metadata: authors: 0: author: Bulman, David
1: author: Eden, Maya
2: author: Nguyen, Ha
count: World
docna: 0: docna: Transitioning from low-income growth to
            high-income growth : is there a middle income trap ?
docty: Policy Research Working Paper
theme: Analysis of economic growth
majtheme: Economic management
subtopic: Social Policy,Legal Products,Real & Intellectual Property Law,Judicial System Reform,Common Property Resource Development,Tertiary Education,International Trade and Trade Rules,Food Security,Inflation,Legal Reform,Legislation,Regulatory Regimes,Intellectual Property Rights
teratopic: Science and Technology Development,Macroeconomics and Economic Growth,Governance,Industry
abstracts: cdata!: Is there a "middle income
            trap"? Theory suggests that the determinants of growth
            at low and high income levels may be different. If countries
            struggle to transition from growth strategies that are
            effective at low income levels to growth strategies that are
            effective at high income levels, they may stagnate at some
            middle income level; this phenomenon can be thought of as a
            "middle income trap." This paper does not find
            evidence for (unusual) stagnation at any particular middle
            income level. However, it does find evidence that the
            determinants of growth at low and high income levels differ.
            These findings suggest a mixed conclusion: middle-income
            countries may need to change growth strategies to transition
            smoothly to high-income growth strategies, but this can be
            done smoothly and does not imply the existence of a middle
            income trap.
repnme: repnme: Transitioning from low-income growth to
            high-income growth : is there a middle income trap ?
display_title: Transitioning from low-income growth
            to high-income growth : is there a middle income trap
listing_relative_url: /research/2014/11/20373154/transitioning-low-income-growth-high-income-growth-middle-income-trap
topicv3: Agriculture and Food Security m1326205 435,Tertiary Education m1326349 482,Inflation m1326709 0870F4727ACED1CF8525815C00471347,Patents m1326812 1041,Trade m1326924 698
publishtoextweb_dt: 2014-11-01T00:00:00Z
historic_topic: Science and Technology Development,Macroeconomics and Economic Growth,Governance,Industry
no_of_pages: 38
model_extractions: WPS7104 Policy Research Working Paper 7104 Transitioning from Low-Income Growth to High-Income Growth Is There a Middle Income Trap?

_David Bulman Maya Eden Ha Nguyen_ Development Research Group Macroeconomics and Growth Team November 2014
Policy Research Working Paper 7104

# **Abstract**

Is there a “middle income trap”? Theory suggests that the determinants of growth at low and high income levels may be different. If countries struggle to transition from growth strategies that are effective at low income levels to growth strategies that are effective at high income levels, they may stagnate at some middle income level; this phenomenon can be thought of as a “middle income trap.” This paper does not find evidence for (unusual) stagnation at any particular middle income level. However, it does find evidence that the determinants of growth at low and high income levels differ. These findings suggest a mixed conclusion: middle-income countries may need to change growth strategies to transition smoothly to high-income growth strategies, but this can be done smoothly and does not imply the existence of a middle income trap.

This paper is a product of the Macroeconomics and Growth Team, Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at dbulman@worldbank.org, meden@worldbank.org and hanguyen@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Transitioning from Low-Income Growth to High-Income Growth:**

# **Is There a Middle Income Trap?**

David Bulman, Maya Eden, Ha Nguyen<sup>1</sup>

## JEL: O4

Key words: Middle Income Trap, Determinants of Growth

> 1 This paper is a part of the World Bank’s participation in G20 Summits. We thank the support from DECOS. We thank Aart Kraay, Zia M. Qureshi and Luis Serven, for very helpful comments. All errors are our own.
# **1. Introduction**

Concerns about the so-called “middle income trap” have recently emerged among many middle income countries. These countries worry that they may become “trapped” at the middle income level, and that existing policies that facilitated earlier growth from low income to middle income might not work as well for transitioning from middle income to high income. More broadly, middle income countries seek a set of policies that can help them achieve strong and sustained growth and eventually help them join the league of high income countries.

Finding a set of appropriate pro-growth policies is always a complicated task, especially because every country faces its own institutional constraints. This paper does not lay out specific policy recommendations; rather, it provides a set of stylized facts about middle income countries and about fundamentals that might facilitate the transition from middle to high income. We focus on changes in relative income (i.e., how countries catch up to other high income countries), rather than absolute income.

We find mixed evidence regarding the existence of a middle income trap—i.e., slowing growth that might cause middle income countries to stagnate prior to joining the high income group. The predominant evidence against the existence of such a middle income trap comes from an examination of the growth paths of successful transitions. We find that “escapees” – countries that “escaped” the middle income trap and became rich – tend to grow fast and consistently to high income, and do not stagnate at any point as a middle income trap theory would suggest. In contrast, “non-escapees” tend to have low growth at all levels of income. In other words, while the existence of a middle income trap implies that growth rates systematically slow down as countries reach middle-income status, no such systematic slowdown is apparent in the data.

