Jointly evaluating the Federal Reserve’s forecasts of GDP growth and inflation
Tài liệu tham khảo
Bernanke, B. S. (2010). Monetary policy and the housing bubble. Speech at the annual meeting of the American Economic Association, Atlanta, Georgia, January 3, 2010. http://www.federalreserve.gov/newsevents/speech/bernanke20100103a.htm.
Capistran, 2008, Bias in Federal Reserve inflation forecasts: is the Federal Reserve irrational or just cautious?, Journal of Monetary Economics, 55, 1415, 10.1016/j.jmoneco.2008.09.011
Clarida, 1998, Monetary policy rules in practice: some international evidence, European Economic Review, 42, 1033, 10.1016/S0014-2921(98)00016-6
Clarida, 2000, Monetary policy rules and macroeconomic stability: evidence and some theory, Quarterly Journal of Economics, 115, 147, 10.1162/003355300554692
Clark, 2005, Estimating equilibrium real interest rates in real time, The North American Journal of Economics and Finance, 16, 395, 10.1016/j.najef.2005.04.002
Clements, 2004, Evaluating the Bank of England density forecasts of inflation, The Economic Journal, 114, 855, 10.1111/j.1468-0297.2004.00246.x
Clements, 1993, On the limitations of comparing mean square forecast errors (with subsequent comments), Journal of Forecasting, 12, 617, 10.1002/for.3980120802
Clements, 2007, An evaluation of the forecasts of the Federal Reserve: a pooled approach, Journal of Applied Econometrics, 22, 121, 10.1002/jae.954
Croushore, 1993, Introducing: the survey of professional forecasters, Business Review, Federal Reserve Bank of Philadelphia
Eisenbeis, 2002, Evaluating Wall Street journal survey forecasters: a multivariate approach, Business Economics, 37, 11
Elliott, 2005, Biases in macroeconomic forecasts: irrationality or asymmetric loss?, Journal of the European Economic Association, 6, 122, 10.1162/JEEA.2008.6.1.122
Elliott, 2008, Estimation and testing of forecast rationality under flexible loss, Review of Economic Studies, 72, 1107, 10.1111/0034-6527.00363
Giannoni, M. P., & Woodford, M. (2002). Optimal interest rate rules: II. Applications. NBER Working Paper No. 9420.
Granger, 2000, A decision-based approach to forecast evaluation
Granger, 2000, Economic and statistical measures of forecast accuracy, Journal of Forecasting, 19, 537, 10.1002/1099-131X(200012)19:7<537::AID-FOR769>3.0.CO;2-G
Hamilton, J. D., Pruitt, S., & Borger, S. C. (2009). The market-perceived monetary policy rule. Board of Governors of the Federal Reserve System International Finance Discussion Papers Number 982.
Hymans, 1968, Simultaneous confidence intervals in econometric forecasting, Econometrica, 36, 18, 10.2307/1909601
Joutz, 2000, An evaluation of the predictions of the Federal Reserve, International Journal of Forecasting, 16, 17, 10.1016/S0169-2070(99)00046-1
Kohn, D. L. (2007). John Taylor rules. Speech at the Conference on John Taylor’s contributions to monetary theory and policy. Federal Reserve Bank of Dallas, Dallas, Texas, October 12, 2007.
Komunjer, I., & Owyang, M. T. (2007). Multivariate forecast evaluation and rationality testing. Federal Reserve Bank of St. Louis working paper no. 2007-047.
Lahiri, 2010, Learning and heterogeneity in GDP and inflation forecasts, International Journal of Forecasting, 26, 265, 10.1016/j.ijforecast.2009.12.009
Leigh, 2008, Estimating the Federal Reserve’s implicit inflation target: a state space approach, Journal of Economic Dynamics and Control, 32, 2013, 10.1016/j.jedc.2007.07.004
Nobay, 2003, Optimal discretionary monetary policy in a model of asymmetric central bank preferences, The Economic Journal, 113, 657, 10.1111/1468-0297.t01-1-00149
Orphanides, 2001, Monetary policy rules based on real-time data, The American Economic Review, 91, 964, 10.1257/aer.91.4.964
Orphanides, 2003, Monetary policy evaluation with noisy information, Journal of Monetary Economics, 50, 605, 10.1016/S0304-3932(03)00027-8
Orphanides, 2008, Economic projections and rules of thumb for monetary policy, Federal Reserve Bank of St. Louis Review, 90, 307
Orphanides, 2007, Robust monetary policy with imperfect knowledge, Journal of Monetary Economics, 54, 1406, 10.1016/j.jmoneco.2007.06.005
Patton, 2007, Properties of optimal forecasts under asymmetric loss and nonlinearity, Journal of Econometrics, 140, 884, 10.1016/j.jeconom.2006.07.018
Patton, 2007, Testing forecast optimality under unknown loss, Journal of the American Statistical Association, 102, 1172, 10.1198/016214506000001176
Pesaran, 2002, Decision-based methods for forecast evaluation, 241
Reifschneider, D., & Tulip, P. (2007). Gauging the uncertainty of the economic outlook from historical forecasting errors. Federal Reserve Board Finance and Economics Discussion Series. 2007-60.
Romer, 2000, Federal reserve information and the behavior of interest rates, American Economic Review, 90, 429, 10.1257/aer.90.3.429
Rudebusch, 2001, Term structure evidence on interest rate smoothing and monetary policy inertia, Journal of Monetary Economics, 49, 1161, 10.1016/S0304-3932(02)00149-6
Sims, 2002, The role of models and probabilities in the monetary policy process, Brookings Papers on Economic Activity, 2, 1, 10.1353/eca.2003.0009
Sinclair, 2010, Directional forecasts of GDP and inflation: a joint evaluation with an application to Federal Reserve predictions, Applied Economics, 42, 2289, 10.1080/00036840701857978
Stekler, 1994, Are economic forecasts valuable?, Journal of Forecasting, 13, 495, 10.1002/for.3980130602
Taylor, 1993, Discretion versus policy rules in practice, Carnegie-Rochester Conference Series on Public Policy, 39, 195, 10.1016/0167-2231(93)90009-L
Taylor, 1999
Taylor, J. B. (2007). Housing and monetary policy. Proceedings of the Federal Reserve Bank of Kansas City (pp. 463–476).
Woodford, 2001, The Taylor rule and optimal monetary policy, American Economic Review, 91, 232, 10.1257/aer.91.2.232
Woodford, M. (2001b). Inflation stabilization and welfare. National Bureau of Economic Research Working Paper 8071.