State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models
In: Essays in Honour of Fabio Canova
Author
Abstract
Suggested Citation
DOI: 10.1108/S0731-90532022000044A003
Download full text from publisher
As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.
Other versions of this item:
- Luis Uzeda, 2016. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," ANU Working Papers in Economics and Econometrics 2016-632, Australian National University, College of Business and Economics, School of Economics.
- Luis Uzeda, 2018. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Staff Working Papers 18-14, Bank of Canada.
References listed on IDEAS
- Perron, Pierre & Wada, Tatsuma, 2009.
"Let's take a break: Trends and cycles in US real GDP,"
Journal of Monetary Economics, Elsevier, vol. 56(6), pages 749-765, September.
- Pierre Perron & Tatsuma Wada, 2005. "Let’s Take a Break: Trends and Cycles in US Real GDP," Boston University - Department of Economics - Working Papers Series wp2009-006, Boston University - Department of Economics, revised Feb 2009.
- Pierre Perron† & Tatsuma Wada, 2005. "Let’s Take a Break: Trends and Cycles in US Real GDP?," Boston University - Department of Economics - Working Papers Series WP2005-031, Boston University - Department of Economics, revised Oct 2005.
- Tom Doan, "undated". "RATS programs to replicate Perron-Wada state space model," Statistical Software Components RTZ00133, Boston College Department of Economics.
- Beveridge, Stephen & Nelson, Charles R., 1981. "A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the `business cycle'," Journal of Monetary Economics, Elsevier, vol. 7(2), pages 151-174.
- Christine Garnier & Elmar Mertens & Edward Nelson, 2015.
"Trend Inflation in Advanced Economies,"
International Journal of Central Banking, International Journal of Central Banking, vol. 11(4), pages 65-136, September.
- Christine Garnier & Elmar Mertens & Edward Nelson, 2013. "Trend inflation in advanced economies," Finance and Economics Discussion Series 2013-74, Board of Governors of the Federal Reserve System (U.S.).
- Peter R. Winters, 1960. "Forecasting Sales by Exponentially Weighted Moving Averages," Management Science, INFORMS, vol. 6(3), pages 324-342, April.
- Koop,Gary & Poirier,Dale J. & Tobias,Justin L., 2007.
"Bayesian Econometric Methods,"
Cambridge Books,
Cambridge University Press, number 9780521671736, June.
- Koop,Gary & Poirier,Dale J. & Tobias,Justin L., 2007. "Bayesian Econometric Methods," Cambridge Books, Cambridge University Press, number 9780521855716, June.
- Koop, Gary M & Poirier, Dale J & Tobias, Justin, 2007. "Bayesian Econometric Methods," Staff General Research Papers Archive 12722, Iowa State University, Department of Economics.
- Snyder, Ralph D & Ord, J Keith & Koehler, Anne B, 2001.
"Prediction Intervals for ARIMA Models,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 19(2), pages 217-225, April.
- Snyder, R.D. & Ord, J.K. & Koehler, A.B., 1997. "Prediction Intervals for Arima Models," Monash Econometrics and Business Statistics Working Papers 8/97, Monash University, Department of Econometrics and Business Statistics.
- Chan, Joshua C.C., 2013.
"Moving average stochastic volatility models with application to inflation forecast,"
Journal of Econometrics, Elsevier, vol. 176(2), pages 162-172.
- Joshua C C Chan, 2012. "Moving Average Stochastic Volatility Models with Application to Inflation Forecast," ANU Working Papers in Economics and Econometrics 2012-591, Australian National University, College of Business and Economics, School of Economics.
- Joshua C.C. Chan, 2013. "Moving Average Stochastic Volatility Models with Application to Inflation Forecast," CAMA Working Papers 2013-31, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Chib, Siddhartha, 2001. "Markov chain Monte Carlo methods: computation and inference," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 57, pages 3569-3649, Elsevier.
- Joshua C. C. Chan & Gary Koop & Simon M. Potter, 2013.
"A New Model of Trend Inflation,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 94-106, January.
- Joshua C C Chan & Gary Koop & Simon M Potter, 2012. "A New Model of Trend Inflation," CAMA Working Papers 2012-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Chan, Joshua & Koop, Gary & Potter, Simon, 2012. "A New Model Of Trend Inflation," SIRE Discussion Papers 2012-12, Scottish Institute for Research in Economics (SIRE).