Among middle income countries, descriptive analyses suggest the following factors associated with higher growth: (1) economic structure, and in particular a faster transformation from agriculture to industry; (2) higher export shares; (3) lower inflation; and (4) decreases in inequality and dependency ratios. At the same time, we find some evidence that the effectiveness of different growth strategies may vary across income levels. This is consistent with middle income trap theories suggesting that middle income countries get stuck in the transition from growth strategies that are effective at low income levels to growth strategies that are effective at high income levels. While we do not find evidence of being “stuck,” we do find evidence that such a transition may be needed. We find that TFP growth is a much larger source of economic growth, both in absolute and relative terms, in middle and high income 2
countries than in low income countries.<sup>2</sup> This highlights the limits of capital accumulation (after all, investment has a decreasing marginal return) and suggests the important roles of education, research and innovation, and structural reforms. Figure 1 presents average contributions to annual growth in output per worker, by income level.<sup>3</sup> The orange part represents average annual TFP growth and the blue part represents average annual growth of the capital-labor ratio (multiplied by the capital share). For low income countries, the overwhelming majority of growth comes from capital accumulation. For middle and high income countries however, the share of TFP growth is much larger.

<!-- Start of picture text --> 6%<br><!-- End of picture text --> <!-- Start of picture text --> Low Income Lower Middle Upper Middle High Income<br>Income Income<br>α∙K/L TFP<br>6%<br>4%<br>2%<br>Average per capita Y/L growth<br>0<br><!-- End of picture text --> <!-- Start of picture text --> Average per capita Y/L growth<br><!-- End of picture text --> <!-- Start of picture text --> High Income<br><!-- End of picture text --> <!-- Start of picture text --> α∙K/L<br><!-- End of picture text --> <!-- Start of picture text --> TFP<br><!-- End of picture text --> <u>Figure 1: Average contributions to growth, by income level</u> The observation makes sense. For low income countries, since the level of capital is still low, it is relatively easier to attract and accumulate more capital (think of giving farmers tractors). When the level of capital accumulation is higher, it is harder to attract investment because the return to capital now becomes lower (i.e. it does not help to give one farmer two tractors). To maintain growth, countries have to turn to other sources: better technologies, better management practices, and research and innovation. Our conjecture is that countries with better strategies to access or, even better, generate state-of-the-art technologies and management practices will be able to catch up with high income countries.

> 2 This is true regardless if human capital is included or excluded from the production function (see the Data Appendix for more details).

> 3 Here, as in the rest of the paper, we define low income countries as those with per capita incomes less than 10% of the US; middle income countries as those with per capita incomes between 10% and 50% of the US; and high income countries as those with per capita incomes over 50% of the US. Here, we further divide middle income countries into lower and upper middle income countries using a threshold of 30% of the US. Table A1 in the Appendix lists countries by income group at 2009. The categorization looks reasonable.

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While this aggregate finding is consistent with the above economic intuition, we fail to find strong support for it on a more disaggregated level. We conduct a regression analysis of growth determinants in low and middle income levels. Our findings do not support the hypothesis that innovation and human capital accumulation are more important determinants of growth for middle income countries compared to low income countries. Rather, the regressions suggest that growth of low and middle-income countries may have to do more with the transformation of the economy: the growth effect of moving from agriculture to industry is stronger for middle income countries than for low income countries, while the growth effect of moving to services is weaker for middle income countries.

The paper is organized as follows: Section 2 reviews related literature on the middle income trap. Section 3 presents basic descriptions of income dynamics for a large set of countries, with a particular focus on the middle income group. Section 4 contrasts middle income “escapees” and “non-escapees” along several dimensions. Section 5 compares middle income country growth based on fundamentals. Section 6 presents regression results comparing growth determinants at middle income and low income levels. Section 7 concludes.

# **2. Literature review**

The term “middle income trap” first appeared in the World Bank’s “An East Asian Renaissance: Ideas for Economic Growth,” which stated that “middle income countries...have grown less rapidly than either rich or poor countries.” Since then, the concept of a middle income trap has become increasingly popularized and discussed,<sup>4</sup> although a consensus on the validity of the concept has yet to emerge.

Early research has tried to document growth patterns for low and middle income countries. Pritchett (2000) shows that the patterns for developing countries are best characterized as volatile. While some countries have steady growth (hills and steep hills), others have rapid growth followed by stagnation (plateaus), rapid growth followed by decline (mountains) or even catastrophic falls (cliffs), continuous stagnation (plains), or steady decline (valleys). This suggests that econometric growth literature that makes use of the panel nature of data is unlikely to be informative—a point previously made by Easterly et al. (1993). In that paper, it is shown that growth is volatile across decades while country characteristics are much more stable, and growth is largely driven by external shocks.

