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The relationship between the inflation rate and inequality across U.S. states: a semiparametric approach


This paper uses a cross-state panel for the United States over the 1976–2007 period to assess the relationship between income inequality and the inflation rate. Employing a semiparametric instrument variable (IV) estimator, we find that the relationship depends on the level of the inflation rate. A positive relationship occurs only if the states exceed a threshold level of inflation rate. Below this value, inflation rate lowers income inequality. The results suggest that a nonlinear relationship exists between income inequality and the inflation rate.

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  1. 1.

    For non-linear effect of inflation on economic growth, see Hess and Morris (1996), Barro (1996), Fischer (1993), Sarel (1996), and Kremer et al. (2013).

  2. 2.

    Please see "Appendix 1".

  3. 3.

    Leigh (2007) finds that Top 10 and 1% income shares are useful proxies for inequality across the income distribution.

  4. 4.

    See Professor Frank constructed his dataset based on the Internal Revenue Service (IRS), which has a limitation of omission of some individual earning less than a threshold level of gross income. For this reason, we focus more on top income shares as primary indicators of inequality measures.

  5. 5.


  6. 6.

    Initially, we tested semiparametirc IV regression without accounting a structural break and results showed threshold around 6 percent inflation. However as there is the structural break in the dataset, we created dummy variable. Following years and states with greater than 6 percent inflation:

    (i) From 1977 to 1981 50 states had higher inflation than 6 percent, except in 1980 Mississippi where inflation rate was below 6 percent. (ii) From 1988–1990 to 2004–2005, inflation rate in California and Hawaii were above 6 percent. The inflation rates were mostly high during the oil shock and Volcker's disinflationary periods. Since the semiparametric estimator is sensitive to outliers, we created a dummy variable that equals one when the inflation rate was less than 6 percent and zero otherwise to avoid biasing the results.

  7. 7.

    Given possible endogeneity issues, we also use the first lag of the control variables in the model—the growth rates of real per capita income, of high school attainment, of college attainment, and of the unemployment rate. Our results here are qualitatively similar to the model that does not address possible endogeneity issues.

  8. 8.

    For robustness, we also estimate threshold using the method suggested by Hansen (1999) and the results are presented in "Appendix 2". We find the results are similar to the results from the semiparametric approach.


  1. Albanesi, S.: Inflation and inequality. J. Monet. Econ. 54(4), 1088–1114 (2007)

    Article  Google Scholar 

  2. Areosa, W.D., Areosa, M.B.: The inequality channel of monetary transmission. J. Macroecon. 48, 214–230 (2016)

    Article  Google Scholar 

  3. Autor, D.H., Katz, L.F., Kearney, M.S.: Trends in US wage inequality: revising the revisionists. Rev. Econ. Stat. 90(2), 300–323 (2008)

    Article  Google Scholar 

  4. Balcilar, M., Gupta, R., Jooste, C.: The growth-inflation nexus for the US over 1801–2013: a semiparametric approach (No. 201447), University of Pretoria, Department of Economics (2014)

  5. Barro, R.: Inflation and growth. Fed. Reserv. Bank St. Louis Rev. 78, 153–169 (1996)

    Google Scholar 

  6. Beck, T., Demirgüç-Kunt, A., Levine, R.: Finance, inequality and the poor. J. Econ. Growth 12(1), 27–49 (2007)

    Article  Google Scholar 

  7. Berry, W.D., Fording, R.C., Hanson, R.L.: An annual cost of living index for the American States, 1960–1995. J. Politics 62(2), 550–567 (2000)

    Article  Google Scholar 

  8. Bulir, A.: Income inequality: Does inflation matter? IMF Staff Papers 48(1), 139–159 (2001)

    Google Scholar 

  9. Bulir, A., Gulde, A.M.: Inflation and income distribution; further evidence on empirical links (No. 95/86). International Monetary Fund (1995)

  10. Camera, G., Chien, Y.: Understanding the distributional impact of long-run inflation. J. Money Credit Bank. 46(6), 1137–1170 (2014)

    Article  Google Scholar 

  11. Chu, M.K.Y., Davoodi, M.H.R., Gupta, M.S.: Income Distribution and Tax and Government Social Spending Policies in Developing Countries (No. 0–62). International Monetary Fund (2000)

  12. Coibion, O., Gorodnichenko, Y., Kueng, L., Silvia, J.: Innocent bystanders? Monetary policy and inequality in the US (No. w18170). National Bureau of Economic Research (2012)

  13. Cutler, D.M., Katz, L.F.: Rising Inequality? Changes in the distribution of income and consumption in the 1980s (No. w3964). National Bureau of Economic Research (1992)

  14. Cysne, R.P., Maldonado, W.L., Monteiro, P.K.: Inflation and income inequality: a shopping-time approach. J. Dev. Econ. 78(2), 516–528 (2005)

    Article  Google Scholar 

  15. Da Costa, C.E., Werning, I.: On the optimality of the Friedman rule with heterogeneous agents and nonlinear income taxation. J. Political Econ. 116(1), 82–112 (2008)

    Article  Google Scholar 

  16. Doepke, M., Schneider, M.: Inflation as a redistribution shock: effects on aggregates and welfare (No. w12319). National Bureau of Economic Research (2006)

