Forecasting the U.S. Unemployment Rate

References

• Ansley , C. F. 1979 . “An Algorithm for the Exact Likelihood of a Mixed Autoregressive Moving Average Process,” . Biometrika , 66 : 59 – 65 .
   Web of Science ®Google Scholar
• Box , G. E. P. , Jenkins , G. M. and Reinsel . 1994 . Time Series Analysis: Forecasting and Control, , 3rd ed. , Englewood Cliffs , NJ : Prentice-Hall .
   Google Scholar
• Chan , K. S. 1993 . “Consistency and Limiting Distribution of the Least Squares Estimator of a Threshold Autoregressive Model,” . The Annals of Statistics , 21 ( 1 ) : 520 – 533 .
   Web of Science ®Google Scholar
• Christoffersen , P. F. and Diebold , F. X. 1996 . “Further Results on Forecasting and Model Selection Under Asymmetric Loss,” , University of Pennsylvania, Dept. of Economics . working paper
   Google Scholar
• Croushore , D. 1993 . “Introducing The Survey of Professional Forecasters,” . The Federal Reserve Bank of Philadelphia Business Review , : 3 – 15 . Nov.–Dec.
   Google Scholar
• Diebold , F. X. and Mariano , R. S. 1995 . “Comparing Predictive Accuracy,” . Journal of Business & Economic Statistics , 13 : 253 – 263 .
   Web of Science ®Google Scholar
• DeLong , J. B. and Summers , L. H. 1986 . “Are Business Cycles Symmetrical?,” . In The American Business Cycle, Continuity and Changes , Edited by: Gorton , R. J. Chicago : University of Chicago Press for NBER .
   Google Scholar
• Donihue , M. R. 1993 . “Evaluating the Role Judgement Plays in Forecasting Accuracy,” . Journal of Forecasting , 12 ( 2 ) : 81 – 92 .
   Google Scholar
• Elwood , S. K. 1996 . “Testing for the Symmetry in the Effects of Time Series Disturbances: An Unobserved Components-Threshold Approach,” , James Madison University, Department of Economics . working paper
   Google Scholar
• Engel , C. 1994 . “Can the Markov Switching Model Forecast Exchange Rates?,” . Journal of International Economics , 36 ( 1–2 ) : 151 – 165 .
   Web of Science ®Google Scholar
• Gelfand , A. E. and Smith , A. F. M. 1990 . “Sampling-Based Approaches to Calculating Marginal Densities,” . Journal of the American Statistical Association , 85 : 398 – 409 .
   Web of Science ®Google Scholar
• Geman , S. and Geman , D. 1984 . “Stochastic Relaxation, Gibbs Distributions and the Bayesian Restoration of Images,” . IEEE Transactions on Pattern Analysis and Machine Intelligence , 6 : 721 – 741 .
   PubMed Web of Science ®Google Scholar
• Ghysels , E. , Granger , C. W. J. and Siklos , P. L. 1996 . “Is Seasonal Adjustment a Linear or Nonlinear Data-Filtering Process?” . Journal of Business & Economic Statistics , 14 : 374 – 386 .
   Web of Science ®Google Scholar
• Granger , C. W. J. and Newbold , P. 1986 . Forecasting Economic Time Series , New York : Academic Press .
   Google Scholar
• Hamilton , J. D. 1989 . “A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle,” . Econometrica , 57 : 357 – 384 .
   Web of Science ®Google Scholar
• Hamilton , J. D. 1990 . “Analysis of Time Series Subject to Changes in Regime,” . Journal of Econometrics , 45 ( 1, 2 ) : 39 – 70 .
   Google Scholar
• Hannan , E. J. and Deistler , M. 1988 . The Statistical Theory of Linear Systems , New York : Wiley .
   Google Scholar
• Hillmer , S. C. and Tiao , G. C. 1979 . “Likelihood Function of Stationary Multiple Autoregressive Moving Average Models,” . Journal of the American Statistical Association , 74 : 652 – 660 .
   Web of Science ®Google Scholar
• Howrey , E. P. , Hymans , S. H. and Donihue , M. R. 1991 . “Merging Monthly and Quarterly Forecasts: Experience With MQEM,” . Journal of Forecasting , 10 : 255 – 268 .
   Web of Science ®Google Scholar
• Ljung , G. M. and Box , G. E. P. 1978 . “On a Measure of Lack of Fit in Time Series Models,” . Biometrika , 65 : 297 – 303 .
   Web of Science ®Google Scholar
• McCulloch , R. E. and Tsay , R. S. 1994 . “Bayesian Analysis of Threshold Autoregressive Processes with a Random Number of Regimes,” . Journal of Time Series Analysis , 15 : 235 – 250 .
