Does a Leapfrogging Growth Strategy Raise Growth Rate? Some International Evidence

Wang, Zhi; Wei, Shang-Jin; Wong, Anna Working Paper Does a Leapfrogging Growth Strategy Raise Growth Rate? Some International Evidence ADB Working Paper Series on Regional Economic Integration, No. 47 Provided in Cooperation with: Asian Development Bank (ADB), Manila Suggested Citation: Wang, Zhi; Wei, Shang-Jin; Wong, Anna (2010) : Does a Leapfrogging Growth Strategy Raise Growth Rate? Some International Evidence, ADB Working Paper Series on Regional Economic Integration, No. 47, Asian Development Bank (ADB), Manila, https://hdl.handle.net/11540/1959 This Version is available at: https://hdl.handle.net/10419/109551 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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Some International Evidence Zhi Wang, Shang-Jin Wei, and Anna Wong No. 47 | April 2010 ADB Working Paper Series on Regional Economic Integration Zhi Wang,+ Shang-Jin Wei,++ and Anna Wong+++ Does a Leapfrogging Growth Strategy Raise Growth Rate? Some International Evidence ADB Working Paper Series on Regional Economic Integration No. 47 April 2010 The views in the paper are those of the authors and are not the official views of the USITC or any other organization that the authors are or have been affiliated with. The authors would like to thank the following for comments: participants at a session of the American Economic Association meeting in 2009, the International Economics Working Group at the University of Chicago, and Maria Porter. This paper was presented at a jointconference of ADB, Bank Negara Malaysia, and European Commission, Beyond the Global Crisis: A New Asian Growth Model? on 18–20 October, 2010. +Zhi Wang is Senior International Economist, Research Division, Office of Economics, United States International Trade Commission (USITC), Room 603F, 500 E Street SW, Washington, DC 20436. [email protected] ++Shang-Jin Wei is Professor of Finance and Economics and N.T. Wang Chair in Chinese Business and Economy, Graduate School of Business, Columbia University, Uris Hall #619, 3022 Broadway, New York, NY 10027. [email protected] +++Anna Wong is a PhD student, Department of Economics, University of Chicago. [email protected] The ADB Working Paper Series on Regional Economic Integration focuses on topics relating to regional cooperation and integration in the areas of infrastructure and software, trade and investment, money and finance, and regional public goods. The Series is a quick-disseminating, informal publication that seeks to provide information, generate discussion, and elicit comments. Working papers published under this Series may subsequently be published elsewhere. Disclaimer: The views expressed in this paper are those of the author and do not necessarily reflect the views and policies of the Asian Development Bank or its Board of Governors or the governments they represent. The Asian Development Bank does not guarantee the accuracy of the data included in this publication and accepts no responsibility for any consequence of their use. Use of the term ―country‖ does not imply any judgment by the authors or the Asian Development Bank as to the legal or other status of any territorial entity. Unless otherwise noted, $ refers to US dollars. © 2010 by Asian Development Bank April 2010 Publication Stock No. Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Abstract v 1. Introduction 1 2. Measuring Leapfrogging 3 2.1 Measures of a Country’s Industrial Sophistication Based on Export Data 4 2.2 Data and Basic Facts 7 3. Do Leapfroggers Grow Faster? An Examination of the Evidence 9 3.1 The Elusive Growth Effect of a Leapfrogging Strategy 9 4. Further Investigations 10 4.1 Does Growth in Sophistication Lead to Growth in Income? 10 4.2 Non-normality and Non-linearity 11 4.3 Panel Regressions with Instrumental Variables 12 5. Comparing Cross-Regional Variations within a Single Country 12 6. Conclusion 14 References 15 ADB Working Paper Series on Regional Economic Integration 38 Tables 1. Replicating Hausman et al. Cross National Growth Regressions with Income Implied in a Country’s Export Bundle (EXPY), 1992–2003 17 2. Alternative Measure of Export Sophistication – Unit Value Adjusted Implied Income in the Export Bundle: Modified EXPY, 1992-2003 18 3. Cross National Growth Regressions with Advanced Technology Products (ATP) Share (narrow), 1992–2003 19 4. Cross National Growth Regressions with Advanced Technology Products (ATP) Share (broad), 1992–2003 20 5. Cross National Growth Regressions with Export Dissimilarity Index (EDI), 1992–2003 21 6. Ranking Growth in Export Sophistication, 1992–2003 22 7. Cross National Growth Regression, with Growth in Export Sophistication 24 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8. Test for Normality 25 9. Long Sample, Panel Regressions with Fixed Effects 26 10. Cross-Section Growth Regressions, Cities in the People’s Republic of China (1997–2006) 27 11. Panel Growth Regressions, Cities in the People’s Republic of China (1996–2005) 28 Appendix Tables 1. HS Products Excluded from Export Data 30 2. Countries (165) Included in the Sample Used in Cross Country Regression 31 3. Cities in the People’s Republic of China Included in the Sample Used in Cross-City Regressions (259 cities) 33 Abstract While openness to trade is a well-recognized hallmark of the Asian growth model, another component of the model is a leapfrogging strategy—the use of policies to guide industrial structural transformation ahead of a country's factor endowment. Does the leapfrogging strategy work? Opinions vary but the evidence is scarce in part because it is more difficult to measure the degree of leapfrogging than the extent of trade openness. We undertake a systematic look at the evidence both across countries and subregions within a large regional Asian economy to assess the efficacy of such a strategy. We conclude that there is no strong and robust evidence that this strategy works reliably. Keywords: growth, trade openness, leapfrogging JEL Classification: O20, O40 Does a Leapfrogging Growth Strategy Raise Growth Rate? Some International Evidence | 7 categories. We convert the OECD high-tech product list to 328 6-digit HS codes based on concordance between SITC (rev3) and HS (2002) published by the United Nations (UN) Statistical Division. To