Abstract
Recent economic crises have posed important challenges for forecasting. Models estimated pre-crisis may perform badly when normal economic relationships have been disrupted. Meanwhile, forecasting, especially in central banks, is increasingly based on a suite of models, following two main approaches: structural (DSGE) and reduced form. The challenge remains to identify which model – or combination of models – is likely to make better forecasts in a changing environment. We explore this issue by assessing the forecasting performance of combinations of a medium-scale DSGE model with standard reduced-form methods applied to the Spanish economy and a reference period that includes both the great recession and the sovereign debt crisis. Our findings suggest that: (i) the mean reverting properties of the DSGE model cause it to underestimate the growth of real variables following the inclusion of crisis episodes in the estimation period; (ii) despite this, reduced-form VARs benefit from the imposition of an economic prior from the structural model; but (iii) pooling information in the form of variables extracted from the structural model with (B)VAR methods does not improve forecast accuracy. By analysing the quantiles of the predictive distributions, we also provide evidence that merging models can help improve the forecast in a context including crisis episodes.
References
Adolfson, M., S. Laséen, J. Linďé, and M. Villani. 2007. “Bayesian Estimation of an Open Economy DSGE Model with Incomplete Pass-Through.” Journal of International Economics 72 (2): 481–511. https://doi.org/10.1016/j.jinteco.2007.01.003.Search in Google Scholar
Amisano, G., and R. Giacomini. 2007. “Comparing Density Forecasts via Weighted Likelihood Ratio Tests.” Journal of Business & Economic Statistics 25 (2): 177–90. https://doi.org/10.1198/073500106000000332.Search in Google Scholar
Andrés, J., P. Burriel, and A. Estrada. 2006. “BEMOD: A DSGE Model for the Spanish Economy and the Rest of the Euro Area.” Banco de España Working Paper No. 0631.10.2139/ssrn.949147Search in Google Scholar
Andrés, J., S. Hurtado, E. Ortega, and C. Thomas. 2010. “Spain in the Euro: A General Equilibrium Analysis.” SERIEs 1 (1–2): 67–95. https://doi.org/10.1007/s13209-009-0015-6.Search in Google Scholar
Andrés, J., O. Arce, and C. Thomas. 2017. “Structural Reforms in a Debt Overhang.” Journal of Monetary Economics 88: 15–34. https://doi.org/10.1016/j.jmoneco.2017.05.004.Search in Google Scholar
Blanchard, O. J., and C. M. Kahn. 1980. “The Solution of Linear Difference Models under Rational Expectations.” Econometrica: Journal of the Econometric Society 48 (5): 1305–11, https://doi.org/10.2307/1912186.Search in Google Scholar
Boscà, J. E., A. Díaz, R. Doménech, E. Pérez, and L. Puch. 2007. “The REMSDB Macroeconomic Database of the Spanish Economy.” Ministerio de Economia y Hacienda Working Paper No. 2007-04.Search in Google Scholar
Boscà, J. E., A. Díaz, R. Doménech, J. Ferri, E. Pérez, and L. Puch. 2010. “A Rational Expectations Model for Simulation and Policy Evaluation of the Spanish Economy.” SERIEs 1 (1–2): 135–69. https://doi.org/10.1007/s13209-009-0013-8.Search in Google Scholar
Boscà, J. E., A. Díaz, R. Doménech, J. Feri, and J. F. Rubio-Ramírez. 2018. “Financial and Fiscal Shocks in the Great Recession and Recovery of the Spanish Economy.” FEDEA Working Paper No. 2018-05.Search in Google Scholar
Burriel, P., J. Fernández-Villaverde, and J. F. Rubio-Ramírez. 2010. “MEDEA: A DSGE Model for the Spanish Economy.” SERIEs 1 (1–2): 175–243.10.1007/s13209-009-0011-xSearch in Google Scholar
Cai, M., M. Del Negro, M. P. Giannoni, A. Gupta, P. Li, and E. Moszkowski. 2018. “DSGE Forecasts of the Lost Recovery.” Federal Reserve Bank of New York Staff Reports No. 844.10.2139/ssrn.3138589Search in Google Scholar
Christiano, L. J., M. Eichenbaum, and C. L. Evans. 2005. “Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy.” Journal of Political Economy 113 (1): 1–45. https://doi.org/10.1086/426038.Search in Google Scholar
Del Negro, M., and F. Schorfheide. 2004. “Priors from General Equilibrium Models for VARs.” International Economic Review 45 (2): 643–73. https://doi.org/10.1111/j.1468-2354.2004.00139.x.Search in Google Scholar
Del Negro, M., and F. Schorfheide. 2006. “How Good Is what You’ve Got? DGSE-VAR as a Toolkit for Evaluating DSGE Models.” Federal Reserve Bank of Atlanta Economic Review 91 (2): 21–37.Search in Google Scholar
