table 6.12: Intervention rates, regression model, scaled by predicted trade. The formulas for the various measures for the ith country are: Eij is the residual (actual minus predicted) of the net exports of the jth commodity for the ith country. Adjusted trade intensity is E j E i J G D P i. GDP weighted intervention is ~ j I E i j I / G D P i, predicted trade S, jIEijI/N~*, where N is predicted trade. The R 2 for each country is ~ , j E i / G D P i / E j ( T i j - Ti , where T/j is actual trade. A.1.3. Import penetration ratios

Trade intensity and import penetration ratios were calculated using data on imports in U.S. dollars for 1982 and 1985 (the latest year with generally available data) from the UNSO trade data base, accessed using the World Bank's TARS system. The aggregates were overall, manufacturing (SITC 5 to 8 less 68), agriculture (SITC 0 + 1 + 2 + 4, less 27, 28) and resources (SITC 27 + 28 + 3 + 68). The ratios of trade to GDP were calculated using dollar GDP data from the

40 As Leamer(1988, p. 186) says, "It is best to think of... the scaled model as describing the smaller countries".

331

L. Pritchett / Journal of Development Economics 49 (1996) 307-335

National accounts (NA) data base maintained by the World Bank, accessed through BESD. A. 1.4. Price-distortion index Summers and Heston (1988) reported on data from the International Comparisons Project (ICP). The ICP has collected detailed price observations from a large number of countries to construct price levels in a common currency. A measure of price distortion was built in Dollar (1992) from this data, estimating the price level as a function of GDP per capita and regional dummy variables and using deviations from this norm as a distortion index. A.1.5. Other variables The data on land area and population were taken from the World Bank's Social Indicators data base through BESD. The data on the C I F / F O B margin were taken from the I M F ' s IFS. GDP per capita in 1985 was taken from Summers and Heston (1988), along with the grade for the data. Oil exporters are those with greater than 30 percent of oil exports, taken from the World Bank (1987). A.2. Regression results using trade intensity and import

Table A. 1 Regression for total trade intensity (imports plus exports) to calculate 'structure adjusted trade intensity' Dependent value Total Independent variables Constant 84.8 (1.97) Population - 0.017 (0.481) Area -9.66 (6.07) GDP per 0.58 capita (2.30) (GDPPC) 2 - 0.0013 (2.06) CIF/FOB 5.02 (0.141) Oil exporter - 17.4 (1.05) Industrial mar- 1.14 ket economy (0.127) N R2

94 0.469

Manufactures

Agriculture

Resources

57.61 (2.53) 0.0038 (0.204) -6.102 (7.22) 0.45 (3.36) - 0.0016 (3.26) - 7.40 (0.392) -7.96 (0.906) -8.27 (0.906)

13.9 (1.29) - 0.015 (1.70) - 1.60 (4.00) - 0.119 (1.87) 0.00027 (1.21 ) 8.077 (0.903) 1.49 (1.55) -3.23 (1.43)

9.82 (6.508) - 0.005 (0.339) - 1.71 (2.39) 0.237 (2.08) - 0.00053 (1.29) 5.44 (0.339) - 15.6 (2.09) 1.12 (2.75)

94 0.590

94 0.340

94 0.34 l

332

L. Pritchett / Journal of Development Economics 49 (1996) 307-335

Table A.2 Regression for import penetration ( i m p o r t s / G D P ) including NTB coverage and average tariffs, LDCs only Dependent value Constant Population Area G D P per capita (GDPPC) 2 CIF/FOB Oil exporter NTB coverage Average tariff N R2

Total - 0.844 (0.024) 0.031 (0.920) - 7.31 (4.81 ) 0.412 (1.85) - 0.0023 (2.17) 15.63 (6.518) - 4.98 (0.732) 0.030 (0.385) - 1.93 (1.22) 72 0.533

Manufactures - 6.43 (0.332) 0.022 (0.619) - 3.70 (4.27) 0.203 (1.63) - 0.00t 1 (1.75) 16.12 (0.938) - 2.04 (0.530) 0.017 (0.413) -0.102 (1.21) 72 0.439

Agriculture 4.14 (0.748) 0.0013 (0.262) - 1.03 (4.42) - 0.0007 (0.018) - 0.00011 (0.631) - 0.702 (0.880) - 0.248 (0.220) 0.0029 (0.229) -0.021 (0.907) 72 0.395

Resources - 1.22 (0.077) 0.015 (1.10) - 2.47 (3.47) 0.197 (1.74) - 0.0011 (2.17) 2.62 (0.186) - 2.42 (0.757) - 0.0068 (0.817) -0.057 (0.792) 72 0.397

L. Pritchett / Journal of Development Economics 49 (1996) 307-335

333

Table A.3 R e g r e s s i o n for trade intensity including the price 'distortion' and ' variability' measures

Constant Population Area G D P per capita (GDPPC) 2 CIF/FOB

All L D C s 41.5 8 (1.09) - 0.017 (0.515) - 6.80 (2.63) 0.12 (1.98) - 0.0001 (1.03) 3.85

(0.122) Oil Exporter Price distbn. Variability

N R2

- 12.49 (1.56) 0.003 (0.050) - 50.9 (1.71) 72 0.316

Non-oil L D C s only 49.92 (1.13) - 0.026 (0.783) 5.44 (2.12) 0.054 (0.694) 0.0001 (0.919) 3.39 (0.124)