condense the US Census ATP list from 10-digit HS to 6-digit HS, we first calculate the ATP value share in both US imports from the world at the HS-6 level based on US trade statistics in 2006, bearing in mind that within each HS-6 heading some of the US HS-10 lines are considered to be ATP and others are not. We choose two separate cutoff points. For a narrow ATP definition, we select the 6-digit HS categories in which the ATP share is 100% of total US imports from the world according to the US Census ATP list, which resulted in 92 HS-6 lines. For a wider ATP definition, we select the 6-digit HS categories in which the ATP share is at least 25% of total US imports from the world, which resulted in 157 HS-6 lines. We use the 6-digit HS code in which all products are in the US Census ATP list and also in the OECD high-tech product list as our narrow definition of ATP. For a wider ATP definition, we deem an HS-6 line as ATP when either it is in the OECD high-tech product list or if at least 25% of its value is ATP products in US imports from the world according to the US Census ATP list. The recent literature also documents significant variations within the same product. Although both developed and developing countries may export products under the same 6-digit HS code, their unit value usually varies significantly, largely reflecting the difference in quality between their exports. To allow for the possibility that a very large difference in the unit values may signal different products (that are misclassified in the same 6-digit category), we take unit value for all products from Japan, the EU15, and the US (G3) in our narrow ATP definition as reference, and any products with a unit value below the G3 unit value minus five times standard deviation will not be counted as ATP. This results in our third definition of ATP. 2.2 Data and Basic Facts The EXPY measure requires data on trade flow and GDP per capita. We computed EXPY for both a short and long sample. For the short sample, dating from 1992 to 2006, the data on country exports come from the UN’s COMTRADE database, downloaded from WITS. The data from 1992 to 2006 is at the 6-digit HS level (1988/1992 version) covering 5,016 product categories and 167 countries. For the long sample, dating from 1962 to 2000, the trade flow data is taken from the National Bureau of Economic Research (NBER)-UN data compiled by Feenstra et al., which can be downloaded from the NBER website. The data is at the 4-digit SITC level, revision 2, covering 700–1000 product categories and 72 countries. The GDP per capita data on purchasing power parity (PPP) basis is taken from the Penn World Table. The modified EXPY measure requires additional data on unit value. The data were obtained from Ferrantino, Feinberg, and Deason (2008) and the UN’s COMTRADE database. The data is only for the year 2005 and is cleaned of products that lack welldefined quantity units and consistent reporting, and have a small value or a unit value belonging to the 2.5% tail of the distribution of the product’s unit values. In total, the resulting unit value dataset covers 3,628 6-digit HS subheadings. 8 | Working Paper Series on Regional Economic Integration No. 47 The other two export sophistication indices—EDI and ATP share (narrow, broad)—are computed excluding HS Chapters 1–27 (agricultural and mineral products) as well as raw materials and their simple transformations (mostly at the HS 4-digit level) in other HS chapters. A list of excluded products is reported in Appendix Table 1. Each country’s ATP exports’ share is computed by the country’s ATP exports divided by its total manufacturing exports. Our sample of countries is listed in Appendix Table 2. The other explanatory variables included in the growth regressions are human capital, GDP per capita, and institutional quality. The human capital variable in the cross country regressions uses the average school year in the Barro–Lee education database. GDP per capita is on a PPP basis and taken from the Penn World Table. The institutional quality variable is proxied by the government effectiveness index downloaded from the World Bank and Transparency International websites.3 Data on the PRC’s exports were obtained from the China Customs General Administration at the 8-digit HS level. The data report the geographic origin of exports (from more than 400 cities in the PRC), firm ownership, and transaction type (whether an export is related to processing trade as determined by customs declarations) for the period from 1996 through 2006. Each PRC city’s EDI is computed by the difference between a PRC city’s manufacturing export structure and the combined manufacturing export structure of G3 countries. Each PRC city’s ATP exports share is computed by dividing the city’s ATP exports by its total manufacturing exports. Similar to the crosscountry exports, we only consider manufactures. We link this database with a separate database on PRC cities—covering gross metropolitan product (GMP) per capita, population, percent of non-agricultural population in the total population, and college enrolment—downloaded from China Data Online, which is a site managed by the University of Michigan’s China Data Center. Unfortunately, the coverage of this second database is more limited (270 cities from 1996 through 2006), which effectively constrains the sample size used in our regression analyses. In these cities, only about 210 cities have complete records for 10 years or more. About 11 cities have records for only 3 years or less. Therefore, we deleted these 11 cities from the sample. There are also eight major cities that re-drew their administrative area during the sample period: Nanning, LiuZhou, Fuyang, Haikou, Chongqing, Kunming, Xinning, and Yinchuan. The total number of cities in our data set is 259 and these are listed in Appendix Table 3. Since we do not have data on the consumer price index (CPI) at the city level, we use provincial CPI to deflate cities in a particular province to obtain real GMP. The base year we chose is 2002. 