Zobrazeno 1 - 10
of 310
pro vyhledávání: '"Fernández, Val"'
We provide a simple distribution regression estimator for treatment effects in the difference-in-differences (DiD) design. Our procedure is particularly useful when the treatment effect differs across the distribution of the outcome variable. Our pro
Externí odkaz:
http://arxiv.org/abs/2409.02311
Rank-rank regressions are widely used in economic research to evaluate phenomena such as intergenerational income persistence or mobility. However, when covariates are incorporated to capture between-group persistence, the resulting coefficients can
Externí odkaz:
http://arxiv.org/abs/2407.06387
We propose an instrumental variable framework for identifying and estimating average and quantile effects of discrete and continuous treatments with binary instruments. The basis of our approach is a local copula representation of the joint distribut
Externí odkaz:
http://arxiv.org/abs/2403.05850
The Arellano-Bond estimator is a fundamental method for dynamic panel data models, widely used in practice. However, the estimator is severely biased when the data's time series dimension $T$ is long due to the large degree of overidentification. We
Externí odkaz:
http://arxiv.org/abs/2402.00584
Using CPS data for 1976 to 2022 we explore how wage inequality has evolved for married couples with both spouses working full time full year, and its impact on household income inequality. We also investigate how marriage sorting patterns have change
Externí odkaz:
http://arxiv.org/abs/2310.07839
We consider the estimation of a dynamic distribution regression panel data model with heterogeneous coefficients across units. The objects of primary interest are specific functionals of these coefficients. These include predicted actual and stationa
Externí odkaz:
http://arxiv.org/abs/2202.04154
Publikováno v:
In Journal of Econometrics March 2024 240(2)
Publikováno v:
In Journal of Econometrics March 2024 240(2)
We provide estimation methods for nonseparable panel models based on low-rank factor structure approximations. The factor structures are estimated by matrix-completion methods to deal with the computational challenges of principal component analysis
Externí odkaz:
http://arxiv.org/abs/2010.12439
In ordinary quantile regression, quantiles of different order are estimated one at a time. An alternative approach, which is referred to as quantile regression coefficients modeling (QRCM), is to model quantile regression coefficients as parametric f
Externí odkaz:
http://arxiv.org/abs/2006.00160