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Inequality-growth nexus along the development process

  • Yi-Chen Lin EMAIL logo , Ho-Chuan (River) Huang and Chih-Chuan Yeh
Published/Copyright: October 11, 2013
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Studies in Nonlinear Dynamics & Econometrics
From the journal Studies in Nonlinear Dynamics & Econometrics Volume 18 Issue 3

Abstract

The paper examines whether the effect of inequality on growth varies with the level of economic development. Using a comprehensive panel of annual data for the 48 contiguous US states over the period 1945–2004, we find overwhelming evidence in support of threshold effects in the relationship between inequality and growth. Our analysis shows that while the effect of inequality on growth is significantly negative at lower levels of development, this effect diminishes along the growth process and then turns significantly positive at higher levels of development. Quantitatively, the coefficient estimates imply that when real income per capita is below the threshold of $12,140 (2004 US dollar), a one standard deviation increase in the share of income held by the top 1% of the population reduces the growth rate of real per capita income by 0.6479 percentage points. In contrast, when income per capita is above the threshold of $21,065 (2004 US dollar), a one standard deviation increase in the top percentile income share raises the rate of growth of real per capita income by 0.2561 percentage points.

Keywords: economic growth; income inequality; panel data; threshold regression
JEL classification:: C14; C23; O11; O15
Corresponding author: Yi-Chen Lin, Department of Economics, Tamkang University, 151 Yingzhuan Rd., Tamshui District, New Taipei City 25137, Taiwan, Phone:+886-2-26215656 ext. 3358, e-mail:
  1. 1

    Borjas, Bronars, and Trejo (1992) find that more able workers tend to be attracted to states with wider income distribution. Partridge (2006) provides evidence that state-level inequality is associated with greater job growth.

  2. 2

    See Anand and Segal (2008) for a useful source of literature review on the empirics of global income inequality.

  3. 3

    Empirical evidences supporting the conjecture that the median voter’s preference for redistributive policies varies with the level of economic development are as follows. Using PSID data, Alesina and Le Ferrara (2005) find evidence that individuals with higher current income are more averse to redistributive policies. Using cross-sectional data for US states, Ashby and Sobel (2008) find that economic freedom, which is conductive to inequality, is positively related to both the level of income and the growth rate of income.

  4. 4

    In contrast, country-level inequality measures are based on surveys that differ in terms of income definitions and coverage of sources of income, the comparability of inequality measures across countries is limited.

  5. 5

    The description of the panel threshold methodology applies to the two-regime (one threshold) case. Similar reasoning can be straightforwardly applied to models with more thresholds. Interested readers are referred to Hansen (1999) for more detailed descriptions of the panel threshold strategy.

  6. 6

    Note that in order to calculate per capita income growth rate, we are left with T=59 time series observations for each state, resulting in a total of 2832 observations in our later application.

  7. 7

    The two variables are multiplied by 100 from the original data provided by Frank (2009).

  8. 8

    The two human capital measures are calculated by multiplying the original data in Frank (2009) by 100 and then taking natural logarithm. Due to the value being zero in several observations, the wage and salary variable for the agriculture sector enters as log(1+agriculture).

  9. 9

    The sum of squared deviation of variable x is separated into two categories using the following equation: ∑i=1N∑t=1T(xit−x¯)2=∑i=1NT(x¯i−x¯)2+∑i=1N∑t=1T(xit−x¯i)2, where i indexes states, t indexes time, and x¯ and x¯ respectively represent overall mean and state mean. The first term on the right-hand-side is the sum of squared deviations within the states and the second term is the sum of squared deviations between the states.

  10. 10

    The hypothesis that credit market tends to improve as an economy develops is also used by Barro (2000) to explain his finding that inequality tends to curtail (promote) economic growth in poorer (richer) countries.

Acknowledgement

The authors are grateful to Bruce E. Hansen and Mark W. Frank for kindly sharing with us the computer code and data, respectively, used in this paper. Helpful and constructive comments from two anonymous referees are also highly appreciated. Any remaining errors are our own responsibility.

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Published Online: 2013-10-11
Published in Print: 2014-5-1

©2014 by Walter de Gruyter Berlin/Boston

Articles in the same Issue

  1. Frontmatter
  2. The effects of the monetary policy stance on the transmission mechanism
  3. Inequality-growth nexus along the development process
  4. Estimating the Wishart Affine Stochastic Correlation Model using the empirical characteristic function
  5. Inventories, business cycles, and variable capital utilization
  6. Factor-based forecasting in the presence of outliers: Are factors better selected and estimated by the median than by the mean?
  7. Estimating VAR-MGARCH models in multiple steps
https://doi.org/10.1515/snde-2012-0037
Keywords for this article
economic growth; income inequality; panel data; threshold regression

Articles in the same Issue

  1. Frontmatter
  2. The effects of the monetary policy stance on the transmission mechanism
  3. Inequality-growth nexus along the development process
  4. Estimating the Wishart Affine Stochastic Correlation Model using the empirical characteristic function
  5. Inventories, business cycles, and variable capital utilization
  6. Factor-based forecasting in the presence of outliers: Are factors better selected and estimated by the median than by the mean?
  7. Estimating VAR-MGARCH models in multiple steps
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