3 http://www.worldbank.org/wbi/governance/govdata/ and http://ww1.transparency.org/surveys/index.html #cpi Does a Leapfrogging Growth Strategy Raise Growth Rate? Some International Evidence | 9 3. Do Leapfroggers Grow Faster? An Examination of the Evidence 3.1 The Elusive Growth Effect of a Leapfrogging Strategy Since Hausman et al. (2007) is the most recent and best known study providing an empirical foundation for the proposition that a leapfrogging strategy, as measured by a country’s export sophistication, delivers a faster economic growth rate, we start our statistical analysis by taking a careful look at their specifications and checking the robustness of their conclusion. In particular, we follow their econometric strategy, regressing economic growth rates across countries on a leapfrogging measure and including other control variables typically used in empirical growth studies. After replicating their regressions with EXPY as the leapfrogging proxy, we use the alternative measures discussed above—modified EXPY, EDI indicator, and the ATP shares. Table 1 shows our replication of the HHR’s cross-section regressions for the short sample 1992–2003, which corresponds to HHR’s Table 8. The controls include human capital and a measure of institutional quality. Since the source of their rule of law index is not clearly stated, we use four other well-known institutional variables: corruption, government effectiveness, regulation quality, and CPI. In the ordinary least squares (OLS) regressions, the coefficients for the first three institutional measures are significant. In particular, the coefficient for regulation quality (0.013) is close to HHR’s coefficient for their rule of law index (0.011). Columns 1, 2, 7, and 8 in Table 1 can be compared to the corresponding regression in HHR’s Table 8; the coefficients for the initial GDP per capita and human capital variables are basically the same as HHR’s. While the coefficients on log initial EXPY have different magnitudes than HHR’s results for the same sample period 1992–2003, they are all statistically significant (though not as strong, depending on the institution variable) and are positive as HHR’s. A possible explanation for this difference in the size of the coefficients is that trade data for the countries in the 1992–2003 sample has been revised since their usage. The bottom line from this replication exercise is that their results can be replicated. In the next step, we replace the EXPY variable with alternative measures of export sophistication—modified EXPY, EDI, and the ATP shares—and re-estimated the regressions. The results for each of these respective variables are displayed in Tables 2–5. In Table 2, the coefficient for the modified EXPY is statistically insignificant in all but the first specification with only human capital as control, even as the direction of the coefficients and significance on initial GDP per capita, human capital, and institutional variables remain the same as in Table 1. This observation extends to the case where either EDI or the broad definition of ATP is used as the export sophistication measure, as shown in Tables 3 and 4. However, the coefficient on the ATP share using a more stringent definition is positively significant across all specifications. We will show in the next section that even this result is not robust. To summarize, the positive association between a country’s export sophistication and economic growth rate is not a strong and robust pattern of the data. In particular, alternative measures of export sophistication often produce statistically insignificant 10 | Working Paper Series on Regional Economic Integration No. 47 coefficients. For example, a reasonable adjustment to the HHR measure of sophistication that accounts for possible differences in unit values when computing the implied income in an export bundle would cause the positive association to disappear. Therefore, we infer that that it may be too early to conclude that pursuing a leapfrogging strategy would accelerate a country’s growth rate. 4. Further Investigations 4.1 Does Growth in Sophistication Lead to Growth in Income? It is possible that the level of a country’s export sophistication may not successfully capture policy incentives or other government actions. In particular, if a country happens to have an unusually large pool of scientists and engineers, its level of export sophistication may surpass what can be predicted based on its income or endowment. A useful empirical strategy is to look at the growth of a country’s export sophistication. Holding constant the initial levels of export sophistication, would those countries that have an unusually fast increase in sophistication also have an unusually high rate of economic growth? In Table 6, we rank the 49 countries in our sample by descending order in terms of the growth of export sophistication. As a smell test, we pay particular attention to the rankings for Ireland and the PRC using this metric since both countries are often viewed as practical examples of extensive government programs used to promote industrial transformation toward high-tech industries. All five measures are able to capture the PRC as having experienced a high level of change in its export sophistication. But only the modified EXPY variable is able to capture both the PRC and Ireland as having undergone a significant change in export sophistication during the period. This further strengthens our confidence in the relative adequacy of the modified EXPY against the original EXPY in capturing leapfrogging in industrial structure. Table 7 displays the regression results with this specification for all five export sophistication measures and their changes over the period 1992–2003. The initial GDP level, human capital, and institutional variable all have the correct signs. None of the export sophistication growth variables enters significantly into the regression. But the most conspicuous observation involves the initial export sophistication measures: all but the EXPY variable are insignificant with this specification. In contrast to the previous specification, the ATP share is no longer significant either. This once again shows that when export sophistication is constructed in alternative ways, it no longer indicates significant impact on growth. To summarize, these results raise skepticism of the view that leapfrogging leads to higher growth. Does a Leapfrogging Growth Strategy Raise Growth Rate? Some International Evidence | 11 4.2 Non-normality and Non-linearity If the effect of leapfrog policies is not linear on log productivity, a potential omission bias