metadata: authors: 0: author: Harrison,Myra Ann
count: World
docna: 0: docna: Openness and growth : a time series,
            cross-country analysis for developing countries
docty: Policy Research Working Paper
subtopic: Economic Theory & Research,Industrial Economics,Trade Policy,Educational Sciences,International Trade and Trade Rules,Rules of Origin,Economic Growth,Trade and Multilateral Issues
teratopic: Environment,Macroeconomics and Economic Growth,International Economics and Trade,Poverty Reduction
abstracts: cdata!: This paper compares the association
            between many popular proxies for openness and the rate of
            GDP growth, as well as the results from cross-section and
            panel estimation, controlling for country effects. The
            results suggest that using period averages versus annual
            data critically affects the strength of the association
            between openness and growth. The paper reviews the empirical
            literature on openness and technological change. It
            discusses the dataset for this paper and the empirical
            specification, while also presenting the main results. The
            sensitivity of the results to the inclusion of both
            macroeconomic variables and country size are also tested. It
            concludes with an agenda for future research.
repnme: repnme: Openness and growth : a time series,
            cross-country analysis for developing countries
display_title: Openness and growth : a time series,
            cross-country analysis for developing countries
listing_relative_url: /research/1991/11/699829/openness-growth-time-series-cross-country-analysis-developing-countries
topicv3: Economic Growth m1326241 471,Trade m1326924 698,Education m1327048 470,Trade Policy and Integration m1327407 775,Trade Policy m1327640 776
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: Environment,Macroeconomics and Economic Growth,International Economics and Trade,Poverty Reduction
origu: Off of Sr VP Dev Econ/Chief Econ (DECVP)
no_of_pages: 39
author_keys: 0: author_key: 2048185
model_extractions: **4.**

<!-- Start of picture text --> Policy Research<br>World Development Report<br><!-- End of picture text --> WPS 809 This paper, a background paper for the _1991 World Development Report,_ is a product of the **Office** of the Vice President, Development [:conomics. Copies are available free from the World Bank, 1818 H Street NW, Washington DC 20433. Please contact the World Development Report office, room P4-001, extension 31393 (34 pages). November 1991.

Harrison draws together a variety of measures of openness to test the association between growth and openness.

Although the correlation across measures is sometimes weak, there is generally a positive association between all these measures and GDP growth. The strength of the association generally depends on whether analysts use cross-section or panel data.

For industrializing countries, trade policies have varied too much over time to make the long-ran averages used in cross-section estimates very meaningful.

in the many specifications Harrison explores, she always finds that _greater_ openness is associated with higher growth. Tests of the sensitivity of these results to country size do not change the results.

Harrison highlights two issues interesting for future research: Does openness cause growth? Or is it **ihe** other w - v around?

And is it possible to disentangle short-run from long-run effects without throwing away annual data?

In many respects, the results are surprisingly robust. When openness _is_ statistically significant ThePolicy Research Working PaperScries disseminates the findings of work under way in theBank. Anobjectiveof the series **is** to get these findings ouL quickly, cven if presentations are less than fully polished. The findings, interpretations, and conclusions in these papers do not ncccssarily rcprcscnt official Bank policy.

Produced by the Policy Research Dissemination Center
# Openness and Growth: A Time-Series, Cross-Country Analysis for Developing Countries

# by Ann Harrison*

# Table of Contents

|I.|An Overview of the Literature on Openness and Economic<br>Growth|3|
|---|---|---|
|I I.|Data and Correlations Between Openness Variables|10|
|III.|Basic Results|14|
|IV.|Sensitivity Tests: Country Size and Macroeconomic<br>Policy|18|
|V.|Conclusion and Directions for Further Research|ao|
|Bibli|ography|23|
|Table|s|26|
|Figur|e|34|

* I would like to thank members of the _World Development Report 1991,_ Lant Pritchett, and Bill Easterly for many useful discussions.
The new interest in the determinants of economic development has reignited the debate on openness and growth. In neoclassical growth models developed by Solow (1956) and others, technological change is exogenous--unaffected by a country's openness to world trade. Yet the "new" growth theories suggest that trade policy affects long run growth through its impact on technological change. 1 In these models, openness to trade provides access to imported inputs, which embody new technology; increases the effective size of the market facing producers, which raises the returns to innovation; and affects a country's specialization in research-intensive production.

New growth theories, however, do not predict that trade will unambiguously raise economic growth. Increased competition ( as Schumpeter argued) could discourage innovation by lowering expected profits. Grossman and Helpman (forthcoming) point out that intervention in trade could raise long run growth if protection encourages investment in research-intensive sectors for countries with an international advantage in these kinds of goods. Since the theoretical literature does not provide a clear answer, empirical efforts are needed to resolve the debate on the relationship between openness and growth.

Despite the already voluminous empirical efforts in this area (see Table 1), it is easy to be skeptical of past results for a number of reasons. First, different studies have used a 1 See, for example, Grossman and Helpman (forthcoming) or Romer (1991).

1
dizzving array of "openness" measures, methodologies, and sample countries, leading to results which may differ for any number of reasons. Most research has examined the relationship between economic growth and trade volumes, not policies--this is partly because measuring "policy" poses difficult questions. Second, it is sometimes difficult to know how to interpret the observed correlation between trade policies and growth (see Levine and Renelt (1990)). Policies that are not directly concerned with trade (macroeconomic policy) may have caused both superior export performance and high GDP growth.

Third, most of the literature (including the more recent efforts by Barro (1991) and others) uses cross-sectional averages or starting values for time-series data. Barro (1991), for example, examines the impact of price distortions in 1960 on post-1960 GDP growth. Applying such an approach to developing countries has two shortcomings. First, the use of cross-section data makes it impossible to control for unobserved countryspecific differences, possibly biasing the results. Second, long run averages or initi values for trade policy variables-particularly in developing countries--ignore the important changes which have occurred over time for the same country.

One exception to this approach is Bhalla and Lau (1991), which uses a panel of time series data for sixty countries to find a strong positive association between openness (proxied by the relative price of traded goods) and growth. Bhalla and Lau, however, do not control for country-specific effects, nor do they 2
examine the association between openness and growth using other measures.

T'-is paper synthesizes previous approaches by comparing the association between many popular proxies for openness and the rate of GDP growth. We also compare the results from crosssection and panel estimation, controlling for country effects. The results suggest that using period averages versus annual data critically affects the strength of the association between openness and growth.

Section I reviews the empirical literature on openness and technological change. Section II discusses the dataset for this paper and the empirical specification, while Section III presents the main results. We test for the sensitivity of the results to the inclusion of both macroeconomic variables and country size in Section IV. Section V concludes and presents an agenda for future research.

I. An overview of the literature on openness and economic growth The concept of openness, applied to trade policy, should be synonymous with the idea of neutrality. Neutrality means that incentives are neutral between saving a unit of foreign exchange through import substitution and earning a unit of foreign exchange through exports. Clearly, a highly export oriented economy may not be neutral in this sense, particularly if it shifts incentives in favor of export production through 3
instruments such as export subsidies. It is also possible for a regime to be neutral on average, and yet intervene in specific sectors. A good measure of trade policy would capture differences between neutral, inward oriented, and export-promoting regimes.

Price comparisons between goods sold in domestic and international markets could provide an ideal measure of the impact of trade policy, particularly in the absense of domestic policy distortions. Direct price comparisons would incorporate the impact of the various policies that affect domestic prices: tariffs, quotas, different exchange rates for imports and exports, and subsidies. Since information on relative prices is often not available, however, many other proxies are often used instead.

The simplest measures of trade orientation are based on actual trade flows, such as imports plus exports as a sYtre of GDP or the growth rates of imports and exports. Most of these measures 'see Section I in Table 1) show a positive association with GDP growth, even after controlling for other factors such as capital or labor. One problem with this approach, however, is that trade flows are at best an imperfect proxy for trade policy. Other factors, such as country size or foreign capital inflows, also affect trade: for example, large countries tend to have smaller trade shares. One improvement over this approach is to use the deviation of actual from predicted trade flows (as in Syrquin and Chenery (1989)), based on variables such as country size. Using this adjusted measure, Syrquin and Chenery (1989) do 4
find a positive association<sup>betwean openness and productivity</sup> growth, but the increase in productivity<sup>associated with more</sup> open economies is not very significant.

