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Re-Examining Vicious Circles of Development: A Panel Var Approach

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Abstract

Using panel data from 102 countries in 1975–2010, this paper explores the dynamic interaction among health, education and growth by applying panel VAR techniques. Empirical findings reveal that the predictive pattern among health, education and economic growth is not stable in the cross section of countries. While health has positive contribution to growth for all countries, education has benefited only higher middle income and high-income OECD countries. Economic growth has predictive power for the components of human development in the high-income OECD countries. Further, econometric evidence reveals that bi-directional relationship between health and education should be supported to reap the benefits of human development on economic growth.

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Notes

  1. Suri et al. (2011), both theoretically and empirically, put forward a strong connection between human development and economic growth, provide an evidence for a systematic link between them, and analyze the priorities in building up policy implications. Their findings display that, without an improvement in human development indicators, sustained economic growth is not achievable, and policies to improve human development must complement economic growth oriented policies.

  2. Recently, three way causality between health, education and economic growth have been examined for different countries and time spans by using different proxies for health and education, such as Dahal (2016) for Nepal, Şen et al. (2015) for eight developing countries, Saksena and Deb (2016) for Indian States and Bleakley et al. (2013) for US. Yet, none of them has focused on relationship among health, education and economic growth for 102 countries between 1975 and 2010 by adopting panel VAR approach based on system GMM estimates.

  3. There are a number of causality studies for some countries based on time series techniques. See, for example, Ahmad and French (2011) for Bangladesh; De Meulemeester and Rochat (1995) for Sweden, Australia, UK, France, Japan and Italy; Ljungberg and Nilson (2009) for Sweden; Asterau and Agiomirgianakis (2001) for Greece; and Selfa and Grabowski (2003) for Japan.

  4. Based on the values of their GNI per capita, the World Bank classifies countries into four categories, namely, low-income, lower middle-income, higher middle-income and higher-income. See “Appendix 1” for the classification and the list of the countries.

  5. Even though health expenditure is the widely-used proxy in the literature, this variable is not available for all countries in the period considered.

  6. For the sensitivity of the results, all regressions are carried out by benefiting from different measures of health and education. To proxy for health and education, under five mortality rates and the percentage of population who have completed secondary education have been employed, respectively. But there is no significant change in the results. All calculations are available upon request.

  7. Due to the lack of space, the panel unit root tests are not reported, but they are available upon request.

  8. The robust regression procedure is implemented by STATA via the rreg command.

  9. Using different lag orders do not generate significant changes in the results. All calculations are available upon request.

  10. All system GMM estimates are carried out by the Roodman`s `xtabond2` command in STATA (v.12). The basic weakness in the system GMM estimation is the use of too many instruments leading to misspecification of the model. In this context, to get valid instruments, we have followed the way suggested by Roodman (2006, 2009). First, a high p value of Hansen test is preferred rather than the conventional level of 0.05. Second, the “collapse” option available in STATA v.12 is used to limit the proliferation of instruments.

  11. Due to the heteroscedasticity problem in the one-step model, robust-to-heteroscedasticity variance–covariance estimator is used as (such the Sargan test statistics cannot be presented).

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Authors and Affiliations

  1. Department of Economics, Hacettepe University, 06800, Ankara, Turkey

    Bahar Bayraktar-Sağlam Bayraktar-Sağlam

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  1. Bahar Bayraktar-Sağlam Bayraktar-Sağlam
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Correspondence to Bahar Bayraktar-Sağlam Bayraktar-Sağlam.

Appendices

Appendix 1

See Table 7.

Table 7 List of countries
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Appendix 2

See Tables 8, 9, 10 and 11.

Table 8 Low income countries
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Table 9 Lower middle income countries
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Table 10 Higher middle income countries
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Table 11 High income OECD countries
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Bayraktar-Sağlam, B.BS. Re-Examining Vicious Circles of Development: A Panel Var Approach. Soc Indic Res 137, 231–256 (2018). https://doi.org/10.1007/s11205-017-1594-4

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