will occur. Rodriguez (2007) shows that a linear regression of a nonlinear data generation process will only produce an average policy effect if the data generating process of the policy variable —in other words, the leapfrogging measure —is distributed according to a normal distribution. We, therefore, test the normality of leapfrogs. Observe that export sophistication can be decomposed into a function of factor endowments, leapfrog policies, and other factors: Export sophistication = f(factor endowments, leapfrog policies, other factors). The growth regression specification is: ititit itititit nInstitutioHumanCap ExpSophisGDPc=GDPcGDPc       1413 121101 LnLnLn (9) The interpretation of α2 can be taken as the average impact of leapfrogging policies since it represents the variation on export sophistication that is unexplained by human capital, institutional variable, and the initial level of development, all three of which are already included as covariates in the regression.. These covariates successfully capture the factor endowment and other factor aspects of export sophistication. We reformulate the procedure to isolate the part of export sophistication that is not attributable to factor endowment and other factors as leapfrog policies.4 Stage 1: Isolate the variation due to leapfrogging. We interpret εi as the portion of export sophistication attributable to a government’s leapfrog policy: ititititit nInstitutioHumanCapGDPc=ExpSophis   3210 Ln (10) Stage 2: Growth regression itititit GDPcGDPc    11 LnLn (11) γ is interpreted as the impact of leapfrogging on growth. It is the equivalent of α2 estimated from equation (1). We then set out to test the normality of the leapfrog variable. Table 8 displays the results from the Shapiro-Wilk and skewness/kurtosis tests of normality of variables. Normality in the distribution of EXPY and the ATP share variables would be comfortably rejected in both tests. On the other hand, the modified EXPY and EDI passed the normality test. We take away two messages from this exercise: (i) a linear regression may not give a meaningful interpretation for the EXPY coefficient, even if it otherwise correctly captures the degree of leapfrogging; and (ii) the modified EXPY appears to be a better regressor to use in the linear model from a pure statistical sense. 4 The results from the normality test would be the same regardless of whether one used the isolated leapfrog variables or the export sophistication variables. We reformulate the variable here for clarity. 12 | Working Paper Series on Regional Economic Integration No. 47 4.3 Panel Regressions with Instrumental Variables The cross section regressions assume that productivity growth is the same for all countries except for the differences in their respective leapfrog policies. As an extension that relaxes this assumption, we turn to a panel analysis with separate country-fixed effects. New challenges emerge with the panel analysis as one has to deal with shorter time intervals and must have instrumental variables with meaningful time series variations. We propose to use the professional background and educational preparedness of political leaders as variables that may affect their choice of economic strategy. Dreher, Lamla, Lein, and Somogyi (2008) constructed a database of the profession and education for more than 500 political leaders from 73 countries for the period 1970– 2002. One set of dummies codify the educational background for the chief executives: law, economics, politics, natural science, and other. Another set of dummies codify the professions of the chief executives before they take office: entrepreneur, white collar, blue collar, union executive, science, economics, law, military, politics, and others. We use this set of variables as instruments for export sophistication. Table 9 shows the growth regression results for the long sample of 1970–2000 when using EXPY and EDI as measures of export sophistication. Unfortunately, we cannot use the ATP shares as they are not available for the early years of the sample period. Panel A shows the results for using EXPY as export sophistication. To compare with the analysis in Hausman et al., our sample starts a few years later (as opposed to 1962), yet our OLS estimation closely replicates their estimates: (i) the coefficient for initial GDP per capita is negative and significant at –0.001, (ii) the coefficient for initial EXPY is positive and significant at 0.02, and (iii) the coefficient for human capital is positive and significant at 0.01. In the fixed effects and IV specifications, neither of the coefficients for initial EXPY is significant, despite the improved Hansen-J statistics and our set of instruments. The R-squared of our regression for the OLS case is more than twice as large as the R-squared from the Hausman et al. study, despite the similarities in the estimates. Panel B shows the results for the same regression, but replacing EXPY with EDI. None of the export sophistication variables are significant, while the initial GDP per capita and human capital variables are both significant. We conclude that in the panel regressions, there is no strong and robust support for the notion that a leapfrogging strategy promotes growth. 5. Comparing Cross-Regional Variations within a Single Country Cross-country analyses could suffer from a serious omitted variable bias as countries differ in history, culture, legal systems, governance institutions, among myriad other factors. There are always some such variables that are not properly controlled for in cross-country regressions. If none of these variables were time-varying, then fixed effects in a panel regression would take care of them. If some of these variables were time-varying (and correlated with the export sophistication measures), then we cannot obtain a consistent estimate of the true effect of a leapfrogging strategy. Assuming these Does a Leapfrogging Growth Strategy Raise Growth Rate? Some International Evidence | 13 omitted country-level variables can be plausibly held constant within a country, one solution to this problem is to explore cross-regional variations within a single country. In our context, regions have to differ in their pursuit of a leapfrogging policy and the country has to be relatively large so that enough statistical power is available from a