Wednesday, November 14, 2018

More Sandwiches, Anyone?

Consider this my Good Deed for the Day!

A re-tweet from a colleague whom I follow on Twitter brought an important paper to my attention. I thought I'd share it more widely.

The paper is titled, "Small-sample methods for cluster-robust variance estimation and hypothesis testing in fixed effect models", by James Pustejovski (@jepusto) and Beth Tipton (@stats-tipton). It appears in The Journal of Business and Economic Statistics.  

You can tell right away, from its title, that this paper is going to be a must-read for empirical economists. And note the words, "Small-sample" in the title - that sounds interesting.

 Here's a compilation of Beth's six tweets:

Monday, November 5, 2018

Econometrics Reading for November

In between raking leaves and dealing with some early snow, I've put together this list of suggested reading for you:
  • Beckert, W., 2018. A note on specification testing in some structural regression models. Mimeo., Department of Economics, Mathematics and Statistics, Birkbeck College, University of London.
  • Clarke, D., 2018. A convenient omitted bias formula for treatment effect models. Economics Letters, in press.
  • Liu, Y. & Y. Rho, 2018. On the choice of instruments in mixed frequency specification tests. Mimeo., School of Business and Economics, Michigan Technological University.
  • Lütkepohl, H., A. Staszewska-Bystrova, & P. Winker, 2018. Constructing joint confidence bands for impulse functions of VAR models - A review. Lodz Economic Working Paper 4/2018, Faculty of Economics and Sociology, University of Lodz.
  • Richardson, A., T. van Florenstein Mulder, & T. Vehbi, 2018. Nowcasting New Zealand GDP using machine learning algorithms.
  • Słoczyński, T., 2018. A general weighted average representation of the ordinary and two-stage least squares estimands. Mimeo., Department of Economics, Brandeis University.

© 2018, David E. Giles