Structural changes in large economic datasets: A nonparametric homogeneity test
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DOI: 10.1016/j.econlet.2018.12.020
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- Billio, Monica & Casarin, Roberto & Costola, Michele & Pasqualini, Andrea, 2016.
"An entropy-based early warning indicator for systemic risk,"
Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 45(C), pages 42-59.
- Monica Billio & Roberto Casarin & Michele Costola & Andrea Pasqualini, 2015. "An entropy-based early warning indicator for systemic risk," Working Papers 2015:09, Department of Economics, University of Venice "Ca' Foscari".
- Maasoumi, Esfandiar & Racine, Jeff, 2002. "Entropy and predictability of stock market returns," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 291-312, March.
- Stock, James H. & Watson, Mark W., 2014.
"Estimating turning points using large data sets,"
Journal of Econometrics, Elsevier, vol. 178(P2), pages 368-381.
- James H. Stock & Mark W. Watson, 2010. "Estimating Turning Points Using Large Data Sets," NBER Working Papers 16532, National Bureau of Economic Research, Inc.
- Travis J. Berge & Òscar Jordà, 2011. "Evaluating the Classification of Economic Activity into Recessions and Expansions," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(2), pages 246-277, April.
- Costantini, Mauro & Lupi, Claudio, 2016. "Identifying stationary series in panels: A Monte Carlo evaluation of sequential panel selection methods," Economics Letters, Elsevier, vol. 138(C), pages 9-14.
- Duncan, Roberto, 2015.
"A threshold model of the US current account,"
Economic Modelling, Elsevier, vol. 48(C), pages 270-280.
- Roberto Duncan, 2014. "A Threshold Model of the US Current Account," Working Papers 20, Peruvian Economic Association.
- Roberto Duncan, 2014. "A threshold model of the US current account," Globalization Institute Working Papers 202, Federal Reserve Bank of Dallas.
- Michael W. McCracken & Serena Ng, 2016.
"FRED-MD: A Monthly Database for Macroeconomic Research,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 574-589, October.
- Michael W. McCracken & Serena Ng, 2015. "FRED-MD: A Monthly Database for Macroeconomic Research," Working Papers 2015-12, Federal Reserve Bank of St. Louis.
- Fabio Canova, 2004.
"Testing for Convergence Clubs in Income Per Capita: A Predictive Density Approach,"
International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(1), pages 49-77, February.
- Fabio Canova, 1997. "Testing for convergence clubs in income per-capita: A predictive density approach," Economics Working Papers 404, Department of Economics and Business, Universitat Pompeu Fabra, revised Jun 1999.
- Canova, Fabio, 2001. "Testing for convergence clubs in income per-capita: A predictive density approach," HWWA Discussion Papers 139, Hamburg Institute of International Economics (HWWA).
- Canova, Fabio, 2001. "Testing for Convergence Clubs in Income Per-Capita: A Predictive Density Approach," Discussion Paper Series 26361, Hamburg Institute of International Economics.
- Canova, Fabio, 1999. "Testing for Convergence Clubs in Income per-capita: A Predictive Density Approach," CEPR Discussion Papers 2201, C.E.P.R. Discussion Papers.
- Griffin, J.E. & Steel, M.F.J., 2011. "Stick-breaking autoregressive processes," Journal of Econometrics, Elsevier, vol. 162(2), pages 383-396, June.
- Keisuke Hirano, 2002. "Semiparametric Bayesian Inference in Autoregressive Panel Data Models," Econometrica, Econometric Society, vol. 70(2), pages 781-799, March.
- repec:dau:papers:123456789/1908 is not listed on IDEAS
- Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2018.
"Bayesian Nonparametric Calibration and Combination of Predictive Distributions,"
Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(522), pages 675-685, April.
- Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2015. "Bayesian nonparametric calibration and combination of predictive distributions," Working Paper 2015/03, Norges Bank.
- Roberto Casarin & Federico Bassetti & Francesco Ravazzolo, 2015. "Bayesian Nonparametric Calibration and Combination of Predictive Distributions," Working Papers 2015:04, Department of Economics, University of Venice "Ca' Foscari".
- Nikola Gradojevic & Marko Caric, 2017.
"Predicting Systemic Risk with Entropic Indicators,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(1), pages 16-25, January.
- Nikola Gradojevic & Marko Caric, 2015. "Predicting Systemic Risk with Entropic Indicators," Working Paper series 15-14, Rimini Centre for Economic Analysis.
- Watson, Mark W. & Stock, James H., 2014. "Estimating turning points using large data sets," Scholarly Articles 33192198, Harvard University Department of Economics.
- Bassetti, Federico & Casarin, Roberto & Leisen, Fabrizio, 2014.
"Beta-product dependent Pitman–Yor processes for Bayesian inference,"
Journal of Econometrics, Elsevier, vol. 180(1), pages 49-72.
- Federico Bassetti & Roberto Casarin & Fabrizio Leisen, 2013. "Beta-Product Dependent Pitman-Yor Processes for Bayesian Inference," Working Papers 2013:13, Department of Economics, University of Venice "Ca' Foscari".
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Cited by:
- Chen, Zhanshou & Xu, Qiongyao & Li, Huini, 2019. "Inference for multiple change points in heavy-tailed time series via rank likelihood ratio scan statistics," Economics Letters, Elsevier, vol. 179(C), pages 53-56.
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More about this item
Keywords
Bayesian nonparametric test; Distributional changes; Large datasets; US economy;All these keywords.
JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
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