crossregional analysis. In this section, we conduct such an analysis across cities in the PRC. Specifically, at the city level, we compute the same set of export sophistication measures as before. In addition, we pay attention to the role of the processing trade and imported ATP inputs, which could not be included in a cross-country analysis. Recent international trade literature (Koopman, Wang, and Wei, 2008; Dean, Fung, and Wang, 2009; De La Cruz et al., 2009) provide evidence that export sophistication in developing countries such as the PRC and Mexico can be explained in large part by vertical specialization and global production fragmentation. The two ratios of ATP imports over ATP exports in a city provide a very rough lower and higher bound for a proxy measure of the foreign content embodied in a PRC city's total ATP exports, which may contribute directly to the sophistication of a city's exports. By comparing the values of export sophistication measures against per capita GMP, we can infer which cities may be more aggressive in upgrading their economic structure (beyond their income level alone). The cities of Wuxi, Zhuhai, and Tianjian can be identified as having been ahead of other cities in 1996 in terms of exporting advanced technological goods. By 2006, Shenzhen, Xiamen, Dongguan, Shanghai, and Guangzhou were among the cities that had risen according to the leapfrog measure. How sensible is this leapfrog measure in identifying cities where the local government installed favorable industrial policies? All the aforementioned cities and other cities that had experienced a rise in their leapfrog measure, with the exception of Dongguan, were established as export processing zones between 2001 and 2002, and high-technology industry development areas between 1996 to 1997.5 Overall, the leapfrog measures seem to be consistent with regional variations in public sector policies in favor of hightech industries in local economies. We now turn to a formal regression analysis.6 The results are reported in Table 10. Most coefficients for export sophistication measures are not statistically significant, with the exception of the ATP (narrow) share and the modified EXPY. However, the coefficient for the modified EXPY is negative. In other words, if a leapfrogging strategy has an effect on local growth, the effect is negative. In any case, the significance of the modified EXPY variable disappears after adding the leapfrog growth as a covariate. 5 Wang and Wei (2008) report the years of establishment of economic zones (e.g., special economic zone [SEZ], economic and technology development area, high-tech industry development area, export processing zone) in the PRC in their Appendix Table 2. 6 Eight major cities redrew their administrative area during the sample period. They are Nanning, LiuZhou, Fuyang, Haikou, Chongqing, Kunming, Xinning, and Yinchuan. Thus, we also re-estimated the regressions to include the interaction of these eight cities with the export sophistication variable on the right-hand side. But the general results did not change. 14 | Working Paper Series on Regional Economic Integration No. 47 For both sets of regressions, there is no clear evidence of a conditional convergence, unlike the cross-country analyses reported in the earlier sections. The variation in growth across cities that can be explained is low. The R-squared ranges from 0.04 to 0.06 in Table 10. The Shapiro-Wilk tests of normality for the export sophistication measures reject normality for all of them, suggesting that some non-linearity is likely present in the data generating process. We also supplemented the cross section results with panel analysis for the period 1996–2005, sampling 3 years for each city and reporting the results in Table 11. The coefficients for the six leapfrog policy variables across three regression specifications are insignificant except for one specification for EXPY and the IV specification for EDI. To summarize, there is no strong case supporting a robust and positive causal effect of leapfrogging on economic growth across cities in the PRC. 6. Conclusion To be able to transform an economy’s economic structure ahead of its income level toward higher domestic value-added and more sophisticated sectors is desirable in the abstract. Many governments have pursued policies to bring about such transformations. To be sure, there are examples of individual success cases, including the promotion of a certain industry by government policies resulting in an expansion of that industry. However, any such policy promotion takes away resources from other industries, especially those that are consistent with the country’s factor endowment and level of development. On balance, the effect is conceptually less clear. Given the popularity of such leapfrogging strategies, it is important to evaluate empirically whether or not they are effective. Unfortunately, such an evaluation is difficult because it is not a straightforward process to quantify the degree of leapfrogging an economy may exhibit. Typical data on production structures are not refined enough and most relevant policies are not easily quantifiable or comparable across countries. One way to gauge the degree of leapfrogging is by inferring from a country’s detailed export data. This paper pursues such a strategy and develops a number of different ways to measure leapfrogging from revealed sophistication in a country’s exports, recognizing that any particular measure may have both advantages and shortcomings. After a whole battery of analyses, a succinct summary of our findings is that there is a lack of strong and robust support for the notion that a leapfrogging industrial policy can reliably raise economic growth. Again, there may be individual success stories. But there are also failures. If leapfrogging is a policy gamble, there is no systematic evidence to suggest that the odds for success are favorable. We conclude by noting once again two distinct aspects of a growth model that embraces the world market. The first aspect is export orientation—an investment environment with few policy impediments to firms participating in international trade. While this paper does not reproduce the vast quantity of analysis on this, we do not doubt its validity. The second aspect is a leapfrogging strategy—the use of policy instruments to engineer a more rapid industrial transformation than what might emerge naturally based on an economy’s stage of development and factor endowment. Our empirical findings have cast some doubt on the effectiveness of such strategies. Does a Leapfrogging Growth Strategy Raise Growth Rate? Some International Evidence | 15 References J. Dean, K.C. Fung, and Z. Wang. 2008. How Vertically Specialized is Chinese Trade? 