• Adolfson M, Linde J, Villani M. 2007. Forecasting performance of an open economy DSGE model. Econometric Reviews 26: 289328.
  • Amisano G, Giacomini R. 2007. Comparing density forecasts via weighted likelihood ratio tests. Journal of Business and Economic Statistics 25: 177190.
  • Andreasen M. 2012. On the effects of rare disasters and uncertainty shocks for risk premia in non-linear DSGE models. Review of Economic Dynamics 15: 295316.
  • Andrews D, Monahan JC. 1992. An improved heteroskedasticity and autocorrelation consistent covariance matrix estimator. Econometrica 60: 953966.
  • Benati L. 2008. The ‘Great Moderation’ in the United Kingdom. Journal of Money, Credit, and Banking 40: 121147.
  • Bianchi F. 2013. Regime switches, agents' beliefs, and post-World War II U.S. macroeconomic dynamics. Review of Economic Studies 80: 463490.
  • Bognanni M. 2013. An empirical analysis of time-varying fiscal multipliers. Working Paper. University of Pennsylvania.
  • Bollerslev T. 1986. Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics 31: 307327.
  • Canarella G, Fang W, Miller S, Pollard S. 2010. Is the Great Moderation ending? UK and US evidence. Modern Economy 1: 1742.
  • Carriero A, Clark T, Marcellino M. 2012. Common drifting volatility in large Bayesian VARs. Working Paper. Federal Reserve Bank of Cleveland.
  • Carter C, Kohn R. 1994. On Gibbs sampling for state space models. Biometrika 81: 541553.
  • Chung H, Laforte J-P, Reifschneider D, Williams J. 2012. Have we underestimated the likelihood and severity of zero lower bound events? Journal of Money, Credit, and Banking 44: 4782.
  • Clark T. 2009. Is the Great Moderation over? An empirical analysis. Federal Reserve Bank of Kansas City Economic Review 94: 542.
  • Clark T. 2011. Real-time density forecasts from BVARs with stochastic volatility. Journal of Business and Economic Statistics 29: 327341.
  • Clark T, McCracken M. 2011a. Nested forecast model comparisons: a new approach to testing equal accuracy. Working Paper. Federal Reserve Bank of St Louis.
  • Clark T, McCracken M. 2011b. Testing for unconditional predictive ability. In Oxford Handbook of Economic Forecasting, Clements MP, Hendry DF (eds). Oxford University Press: Oxford; 415440.
  • Clark T, Ravazzolo F. 2012. The macroeconomic forecasting performance of autoregressive models with alternative specifications of time-varying volatility. Working Paper 2012-09. Norges Bank.
  • Cogley T, Sargent T. 2005. Drifts and volatilities: monetary policies and outcomes in the post-World War II U.S. Review of Economic Dynamics 8: 262302.
  • Cogley T, Morozov S, Sargent T. 2005. Bayesian fan charts for U.K. inflation: forecasting and sources of uncertainty in an evolving monetary system. Journal of Economic Dynamics and Control 29: 18931925.
  • Croushore D. 2006. Forecasting with real-time macroeconomic data. In Handbook of Economic Forecasting, Elliott G, Granger C, Timmermann A (eds). North-Holland: Amsterdam; 961982.
  • Croushore D, Stark T. 2001. A real-time data set for macroeconomists. Journal of Econometrics 105: 111130.
  • Curdia V, Del Negro M, Greenwald D. 2013. Rare shocks, great recessions. Working Paper. Federal Reserve Bank of New York.
  • D'Agostino A, Gambetti L, Giannone D. 2013. Macroeconomic forecasting and structural change. Journal of Applied Econometrics 28: 82101.
  • Del Negro M, Primiceri G. 2013. Time varying structural vector autoregressions and monetary policy: a corrigendum. Working Paper. Northwestern University.
  • Diebold F, Mariano R. 1995. Comparing predictive accuracy. Journal of Business and Economic Statistics 13: 253263.
  • Engle R. 1982. Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica 50: 9871007.
  • Faust J, Wright J. 2009. Comparing Greenbook and reduced form forecasts using a large realtime dataset. Journal of Business and Economic Statistics 27: 468479.
  • Fernandez-Villaverde J, Rubio-Ramierez J. 2007. Estimating macroeconomic models: a likelihood approach. Review of Economic Studies 74: 10591087.
    Direct Link:
  • Fernandez-Villaverde J, Rubio-Ramierez J. 2010. Macroeconomics and volatility: data, models, and estimation. Working Paper. University of Pennsylvania.
  • Fernandez-Villaverde J, Guerron-Quintana P, Rubio-Ramierez J. 2010. Fortune or virtue: time-variant volatilities versus parameter drifting in U.S. data. Working Paper. University of Pennsylvania.