A more ambitious attempt to<sup>use adjusted trade shares as a</sup> proxy for trade policy openness<sup>was attempted by Leamer (1988).</sup> Leamer uses a theoretical<sup>model to predict the pattern and volume</sup> of trade in the absense of protection.<sup>He then measures</sup> "openness" as a function of<sup>the extent to which actual trade</sup> deviates from the pattern of trade<sup>rcedicted by the model.</sup> Edwards (1989) has used Leamer's measure to show a positive<sup>and</sup> statistically significant impact<sup>of openness on growth. Although</sup> this approach is quite promising--particularly<sup>since it relies on</sup> easily available data--the methodology<sup>in its current form has a</sup> number of shortcomings. In particular,<sup>Pritchett (1991) showed</sup> that Leamer's measure is negatively<sup>correlated with several other</sup> measures of openness, including<sup>import penetration, tariff</sup> levels, and the extent of non-tariff<sup>barriers. Leamer (1988)</sup> concludes that "in the absence<sup>of direct measures of barriers, it</sup> will be impossible to determine<sup>the degree of openness for most</sup> countries with much confidence." Direct measures of trade barriers<sup>could include</sup> administrative data, such as<sup>average tariff rates or coverage</sup> ratios for nontariff barriers.<sup>Problems typically arise,</sup> however, in attempting to aggregate<sup>these data into an overall</sup> index. Coverage ratios for nontariff<sup>barriers cause the greatest</sup> difficulty. Since the coverage<sup>ratio indicates the percentage of</sup> 5
imports covered by trade barriers,<sup>an extremely effective barrier</sup> that excludes almost all imports<sup>would receive little weight.</sup> The coverage ratio only suggests<sup>that barrie-s to trade exist,</sup> but cannot measure their effect<sup>(for a discussion of the</sup> relationship between these<sup>administrative measures and other</sup> indicators of openness, see Pritchett<sup>(1990)).</sup> Related efforts have focused<sup>on using measures derived from</sup> a careful examination of tariffs<sup>and non-tariff barriers.</sup> Thomas, Halevi, and Stanton (1991)<sup>use a measure of trade</sup> liberalization based on a country-by-country<sup>assessment. They</sup> find that countries which liberalized<sup>in the 1980s increased</sup> their rate of GDP growth significantly,<sup>even when other effects</sup> were taken into account, including<sup>external financing, changes in</sup> the terms of trade, movements<sup>in the real exchange rate, and</sup> faster growth in OECD countries.

Research on trade and growth<sup>using both price-based or</sup> administrative measures has<sup>increased in the last several years.</sup> Studies based on these types<sup>of measures (See Section II in Table</sup> 1) have generally found a positive<sup>relationship between trade and</sup> growth. Although more recent<sup>efforts to identify the impact of</sup> openness on economic growth have<sup>relied on the use of cross-</sup> sectional averages of time-series<sup>data, one exception to this</sup> trend is Bhalla and Lau (1991),<sup>which examines the association</sup> between openness and growth using<sup>annual data. Bhalla and Lau</sup> (extending Lau, Jamison, and<sup>Louat (1991)) also construct annual</sup> measures of capital stock and educational<sup>stocks, which allows</sup> 6
them to disassociate the impact of openness from the effects of education and investment on growth. Their openness measure is constructed using national accounts data to derive the relative price of tradables, which is then compared with a benchmark price of tradeables. Their resutlts suggest that openness significantly affects growth, even after controlling for the rate of growth of capital stock, land, labor, and educational stocks. They also find that the interaction between education and openness is important: the rate of return to education rises in more open economies.

Micro studies (Section III in Table 1) have generally shown a positive association between increased exports and productivity growth. However, the relationship between imports and productivity growth is often negative. Interestingly enough, Lopez (1990) finds a similar pattern in macroeconomic data, using different measures for policies affecting imports and exports: export incentives positively affect overall growth, while import restrictions have an insignificant effect. Lopez (1990) attributes this to a break-down of Lerner symmetry: restricting imports may not act as an implicit tax on exporters.

In the micro productivity literature, the observed pattern is likely to be due to two factors, both related to estimation problems arising from simultaneity bias. First, countries tend to export goods in which they have a comparative advantage and to import goods in which they do not. Past empirical work--which generally ignores any problems due to 7
simultaneity--has been unable to distinguish between the expected positive effect of imports on productivity growth in the long run and the fact that imports are drawn to low productivity sectors where a country does not have an international advantage. Second, the observed relationships could also be explained by the well-known pro-cyclical nature of productivity growth: productivity growth tends to be higher when output is growing, and falls during recessions or low-growth periods. Corsequently, if greater import penetration is accompanied by a contraction of domestic industry, it is not surprising th:Nt productivity growth also falls.

One paper which has been able to convincingly address this simultaneity problem is Kaufman (1991). Using micro-level data on the rate of return to World Bank investment projects, Kaufman finds that a range of policies--including trade and exchange rate policies--significantly affect the rate of return to projects. A more open policy environment can double the rate of return to investment, even after controlling for general economic trends, such as GDP growth.

One difficulty in measuring the impact of trade policies on growth is that trade policy itself may be a function of other variables, including growth. Studies that have tried to identify the causal relationship between GDP growth and growth in exports or imports have i,+d mixed results (See Section IV in Table 1).

This brief review of the literature on openness and economic growth reveals twe important considerations. First, 8
despite the voluminous literature on this topic,<sup>the debate is by</sup> no means resolved. Many studies do reveal a positive<sup>relationship</sup> between various measures of openness and growth.<sup>But nagging</sup> problems remain. Methodological shortcomings make<sup>it difficult to</sup> link performance outcomes with policies per<sup>se; causality tests</sup> and micro-level anaJyses yield mixed results.

Second, it should be evident that no independent<sup>measure of</sup> so-called "openness" is free of methodological<sup>problems. Even the</sup> most recent use of direct price comparisons,<sup>facilitated by the</sup> work of Summers and Heston (1988), is plagued<sup>by small sample</sup> size--the data l'as not been collected for the same<sup>setof</sup> benchmark countries over many years. This may<sup>be one factor</sup> which has led to an emphasis on the use of cross-section estimation. Even if panel data--which spans a number<sup>of countries</sup> over several years--was widely available for international<sup>price</sup> comparisons, there would still exist the possibility<sup>that price</sup> distortions reflect domestic market imperfections (such<sup>as</sup> oligopolistic marketing channels for imported goods)<sup>as much as</sup> tradre policy interventions.

Consequently, the approach adopted in this paper<sup>is to</sup> gather as many different measures of openness as<sup>are available</sup> for a cross-section of developing countries over<sup>time, and test</sup> whether these measures generally yield the same results. Unfortunately, we are forced to exclude a number<sup>of openness</sup> measures which are not available over time, such<sup>as the indices</sup> computed by Leamer (1988), and the comprehensive<sup>data on tariffs</sup> 9
and non-tariff barriers gathered by UNCTAD for a cross-section of developing countries in 1987. **2** II. Data and correlations between openness variables.

The empirical specification employed in this paper is derived from a general production function, with output growth (GDP) as a function of capital stock, average years of education, population, labor force, agricultural land, and technological change. Inclusion of openness measures (or other policy variables) in the production function is consequently a test their impact on technological change--growth in output after controlling for increases in resource use. The production function is augmented--through the use of country dummy variables--to allow for unobserved country-specific differences in productivity.

GDP growth is calculated as log differences using national accounts data in 1980 dollars, collected by the World Bank. Physical and human capital stocks were calculated by Bhalla and Lau (1991), extending a method applied by Lau, Jamison, and Louat (1991) on a smtller sample of countries. Bhalla and Lau computed capital stock and years of education from annual capital investment and educational enrollment data, using the perpetual

> 2 See Pritchett (1991) for further details regarding the UNCTAD data. Pritchett (1991) uses cross-section data to compare a number of different openness measures, including the UNCTAD and Leamer measures. Although we considered using the UNCTAD data to estimate the impact of 1987 tariff and non-tariff barriers on consequent groqth, not enough post-1987 data was available to do this exercise.