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The life and death implications of globalization. IMF Working Paper. Does a Leapfrogging Growth Strategy Raise Growth Rate? Some International Evidence | 23 Ranking Country EXPY Country Modified EXPY Country ATP (narrow) Country ATP (broad) Country EDI 27 Switzerland 0.65 Australia 1.06 Algeria 0.04 Bolivia 0.14 Cyprus -0.46 28 Australia 0.63 India 1.06 Saudi Arabia 0.03 Algeria 0.14 Japan -0.43 29 New Zealand 0.54 Netherlands 1.04 Paraguay 0.03 Saudi Arabia 0.10 Tunisia -0.42 30 Oman 0.52 Switzerland 0.98 Ecuador 0.03 Turkey 0.08 South Africa -0.40 31 Ireland 0.31 Finland 0.93 Peru 0.01 Chile 0.05 Croatia -0.39 32 Brazil 0.27 Denmark 0.91 Chile 0.01 Spain 0.03 Sri Lanka -0.37 33 Tunisia 0.27 Bolivia 0.88 Turkey 0.01 Peru 0.02 Canada -0.36 34 Denmark 0.27 Paraguay 0.80 Bangladesh 0.00 Japan 0.02 Peru -0.31 35 Japan 0.25 Spain 0.67 South Africa 0.00 Bangladesh 0.01 Singapore -0.25 36 Sweden 0.25 Peru 0.66 Belize 0.00 Belize 0.01 Bolivia -0.22 37 Netherlands 0.20 Brazil 0.24 Trinidad and Tobago 0.00 Trinidad and Tobago 0.00 Algeria -0.07 38 St. Lucia 0.20 Japan 0.24 Brunei Darussalam 0.00 Canada 0.00 Brunei Darussalam -0.01 39 Spain 0.20 Sweden 0.17 Jamaica 0.00 Brunei Darussalam 0.00 Bangladesh -0.01 40 Canada 0.17 Algeria 0.11 Spain -0.01 Jamaica -0.01 Netherlands 0.00 41 Chile 0.07 Chile 0.09 Japan -0.01 Ecuador -0.02 Chile 0.00 42 Algeria 0.01 Macao -0.22 Colombia -0.02 Madagascar -0.02 Switzerland 0.01 43 Brunei Darussalam -0.03 Canada -0.37 Madagascar -0.02 Sri Lanka -0.03 Belize 0.02 44 Saudi Arabia -0.07 Belize -0.42 Brazil -0.03 Cyprus -0.05 Trinidad and Tobago 0.04 45 Jamaica -0.25 Saudi Arabia -0.50 Sri Lanka -0.04 Colombia -0.05 Finland 0.11 46 Macao -0.40 Oman -0.51 Macao -0.06 Ireland -0.08 Madagascar 0.14 47 Romania -0.68 Romania -0.91 Ireland -0.15 South Africa -0.10 Jamaica 0.16 48 Peru -0.84 Trinidad and Tobago -2.74 Canada -0.24 Macao -0.13 Ireland 0.34 49 Belize -1.09 Jamaica -3.17 Oman -0.25 Oman -0.23 Macao 0.48 24 | Working Paper Series on Regional Economic Integration No. 47 Table 7: Cross National Growth Regression, with Growth in Export Sophistication Dependent variable: growth in real GDP per capita, 1992–2003 (1) (2) (3) (4) (5) Log initial GDP per capita -0.028 -0.02 -0.02 -0.02 -0.02 [0.005]** [0.005]** [0.005]** [0.005]** [0.005]** Human Capital 0.016 0.021 0.022 0.019 0.023 [0.010] [0.011] [0.010]* [0.010] [0.011] Regulation quality 0.018 0.015 0.015 0.016 0.018 [0.006]** [0.007]* [0.006]* [0.006]* [0.007]* Log initial EXPY 0.032 [0.009]** Growth in log EXPY 0.252 [0.240] Log initial modified EXPY 0.005 [0.005] Growth in log modified EXPY 0.081 [0.153] initial ATP share (narrow) 0.04 [0.031] Growth in ATP share (narrow) 0.891 [0.567] initial ATP share (broad) 0.026 [0.023] Growth in ATP share (broad) 0.731 [0.388] initial log EDI -0.001 [0.015] Growth in log EDI -0.003 [0.407] Constant -0.06 0.12 0.16 0.162 0.17 [0.070] [0.052]* [0.033]** [0.033]** [0.095] Observations 41 41 41 41 39 R-squared 0.51 0.36 0.44 0.43 0.33 Robust standard errors in brackets; * significant at 5%; ** significant at 1%. Does a Leapfrogging Growth Strategy Raise Growth Rate? Some International Evidence | 25 Table 8: Test for Normality Shapiro–Wilk W Test for Normal Data Variable Obs W V z Prob>z log EXPY 42.00 0.94 2.41 1.86 0.03 log Modified EXPY 42.00 0.96 1.47 0.81 0.21 ATP (narrow) 42.00 0.76 9.86 4.83 0.00 ATP (broad) 42.00 0.87 5.34 3.53 0.00 log ATP 41.00 0.99 0.59 -1.13 0.87 Skewness/Kurtosis Tests for Normality Variable Pr(Skewness) Pr(Kurtosis) adj chi2(2) Prob>chi2 log EXPY 0.028 0.192 6.09 0.0475 log Modified EXPY 0.131 0.894 2.44 0.2946 ATP (narrow) 0 0.004 19.43 0.0001 ATP (broad) 0.001 0.074 11.16 0.0038 log ATP 0.491 0.926 0.5 0.78 26 | Working Paper Series on Regional Economic Integration No. 47 Table 9: Long Sample, Panel Regressions with Fixed Effects A. EXPY 5-year panels (1) (2) (3) OLS FE IV log initial GDP/cap -0.0103 -0.0479 -0.0113 [0.0027]** [0.0060]** [0.0104] log initial EXPY 0.0208 0.0027 0.0223 [0.0055]** [0.0091] [0.0423] log human capital 0.0116 -0.0102 0.0088 [0.0027]** [0.0065] [0.0078] Constant -0.059 0.3688 -0.0573 [0.0379] [0.0788]** [0.3033] Observations 640 640 369 R-squared 0.39 0.47 First stage F stat 1.35 Hansen J-statistics (p-value) 0.186 B. EDI 5-year panels (1) (2) (3) OLS FE IV log initial GDP/cap -0.0065 -0.0517 -0.0097 [0.0026]* [0.0062]** [0.0054] Initial log EDI -0.0117 0.004 -0.0271 [0.0071] [0.0191] [0.0180] log human capital 0.0128 -0.0256 0.0081 [0.0030]** [0.0079]** [0.0041]* Constant 0.1555 0.4266 0.2709 [0.0473]** [0.1136]** [0.1222]* Observations 475 475 314 R-squared 0.43 0.59 First stage F stat 3.08 Hansen J-statistics (p-value) 0.089 * Significant at 5%; ** significant at 1%; robust standard errors in brackets; instruments are the professions and educational background of political leaders from Dreher, Lamla, Lein, and Somogyi (2008). Does a Leapfrogging Growth Strategy Raise Growth Rate? Some International Evidence | 27 Table 10: Cross-Section Growth Regressions, Cities in the People’s Republic of China (1997–2006) Dependent variable: growth rate over 1997–2006 (1) (2) (4) (6) (8) (10) OLS OLS OLS OLS OLS OLS log initial GDP/cap 0.0089 0.0095 0.0103 0.0096 0.0094 0.0065 [0.0050] [0.0051] [0.0049]* [0.0051] [0.0050] [0.0057] initial Human Capital 0.1505 0.1372 0.153 0.135 0.1624 0.1045 [0.1501] [0.1484] [0.1489] [0.1488] [0.1468] [0.1528] SEZdummy -0.0053 -0.0046 -0.0028 -0.0039 -0.0036 -0.0068 [0.0080] [0.0079] [0.0079] [0.0081] [0.0078] [0.0089] log initial ATP share (narrow) 0.0549 [0.0215]* log initial ATP share (broad) 0.0103 [0.0158] log initial ATP share (G3) -0.0354 [0.0248] log initial EXPY -0.0073 [0.0077] log initial modified EXPY -0.0084 [0.0030]** log initial EDI -0.0556 [0.0623] Constant 0.0257 0.0197 0.0145 0.0867 0.0972 0.339 [0.0426] [0.0434] [0.0418] [0.0845] [0.0536] [0.3527] Observations 209 209 208 208 208 208 R-squared 0.04 0.04 0.06 0.04 0.06 0.04 Robust standard errors in brackets; * significant at 5%; ** significant at 1%. 