Regression Discontinuity Applications with Rounding Errors in the Running Variable

Many empirical applications of regression discontinuity (RD) models use a running variable that is rounded and hence discrete, e.g. age in years, or birth weight in ounces. This paper shows that standard RD estimation using a rounded discrete running variable leads to inconsistent estimates of treat...
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Gespeichert in:

Autor*in:	Dong, Yingying [verfasserIn]

Format:	Artikel
Sprache:	Englisch

Erschienen:	2015

Rechteinformationen:	Nutzungsrecht: Copyright © 2014 John Wiley & Sons, Ltd.

Schlagwörter:	Regression analysis Studies Estimating techniques Econometrics United States--US Errors China Mandatory insurance coverage

Übergeordnetes Werk:	Enthalten in: Journal of applied econometrics - Chichester : Wiley-Blackwell, 1986, 30(2015), 3, Seite 422-446
Übergeordnetes Werk:	volume:30 ; year:2015 ; number:3 ; pages:422-446

Links:	Volltext Link aufrufen Link aufrufen

DOI / URN:	10.1002/jae.2369

Katalog-ID:	OLC1957252952

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title	Regression Discontinuity Applications with Rounding Errors in the Running Variable
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title_full	Regression Discontinuity Applications with Rounding Errors in the Running Variable
author_sort	Dong, Yingying
journal	Journal of applied econometrics
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author-letter	Dong, Yingying
doi_str_mv	10.1002/jae.2369
dewey-full	330
title_sort	regression discontinuity applications with rounding errors in the running variable
title_auth	Regression Discontinuity Applications with Rounding Errors in the Running Variable
abstract	Many empirical applications of regression discontinuity (RD) models use a running variable that is rounded and hence discrete, e.g. age in years, or birth weight in ounces. This paper shows that standard RD estimation using a rounded discrete running variable leads to inconsistent estimates of treatment effects, even when the true functional form relating the outcome and the running variable is known and is correctly specified. This paper provides simple formulas to correct for this discretization bias. The proposed approach does not require instrumental variables, but instead uses information regarding the distribution of rounding errors, which is easily obtained and often close to uniform. Bounds can be obtained without knowing the distribution of the rounding error. The proposed approach is applied to estimate the effect of Medicare on insurance coverage in the USA, and to investigate the retirement‐consumption puzzle in China, utilizing the Chinese mandatory retirement policy. Copyright © 2014 John Wiley & Sons, Ltd.
abstractGer	Many empirical applications of regression discontinuity (RD) models use a running variable that is rounded and hence discrete, e.g. age in years, or birth weight in ounces. This paper shows that standard RD estimation using a rounded discrete running variable leads to inconsistent estimates of treatment effects, even when the true functional form relating the outcome and the running variable is known and is correctly specified. This paper provides simple formulas to correct for this discretization bias. The proposed approach does not require instrumental variables, but instead uses information regarding the distribution of rounding errors, which is easily obtained and often close to uniform. Bounds can be obtained without knowing the distribution of the rounding error. The proposed approach is applied to estimate the effect of Medicare on insurance coverage in the USA, and to investigate the retirement‐consumption puzzle in China, utilizing the Chinese mandatory retirement policy. Copyright © 2014 John Wiley & Sons, Ltd.
abstract_unstemmed	Many empirical applications of regression discontinuity (RD) models use a running variable that is rounded and hence discrete, e.g. age in years, or birth weight in ounces. This paper shows that standard RD estimation using a rounded discrete running variable leads to inconsistent estimates of treatment effects, even when the true functional form relating the outcome and the running variable is known and is correctly specified. This paper provides simple formulas to correct for this discretization bias. The proposed approach does not require instrumental variables, but instead uses information regarding the distribution of rounding errors, which is easily obtained and often close to uniform. Bounds can be obtained without knowing the distribution of the rounding error. The proposed approach is applied to estimate the effect of Medicare on insurance coverage in the USA, and to investigate the retirement‐consumption puzzle in China, utilizing the Chinese mandatory retirement policy. Copyright © 2014 John Wiley & Sons, Ltd.
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container_issue	3
title_short	Regression Discontinuity Applications with Rounding Errors in the Running Variable
url	http://dx.doi.org/10.1002/jae.2369 http://onlinelibrary.wiley.com/doi/10.1002/jae.2369/abstract http://search.proquest.com/docview/1676127947
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doi_str	10.1002/jae.2369
up_date	2024-07-03T23:40:51.044Z
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