Characterising economic trends by Bayesian stochastic model specification search
A recently proposed Bayesian model selection technique, stochastic model specification search, is carried out to discriminate between two trend generation hypotheses. The first is the trend-stationary hypothesis, for which the trend is a deterministic function of time and the short run dynamics are represented by a stationary autoregressive process. The second is the difference-stationary hypothesis, according to which the trend results from the cumulation of the effects of random disturbances. A difference-stationary process may originate in two ways: from an unobserved components process adding up an integrated trend and an orthogonal transitory component, or implicitly from an autoregressive process with roots on the unit circle. The different trend generation hypotheses are nested within an encompassing linear state space model. After a reparameterisation in non-centred form, the empirical evidence supporting a particular hypothesis is obtained by performing variable selection on the model components, using a suitably designed Gibbs sampling scheme. The methodology is illustrated with reference to a set of US macroeconomic time series which includes the traditional Nelson and Plosser dataset. The conclusion is that most series are better represented by autoregressive models with time-invariant intercept and slope and coefficients that are close to boundary of the stationarity region. The posterior distribution of the autoregressive parameters provides useful insight on quasi-integrated nature of the specifications selected.
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Volume (Year): 71 (2014)
Issue (Month): C ()
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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Christopher A. Sims, 1988.
"Bayesian skepticism on unit root econometrics,"
Discussion Paper / Institute for Empirical Macroeconomics
3, Federal Reserve Bank of Minneapolis.
- Tom Doan, "undated". "BAYESTST: RATS procedure to perform Bayesian Unit Root test," Statistical Software Components RTS00014, Boston College Department of Economics.
- Smith, Michael & Kohn, Robert, 1996.
"Nonparametric regression using Bayesian variable selection,"
Journal of Econometrics,
Elsevier, vol. 75(2), pages 317-343, December.
- Smith, M. & Kohn, R., "undated". "Nonparametric Regression using Bayesian Variable Selection," Statistics Working Paper _009, Australian Graduate School of Management.
- Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
- 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, 02.
- Serena Ng & Pierre Perron, 1997.
"Lag Length Selection and the Construction of Unit Root Tests with Good Size and Power,"
Boston College Working Papers in Economics
369, Boston College Department of Economics, revised 01 Sep 2000.
- Serena Ng & Pierre Perron, 2001. "LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power," Econometrica, Econometric Society, vol. 69(6), pages 1519-1554, November.
- Koop, Gary & Dijk, Herman K. Van, 2000.
"Testing for integration using evolving trend and seasonals models: A Bayesian approach,"
Journal of Econometrics,
Elsevier, vol. 97(2), pages 261-291, August.
- Koop, G. & van Dijk, H.K., 1999. "Testing for integration using evolving trend and seasonal models: A Bayesian approach," Econometric Institute Research Papers EI 9934/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Gary Koop & Herman K. van Dijk & Henk Hoek, 1997. "Testing for Integration using Evolving Trend and Seasonals Models: A Bayesian Approach," Tinbergen Institute Discussion Papers 97-078/4, Tinbergen Institute.
- Gary Koop & Herman K. van Dijk, 1999. "Testing for Integration using Evolving Trend and Seasonals Models: A Bayesian Approach," Tinbergen Institute Discussion Papers 99-072/4, Tinbergen Institute.
- Fossati, Sebastian, 2011.
"Covariate Unit Root Tests with Good Size and Power,"
2011-4, University of Alberta, Department of Economics.
- Fossati, Sebastian, 2012. "Covariate unit root tests with good size and power," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3070-3079.
- 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.
- Strickland, Chris M. & Martin, Gael M. & Forbes, Catherine S., 2008.
"Parameterisation and efficient MCMC estimation of non-Gaussian state space models,"
Computational Statistics & Data Analysis,
Elsevier, vol. 52(6), pages 2911-2930, February.
- Chris M Strickland & Gael Martin & Catherine S Forbes, 2006. "Parameterisation and Efficient MCMC Estimation of Non-Gaussian State Space Models," Monash Econometrics and Business Statistics Working Papers 22/06, Monash University, Department of Econometrics and Business Statistics.
- Schwert, G William, 1989.
"Tests for Unit Roots: A Monte Carlo Investigation,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 7(2), pages 147-159, April.
- 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.
- Peter C.B. Phillips, 1990.
"To Criticize the Critics: An Objective Bayesian Analysis of Stochastic Trends,"
Cowles Foundation Discussion Papers
950, Cowles Foundation for Research in Economics, Yale University.
- Phillips, P C B, 1991. "To Criticize the Critics: An Objective Bayesian Analysis of Stochastic Trends," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(4), pages 333-364, Oct.-Dec..
- Schotman, Peter C & van Dijk, Herman K, 1991.
"On Bayesian Routes to Unit Roots,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 6(4), pages 387-401, Oct.-Dec..
