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Superior Forecasts of the U.S. Unemployment Rate Using a Nonparametric Method

  • Golan, Amos
  • Perloff, Jeffrey M.

We use a nonlinear, nonparametric method to forecast the unemployment rates. We compare these forecasts to several linear and nonlinear parametric methods based on the work of Montgomery et al. (1998) and Carruth et al. (1998). Our main result is that, due to the nonlin-earity in the data generating process, the nonparametric method outperforms many other well-known models, even when these models use more information. This result holds for forecasts based on quarterly and on monthly data.

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Paper provided by Department of Agricultural & Resource Economics, UC Berkeley in its series Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series with number qt2bw559zk.

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Date of creation: 01 Jan 2002
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Handle: RePEc:cdl:agrebk:qt2bw559zk
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  1. Carruth,a. & Hooker, N. & Oswald,A., 1997. "Unemployment Equilibria and Input Prices: Theory and Evidence from the United States," Papers 22, Centre for Economic Performance & Institute of Economics.
  2. Mulhern, Francis J. & Caprara, Robert J., 1994. "A nearest neighbor model for forecasting market response," International Journal of Forecasting, Elsevier, vol. 10(2), pages 191-207, September.
  3. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
  4. Fernandez-Rodriguez, Fernando & Sosvilla-Rivero, Simon & Andrada-Felix, Julian, 1999. "Exchange-rate forecasts with simultaneous nearest-neighbour methods: evidence from the EMS," International Journal of Forecasting, Elsevier, vol. 15(4), pages 383-392, October.
  5. Ramsey James B., 1996. "If Nonlinear Models Cannot Forecast, What Use Are They?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 1(2), pages 1-24, July.
  6. Christopher A. Sims, 1989. "A nine variable probabilistic macroeconomic forecasting model," Discussion Paper / Institute for Empirical Macroeconomics 14, Federal Reserve Bank of Minneapolis.
  7. Agnon, Yehuda & Golan, Amos & Shearer, Matthew, 1999. "Nonparametric, nonlinear, short-term forecasting: theory and evidence for nonlinearities in the commodity markets," Economics Letters, Elsevier, vol. 65(3), pages 293-299, December.
  8. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
  9. Fernandez-Rodriguez, Fernando & Sosvilla-Rivero, Simon, 1998. "Testing nonlinear forecastability in time series: Theory and evidence from the EMS," Economics Letters, Elsevier, vol. 59(1), pages 49-63, April.
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