The Middle-Income Trap: Definitions, Theories and Countries Concerned—A Literature Survey

Abstract

The term middle-income trap (MIT) usually refers to countries that have experienced rapid growth and thus quickly reached middle-income status, but then failed to overcome that income range to further catch up to the developed countries. This paper surveys the MIT literature. It begins by laying out different approaches to defining the MIT and by presenting as well as classifying the most important empirical studies. After a short overview of the currently identified MIT countries, the article summarizes the main explanatory approaches, taking into account both the theoretical foundations and the empirically identified triggering factors.

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Figure 1

Source: EBSCOhost, Web of Science (Core Collection, by Thomson Reuters).

Figure 2

Source: Own representation based on data from Google Trends.

Figure 3

Source: Penn World Tables (PWT) Version 8.0. Own representation.

Figure 4

Source: Own representation based on Ohno (2009).

Notes

  1. 1.

    However, Garrett (2004) also describes the MIT but does not mention it explicitly.

  2. 2.

    For example, Im and Rosenblatt (2015) focus primarily on the empirical definitions of the MIT (in particular on the distinction between the absolute and relative thresholds). Kanchoochat (2014) develops a classification of the MIT literature based on the different solutions of the MIT problem proposed by different papers. That is, she concentrates primarily on the measures a country has to adopt to avoid the MIT. Finally, Gill and Kharas (2015) mention various empirical definitions and theoretical explanations, but concentrate especially on the evaluation of their 2007 paper.

  3. 3.

    Own calculations with data from the Penn World Tables (PWT) Version 8.0.

  4. 4.

    Thereby 176 EBSCOhost and 45 Web of Science articles in academic journals.

  5. 5.

    Google Trends, search term ‘middle-income trap’, accessed online 31.03.2016. According to Google Trends, the data depicted in Figure 2 represent ‘search interest relative to the highest point on the chart’. In Figure 2, the highest point is reached in November 2014. Hence, Figure 2 does not convey absolute search volume.

  6. 6.

    Since the beginning of the slowdown of the Chinese economy in recent years, Google Searches for the term ‘middle income trap China’ also show an upward trend. See Figure A1 in Appendix A.

  7. 7.

    See https://scholar.google.de/scholar?q=%22middle-income+trap%22+&btnG=&hl=de&as_sdt=0%2C5, accessed online 16.09.2016 and https://scholar.google.de/scholar?q=%22middle-income+trap%22+china&btnG=&hl=de&as_sdt=0%2C5, accessed online 16.09.2016. Additionally, 442 articles include the term ‘middle-income trap’ in the title (see https://scholar.google.de/scholar?as_q=&as_epq=middle+income+trap&as_oq=&as_eq=&as_occt=title&as_sauthors=&as_publication=&as_ylo=&as_yhi=&hl=de&as_sdt=0%2C5, accessed online 16.09.2016).

  8. 8.

    The threshold separating low-income from lower-middle-income countries is based on the operational threshold for civil works preference and the threshold separating lower-middle-income from upper-middle-income countries. The World Bank refers to a now-discontinued threshold for 17-year IBRD terms. The threshold that is used to define high-income countries is based on the Staff Report Per Capita Income: Estimating Internationally Comparable Numbers. For further information, see https://datahelpdesk.worldbank.org/knowledgebase/articles/378833-how-are-the-income-group-thresholds-determined.

  9. 9.

    World Bank (2013), using Maddison (2010) data, considers countries that have been in the middle-income range between 1960 and 2008 as MIT countries. Note that in Figure 3b, we consider the period 1960–2011 and use PWT data for illustration purposes.

  10. 10.

    This increase in period length can be attributed to the fact that the 2014 study uses a larger country sample in comparison to the 2012 study. Felipe et al. (2014) argue that the East and Southeast Asian success countries have a strong impact on their 2012 results, while, however, the growth experience of these countries and in particular their fast transition is not representative of the growth process in general. Therefore, Felipe et al. (2014) enlarge their sample so that it includes a greater number of economies. In particular, their 2014 sample includes all the economies that managed to traverse the LMIR and UMIR until 2013 and not only those that became LMI and UMI after 1950 as in their 2012 sample.

  11. 11.

    This approach is also used in some other publications, e.g., in Athukorala and Woo (2011).

  12. 12.

    See World Bank (2013, p. 12) and Agénor et al. (2012, p. 2), Figure 1 (e1.6 ≈ 5% and e1.8 ≈ 45%, respectively). The authors refer here to the above-mentioned income classification of the World Bank (see Table 1 and footnote 8).

  13. 13.

