Evaluating point and density forecasts of DSGE models

Wolters, Maik Hendrik (2012): Evaluating point and density forecasts of DSGE models.

Abstract

This paper investigates the accuracy of point and density forecasts of four DSGE models for inflation, output growth and the federal funds rate. Model parameters are estimated and forecasts are derived successively from historical U.S. data vintages synchronized with the Fed’s Greenbook projections. Point forecasts of some models are of similar accuracy as the forecasts of nonstructural large dataset methods. Despite their common underlying New Keynesian modeling philosophy, forecasts of different DSGE models turn out to be quite distinct. Weighted forecasts are more precise than forecasts from individual models. The accuracy of a simple average of DSGE model forecasts is comparable to Greenbook projections for medium term horizons. Comparing density forecasts of DSGE models with the actual distribution of observations shows that the models overestimate uncertainty around point forecasts.

• Item Type: MPRA Paper
• Language: English
• Keywords: DSGE models; forecasting; model uncertainty; forecast combination; density forecasts; real-time data; Greenbook
• Subjects: E - Macroeconomics and Monetary Economics > E0 - General; E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E32 - Business Fluctuations ; Cycles; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods; E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E31 - Price Level ; Inflation ; Deflation; E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E37 - Forecasting and Simulation: Models and Applications

References

Adolfson, M., Andersson, M. K., Lind´e, J., Villani, M., Vredin, A., 2007. Modern forecasting models in action: improving macroeconomic analyses at central banks. International Journal of Central Banking 3(4), 111–144.

Adolfson, M., Laseen, S., Linde, J., Villani, M., 2007. Bayesian estimation of an open economy DSGE model with incomplete pass-through. Journal of International Economics 72(2), 481–511.

An, S., Schorfheide, F., 2007. Bayesian analysis of DSGE models. Econometric Reviews 26(2-4), 113–172.

Andersson, M. K., Karlsson, S., 2007. Bayesian forecast combination for VAR models, Sveriges Riksbank Working Paper No 216.

Bache, I. W., Jore, A. S., Mitchell, J., Vahey, S. P., 2009. Combining VAR and DSGE forecast densities, Norges Bank Working paper 2009/23.

Berkowitz, J., 2001. Testing density forecasts, with applications to risk management. Journal of Business and Economic Statistics 19(4), 465–474.

Bernanke, B. S., Boivin, J., 2003. Monetary policy in a data-rich environment. Journal of Monetary Economics 50(3), 525–546.

Christiano, L. J., Eichenbaum, M., Evans, C. L., 2005. Nominal rigidities and the dynamic effects of a shock to monetary policy. Journal of Political Economy 113(1), 1–45.

Christoffel, K., Coenen, G., Warne, A., 2008. The new area-wide model of the euro area - a microfounded open-economy model for forecasting and policy analysis, European Central Bank Working Paper 944.

Christoffel, K., Coenen, G., Warne, A., 2011. Forecasting with DSGE models. In: Clements, M. P., Hendry, D. F. (Eds.), Oxford Handbook on Economic Forecasting. Oxford University Press, USA.

Del Negro,M., Schorfheide, F., 2004. Priors from general equilibrium models for VARS. International Economic Review 45(2), 643–673.

Del Negro, M., Schorfheide, F., Smets, F. R.,Wouters, R., 2007. On the fit of new Keynesian models. Journal of Business and Economic Statistics 25, 123–143.

Diebold, F. X., Gunther, T. A., Tay, A. S., 1998. Evaluating density forecasts with applications to financial risk management. International Economic Review 39(4), 863–883.

Diebold, F. X., Hahn, J., Tay, A. S., 1999. Multivariate density forecast evaluation and calibration in financial risk management: High-frequency returns on foreign exchange. Review of Economics and Statistics 81(4), 661–673.

Diebold, F. X.,Mariano, R. S., 1995. Comparing predictive accuracy. Journal of Business & Economic Statistics 13, 253–263.

Doan, T., Litterman, R., Sims, C., 1984. Forecasting and conditional projection using realistic prior distributions. Econometric Reviews 3, 1 – 100.

Edge, R., Gürkaynak, R., 2010. How useful are estimated DSGE model forecasts for central bankers? Brookings Papers on Economic Activity 2, 209–244.

Edge, R. M., Kiley, M. T., Laforte, J.-P., 2007. Documentation of the research and statistics divisions estimated DSGE model of the U.S. economy: 2006 version, finance and Economics Discussion Series, Divisions of Research & Statistics and Monetary Affairs, Federal Reserve Board, Washington, D.C.: 2007-53.

Edge, R. M., Kiley, M. T., Laforte, J.-P., 2008. Natural rate measures in an estimated DSGE model of the U.S. economy. Journal of Economic Dynamics and Control 32, 2512–2535.

Edge, R. M., Kiley, M. T., Laforte, J.-P., 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), 720–754.

Eklund, J., Karlsson, S., 2007. Forecast combination and model averaging using predictive measures. Econometric Reviews 26(2-4), 329–363.

