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Modeling Unemployment Rates by Race and Gender: A Nonlinear Time Series Approach

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Author Info

  • Bradley Ewing
  • William Levernier
  • Farooq Malik

Abstract

This paper presents an unemployment rate model that provides insight into how the time series behavior, in terms of both the mean and volatility, of the unemployment rates of black males, white males, black females, and white females differ. Demographic differences in the unemployment rate response are likely to occur if certain demographic groups face discrimination or if different demographic groups gave differing investments in human capital, for example. In addition, there may be differences in other characteristics of the groups, such as differences in the age of distribution or in the marital status distribution. This paper develops and estimates a model to determine whether or not differences in unemployment rate volatility among demographic groups actually exist, utilizing an ARCH-class (autoregressive conditional heteroscedasticity) model. The findings suggest that conditional variance is symmetric for white females, black females, and black males, but is asymmetric for white males. In particular, the findings indicate that innovations increase the conditional volatility changes in each group's unemployment rate and have symmetric effects for all groups except white males.

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File URL: http://college.holycross.edu/RePEc/eej/Archive/Volume31/V31N3P333_347.pdf
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Bibliographic Info

Article provided by Eastern Economic Association in its journal Eastern Economic Journal.

Volume (Year): 31 (2005)
Issue (Month): 3 (Summer)
Pages: 333-347

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Handle: RePEc:eej:eeconj:v:31:y:2005:i:3:p:333-347

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Postal: c/o Dr. Alexandre Olbrecht, The Anisfield School of Business 205, Ramapo College, 505 Ramapo Valley Road, Ramapo, New Jersey 07430, USA
Phone: (201) 684-7346
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Web page: http://www.ramapo.edu/eea/journal.html
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  1. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Clara Vega, 2002. "Micro Effects of Macro Announcements: Real-Time Price Discovery in Foreign Exchange," NBER Working Papers 8959, National Bureau of Economic Research, Inc.
  2. Rabemananjara, R & Zakoian, J M, 1993. "Threshold Arch Models and Asymmetries in Volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(1), pages 31-49, Jan.-Marc.
  3. Rothman, Philip, 1991. "Further evidence on the asymmetric behavior of unemployment rates over the business cycle," Journal of Macroeconomics, Elsevier, vol. 13(2), pages 291-298.
  4. Robert F. Engle & Victor K. Ng, 1991. "Measuring and Testing the Impact of News on Volatility," NBER Working Papers 3681, National Bureau of Economic Research, Inc.
  5. James Payne & Bradley Ewing & Erik George, 1999. "Time series dynamics of US State unemployment rates," Applied Economics, Taylor & Francis Journals, vol. 31(11), pages 1503-1510.
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Cited by:
  1. Dimitrios Bakas & Evangelia Papapetrou, 2014. "Unemployment by Gender: Evidence from EU Countries," International Advances in Economic Research, Springer, vol. 20(1), pages 103-111, February.
  2. Peiró, Amado & Belaire-Franch, Jorge & Gonzalo, Maria Teresa, 2012. "Unemployment, cycle and gender," Journal of Macroeconomics, Elsevier, vol. 34(4), pages 1167-1175.
  3. Herve Queneau & Amit Sen, 2009. "Regarding the unemployment gap by race and gender in the United States," Economics Bulletin, AccessEcon, vol. 29(4), pages 2749-2757.
  4. Queneau, Hervé & Sen, Amit, 2012. "On the structure of US unemployment disaggregated by race, ethnicity, and gender," Economics Letters, Elsevier, vol. 117(1), pages 91-95.

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