Following Pritchett’s (2000) suggestions, Hausmann, et al. (2005) look for instances of rapid but sustained acceleration in economic growth. They find that growth accelerations tend to be correlated with

> 4 See, for example, _The Economist_ June 23rd, 2011 for China’s “Middle Income Trap,” and other media coverage for other countries (Russia, Malaysia and Latin Americas).

4
increases in investment and trade, and with real exchange rate depreciations. Growth accelerations are also correlated with political regime changes and economic reforms. At the same time, growth accelerations are highly unpredictable; a majority of reforms do not lead to growth acceleration.

Related to growth acceleration, recent literature analyzes growth slowdowns, with implications for the future growth of China. Eichengreen et al. (2011) construct a sample of cases where fast-growing economies slow down. They show that rapidly growing economies slow down significantly when their per capita incomes reach around $US17,000 in year-2005 constant international prices. Since China will soon reach this level of income, the paper implies that China will likely witness a slowdown. In a recent paper, Cai (2012), through a discussion of many of China’s current problems, shares this concern. In our own work, we do not find support for the hypothesis that growth slowdowns occur at any particular income level. A potential reason for this difference is our use of relative, as opposed to absolute, income levels.

More recently, Im and Rosenblatt (2013) discuss the definition of middle income traps. They explore both the absolute and relative thresholds of the “traps”. With transitional matrix analysis, they also find little support for the idea of middle income traps.

# **3. Basic facts on countries’ income dynamics**

In this section we present some stylized facts on countries’ income dynamics. The sources of data are presented in the appendix.

We divide countries into three groups: low income, middle income and high income. Low income, middle income, and high income countries are those that have PPP GDP per capita less than or equal to 10%, between 10% and 50% and above 50% of U.S. PPP GDP per capita. Table A1 in the appendix lists all countries in the three categories in 2009 (in smaller bins).

We remove oil-exporters from our analysis for two reasons. First and more importantly, growth of these countries is driven largely by oil exports and not so much by fundamentals. Second, proceeds from oil exports can be very volatile, which would distort the persistence of countries’ relative income. See the Data Appendix for the list of oil exporters removed from the sample.

5
<!-- Start of picture text --> SGP<br>KORTWN HKSYCPR GRCJPNESPIRL<br>0 2 4 6<br>1960 Log of % Income relative to the U.S<br>6<br>4<br>2<br>0<br>2009 Log of % Income Relative to US<br><!-- End of picture text --> <!-- Start of picture text --> 1960 Log of % Income relative to the U.S<br><!-- End of picture text --> <u>Figure 2: Relative income dynamics, 1960-2009</u> Figure 2 shows countries’ long run changes of their income relative to the U.S. The log of per capita income relative to the U.S. in 1960 is on the x axis, with the 2009 value on the y axis. Each axis is divided into three areas, representing the three income groups. Countries in the top-middle quadrant (in red) are those that “escaped” from middle income to high income over this period. The list of escapees includes Greece; Hong Kong SAR, China; Ireland; Japan; Puerto Rico; the Republic of Korea; Seychelles; Singapore; Spain; and Taiwan, China. Two countries that nearly make the list (the top of the middle quadrant) are Portugal and Cyprus, which are still classified as middle income in 2009. Table 1 below summarizes the number of countries in 1960 (and alternatively, in 1970, where we have more data).

The predominant fact that emerges from Figure 2 and Table 1 is that relative income levels are highly persistent. All high income countries in 1960 remained high income in 2009; a majority of middle income countries remained middle income;<sup>5</sup> and only a handful of low income countries joined the middle income group. A concern is that there might have been more fluid movements of countries between 1960 and 2009 - for example, some countries might have moved to high income and moved back, which Figure 1 would fail to capture. Figure A1 in the appendix shows that there are few such movements. Almost all of the countries that have ever moved into high income have stayed there. Two exceptions are the Czech Republic and Lebanon.<sup>6</sup> Another potential concern is that this persistence is an artifact of our selected

> 5 A few middle income countries declined to poor income groups (Bolivia, Ghana, Haiti, Honduras, Nicaragua, Paraguay, and Zambia).

> 6 Czech Republic was a high income country (52% of the US) in 1990, but then it dropped to middle income throughout the 1990s and early 2000s, and since 2005 it has again been high income. Lebanon became rich in the mid-1970s but went to middle income in the early 1980s as it had a long civil war in the 1980s.

