scholarly journals ESTIMATING CAUSAL EFFECTS OF ALCOHOL ACCESS AND USE ON A BROAD SET OF RISKY BEHAVIORS: REGRESSION DISCONTINUITY EVIDENCE

2018 ◽  
Vol 37 (3) ◽  
pp. 427-448 ◽  
Author(s):  
Jason M. Fletcher
Keyword(s):  
Regression Discontinuity ◽  
Risky Behaviors ◽  
Causal Effects ◽  
Alcohol Access

Causal effects of corporate taxes on private firms' earnings management: a regression discontinuity analysis

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gaowen Kong
Keyword(s):  
Earnings Management ◽  
Regression Discontinuity ◽  
Tax Incentives ◽  
Causal Effects ◽  
Private Firms ◽  
Effective Tax Rate ◽  
Tax Collection ◽  
Content Type ◽  
Tax Rate ◽  
Earnings Information

PurposeThe authors emphasize the information role of earnings management and how it may be used to “mislead some stakeholders about the underlying economic performance of the company or to influence contractual outcomes that depend on reported accounting numbers.” Specifically, the authors examine the causal effect of tax incentives on private firms' earnings management based on a corporate tax reform in China.Design/methodology/approachIn December 2001, China implemented a tax collection reform which moved the collection of corporate income taxes from the local tax bureau to the state tax bureau. This reform results in exogenous variations in the effective tax rate among similar firms established before and after 2002. The authors apply a regression discontinuity design and use the generated variation in the effective tax rate to investigate the impact of taxes on firm earnings management.FindingsThe authors find that tax reduction substantially increases private firms' incentives to manage earnings information, and such effect is particularly pronounced when tax collection intensity and government interventions are low. Further evidence shows that lower tax rates stimulate firms' investment, inventory turnover and recruitment of skilled human capital. A plausible mechanism is that private firms signal a promising outlook by managing earnings to attain greater financing and improve investment/operation levels when financial constraints are removed.Originality/valueFirst, the authors present the causal effects of tax incentives on private firm's earnings management, which deepens the authors’ understanding on the determinants of firm's earnings information production. Second, this study also contributes to the literature on tax-induced earnings management. Third, the authors believe that this topic offers clear policy implications and would be of particular interest to regulators.

scholarly journals Graphical Models for Quasi-experimental Designs

2015 ◽  
Vol 46 (2) ◽  
pp. 155-188 ◽  
Author(s):  
Peter M. Steiner ◽  
Yongnam Kim ◽  
Courtney E. Hall ◽  
Dan Su
Keyword(s):  
Graphical Models ◽  
Instrumental Variable ◽  
Regression Discontinuity ◽  
Experimental Designs ◽  
Causal Effects ◽  
Confounding Bias ◽  
Randomized Controlled ◽  
Quasi Experimental ◽  
Causal Graphs ◽  
Latent Subgroups

Randomized controlled trials (RCTs) and quasi-experimental designs like regression discontinuity (RD) designs, instrumental variable (IV) designs, and matching and propensity score (PS) designs are frequently used for inferring causal effects. It is well known that the features of these designs facilitate the identification of a causal estimand and, thus, warrant a causal interpretation of the estimated effect. In this article, we discuss and compare the identifying assumptions of quasi-experiments using causal graphs. The increasing complexity of the causal graphs as one switches from an RCT to RD, IV, or PS designs reveals that the assumptions become stronger as the researcher’s control over treatment selection diminishes. We introduce limiting graphs for the RD design and conditional graphs for the latent subgroups of compliers, always takers, and never takers of the IV design, and argue that the PS is a collider that offsets confounding bias via collider bias.

scholarly journals Bounds on treatment effects in regression discontinuity designs with a manipulated running variable

2020 ◽  
Vol 11 (3) ◽  
pp. 839-870 ◽  
Author(s):  
François Gerard ◽  
Miikka Rokkanen ◽  
Christoph Rothe
Keyword(s):  
Unemployment Insurance ◽  
General Model ◽  
Regression Discontinuity ◽  
Causal Effects ◽  
Potential Outcomes ◽  
Binary Decision ◽  
Sharp Bounds ◽  
Wide Range ◽  
Regression Discontinuity Designs ◽  
Disincentive Effect

