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Estimating the Elasticity of Growth in the US Using the Generalized Means of Income

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Abstract

Economic growth has been a key mantra to promote poverty reduction in developing countries. Studies have shown that a 1 % GDP growth can reduce absolute poverty (or increase the average income of the poorest quintile) by 1 % or more in developing countries. The literature calls this relationship between poverty reduction and growth as growth elasticity. However, there is very little research available studying the extent of growth elasticity in a developed economy. I fill this vacuum in literature by applying the method of generalized means of income outlined in Foster and Székely (Int Econ Rev 49(4):1143–1172, 2008) on micro-level data to estimate the elasticity of growth in the US. The generalized means of income of Foster and Székely (Int Econ Rev 49(4):1143–1172, 2008) satisfies all the axioms of a good income standard, which makes it a preferred method to measure the elasticity of growth. My analysis shows that most of the growth in the US is driven by the richer segment of the society. The ‘wealthier’ poor get some benefit from growth—a 1 % increase in per-capita state-level income leads to about 0.9 % increase in their income both in the short and long-run. However, this relationship diminishes when I calculate the growth elasticity of those in deeper poverty. Sector-wise decomposition of income shows that the ‘wealthier’ poor benefits from an increase in the size of the service sector, but those in deeper poverty do not see this benefit.

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Notes

  1. \({\text{Growth}}\,{\text{elasticity}} = \frac{{{\text{Percentage}}\,{\text{improvment}}\,{\text{of}}\,{\text{the}}\,{\text{condition}}\,{\text{of}}\,{\text{the}}\,{\text{poor}}\,{\text{in}}\,{\text{country}}\,{\text{i}}\,{\text{at}}\,{\text{time}}\,{\text{t}}}}{{{\text{Economic}}\,{\text{growth}}\,{\text{in}}\,{\text{country}}\,{\text{i}}\,{\text{at}}\,{\text{time}}\,{\text{t}}}}\).

  2. Number in Poverty and Poverty Rate: 1959 to 2011. US Census Bureau. http://www.census.gov/hhes/www/poverty/data/incpovhlth/2011/Figure4.pdf.

  3. An income standard is a method that summarizes individual income of a population into one single index, without using any kind of poverty line or cutoffs to summarize the income (Foster and Székely 2008).

  4. For example, the World Bank uses $4 a day poverty line for Latin American countries. http://www.worldbank.org/en/news/press-release/2012/11/13/new-world-bank-report-finds-fifty-percent-increase-middle-class-latin-america-over-last-decade.

  5. “Household Income for States: 2010 and 2011” US Census Bureau. http://www.census.gov/prod/2012pubs/acsbr11-02.pdf.

  6. Equation (2) is slightly different from equation estimated by Foster and Székely (2008). They use the following equation for estimation (Eq. 2 of their paper): \(y_{\alpha ,it} - y_{\alpha ,it - 1} = \gamma + \beta \left( {y_{1,it} - y_{1,it - 1} } \right) + Z'_{it} \theta + \mu_{i} + \tau_{t} + \varepsilon_{it}\). In their paper, β has a slightly different meaning. It measures how much the generalized means of income increases (in terms of percentage points) if growth rate increases by one percentage point. Nonetheless, in both cases, the β can be used to draw similar conclusions about evolution of income.

  7. http://www.clevelandfed.org/research/data/us-inflation/chartsdata/index.cfm.

  8. I also repeated the robustness tests using lagged value of ln(y1) instead of its contemporaneous value. Although not reported, I found that generally, the results obtained are similar to that seen in Tables 4 through 6.

References

  • Acemoglu, D., Johnson, S., & Robinson, J. A. (2005). Institutions as a fundamental cause of long-run growth. Handbook of Economic Growth, 1, 385–472.

    Article  Google Scholar 

  • Adelman, I., & Morris, C. T. (1973). Economic growth and social equity in developing countries. Stanford, Calif: Stanford University Press.

    Google Scholar 

  • Ahluwalia, M. S. (1976). Income distribution and development: Some stylized facts. The American Economic Review, 66(2), 128–135.

    Google Scholar 

  • Atkinson, A. B. (1970). On the measurement of inequality. Journal of Economic Theory, 2(3), 244–263.

    Article  Google Scholar 

  • Banerjee, A. V., & Duflo, E. (2003). Inequality and growth: What can the data say?. Journal of economic growth, 8(3), 267–299

    Article  Google Scholar 

  • Barro, R. J., & Sala-i-Martin, X. (1992). Convergence. Journal of Political Economy, 100(2), 223–251.

    Article  Google Scholar 

  • Blank, R. M. (2000). Distinguished lecture on economics in government: Fighting poverty: Lessons from recent US History. The Journal of Economic Perspectives, 14(2), 3–19.