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middle income threshold (i.e., 10-50% of US per capita GDP). Figure A2 in the appendix shows that this is not the case: relative income mobility is no more persistent for middle income countries than other countries regardless of the threshold selected. In fact, through low and middle income, income levels become decreasingly persistent as countries get wealthier (i.e., low income levels are the most persistent, lower middle income levels are slightly less persistent, and upper middle income levels are even less persistent).

||Base<br>|Year<br>|
|---|---|---|
||1960|1970|
|_# of countries in sample_|||
|Low income|42|59|
|Middle income|41|58|
|High income|19|26|
|Total|102|143|
|_# (%) of income group transi_|_tions, base year to 2_|_009_|
|LowLow|37 (88.1%)|50 (84.7%)|
|LowMiddle|5 (11.9%)|9 (15.3%)|
|LowHigh|0 (0.0%)|0 (0.0%)|
|MiddleLow|7 (17.1%)|8 (13.8%)|
|MiddleMiddle|24 (58.5%)|41 (70.7%)|
|MiddleHigh|10 (24.4%)|9 (15.5%)|
|HighLow|0 (0.0%)|0 (0.0%)|
|HighMiddle|0 (0.0%)|1 (3.8%)|
|HighHigh|19 (100.0%)|25 (96.2%)|

<u>Table 1: Countries’ income distribution, 1960 and 1970</u> We also observe that escapees grow faster than non-escapees at all levels of income. Figure 3 shows the average annual growth rates at different per capita income levels relative to the U.S. (shown in the x- axis). The blue columns are the average growth rates for countries that ever escape from middle to rich, and the red columns represent growth rates for those countries that never escape. The escapees do consistently much better than their non-escapee counterparts, and they do not exhibit significant signs of slowing down. In contrast, non-escapees have low and stable growth over all levels of income: they too do not show signs of slowing down at middle income.

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<!-- Start of picture text --> 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50<br>Escapees Non-Escapees<br>10%<br>8%<br>6%<br>4%<br>Average GDP Growth<br>2%<br>0<br><!-- End of picture text --> <!-- Start of picture text --> Average GDP Growth<br><!-- End of picture text --> <!-- Start of picture text --> Escapees<br><!-- End of picture text --> <!-- Start of picture text --> Non-Escapees<br><!-- End of picture text --> <u>Figure 3: Average annual change of PPP GDP per capita</u> Figure 3 presents evidence against the existence of a middle income trap that causes growth to stagnate at a particular income level. Rather, non-escapees on average have slower growth at all levels of income, suggesting a persistent role of country-specific constraints and policy problems. A very familiar graph reinforces the point. Figure 4 shows the levels of PPP GDP per capita for escapees and some notable nonescapees over time. One can see that escapees as a whole grow strongly towards high income and do not see a “middle income trap”, while selected key non-escapees (Mexico, Malaysia, Brazil, Turkey) witness relative stagnation for the entire period.

Another graph reinforces the notion that countries do not slow down at middle income levels (relative to the U.S.). Figure 5 below shows a scatter plot of countries’ subsequent 10 year average growth against (log of) countries’ initial income relative to the U.S. in 1960, 1970, 1980, 1990 and 2000. Evidence for a middle income trap would imply a U-shaped curve, with countries systematically slowing down at middle income levels. We do not see such evidence.

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<!-- Start of picture text --> 140<br>Singapore<br>120 Hong Kong<br>Ireland<br>100<br>Middle/high income Japan<br>80 threshold Spain<br>Taiwan<br>60<br>Greece<br>Korea<br>40<br>Mexico<br>20 Malaysia<br>Turkey<br>0<br>Brazil<br>Income relative to US (%)<br>1950 1953 1956 1959 1962 1965 1968 1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007<br><!-- End of picture text --> <u>Figure 4: Income dynamics of escapees vs. non-escapees.</u> _Note: The list of countries on the right hand side is sorted by 2009 income level_ <!-- Start of picture text --> 0 1 2 3 4 5<br>Log of % income relative to US in 1960, 1970, 1980, 1990, and 2000<br>.15<br>.<br>.05<br>0<br>-<br>Subsequent 10yr average<br>-.1<br><!-- End of picture text --> <!-- Start of picture text --> Log of % income relative to US in 1960, 1970, 1980, 1990, and 2000<br><!-- End of picture text --> <u>Figure 5: Initial relative income and growth</u> For escapees, GDP growth was high and sustainable-- strong growth in one period was followed by strong growth in the subsequent period -- as if previous high growth paves the way for subsequent growth. We refer to this as the “momentum” hypothesis. A look at all countries confirms empirically the momentum hypothesis: there is a correlation between previous growth and current growth. Figure 6 shows the scatter plot of a middle income country’s average decadal growth rates in two consecutive 9
decades. The x axis presents average growth over t-10 through t-1, while the y axis presents average growth from t+1 through t+10, for all available years. The orange dots correspond to those countries that escaped from the middle income to the high income group. For all middle income countries, there is a significant, positive correlation between lagged and current decadal growth rates. The correlation coefficient for middle income escapees is 0.47, while the correlation coefficient for middle income nonescapees is 0.25.<sup>7</sup> The positive correlation we find is particularly strong for escapees. Also for escapees, the dots are much more concentrated at the upper right end of the scatter plot, implying that the escapees’ GDP growth is not only higher, but also more stable than other countries.