- Chan, Joshua & Koop, Gary & Potter, Simon, 2012. "A new model of trend inflation," MPRA Paper 39496, University Library of Munich, Germany.
- Joshua Chan & Gary Koop & Simon Potter, 2012. "A New Model of Trend Inflation," Working Papers 1202, University of Strathclyde Business School, Department of Economics.
- Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998.
"Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models,"
The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 361-393.
- Sangjoon Kim, Neil Shephard & Siddhartha Chib, "undated". "Stochastic volatility: likelihood inference and comparison with ARCH models," Economics Papers W26, revised version of W, Economics Group, Nuffield College, University of Oxford.
- Sangjoon Kim & Neil Shephard, 1994. "Stochastic volatility: likelihood inference and comparison with ARCH models," Economics Papers 3., Economics Group, Nuffield College, University of Oxford.
- Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1996. "Stochastic Volatility: Likelihood Inference And Comparison With Arch Models," Econometrics 9610002, University Library of Munich, Germany.
- James C. Morley & Charles R. Nelson & Eric Zivot, 2003.
"Why Are the Beveridge-Nelson and Unobserved-Components Decompositions of GDP So Different?,"
The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 235-243, May.
- Charles Nelson & Eric Zivot, 2000. "Why are Beveridge-Nelson and Unobserved-Component Decompositions of GDP so Different?," Econometric Society World Congress 2000 Contributed Papers 0692, Econometric Society.
- James Morley & Charles Nelson & Eric Zivot, 2002. "Why Are Beveridge-Nelson and Unobserved-Component Decompositions of GDP So Different?," Working Papers UWEC-2002-01, University of Washington, Department of Economics.
- James C. Morley & Charles Nelson & Eric Zivot, 2000. "Why Are Beveridge-Nelson and Unobserved-Component Decompositions of GDP So Different?," Working Papers 0013, University of Washington, Department of Economics.
- James C. Morley & Charles Nelson & Eric Zivot, 2000. "Why Are Beveridge-Nelson and Unobserved-Component Decompositions of GDP So Different?," Discussion Papers in Economics at the University of Washington 0013, Department of Economics at the University of Washington.
- James Morley & Charles Nelson & Eric Zivot, 2003. "Why are Beveridge-Nelson and Unobserved-component decompositions of GDP so Different?," Working Papers UWEC-2002-18-P, University of Washington, Department of Economics.
- Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.
- Zarnowitz, Victor & Ozyildirim, Ataman, 2006.
"Time series decomposition and measurement of business cycles, trends and growth cycles,"
Journal of Monetary Economics, Elsevier, vol. 53(7), pages 1717-1739, October.
- Victor Zarnowitz & Ataman Ozyildirim, 2001. "Time Series Decomposition and Measurement of Business Cycles, Trends and Growth Cycles," Economics Program Working Papers 01-03, The Conference Board, Economics Program.
- Victor Zarnowitz & Ataman Ozyildirim, 2002. "Time Series Decomposition and Measurement of Business Cycles, Trends and Growth Cycles," NBER Working Papers 8736, National Bureau of Economic Research, Inc.
- Andrew Harvey & Siem Jan Koopman, 2000.
"Signal extraction and the formulation of unobserved components models,"
Econometrics Journal, Royal Economic Society, vol. 3(1), pages 84-107.
- Harvey, A.C. & Koopman, S.J.M., 1999. "Signal Extraction and the Formulation of Unobserved Components Models," Discussion Paper 1999-44, Tilburg University, Center for Economic Research.
- Harvey, A.C. & Koopman, S.J.M., 1999. "Signal Extraction and the Formulation of Unobserved Components Models," Other publications TiSEM 44688527-92c9-4c46-ac53-f, Tilburg University, School of Economics and Management.
- Frank Smets & Rafael Wouters, 2007.
"Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach,"
American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
- Smets, Frank & Wouters, Raf, 2007. "Shocks and frictions in US business cycles: a Bayesian DSGE approach," Working Paper Series 722, European Central Bank.
- Smets, Frank & Wouters, Rafael, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," CEPR Discussion Papers 6112, C.E.P.R. Discussion Papers.
- Frank Smets & Raf Wouters, 2007. "Shocks and Frictions in US Business Cycles : a Bayesian DSGE Approach," Working Paper Research 109, National Bank of Belgium.
- Efrem Castelnuovo & Luciano Greco & Davide Raggi, 2010.
