Lozano, Francisco-Javier (2013): Evaluación de modelos de predicción para la venta de viviendas. Published in: Working Papers No. 73 (2013)
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Abstract
The aim of this working paper is assessing the predictive ability of different econometric models with forecasting windows of 3, 6 and 12 months, in order to improve housing sales forecasts published by the Chilean Chamber of Construction. To do so, five different families of models are estimated, among which Bayesian Vector Autorregresive (BVAR) stands due to a wide acceptance in the last decade. The main result of this paper shows that, in most cases, BVAR models provide more accurate predictions than classical models. This is consistent with the evidence found in several macroeconomic and sectoral applications of this type of models.
Item Type: | MPRA Paper |
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Original Title: | Evaluación de modelos de predicción para la venta de viviendas |
English Title: | Evaluation of forecasting models for house sales |
Language: | Spanish |
Keywords: | forecasting, housing, real estate |
Subjects: | R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R3 - Real Estate Markets, Spatial Production Analysis, and Firm Location > R31 - Housing Supply and Markets |
Item ID: | 118652 |
Depositing User: | Francisco-Javier Lozano Navarro |
Date Deposited: | 21 Sep 2023 07:32 |
Last Modified: | 21 Sep 2023 07:32 |
References: | Banbura, M., Giannone, D., & Reichlin, L. (2010). Large Bayesian Vector Auto Regressions. Journal of Applied Econometrics, 25(1), 71–92. Bernanke, B., Boivin, J., & Eliasz, P. (2005). Measuring monetary policy: a factor augmented autoregressive (FAVAR) approach. Quarterly Journal of Economics, 120, 387–442. Box, G., & Jenkins, G. (1970). Time Series Analysis: Forecasting and Control. Holden Day, San Francisco. Canova, F. (1999). Vector Autoregressive Models: Specification, Estimation, Inference, and Forecasting. Handbook of Applied Econometrics. Volume I: Macroeconomics (M. Hashem Pesaran and Michael R. Wickens.). Blackwell Publishing. Canova, F. (2007). Bayesian VARs. Methods for Applied Macroeconomic Research (pp. 351–394). Princeton University Press. Ciccarelli, M., & Rebucci, A. (2003). Bayesian VARs: A Survey of the Recent Literature with an Application to the European Monetary System. Working Paper WP/03/102, International Monetary Fund. Crone, T. M., & McLaughlin, M. P. (1999). A Bayesian VAR Forecasting Model for the Philadelphia Metropolitan Area. Working Paper No. 99-7, Federal Reserve Bank of Philadelphia. De Boef, S., & Granato, J. (1999). Testing for Cointegrating Relationships with Near-Integrated Data. Political Analysis, 8(1), 99–117. Demers, F. (2005). Modelling and Forecasting Housing Investment: The Case of Canada. Working Paper 2005-41, Bank of Canada. Diebold, F. X. (2007). Forecasting with Regression Models. Elements of forecasting (4th ed., pp. 219–256). Thomson/South-Western. Diebold, F. X., & Mariano, R. (1995). Comparing Predictive Accuracy. Journal of Business & Economic Statistics, 13(3), 253–263. Doan, T., Litterman, R., & Sims, C. A. (1983). Forecasting and Conditional Projection Using Realistic Prior Distributions. NBER Working Paper No. 1202. Dua, P., Miller, S. M., & Smyth, D. J. (1996). Using Leading Indicators to Forecast US Home Sales in a Bayesian VAR Framework. Working papers 1996-08, University of Connecticut, Department of Economics. Engle, R. F., & Granger, C. W. J. (1987). Co-integration and Error Correction: Representation, Estimation, and Testing. Econometrica, Econometric Society, 55(2), 251–76. Garcia-Ferrer, A., Highfield, R.A., Palm, F., & Zellner, A. (1987). Macroeconomic Forecasting Using Pooled International Data. Journal of Business & Economic Statistics, 5(1), 53–67. Giannone, D., Lenza, M., & Primiceri, G. E. (2012). Prior