The key assumption in regression discontinuity analysis is that the distribution of potential outcomes varies smoothly with the running variable around the cutoff. In many empirical contexts, however, this assumption is not credible; and the running variable is said to be manipulated in this case. In this paper, we show that while causal effects are not point identified under manipulation, one can derive sharp bounds under a general model that covers a wide range of empirical patterns. The extent of manipulation, which determines the width of the bounds, is inferred from the data in our setup. Our approach therefore does not require making a binary decision regarding whether manipulation occurs or not, and can be used to deliver manipulation‐robust inference in settings where manipulation is conceivable, but not obvious from the data. We use our methods to study the disincentive effect of unemployment insurance on (formal) reemployment in Brazil, and show that our bounds remain informative, despite the fact that manipulation has a sizable effect on our estimates of causal parameters.

scholarly journals Effect of holding office on the behavior of politicians

2016 ◽  
Vol 113 (48) ◽  
pp. 13690-13695 ◽  
Author(s):  
Daniel Enemark ◽  
Clark C. Gibson ◽  
Mathew D. McCubbins ◽  
Brigitte Seim
Keyword(s):  
Regression Discontinuity ◽  
Experimental Designs ◽  
Causal Effects ◽  
Government Officials ◽  
Public Resources ◽  
Previous Election ◽  
Vote Trading ◽  
Recruitment And Selection ◽  
Behavioral Games ◽  
Norm Of Reciprocity

Reciprocity is central to our understanding of politics. Most political exchanges—whether they involve legislative vote trading, interbranch bargaining, constituent service, or even the corrupt exchange of public resources for private wealth—require reciprocity. But how does reciprocity arise? Do government officials learn reciprocity while holding office, or do recruitment and selection practices favor those who already adhere to a norm of reciprocity? We recruit Zambian politicians who narrowly won or lost a previous election to play behavioral games that provide a measure of reciprocity. This combination of regression discontinuity and experimental designs allows us to estimate the effect of holding office on behavior. We find that holding office increases adherence to the norm of reciprocity. This study identifies causal effects of holding office on politicians’ behavior.

scholarly journals Effects of Peers and Rank on Cognition, Preferences, and Personality

2020 ◽  
pp. 1-47
Author(s):  
Utteeyo Dasgupta ◽  
Subha Mani ◽  
Smriti Sharma ◽  
Saurabh Singhal
Keyword(s):  
Big Five ◽  
Regression Discontinuity ◽  
Big Five Personality Traits ◽  
Causal Effects ◽  
Big Five Personality ◽  
Risk Averse ◽  
Regression Discontinuity Design ◽  
Selective College ◽  
Selective Colleges ◽  
Economic Preferences

We exploit the variation in admission cutoffs across colleges at a leading Indian university to estimate the causal effects of enrolling in a selective college on cognitive attainment, economic preferences, and Big Five personality traits. Using a regression discontinuity design, we find that enrolling in a selective college improves university exam scores of the marginally admitted females, and makes them less overconfident and less risk averse, while males in selective colleges experience a decline in extraversion and conscientiousness. We find differences in peer quality and rank concerns to be driving our findings.

scholarly journals Evaluating Econometric Evaluations of Post-Secondary Aid

2015 ◽  
Vol 105 (5) ◽  
pp. 502-507 ◽  
Author(s):  
Josh Angrist ◽  
David Autor ◽  
Sally Hudson ◽  
Amanda Pallais
Keyword(s):  
Financial Aid ◽  
Regression Discontinuity ◽  
Causal Effect ◽  
Causal Effects ◽  
Regression Discontinuity Design ◽  
Random Assignment ◽  
Post Secondary ◽  
Design Selection ◽  
Ongoing Evaluation

In an ongoing evaluation of post-secondary financial aid, we use random assignment to assess the causal effects of large privately-funded aid awards. Here, we compare the unbiased causal effect estimates from our RCT with two types of non-experimental econometric estimates. The first applies a selection-on-observables assumption in data from an earlier, nonrandomized cohort; the second uses a regression discontinuity design. Selection-on-observables methods generate estimates well below the experimental benchmark. Regression discontinuity estimates are similar to experimental estimates for students near the cutoff, but sensitive to controlling for the running variable, which is unusually coarse.

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