Abstract
This paper examines the impact of unemployment and inflation on family income shares. Unemployment and inflation are decomposed into their structural (long-term), cyclical (short-term), anticipated and unanticipated components, respectively. I propose a new framework to analyze family income quintile shares by using a two-state Markov-switching model, also known as Hamilton’s regime-switching model. The benefit of using a Markov-switching model is that it permits capturing complex dynamic behavior of non-linear time series macroeconomic variables. The switching mechanism follows a first-order Markov chain of unobservable state variables and subsequent estimated conditional transition probabilities. This paper applies a two-state regime-switching process to capture the asymmetrical effects of unemployment and inflation on family income shares. The two states of family income quintile shares are state 1 (lower income) and state 2 (upper income). This approach differs from previous studies because it examines income inequality within each quintile rather than between quintiles. It is well documented in the literature that there is income inequality between lower and higher income quintiles. Therefore, the analysis of income inequality within the quintile allows for greater insight into changes in family income share corresponding to changes in the state variables. The general findings are that unemployment has adverse effects on lower income shares while inflation acts like a progressive tax on higher income shares.
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Notes
Stagflation led to the emergence of the misery index. This index, which is the simple sum of the inflation rate and unemployment rate, served as a tool to show just how badly people were feeling when stagflation hit the economy.
The unemployment rate represents the number of unemployed as a percentage of the labor force. Labor force data are restricted to people 16 years of age and older, who currently reside in 1 of the 50 states or the District of Columbia, who do not reside in institutions (e.g., penal and mental facilities, homes for the aged), and who are not on active duty in the Armed Forces).
The GDP implicit price deflator, or GDP deflator, measures changes in the prices of goods and services produced in the United States, including those exported to other countries. Prices of imports are excluded.
References
Ang, A., & Timmermann, A. (2012). Regime changes and financial markets. Annual Review of Financial Economics, 4(1), 313–337.
Ayala, Luis, Cantó, Olga and Rodríguez, Juan. (2011). Poverty and the business cycle: The role of the intra-household distribution of unemployment, no 222. Working Papers, ECINEQ, Society for the Study of Economic Inequality. http://www.ecineq.org/milano/WP/ECINEQ2011-222.pdf.
Beach, C. M. (1976). Cyclical impacts on the personal distribution of income. Annals of Economic and Social Measurement, 5, 29–52.
Bernanke, B. S. (2019). In O. Blanchard & L. H. Summers (Eds.), Monetary policy in a New Era, in evolution or revolution? Rethinking macroeconomic policy after the great recession (1st ed., pp. 3–47). Cambridge, MA: The MIT Press.
Bivens, J. (2015). Gauging the impact of the fed on inequality during the great recession. Hutchins Center on Fiscal and Monetary Policy at the Brookings Institution, Hutchins Center Working Paper #12, Washington, DC https://www.brookings.edu/research/gauging-the-impact-of-the-fed-on-inequality-during-the-great-recession/.
Blank, R., & Blinder, A. (1986). Macroeconomics, income distribution and poverty. In S. Danziger & D. Weinberg (Eds.), Fighting poverty (pp. 180–208). Cambridge, MA: Harvard University Press.
Blinder, A., & Esaki, H. (1978). Macroeconomic activity and income distribution in the postwar United States. The Review of Economics and Statistics, 60(4), 604–609.
Board of Governors of the Federal Reserve System. (1979). Transcript, federal open market committee meeting. http://www.federalreserve.gov/monetarypolicy/files/FOMC19790417meeting.pdf
Brooks, C., & Tsolacos, S. (1999). The impact of economic and financial factors on UK property performance. Journal of Property Research, 16(2), 139–152.
Cairo, I., & Jae S. (2018). “Income Inequality, Financial Crises, and Monetary Policy,” Finance and Economics Discussion Series 2018-048. Washington: Board of Governors of the Federal Reserve System, https://doi.org/10.17016/FEDS.2018.048.
Congressional Budget Office Report. (2018). The distribution of household income, 2014. Average income before and after mean-tested transfers and federal taxes, by income group, 2014. Available at: https://www.cbo.gov/system/files/115th-congress-2017-2018/reports/53597-distribution-household-income-2014.pdf.
Dickey, D., & Fuller, W. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366), 427–431.
DiPietro, W. R., Anoruo, E., & Sawhney, B. (2005). Macroeconomic determinants of the income shares of the very highest income groups. Review of Applied Economics, 1(1), 19.
Doepke, M., & Schneider, M. (2006). Inflation and the redistribution of nominal wealth. Journal of Political Economy, 114(6), 1069–1097.
Dolado, Juan and Motyovszki, Gergo and Pappa, Evi, (2018). Monetary policy and inequality under labor market frictions and capital-skill complementarity. CEPR discussion paper no. DP12734. Available at SSRN: https://ssrn.com/abstract=3130172
Donovan, Sarah A. & Labonte, Marc & Dalaker, Joseph. (2016). The U.S. income distribution: Trends and issues. Congressional Research Service Report, 7-5700, R44705. Available at: https://fas.org/sgp/crs/misc/R44705.pdf
Duprey, Thibaut and Klaus, Benjamin, (2017). How to predict financial stress? An assessment of Markov switching models. Working Paper No. 2057.
Engel, C. (1994). Can the Markov switching model forecast exchange rates? Journal of International Economics, 36, 151–165 North-Holland.
Federal Reserve Bank of St. Louis (2019a). Gross domestic product: Implicit price deflator [GDPDEF]. Retrieved from FRED http://fred.stlouisfed.org/series/GDPDEF
Federal Reserve Bank of St. Louis (2019b). Unemployment rate [UNRATE]. Retrieved from FRED, Federal Reserve Bank of St. Louis. https://fred.stlouisfed.org/series/UNRATE
Geske, R., & Roll, R. (1983). The fiscal and monetary linkage between Stock returns and inflation. The Journal of Finance, 38(1), 1–33.
