{"title":"On the Size Distortion of a Test for Equality between the ATE and FE Estimands","authors":"David H. Pacini","doi":"10.1515/JEM-2018-0011","DOIUrl":"https://doi.org/10.1515/JEM-2018-0011","url":null,"abstract":"Abstract This note investigates the numerical performance of an existing asymptotic test for the null hypothesis of equality between the average treatment effect (ATE) and the group fixed-effect (FE) estimands based on the standardized difference between ATE and FE estimators. It shows that this test has a size distortion. This distortion has implications to empirical economic research. It can lead to erroneously confirm the relevance of heterogeneous responses to policy interventions.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/JEM-2018-0011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45406922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Testing Spatial Dependence in Spatial Models with Endogenous Weights Matrices","authors":"Anil K. Bera, Osman Doğan, Suleyman Taspinar","doi":"10.2139/ssrn.3167555","DOIUrl":"https://doi.org/10.2139/ssrn.3167555","url":null,"abstract":"Abstract In this study, we propose simple test statistics for identifying the source of spatial dependence in spatial autoregressive models with endogenous weights matrices. Elements of the weights matrices are modelled in such a way that endogenity arises when the unobserved factors that affect elements of the weights matrices are correlated with the unobserved factors in the outcome equation. The proposed test statistics are robust to the presence of endogeneity in the weights and can be used to detect spatial dependence in the dependent variable and/or the disturbance terms. The robust test statistics are easy to calculate as computationally simple estimations are needed for their calculations. Our Monte Carlo results indicate that these tests have good size and power properties in finite samples. We also provide an empirical illustration to demonstrate the usefulness of the robust tests in identifying the source of spatial dependence.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2139/ssrn.3167555","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47034295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Nonparametric estimation of natural direct and indirect effects based on inverse probability weighting","authors":"Yu‐Chin Hsu, M. Huber, Tsung-Chih Lai","doi":"10.1515/JEM-2017-0016","DOIUrl":"https://doi.org/10.1515/JEM-2017-0016","url":null,"abstract":"Abstract Using a sequential conditional independence assumption, this paper discusses fully nonparametric estimation of natural direct and indirect causal effects in causal mediation analysis based on inverse probability weighting. We propose estimators of the average indirect effect of a binary treatment, which operates through intermediate variables (or mediators) on the causal path between the treatment and the outcome, as well as the unmediated direct effect. In a first step, treatment propensity scores given the mediator and observed covariates or given covariates alone are estimated by nonparametric series logit estimation. In a second step, they are used to reweigh observations in order to estimate the effects of interest. We establish root-n consistency and asymptotic normality of this approach as well as a weighted version thereof. The latter allows evaluating effects on specific subgroups like the treated, for which we derive the asymptotic properties under estimated propensity scores. We also provide a simulation study and an application to an information intervention about male circumcisions.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/JEM-2017-0016","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47315252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Regression Discontinuity and Heteroskedasticity Robust Standard Errors: Evidence from a Fixed-Bandwidth Approximation","authors":"Otávio Bartalotti","doi":"10.1515/JEM-2016-0007","DOIUrl":"https://doi.org/10.1515/JEM-2016-0007","url":null,"abstract":"Abstract In regression discontinuity designs (RD), for a given bandwidth, researchers can estimate standard errors based on different variance formulas obtained under different asymptotic frameworks. In the traditional approach the bandwidth shrinks to zero as sample size increases; alternatively, the bandwidth could be treated as fixed. The main theoretical results for RD rely on the former, while most applications in the literature treat the estimates as parametric, implementing the usual heteroskedasticity-robust standard errors. This paper develops the “fixed-bandwidth” alternative asymptotic theory for RD designs, which sheds light on the connection between both approaches. I provide alternative formulas (approximations) for the bias and variance of common RD estimators, and conditions under which both approximations are equivalent. Simulations document the improvements in test coverage that fixed-bandwidth approximations achieve relative to traditional approximations, especially when there is local heteroskedasticity. Feasible estimators of fixed-bandwidth standard errors are easy to implement and are akin to treating RD estimators as locally parametric, validating the common empirical practice of using heteroskedasticity-robust standard errors in RD settings. Bias mitigation approaches are discussed and a novel bootstrap higher-order bias correction procedure based on the fixed bandwidth asymptotics is suggested.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/JEM-2016-0007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45475970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Testing for a Functional Form of Mean Regression in a Fully Parametric Environment","authors":"Stanislav Anatolyev","doi":"10.1515/JEM-2016-0013","DOIUrl":"https://doi.org/10.1515/JEM-2016-0013","url":null,"abstract":"Abstract We develop a test for a restricted functional form of a mean regression when a complex distributional model for all variables is estimated. The test statistic is an average squared deviation from the estimated hypothesized function of the form implied by the estimated parametric model, and is asymptotically distributed as a mixture of χ2 distributions. The test is easy to implement using numerical derivatives, and it performs well in samples of typical size. We illustrate the test using data on labor market characteristics of US young men.