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Forecasting the Colombian Unemployment Rate Using Labour Force Flows

Author

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  • Francisco Lasso-Valderrama

    () (Banco de la República de Colombia)

  • Héctor M. Zárate-Solano

    () (Banco de la República de Colombia)

Abstract

Accurate predictions of future magnitudes of the unemployment rate are crucial for monetary policy. This paper investigates whether the use of disaggregated household survey data improves the forecasts of the Colombian 13 cities unemployment rate. We conduct an outof-sample forecast exercise to compare the performance of a model that incorporates flows of workers across different states of the labour market to that of various macroeconomic non-structural models. The paper follows the approach proposed by Barnichon & Nekarda (2013). Our results indicate that the two-state-flow model provides substantially better forecasts of the unemployment rate over longer horizons (more than five months ahead). Additionally, when forecasts are combined, significant gains in every forecasting horizon occurs. This combined forecast shows a 23% reduction in overall RMSE. **** ABSTRACT: En este documento se evalúan los pronósticos de la tasa de desempleo urbana en Colombia utilizando varias metodologías. La primera se basa en las propiedades estadísticas de la serie de tiempo de la tasa de desempleo. La segunda considera la relación entre el crecimiento del producto y los cambios en el desempleo, conocida como la Ley de Okun. Finalmente, con base en los microdatos de las encuestas de hogares se calculan los flujos de trabajadores del mercado laboral para pronosticar la tasa de desempleo de acuerdo con Barnichon y Nekarda (2013). La evaluación de los pronósticos fuera de muestra indica que el modelo de dos estados (ocupado-desocupado) es el mejor en horizontes superiores a cinco meses. Por su parte, los modelos ARIMA y la Ley de Okun compiten en precisión en horizontes de corto plazo. Cabe destacar que la combinación de los modelos de pronóstico genera ganancias significativas en todos los horizontes, alcanzando una reducción global de 23% en la raíz del error cuadrático medio. Classification-JEL: C53, E24, E27, E3, J64

Suggested Citation

  • Francisco Lasso-Valderrama & Héctor M. Zárate-Solano, 2019. "Forecasting the Colombian Unemployment Rate Using Labour Force Flows," Borradores de Economia 1073, Banco de la Republica de Colombia.
  • Handle: RePEc:bdr:borrec:1073
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    References listed on IDEAS

    as
    1. Floros, Ch., 2005. "Forecasting the UK Unemployment Rate: Model Comparisons," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 2(4), pages 57-72.
    2. Regis Barnichon & Andrew Figura, 2010. "What drives movements in the unemployment rate? a decomposition of the Beveridge curve," Finance and Economics Discussion Series 2010-48, Board of Governors of the Federal Reserve System (US).
    3. Gary Solon & Ryan Michaels & Michael W. L. Elsby, 2009. "The Ins and Outs of Cyclical Unemployment," American Economic Journal: Macroeconomics, American Economic Association, vol. 1(1), pages 84-110, January.
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    5. Rothman Philip A, 2008. "Reconsideration of the Markov Chain Evidence on Unemployment Rate Asymmetry," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(3), pages 1-18, September.
    6. Raffaella Giacomini & Barbara Rossi, 2010. "Forecast comparisons in unstable environments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 595-620.
    7. Michael W. L. Elsby & Bart Hobijn & Ayşegül Şahin, 2013. "Unemployment Dynamics in the OECD," The Review of Economics and Statistics, MIT Press, vol. 95(2), pages 530-548, May.
    8. 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.
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    12. Shigeru Fujita, 2011. "Dynamics of worker flows and vacancies: evidence from the sign restriction approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(1), pages 89-121, January/F.
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    More about this item

    Keywords

    Forecasting; unemployment; VAR models; labour market flows; Pronósticos; desempleo; modelos VAR; flujos del mercado laboral;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search

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