"Policy Rules, Regime Switches, and Trend Inflation: An Empirical Investigation for the U.S,"
"Marco Fanno" Working Papers
0109, Dipartimento di Scienze Economiche "Marco Fanno".
- E. Castelnuovo & L. Greco & D. Raggi, 2010. "Policy Rules, Regime Switches, and Trend Inflation: An Empirical Investigation for the U.S," Working Papers 691, Dipartimento Scienze Economiche, Universita' di Bologna.
- Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen V.K. Rombouts, 2015.
"The Contribution of Structural Break Models to Forecasting Macroeconomic Series,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 596-620, June.
- BAUWENS, Luc & KOOP, Gary & KOROBILIS, Dimitris & ROMBOUTS, Jeroen V. K., 2011. "A comparison of forecasting procedures for macroeconomic series: the contribution of structural break models," LIDAM Discussion Papers CORE 2011003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Bauwens, Luc & Korobilis, Dimitris & Koop, Gary & Rombouts, Jeroen V.K., 2011. "A Comparison Of Forecasting Procedures For Macroeconomic Series: The Contribution Of Structural Break Models," SIRE Discussion Papers 2011-25, Scottish Institute for Research in Economics (SIRE).
- Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen V.K. Rombouts, 2011. "The Contribution of Structural Break Models to Forecasting Macroeconomic Series," Working Paper series 38_11, Rimini Centre for Economic Analysis.
- Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen Rombouts, 2011. "A Comparison of Forecasting Procedures For Macroeconomic Series: The Contribution of Structural Break Models," CIRANO Working Papers 2011s-13, CIRANO.
- Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen Rombouts, 2011. "A comparison of Forecasting Procedures for Macroeconomic Series: The Contribution of Structural Break Models," Working Papers 1113, University of Strathclyde Business School, Department of Economics.
- Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen V.K. Rombouts, 2011. "A Comparison of Forecasting Procedures for Macroeconomic Series: the Contribution of Structural Break Models," Cahiers de recherche 1104, CIRPEE.
- John Geweke & Gianni Amisano, 2011.
"Hierarchical Markov normal mixture models with applications to financial asset returns,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(1), pages 1-29, January/F.
- Amisano, Gianni & Geweke, John, 2007. "Hierarchical Markov normal mixture models with applications to financial asset returns," Working Paper Series 831, European Central Bank.
- John Geweke & Gianni Amisano, 2007. "Hierarchical Markov Normal Mixture Models with Applications to Financial Asset Returns," Working Papers 0705, University of Brescia, Department of Economics.
- Michael Woodford, 2008.
"How Important Is Money in the Conduct of Monetary Policy?,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(8), pages 1561-1598, December.
- Michael Woodford, 2008. "How Important Is Money in the Conduct of Monetary Policy?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(8), pages 1561-1598, December.
- Michael Woodford, 2006. "How Important Is Money In The Conduct Of Monetary Policy?," Working Paper 1104, Economics Department, Queen's University.
- Woodford, Michael, 2007. "How Important is Money in the Conduct of Monetary Policy?," CEPR Discussion Papers 6211, C.E.P.R. Discussion Papers.
- Michael Woodford, 2007. "How Important is Money in the Conduct of Monetary Policy?," NBER Working Papers 13325, National Bureau of Economic Research, Inc.
- Michael Woodford, 2007. "How Important is Money in the Conduct of Monetary Policy?," Levine's Working Paper Archive 122247000000001419, David K. Levine.
- James H. Stock & Mark W. Watson, 2016.
"Core Inflation and Trend Inflation,"
The Review of Economics and Statistics, MIT Press, vol. 98(4), pages 770-784, October.
- James H. Stock & Mark W. Watson, 2015. "Core Inflation and Trend Inflation," NBER Working Papers 21282, National Bureau of Economic Research, Inc.
- Cogley, Timothy & Morozov, Sergei & Sargent, Thomas J., 2005.
"Bayesian fan charts for U.K. inflation: Forecasting and sources of uncertainty in an evolving monetary system,"
Journal of Economic Dynamics and Control, Elsevier, vol. 29(11), pages 1893-1925, November.
- Cogley, Timothy W. & Morozov, Sergei & Sargent, Thomas J., 2003. "Bayesian fan charts for UK inflation: Forecasting and sources of uncertainty in an evolving monetary system," CFS Working Paper Series 2003/44, Center for Financial Studies (CFS).
- Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005.
"Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy,"
Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
- Lawrence J. Christiano & Martin S. Eichenbaum & Charles L. Evans, 2001. "Nominal rigidities and the dynamic effects of a shock to monetary policy," Proceedings, Federal Reserve Bank of San Francisco, issue Jun.
- Lawrence J. Christiano & Martin Eichenbaum & Charles Evans, 2001. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," NBER Working Papers 8403, National Bureau of Economic Research, Inc.
- Lawrence J. Christiano & Martin S. Eichenbaum & Charles L. Evans, 2001. "Nominal rigidities and the dynamic effects of a shock to monetary policy," Working Paper Series WP-01-08, Federal Reserve Bank of Chicago.
- Lawrence J. Christiano & Martin S. Eichenbaum & Charles L. Evans, 2001. "Nominal rigidities and the dynamic effects of a shock to monetary policy," Working Papers (Old Series) 0107, Federal Reserve Bank of Cleveland.
- McCausland, William J. & Miller, Shirley & Pelletier, Denis, 2011. "Simulation smoothing for state-space models: A computational efficiency analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 199-212, January.
- Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2006.
"A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series,"
Journal of Econometrics, Elsevier, vol. 135(1-2), pages 499-526.
- Stock, James & Watson, Mark & Marcellino, Massimiliano, 2005. "A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series," CEPR Discussion Papers 4976, C.E.P.R. Discussion Papers.
- Massimiliano Marcellino & James Stock & Mark Watson, 2005. "A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series," Working Papers 285, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
- Luo, Sui & Startz, Richard, 2014. "Is it one break or ongoing permanent shocks that explains U.S. real GDP?," Journal of Monetary Economics, Elsevier, vol. 66(C), pages 155-163.
- Andrea Stella & James H. Stock, 2012. "A state-dependent model for inflation forecasting," International Finance Discussion Papers 1062, Board of Governors of the Federal Reserve System (U.S.).
- Frühwirth-Schnatter, Sylvia & Wagner, Helga, 2010. "Stochastic model specification search for Gaussian and partial non-Gaussian state space models," Journal of Econometrics, Elsevier, vol. 154(1), pages 85-100, January.
- James H. Stock & Mark W. Watson, 2007.
"Why Has U.S. Inflation Become Harder to Forecast?,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
- James H. Stock & Mark W. Watson, 2006. "Why Has U.S. Inflation Become Harder to Forecast?," NBER Working Papers 12324, National Bureau of Economic Research, Inc.
- Oh, Kum Hwa & Zivot, Eric & Creal, Drew, 2008. "The relationship between the Beveridge-Nelson decomposition and other permanent-transitory decompositions that are popular in economics," Journal of Econometrics, Elsevier, vol. 146(2), pages 207-219, October.
- Harvey, A C, 1985. "Trends and Cycles in Macroeconomic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(3), pages 216-227, June.
- Joshua C. C. Chan, 2017.
"The Stochastic Volatility in Mean Model With Time-Varying Parameters: An Application to Inflation Modeling,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 17-28, January.
- Joshua C.C. Chan, 2015. "The Stochastic Volatility in Mean Model with Time-Varying Parameters: An Application to Inflation Modeling," CAMA Working Papers 2015-07, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Chan,Joshua & Koop,Gary & Poirier,Dale J. & Tobias,Justin L., 2019.
"Bayesian Econometric Methods,"
Cambridge Books,
Cambridge University Press, number 9781108437493, September.
- Chan,Joshua & Koop,Gary & Poirier,Dale J. & Tobias,Justin L., 2019. "Bayesian Econometric Methods," Cambridge Books, Cambridge University Press, number 9781108423380, October.
- Koop, Gary M & Poirier, Dale J & Tobias, Justin, 2007. "Bayesian Econometric Methods," Staff General Research Papers Archive 12722, Iowa State University, Department of Economics.
- Diebold, Francis X & Mariano, Roberto S, 2002.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
- Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-263, July.
- Francis X. Diebold & Roberto S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Watson, Mark W., 1986. "Univariate detrending methods with stochastic trends," Journal of Monetary Economics, Elsevier, vol. 18(1), pages 49-75, July.
- Peter K. Clark, 1987. "The Cyclical Component of U. S. Economic Activity," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 102(4), pages 797-814.
- Tommaso Proietti, 2006. "Trend-Cycle Decompositions with Correlated Components," Econometric Reviews, Taylor & Francis Journals, vol. 25(1), pages 61-84.