- Peter C. Schotman & Herman K. van Dijk, 1991. "On Bayesian routes to unit roots," Discussion Paper / Institute for Empirical Macroeconomics 43, Federal Reserve Bank of Minneapolis.
- Christopher A. Sims & Harald Uhlig, 1988.
"Understanding unit rooters: a helicopter tour,"
Discussion Paper / Institute for Empirical Macroeconomics
4, Federal Reserve Bank of Minneapolis.
- DeJong, David N & Whiteman, Charles H, 1991.
"The Case for Trend-Stationarity Is Stronger Than We Thought,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 6(4), pages 413-421, Oct.-Dec..
- DeJong, D.N. & Whiteman, C.H., 1991. "The Case for Trend-Stationarity is Stronger than we Thought," Working Papers 91-05, University of Iowa, Department of Economics.
- Kilian, L. & Caner, M., 1999.
"Size Distortions of Tests of the Null Hypothesis of Stationarity: Evidence and Implications for the PPP Debate,"
99-05, Michigan - Center for Research on Economic & Social Theory.
- Caner, M. & Kilian, L., 2001. "Size distortions of tests of the null hypothesis of stationarity: evidence and implications for the PPP debate," Journal of International Money and Finance, Elsevier, vol. 20(5), pages 639-657, October.
- Caner, Mehmet & Kilian, Lutz, 2000. "Size Distortions Of Tests Of The Null Hypothesis Of Stationarity: Evidence And Implications For The PPP Debate," CEPR Discussion Papers 2425, C.E.P.R. Discussion Papers.
- James H. Stock & Mark W. Watson, 2007. "Erratum to "Why Has U.S. Inflation Become Harder to Forecast?"," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1849-1849, October.
- Graham Elliott & Thomas J. Rothenberg & James H. Stock, 1992.
"Efficient Tests for an Autoregressive Unit Root,"
NBER Technical Working Papers
0130, National Bureau of Economic Research, Inc.
- Kwiatkowski, D. & Phillips, P.C.B. & Schmidt, P., 1990.
"Testing the Null Hypothesis of Stationarity Against the Alternative of Unit Root : How Sure are we that Economic Time Series have a Unit Root?,"
8905, Michigan State - Econometrics and Economic Theory.
- Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
- Denis Kwiatkowski & Peter C.B. Phillips & Peter Schmidt, 1991. "Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root: How Sure Are We That Economic Time Series Have a Unit Root?," Cowles Foundation Discussion Papers 979, Cowles Foundation for Research in Economics, Yale University.
- Koop, Gary, 1992. "'Objective' Bayesian Unit Root Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(1), pages 65-82, Jan.-Marc.
- 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.
- Tommaso, Proietti & Stefano, Grassi, 2010.
"Bayesian stochastic model specification search for seasonal and calendar effects,"
27305, University Library of Munich, Germany.
- Stefano Grassi & Tommaso Proietti, 2011. "Bayesian stochastic model specification search for seasonal and calendar effects," CREATES Research Papers 2011-08, Department of Economics and Business Economics, Aarhus University.
- Koop, Gary, 1994. " Recent Progress in Applied Bayesian Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 8(1), pages 1-34, March.
- Chib S. & Jeliazkov I., 2001. "Marginal Likelihood From the Metropolis-Hastings Output," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 270-281, March.
- 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.
- Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003.
"What Happens After a Technology Shock?,"
NBER Working Papers
9819, National Bureau of Economic Research, Inc.
- DeJong, David N. & Nankervis, John C. & Savin, N. E. & Whiteman, Charles H., 1992. "The power problems of unit root test in time series with autoregressive errors," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 323-343.
- Proietti, Tommaso & Harvey, Andrew, 2000. "A Beveridge-Nelson smoother," Economics Letters, Elsevier, vol. 67(2), pages 139-146, May.
- Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," Review of Economic Studies, Oxford University Press, vol. 65(3), pages 361-393.
- Leybourne, S J & McCabe, B P M, 1994. "A Consistent Test for a Unit Root," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 157-166, April.
- Phillips, Peter C.B. & Ploberger, Werner, 1994.
"Posterior Odds Testing for a Unit Root with Data-Based Model Selection,"
Cambridge University Press, vol. 10(3-4), pages 774-808, August.
- Peter C.B. Phillips & Werner Ploberger, 1992. "Posterior Odds Testing for a Unit Root with Data-Based Model Selection," Cowles Foundation Discussion Papers 1017, Cowles Foundation for Research in Economics, Yale University.
- Perron, Pierre, 1989.
"The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis,"
Econometric Society, vol. 57(6), pages 1361-1401, November.
- Perron, P, 1988. "The Great Crash, The Oil Price Shock And The Unit Root Hypothesis," Papers 338, Princeton, Department of Economics - Econometric Research Program.
- Harvey, Andrew, 2001. "Testing in Unobserved Components Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(1), pages 1-19, January.
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