000109524 001__ 109524
000109524 005__ 20220120235522.0
000109524 0247_ $$2doi$$a10.1007/s00181-017-1355-x
000109524 0248_ $$2sideral$$a102283
000109524 037__ $$aART-2019-102283
000109524 041__ $$aeng
000109524 100__ $$0(orcid)0000-0002-1610-5451$$aGimenez-Nadal, José Ignacio$$uUniversidad de Zaragoza
000109524 245__ $$aResampling and bootstrap algorithms to assess the relevance of variables: applications to cross-section entrepreneurship data
000109524 260__ $$c2019
000109524 5060_ $$aAccess copy available to the general public$$fUnrestricted
000109524 5203_ $$aIn this paper, we propose an algorithmic approach based on resampling and bootstrap techniques to measure the importance of a variable, or a set of variables, in econometric models. This algorithmic approach allows us to check the real weight of a variable in a model, avoiding the biases of classical tests, and to select the more relevant variables, or models, in terms of predictability, by reducing dimensions. We apply this methodology to the Global Entrepreneurship Monitor data for the year 2014, to analyze the individual- and national-level determinants of entrepreneurial activity, and compare the results with a forward selection approach, also based on resampling
predictability, and a standard forward stepwise selection process. We find that our proposed techniques offer more accurate results, which show that innovation and new technologies, peer effects, the sociocultural environment, entrepreneurial education at University, R&D transfers, and the availability of government subsidies are among the most important predictors of entrepreneurial behavior.
000109524 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/ECO2012-34828$$9info:eu-repo/grantAgreement/ES/MINECO/MTM2014-53340-P
000109524 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000109524 590__ $$a1.308$$b2019
000109524 591__ $$aSOCIAL SCIENCES, MATHEMATICAL METHODS$$b30 / 51 = 0.588$$c2019$$dQ3$$eT2
000109524 591__ $$aECONOMICS$$b201 / 371 = 0.542$$c2019$$dQ3$$eT2
000109524 592__ $$a0.586$$b2019
000109524 593__ $$aSocial Sciences (miscellaneous)$$c2019$$dQ1
000109524 593__ $$aStatistics and Probability$$c2019$$dQ2
000109524 593__ $$aEconomics and Econometrics$$c2019$$dQ2
000109524 593__ $$aMathematics (miscellaneous)$$c2019$$dQ2
000109524 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000109524 700__ $$0(orcid)0000-0001-8471-3224$$aLafuente, Miguel$$uUniversidad de Zaragoza
000109524 700__ $$0(orcid)0000-0002-9437-4606$$aMolina, José Alberto$$uUniversidad de Zaragoza
000109524 700__ $$0(orcid)0000-0002-0553-6360$$aVelilla Gambó, Jorge$$uUniversidad de Zaragoza
000109524 7102_ $$12007$$2265$$aUniversidad de Zaragoza$$bDpto. Métodos Estadísticos$$cÁrea Estadís. Investig. Opera.
000109524 7102_ $$14000$$2415$$aUniversidad de Zaragoza$$bDpto. Análisis Económico$$cÁrea Fund. Análisis Económico
000109524 773__ $$g56, 1 (2019), 233-267$$pEmpir. econ.$$tEmpirical Economics$$x0377-7332
000109524 8564_ $$s1096796$$uhttps://zaguan.unizar.es/record/109524/files/texto_completo.pdf$$yPostprint
000109524 8564_ $$s1367735$$uhttps://zaguan.unizar.es/record/109524/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000109524 909CO $$ooai:zaguan.unizar.es:109524$$particulos$$pdriver
000109524 951__ $$a2022-01-20-22:51:17
000109524 980__ $$aARTICLE