000063059 001__ 63059 000063059 005__ 20190709135423.0 000063059 0247_ $$2doi$$a10.1016/j.matcom.2016.09.010 000063059 0248_ $$2sideral$$a97466 000063059 037__ $$aART-2017-97466 000063059 041__ $$aeng 000063059 100__ $$0(orcid)0000-0002-5583-3697$$aFerrer-Pérez, H.$$uUniversidad de Zaragoza 000063059 245__ $$aA comparison of two modified stationarity tests. A Monte Carlo study 000063059 260__ $$c2017 000063059 5060_ $$aAccess copy available to the general public$$fUnrestricted 000063059 5203_ $$aTo specify an econometric model with time series data, it is important to determine the order of integration of the variables in the model. In this paper, using a complete set of Monte Carlo experiments, we compare the behaviour of two stationarity tests, the Xiao test (Sn) and the KPSS (Kwiatkowski, Phillips, Schmidt and Shin) test, using an alternative estimator of the long-run variance to those used in the original version of the tests, to recommend which one to use in practice. First, we compare the small sample properties of the original Sn test with those of its modified version. We conclude that this modified version has a better size versus power trade-off than the original test. So, second, we compare the finite sample properties of the modified Sn and the modified KPSS. Since the modified KPSS exhibits higher power and size, we conduct a second experiment determining the critical value of each test, in such a way that the power of both tests coincides at 0.5, and then we examine their size for some local-to-unity values. The results show that, in most cases, the performance of the modified KPSS test dominates that of the modified Sn test. 000063059 536__ $$9info:eu-repo/grantAgreement/ES/DGA/S21$$9info:eu-repo/grantAgreement/ES/MICINN/ECO2009-07936$$9info:eu-repo/grantAgreement/ES/MICINN/ECO2015-65582$$9info:eu-repo/grantAgreement/ES/MICINN/ECO2016-74940-P 000063059 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/ 000063059 590__ $$a1.476$$b2017 000063059 591__ $$aMATHEMATICS, APPLIED$$b60 / 252 = 0.238$$c2017$$dQ1$$eT1 000063059 591__ $$aCOMPUTER SCIENCE, SOFTWARE ENGINEERING$$b46 / 104 = 0.442$$c2017$$dQ2$$eT2 000063059 591__ $$aCOMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS$$b70 / 105 = 0.667$$c2017$$dQ3$$eT3 000063059 592__ $$a0.613$$b2017 000063059 593__ $$aComputer Science (miscellaneous)$$c2017$$dQ1 000063059 593__ $$aTheoretical Computer Science$$c2017$$dQ2 000063059 593__ $$aApplied Mathematics$$c2017$$dQ2 000063059 593__ $$aModeling and Simulation$$c2017$$dQ2 000063059 593__ $$aNumerical Analysis$$c2017$$dQ3 000063059 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion 000063059 700__ $$0(orcid)0000-0001-8691-1064$$aAyuda, M.I.$$uUniversidad de Zaragoza 000063059 700__ $$0(orcid)0000-0002-8601-9380$$aAznar, A.$$uUniversidad de Zaragoza 000063059 7102_ $$14008$$2225$$aUniversidad de Zaragoza$$bDpto. Estruc.Hª Econ.y Eco.Pb.$$cÁrea Economía Aplicada 000063059 7102_ $$14000$$2415$$aUniversidad de Zaragoza$$bDpto. Análisis Económico$$cÁrea Fund. Análisis Económico 000063059 773__ $$g134 (2017), 28-36$$pMath. comput. simul.$$tMATHEMATICS AND COMPUTERS IN SIMULATION$$x0378-4754 000063059 8564_ $$s391147$$uhttps://zaguan.unizar.es/record/63059/files/texto_completo.pdf$$yPostprint 000063059 8564_ $$s56443$$uhttps://zaguan.unizar.es/record/63059/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint 000063059 909CO $$ooai:zaguan.unizar.es:63059$$particulos$$pdriver 000063059 951__ $$a2019-07-09-11:27:44 000063059 980__ $$aARTICLE