Del Negro, M., and F. Schorfheide. 2008. “Forming Priors for DSGE Models (And How it Affects the Assessment of Nominal Rigidities).” Journal of Monetary Economics 55 (7): 1191–208. https://doi.org/10.1016/j.jmoneco.2008.09.006.Search in Google Scholar
Del Negro, M., F. Schorfheide, F. Smets, and R. Wouters. 2007. “On the Fit of New Keynesian Models.” Journal of Business & Economic Statistics 25 (2): 123–43. https://doi.org/10.1198/073500107000000016.Search in Google Scholar
Del Negro, M., Raiden B. Hasegawa, and F. Schorfheide. 2016. “Dynamic Prediction Pools: An Investigation of Financial Frictions and Forecasting Performance.” Journal of Econometrics 192 (2): 391–405. https://doi.org/10.1016/j.jeconom.2016.02.006.Search in Google Scholar
Diebold, F. X. 1998. “The Past, Present, and Future of Macroeconomic Forecasting.” The Journal of Economic Perspectives 12 (2): 175–92. https://doi.org/10.1257/jep.12.2.175.Search in Google Scholar
Diebold, F. X., and R. S. Mariano. 1995. “Comparing Predictive Accuracy.” Journal of Business & Economic Statistics 13 (3): 253–63. https://doi.org/10.2307/1392185.Search in Google Scholar
Diebold, F. X., A. Gunther, and A. S. Tay. 1998. “Evaluating Density Forecasts with Applications to Financial Risk Management.” International Economic Review 39 (4): 863–83. https://doi.org/10.2307/2527342.Search in Google Scholar
Edge, R. M., and R. S. Gürkaynak. 2010. “How Useful Are Estimated DSGE Model Forecasts for Central Bankers?” CEPR Disussion Paper 8158.10.2139/ssrn.1810075Search in Google Scholar
Edge, R. M., M. T. Kiley, and J. P. Laforte. 2010. “A Comparison of Forecast Performance between Federal Reserve Staff Forecasts, Simple Reduced-form Models, and a DSGE Model.” Journal of Applied Econometrics 25 (4): 720–54. https://doi.org/10.1002/jae.1175.Search in Google Scholar
Elliott, G., and A. Timmermann. 2005. “Optimal Forecast Combination Using under Regime Switching.” International Economic Review 46: 1081–102. https://doi.org/10.1111/j.1468-2354.2005.00361.x.Search in Google Scholar
Erceg, C. J., L. Guerrieri, and C. J. Gust. 2006. “SIGMA: A New Open Economy Model for Policy Analysis.” International Journal of Central Banking 2 (1): 1–50. https://doi.org/10.17016/ifdp.2005.835r.Search in Google Scholar
Fernández-de-Córdoba, G., and J. L. Torres. 2011. “Forecasting the Spanish Economy with an Augmented VAR–DSGE Model.” SERIEs 2 (3): 379–99. https://doi.org/10.1007/s13209-010-0036-1.Search in Google Scholar
Giacomini, R. 2013. “The Relationship between DSGE and VAR Models.” In Advances in Econometrics in VAR Models in Macroeconomics – New Developments and Applications: Essays in Honor of Christopher A. Sims, 32, 1–25. Bingley: Emerald Group Publishing Limited.10.1108/S0731-9053(2013)0000031001Search in Google Scholar
Giacomini, R., and B. Rossi. 2010. “Forecast Comparisons in Unstable Environments.” Journal of Applied Econometrics 25 (4): 595–620. https://doi.org/10.1002/jae.1177.Search in Google Scholar
Giacomini, R., and H. White. 2006. “Tests of Conditional Predictive Ability.” Econometrica 74 (6): 1545–78. https://doi.org/10.1111/j.1468-0262.2006.00718.x.Search in Google Scholar
Giannone, D., M. Lenza, and G. Primiceri. 2015. “Prior Selection for Vector Autoregressions.” The Review of Economics and Statistics 97 (2): 436–51. https://doi.org/10.1162/rest_a_00483.Search in Google Scholar
Gómez-González, P., and D. M Rees. 2018. “Same Spain, Less Pain?” European Economic Review 110 (C): 78–2107. https://doi.org/10.1016/j.euroecorev.2018.08.006.Search in Google Scholar
Goodwin, P. 2000. “Correct or Combine? Mechanically Integrating Judgmental Forecasts with Statistical Methods.” International Journal of Forecasting 16: 261–75. https://doi.org/10.1016/s0169-2070(00)00038-8.Search in Google Scholar
Gürkaynak, R. S., B. Kısacıkoglu, and B. Rossi. 2013. “Do DSGE Models Forecast More Accurately Out-Of-Sample Than VAR Models?” CEPR Discussion Paper No. 9576.10.1108/S0731-9053(2013)0000031002Search in Google Scholar
Hall, S. G., and J. Mitchell. 2007. “Combining Density Forecasts.” International Journal of Forecasting 23 (1): 1–13. https://doi.org/10.1016/j.ijforecast.2006.08.001.Search in Google Scholar
Harrison, R., K. Nikolov, M. Quinn, G. Ramsay, A. Scott, and R. Thomas. 2005. The Bank of England Quarterly Model. London: Publications Group, Bank of England.Search in Google Scholar
Kilponen, J., and A. Ripatti. 2006. Introduction to AINO. Mimeo: Bank of Finland.Search in Google Scholar