    However, Bulman et al. (2014) could also be assigned to the theoretical definition approach as they also (additionally) define the MIT as a failed growth strategy of a middle-income country (see Bulman et al., 2014, p. 2).

  14. 14.

    Bulman et al. (2014) do not justify this choice of income thresholds but generalize it later to some extent.

  15. 15.

    Namely Albania, Algeria, Bolivia, Botswana, Brazil, Colombia, Congo (Rep.), Dominican Republic, Ecuador, Egypt, El Salvador, Gabon, Guatemala, Iran, Jamaica, Kenya, Jordan, Lebanon, Libya, Malaysia, Morocco, Namibia, Panama, Paraguay, Peru, Philippines, Romania, Saudi Arabia, South Africa, Sri Lanka, Swaziland, Syrian Arab Republic, Tunisia, Uruguay, Venezuela, Yemen (Rep.). Countries in bold are caught in the upper-middle-income trap.

  16. 16.

    For example, according to the authors, Indonesia and Pakistan may soon enter a lower-middle-income trap. In addition, Poland, Oman, Mexico and Hungary are possible upper-middle-income-trap candidates (see Felipe et al., 2012 and Appendix Table 1.A).

  17. 17.

    In contrast to the World Bank (2013), Bulman et al. (2014) do not identify Equatorial Guinea, Israel, Mauritius, and Portugal as middle-income escapees.

  18. 18.

    These results change if the authors base their analysis on the period between 1970 and 2009, with 41 countries being classified as non-escapees of the middle-income range.

  19. 19.

    In contrast to Felipe et al. (2012), their list of MIT countries also includes Argentina, Belarus, Chile, Costa Rica, Lithuania, Mexico, Russian Federation, Thailand, and Turkey, but excludes Albania, Algeria, Botswana, Congo (Rep.), Ecuador, Egypt, Iran, Jamaica, Kenya, Libya, Namibia, Saudi Arabia, Sri Lanka, Swaziland, Venezuela, and Yemen (Rep.). Hence, their empirically identified MIT countries differ in 25 cases; only 18 countries are identified in both studies.

  20. 20.

    See “Relative Approaches” for a precise definition of x i,t .

  21. 21.

    Namely Cuba, El Salvador, Lebanon, Peru, Syria, and Thailand.

  22. 22.

    Namely Bolivia, Botswana, Bulgaria, Costa Rica, Guatemala, Honduras, Indonesia, Iran, Iraq, Jordan, Mexico, Mongolia, Morocco, Panama, Romania, South Africa, Swaziland, Tunisia, and Turkey in addition to the countries listed in footnote 21.

  23. 23.

    Bulman et al.’s (2014) results stand out as well, as they identify many European MIT countries (literally ‘non-escapees’) among others.

  24. 24.

    See also Aiyar et al. (2013), who note that most of the slowdowns identified by Eichengreen et al. (2012) occurred in rather developed economies or oil exporting countries (see also Paus, 2014).

  25. 25.

    Of course, the subdivision of MIT explanations into ‘theoretical explanations’ and ‘empirically identified triggering factors’ is only one alternative among many. For example, Kanchoochat (2014) distinguishes between the following classes or groups of MIT explanations: (a) explanations based on the quality of institutions and education (group 1), and (b) explanations based on the changes in export composition, where the latter group is subdivided depending on whether the export change is made by following (group 2) or defying (group 3) comparative advantage. Furthermore, she refers to the fact that the need for government intervention from group 1 to group 3 increases.

  26. 26.

    Robertson and Ye (2015) come to a similar conclusion. They argue that the MIT is “a more subtle phenomenon” than the general concept of club convergence.

  27. 27.

    The MENA region comprises countries of the Middle East and North Africa. See e.g., http://www.worldbank.org/en/region/mena.

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Correspondence to Linda Glawe.

Appendices

Appendix A

See Figure A1.

Figure A1
figure5

Source: Own representation based on data from Google Trends. Note The thin black line indicates the five-year-average trend.

Google Searches for ‘middle income trap China’.

Appendix B

See Table B1.

Table B1 MIT-countries identified by Eichengreen et al. (2012, 2014), Aiyar et al. (2013), Felipe et al. (2012, 2014), Zhuang et al. (2012), and Robertson and Ye (2015)

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Glawe, L., Wagner, H. The Middle-Income Trap: Definitions, Theories and Countries Concerned—A Literature Survey. Comp Econ Stud 58, 507–538 (2016). https://doi.org/10.1057/s41294-016-0014-0

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Keywords

  • middle-income trap
  • middle-income countries
  • economic growth
  • economic development
  • growth slowdowns
  • catching up

JEL Classification

  • O10
  • O40