(This article was originally published at Econometrics Beat: Dave Giles' Blog, and syndicated at StatsBlogs.)
Here are some of the papers that I've been reading recently. Some of them may appeal to you, too:
- Bampinas, G., K. Ladopoulos, &T. Panagiotidis, 2017. A note on the estimated GARCH coefficients from the S&P1500 universe. WP 17-09, Rimini Centre for Economic Analysis.
- Heberle, J. & C. Sattarhoff, 2017. A fast algorithm for the computation of HAC covariance matrix estimators. Econometrics, 5(1), 9; doi:10.3390/econometrics5010009.
- Kristensen, D. & B. Salanié, 2017. Higher-order properties of approximate estimators. Journal of Econometrics, online.
- Lei, J., M. G'Sell, A. Rinaldo, R. J. Tibshirani, & L. Wasserman, 2017.Distribution-free predictive inference for regression. Journal of the American Statistical Association, online.
- Tsagbey, S., M. De carvalho, & G. L. Page, 2017. All data are wrong, but some are useful? Advocating the need for data auditing. American Statistician, online.
- Zhang, X. & C-A. Liu, 2017. Inference after model averaging in linear regression models. IEAS Working Paper No. 17-A005.
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