  • Gerlach R, Carter C, Kohn R. 2000. Efficient Bayesian inference for dynamic mixture models. Journal of the American Statistical Association 95: 819828.
  • Geweke J, Amisano G. 2010. Comparing and evaluating Bayesian predictive distributions of asset returns. International Journal of Forecasting 26: 216230.
  • Giacomini R, White H. 2006. Tests of conditional predictive ability. Econometrica 74: 15451578.
  • Giordani P, Villani M. 2010. Forecasting macroeconomic time series with locally adaptive signal extraction. International Journal of Forecasting 26: 312325.
  • Giordani P, Kohn R, van Dijk D. 2007. A unified approach to nonlinearity, outliers and structural breaks. Journal of Econometrics 137: 112137.
  • Gneiting T, Raftery A. 2007. Strictly proper scoring rules, prediction, and estimation. Journal of the American Statistical Association 102: 359378.
  • Gneiting T, Ranjan R. 2011. Comparing density forecasts using threshold and quantile weighted proper scoring rules. Journal of Business and Economic Statistics 29: 411422.
  • Groen J, Paap R, Ravazzolo F. 2013. Real-time inflation forecasting in a changing world. Journal of Business and Economic Statistics 31: 2944.
  • Hansen P, Lunde A. 2005. A forecast comparison of volatility models: does anything beat a GARCH(1,1)? Journal of Applied Econometrics 20: 873889.
  • Hubrich K, Tetlow R. 2012. Financial stress and economic dynamics: the transmission of crises. FEDS Working Paper 2012-82. Federal Reserve Board of Governors.
  • Jacquier E, Polson N, Rossi P. 2004. Bayesian analysis of stochastic volatility models with fat-tails and correlated errors. Journal of Econometrics 122: 185212.
  • Jore A, Mitchell J, Vahey S. 2010. Combining forecast densities from VARs with uncertain instabilities. Journal of Applied Econometrics 25: 621634.
  • Justiniano A, Primiceri G. 2008. The time-varying volatility of macroeconomic fluctuations. American Economic Review 98: 604641.
  • Kadiyala K, Karlsson S. 1997. Numerical methods for estimation and inference in Bayesian VAR-models. Journal of Applied Econometrics 12: 99132.
  • Karapanagiotidis P. 2012. Improving Bayesian VAR density forecasts through autoregressive Wishart stochastic volatility. Working Paper. University of Toronto.
  • Kim S, Shephard N, Chib S. 1998. Stochastic volatility: Likelihood inference and comparison with ARCH models. Review of Economic Studies 65: 361393.
    Direct Link:
  • Koop G. 2003. Bayesian Econometrics. Wiley: Chichester.
  • Koop G, Korobilis D. 2013. Large time-varying parameter VARs. Journal of Econometrics 177: 185198.
  • Koop G, Potter S. 2007. Estimation and forecasting in models with multiple breaks. Review of Economic Studies 74: 763789.
    Direct Link:
  • Nakajima J. 2012. Bayesian analysis of generalized autoregressive conditional heteroskedasticity and stochastic volatility: modeling leverage, jumps and heavy-tails for financial time series. Japanese Economic Review 63: 81103.
  • Primiceri G. 2005. Time varying structural vector autoregressions and monetary policy. Review of Economic Studies 72: 821852.
    Direct Link:
  • Ravazzolo F, Vahey S. 2013. Forecast densities for economic aggregates from disaggregate ensembles. Studies in Nonlinear Dynamics and Econometrics. (forthcoming).
  • Romer C, Romer D. 2000. Federal Reserve information and the behavior of interest rates. American Economic Review 90: 429457.
  • Sims C. 2002. The role of models and probabilities in the monetary policy process. Brookings Papers on Economic Activity 2: 140.
  • Sims C, Zha T. 2006. Were there regime switches in US monetary policy? American Economic Review 96: 5481.
  • So M, Chen C, Chen M-T. 2005. A Bayesian threshold nonlinearity test for financial time series. Journal of Forecasting 24: 6175.
  • Stock J, Watson M. 2003. Has the business cycle changed? Evidence and explanations. Monetary Policy and Uncertainty: adapting to a Changing Economy, a symposium sponsored by the Federal Reserve Bank of Kansas City.
  • Stock J, Watson M. 2007. Has U.S. inflation become harder to forecast? Journal of Money, Credit, and Banking 39: 333.
  • Vrontos ID, Dellaportas P, Politis DN. 2000. Full Bayesian inference for GARCH and EGARCH models. Journal of Business and Economic Statistics 18: 187198.