   Google Scholar
• Meese , R. A. and Rogoff , K. 1988 . “Was it Real? The Exchange Rate-Interest Differential Relation Over the Modern Floating-Rate Period,” . Journal of Finance , 43 : 933 – 948 .
   Web of Science ®Google Scholar
• Mitchell , W. C. 1927 . Business Cycles: The Problem of Its Setting , New York : NBER .
   Google Scholar
• Montgomery , A. L. , Zarnowitz , V. , Tsay , R. S. and Tiao , G. C. 1996 . “Modeling Nonlinearity in the U.S. Unemployment Rate with Unobserved Component Models,” , University of Chicago, Graduate School of Business . technical report
   Google Scholar
• Moore , G. H. 1983 . Business Cycles, Inflation, and Forecasting , New York : Ballinger Pub. Co. for NBER .
   Google Scholar
• Neftci , S. N. 1984 . “Are Economic Time Series Asymmetric Over the Business Cycles?,” . Journal of Political Economy , 85 : 281 – 291 .
   Google Scholar
• Preston , J. M. and Chin , D. M. 1996 . “Using Monthly Data to Improve Quarterly Model Forecasts,” . Federal Reserve Bank of Minneapolis Quarterly Review , 20 ( 2 ) : 16 – 33 .
   Google Scholar
• Rothman , P. 1996 . “Forecasting Asymmetric Unemployment Rates,” , East Carolina University, Dept. of Economics . working paper
   Google Scholar
• Sichel , D. E. 1989 . “Business Cycle Asymmetry: A Deeper Look,” , Federal Reserve Board of Governors . Economic Working Paper 93
   Google Scholar
• Sims , C. A. 1989 . “A Nine-Variable Probabilistic Macroeconomic Forecasting Model,” , Federal Reserve Bank of Minneapolis . Discussion Paper 14
   Google Scholar
• Sims , C. A. and Todd , R. M. “Evaluating Bayesian Vector Autoregressive Forecasting Procedures for Macroeconomic Data,” . paper presented at the NSF-NBER Seminar on Bayesian Inference in Econometrics and Statistics . April 1991 , St. Paul .
   Google Scholar
• Swanson , N. and White , H. 1997 . “A Model Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks,” . Review of Economics and Statistics , 79 : 540 – 550 .
   Web of Science ®Google Scholar
• Telser , L. 1967 . “Discrete Samples and Moving Sums in Stationary Stochastic Processes,” . Journal of the American Statistical Association , 62 : 484 – 499 .
   Web of Science ®Google Scholar
• Tiao , G. C. 1972 . “Asymptotic Behavior of Temporal Aggregates of Time Series,” . Biometrika , 59 : 525 – 531 .
   Web of Science ®Google Scholar
• Tiao , G. C. and Box , G. E. P. 1981 . “Modeling Multiple Time Series With Applications,” . Journal of the American Statistical Association , 76 : 802 – 816 .
   Web of Science ®Google Scholar
• Tiao , G. C. and Tsay , R. S. 1989 . “Model Specification in Multivariate Time Series” . Journal of the Royal Statistical Society , 51 : 157 – 213 . (with discussion), Ser. B
   Google Scholar
• Tiao , G. C. and Tsay , R. S. 1994 . “Some Advances in Nonlinear and Adaptive Modelling in Time-Series,” . Journal of Forecasting , 13 : 109 – 131 .
   Web of Science ®Google Scholar
• Tong , H. 1983 . Threshold Models in Nonlinear Time Series Analysis , New York : Springer-Verlag . Lecture Notes in Statistics 21
   Google Scholar
• Tsay , R. S. 1989 . “Testing and Modeling Threshold Autoregressive Processes,” . Journal of American Statistical Association , 84 : 231 – 240 .
   Web of Science ®Google Scholar
• Tsay , R. S. and Tiao , G. C. 1984 . “Consistent Estimates of Autoregressive Parameters and Extended Sample Autocorrelation Function for Stationary and Nonstationary ARMA Models,” . Journal of the American Statistical Association , 79 : 84 – 96 .
   Web of Science ®Google Scholar
• White , H. 1980 . “A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity,” . Econometrica , 48 : 817 – 838 .
   Web of Science ®Google Scholar
• Zarnowitz , V. 1992 . Business Cycles: Theory, History, Indicators, and Forecasting , Chicago : University of Chicago Press for NBER .
   Google Scholar
• Zarnowitz , V. and Braun , P. 1993 . “Twenty-Two Years of the SPF Quarterly Economic Outlook Surveys: Aspects and Comparisons of Forecasting Performance,” . In Business Cycles, Indicators, and Forecasting , Edited by: Stock , J. H. and Watson , M. W. 11 – 84 . Chicago : University of Chicago Press for NBER .
   Google Scholar