<!-- Start of picture text --> 15%<br><!-- End of picture text --> <!-- Start of picture text -->
-5% 0% 5% 10% 15%<br>10 year lagged growth average<br>Non-Escapees Non-escapee fitted values<br>Escapees Escapee fitted values<br>15%<br>10%<br>5%<br>0%<br>10 year future growth avg<br>-5%<br><!-- End of picture text -->

<!-- Start of picture text --> 10 year future growth avg<br><!-- End of picture text --> <!-- Start of picture text --> Escapees<br><!-- End of picture text --> <!-- Start of picture text --> Escapee fitted values<br><!-- End of picture text --> <u>Figure 6: Growth correlation for middle income countries</u> There are several possible economic interpretations for the persistence in growth. For example, it is possible that high growth provides more resources for investment (in infrastructure and education), paving the way for high growth in the next period. Political economy may also play a role: it may be politically easier for reforms to continue and deepen if they yielded economic success and high growth in the previous period.

> 7 For all low and middle income countries, using non-overlapping decadal growth, the correlation coefficient between lagged and future growth is 0.19.  Easterly et. al. (1993) calculate the correlation coefficient between 1960s-1970s for developing countries as 0.1 and 1970s-1980s as 0.33

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# **4. Comparing fundamentals of escapees and non-escapees**

In this part we document several differences in fundamentals of escapees (middle income countries that successfully transitioned to high income countries) and non-escapees (middle income countries that have yet to transition).

In the graphs below, blue bars represent escapees from any base year, while orange bars represent nonescapees.<sup>8</sup> In the appendix, figures A3-A12, results are presented for a similar exercise that disaggregates escapee and non-escapee fundamentals across four middle income categories (10-20%, 20-30%, 30-40%, and 40-50% of US income).

# **_The basics and human capital_**

As seen in the left panel of Figure 7 below, escapees have higher growth as well as higher TFP growth. Escapees exhibit higher levels of primary, secondary, and tertiary education, and are also clearly differentiated from non-escapees by the number of patents they generate. Results presented in the appendix suggest that tertiary education is more important for escapees at lower middle income levels, while patents are more prevalent for escapees at upper middle income levels. This finding suggests that the quality of education is more important at middle-high income levels, which is consistent with the view that transition from middle to high income must be fueled by innovation-led growth.

<!-- Start of picture text --> Growth and TFP Years of education Patents<br>7% relative to US 4.5<br>6% 0.9 4<br>0.8 3.5<br>5%<br>0.7<br>3<br>4% 0.6<br>2.5<br>3% 0.5<br>2<br>0.4<br>2% 1.5<br>0.3<br>1% 0.2 1<br>0% 0.1 0.5<br>Per capita GDP TFP growth 0 0<br>growth Prim. Sec. Tert. Patents (1000)<br>Escapees Non-Escapees Escapees Non-Escapees Escapees Non-Escapees<br><!-- End of picture text --> <u>Figure 7: Growth and TFP (left), years of education (center), and patents (right)</u>

> 8 Unlike the previous list of escapees, which only included countries that “escaped” between 1960 and 2009, this list includes countries that escaped earlier as well as countries for which we do not have 1960 data.  These include: Austria; Bahamas; Spain; Finland; Greece; Hong Kong SAR, China; Ireland; Iceland; Israel; Italy; Japan; Korea; Macao; Malta; Puerto Rico; Singapore; Slovenia; Seychelles; and Taiwan, China.

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# **_Economic structure, openness, and macroeconomic conditions_**

Countries that escape seem to show a clear and rapid transition from agriculture to industry. As seen in the appendix, this transition is particularly prevalent at lower-middle income levels. Escapees tend to have larger industry sectors and smaller agriculture and service sectors, and they also have higher growth in industry and lower growth in agriculture and services.

Escapees are in general more open and have better macroeconomic conditions. They are significantly more export-oriented and have more undervalued currencies (defined as in Rodrik, 2008). This undervaluation is particularly prevalent at lower middle income. Moreover, escapees, and particularly upper-middle income escapees, do not experience high inflation. No middle income “eventual escapee” ever experiences inflation over 20%, and by the time they reach upper-middle income levels they very rarely experience inflation over 10%. The graph on the right below shows average annual inflation calculated by excluding all inflation observations in the top 5%.<sup>9</sup> Even excluding the outliers, middle income escapees experience lower inflation than non-escapees. However, they have higher levels of external debt, which might be a result of greater access to outside markets or more financial development. Due to a lack of data, we cannot include other financial development indices.

<!-- Start of picture text --> Sectoral Shares of GDP Growth in Sectoral Openness and Macro<br>60 Shares Conditions<br>0.02 0.7<br>50<br>0.6<br>0.01<br>0.5<br>40<br>0 0.4<br>30 -0.01 0.3<br>0.2<br>-0.02<br>20 0.1<br>-0.03 0<br>10<br>-0.04<br>0 -0.05<br>Agric. Industry Services Agric. Industry Services<br>Escapees Non-Escapees Escapees Non-Escapees Escapees Non-Escapees<br><!-- End of picture text --> <u>Figure 8: Sectoral GDP share level (left) and growth (center), and openness and macro conditions (right)</u> 9 The top 5% of inflation observations for non-escapee middle-income countries (of nearly 2000 observations) includes all countries with inflation over 85.7%. The top 5% outliers are not driven simply by a few countries with persistently high inflation (although many countries are indeed frequently delinquent); rather, 20 countries join the list at some point (Argentina, Belarus, Brazil, Bulgaria, Costa Rica, Croatia, Ecuador, Estonia, Latvia, Lithuania, Macedonia, Mexico, Peru, Poland, Romania, Russia, Suriname, Turkey, Ukraine, and Uruguay).