10
inventory method for investment and a similar approach for educational stocks.

All values have been transformed into differences of log values, with the exception of years of education, where differences of levels are used. The stock of education has been divided into splines to test the impact on growth of 0 to 3 years of schooling and the additional effects of more than 3 years of schooling separately.

Seven different proxies for trade and exchange rate policies were collected from different sources to test the statistical relationship between openness and growth. The first, an annual index of trade liberalization for 1960-84, was derived using observations on exchange rate and commercial policies (Source: Papageorgiou, Miclhaely, and Choksi, 1990). Second, an index of trade liberalization for 1978-88, was calculated using country sources on tariffs and nontariff barriers (source: Thomas, Halevi, and Stanton, 1991). The third, a black market premium, measures the deviation of the black market rate from the official exchange rate (source: International Currency Analysis, Inc., various years). The fourth, trade shares, measures the ratio of exports and imports to GDP (source: World Bank data). The fifth, movement toward international prices, was derived from the relative price of a country's tradables, which was computed using current and constant national accounts price indexes (for more details, see Bhalla and Lau (1991) or the discussion above). This variable uses as a benchmarket the relative price of 11
consumption goods for 1980 from Summers<sup>and Heston (1988). It is</sup> then transformed to measure the movement<sup>toward urnity. The sixth,</sup> index of price distortion, is a modified<sup>version of the index</sup> used in Dollar (1991). The relative price<sup>of consumption goods</sup> from Summers-Heston is "purged" of its<sup>non-traded component by</sup> taking the residual from a regression<sup>of this index on</sup> urbanization, land, and population.<sup>The seventh, bias against</sup> agriculture, measures the indirect bias<sup>against agriculture from</sup> industrial sector protection and overvaluation<sup>of the exchange</sup> rate (source: Krueger, Schiff, and Valdes<sup>(1991)).</sup> Annual observations were available for<sup>time periods which</sup> ranged from 1960-87 for trade shares to<sup>1978-88 for the Thomas et</sup> al. trade liberalization index. The number<sup>of countries</sup> available for each index varies, ranging<sup>from 60 (for trade</sup> shares) to 19.

Tables 2 and 3 examine the rank correlation<sup>between</sup> these seven different measures of openness.<sup>Table 2, which</sup> examines the rank correlation between<sup>openness measures in</sup> levels, excludes the measure for movement<sup>towards international</sup> prices, which is an estimate of changes<sup>in policy. The results</sup> suggest that there is generally a statistically<sup>significant (and</sup> positive) correlation between the two<sup>measures of trade reform,</sup> minimal disprotection of agriculture,<sup>and trade shares. This</sup> positive relationship exists for both<sup>levels of openness as well</sup> as changes, for a pure cross section<sup>as well as for a panel.</sup> However, the majority of the rank correlations<sup>using the pure</sup> 12
cross section (averages of the time series for each country) are not statistically significant. In many cases, the value of the rank correlation is unchanged across the annual and cross-section samples, but the significance is simply much lower for the crosssection data.

As expected, there is also a negative relationship between those four measures and the extent of a black market premium. The rank correlations in Tables 2 and 3 confirm that inappropriate levels of the official exchange rate, proxied by the black market premium, are generally inversely associated with "open" trade policies. Of course, these correlations do not indicate the direction of causation between exchange rate and trade policies; they only indicate that the two are significantly related.

The two remaining measures employed in the analysis, both measures of price distortions, do not show a consistent or generally significant relationship with the other measures (see Tables 2 and 3). Although the lack of an association between these measures and the others is surprising, it says nothing about the extent to which one measures is necessarily preferable to others. The lack of a perfect (or even appropriately signed) correlation between all these measures is likely to indicate that they are not capturing the same aspects of "openness": the black market premium, for example, is a direct measure of the extent to which inappropriate exchange rate policies may trigger (or be a consequence of) protection.

13
# III. Basic Results

Tables 4 and 5 present the first<sup>set of regression results.</sup> Period averages were corAputed over time<sup>for each country to</sup> create a pure cross-section estimation across<sup>countries. The</sup> size of each sample depends on the number<sup>of countries with each</sup> of the openness measures, as well<sup>as the availability of</sup> educational and capital stocks. Table 4<sup>presents the results when</sup> levels of openness are included as independent<sup>right-hand side</sup> variables, while Table 5 presents the<sup>impact of chanaes in</sup> openness. Static trade models do suggest<sup>that movements towards</sup> openness can temporarily increase the<sup>rate of growth due to</sup> short-run gains from the reallocation of<sup>resources, which would</sup> imply a positive relationship between<sup>changes in openness and GDP</sup> growth. Neoclassical growth models, however,<sup>do not suggest any</sup> long run relationship between the level<sup>of openness and economic</sup> growth. Recent efforts to model the impact<sup>of openness in a</sup> dynamic framework, however, predict that<sup>both levels and changes</sup> in openness can have a long-run impact on growth.

The results in Tables 4 and 5 suggest<sup>that after</sup> controlling for other inputs, when openness<sup>is computed as an</sup> average over several decades it generally<sup>has an insignificant</sup> impact on economic growth. The only variables<sup>which significantly</sup> affected growth are the level of the black<sup>market premium and</sup> changes in trade shares, both of which have<sup>the correct signs.</sup> Increasing the share of trade in GDP positively<sup>affects growth,</sup> 14
while a higher black market premium<sup>is negatively associated with</sup> growth.

What about other factors? The most important<sup>variables are</sup> the growth of the labor force and<sup>the capital stock: on average a</sup> one percent increase in capital accounts<sup>for an increase in the</sup> rate of GDP growth of between .4<sup>and .6 percent. The coefficients</sup> on arable land and human capital, as<sup>proxied by years of</sup> education, vary in both magnitude and<sup>significance, indicating</sup> that the impact of these measures<sup>on growth is extremely</sup> sensitive to the sample of countries and<sup>time period chosen. In</sup> general, the impact of changes in the<sup>stock of education seem to</sup> be greater for the first three years<sup>of schooling than for any</sup> increments which follow. One possible reason for the sometimes insignificant impact of changes in<sup>the average years of education</sup> on growth could be that this variable<sup>changes only slowly over</sup> time. Alternative specifications which<sup>used the stock of</sup> education at the beginning of the<sup>sample period generally showed</sup> a positive and statistically significant<sup>association between</sup> average years of education and the<sup>rate of GDP growth.</sup> Although a large share of earlier research<sup>has focused on</sup> period averages to identify the determinants<sup>of long run growth,</sup> using period averages is likely to<sup>hide significant variations in</sup> individual country performance. Most<sup>developing countries have</sup> experienced large swings in commercial<sup>and exchange rate policies</sup> over the last thirty years, which could<sup>render any proxies for</sup> openness essentially meaningless. Due<sup>to the large variation in</sup> 15
country policies since the 1950s, beginning of period values could also have little explanatory power. Consequently, the regressions were redone using annual data for the same dependent and independent variables. To control for unobserved countryspecific differences in growth rates, we included dummy variables for each country--the so-called fixed effects model. The results are given in Tables 6 and 7.

The results presented in Tables 6 and 7 show very different effects of the seven openness measures on growth. Four of the seven measures have a statistically significant impact at the 5 percent level of significance; all seven measures are significant--in either levels or differences--at the 10 percent level. All the measures have the expected sign--movements toward openness positively affect growth; greater distortions (as measured by the black market premium and modified Dollar (1991) measure) negatively affect growth. In addition, the F-tests reported in Tables 6 and 7 reject the null hypothesis that country effects are not important. In nearly all the specifications, the country dummies are jointly significant-suggesting the presence of country-specific differences that persist over time, even after accounting for changes in policy and increases in the labor force, education, and capital stock.

One problem with using annual data to identify the determinants of long run growth is that short term or cyclical fluctuations could be responsible for the strong relationship between policy variables and GDP growth. Quah and Rauch (1990) 16
used trade shares as a proxy for openness to decompose the short and long run effects of openness on economic growth. Using annual data, they found that most of the observed positive relationship between openness and growth was due to short-run cyclical fluctuations. Consequently, we also compute period averages for 1960-66, 67-73, 74-81, and 82-88. These results are given in Tables 6 and 7.

