Heteroscedasticity and Autocorrelation Robust F and t Tests in Stata

Xiaoqing Ye and Yixiao Sun

University of California at San Diego, Economics Working Paper Series from Department of Economics, UC San Diego

Abstract: In this article, we consider time series OLS and IV regressions and introduce a new pair of commands, har and hart, which implement a more accu- rate class of heteroscedasticity and autocorrelation robust (HAR) F and t tests. These tests represent part of the recent progress on HAR inference. The F and t tests are based on the convenient F and t approximations and are more accurate than the conventional chi-squared and normal approximations. The underlying smoothing parameters are selected to target the type I and type II errors, the two fundamental objects in every hypothesis testing problem. The estimation com- mand har and the post-estimation test command hart allow for both kernel HAR variance estimators and orthonormal series HAR variance estimators. In addition, we introduce another pair of new commands, gmmhar and gmmhart which imple- ment the recently developed F and t tests in a two-step GMM framework. For this command we opt for the orthonormal series HAR variance estimator based on the Fourier bases, as it allows us to develop convenient F and t approxima- tions as in the first-step GMM framework. Finally, we present several examples to demonstrate the use of these commands.

Keywords: Social; and; Behavioral; Sciences (search for similar items in EconPapers)
Date: 2018-07-09
New Economics Papers: this item is included in nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.escholarship.org/uc/item/0bb8d0s9.pdf;origin=repeccitec (application/pdf)

Related works:
Journal Article: Heteroskedasticity- and autocorrelation-robust F and t tests in Stata (2018)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cdl:ucsdec:qt0bb8d0s9

Access Statistics for this paper

More papers in University of California at San Diego, Economics Working Paper Series from Department of Economics, UC San Diego Contact information at EDIRC.
Bibliographic data for series maintained by Lisa Schiff ().