    Article  Google Scholar 

  • Blank, R. M. (2008). Presidential address: How to improve poverty measurement in the United States. Journal of Policy Analysis and Management, 27(2), 233–254.

    Article  Google Scholar 

  • DeFina, R. H. (2008). The impact of state minimum wages on child poverty in female-headed families. Journal of Poverty, 12(2), 155–174.

    Article  Google Scholar 

  • Dollar, D., & Kraay, A. (2002). Growth is good for the poor. Journal of Economic Growth, 7(3), 195–225.

    Article  Google Scholar 

  • Durlauf, S. N., & Quah, D. T. (1999). The new empirics of economic growth. Handbook of Macroeconomics, 1, 235–308.

    Article  Google Scholar 

  • Fanta, F., & Upadhyay, M. P. (2009). Poverty reduction, economic growth and inequality in Africa. Applied Economics Letters, 16(18), 1791–1794.

    Article  Google Scholar 

  • Foster, J. E., & Székely, M. (2008). Is economic growth good for the poor? Tracking low incomes using general means. International Economic Review, 49(4), 1143–1172.

    Article  Google Scholar 

  • Gallup, J. L., Sachs, J. D., & Mellinger, A. D. (1999). Geography and economic development. International Regional Science Review, 22(2), 179–232.

    Article  Google Scholar 

  • Gasparini, L., Gutiérrez, F., & Tornarolli, L. (2007). Growth and income poverty in Latin America and the Caribbean: Evidence from household surveys. Review of Income and Wealth, 53(2), 209–245.

    Article  Google Scholar 

  • Gundersen, C., & Ziliak, J. P. (2004). Poverty and macroeconomic performance across space, race, and family structure. Demography, 41(1), 61–86.

    Article  Google Scholar 

  • Hasanov, F., & Izraeli, O. (2011). Income Inequality, Economic Growth, and the Distribution of Income Gains: Evidence from the U.S. States. Journal of Regional Sciences, 51(3), 518–539.

    Article  Google Scholar 

  • Islam, T. M. T., Minier, J., & Ziliak, J. P. (2015). On persistent poverty in a rich country. Southern Economic Journal, 81(3), 653–678.

    Article  Google Scholar 

  • Kraay, A. (2006). When is growth pro-poor? Evidence from a panel of countries. Journal of Development Economics, 80(1), 198–227.

    Article  Google Scholar 

  • Lerman, R. I. (1996) The impact of the changing US family structure on child poverty and income inequality. Economica, 63(250), S119–S139.

    Article  Google Scholar 

  • Levernier, W., Partridge, M. D., & Rickman, D. S. (2002). The causes of regional variations in US poverty: A cross-county analysis. Journal of Regional Science, 40(3), 473–497.

    Article  Google Scholar 

  • Loayza, N., & Raddatz, C. (2010). The composition of growth matters for poverty alleviation. Journal of Development Economics, 93(1), 137–151.

    Article  Google Scholar 

  • Nelson, C. (2006). What do we know about differences between CPS and ACS income and poverty estimates?. US Census Bureau. http://www.census.gov/hhes/www/income/nelson_082906.pdf.

  • Partridge, M. D. (2005). Does income distribution affect us state economic growth?*. Journal of Regional Science, 45(2), 363–394.

    Article  Google Scholar 

  • Partridge, M. D., & Rickman, D. S. (2008). Distance from urban agglomeration economies and rural poverty. Journal of Regional Science, 48(2), 285–310.

    Article  Google Scholar 

  • Rappaport, J., & Sachs, J. D. (2003). The United States as a coastal nation. Journal of Economic Growth, 8(1), 5–46.

    Article  Google Scholar 

  • Ravallion, M. (2001). Growth, inequality and poverty: Looking beyond averages. World Development, 29(11), 1803–1815.

    Article  Google Scholar 

  • Ravallion, M., & Chen, Shaohua. (1997). What can new survey data tell us about recent changes in distribution and poverty? The World Bank Economic Review, 11(2), 357–382.

    Article  Google Scholar 

  • Roemer, M., & Gugerty, M. K. (1997). Does economic growth reduce poverty? CAER II. http://pdf.usaid.gov/pdf_docs/Pnaca656.pdf.

  • Tabellini, G. (2010). Culture and institutions: Economic development in the regions of Europe. Journal of the European Economic Association, 8(4), 677–716.

    Article  Google Scholar 

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Correspondence to T. M. Tonmoy Islam.

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Islam, T.M.T. Estimating the Elasticity of Growth in the US Using the Generalized Means of Income. Soc Indic Res 129, 95–112 (2016). https://doi.org/10.1007/s11205-015-1093-4

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