The six-year averages do seem to indicate a robust relationship between openness and growth. Five of the seven variables show a positive relationship between openness and growth, after controlling for investment, education, and countryspecific effects captured through the use of dummy variables. Again, the null hypothesis that country dummy variables are jointly insignificant is generally rejected, although with less regularity than for the annual data.

Table 10 summarizes the relationship between openness and growth presented in Tables 4 through 9. Using six-year or annual data, the different specifications show a positive, generally significant association between the various measures of openness used in this study and productivity growth. However, using crosssectional data derived from long run averages only reveals a significant relationship between openness and growth for two of the seven indicators.

Figure 1 plots the partial correlations between all seven measures of openness and productivity growth, using six-year averages. The scatter plots in Figure 1 reveal an important 17
stylized fact: although the partial correlations are generally statistically significant, explanatory power of these seven measures varies. The R-square on the partial correlations ranged from .03 to .30, indicating that although trade policy is important, much variation in growth rates is still unexplained, even after accounting for changes in education, labor, land, and capital stock.

IV. Sensitivity Tests: Country Size and Macroeconomic policy Past efforts to isolate the impact of openness on growth have generally failed to control for two factors: country size and macroeconomic policy. If one of the primary gains from openness is through its impact on competition, then would it be possible for domestic competition in large countries to substitute for the effects of trade? If so, then openness may generate gains only for smaller countries. Another critique of existing studies arises from the possibility of omitted variable bias. Prudent macroeconomic policies--which often go hand in hand with more open trade and exchange rate policies--may lead to higher productivity growth. If so, then excluding these variables from the analysis may lead to mistakenly identifying the gains from trade instead of the real cause--macroeconomic stability. For example, Levine and Renelt (1990) found that the positive association between trade shares and GDP growth disappeared in a cross-section of countries when they included government 18
expenditures in the regression. We examine these two hypotheses in turn.

Although a number of different variables may be used to measure country size, we followed Kuznets, Chenery and<sup>Syrauin</sup> and chose country population as our measure. (The analys.s was also conducted using the level of GDP as a measure of size, which did not significantly affect the results). The results are shown in Table 11. The size variable was included by itself and interacted with trade policy. If it is true that large countries benefit less from more open policies than small countries, then the coefficient on the interaction of trade policy and size should be opposite in sign to the cocificient on openness, mitigating its effect. The results in Table 11 do show a mitigating effect for 4 of the 7 variables, but none of these are statistically significant. The only trade policy variable<sup>for</sup> which the inclusion of size affects openness is the Choksi measure, yet it has the opposite of its expected effect: the impact of liberalization is positive and significant for larger countries.

Although the impact of size by itself varies with the number of countries included in the sample, country size is statistically significant (and always positive) in four specifications--those with the largest number of observations. This suggests that if the sample of countries is sufficiently large, one generally finds that larger countries have experienced higher productivity growth. This confirms results from earlier 19
studies, using a different sample of countries and different methodology (see, for example, Perkins and Syrquin (1989)).

To test for the possibility of omitted variable bias due to the exclusion of macroeconomic policy variables, we re-estimated the basic equations for the annual data, six-year averages, and long-run averages. Renelt and Levine (1990) showed that if changes in government consumption are included in a regression of GDP growth on trade shares, then the positive association between trade shares (often used as a measure of openness) and GDP growth becomes statistically insignificant. The results in Table 12 confirm this result. The statistically significant and positive relationship between changes in trade shares and growth disappears when we include changes in government spending as a share of GDP. The other openness measures, however, are generally robust to the inclusion of the government spending variable. Only in the annual data--which is more likely to pick up short-term fluctuations captured by changes in government consumption--do several openness measures lose statistical significance when government consumption is included--such as the black market premium, the Choksi et al. measure of trade liberalization, and the measure for bias against agriculture.

# V. Conclusion and Directions for Further Research

This paper provides a summary of previous work on openness and growth and contributes to that literature by measuring the impact of a wide range of openness measures on economic growth.

20
The results suggest that the choice of time period for analysis is critical: whereas only 2 of the 7 openness measures positively affect growth when cross-section data are employed, 5 of the 7 proxies for openness reveal a positive association with growth when the data is averaged over six-year periods, and all 7 measures are statistically significant (in either levels or differences) using annual data.

Nevertheless, in other respects the results are surprisingly robust: when openness is statistically significant in any of the many specifications explored in this paper, we always find that greater openness is associated with higher growth. Tests of the sensitivity of these results to country size do not change the conclusions. We also test for the possibility of omitted variable bias by including government spending in the regressions. The inclusion of government spending does eliminate the statistical significance of trade shares in explaining growth, but leaves the results using other proxies for openness generally unchanged.

Two issues have been highlighted by this paper as interesting for future research. First, the literature is still unresolved on the issue of causality. Does openness cause growth? Or is it the other way around? Harrison (in progress) applies causality tests using vector autoregressions to investigate the direction of causation between openness and growth. Although the limitations of such tests are well known, such an exercise constitutes at least a first step towards analyzing the problem 21
of causation. Second, the different results which arise from the use of cross-section and panel data suggest the importance of disentangling short-run from long run effects without throwing away the information in annual data. Quah and Rauch (1990) have made a first attempt to disentangle the impact of cyclical from long-run effects of policies on growth in time series data. Unfortunately, Quah and Rauch use trade shares as their proxy for openness, which is one of the least robust measure of openness in our analysis. Extending Quah and Rauch (1990) to analyze other openness measures would be a useful exercise.

22
# Biblioaraphy

Balassa, Bela. 1985. "Exports, Policy Choices, and Economic Growth in Developing Countries after the 1973 Oil Shock". Journal of Development Economics 18:23-35. The Johns Hopkins University, Baltimore, MD and The World Bank, Washington, D.C., Balassa, Bela and Associates. 1971. The Structure of Protection in Developing Countries. The Johns Hopkins Press, Baltimore, Maryland and London Barro, R.J. 1991. "Economic Growth in a Cr3ss Section of Countries." Ouarterlv Journal of Economics, (May) 106.

Bhagwati, Jagdish. 1978. Foreian Trade Regimes and Economic DeveloRment: Anatomy and Consecruences of Exchange Control Regimes. Ballinger Press for the National Bureau of Economic Research, Cambridge, Massachusetts.

Bhalla, Surgit, and Lawrence J. Lau. 1991. "Openness, Technological Progress, and Economic Growth in Developing Countries." Background paper for World Development Report 1991.

De Long, J. Bradford and Lawrence H. Summers. 1990. "Equipment Investment and Economic Growth." Harvard University and NBER (October).

Dollar, David. "Outward-oriented Developing Economies Really Do Grow More Rapidly, Evidence from 95 LDCs, 1976-85." Forthcoming, 1991, in Economic DeveloRment and Cultural Change.

Edwards, Sebastian. 1989. "Openness, Outward Orientation, Trade Liberalization and Economic Performance in Developing Countries," World Bank PPR Working Paper # 191.

Esfahani, Hadi S. 1989.. "Exports, Imports, and Economic Growth in Semi-Industrialized Countries." Revised (September). Department of Economics, University of Illinois at UrbanaChampaign, Urbana, Illinois.

Geroski, Paul A. 1989. "Entry, Innovation and Productivity Growth." The Review of Economics and Statistics. 572-578. London Business School.

Grossman, Gene M. and Elhanen Helpman. Forthcoming, 1991. Innovation and Growth: Technological ComPetition in the Global Economy. MIT Press, Boston, Massachusetts.

23
Heitger, Bernhard. 1986. "Import Protection and Export Performance: Their impact on Economic Growth." Weltwirtschaftliches Archiv. 260(July):1-19.

Helliwell, John F. and Alan Chung. 1990. "Macroeconomic Convergence: International Transmission of Growth and Technical Progress." Hsiao, M.W. 1987. Tests of casuality and exogeneity between exports and economic growth: the case of the Asian NICs, Journal of Economic Development, 12(2):143-159.