28 | Working Paper Series on Regional Economic Integration No. 47 Table 11: Panel Growth Regressions, Cities in the People’s Republic of China (1996–2005) 3-year panels (1) (2) (3) (4) (5) (6) (7) (8) (9) OLS FE IV OLS FE IV OLS FE IV log initial GDP/cap 0.0042 -0.2007 0.0337 0.0044 -0.2013 -0.0004 0.0038 -0.2038 0.0107 [0.0049] [0.0228]** [0.0205] [0.0048] [0.0227]** [0.0064] [0.0049] [0.0227]** [0.0187] human capital 0.0373 0.0316 -0.5121 0.0415 0.0363 0.0952 0.0477 0.0374 -0.951 [0.1240] [0.1947] [0.3847] [0.1228] [0.1946] [0.1271] [0.1231] [0.1946] [1.4628] initial ATP (narrow) -0.0158 -0.0426 -1.5058 [0.0325] [0.0733] [0.9376] initial ATP (broad) -0.0188 -0.0096 0.113 [0.0160] [0.0225] [0.1406] initial ATP (G3) -0.0036 0.0041 0.777 [0.0022] [0.0037] [1.1354] Constant 0.0653 1.972 -0.1181 0.0644 1.9778 0.1432 0.0681 1.9997 0.0224 [0.0424] [0.2051]** [0.1616] [0.0419] [0.2047]** [0.0532]** [0.0428] [0.2043]** [0.1673] Observations 662 662 662 662 662 662 661 661 661 R-squared 0.32 0.55 0.32 0.55 0.32 0.55 Number of id 256 256 256 Hansen J (p-value) 0.307 0.05 0.855 Does a Leapfrogging Growth Strategy Raise Growth Rate? Some International Evidence | 29 3-year panels (10) (11) (12) (13) (14) (15) (16) (17) (18) OLS FE IV OLS FE IV OLS FE IV log initial GDP/cap 0.004 -0.2072 0.0075 0.0044 -0.2056 0.0068 0.0022 -0.2019 0.044 [0.0049] [0.0226]** [0.0089] [0.0049] [0.0227]** [0.0055] [0.0058] [0.0231]** [0.0213]* human capital 0.0431 0.0418 0.0865 0.066 0.051 0.1945 0.0292 0.0368 0.3632 [0.1231] [0.1937] [0.1218] [0.1211] [0.1946] [0.1468] [0.1282] [0.1960] [0.2083] initial log EXPY -0.0028 0.0343 -0.1094 [0.0117] [0.0151]* [0.1574] initial log Modified EXPY -0.008 0.0086 -0.0482 [0.0041] [0.0055] [0.0260] initial log EDI -0.0307 0.0116 0.7304 [0.0531] [0.1680] [0.3678]* Constant 0.0928 1.71 1.0948 0.1353 1.9377 0.5175 0.2439 1.9219 -4.0894 [0.1205] [0.2362]** [1.3989] [0.0615]* [0.2059]** [0.2194]* [0.3080] [0.9396]* [2.1198] Observations 661 661 661 661 661 661 661 661 661 R-squared 0.32 0.56 0.33 0.55 0.32 0.55 Number of id 256 256 256 Hansen J (p-value) 0.048 0.289 0.516 All regressions include time dummies and special economic zone (SEZ) dummies. Standard errors are in brackets. The instruments are log(land) and log(population); * significant at 5%; ** significant at 1%. 30 | Working Paper Series on Regional Economic Integration No. 47 Appendix Table 1: HS Products Excluded from Export Data HS Code Description HS Code Description 01-24 Agricultural products 25-27 Mineral products 4103 Other raw hides and skins (fresh, o 8002 Tin waste and scrap. 4104 Tanned or crust hides and skins of 8101 Tungsten (wolfram) and articles the 4105 Tanned or crust skins of sheep or l 8102 Molybdenum and articles thereof, in 4106 Tanned or crust hides and skins of 8103 Tantalum and articles thereof, incl 4402 Wood charcoal (including shell or n 8104 Magnesium and articles thereof, inc 4403 Wood in the rough, whether or not s 8105 Cobalt mattes and other intermediate 7201 Pig iron and spiegeleisen in pigs, 8106 Bismuth and articles thereof, incl 7202 Ferro-alloys. 8107 Cadmium and articles thereof, incl 7204 Ferrous waste and scrap; re-melting 8108 Titanium and articles thereof, incl 7404 Copper waste and scrap. 8109 Zirconium and articles thereof, inc 7501 Nickel mattes, nickel oxide sinters 8110 Antimony and articles thereof, incl 7502 Unwrought nickel. 8111 Manganese and articles thereof, inc 7503 Nickel waste and scrap. 8112 Beryllium, chromium, germanium, van 7601 Unwrought aluminum. 8113 Cermets and articles thereof, incl 7602 Aluminum waste and scrap. 9701 Paintings, drawings and pastels, ex 7801 Unwrought lead. 9702 Original engravings, prints and lit 7802 Lead waste and scrap. 9703 Original sculptures and statuary, i 7901 Unwrought zinc. 9704 Postage or revenue stamps, stamp-po 7902 Zinc waste and scrap. 9705 Collections and collectors' pieces 8001 Unwrought tin. 9706 Antiques of an age exceeding one hundred years 530521 Coconut, abaca (Manila hemp or Musa 811252 Beryllium, chromium, germanium, van Does a Leapfrogging Growth Strategy Raise Growth Rate? Some International Evidence | 31 Appendix Table 2: Countries (165) Included in the Sample Used in Cross Country Regression Code Reporting Country No. Year reported Code Reporting Country No. Year reported Code Reporting Country No. Year reported ABW Aruba 5 GBR United Kingdom 14 NCL New Caledonia 8 AIA Anguilla 6 GEO Georgia 11 NER Niger 11 ALB Albania 11 GHA Ghana 10 NGA Nigeria 8 AND Andorra 12 GIN Guinea 8 NIC Nicaragua 14 ARG Argentina 14 GMB Gambia, The 12 NLD Netherlands 15 ARM Armenia 9 GRC Greece 15 NOR Norway 14 AUS Australia 15 GRD Grenada 14 NPL Nepal 5 AUT Austria 13 GRL Greenland 13 NZL New Zealand 15 AZE Azerbaijan 11 GTM Guatemala 14 OMN Oman 15 BDI Burundi 14 GUY Guyana 10 PAK Pakistan 4 BEL Belgium 8 HKG Hong Kong, China 14 PAN Panama 12 BEN Benin 8 HND Honduras 13 PER Peru 14 BFA Burkina Faso 10 HRV Croatia 15 PHL Philippines 11 BGD Bangladesh 12 HTI Haiti 6 PNG Papua New Guinea 6 BGR Bulgaria 11 HUN Hungary 15 POL Poland 13 BHR Bahrain 7 IDN Indonesia 15 PRT Portugal 15 BHS Bahamas, The 6 IND India 15 PRY Paraguay 15 BIH Bosnia and Herzegovina 4 IRL Ireland 15 PYF French Polynesia 11 BLR Belarus 9 IRN Iran, Islamic Republic of 10 QAT Qatar 7 BLZ Belize 15 ISL Iceland 15 ROM Romania 15 BOL Bolivia 15 ISR Israel 12 RUS Russian Federation 11 BRA Brazil 15 ITA Italy 13 RWA Rwanda 10 BRB Barbados 10 JAM Jamaica 13 SAU Saudi Arabia 14 BRN Brunei Darussalam 9 JOR Jordan 12 SDN Sudan 12 BTN Bhutan 4 JPN Japan 15 SEN Senegal 11 BWA Botswana 7 KAZ Kazakhstan 7 SER Yugoslavia 11 CAF Central African 13 KEN Kenya 11 SGP Singapore 15 32 | Working Paper Series on Regional Economic Integration No. 47 Code Reporting Country No. Year reported Code Reporting Country No. Year reported Code Reporting Country No. Year reported Republic CAN Canada 15 KGZ Kyrgyz Republic 9 SLV El Salvador 13 CHE Switzerland 15 KHM Cambodia 5 STP Sao Tome and Principe 8 CHL Chile 15 KIR Kiribati 6 SUR Suriname 6 CHN PRC 15 KNA St. Kitts and Nevis 13 SVK Slovak Republic 13 CIV Cote d'Ivoire 12 KOR Korea, Rep. of 15 SVN Slovenia 13 CMR Cameroon 10 LBN Lebanon 8 SWE Sweden 15 COK Cook Islands 4 LCA St. Lucia 15 SWZ Swaziland 6 COL Colombia 15 