Selection for Vector Autoregressions. NBER Working Paper No. 18467. González, W. (2012). Un Gran VAR Bayesiano para la Economía Chilena. Documento de Trabajo No 653, Banco Central de Chile. Gupta, R., Jurgilas, M., Kabundi, A., & Miller, S. M. (2009). Monetary Policy and Housing Sector Dynamics in a Large-Scale Bayesian Vector Autoregressive Model. Working Paper 2009-19, Department of Economics Working Paper Series, University of Connecticut. Gupta, R., & Sichei, M. M. (2006). A BVAR Model for the South African Economy. Working Papers 200612, University of Pretoria, Department of Economics. Hjalmarsson, E., & Österholm, P. (2007). Testing for Cointegration Using the Johansen Methodology when Variables are Near-Integrated. IMF Working Paper WP/07/141. Jaramillo, P. (2009). Estimación de VAR bayesianos para la economía chilena. Revista de Análisis Económico, 24(1), 101–126. Johnston, J., & DiNardo, J. (1997). Univariate Time Series Modeling. Econometric Methods (4th ed., pp. 204–243). McGraw-Hill. Joiner, A. (2001). Monetary policy effects in an Australian Bayesian VAR model. Working Paper, Departament of Econometrics and Business Statistics, Monash University. Kadiyala, K. R., & Karlsson, S. (1997). Numerical Methods For Estimation and Inference in Bayesian VAR Models. Journal of Applied Econometrics, 12, 99–132. Keller, E. (2007). Classical and Bayesian Methods for the VAR Analysis: International Comparisons. Rivista di Politica Economica, 97(6), 149–202. Kenny, G., Meyler, A., & Quinn, T. (1998). Bayesian Var Models for Forecasting Irish Inflation. Research Technical Papers 4/RT/98, Central Bank of Ireland. Koop, G. (2003). Bayesian Econometrics. John Wiley & Sons Ltd. Koop, G., & Korobilis, D. (2009). Bayesian Multivariate Time Series Methods for Empirical Macroeconomics. Working Paper Series 47_09, The Rimini Centre for Economic Analysis. Leamer, E. E. (2007). Housing is the business cycle. NBER Working Paper No. 13428. Litterman, R. (1979). Techniques of Forecasting Using Vector Autoregressions. Working Paper No. 15, Federal Reserve Bank of Minneapolis. Litterman, R. (1986). Forecasting With Bayesian Vector Autoregressions - Five Years of Experience. Journal of Business & Economic Statistics, 4(1), 25–38. Llosa, G., Tuesta, V., & Vega, M. (2006). Un modelo de proyección BVAR para la inflación peruana. Estudios Económicos No 13, Banco Central de Reserva del Perú. Phillips, P. C. B. (1988). Regression Theory for Near-Integrated Time Series. Econometrica, 56(5), 1021–1043. Robertson, J. C., & Tallman, E. W. (1999). Vector Autoregressions: Forecasting and Reality. Economic Review, First Quarter 1999, Federal Reserve of Atlanta. Sevinç, V., & Ergün, G. (2009). Usage of different prior distributions in bayesian vector autoregressive models. Hacettepe Journal of Mathematics and Statistics, 38(1), 85–93. Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–47. Sims, C. A. (1988). Bayesian skepticism on unit root econometrics. Discussion Paper 3, Institute for Empirical Macroeconomics, Federal Reserve Bank of Minneapolis. Sims, C. A., & Zha, T. (1996). Bayesian Methods for Dynamic Multivariate Models. Working Paper 96-13, Federal Reserve Bank of Atlanta. Todd, R. M. (1988a). Implementing Bayesian Vector Autoregressions. Working Paper 384, Federal Reserve Bank of Minneapolis. Todd, R. M., & Morande, F. G. (1988a). A BVAR Forecasting Model for the Chilean Economy. Revista de Análisis Económico, 3(2), 45–78. Zellner, A., & Hong, C. (1989). Forecasting international growth rates using Bayesian shrinkage and other procedures. Journal of Econometrics, 40(1), 183–202. Zellner, Arnold, & Tobias, J. (2000). A Note on Aggregation, Disaggregation and Forecasting Performance. Staff General Research Papers, Iowa State University, Department of Economics. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/118652 |