Jung, W. and P. Marshall. 1985. "Exports, Growth and Casuality in Developing Countries." journal of Development Economics. 14:241-250.

Kaufman, Daniel. 1991. "Determinants of the Productivity of Projects in Developing Countries: Evidence from 1,200 Projects". Background paper for World Development Report 1991.

Krueger, Anne 0. and Baran Tuncer. "An Empirical Test of the Infant Industry Argument." The American Economic Review, 72(5):1142-1152.

Kunst, Robert M. and Dalia Marin. 1989. "On Exports and Productivity: A Casual Analysis." The Review of Economics and Statistics. 699-703. Institute of Advanced Studies.

Leamer, Edward E. 1988. "Measures of Openness," in Robert E. Baldwin,editor, Trade Policy Issues and Empirical Analysis.

Levine, Ross and David Renelt. 1990. "A Sensitivity Analysis of Cross-Country Growth Regressions." World Bank.

Lopez, Ramon. 1990. "Economic Growth, Capital Accumulation and Trade Policy in LDCs". (July) Trade Policy Division, Country Economics Department, World Bank, Washington, D.C. Nishimizu, Mieko and John M. Page, Jr. 1990. "Trade Policy, Market Orientation, and Productivity Change in Industry", in J. de Melo and A. Sapir, eds., Trade Theory and Economic Reform North. South. and East.

Nishimizu, Mieko and Sherman Robinson. 1984. "Trade Policies and Productivity Change in Semi-Industrialized Countries." Journal of Development Economics, 16:177-206.

Papageorgiou, Demetrios, Michael Michaely and Armeane M. Choksi, 1991, eds. in Liberalizina Foreign Trade: Lessons of Experience in the Developina World. 7:1-440. Basil Blackwell, Cambridge, Massachusetts.

24
Perkins, Dwight H. and Moshe Syrquin. 1989. "Large Countries: The Influence of Size." Handbook of Development Economics. volume II. Edited by H. Chenery and T.N. Srinivasan. Elsevier Science Publishers.

Phillips, Robert and Oli Havrylyshyn. 1990. "The 'ffect of Trade Liberalization or Productivity: An Aggregate Production Function Analysis". (June).

Pritchett, Lant. 1991. "Measuring OUtward Orientation in Developing Countries: Can it be done?". PRE Working Paper 566. World Bank.

Quah, Danny and James E. Rauch. 1990. "Openness and the Rate of Economic Growth." Preliminary draft (October). Economics Department, Massachusetts Institute of Technology and Economics Department, University of California San Diego, U.S.A.

Ram, Rati. 1985. "Exports and Economic Growth: Some Add.iional Evidence." Economic Develooment and Cultural Change, 33(2):415425.

Summers, Robert and Alan Heston. 1988. "A New Set of International Comparisons of Real Product and Price Levels: Estimates for 130 Countries, 1950-1985." Review of Income and Wealth, March:1-24.

Syrquin, Moshe and Hollis Chenery. 1989. "Three Decades of Industrialization". The World Bank Economic Review 3(2):145-181.

Thomas, Vinod, Nadav Halevi, and Julie Stanton. 1991. "Does Policy Reform Improve Performance?". Background paper for World Development Report 1991.

Thomas, Vinod and John Nash. Forthcoming, 1991. Best Practices: Lessons in Trade Policy Reform. New York, Oxford University Press.

Tybout, J. 1990a. "Researching the Trade/Productivity Link: New Directions." Forthcoming in The World Bank Research Observer.

World Bank. 1991. World Develoyment Report 1991. New York: Oxford University Press.

25
Table 1 Summary evidence on openness and growth

|Openness measure<br>C|ountries|Period|Impact|Source|
|---|---|---|---|---|
|1 Measures Based on Trade Shar|es||||
|.|||Coefficient<br>on openness||
|Deviation from predicted<br>trade|45|1973-78|Significant,<br>>0|Salassa (1985)|
|Deviation from predicted<br>trade (Leawmr (¶988))||1982|Significant,<br>>0|Edwards (1989)|
|<br>Changes in trade shares<br>Trade shares|19<br>81 LDCs|1960-85<br>1960-85|Significant, >0<br>Weakly significant,<br>>0|Helliwell<br>and Chung (1990)<br>Quah and Rauch (1990)|
|II.<br>Price-based<br>and administrative|<br>measure|s|||
|8halla/Lau (1991), using<br>the relative price of<br>tradables to<br>international<br>prices|60|1960-87|Raises GDP growth|Bhalla and Lau (1991)|
|Relative domestic price<br>of investment goods<br>t ittil<br>ri|98|1960-65|Raises GDP growth<br>per capita|Barro (1990)|
|o nernaona<br>pces<br>Relative price of traded<br>goods|95|1960-85|Raises GDP growth<br>per capita|Dollar (1990)|
|Effective rate of<br>protection in manufacturi|47<br>ng|1950-80|Lower protection<br>raises GDP growth|Heitger (1987)|
|Trade Liberalization<br>index<br>from Choksi (1989)|20|1964-84|Weak evidence of<br>increased productivity|Philtips and<br>Havrylyshyn (1990)|
|Trade liberalization<br>index<br>from Halevi (1989)|35|1975-85|Export incentives<br>positively<br>affect GDP<br>per capita<br>growth,<br>insignificant<br>inpact of<br>import restrictiveness|Lopez (1990)|
|Trade liberalization<br>index<br>from HaLevi-Thomas (1990)||1978-88|Trade reform positively<br>affects<br>GDPgrowth.|Thomas/Nash (1991)|
|III.<br>Micro and Productivity<br>stud|ies||||
|Deviation from predicted<br>export share|108|1960-82|Positive|Syrquin and Chenery (1989)|
|<br>Export growth|4|1955-78|Positive<br>|Nishimizu and Robinson 1984<br>|
|Export growth<br>|17<br>|1950-80<br>|Positive<br>|Nishimizu and Page (1990)<br>Tb 1990|
|Export growth<br>|4<br>|1976-88<br>|Positive<br>|yout ()<br> P 1990|
|Import penetration|17|1950-73<br>1973-85|Ambiguous<br>Negative|Nishimizuand age ()|
|Import substitution<br>(IS)<br>(1 - Inport penetration)|4|1955-78|IS negatively<br>affects<br>TFP|Nishimizu and Robinson<br>(1984)|
|<br>Import substitution|4|1976-88|ISpositively<br>affects<br>TFP|Tybout (1990)|
|Effi<br>t f|||||
|ectve<br>raes o<br>protection<br>and domestic|||||
|<br>resource costs<br>Change in import shares|1<br>UK|1963-76<br>1976-79|Ambiguous<br>Ambiguous|Krueger and Tuncer (1982)<br>Ge,oski (1989)|
|IV.**Causality**tests|||||
|Methodology<br>Granger tests<br>Whi ifii|37|1950-81|Exports cause growth?<br>For only 4 countries|Jung and Marshall(1985)|
|te speccaton<br>test<br>Granger, Sims tests<br>(Asi|73<br>4<br>n NICs)|1960-77|Yes<br>Sometimes|**Ram**(1985)<br>tsio(1987)|
|<br>Granger tests|<br>Austria|<br>1965|No, but productivity<br>growth causes exports|Kunst and Marin (1989)|

26
Table 2 Spearman Rank Correlation Coefficients for 7 **Opennese** Measures in Levels: Cross-Section and Anriual Data **i/**

||TR I|TR II|BLACK|DOLLAR|TRADE<br>SHARES|INDIRECT|
|---|---|---|---|---|---|---|
|rrade<br>reform (TRI)<br>(1960-84)|1.0<br>1.0|.10<br>.73w|*44**<br>-.37***|.36<br>.08|.70***<br>.51***|<br>.37<br> <br>.38***|
|Trade reform<br>(1979-88) (TRII)||1.0<br>1.0|-.39***<br>-.34***|.05<br>.14**|.06<br>.26***|.20<br> <br>.52***|
|Black market premium (BLACK)|||1.0<br>1.0|-. 07<br>.00|-.16<br>-. 21***|..61***<br>-.470*|
|ice distortion (DOLLAR)||||1.0<br>1.0|.11<br>.06**|.50**<br>.22*0*|
|-ade shares|||||1.0<br>1.0|.25<br>.36***|
|Disprotection of<br>agriculture (INDIRECT)||||||1.0<br>1.0|

