matching estimators
A Martingale Representation for Matching Estimators
... Matching estimators (Rubin, 1973a, 1977; Rosenbaum, 2002) are widely used in statistical data ...of matching estimators has been derived only for particular cases (Abadie and Imbens, ...a ...
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A wild bootstrap algorithm for propensity score matching estimators
... We introduce a wild bootstrap algorithm for the approximation of the sampling distribution of pair or one-to-many propensity score matching estimators. Unlike the conventional iid bootstrap, the proposed ...
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Bootstrap inference of matching estimators for average treatment effects
... This paper proposes a weighted bootstrap inference method for matching estimators of treatment effects. In contrast to the naive bootstrap, our weighted bootstrap method is valid under asymptotics with a ...
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Bootstrap Inference for K-Nearest Neighbour Matching Estimators
... (KNN) matching estimators of average causal ...the matching covariate, we obtain a bootstrap scheme valid also with heterogeneous causal effects where mild assumptions on the heterogeneity are ...
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Bootstrap inference for K-nearest neighbour matching estimators
... (KNN) matching estimators (Abadie and Imbens, 2006) are popular for estimating, non-parametrically, the average causal effect of a binary variable on an outcome in observational studies, where confounders ...
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Simple and Bias-Corrected Matching Estimators for Average Treatment Effects
... Matching estimators for average treatment effects are widely used in evaluation research despite the fact that their large sample properties have not been established in many ...of matching ...
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Does bullying reduce educational achievement? An evaluation using matching estimators
... several matching methods based on the propensity score estimator (PSM) which does not require an exclusion restriction, or a particular specification of the model for bullying at ...observed. Matching ...
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Score-matching estimators for continuous-time point-process regression models
... efficient estimators based on score matching for probabilistic point process ...likelihood-based estimators, score matching estimators operate on continuous-time data, with computa- ...
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On the Failure of the Bootstrap for Matching Estimators
... addresses the question of the validity of the bootstrap for nearest-neighbor matching estimators with a fixed number of neighbors. We show in a simple case with a single continuous covariate that the ...
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On the Failure of the Bootstrap for Matching Estimators
... Matching estimators are widely used for the evaluation of programs or treat- ...neighbor matching, the standard conditions for the bootstrap are not satisfied, leading the bootstrap variance to ...
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Matching Estimators with Few Treated and Many Control Observations
... of matching estimators when the number of con- trol observations is large, but the number of treated observations is ...neighbor matching estimator is asymptotically unbiased for the ATT under stan- ...
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Evaluating the foreign ownership wage premium using a difference-indifferences matching approach
... this matching estimator in levels but rather use a difference-in-differences (DID) matching estimator on the matched plants ...standard matching estimators are usually unsatisfactory ...
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The Broadband Digital Divide and the Benefits of Mobile Broadband for Minorities
... This study sets out the facts regarding broadband deployment and usage in the US and the particular promise of mobile broadband for minorities. Fixed broadband is nearly ubiquitous and most people have access to four or ...
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The Effects of Remittances on Poverty at the Household Level in Bolivia: A Propensity Score Matching Approach
... bias estimators because of a possible identification problem; unobserved determinants of poverty may be correlated with receiving ...propensity matching estimators introduced first by Rosenbaun and ...
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Who’s got a match?:The development of skills at university and the returns to skills at work
... In Table 1, the focus is on respondents who state that their undergraduate course developed specific skills and capabilities ‘a lot’. The coefficients reported in the table refer to the impact of this intervention on ...
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The finite sample performance of inference methods for propensity score matching and weighting estimators
... the matching estimators, the methods based on bootstrapping t-statistics which include the propensity score adjustment generally do best in terms of size, while the ones without adjustment are conservative, ...
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Balancing Score Adjusted Targeted Minimum Loss-based Estimation
... We say that an estimator using the propensity score has the balancing score property if it is consistent when the estimated propensity score con- verges to a balancing score. Such estimators are in general not ...
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Some problems of inference in two-dimensional distributions
... carefully measured stone ring data of Alexander Thom and in the next few sections fitting of this data will be discussed, as well as some discussion of some of the methods used by Thom and others to estimate the circular ...
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Improved Estimators of Finite Population Variance using Unknown Weight of Auxiliary Variable
... proposed estimators were obtained by transforming [S+18] ...proposed estimators have been obtained and the conditions for their efficiencies over some existing variance estimators have been ...
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Empirical Bayes Estimation in Cross-Classified Gaussian Models With Unbalanced Design
... An advantage of the empirical Bayes approach is that in using the data to estimate the hyperparameter, one can appeal to frequentist considerations. In other words, use the Bayesian formalism to obtain a parametric ...
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