- Durbin, James & Koopman, Siem Jan, 2012.
"Time Series Analysis by State Space Methods,"
OUP Catalogue,
Oxford University Press,
edition 2, number 9780199641178.
- Durbin, James & Koopman, Siem Jan, 2001. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, number 9780198523543.
- Tom Doan, "undated". "SEASONALDLM: RATS procedure to create the matrices for the seasonal component of a DLM," Statistical Software Components RTS00251, Boston College Department of Economics.
- Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen V.K. Rombouts, 2015.
"The Contribution of Structural Break Models to Forecasting Macroeconomic Series,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 596-620, June.
- Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen V.K. Rombouts, 2011. "The Contribution of Structural Break Models to Forecasting Macroeconomic Series," Working Paper series 38_11, Rimini Centre for Economic Analysis.
- BAUWENS, Luc & KOOP, Gary & KOROBILIS, Dimitris & ROMBOUTS, Jeroen, 2015. "The Contribution of Structural Break Models to Forecating Macroeconomic Series," LIDAM Reprints CORE 2651, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Cochrane, John H, 1988. "How Big Is the Random Walk in GNP?," Journal of Political Economy, University of Chicago Press, vol. 96(5), pages 893-920, October.
- Kum Hwa Oh & Eric Zivot, 2006. "The Clark Model with Correlated Components," Working Papers UWEC-2006-06, University of Washington, Department of Economics.
- Shigeru Iwata & Han Li, 2015. "What are the Differences in Trend Cycle Decompositions by Beveridge and Nelson and by Unobserved Component Models?," Econometric Reviews, Taylor & Francis Journals, vol. 34(1-2), pages 146-173, February.
- Forbes, C.S. & Snyder, R.D. & Shami, R.S., 2000. "Bayesian Exponential Smoothing," Monash Econometrics and Business Statistics Working Papers 7/00, Monash University, Department of Econometrics and Business Statistics.
- Granger, C. W. J. & Newbold, Paul, 1986. "Forecasting Economic Time Series," Elsevier Monographs, Elsevier, edition 2, number 9780122951831 edited by Shell, Karl.
- Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-247, July-Sept.
- Harvey, Andrew, 2006. "Forecasting with Unobserved Components Time Series Models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 7, pages 327-412, Elsevier.
- J Keith Ord & Ralph D Snyder & Anne B Koehler & Rob J Hyndman & Mark Leeds, 2005. "Time Series Forecasting: The Case for the Single Source of Error State Space," Monash Econometrics and Business Statistics Working Papers 7/05, Monash University, Department of Econometrics and Business Statistics.
- Kang Kyu Ho & Kim Chang-Jin & Morley James, 2009. "Changes in U.S. Inflation Persistence," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(4), pages 1-23, September.
- Sylvia Frühwirth‐Schnatter, 1994. "Data Augmentation And Dynamic Linear Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 15(2), pages 183-202, March.
- Dungey, Mardi & Jacobs, Jan P.A.M. & Tian, Jing & van Norden, Simon, 2015. "Trend In Cycle Or Cycle In Trend? New Structural Identifications For Unobserved-Components Models Of U.S. Real Gdp," Macroeconomic Dynamics, Cambridge University Press, vol. 19(4), pages 776-790, June.
- Castelnuovo, Efrem & Greco, Luciano & Raggi, Davide, 2014. "Policy Rules, Regime Switches, And Trend Inflation: An Empirical Investigation For The United States," Macroeconomic Dynamics, Cambridge University Press, vol. 18(4), pages 920-942, June.
- J. Durbin, 2002. "A simple and efficient simulation smoother for state space time series analysis," Biometrika, Biometrika Trust, vol. 89(3), pages 603-616, August.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Angelia L. Grant & Joshua C.C. Chan, 2017.
"A Bayesian Model Comparison for Trend‐Cycle Decompositions of Output,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(2-3), pages 525-552, March.
- Joshua C.C. Chan & Angelia L. Grant, 2015. "A Bayesian model comparison for trend-cycle decompositions of output," CAMA Working Papers 2015-31, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Agbeyegbe, Terence D., 2020. "Bayesian analysis of output gap in Barbados," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
- Joshua C.C. Chan & Rodney W. Strachan, 2023.