Table 3 Spearman Rank Correlations for Changes in Openness:/

||TR I|TR II|BLACK|DOLLAR|MTP<br><br>|TRADE<br>SHARES|INDIRECT|
|---|---|---|---|---|---|---|---|
|ade reform (TR1)<br>(1960-84)|1.0<br>1.0|-.07<br>.47***|-.60***<br>- . III*"|.01<br>.02|-.11<br>-.14***|.46*<br> .17*0*|.74***<br>.17***|
|ade reform (TR II)<br>(1979-88)||1.0<br>1.0|-. 27*<br>-.11**|.17<br>.12|.07<br>.08|.12<br>.05|-. 23<br>.32**-|
|ack market prefnium<br>(BLACK)|||1.0<br>1.0|.21<br>-. 01|.06<br>-. 01|-. 11<br>.. 15**0|-. 27<br>**..15*5e**|
|ice distortion (DOLLAR)||||1.0<br>1.0|.27<br>.10***|-.385**<br>.14*^*|<br>.16<br> -. 05|
|vement towards<br>International<br>Prices (MTP)|||||1.0<br>1.0|-.10<br>-.03|.27<br>-.09|
|ade shares||||||1.0<br>1.0|.49***<br>.25***|
|sprotection of<br>agriculture (INDIRECT)|||||||1.0<br>1.0|

tes: **1/** Top figure indicates rank correlation for coefficients averaged over entire time period; bottom figure gives annual te rank correlations.

Indicates significant at 15 X level; ** indicates significant at 10 X level; *** indicates significant at 5 X level.

27
aWle 4 Cross-section estimation using twenty-seven year averages ana levets of trace roticy

||(1)|(2)|(3)|(4)|(5)|(6)||
|---|---|---|---|---|---|---|---|
|Intercept|0.0<br>(.01)|0.0<br>(0.0)|-0.0<br>(0.0)|-0.02<br>(.01)|<br>-0.01<br>(.01)|<br>0.01<br>(.01)||
|TRI|-0.05<br>(.16)|||-||||
|TR|-|0.0<br>(0.0)|-|_|_|||
|SLACK|-||-.013**<br>(.005)|||||
|DOLLAR||||0.01<br>(.02)||||
|TRADE SHARES||-|||0.013<br>(.008)|||
|INDIRECT|-|-|-|-|-|1.14<br>(2.14)||
|LAND|-0.48<br>(0.28)|0.50<br>(.27)|-0.10<br>(.73)|-0.12<br>(.21)|-0.01<br>(.14)|0.02<br>(.28)||
|LABOR FORCE|0.65<br>(.27)|0.98<br>(.33)|0.44<br>(.17)|0.74<br>(.35)|0.34<br>(.18)|0.07<br>(.47)||
|EDUCATION<br>(0-3 Years)|0.21<br>(.14)|-0.13<br> <br>(.08)|-0.03<br> <br>(.06)|0.01<br>(.10)|0.02<br> <br>(.06)|0.01<br> <br>(.10)||
|EDUCATION<br>(3-9 Years)|0.09<br>(.07)|-0.01<br> <br>(.05)|0.06<br> <br>(.03)|*0.01<br>(.06)|0.07<br> <br>(.03)|-0.05<br> <br>(.07)||
|CAPITAL<br>STOCK|0.37<br>(.10)|0.45<br>(.09)|0.48<br>(.06)|0.60<br>(.10)|0.52<br>(.07)|0.61<br>(.10)||
|N|17|32|65|31|67|17||
|R-Square<br>TabLe S Cross-section estimation|86<br>using twenty-sev|.72<br>en year a|.66<br>verages and|.72<br>changes|.65<br>in trade p|.87<br>oticy||
||()|(2)|(3)|(4)|(5)|(6)|(7)|
|TR I|0.18<br>(.94)||||-|||
|TR11|-|-.02<br>(.02)|-|-||||
|BLACK|-|-|-0.09<br>(.07)|-||||
|DOLLAR|-|-|-|-.38<br>(.35)||||
|TRADE SHARES|||||0.78*<br>(.33)|-||
|INDIRECT|-|-||-|-|2.2<br>(26.8)||
|Movement towards<br>Internatonat<br>Prices|||||||0.04<br>(.07)|
|R-Square|.85|.73|.63|.73|.67|.87|.87|

Nctec Standard "rrors in i)."*" indicates significant at 5 percent Levtl; * indicates significant at 10 percent LeveL. Intercep **t** erm included in *ll regressions but not reported here.

28
'anoe o Fixeo erfect estimacion using annuaaL data ano tevets or trade poticy

||(1)|(2)|(3)|(4)|(5)|(6)|
|---|---|---|---|---|---|---|
|TRI|0.10*<br>(.05)|||||-|
|TRIt||0.02"<br>(.005)|-|||-|
|BLACK|--||0.01**<br>(.00)||||
|DOLLAR||||*O.05*<br>(.02)|||
|TRADESHARES|-||-||0.01<br>(.02)||
|INDIRECT|||-|||2.82*<br>(1.65)|
|LAND|0.00<br>(.03)|0.20<br>(.21)|0.13<br>(.05)|0.01<br>(.03)|0.04<br>(.03)|0.04<br>(.07)|
|LABOR FORCE|0.37<br>(.30)|-0.14<br>(.25)|0.68<br>(.18)|0.22<br>(.18)|0.64<br>(.17)|0.41<br>(.29)|
|EDUCATION<br>(0.3Years)|0.11<br>(.12)|0.33<br>(.14)|0.11<br>(.05)|0.04<br>(.07)|0.09<br>(.04)|0.06<br>(.09)|
|EDUCATION<br>(3-9 Years)|0.01<br>(.07)|0.01<br>(.06)|0.02<br>(.04)|0.02<br>(.05)|0.01<br>(.03)|0.03<br>(.07)|
|CAPITAL<br>STOCK|0.58<br>(.06)|0.67<br>(.10)|0.51<br>(.03)|0.56<br>(.04)|0.52<br>(.03)|0.50<br>(.06)|
|F-Value<br>1/|1.3|1.7|1.6|2.1|1.7|1.4|
|N|380|258|1498|838|1737|395|
|R-Square|.35|.37|.28|.33|.25|.38|

Table 7 Fixed effect estimation using anmual data and changes in trade policy

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|---|---|---|---|---|---|---|---|
|TR I0.13|(.09)|||||||
|TR 11|-|0.01<br>(.01)||||||
|BLACK||.|O<br>.**<br>(.004)|-||||
|OOLLAR||||0.01<br>(0.04)||||
|TRADE<br>SHARES|.|_-_|-|-|0.06*<br>(.03)|||
|INDIRECT|-|-||-|-|0.16<br>(2.29)||
|Movement toiwards<br>International<br>Prices|-|-|-|-|||0.04**<br>t.01)|
|F-Value 1/|1.3|1.1|1.9|1.9|1.9|1.2|1.1|
|R-Square|.36|.31|.28|.33|.26|.39|.34|

Note: Stmnoard errors in 0). '" indicate **s** ignificant at S percent level; * indicates significant at 10 percent level. 1/ **F-Value** for test of Null hypothesis that country effects are _0._ 29
boLe 3 FiXeo etfect estimacion using siA-year averages and tevets or traae OootIcY

||cl)|(2)|(3)|(4)|(5)|
|---|---|---|---|---|---|
|TR1|0.20*-<br>(.08)|||||
|BLACK|-|-0.02"<br>(.004)||||
|DOLLAR||.|0.05**<br>(.02)|||
|TRADE<br>SHARES||-||-0.02<br>(.02)||
|INDIRECT|||-|-|5.t6'<br>(3.61)|
|LAND|-0.13<br>(.17)|0.01<br>(.11)|-0.23<br>(.13)|0.12<br>(.11)|-0.09<br>(.19)|
|LABOR<br>FORCE|0.36<br>(.58)|0.83<br>(.28)|0.60<br>(.32)|0.67<br>(.28)|0.68<br>(.52)|
|EDUCATION<br>(0-3<br>Years)|0.17<br>(.16)|0.14<br>(.06)|0.09<br>(.10)|0.06<br>(.06)|0.04<br>(.11)|
|E3DUCATION<br>(3-9<br>Years)|0.07<br>(.09)|0.04<br>(.04)|0.03<br>(.06)|0.00<br>(.04)|0.06<br>(.08)|
|CAPITAL STOCK|0.54<br>(.07)|0.42<br>(.04)|0.51<br>(.05)|0.44<br>(.04)|0.36<br>(.07)|
|;-Value<br>1/|1.1|1.6|1.6|1.4|1.3|
|N|67|237|125|265|69|
|R-Square|.76|.71|.75|.85|.76|