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# **_Governance, inequality, and demographics_**

Escapees and non-escapees have similar levels of democracy, however escapees have greater equality and lower age dependency ratios. Escapees at all middle-income levels are also less likely to see increases in inequality as well as decreases in the age dependency ratio (i.e., the so-called “demographic dividend”).

<!-- Start of picture text --> Governance indicators Inequality and Growth of inequality<br>(0-10) dependency and dependency<br>6 80 0.01<br>70<br>5 0.005<br>60<br>0<br>4 50<br>40 -0.005<br>3<br>30<br>-0.01<br>2 20<br>-0.015<br>10<br>1<br>0 -0.02<br>0 Gini coefficient Dependency Gini Dependency<br>Democracy Autocracy ratio coefficient ratio<br>Escapees Non-Escapees Escapees Non-Escapees Escapees Non-Escapees<br><!-- End of picture text --> <u>Figure 9: Governance (left) and inequality and dependency levels (center) and growth (right)</u> To sum up, this descriptive analysis reveals that escapees have higher GDP and TFP growth at all relative income levels. They have greater levels of human capital, experience a faster transformation to industry, are consistently export-oriented, have better macroeconomic management, and have more income equality and more growth-conducive demographic conditions.

# **5. Comparing middle income average growth based on fundamentals**

The discussion in the previous section suffers from a potential methodological oversight. If we think of escapees as rapidly growing countries, then the previous section basically showed that fast-growing countries have better fundamentals than slow-growing countries. These associations could be very misleading about the causal impact of the fundamentals. For instance, advocates like to point out that fast-growing countries like Korea engaged in industrial policy, but this ignores the fact that many countries have experimented with industrial policy _without_ growing rapidly.

This section looks at growth performance based on fundamentals, rather than the reverse. In the following discussion, each chart represents one potential determinant of future growth, similar to previous sections. Here, the blue bars represent average growth trajectories (future 10-year average growth rates) 13
for countries with values below the median for that particular characteristic, and the orange bars represent average growth trajectories for countries with values above the median. We separate results for lower middle income countries (10-30% of U.S. income) and upper middle income countries (30-50% of U.S. income) in order to see how growth determinants differ across the middle income spectrum. Medians are calculated on an annual basis for lower and upper middle income countries separately. So, for instance, in the first graph below, the blue bars represent the average future 10-year average growth rates for all country/year observations in which the level of tertiary education is lower than the median value for all lower/upper middle income countries in that particular year.

# **_Human capital_**

Average years of tertiary education has little predictive power with regard to future growth; in the slight (1/4 percentage point) differences, lower middle income countries benefit from more tertiary education, while upper middle income countries seem to suffer. With regard to patents, a similar pattern emerges: while lower middle income countries with above-median patents grow faster, upper middle income countries grow slower. (This contrasts with the escapee vs. non-escapee chart, which shows upper middle income level escapees with many more patents than non-escapees. The result in the previous chart was driven by the patent performance of Korea and Japan, which is why this current exercise adds value.) <!-- Start of picture text --> Average years of tertiary schooling relative to the US Number of patents (beginning of period)<br>.0 (beginning of period) .0<br>.04<br>.03<br>.03<br>.02<br>.02<br>.01<br>.01<br>0 0<br>Lower Middle Income Upper Middle Income Lower Middle Income Upper Middle Income<br>Below Median Average Above Median Average Below Median Average Above Median Average<br>Future 10 Year Growth Avg Future 10 Year Growth Avg<br><!-- End of picture text --> <u>Figure 10: Tertiary education (left) and patents (right)</u>

# **_Economic structure_**

Lower-middle income countries that see larger declines in the agricultural share and increases in the industry share grow much faster on average, while an increase in the share of the service sector translates into slower growth; these trends hold for the upper middle income level, but are reduced in magnitude.

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<!-- Start of picture text --> Growth in agricultural share of GDP Growth in industry share of GDP<br>.05 (concurrent 10 year annual average) (concurrent 10 year annual average)<br>.05<br>.04 .04<br>.03 .03<br>.02 .02<br>.01 .01<br>0 0<br>Lower Middle Income Upper Middle Income Lower Middle Income Upper Middle Income<br>Below Median Average Above Median Average Below Median Average Above Median Average<br>Future 10 Year Growth Avg<br>Future 10 Year Growth Avg<br><!-- End of picture text --> <u>Figure 11: Agriculture share of GDP (left) and industry share of GDP (right)</u>

# **_Openness_**

For both lower and upper middle income countries, export-orientation is associated with higher growth and undervaluation is associated with lower growth. These trends are particularly strong for upper middle income countries.