"Bayesian State Space Models In Macroeconometrics,"
Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
- Joshua C.C. Chan & Rodney W. Strachan, 2020. "Bayesian state space models in macroeconometrics," CAMA Working Papers 2020-90, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Michael O’Grady, 2019. "Estimating the Output, Inflation and Unemployment Gaps in Ireland using Bayesian Model Averaging," The Economic and Social Review, Economic and Social Studies, vol. 50(1), pages 35-76.
- Sbrana, Giacomo, 2013.
"The exact linkage between the Beveridge–Nelson decomposition and other permanent-transitory decompositions,"
Economic Modelling, Elsevier, vol. 30(C), pages 311-316.
- Giacomo Sbrana, 2010. "The exact linkage between the Beveridge-Nelson decomposition and other permanent-transitory decompositions," Working Papers 10-09, Association Française de Cliométrie (AFC).
- Giacomo Sbrana, 2013. "The exact linkage between the Beveridge-Nelson decomposition and other permanent-transitory decompositions," Post-Print hal-00779344, HAL.
- David Kohns & Arnab Bhattacharjee, 2020.
"Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model,"
Papers
2011.00938, arXiv.org, revised May 2022.
- Bhattacharjee, Arnab & Kohns, David, 2022. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," National Institute of Economic and Social Research (NIESR) Discussion Papers 538, National Institute of Economic and Social Research.
- Juan Antolin-Diaz & Thomas Drechsel & Ivan Petrella, 2017.
"Tracking the Slowdown in Long-Run GDP Growth,"
The Review of Economics and Statistics, MIT Press, vol. 99(2), pages 343-356, May.
- Juan Antolin-Diaz & Thomas Drechsel & Ivan Petrella, 2014. "Tracking the Slowdown in Long-Run GDP Growth," Discussion Papers 1604, Centre for Macroeconomics (CFM), revised Jan 2016.
- Antolin-Diaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2017. "Tracking the slowdown in long-run GDP growth," LSE Research Online Documents on Economics 81869, London School of Economics and Political Science, LSE Library.
- Antolin-Diaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2016. "Tracking the slowdown in long-run GDP growth," LSE Research Online Documents on Economics 86243, London School of Economics and Political Science, LSE Library.
- Antolin-Diaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2016. "Tracking the slowdown in long-run GDP growth," Bank of England working papers 587, Bank of England.
- Oh, Kum Hwa & Zivot, Eric & Creal, Drew, 2008. "The relationship between the Beveridge-Nelson decomposition and other permanent-transitory decompositions that are popular in economics," Journal of Econometrics, Elsevier, vol. 146(2), pages 207-219, October.
- Mengheng Li & Ivan Mendieta-Munoz, 2019.
"The multivariate simultaneous unobserved components model and identification via heteroskedasticity,"
Working Paper Series
2019/08, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
- Ivan Mendieta-Munoz & Mengheng Li, 2019. "The Multivariate Simultaneous Unobserved Compenents Model and Identification via Heteroskedasticity," Working Paper Series, Department of Economics, University of Utah 2019_06, University of Utah, Department of Economics.
- Kum Hwa Oh & Eric Zivot & Drew Creal, 2006. "The Relationship between the Beveridge-Nelson Decomposition andUnobserved Component Models with Correlated Shocks," Working Papers UWEC-2006-16-FC, University of Washington, Department of Economics.
- Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
- Günes Kamber & James Morley & Benjamin Wong, 2018.
"Intuitive and Reliable Estimates of the Output Gap from a Beveridge-Nelson Filter,"
The Review of Economics and Statistics, MIT Press, vol. 100(3), pages 550-566, July.
- Güneş Kamber & James Morley & Benjamin Wong, 2016. "Intuitive and reliable estimates of the output gap from a Beveridge-Nelson filter," BIS Working Papers 584, Bank for International Settlements.
- Gunes Kamber & James Morley & Benjamin Wong, 2017. "Intuitive and Reliable Estimates of the Output Gap from a Beveridge-Nelson Filter," Discussion Papers 2016-09A, School of Economics, The University of New South Wales.
- Güneş Kamber & James Morley & Benjamin Wong, 2017. "Intuitive and Reliable Estimates of the Output Gap from a Beveridge-Nelson Filter," Reserve Bank of New Zealand Discussion Paper Series DP2017/01, Reserve Bank of New Zealand.