- 0.041 (0.519) - 36.05 (1.19) 59 0.440

References Aitken, Brian, 1992, Measuring trade policy intervention: A cross-country index of relative price dispersion, Policy research working paper no. 838 (World Bank, Washington, DC). Anderson, J.E. and J.P. Neary, 1992, Trade reform with quotas, partial rent retention and tariffs, Econometrica 60, 57-76. Balassa, Bela, 1982, Development strategies and economic performance, In: Development strategies in semi-industrialized economies (Oxford University Press, London). Balassa, Bela, 1985, Exports, policy choices and economic growth in developing countries alter the 1973 oil shock, Journal of Development Economics, May/June, 23 35. Balassa, B. and M. Noland, 1988, Japan in the world economy (Institute for International Economics, Washington, DC). Baldwin, R., 1989, Measuring nontariff trade policies, Working paper no. 2978 (NBER, Cambridge, MA) May, 34-39. Bhalla, Surjit S., 1994, Freedom and economic growth; a virtuous cycle'? International Monetary Fund Seminar series no. 1994-33, 1-73. Chenery, H. and M. Syrquin, 1975, Patterns of development (Oxford University Press, London). Chenery, H. and M. Syrquin, 1989, Three decades of industrialization, World Bank Economic Review 3, no. 2, May.

334

L. Pritchett /Journal of Development Economics 49 (1996) 307-335

Choksi, Armeane, M. Michaely and D. Papageorgiou, eds., 1989, Liberalizing foreign trade (Oxford University Press, London). Dollar, David, 1992, Outward-oriented developing economies really do grow more rapidly: Evidence from 95 LDCs, 1976-85, Economic Development and Cultural Change 40, April, 523-544. Edwards, Sebastian, 1992, Trade orientation, distortions and growth in developing countries, Journal of Development Economics 39, 31-57. Erzan, R. et al., 1989, The structure of protection in the developing countries, UNCTAD Review 1, no. 1. Feder, Gershon, 1983, On exports and economic growth. Journal of Development Economics 12, 59-73. Harrison, Ann, 1991, Openness and growth: A time series cross section analysis for developing countries, Policy research working paper 809 (World Bank, Washington, DC). Havrylyshyn, Oleh, 1990, Trade policy and productivity gains in developing countries: A survey of the literature, World Bank Research Observer 5, no. 1, 1-24. Helleiner, G.K., 1990, Trade strategy in medium-term adjustment, World Development 18, no. 6, 879-897. Jung, Woo S. and Peyton Marshall, 1985, Exports, growth, and causality in developing countries. Journal of Development Economics 18, 1- 12. Kostecki, M.M. and M.J. Tymoski, 1985, Customs duties versus other import charges in the developing countries, Journal of World Trade Law 19, no. 13. Krishna, Kala, 1991, Openness: A conceptual approach, Mimeo. Krneger, Anne O., 1978, Foreign trade regimes (Ballinger for NBER, Cambridge, MA). Laird, Samuel and A. Yeats, 1988, Non-tariff barriers of developed countries: 1966-86, Finance and Development 26, March, 12-13. Leamer, Edward, 1988, Measures of openness, lin: Robert Baldwin, ed., Trade policy issues and empirical analysis (University of Chicago Press, Chicago, IL) 147-200. Little, Ian Malcolm David, Tibor Scitovski and Maurice FitzGerald Scott, 1970, Industry and trade and some developing countries: a comparative study. Development Centre for Economic Co-operation and Development (Oxford University Press, Oxford). Narasimhan, Bhanu and Lant Pritchett, 1993, The evolution of import restrictiveness in Sub-Saharan Africa in the 1980s, Mimeo. Nogues, Julio, Andrezj Olechowski and Alan Winters, 1986, The extent of nontariff barriers to industrial countries' imports, World Bank Economic Review 1, 181-199. Pritchett, Lant, 1988, Imports and Foreign exchange constraints: estimates of import demand in developing countries. Essays in Empirical International Trade, Chapter 2 (Ph.D. dissertation, MIT). Pritchett, Lant and Geeta Sethi, 1993, Tariff rates: What do we know? Why do we care?, Mimeo. Rodrik, Dani, 1990, How should structural adjustment programs be designed? World Development 18, 933-947. Rodrik, Dani, 1994, King Kong meets Godzilla: The World Bank and the East Asian Miracle. Centre For Economic Policy Research, Discussion Paper series 944, 1-51. Rodrik, Dani, 1996, Trade and industrial policy reform in developing countries: A review of recent theory and evidence, In: J. Behrman and T.N. Srinivasan, eds., Handbook of development economics and trade (North-Holland, Amsterdam). Saxonhouse, G., 1985, What's wrong with the Japanese trade structure? Pacific economic papers, no. 137 (Australia-Japan Research Center). Summers, R. and A. Heston, 1988, A new set of international comparisons of real product and price levels estimates for 130 countries, 1950-85, Review of Income and Wealth 34, 1-25. Tybout, 1992, Linking trade and productivity: New research directions, World Bank Economic Review (International) 6, May, 189-211. UNCTAD, 1988, Handbook of trade control measures of developing countries supplement: A statistical

L. Pritchett / Journal of Det:elopment Economics 49 (1996) 307 335

335

analysis of trade control measures of developing countries, 1987, UNCTAD/DDM/Misc. 2 GE.89-55071 (UNCTAD, Geneva). Van Wijnbergen, S., 1985, Aid, export promotion and the real exchange rate: An African dilemma'?, CPD discussion paper no. 1985-54 (World Bank, Washington, DC). Wade, Robert, 1990, Governing the market: Economic theory and the role of government in East Asian industrialization (Princeton University Press, Princeton, NJ). Wolf, Holger, 1993, Trade orientation: Measurement and consequences, Mimeo. World Bank, 1987, World Bank Development Report (Oxfurd University Press, London)