Tabte 9 Fixed effect estimation using six-year averages and changes in trade policy

||(1)|(2)|(3)|(4)|(5)|(6)|
|---|---|---|---|---|---|---|
|TR 1|0.20<br>(.24)||||||
|BLACK||-0.02<br>(.02)|-||||
|COLLAR|||0.04".<br>(.01)||||
|TRADE<br>SHARES|-|||0.23"<br>(.10)|||
|INDIRECT|-|-|-|-|16.75**<br>(5.27)||
|Movement towards<br>international<br>Prices|-|-|-|-|-|0.05<br>(.03)|
|F-Value<br>1/|0.7|1.4|1.4|1.5|1.6|0.7|
|R-Square|.72|.67|.74|.65|.80|.69|

Note: Stanoard errors in 0."" indicates significant at 5 percent level; * indicates significant at 10 percent Level. 1/ F-Value for test of Nutt hypothesis that country effects are 0.

30
Table 10 Impnct of ometmness on growth: synthesis of findings

||Annual<br>|<br>data|Six-year<br>av|erages|Entire Peri|od<br>averages|
|---|---|---|---|---|---|---|
|Openness<br>variable|Levels dif<br>(1)|ferences<br>(2)|Levels<br>diff<br>(3)|erences<br>(4)|Levels<br>dif<br>(5)|ferences<br>(6)|
|Trade liberalization<br>Index (1960-84)|<br>>0*|>0<br>|>0,'*|O|°0|>0|
|Trade liberalization<br>Index (1978-88)|<br>>0<br>)|'O|-|-|°0|<|
|Black<br>market premium<br>1/|<br>>0,**|>0,**|<br>>0,**|>0|>0,**|>0|
|Trade<br>shares|>0|>0,*|0|>0,**|<br>>0|0,**|
|Price distortion<br>measure<br>1/|>0,**|0|>0,**|0,**|<br>O|>0|
|Movement<br>towards|||||||
|world prices||>0,**|<br>-|>0|-|>0|
|Bias against agricultur|e1/40,*|>0|>0,*|>0,**|>0|>0|

** Indicate **s** ignificant at 5 percent level; * indizates significant at 10 percent LeveL.

Notes: ALL regressions except entire period average include country dummies. 1. For purposes of comparison, a value of 1>0" indicates that more openness (Less distortion) positively affects growth. Consequently, for the bLack market premium, price distortion measures, and bias against agriculture, this table wi'L show ">0" when a higher Level of distortion negatively affects growth.

31
Table 11 Testing for Sensitivity of Results to Country Size, Using Six Year Averages and Trade Policy 1/

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|---|---|---|---|---|---|---|---|
|TRI|0.03<br>(.11)|-|-|-|-|-|-|
|TRI*Slze|5.00**<br>(2.35)|<br>-|-|-|-|-|-|
|TR II|-|0.0<br>(0.0)|-|-|-|-|-|
|TRII*Size|-|0.05<br>(.16)|-|-|-|-||
|Black|-|-|-0.02**<br>(0.0)|-|-|-||
|Black*Size|-|-|0.04<br>(.05)|-|-|-|-|
|Dollar|-|-|-|-0.06**<br>(.02)|-|-||
|Dollar*Size|-|-|-|.61<br>(.42)|-|-||
|Trade Shares|-|-|-|-|0.25*<br>(.10)|--||
|Trade Share*Size|-|-|-|-|-3.60<br>(3.36)|-||
|Indlr|-|-|-|-||29.44**<br>(7.97)||
|Indir*Size|-|-|-|-|-|-766.09<br>(367.80)||
|Movement towards<br>international prices||-|-|-|||0.04<br>(.03)|
|Movement*Size|-|-|-|-|-|-|0.71<br>(.82)|
|Land|-0.24<br>(.17)|0.07<br>(.47)|-0.01<br>(.11)|-0.25<br>(.12)|0.16<br>(.11)|-0.21<br>(.17)|-0.13<br>(.22)|
|Labor force|-0.07<br>(.58)|0.92<br>(.47)|0.82<br>(.27)|0.61<br>(.31)|0.59<br>(.27)|0.38<br>(.49)|-0.02<br>(.52)|
|Education<br>(0-3 years)|0.18<br>(.16)|-.22<br>(.09)|0.17<br>(.06)|0.15<br>(.10)|0.10<br>(.06)|0.16<br>(.11)|0.06<br>(.14)|
|Education|05|-0.10|0.04|0.03|0.00|0.09|0.02|
|(3-9 years)|(.09)|(.06)|(.04)|(.06)|(.04)|(.08)|(.08).|
|Capital Stock|0.50<br>(.08)|0.34<br>(.11)|0.43<br>(.04)|0.51<br>(.05)|0.44<br>(.04)|0.37<br>(.07)|0.53<br>(.07)|
|SLze|-0.42|-0.04|0.17|0.32|0.22|0.28|0.22|
||(.46)|(.22)|(.06)|(.13)|(.08)|(.32)|(.12)|
|_N_|67|32|231|125|263|67|102|
|<br>R-Square|<br>.96|<br>.62|<br>.90|<br>.94|<br>.89|<br>.96|.91|

}/ Levels of policy variables used for all variables except trade **shares,** indir, and movement towards international prices -- which urs changes in policies.

32
Table 12 Testing for Sensitivity of Resuits to Inclusion of Changes in Government Spendingi'

||ANNUA|L DATA|SIX-YEAR A|VERAGES|PERIOD A|VERAGES|
|---|---|---|---|---|---|---|
||OPENNESS|GOV'T.<br>SPENDIN|OPENNESS<br>G|GOV'T.<br>SPENDING|OPENNESS<br>|GOV'T.<br>SPENDING|
|(1) TR I|0.08<br>(0.09)|0.86<br>(.39)|0.25**<br>(.12)|1.35<br>(1.06)|-0.30<br>(.74)|1.14<br>(2.46)|
|(2) TR II|0.02**<br>(0.0)|0.22<br>(.21)|0.02*<br>(.01)|-1.26<br>(1.24)|0.0<br>(0.0)|0.96<br>(.77)|
|(3) BLACK|-0.01<br>(.01)|0.44<br>(.14)|-0.03**<br>(.01)|40.30<br>(.43)|-0.02**<br>(.01)|1.41<br>(.55)|
|(4) DOLLAR|-0.06**<br>(.02)|0.80<br>(.20)|-0.06*<br>(.03)|-0.03<br>_(.-'5)_|-0.01<br>(.02)|0.27<br>(.93)|
|_(5)_TRADE<br>SHARES|-0.06<br>(.06)|0.42<br>(.14)|-0.10<br>(.27)|-. 44<br>(.48j|0.41<br>_(.51)_|1.59<br>(.60)|
|(6)INDIR<br>.___________|1.50<br>_______<br>(3.09)|0.33<br>(.20)|6.00**<br>(2.91)|-0.82<br>(.42)|27.11<br>(28.85)|_-0.15_<br>(1.08)|
|(7) MOVEMENT|0.05**<br>(.02)|0.63<br>(.21)|0.07<br>(.05)|-0.05<br>(.62)|0.08<br>(.08)|0.68<br>_(.55)_|

1/ Levels of policy variables used for all variables except trade shares, in dir, and movement towards - international prices which use changes in policies. Standard errors in (). Significance levels for openness variables (only) indicated by ** (5 percent), and * (10 percent).

