Superior Forecasts of the U.S. Unemployment Rate Using a Nonparametric Method
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- Amos Golan & Jeffrey M. Perloff, 2004. "Superior Forecasts of the U.S. Unemployment Rate Using a Nonparametric Method," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 433-438, February.
References listed on IDEAS
- 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.
- Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero & Julián Andrada, "undated". "Exchange-rate forecasts with simultaneous nearest-neighbour methods: Evidence from the EMS," Working Papers 98-17, FEDEA.
- Alan A. Carruth & Mark A. Hooker & Andrew J. Oswald, 1998.
"Unemployment Equilibria And Input Prices: Theory And Evidence From The United States,"
The Review of Economics and Statistics,
MIT Press, vol. 80(4), pages 621-628, November.
- 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.
- Carruth, A.A. & Hooker, M.A. & Oswald, A.J., 1998. "Unemployment Equilibria and Input Prices: Theory and Evidence from the United States," The Warwick Economics Research Paper Series (TWERPS) 496, University of Warwick, Department of Economics.
- Christopher A. Sims, 1993.
"A Nine-Variable Probabilistic Macroeconomic Forecasting Model,"
NBER Chapters,in: Business Cycles, Indicators and Forecasting, pages 179-212
National Bureau of Economic Research, Inc.
- Christopher A. Sims, 1989. "A nine variable probabilistic macroeconomic forecasting model," Discussion Paper / Institute for Empirical Macroeconomics 14, Federal Reserve Bank of Minneapolis.
- Christopher A. Sims, 1992. "A Nine Variable Probabilistic Macroeconomic Forecasting Model," Cowles Foundation Discussion Papers 1034, Cowles Foundation for Research in Economics, Yale University.
- 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.
- 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 357-384, March.
- Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
- 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.
- 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.
- 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.
CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Christian Hutter & Enzo Weber, 2015.
"Constructing a new leading indicator for unemployment from a survey among German employment agencies,"
Taylor & Francis Journals, vol. 47(33), pages 3540-3558, July.
- Hutter, Christian & Weber, Enzo, 2013. "Constructing a new leading indicator for unemployment from a survey among German employment agencies," IAB Discussion Paper 201317, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
- D'Amuri, Francesco & Marcucci, Juri, 2009.
"'Google it!' Forecasting the US unemployment rate with a Google job search index,"
ISER Working Paper Series
2009-32, Institute for Social and Economic Research.
- Francesco D’Amuri & Juri Marcucci, 2010. "“Google it!”Forecasting the US Unemployment Rate with a Google Job Search index," Working Papers 2010.31, Fondazione Eni Enrico Mattei.
- D'Amuri, Francesco/FD & Marcucci, Juri/JM, 2009. ""Google it!" Forecasting the US unemployment rate with a Google job search index," MPRA Paper 18248, University Library of Munich, Germany.
- Regis Barnichon & Christopher J. Nekarda, 2012.
"The Ins and Outs of Forecasting Unemployment: Using Labor Force Flows to Forecast the Labor Market,"
Brookings Papers on Economic Activity,
Economic Studies Program, The Brookings Institution, vol. 43(2 (Fall)), pages 83-131.
- Regis Barnichon & Christopher J. Nekarda, 2013. "The ins and outs of forecasting unemployment: Using labor force flows to forecast the labor market," Finance and Economics Discussion Series 2013-19, Board of Governors of the Federal Reserve System (U.S.).
- Magnus Gustavsson & Pär Österholm, 2010. "The presence of unemployment hysteresis in the OECD: what can we learn from out-of-sample forecasts?," Empirical Economics, Springer, vol. 38(3), pages 779-792, June.
- Pär Österholm, 2010.
"Improving Unemployment Rate Forecasts Using Survey Data,"
Finnish Economic Papers,
Finnish Economic Association, vol. 23(1), pages 16-26, Spring.
- Österholm, Pär, 2009. "Improving Unemployment Rate Forecasts Using Survey Data," Working Papers 112, National Institute of Economic Research.
- Theodore Panagiotidis, 2010.
"An Out-of-Sample Test for Nonlinearity in Financial Time Series: An Empirical Application,"
Springer;Society for Computational Economics, vol. 36(2), pages 121-132, August.
- Theodore Panagiotidis, 2010. "An out-of-sample test for nonlinearity in financial time series: An empirical application," Discussion Paper Series 2010_08, Department of Economics, University of Macedonia, revised Jun 2010.
- Theodore Panagiotidis, 2010. "An Out-of-Sample Test for Nonlinearity in Financial Time Series: An Empirical Application," Working Paper series 20_10, Rimini Centre for Economic Analysis.
- Francesco D'Amuri & Juri Marcucci, 2012. "The predictive power of Google searches in forecasting unemployment," Temi di discussione (Economic working papers) 891, Bank of Italy, Economic Research and International Relations Area.
- Elena Olmedo, 2014. "Forecasting Spanish Unemployment Using Near Neighbour and Neural Net Techniques," Computational Economics, Springer;Society for Computational Economics, vol. 43(2), pages 183-197, February.
- Barnichon, Regis & Garda, Paula, 2016.
"Forecasting unemployment across countries: The ins and outs,"
European Economic Review,
Elsevier, vol. 84(C), pages 165-183.
- Barnichon, Régis & Garda, Paula, 2015. "Forecasting Unemployment across Countries: the Ins and Outs," CEPR Discussion Papers 10910, C.E.P.R. Discussion Papers.
- Ullrich Heilemann & Herman Stekler, 2010. "Perspectives on Evaluating Macroeconomic Forecasts," Working Papers 2010-002, The George Washington University, Department of Economics, Research Program on Forecasting.
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Keywordsembedding dimension; nonlinearity; nonparametric; unemployment rate;
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