- Gunes Kamber & James Morley & Benjamin Wong, 2017. "Intuitive and reliable estimates of the output gap from a Beveridge-Nelson Filter," CAMA Working Papers 2017-03, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Gunes Kamber & James Morley & Benjamin Wong, 2016. "Intuitive and Reliable Estimates of the Output Gap from a Beveridge-Nelson Filter," Discussion Papers 2016-09, School of Economics, The University of New South Wales.
- Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2022.
"A Model of the Fed's View on Inflation,"
The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 686-704, October.
- Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017. "A Model of the Fed’s View on Inflation," Economic Research Papers 269087, University of Warwick - Department of Economics.
- Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2020. "A Model of the Fed's View on Inflation," Papers 2006.14110, arXiv.org.
- Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2018. "A model of FED'S view on inflation," Documents de Travail de l'OFCE 2018-03, Observatoire Francais des Conjonctures Economiques (OFCE).
- Thomas Hasenzagl & Fillipo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2018. "A model of the FED's view on inflation," Working Papers hal-03458456, HAL.
- Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017. "A Model of the Fed’s View on Inflation," The Warwick Economics Research Paper Series (TWERPS) 1145, University of Warwick, Department of Economics.
- Reichlin, Lucrezia & Hasenzagl, Thomas & Pellegrino, Filippo & Ricco, Giovanni, 2018. "A Model of the Fed's View on Inflation," CEPR Discussion Papers 12564, C.E.P.R. Discussion Papers.
- Tommaso Proietti & Alessandra Luati, 2013.
"Maximum likelihood estimation of time series models: the Kalman filter and beyond,"
Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 15, pages 334-362,
Edward Elgar Publishing.
- Luati, Alessandra & Proietti, Tommaso, 2012. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," Working Papers 2012_02, University of Sydney Business School, Discipline of Business Analytics.
- Tommaso, Proietti & Alessandra, Luati, 2012. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," MPRA Paper 39600, University Library of Munich, Germany.
- Joshua C.C. Chan & Todd E. Clark & Gary Koop, 2018.
"A New Model of Inflation, Trend Inflation, and Long‐Run Inflation Expectations,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(1), pages 5-53, February.
- Joshua C. C. Chan & Todd E. Clark & Gary Koop, 2015. "A New Model of Inflation, Trend Inflation, and Long-Run Inflation Expectations," Working Papers (Old Series) 1520, Federal Reserve Bank of Cleveland.
- Berger, Tino & Everaert, Gerdie & Vierke, Hauke, 2016.
"Testing for time variation in an unobserved components model for the U.S. economy,"
Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 179-208.
- Tino Berger & Gerdie Everaert & Hauke Vierke, 2015. "Testing for time variation in an unobserved components model for the U.S. economy," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 15/903, Ghent University, Faculty of Economics and Business Administration.
- Tommaso Proietti, 2016.
"The Multistep Beveridge--Nelson Decomposition,"
Econometric Reviews, Taylor & Francis Journals, vol. 35(3), pages 373-395, March.
- Proietti, Tommaso, 2009. "The Multistep Beveridge-Nelson Decomposition," MPRA Paper 15345, University Library of Munich, Germany.
- Proietti, Tommaso, 2011. "The Multistep Beveridge-Nelson Decomposition," Working Papers 09/2011, University of Sydney Business School, Discipline of Business Analytics.
- Tommaso Proietti, 2009. "The Multistep Beveridge-Nelson Decomposition," EERI Research Paper Series EERI_RP_2009_24, Economics and Econometrics Research Institute (EERI), Brussels.
- Tobias Hartl & Rolf Tschernig & Enzo Weber, 2020. "Fractional trends and cycles in macroeconomic time series," Papers 2005.05266, arXiv.org, revised May 2020.
- Joshua C. C. Chan, 2017.
"The Stochastic Volatility in Mean Model With Time-Varying Parameters: An Application to Inflation Modeling,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 17-28, January.
- Joshua C.C. Chan, 2015. "The Stochastic Volatility in Mean Model with Time-Varying Parameters: An Application to Inflation Modeling," CAMA Working Papers 2015-07, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Yu-Fan Huang & Sui Luo, 2018. "Potential output and inflation dynamics after the Great Recession," Empirical Economics, Springer, vol. 55(2), pages 495-517, September.
More about this item
Keywords
Bayesian; states; correlation; forecasting; trend inflation; C11; C15; C51; C53;All these keywords.
JEL classification:
- C - Mathematical and Quantitative Methods
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eme:aecozz:s0731-90532022000044a003. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Emerald Support (email available below). General contact details of provider: .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.