A two factor model to combine US inflation forecasts

References

• Ahn , SK . 1997 . Inference of vector autoregressive models with cointegration and scalar components . Journal of the American Statistical Association , 437 : 350 – 56 .
   Google Scholar
• Anderson , TW . 1963 . The use of factor analysis in the statistical analysis of multiple time series . Psychometrika , 28 : 1 – 25 .
   Web of Science ®Google Scholar
• Baghestani , H . 2005 . On the rationality of professional forecasts of corporate bond yield spreads . Applied Economics Letters , 4 : 213 – 16 .
   Google Scholar
• Bates , JM and Granger , CWJ . 1969 . The combination of forecasts . Operations Research Quarterly , 20 : 451 – 68 .
   Google Scholar
• Batchelor , R . 2001 . How useful are the forecasts of intergovernmental agencies? The IMF and OECD versus the consensus . Applied Economics , 33 : 225 – 335 .
   Web of Science ®Google Scholar
• Batchelor , R and Dua , P . 1996 . Empirical measures of inflation uncertainty: a cautionary note . Applied Economics , 28 : 333 – 41 .
   Web of Science ®Google Scholar
• Belton Jr , WJ , Cebula , RJ and Nair-Reichert , U . 2002 . Money and the dispersion of relative prices revisited . Applied Economics , 34 : 1765 – 73 .
   Web of Science ®Google Scholar
• Berk , JM . 1999 . Measuring inflation expectations: a survey data approach . Applied Economics , 31 : 1467 – 80 .
   Web of Science ®Google Scholar
• Bomberger , WA . 1996 . Disagreement as a measure of uncertainty . Journal of Money, Credit and Banking , 28 : 381 – 92 .
   Web of Science ®Google Scholar
• Bomberger , WA and Frazer Jr , WJ . 1981 . Interest rates, uncertainty and the Livingston Data . The Journal of Finance , XXXVI : 661 – 75 .
   Google Scholar
• Box , G and Tiao , G . 1977 . A canonical analysis of multiple time series . Biometrika , 64 : 355 – 65 .
   Web of Science ®Google Scholar
• Brillinger , DR . 1981 . Time Series Data Analysis and Theory , expanded edn , San Francisco : Holden-Day .
   Google Scholar
• Caporale , T and McKiernan , B . 1997 . High and variable inflation: further evidence on the Friedman hypothesis . Economics Letters , 54 : 65 – 8 .
   Web of Science ®Google Scholar
• Chan , YL , Stock , J and Watson , M . 1999 . A dynamic factor model framework for forecast combination . Spanish Economic Review , 1 : 91 – 121 .
   Google Scholar
• Clemen , RT . 1989 . Combining forecasts: a review and annotated bibliography . International Journal of Forecasting , 5 : 559 – 83 .
   Web of Science ®Google Scholar
• Cukierman , A and Wachtel , P . 1979 . Differential inflationary expectations and the variability of the rate of inflation: theory and evidence . The American Economic Review , 69 : 595 – 609 .
   Web of Science ®Google Scholar
• Diebold , FX and Lopez , JA . 1996 . “ Forecast evaluation and combination ” . In Handbook of Statistics , Vol. 14 , 241 – 68 . Amsterdam : North-Holland .
   Google Scholar
• Dutt , SD and Ghosh , D . 2000 . Inflation expectations: are they rational? An empirical examination . Applied Economic Letters , 7 : 103 – 6 .
   Web of Science ®Google Scholar
• Engle , RF . 1983 . Estimates of the variance of US inflation based upon the ARCH model . Journal of Money, Credit and Banking , 15 : 286 – 301 .
   Web of Science ®Google Scholar
• Engsted , T . 1991 . A note on the rationality of survey inflation expectations in the United Kingdom . Applied Economics , 23 : 1269 – 76 .
   Web of Science ®Google Scholar
• Favero , C , Marcellino , M and Neglia , F . 2005 . Principal components at work: the empirical analysis of monetary policy with large data sets . Journal of Applied Econometrics , 20 : 603 – 20 .
   Web of Science ®Google Scholar
• Figlewski , S . 1983 . Optimal price forecasting using survey data . The Review of Economics and Statistics , 65 : 13 – 21 .
   Web of Science ®Google Scholar
• Figlewski , S and Urich , T . 1983 . Optimal aggregation of money supply forecasts: accuracy, profitability and market efficiency . The Journal of Finance , 28 : 695 – 710 .
