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Bootstrap Tests for the Effect of a Treatment on the Distribution of an Outcome Variable
Abadie, Alberto - 2021
This paper considers the problem of assessing the distributional consequences of a treatment on some outcome variable of interest when treatment intake is (possibly) non-randomized but there is a binary instrument available for the researcher. Such scenario is common in observational studies and...
Persistent link: https://www.econbiz.de/10013238969
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What are We Weighting for?
Solon, Gary - 2013
, (2) to achieve consistent estimates by correcting for endogenous sampling, and (3) to identify average partial effects in …
Persistent link: https://www.econbiz.de/10013085910
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How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise
Ait-Sahalia, Yacine - 2005
optimal sampling frequency at which to estimate the parameters of a discretely sampled continuous-time model can be finite … that sampling as often as possible is optimal. But, more surprisingly, we also demonstrate that this is true even if one …
Persistent link: https://www.econbiz.de/10012785227
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Using Samples of Unequal Length in Generalized Method of Moments Estimation
Lynch, Anthony W. - 2008
Many applications in financial economics use data series with different starting or ending dates. This paper describes estimation methods, based on the generalized method of moments (GMM), which make use of all available data for each moment condition. We introduce two asymptotically equivalent...
Persistent link: https://www.econbiz.de/10012769647
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Maximum Likelihood Estimation of Discretely Sampled Diffusions : A Closed-Form Approach
Ait-Sahalia, Yacine - 2021
When a continuous-time diffusion is observed only at discrete dates, not necessarily close together, the likelihood function of the observations is in most cases not explicitly computable. Researchers have relied on simulations of sample paths in between the observations points, or numerical...
Persistent link: https://www.econbiz.de/10013216521
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Conditioning on the Probability of Selection to Control Selection Bias
Angrist, Joshua D. - 2021
Problems of sample selection arise in the analysis of both experimental and non-experimental data. In clinical trials to evaluate the impact of an intervention on health and mortality, treatment assignment is typically nonrandom in a sample of survivors even if the original assignment is random....
Persistent link: https://www.econbiz.de/10013221121
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A La Recherche Des Moments Perdus : Covariance Models for Unbalanced Panels with Endogenous Death
Abowd, John M.; Crepon, Bruno; Kramarz, Francis; … - 2021
We develop a model for decomposing the covariance structure of panel data on firms into a part due to permanent heterogeneity, a part due to differential histories with unknown ages, and a part due to the evolution of economic shocks to the firm. Our model allows for the endogenous death of...
Persistent link: https://www.econbiz.de/10013221330
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Sample Selection Bias as a Specification Error (with an Application to the Estimation of Labor Supply Functions)
Heckman, James J. - 2021
In this paper, I present a simple characterization of the sample selection bias problem that is also applicable to the conceptually distinct econometric problems that arise from truncated samples and from models with limited dependent variables. The problem of sample selection bias is fit within...
Persistent link: https://www.econbiz.de/10013222664
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Consistent Estimation Using Data from More than One Sample
Dickens, William T.; Ross, Brian A. - 2021
This paper considers the estimation of linear models when group average data from more than one sample is used. Conditions under which OL8 coefficient estimates are consistent are identified. The standard OL8 covariance estimate is shown to be inconsistent and a consistent estimator is proposed....
Persistent link: https://www.econbiz.de/10013248725
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The Effects of Random and Discrete Sampling When Estimating Continuous-Time Diffusions
Ait-Sahalia, Yacine; Mykland, Per A. - 2021
particular, we measure the additional effects of the randomness of the sampling intervals over and beyond those due to the … discreteness of the data. We also examine the effect of simply ignoring the sampling randomness. We find that in many situations … the randomness of the sampling has a larger impact than the discreteness of the data …
Persistent link: https://www.econbiz.de/10013210694