Characterizing Selection Bias Using Experimental Data

Heckman, James J.; Ichimura, Hidehiko; Smith, Jeffrey A.; Todd, Petra

doi:10.2307/2999630

Cited by 1,795 publications

(915 citation statements)

References 33 publications

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“…The PSM also assumes conditional independence and the presence of a reasonable overlap of propensity scores (common support) (Winters et al, 2010). The method is intuitively attractive as it helps in comparing the observed outcomes of treated with the outcomes of the counterfactual control group (Heckman et al, 1998). It helps to evaluate programs that require longitudinal datasets using single cross-sectional dataset where the former does not exist.…”

Section: Propensity Score Matching Methodsmentioning

confidence: 99%

“…Despite its advantages, it requires enough data that must be available or feasible to produce experimental treatment effect results. The PSM method basically matches observations of participant and non-participant farmers according to their predicted propensity of participation in AVCMP (Rosebaum & Rubin, 1983;Heckman et al, 1998;Smith & Todd, 2005;Wooldridge, 2005). In the first step, the conditional probability of participation (propensity score) is estimated using the Probit model by controlling for observed household characteristics.…”

Section: Propensity Score Matching Methodsmentioning

confidence: 99%

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Impact of Farmer Mentorship Project on Farm Efficiency and Income in Rural Ghana

Martey¹,

Dogbe²,

Etwire³

et al. 2015

JAS

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This paper examines the impact of participation in Agricultural Value Chain Mentorship Project on farm efficiency and income of soybean farmers in Northern Region of Ghana. Due to the exogenous and non-random assignment of the intervention, propensity score matching analysis was used to estimate impact on a cross-section of 200 smallholder farmers. Participation in farmer mentorship project impacts positively on farm technical efficiency by 28 percent. However, participation did not significantly translate into higher farm income. This finding suggests that exposing farmers to agricultural development projects may directly increase their technical capability wtihtin the short term but does not guarantee higher income. The design of any agricultural development project must incorporate the specific needs of farmers to ensure ownership, increased participation and sustainability.

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Section: Propensity Score Matching Methodsmentioning

confidence: 99%

Section: Propensity Score Matching Methodsmentioning

confidence: 99%

Impact of Farmer Mentorship Project on Farm Efficiency and Income in Rural Ghana

Martey¹,

Dogbe²,

Etwire³

et al. 2015

JAS

View full text Add to dashboard Cite

show abstract

“…Researchers suggest that covariates that affect both intervention participation and outcomes should be included in the estimation of the propensity score (Caliendo & Kopeinig, 2008;Heckman, Ichimura, Smith, & Todd, 1998;Lechner, 2002;Ravallion, 2001). Covariates included in this study were derived from correlates of college enrollment and transition planning participation that have been cited in the literature described above: youth's gender, age, race/ethnicity, disability severity, high school achievement, family income, mother's education level, whether parents ever enrolled in a postsecondary school/program, and parents' expectation of youth attending college.…”

Section: Covariatesmentioning

confidence: 99%

The Effect of Transition Planning Participation and Goal-Setting on College Enrollment Among Youth With Autism Spectrum Disorders

Wei

Wagner

Hudson

et al. 2015

Remedial and Special Education

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This study used propensity score techniques to assess the relationship between transition planning participation and goalsetting and college enrollment among youth with Autism Spectrum Disorders. Using data from Waves 1 through 5 of the National Longitudinal Transition Study-2, this study found that 2-or 4-year college enrollment rates were significantly higher among youth with ASDs who participated in transition planning and those who had a primary transition goal of college enrollment. Educational implications are discussed.

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“…[...] Thus the choice of an appropriate econometric model critically depends on the data on which it is applied" (Heckman et al 1998b). …”

Section: Mergingmentioning

confidence: 99%

Evaluating the Impact of Public Start-up Assistance - Results from an Econometric Approach

Almus

2002

SSRN Journal

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This paper analyzes the medium-term growth performance of firms that exclusively received start-up assistance from programs administered by the Deutsche Ausgleichsbank (DtA), a state owned bank, within two years after startup. I apply a parametric selection approach that controls for two potential sources of self selection (receipt of assistance, complete interview data). The empirical analysis shows that firms receiving assistance perform better in terms of employment growth over a six year period. +49/621-1235-170 E-mail: almus@zew.de † Financial support from the Deutsche Ausgleichsbank (DtA) and the German Science Foundation under the grant LE1147/1-1 is gratefully acknowledged. Thanks to Wolfgang Franz, Georg Licht, Susanne Prantl, Frank Reize, Daniel Skambracks and Jochen Struck for valuable comments and discussion. Moreover, I thank Ruth Dollard for proof-reading. All errors that remain are, of course, the responsibility of the author alone. Non-technical summary:The Deutsche Ausgleichsbank (DtA), a state owned bank, provides with its programs in the 'Entrepreneurship/Start-up' segment more than 80 per cent of all in Germany allocated public assistance means in this segment in the past decade. An evaluation of whether these programs have an impact on the medium-term development of firms or not is necessary and wanted because of the huge amount of means spent and the high expectations connected with these programs.This study uses information of the ZEW Entrepreneurship Study and a DtA data set that contains all assistance acceptances from 1990 to 1999 to evaluate the impact of the DtA assistance segment 'Entrepreneurship/ Start-up'.This was already done in some previous studies. Contrary to the short term horizon of these studies this analysis has a medium term evaluation horizon since employment growth over a six year period serves as success measure.Moreover, this study avoids some methodological problems of previous studies. An approach that controls for two possible sources of selection, which could lead to biased results if not considered, is therefore applied to assess whether DtA assistance has a medium term influence on the employment development. One possible source of selection concerns the fact that not the same amount of information for all firms is available in the ZEW Entrepreneurship Study. Therefore, it is possible that certain firms are more likely to possess a higher information content that can be used in the analysis. On the other hand, a descriptive analysis showed that the allocation of the DtA funds does not follow a principle of 'equal shares for all', but special firm groups are more likely to receive funding. This separates the observations into four groups. The econometric analysis shows that assistance receiving firms grow, other things equal, on average seven percentage points faster compared to firms not receiving DtA assistance. This result indicates the success of the programs under consideration.

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Characterizing Selection Bias Using Experimental Data

Cited by 1,795 publications

References 33 publications

Impact of Farmer Mentorship Project on Farm Efficiency and Income in Rural Ghana

Impact of Farmer Mentorship Project on Farm Efficiency and Income in Rural Ghana

The Effect of Transition Planning Participation and Goal-Setting on College Enrollment Among Youth With Autism Spectrum Disorders

Evaluating the Impact of Public Start-up Assistance - Results from an Econometric Approach

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