121064 20240319080946.0 doi 10.1080/07350015.2020.1773834 sideral 118842 ART-2022-118842 eng Camacho, Máximo A new approach to dating the reference cycle 2022 Access copy available to the general public Unrestricted This article proposes a new approach to the analysis of the reference cycle turning points, defined on the basis of the specific turning points of a broad set of coincident economic indicators. Each individual pair of specific peaks and troughs from these indicators is viewed as a realization of a mixture of an unspecified number of separate bivariate Gaussian distributions whose different means are the reference turning points. These dates break the sample into separate reference cycle phases, whose shifts are modeled by a hidden Markov chain. The transition probability matrix is constrained so that the specification is equivalent to a multiple change-point model. Bayesian estimation of finite Markov mixture modeling techniques is suggested to estimate the model. Several Monte Carlo experiments are used to show the accuracy of the model to date reference cycles that suffer from short phases, uncertain turning points, small samples, and asymmetric cycles. In the empirical section, we show the high performance of our approach to identifying the US reference cycle, with little difference from the timing of the turning point dates established by the NBER. In a pseudo real-time analysis, we also show the good performance of this methodology in terms of accuracy and speed of detection of turning point dates. info:eu-repo/grantAgreement/ES/MICINN/ECO2017-83255-C3-1-P info:eu-repo/grantAgreement/ES/MICINN/ECO2017-83255-C3-3-P info:eu-repo/semantics/openAccess by-nc http://creativecommons.org/licenses/by-nc/3.0/es/ 3.0 2022 STATISTICS & PROBABILITY 17 / 125 = 0.136 2022 Q1 T1 SOCIAL SCIENCES, MATHEMATICAL METHODS 16 / 53 = 0.302 2022 Q2 T1 ECONOMICS 130 / 380 = 0.342 2022 Q2 T2 6.15 2022 Economics and Econometrics 2022 Q1 Statistics, Probability and Uncertainty 2022 Q1 Statistics and Probability 2022 Q1 Social Sciences (miscellaneous) 2022 Q1 7.6 2022 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Gadea, María Dolores Universidad de Zaragoza (orcid)0000-0001-6609-4247 Gómez Loscos, Ana 4014 225 Universidad de Zaragoza Dpto. Economía Aplicada Área Economía Aplicada 40, 1 (2022), 66-81 J. bus. econ. stat. JOURNAL OF BUSINESS & ECONOMIC STATISTICS 0735-0015 1882253 http://zaguan.unizar.es/record/121064/files/texto_completo.pdf Postprint 1673480 http://zaguan.unizar.es/record/121064/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:121064 articulos driver 2024-03-18-12:33:16 ARTICLE