González, M., Jareño, F., & Skinner, F. S. (2016). Interest and inflation risk: Investor behavior. Frontiers in Psychology, 7(390), 1–18.
Goodwin, T. (1993). Business-cycle analysis with a Markov-switching model. Journal of Business & Economic Statistics, 11(3), 331–339.
Guidolin, M. (2011). Markov switching models in empirical finance. In D. Drukker (Ed.), Missing data methods: Time-series methods and applications. Advances in econometrics (Vol. 27 Part (2), pp. 1–86). Bingley: Emerald Group Publishing Limited.
Hamilton, J. D. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica, 57, 357–384.
Heer, B., & Süssmuth, B. (2003). Inflation and wealth distribution, CESifo. Working paper, no. 835. Munich: Center for Economic Studies and Ifo Institute (CESifo). Available at: https://www.cesifo.org/DocDL/cesifo_wp835.pdf
Kaliski, S. F., & Smith, D. C. (1973). Inflation, unemployment and incomes policy. The Canadian Journal of Economics/Revue Canadienne D’Economique, 6(4), 574–591.
Kontolemis, Z. G. (2001). Analysis of the US business cycle with a vector-Markov-switching model. Journal of Forecasting, John Wiley & Sons, Ltd., 20(1), 47–61.
Liu, C. H., Hartzell, D. J., & Hoesli, M. E. (1997). International evidence on real estate securities as an inflation hedge [electronic version]. Retrieved [December 2019], from Cornell University, School of Hospitality Administration site: http://scholarship.sha.cornell.edu/articles/276
McCall, L., & Percheski, C. (2010). Income inequality: New trends and research directions. Annual Review of Sociology, 36(1), 329–347.
Mocan, H. N. (1999). Structural unemployment, cyclical unemployment, and income inequality. The Review of Economics and Statistics, 81(1), 122–134.
Nelson, C., Piger, J., & Zivot, E. (2001). Markov regime switching and unit-root tests. Journal of Business & Economic Statistics, 19(4), 404–415.
Noah, T. (2012). The great divergence: America’s growing inequality crisis and what. We can do about it (pp. 1–370). New York: Bloomsbury Press.
Palmer, J. L. (1973). Inflation, unemployment and poverty. Lexington: D. C. Heath.
Parker, S. (1998). Income inequality and the business cycle: A survey of the evidence and some new results. Journal of Post Keynesian Economics, 21(2), 201–225.
Perron, P. (1989). The great crash, the oil price shock and the unit root hypothesis. Econometrica, 57, 1361–1401.
Pfeffer, F., Danziger, S., & Schoeni, R. (2013). Wealth disparities before and after the great recession. The Annals of the American Academy of Political and Social Science, 650, 98–123.
Piketty, T., & Saez, E. (2003). Income inequality in the United States, 1913–1998. The Quarterly Journal of Economics, 118(1), 1–39.
Piketty, T., & Saez, E. (2007). How progressive is the U.S. Federal tax System? A historical and international perspective. The Journal of Economic Perspectives, 21(1), 3–24.
Powers, E. (1995). Inflation, unemployment and poverty revisited. Economic Review of the Federal Reserve Bank of Cleveland, 2, 2–13.
Redbird, B., & Grusky, D. B. (2016). Distributional effects of the great recession: Where has all the sociology gone? Annual Review of Sociology, 42, 185–215.
Romer, David & Romer, Christina D. (1999). Monetary policy and the well-being of the poor. Economic Review, Federal Reserve Bank of Kansas City, 84 issue qi, pages 21–49. Available at: https://www.kansascityfed.org/PUBLICAT/ECONREV/PDF/1q99romr.pdf
Smeeding, T., Thompson, J., Levanon, A., & Burak, E. (2011). Poverty and income inequality in the early stages of the great recession. In D. Grusky, B. Western, & C. Wimer (Eds.), The great recession (pp. 82–126). New York: Russell Sage Foundation.
Solt, F. (2008). Economic inequality and democratic political engagement. American Journal of Political Science, 52(1), 48–60.
StataCorp. (2019). Stata 16 time-series reference manual. College Station: Stata Press Available at. https://www.stata.com/manuals/ts.pdf.
Stock, J. H. (1994). Unit roots, structural breaks and trends. In R. F. Engle & D. MacFaden (Eds.), Handbook of econometrics (Vol. 4, pp. 2740–2841). Amsterdam: Elsevier.
Tobin, James. (1993). Poverty in relation to macroeconomic trends, cycles, and policies. Cowles Foundation discussion papers 1030R. Cowles Foundation for Research in Economics, Yale University. http://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=28AE9E5C4E52BC02920F39A6D977928A?doi=10.1.1.193.7462&rep=rep1&type=pdf
United States Census Bureau. (2019). Historical income tables: Families: table F-2. Share of aggregate income received by each fifth and top 5 percent of families, all races: 1947 to 2018. Data retrieved July 2, 2019. Available at: https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-income-families.html
Yellen, J. L. (2016). Perspectives on inequality and opportunity from the survey of consumer finances. RSF: The Russell Sage Foundation Journal of the Social Sciences, 2(2), 44–59.
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Papanikolaou, N. Markov-Switching Model of Family Income Quintile Shares. Atl Econ J 48, 207–222 (2020). https://doi.org/10.1007/s11293-020-09664-4
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DOI: https://doi.org/10.1007/s11293-020-09664-4