  17. Easterly, W., Fischer, S.: Inflation and the poor. J. Money Credit Bank 33, 160–178 (2001)

    Article  Google Scholar 

  18. Erosa, A., Ventura, G.: On inflation as a regressive consumption tax. J. Monet. Econ. 49(4), 761–795 (2002)

    Article  Google Scholar 

  19. Fischer, S.: The role of macroeconomic factors in growth. J. Monet. Econ. 32(3), 485–512 (1993)

    Article  Google Scholar 

  20. Funk, P., Kromen, B.: Inflation and innovation-driven growth. BE J. Macroecon. 10(1), 1–52 (2010)

    Google Scholar 

  21. Galli, R., Van der Hoeven, R.: Is inflation bad for income inequality? The Importance of the Initial Rate of Inflation, ILO Employment Paper, 2001/29 (2001)

  22. Hansen, B.E.: Threshold effects in non-dynamic panels: estimation, testing, and inference. J. Econom. 93(2), 345–368 (1999)

    Article  Google Scholar 

  23. Heer, B., Maußner, A.: Distributional effects of monetary policies in a new neoclassical model with progressive income taxation. Comput. Econ. Financ. 12, 1–26 (2005)

    Google Scholar 

  24. Hess, G.D., Morris, C.S.: The long-run costs of moderate inflation. Econ. Rev. Fed. Reserv. Bank Kansas City 81(2), 71 (1996)

    Google Scholar 

  25. Im, K.S., Pesaran, M.H., Shin, Y.: Testing for unit roots in heterogeneous panels. J. Econom. 115(1), 53–74 (2003)

    Article  Google Scholar 

  26. Jin, Y.: A note on inflation, economic growth, and income inequality. Macroecon. Dyn. 13(1), 138–147 (2009)

    Article  Google Scholar 

  27. Johnson, D.S., Shipp, S.: Inequality and the business cycle: a consumption viewpoint. Empir. Econ. 24(1), 173–180 (1999)

    Article  Google Scholar 

  28. Kremer, S., Bick, A., Nautz, D.: Inflation and growth: new evidence from a dynamic panel threshold analysis. Empir. Econ. 44(2), 861–878 (2013)

    Article  Google Scholar 

  29. Leigh, A.: How closely do top income shares track other measures of inequality?*. Econ. J. 117(524), F619–F633 (2007)

    Article  Google Scholar 

  30. Li, Q., Lin, J., Racine, J.S.: Optimal bandwidth selection for nonparametric conditional distribution and quantile functions. J. Bus. Econ. Stat. 31(1), 57–65 (2013)

    Article  Google Scholar 

  31. Maestri, V., Roventini, A.: Inequality and macroeconomic factors: a time-series analysis for a set of OECD countries. Available at SSRN 2181399 (2012)

  32. Menna, L., Tirelli, P.: Optimal inflation to reduce inequality. Rev. Econ. Dyn. 24, 79–94 (2017)

    Article  Google Scholar 

  33. Park, S.: Semiparametric instrumental variables estimation. J. Econom. 112(2), 381–399 (2003)

    Article  Google Scholar 

  34. Pindyck, R.S., Solimano, A.: Economic instability and aggregate investment. In: NBER Macroeconomics Annual 1993, vol. 8, pp. 259–318. MIT Press (1993)

  35. Ribba, A.: Short-run and long-run interaction between inflation and unemployment in the USA. Appl. Econ. Lett. 10(6), 373–376 (2003)

    Article  Google Scholar 

  36. Romer, C.D., Romer, D.H.: Monetary policy and the well-being of the poor (No. w6793). National Bureau of Economic Research (1998)

  37. Sarel, M.: Nonlinear effects of inflation on economic growth. IMF Staff Papers 43(1), 199–215 (1996)

    Article  Google Scholar 

  38. Scully, G.W.: Economic freedom, government policy and the trade-off between equity and economic growth. Public Choice 113(1–2), 77–96 (2002)

    Article  Google Scholar 

  39. Sun, H.: Monetary and fiscal policies in a heterogeneous-agent economy. Queen’s University, Department of Economics, Kingston (2012)

    Google Scholar 

  40. Sun, H.: Search, distributions, monetary and fiscal policy. Queen’s University, Department of Economics, Kingston (2011)

    Google Scholar 

  41. Vaona, A., Schiavo, S.: Nonparametric and semiparametric evidence on the long-run effects of inflation on growth. Econ. Lett. 94(3), 452–458 (2007)

    Article  Google Scholar 

  42. Wyplosz, C.: Do we know how low should inflation be. CEPR Discussion Paper No. 2722 (2000)

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Corresponding author

Correspondence to Stephen M. Miller.

Additional information

We would like to thank two anonymous referees for many helpful comments. However, any remaining errors are solely ours.



Appendix 1

Park (2003) considers a semiparametric regression model in which the error term is correlated with the nonparametric part. Although the model cannot eliminate the nonparametric part in the two-step estimation procedure, the author can still obtain a semiparametric estimator with consistency and asymptotic normality with two existing sets of instrumental variables which meet an orthogonality conditions.

The regression model takes the form

$$g_{t} = \phi x_{t} + f\left( {\pi_{t} } \right) + \varepsilon_{t} , t = 1, \ldots ,T$$


$$E[\varepsilon_{t} |\pi_{t} ] \ne 0$$

The author considers a case in which an error term, \(\varepsilon_{t} \in R,\) is correlated with a nonparametric part, say \(f\left( {\pi_{t} } \right)\), where \(f\) is an unknown function from \(R^{1}\) to \(R\).

Appendix 2

See Table 3.

Table 3 Results of Hansen (1999) threshold method

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Balcilar, M., Chang, S., Gupta, R. et al. The relationship between the inflation rate and inequality across U.S. states: a semiparametric approach. Qual Quant 52, 2413–2425 (2018).

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  • Income inequality
  • Inflation rate
  • Semiparametric instrumental variable estimation

JEL Classification

  • E31
  • D31
  • C14