<!-- Start of picture text --> Exports as a share of GDP (concurrent 10yr avg) Log undervaluation (concurrent 10yr avg)<br>.0 .05<br>.04 .04<br>.03 .03<br>.02 .02<br>.01 .01<br>0 0<br>Lower Middle Income Upper Middle Income Lower Middle Income Upper Middle Income<br>Below Median Average Above Median Average Below Median Average Above Median Average<br>Future 10 Year Growth Avg Future 10 Year Growth Avg<br><!-- End of picture text --> <u>Figure 12: Exports (left) and undervaluation (right)</u>

# **_Macroeconomic conditions_**

Countries with lower levels of inflation grow faster. Inflation itself is fairly persistent, so it is not surprising that lagged and concurrent inflation both have negative predicted effects on growth. Countries with lower external debt grow faster.

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<!-- Start of picture text --> External debt as a share of GNI<br>CPI inflation (concurrent 10yr average)<br>(concurrent 10 year average)<br>.0<br>.04<br>.04<br>.03<br>.03<br>.02<br>.02<br>.01 .01<br>0 0<br>Lower Middle Income Upper Middle Income Lower Middle Income Upper Middle Income<br>Below Median Average Above Median Average Below Median Average Above Median Average<br>Future 10 Year Growth Avg Future 10 Year Growth Avg<br><!-- End of picture text --> <u>Figure 13: Inflation (left) and external debt (right)</u>

# **_Governance and politics_**

Democracy has little if any predicted effect on growth for either lower or upper middle income countries. Similar to the previous results, autocracy seems to help growth at lower middle income levels but harm growth at upper middle income levels.

<!-- Start of picture text --> Democracy indicator (beginning of period) Autocracy indicator (beginning of period)<br>.0 .05<br>.04 .04<br>.03 .03<br>.02 .02<br>.01 .01<br>0 0<br>Lower Middle Income Upper Middle Income Lower Middle Income Upper Middle Income<br>Below Median Average Above Median Average Below Median Average Above Median Average<br>Future 10 Year Growth Avg Future 10 Year Growth Avg<br><!-- End of picture text --> <u>Figure 14: Democracy (left) and autocracy (right)</u>

# **_Inequality and demographics_**

Both the level of demographic characteristics at the beginning of the period and changes in demographic characteristics over the period affect growth. Lower dependency ratios result in faster growth, and declining dependency ratios (the “demographic dividend”) also translate into faster growth.

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In terms of inequality, beginning-of-period levels are largely irrelevant, but larger increases in the Gini coefficient are associated with slower growth, with a particularly pronounced effect for upper middle income countries.

<!-- Start of picture text --> Age dependency ratio (beginning of period) Change in age dependency ratio (concurrent 10yr avg)<br>.05<br>.04<br>.04<br>.03<br>.03<br>.02<br>.02<br>.01<br>.01<br>0 0<br>Lower Middle Income Upper Middle Income Lower Middle Income Upper Middle Income<br>Below Median Average Above Median Average Below Median Average Above Median Average<br>Future 10 Year Growth Avg Future 10 Year Growth Avg<br><!-- End of picture text --> <u>Figure 15: Age dependency level (left) and change (right)</u> <!-- Start of picture text --> Gini coefficient (beginning of period) Change in Gini coefficient (concurrent 10yr avg)<br>.0<br>.05<br>.04<br>.04<br>.03 .03<br>.02 .02<br>.01 .01<br>0 0<br>Lower Middle Income Upper Middle Income Lower Middle Income Upper Middle Income<br>Below Median Average Above Median Average Below Median Average Above Median Average<br>Future 10 Year Growth Avg Future 10 Year Growth Avg<br><!-- End of picture text --> <u>Figure 16: Gini coefficient level (left) and change (right)</u> To sum up, the factors that stand out from the descriptive analysis in sections 4 and 5 as associated with growth for middle income countries are: (1) economic structure, namely a faster transformation from agriculture to industry; (2) export-orientation; (3) lower inflation and external debt; and (4) decreases in inequality and the age dependency ratio.

# **6. Regressions**

The differential growth performance suggests that there is room for a more systematic investigation. In this section we do the following: (1) run a pooled OLS regression on middle income countries, to see what factors have significant impacts on output growth, and (2) run a pooled OLS regression on middle 17
and low income countries, and interact the factors with a middle income dummy to identify which factors matter for poor countries but not for middle income countries and vice versa.<sup>10</sup> While we are aware that several issues exist with cross-country growth regressions (see Esterly et al, 1993), the regressions help to provide some additional suggestive evidence for our exercises in section 5.