   Google Scholar
• Forni , M , Hallin , M , Lippi , M and Reichlin , L . 2000 . The generalized factor model: identification and estimation . Review of Economic and Statistics , 82 : 540 – 54 .
   Web of Science ®Google Scholar
• Friedman , M . 1977 . Inflation and unemployment . Journal of Political Economy , 85 : 451 – 72 .
   Web of Science ®Google Scholar
• Geweke , JF and Singleton , KJ . 1981 . Maximum likelihood confirmatory analysis of economic time series . International Economic Review , 22 : 37 – 54 .
   Web of Science ®Google Scholar
• Kontonikas , A . 2004 . Inflation and inflation uncertainty in the United Kingdom, evidence from GARCH modelling . Economic Modelling , 21 : 525 – 43 .
   Web of Science ®Google Scholar
• Nath , HK . 2004 . Relative importance of sectoral and aggregate sources of price changes . Applied Economics , 36 : 1781 – 96 .
   Web of Science ®Google Scholar
• Newbold , P and Granger , CWJ . 1974 . Experience with forecasting univariate time series and the combination of forecasts . Journal of the Royal Statistical Society A , 137 : 131 – 46 .
   Web of Science ®Google Scholar
• Newbold , P and Harvey , DI . 2002 . “ Forecasting combination and encompassing ” . In A Companion to Economic Forecasting , Edited by: Clements , M and Hendry , D . 268 – 83 . Oxford : Blackwells .
   Google Scholar
• Peña , D and Box , G . 1987 . Identifying a simplifying structure in time series . Journal of the American Statistical Association , 82 : 836 – 43 .
   Web of Science ®Google Scholar
• Peña , D and Poncela , P . 2004 . Forecasting with nonstationary dynamic factor models . Journal of Econometrics , 119 : 291 – 321 .
   Web of Science ®Google Scholar
• Peña , D and Poncela , P . 2006 . Nonstationary dynamic factor models . Journal of Statistical Planning and Inference , 136 : 1237 – 1257 .
   Web of Science ®Google Scholar
• Priestley , MB , Rao , TS and Tong , J . 1974 . Applications of principal component analysis and factor analysis in the identification of multivariable systems . IEEE Transactions on Automatic Control , 19 : 703 – 704 .
   Google Scholar
• Reinsel , GC . 1993 . Elements of Multivariate Time Series Analysis , New York : Springer-Verlag .
   Google Scholar
• Shoesmith , GL . 2000 . A further interpretation of Friedman's hypothesis: the cointegration of component CPI indexes . Economics Letters , 67 : 49 – 52 .
   Google Scholar
• Stock , JH and Watson , M . 1999 . Forecasting inflation . Journal of Monetary Economics , 44 : 293 – 335 .
   Web of Science ®Google Scholar
• Stock , JH and Watson , M . 2002a . Forecasting using principal components from a large number of predictors . Journal of the American Statistical Association , 97 : 1167 – 79 .
   Web of Science ®Google Scholar
• Stock , JH and Watson , M . 2002b . Macroeconomic forecasting using diffusion indexes . Journal of Business & Economic Statistics , 20 : 147 – 63 .
   Web of Science ®Google Scholar
• Stock , JH and Watson , M . 2004 . Combination forecasts of output growth in a seven-country data set . Journal of Forecasting , 23 : 405 – 30 .
   Web of Science ®Google Scholar
• Tiao , GC and Tsay , RS . 1989 . Model specification in multivariate time series . Journal of the Royal Statistical Society B , 51 : 157 – 213 .
   Google Scholar
• Velu , RP , Reinsel , GC and Wichern , DW . 1986 . Reduced rank models for multiple time series . Biometrika , 73 : 105 – 18 .
   Web of Science ®Google Scholar
• Zarnowitz , V and Lambros , LA . 1987 . Consensus and uncertainty in economic prediction . Journal of Political Economy , 95 : 591 – 621 .
   Web of Science ®Google Scholar
• Zarnowitz , V and Braun , P . 1993 . “ Twenty-two years of the NBER-ASA quarterly economic outlook survey: aspects and comparisons of forecasting performance ” . In Business Cycles, Indicators and Forecasting , Edited by: Stock , J and Watson , M . 11 – 93 . Chicago : The University of Chicago Press .
   Google Scholar