33
Figure **..** OPENNESS AND GROWTH: PARTIAL CORRELATIONS FOR A SAMPLE OF COUNTRIES, 1960-87 <!-- Start of picture text --> pROolaTIVITV GOWCTH G.S PROMCTIVITV GRDOWTH<br>0.0J 0. ,<br>0 02 , *.'' 5<br>0.0= 0.1<br>o00 . .. ~~~ 0.0<br>-002 .,'. -0.1 _ _<br>-0.02 -0. 0<br>-0.03 - I0NDEX OF TRADE LISERALiEATWU<br>INDEX OF TRADE LIEERAI.IZAIIOIi(OEE<br>PRODUCTIVITI GowTH 0 06 PROOUCTIVITV GROWTH<br>0 0606<br>004 004<br>002 002<br>0 0~~~~~~~~~~~~~~~~~~~~~~~~~~.<br>0 . 0 0 .<br>.~~~~~~~~~~~~~~~~~~~I.<br>-006 00<br>-0 o 06 4 02 0 02 04 0o6<br>BLACK MARKET oaEUIUU , CHANGES N TRADE SHARES<br>0.06k PRCOCCTIVITV GROWTH 6% PROOUCTIVITY GROWTH<br>0 04 .', %"<br>0 00'% 02 . ', ' ,2* ;.<br>002 " '. . ' 2% '<br>.00- . .<br>-006 .6%<br>MOVEMENT TOMAR03 INTERNATIONAL POICES PAICE DISTORTION INoeX<br>PRODUCTIvITV GROWTH WoteCO Tily of the sA .aewe of op_eas de a iUL@mZ at<br>the 3 X Levl in a regreslon of CDP geowth oa eP_e, Lopa<br>004 growth (capital, Labor, education. land) and Odl_tZY d_W<br>vagiebLes. The stinn tvo, the price dLatortios Lades ad<br>the movement toward intecnatLoaal prScoe, aiS nificant At<br>0 02 of the 10 the partial X Leve. comLation %Iwae scatter between pLats GOP present ggowth *1swal a and Op_nes, pictue<br>: ~~~~~~~~fter accountin for otba x feters. Counry d_*"o ere<br>o z_ Liberaligation L cluded in all *ad regressions. hh uses anuaL vlues, ALL values (0(e t the 197-e) tr<br>. ,'avraes for 1960-60, 67-73. 74-81. and 82-O8. The mb of<br>countrtie rauses from 60 (for trad& shams) to t9 (for tie<br>-0.02 LLbSrILgat*u La., 1900-U4).<br>6Sue For black cket premiu. Pick's Ovm7 Yearbooks &ade<br>-0.04 of trade LberaLstlsou 1940.44 * e , M ,aie Niabs<br>(199) I LaI.s of sErd 1i)ermLis 197846. fer 3a3.wiIThin<br>(1091)s bLas acda sexirni,. Kiam. l$GM"* a" TAU , 19<br>-0.06 I_____________________ *oaes Lo cgs". eks.. and - em towardse lainssums I pwit.s<br>K4A I *IA8 ^ aAGAINST zst 4aeut ut AORICULTURU ,_ 34Ao World Dellar Bank. rhu puceo dlavewtiou Index (191* Ls a mdwif J fogwser of<br>_ ~~~~34<br><!-- End of picture text -->
||Policy Research Workn|g<br>er ie|Contact|
|---|---|---|---|
|~~~~~~|~~~~~AZau||for paper|
|WPS785 How Did the Asian Countries Avoid<br>the Debt Crisis?|Ishrat Husain|October 1991|S. King-Watson<br>31047|
|WPS786 Fiscal Policy for Managing<br>Indonesia's Environment|Sadiq Ahmed|October 1991|B. Prasertwaree<br>82477|
|WPS787 Private Investment Under Macroeco<br>nomic Adjustment in Morocco|- Klaus Schmidt-Hebbel<br>Tobias Muller|October 1991|S. Jonnakuty<br>39074|
|WPS788 How Expectations Affect Reform<br>Dynamics in Developing Countries|Fra,-cesco Daveri|October 1991|S. Jonnakuty<br>39074|
|WPS789 Intrahousehold Inequality and the<br>Theory of Targeting|Lawrence Haddad<br>Ravi Kanbur|October 1991|J. Sweeney<br>31021|
|WPS790 Reforming and Privatizing Hungary's<br>Road Haulage|Esra Bennathan<br>Jeffrey Gutman<br>Louis Thompson|October 1991|B. Gregory<br>33744|
|WPS791 Measuring Real Exchange Rate<br>Instability in Developing Countries:<br>Empirical Evidence and Implications|Lant Pritchett|October 1991|K. Cabana<br>37947|
|WPS792 Reducing Labor Redundancy in<br>State-Owned Enterprises|Jan Svejnar<br>Katherine Terrell|October 1991|B. Gregory<br>33744|
|WPS793 Decollectivization and the<br>Agricultural Transition in Eastern and<br>Central Europe|Karen M. Brooks|October 1991|C. Spooner<br>30464|
|WPS794 How Do NatWnal Policies Affect<br>Long-Run Growth? A Research<br>Agenda|William Easterly<br>Robert King<br>Ross Levine<br>Sergio Rebelo|October 1991|R. Martin<br>39065|
|WPS795 Economic Stagnation, Fixed Factors,<br>and Policy Thresholds|William Easterly|October 1991|R. Martin<br>39065|
|WPS796 Excess Liquidity and Monetary<br>Overhangs|Gerard Caprio, Jr.<br>Patrick Honohan|October 1991|W. Pitayatonakarn<br>37666|
|WPS797 Using Field Visits to Improve the<br>Quality of Family Planning, Health,<br>and Nutrition Programs: A Supervisor'<br>Manual|Richard Heaver<br>s|October 1991|0. Nadora<br>31091|
|WPS798 Agriculture's Decline in Indonesia:<br> <br>Supply or Demand Determined?|Will Martin<br>Peter G. Warr|October 1991|M. Sanchez<br>33731|
|WPS799 Growth in Open Economies<br>|Sergio Rebelo|November 1991|R. Martin<br>39065|
# Policy Esearh Working Paper Series

||_lb_|Author|DOWor|Contact<br>pae r|
|---|---|---|---|---|
|WPS800|The Legal Framework for Private<br>Sector Development in a Transitional<br>Economy: The Case of Poland|Cheryl W. Gray<br>Rebecca J.<sup>Hanson</sup><br>Michael A. Heller<br>Peter lanachokov<br>YoussefL)hane|November 1991|CECSE<br>37188|
|WP3801|Unraveling the Mysteries of China's<br>Foreign Trade Regime: A View from<br>Jiangsu Province|Arvind Panagariya|November 1991|D. Ballantyne<br>37947|
|WPS802|Strengthening ths Bank's Population<br>Work in the Nineties|Steven<sup>W. Sinding</sup>|November 1991|0. Nadora<br>31091|
|WPS803|Financial Regulation: Changing the<br>Rules of the Game|Millard Long<br>Dimitri Vittas|November 1991|W. Pitayatonakarn<br>37666|
|WPS804|Global Trends in Raw Materials<br>Consumption|Boum-Jong Choe|November 1991|S. Lipscomb<br>33718|
|WPS805|Privatization in the Soviet Union:<br>The Beginnings of a Transition|Sergei Shatalov|November 1991|CECSE<br>37188|
|WPS806|Measuring Commercial Bank<br>Efficiency: Use and Misuse of Bank<br>Operating Ratios|Dimitri Vittas|November 1991|W. Pitayatonakarn<br>37666|
|WPS807|Moderate Inflation|Rudiger Dornbusch<br>Stanley Fischer|November 1991|S. Moussa<br>33490|
|WPS808|The New Trade Protection: Pric~e<br>Effects of Antidumping and<br>Countervailing Measures in the United<br>States|Ann Harrison<br>|November 1991|D. Ballantyne<br>37947|
|WPS809|Openness and Growth: A Time<br>Series, Cross-Country Analysis for<br>Developing Countries|Ann Harrison|November 1991|WDR Office<br>31393|