Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Gafarov, Bulat"'
We propose a novel approach to identification in structural vector autoregressions (SVARs) that uses external instruments for heteroscedasticiy of a structural shock of interest. This approach does not require lead/lag exogeneity for identification,
Externí odkaz:
http://arxiv.org/abs/2407.03265
Autor:
Gafarov, Bulat
It is well known that in the presence of heteroscedasticity ordinary least squares estimator is not efficient. I propose a generalized automatic least squares estimator (GALS) that makes partial correction of heteroscedasticity based on a (potentiall
Externí odkaz:
http://arxiv.org/abs/2304.07331
Publikováno v:
In Journal of Econometrics February 2024 239(1)
We study the bias of classical quantile regression and instrumental variable quantile regression estimators. While being asymptotically first-order unbiased, these estimators can have non-negligible second-order biases. We derive a higher-order stoch
Externí odkaz:
http://arxiv.org/abs/2011.03073
Autor:
Gafarov, Bulat
This paper studies a regularized support function estimator for bounds on components of the parameter vector in the case in which the identified set is a polygon. The proposed regularized estimator has three important properties: (i) it has a uniform
Externí odkaz:
http://arxiv.org/abs/1904.00111
Climate change impact studies inform policymakers on the estimated damages of future climate change on economic, health and other outcomes. In most studies, an annual outcome variable is observed, e.g. agricultural yield, along with a higher-frequenc
Externí odkaz:
http://arxiv.org/abs/1808.07861
Publikováno v:
In Journal of Econometrics April 2018 203(2):316-327
Akademický článek
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We study the small sample properties of conditional quantile estimators such as classical and IV quantile regression. First, we propose a higher-order analytical framework for comparing competing estimators in small samples and assessing the accuracy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1687::f35c998c39eec886d3fadf4db76c0260
https://hdl.handle.net/10419/235416
https://hdl.handle.net/10419/235416