Elder, R., Kapetanios, G., Taylor, T., Yates, T., 2005. Assessing the MPC’s fan charts. Bank of England Quarterly Bulletin Autumn, 326–345. 41

Fair, R. C., 2007. Evaluating inflation targeting using a macroeconometric model. Economics: The Open-Access, Open-Assessment E-Journal 8.

Faust, J.,Wright, J. H., 2009. Comparing Greenbook and reduced form forecasts using a large realtime dataset. Journal of Business and Economic Statistics 27(4), 468–479.

Forni, M., Hallin, M., Lippi, M., Reichlin, L., 2003. Do financial variables help forecasting inflation and real activity in the Euro area? Journal of Monetary Economics 50, 1243–1255.

Francis, N., Ramey, V. A., 2009. Measures of per capita hours and their implications for the technology-hours debate. Journal of Money, Credit and Banking 41(6), 1071–1097.

Fuhrer, J. C., 1997. Inflation/output variance trade-offs and optimal monetary policy. Journal of Money, Credit and Banking 29(2), 214–234.

Fuhrer, J. C., Moore, G., 1995a. Inflation persistence. The Quarterly Journal of Economics 110(1), 127–159.

Fuhrer, J. C., Moore, G., 1995b. Monetary policy trade-offs and the correlation between nominal interest rates and real output. The American Economic Review 85(1), 219–239.

Gerard, H., Nimark, K., 2008. Combing multivariate density forecasts using predictive criteria, Research Discussion Paper 2008-2, Reserve Bank of Australia.

Giannone, D., Monti, F., Reichlin, L., 2009. Incorporating conjunctural analysis in structural models. In: Wieland, V. (Ed.), The Science and Practice of Monetary Policy Today. Springer Science, pp. 41–57.

Goodfriend, M., King, R. G., 1997. The new neoclassical synthesis and the role of monetary policy. In: Bernanke, B. S., Rotemberg, J. J. (Eds.), National Bureau of Economic Research Macroeconomics Annual 1997. MIT Press, Cambridge, MA.

Hamilton, J. D., 1994. Time Series Analysis. Princeton University Press, Princeton, NJ.

Herbst, E., Schorfheide, F., 2011. Evaluating DSGE model forecasts of comovements, manuscript, University of Pennsylvania.

Hsiao, C., Wan, S. K., 2010. Is there an optimal forecast combination?, Working Paper University of Southern California.

Kimball, M., 1995. The quantitative analytics of the basic monetarist model. Journal of Money, Credit and Banking 27(4), 1241–1277.

Marcellino, M., Stock, J., Watson, M., 2003. Macroeconomic forecasting in the Euro area: Countryspecific versus area-wide information. European Economic Review 47, 1–18.

Murchison, S., Rennison, A., 2006. ToTEM: The Bank of Canada’s new quarterly projection model, Technical Reports 97, Bank of Canada.

Romer, C. D., Romer, D. H., 2000. Federal reserve information and the behavior of interest rates. American Economic Review 90, 429–457.

Rossi, B., 2012. Advances in forecasting under instability. In: Elliott, G., Timmermann, A. (Eds.), Handbook of Economic Forecasting. Vol. 2. Elsevier Publications.

Rotemberg, J. J., Woodford, M., 1997. An optimization-based econometric framework for the evaluation of monetary policy, in B. Bernanke and J. Rotemberg, (eds.), NBER Macroeconomics Annual, The MIT Press.

Schorfheide, F., 2000. Loss function-based evaluation of DSGE models. Journal of Applied Econometrics 15, 645–670.

Sims, C. A., 2002. The role of models and probabilities in the monetary policy process. Brookings Papers on Economic Activity 2, 1–40.

Smets, F., Christoffel, K., Coenen, G., Motto, R., Rostagno, M., 2010. DSGE models and their use at the ECB. Journal of the Spanish Economic Society 1(1), 51–65.

Smets, F., Wouters, R., 2004. Forecasting with a bayesian DSGE model: An application to the Euro area. Journal of Common Market Studies 42(4), 841–867.

Smets, F.,Wouters, R., 2007. Shocks and frictions in US business cycles: A Bayesian DSGE approach. The American Economic Review 97(3), 586–606.

Stock, J., Watson, M., 2002. Forecasting using principal components from a large number of predictors. Journal of the American Statistical Association 97, 1167–1179.

Timmermann, A., 2006. Forecast combinations. In: Elliott, G., Granger, C. W. J., Timmermann, A. (Eds.), Handbook of Economic Forecasting. Amsterdam: North Holland, pp. 135–196.

Wang, M.-C., 2009. Comparing the DSGEmodel with the factor model: An out-of-sample forecasting experiment. Journal of Forecasting 28(2), 167–182.

Wieland, V.,Wolters, M. H., 2011. The diversity of forecasts from macroeconomic models of the U.S. economy. Economic Theory 47(2-3), 247–292.

Wieland, V., Wolters, M. H., 2012. Forecasting and policy making. In: Elliott, G., Timmermann, A. (Eds.), Handbook of Economic Forecasting. Vol. 2. Elsevier Publications.

Woodford, M., 2003. Interest and Prices: Foundations of a Theory of Monetary Policy. Princeton University Press.