In all of the regressions, the dependent variable is the overlapping decade average growth of annual PPP GDP per capita. To control for heteroscedasticity and within-country serial correlations in the error terms, we report robust Newey-West type t-statistics. The nine right hand side variables are _Gini coefficient_ (concurrent average level), _Fertility Rate_ (5 year lag average level), _Age Dependency_ (concurrent average change), _Agriculture share of GDP_ (concurrent average change), _Tertiary education level relative to the U.S._ (at the beginning of the 10-year period), _Inflation_ (5 year lag average), _Polity score_ (5 year lag average), _Trade share of GDP_ (concurrent average level), _Log of undervaluation_ (concurrent average level). Since many of these variables can be endogenously determined with growth, the results reported below are best treated as associations. Please see the definition, the construction, and detailed data sources in the Data Appendix.

# **_Baseline regressions_**

The baseline regression pools low and middle income countries and looks at nine variables and their _interaction terms_ with the middle income dummy, along with controls for lagged income growth and income relative to the United States (see table A2 in the Appendix). Along with the baseline regression, table A2 also presents results using absolute income as a control; not including the control for lagged growth; and regression results for both the low and middle income sub-samples, excluding the interaction terms.

As suggested by the “momentum” argument, _lagged five year growth_ is significant in all specifications. This is consistent with the standard conditional convergence story, which suggests that growth rates of developing countries should decline over time (thus implying a serial correlation in growth levels). But the coefficient is nearly twice as large and much more significant for the middle income sub-sample than for the low income sub-sample, implying that momentum may be more important for middle income countries.

> 10 Our approach is related to Barreto and Hugh (2004). They show differential growth determinants for underachievers (i.e. countries that grow more slowly than traditional characteristics predict that it should) and overachievers.

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Generally, the following factors are significant for growth of middle income countries: Gini coefficient (at 10% level), fertility rate (at 10% level), decline in the agricultural share of GDP (at 5% level), and the trade share of GDP (at the 10% level). We discuss the important indicators in more detail below.

# **_Structural variables_**

In the baseline regressions, regardless of the controls or sample (low, middle, or both), the coefficient on the change in the agricultural share of GDP is significantly negative, suggesting that declining agriculture shares of GDP are important for growth (see Tables A2 and A3). The absolute coefficient for the low income sub-sample is larger than that for the middle income sub-sample. However, the interaction term (the middle income dummy) is not robustly significant.

Table A3 shows that industrial share of GDP has a significant positive effect on growth for middle income countries, and but has insignificant differential impacts on low and middle income countries. Interestingly, growth in the services share of GDP leads to a negative and significant coefficient on growth in middle income countries. The interaction term is also significant and negative.

The regression results can be interpreted as follows: a decline in the share of agriculture or an increase in industry share is positively associated with growth both in low and middle income countries. However, growth in services actually harms growth in middle income countries. This is probably because services in middle income countries are still of lower productivity than industry; an expansion of services at the cost of manufacturing can actually hurt growth.

# **_Human capital and Inequality_**

The lagged level of years of tertiary education is insignificant in the pooled sample, as is the interaction term. This is consistent with existing literature: current measures of human capital have little effect on growth. Similarly, higher inequality does not seem to have an impact on most of the sample, except for middle income countries. It has a negative coefficient but is only significant at the 10% level.

# **_Openness_**

In the full regressions, trade has a negative but insignificant coefficient. In the middle income sub-sample however, trade has a slightly significant and positive association with growth. Similarly we find the interaction term is positive, implying that trade has a stronger effect for middle income countries than low income countries. Undervaluation, on the other hand, has little impact on growth. However, the interaction term (the middle income dummy) is negative and significant, implying that the benefit of undervaluation on growth (if any) is much smaller when a country is already a middle income country.

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# **7. Conclusion**

In this paper, we have attempted to answer two questions: Is there a middle income trap? If there is a middle income trap, what causes it?

We answer the first question in the negative: countries that grow fast continue to grow fast, and they do not get “stuck” at any particular middle income level. This suggests that becoming “trapped” in some middle income level is not inevitable. However, this finding does not mean that there are no countries that are _trapped_ at a middle income level. Indeed, middle income countries that did not “escape” remain stagnant with low growth at all levels of relative income. Relative income levels are highly persistent, and transitioning from middle income to high income is hard.

Even in the absence of any evidence for a middle income trap, it is worth exploring the different fundamentals of escapees and non-escapees, as well as the effects of different growth strategies at middle income and low income levels. We find that common wisdom largely applies: escapees have higher growth at all relative income levels, higher TFP growth, and experience a faster transformation towards industry. They have better macroeconomic management and greater income equality, and they are consistently more export-oriented. An alternative analysis focused on fundamentals also reveals that faster transformation to industry, low inflation, stronger exports, and reduced inequality are associated with stronger growth.

Cross-country growth regressions seem to confirm that growth in middle income countries is positively associated with industrialization, openness, and equality. However, we do not see clear associations between education and innovation to growth in middle and low income countries.

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