LKA Sri Lanka 9 SYC Seychelles 11 COM Comoros 10 LSO Lesotho 5 SYR Syrian Arab Republic 6 CPV Cape Verde 10 LTU Lithuania 13 TCA Turks and Caicos Isl. 6 CRI Costa Rica 13 LUX Luxembourg 8 TGO Togo 12 CUB Cuba 8 LVA Latvia 13 THA Thailand 15 CYP Cyprus 15 MAC Macau, China 14 TTO Trinidad and Tobago 15 CZE Czech Republic 14 MAR Morocco 14 TUN Tunisia 15 DEU Germany 15 MDA Moldova 11 TUR Turkey 15 DMA Dominica 13 MDG Madagascar 15 TWN Taipei,China 10 DNK Denmark 15 MDV Maldives 12 TZA Tanzania 10 DZA Algeria 15 MEX Mexico 15 UGA Uganda 13 ECU Ecuador 15 MKD Macedonia, FYR 13 UKR Ukraine 11 EGY Egypt 13 MLI Mali 11 URY Uruguay 13 ESP Spain 15 MLT Malta 13 USA United States 15 EST Estonia 12 MNG Mongolia 11 VCT St. Vincent and the Grena 14 ETH Ethiopia (excludes Eritrea) 11 MOZ Mozambique 7 VEN Venezuela 13 FIN Finland 15 MSR Montserrat 8 VNM Viet Nam 6 FJI Fiji 6 MUS Mauritius 14 WSM Samoa 5 FRA France 13 MWI Malawi 13 ZAF South Africa 15 FRO Faeroe Islands 11 MYS Malaysia 15 ZMB Zambia 12 GAB Gabon 13 NAM Namibia 7 ZWE Zimbabwe 6 39 | Working Paper Series on Regional Economic Integration No. 47 17. "Real and Financial Integration in East Asia" by Soyoung Kim and Jong-Wha Lee 18. ―Global Financial Turmoil: Impact and Challenges for Asia’s Financial Systems‖ by Jong-Wha Lee and Cyn-Young Park 19. ―Cambodia’s Persistent Dollarization: Causes and Policy Options‖ by Jayant Menon 20. "Welfare Implications of International Financial Integration" by Jong-Wha Lee and Kwanho Shin 21. "Is the ASEAN-Korea Free Trade Area (AKFTA) an Optimal Free Trade Area?" by Donghyun Park, Innwon Park, and Gemma Esther B. Estrada 22. "India’s Bond Market—Developments and Challenges Ahead" by Stephen Wells and Lotte SchouZibell 23. ―Commodity Prices and Monetary Policy in Emerging East Asia‖ by Hsiao Chink Tang 24. "Does Trade Integration Contribute to Peace?" by Jong-Wha Lee and Ju Hyun Pyun 25. ―Aging in Asia: Trends, Impacts, and Responses‖ by Jayant Menon and Anna Melendez-Nakamura 26. ―Re-considering Asian Financial Regionalism in the 1990s‖ by Shintaro Hamanaka 27. ―Managing Success in Viet Nam: Macroeconomic Consequences of Large Capital Inflows with Limited Policy Tools‖ by Jayant Menon 28. ―The Building Block versus Stumbling Block Debate of Regionalism: From the Perspective of Service Trade Liberalization in Asia‖ by Shintaro Hamanaka 29. ―East Asian and European Economic Integration: A Comparative Analysis‖ by Giovanni Capannelli and Carlo Filippini 30. ―Promoting Trade and Investment in India’s Northeastern Region‖ by M. Govinda Rao 31. "Emerging Asia: Decoupling or Recoupling" by Soyoung Kim, Jong-Wha Lee, and Cyn-Young Park 32. ―India’s Role in South Asia Trade and Investment Integration‖ by Rajiv Kumar and Manjeeta Singh 33. ―Developing Indicators for Regional Economic Integration and Cooperation‖ by Giovanni Capannelli, Jong-Wha Lee, and Peter Petri 34. ―Beyond the Crisis: Financial Regulatory Reform in Emerging Asia‖ by Chee Sung Lee and Cyn-Young Park Does a Leapfrogging Growth Strategy Raise Growth Rate? Some International Evidence | 40 35. "Regional Economic Impacts of Cross-Border Infrastructure: A General Equilibrium Application to Thailand and Lao PDR" by Peter Warr, Jayant Menon, and Arief Anshory Yusuf 36. "Exchange Rate Regimes in the Asia-Pacific Region and the Global Financial Crisis" by Warwick J. McKibbin and Waranya Pim Chanthapun 37. ―Roads for Asian Integration: Measuring ADB's Contribution to the Asian Highway Network‖ by Srinivasa Madhur, Ganeshan Wignaraja,and Peter Darjes 38. "The Financial Crisis and Money Markets in Emerging Asia" by Robert Rigg and Lotte Schou-Zibell 39. ―Complements or Substitutes? Preferential and Multilateral Trade Liberalization at the Sectoral Level‖ by Mitsuyo Ando, Antoni Estevadeordal, and Christian Volpe Martincus 40. ―Regulatory Reforms for Improving the Business Environment in Selected Asian Economies—How Monitoring and Comparative Benchmarking can Provide Incentive for Reform‖ by Lotte Schou-Zibell and Srinivasa Madhur 41. ―Global Production Sharing, Trade Patterns, and Determinants of Trade Flows in East Asia‖ by Prema–Chandra Athukorala and Jayant Menon 42. ―Regionalism Cycle in Asia (-Pacific): A Game Theory Approach to the Rise and Fall of Asian Regional Institutions‖ by Shintaro Hamanaka 43. ―A Macroprudential Framework for Monitoring and Examining Financial Soundness‖ by Lotte Schou-Zibell, Jose Ramon Albert, and Lei Lei Song 44. ―A Macroprudential Framework for the Early Detection of Banking Problems in Emerging Economies‖ by Claudio Loser, Miguel Kiguel, and David Mermelstein 45. ―The 2008 Financial Crisis and Potential Output in Asia: Impact and Policy Implications‖ by Cyn-Young Park, Ruperto Majuca, and Josef Yap 46. ―Do Hub-and-Spoke Free Trade Agreements Increase Trade? A Panel Data Analysis‖ by Joseph Alba, Jung Hur, and Donghyun Park * These papers can be downloaded from: (ARIC) http://aric.adb.org/reipapers/ or (ADB) www.adb.org/publications/category.asp?id=2805 Does a Leapfrogging Growth Strategy Raise Growth Rate? Some International Evidence In this paper, Zhi Wang, Shang-Jin Wei, and Anna Wong test the leapfrogging strategy— the use of government policies to promote high-tech and high-domestic-value-added industries beyond an economy’s natural development—on 165 countries and 259 cities in the People’s Republic of China. They find no evidence that the strategy contributes to higher growth. About the Asian Development Bank ADB’s vision is an Asia and Pacific region free of poverty. Its mission is to help its developing member countries substantially reduce poverty and improve the quality of life of their people. Despite the region’s many successes, it remains home to two-thirds of the world’s poor: 1.8 billion people who live on less than $2 a day, with 903 million struggling on less than $1.25 a day. ADB is committed to reducing poverty through inclusive economic growth, environmentally sustainable growth, and regional integration. Based in Manila, ADB is owned by 67 members, including 48 from the region. Its main instruments for helping its developing member countries are policy dialogue, loans, equity investments, guarantees, grants, and technical assistance. Asian Development Bank 6 ADB Avenue, Mandaluyong City 1550 Metro Manila, Philippines www.adb.org/poverty Publication Stock No. Printed in the Philippines