King, R. G., and S. T. Rebelo. 1999. “Resuscitating Real Business Cycles.” In Handbook of Macroeconomics, 1, 927–1007. Amsterdam: Elsevier.10.1016/S1574-0048(99)10022-3Search in Google Scholar
Kortelainen, M. 2002. “EDGE: A Model of the Euro Area with Applications to Monetary Policy.” Bank of Finland Studies E23.Search in Google Scholar
Lees, K., T. Matheson, and C. Smith. 2011. “Open Economy Forecastsing with a DSGE–VAR: Head to Head with the RBNZ Published Forecasts.” International Journal of Forecasting 27 (1): 512–28. https://doi.org/10.1016/j.ijforecast.2010.01.008.Search in Google Scholar
Litterman, R. B. 1986a. “A Statistical Approach to Economic Forecasting.” Journal of Business & Economic Statistics 4 (1): 1–4. https://doi.org/10.2307/1391378.Search in Google Scholar
Litterman, R. B. 1986b. “Forecasting with Bayesian Vector Autoregressions—Five Years of Experience.” Journal of Business & Economic Statistics 4 (1): 25–38. https://doi.org/10.2307/1391384.Search in Google Scholar
Manzan, S., and D. Zerom. 2013. “Are Macroeconomic Variables Useful for Forecasting the Distribution of U.S. Inflation?” International Journal of Forecasting 29 (3): 469–78. https://doi.org/10.1016/j.ijforecast.2013.01.005.Search in Google Scholar
Mincer, J. A., and V. Zarnowitz. 1969. “The Evaluation of Economic Forecasts.” In Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance, 3–46. New York: NBER.Search in Google Scholar
Murchison, S., and A. Rennison. 2006. “ToTEM: The Bank of Canada’s New Quarterly Projection Model.” Bank of Canada Technical Report No. 97.Search in Google Scholar
Rossi, B., and T. Sekhposyan. 2010. “‘Have Economic Models’ Forecasting Performance for US Output Growth and Inflation Changed over Time, and when?” International Journal of Forecasting 26 (4): 808–35. https://doi.org/10.1016/j.ijforecast.2009.08.004.Search in Google Scholar
Rossi, B., and T. Sekhposyan. 2016. “Forecast Rationality Tests in the Presence of Instabilities, with Applications to Federal Reserve and Survey Forecasts.” Journal of Applied Econometrics 31 (3): 507–32. https://doi.org/10.1002/jae.2440.Search in Google Scholar
Sims, C. A. 1980. “Macroeconomics and Reality.” Econometrica 48 (1): 1–48. https://doi.org/10.2307/1912017.Search in Google Scholar
Smets, F., and R. Wouters. 2003. “An Estimated Dynamic Stochastic General Equilibrium Model of the Euro Area.” Journal of the European Economic Association 1 (5): 1123–75. https://doi.org/10.1162/154247603770383415.Search in Google Scholar
Stock, J. H., and M. W. Watson. 2003. “Forecasting Output and Inflation: The Role of Asset Prices.” Journal of Economic Literature 41 (3): 788–829. https://doi.org/10.1257/jel.41.3.788.Search in Google Scholar
Warne, A., G. Coenen, and K. Christoffel. 2008. “The New Area-wide Model of the Euro Area: A Micro-founded Open-Economy Model for Forecasting and Policy Analysis.” ECB Working Paper No. 944.Search in Google Scholar
West, K. D., and M. W. McCracken (1998), “Regression-based Tests of Predictive Ability.” NBER Working Paper t0226.10.3386/t0226Search in Google Scholar
Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/bejm-2022-0170).
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Articles in the same Issue
- Frontmatter
- Advances
- Optimal Taxation of Informal Firms: Misreporting Costs and a Tax Reform in Brazil
- Initial Beliefs Uncertainty
- Credit Resource Misallocation and Macroeconomic Fluctuations in China: From the Perspective of Heterogeneous Financial Frictions
- The Bitcoin Premium: A Persistent Puzzle
- Contributions
- Intermediate Goods–Skill Complementarity
- Perfect Competition and Fixed Costs: The Role of the Ownership Structure
- Optimal Monetary Policy with Government-Provided Unemployment Benefits
- Employment Protection in Dual Labor Markets: Any Amplification of Macroeconomic Shocks?
- A Tide that Lifts Some Boats: Assessing the Macroeconomic Effects of EU Enlargement
- Current Account Balances’ Divergence in the Euro Area: An Appraisal of the Underlying Forces
- Merging Structural and Reduced-Form Models for Forecasting
- Trust in Government in a Changing World: Shocks, Tax Evasion, and Economic Growth
- The Fiscal Multiplier of Public Investment: The Role of Corporate Balance Sheet
- Does Uncertainty Matter for the Fiscal Consolidation and Investment Nexus?
- Government Spending Between Active and Passive Monetary Policy: An Invariance Result
- A DSGE Model with Government-owned Banks