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/JEM-2016-0013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44970252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Further Results on Interpreting Coefficients in Regressions with a Logarithmic Dependent Variable","authors":"Aren Megerdichian","doi":"10.1515/jem-2016-0015","DOIUrl":"https://doi.org/10.1515/jem-2016-0015","url":null,"abstract":"Abstract Estimators are presented for quantifying the proportional rate of change in the continuous variable Y from a regression in which the dependent variable is the logarithm of Y, and the data generation process includes explanatory variables of interest that may be binary (dummy), continuous, or logarithmic. Estimators from earlier works that examine the binary explanatory variable are special cases of the results presented here. The additional estimators provided here will be useful to practitioners who must convert coefficients estimated from regression models specified with a logarithmic dependent variable into proportional rates of change.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/jem-2016-0015","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47309679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Esmeralda A. Ramalho, Joaquim J. S. Ramalho, L. Coelho
{"title":"Exponential Regression of Fractional-Response Fixed-Effects Models with an Application to Firm Capital Structure","authors":"Esmeralda A. Ramalho, Joaquim J. S. Ramalho, L. Coelho","doi":"10.1515/jem-2015-0019","DOIUrl":"https://doi.org/10.1515/jem-2015-0019","url":null,"abstract":"Abstract New fixed-effects estimators are proposed for logit and complementary loglog fractional regression models. The standard specifications of these models are transformed into a form of exponential regression with multiplicative individual effects and time-variant heterogeneity, from which four alternative estimators that do not require assumptions on the distribution of the unobservables are proposed. All new estimators are robust to both time-variant and time-invariant heterogeneity and can accomodate fractional responses with observations at the boundary value of zero. Additionally, some of these estimators can be applied to dynamic panel data models and can accommodate endogenous explanatory variables without requiring the specification of a reduced form model. A Monte Carlo study and an application to firm capital structure choices illustrate the usefulness of the suggested estimators.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/jem-2015-0019","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45840670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Working with Data: Two Empiricists’ Experience","authors":"Christopher R. Knittel, Konstantinos Metaxoglou","doi":"10.1515/jem-2016-0001","DOIUrl":"https://doi.org/10.1515/jem-2016-0001","url":null,"abstract":"Abstract We propose a set of best practices on how to organize empirical research drawn from our experience. We offer some ideas on organizing, processing and analyzing data efficiently with an eye towards quality control, documentation, and replicability. Although these best practices are by no means unique, they have served us and colleagues well over the years. We hope they will be helpful to students and young economists in their research endeavors.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/jem-2016-0001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42369647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"On the Validity of Edgeworth Expansions and Moment Approximations for Three Indirect Inference Estimators","authors":"Stelios Arvanitis, Antonis Demos","doi":"10.1515/jem-2015-0009","DOIUrl":"https://doi.org/10.1515/jem-2015-0009","url":null,"abstract":"Abstract This paper deals with higher order asymptotic properties for three indirect inference estimators. We provide conditions that ensure the validity of locally uniform, with respect to the parameter, Edgeworth approximations. When these are of sufficiently high order they also form integrability conditions that validate locally uniform moment approximations. We derive the relevant second order bias and MSE approximations for the three estimators as functions of the respective approximations for the auxiliary estimator. We confirm that in the special case of deterministic weighting and affinity of the binding function, one of them is second order unbiased. The other two estimators do not have this property under the same conditions. Moreover, in this case, the second order approximate MSEs imply the superiority of the first estimator. We generalize to multistep procedures that provide recursive indirect inference estimators which are locally uniformly unbiased at any given order. Furthermore, in a particular case, we manage to validate locally uniform Edgeworth expansions for one of the estimators without any differentiability requirements for the estimating equations. We examine the bias-MSE results in a small Monte Carlo exercise.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/jem-2015-0009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66939654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Inference with Difference-in-Differences Revisited","authors":"M. Brewer, Thomas F. Crossley, R. Joyce","doi":"10.1515/jem-2017-0005","DOIUrl":"https://doi.org/10.1515/jem-2017-0005","url":null,"abstract":"Abstract A growing literature on inference in difference-in-differences (DiD) designs has been pessimistic about obtaining hypothesis tests of the correct size, particularly with few groups. We provide Monte Carlo evidence for four points: (i) it is possible to obtain tests of the correct size even with few groups, and in many settings very straightforward methods will achieve this; (ii) the main problem in DiD designs with grouped errors is instead low power to detect real effects; (iii) feasible GLS estimation combined with robust inference can increase power considerably whilst maintaining correct test size – again, even with few groups, and (iv) using OLS with robust inference can lead to a perverse relationship between power and panel length.","PeriodicalId":36727,"journal":{"name":"Journal of Econometric Methods","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/jem-2017-0005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66939359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}