Does the Running Variable Matter? A Second Look at Discontinuity Designs for Evaluating Regional Economic Development and Business Incentive Policies

Detalhes bibliográficos
Autor(a) principal: Bondonio, D.
Data de Publicação: 2019
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10071/18936
Resumo: Regional economic development and business incentive programs have a prominent role in the European Union (EU). For evaluating these programs, in recent years, a growing number of studies have exploited either spatial discontinuities, set by boundaries of the targeted areas, or ranking discontinuities, based on EU-fund eligibility indexes or firm-level application scores. In light of this literature, impact evaluations are being increasingly commissioned and designed under an a-priori assumptions that discontinuity designs have superior impact identification properties. This paper argues that in a number of frequently encountered, but often unrecognized, circumstances this assumption does not hold ground. When the running variable has a weak influence on the outcome of the analysis, discontinuity designs are at risk of either unnecessarily reduce external validity or, in the presence small sample sizes, failing to achieve the complete balancing of relevant controls. In this scenario, ensuring the common support for the crucial confounders and adopting statistical matching estimators, often constitute a more viable empirical option.
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spelling Does the Running Variable Matter? A Second Look at Discontinuity Designs for Evaluating Regional Economic Development and Business Incentive PoliciesDiscontinuity designsRegional economic developmentBusiness incentivesRegional economic development and business incentive programs have a prominent role in the European Union (EU). For evaluating these programs, in recent years, a growing number of studies have exploited either spatial discontinuities, set by boundaries of the targeted areas, or ranking discontinuities, based on EU-fund eligibility indexes or firm-level application scores. In light of this literature, impact evaluations are being increasingly commissioned and designed under an a-priori assumptions that discontinuity designs have superior impact identification properties. This paper argues that in a number of frequently encountered, but often unrecognized, circumstances this assumption does not hold ground. When the running variable has a weak influence on the outcome of the analysis, discontinuity designs are at risk of either unnecessarily reduce external validity or, in the presence small sample sizes, failing to achieve the complete balancing of relevant controls. In this scenario, ensuring the common support for the crucial confounders and adopting statistical matching estimators, often constitute a more viable empirical option.DINÂMIA'CET - IUL2019-12-02T11:55:46Z2019-11-01T00:00:00Z2019-11info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/18936engBondonio, D.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:26:36Zoai:repositorio.iscte-iul.pt:10071/18936Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:11:54.298086Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Does the Running Variable Matter? A Second Look at Discontinuity Designs for Evaluating Regional Economic Development and Business Incentive Policies
title Does the Running Variable Matter? A Second Look at Discontinuity Designs for Evaluating Regional Economic Development and Business Incentive Policies
spellingShingle Does the Running Variable Matter? A Second Look at Discontinuity Designs for Evaluating Regional Economic Development and Business Incentive Policies
Bondonio, D.
Discontinuity designs
Regional economic development
Business incentives
title_short Does the Running Variable Matter? A Second Look at Discontinuity Designs for Evaluating Regional Economic Development and Business Incentive Policies
title_full Does the Running Variable Matter? A Second Look at Discontinuity Designs for Evaluating Regional Economic Development and Business Incentive Policies
title_fullStr Does the Running Variable Matter? A Second Look at Discontinuity Designs for Evaluating Regional Economic Development and Business Incentive Policies
title_full_unstemmed Does the Running Variable Matter? A Second Look at Discontinuity Designs for Evaluating Regional Economic Development and Business Incentive Policies
title_sort Does the Running Variable Matter? A Second Look at Discontinuity Designs for Evaluating Regional Economic Development and Business Incentive Policies
author Bondonio, D.
author_facet Bondonio, D.
author_role author
dc.contributor.author.fl_str_mv Bondonio, D.
dc.subject.por.fl_str_mv Discontinuity designs
Regional economic development
Business incentives
topic Discontinuity designs
Regional economic development
Business incentives
description Regional economic development and business incentive programs have a prominent role in the European Union (EU). For evaluating these programs, in recent years, a growing number of studies have exploited either spatial discontinuities, set by boundaries of the targeted areas, or ranking discontinuities, based on EU-fund eligibility indexes or firm-level application scores. In light of this literature, impact evaluations are being increasingly commissioned and designed under an a-priori assumptions that discontinuity designs have superior impact identification properties. This paper argues that in a number of frequently encountered, but often unrecognized, circumstances this assumption does not hold ground. When the running variable has a weak influence on the outcome of the analysis, discontinuity designs are at risk of either unnecessarily reduce external validity or, in the presence small sample sizes, failing to achieve the complete balancing of relevant controls. In this scenario, ensuring the common support for the crucial confounders and adopting statistical matching estimators, often constitute a more viable empirical option.
publishDate 2019
dc.date.none.fl_str_mv 2019-12-02T11:55:46Z
2019-11-01T00:00:00Z
2019-11
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publisher.none.fl_str_mv DINÂMIA'CET - IUL
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