Summer Reading

The schools are out, and here in Canada we celebrated Canada Day yesterday. That means it's now summer! And summer means summer reading.

So, here are some suggestions for you:

• Andreou, E., E. Ghysels, and A. Kourtellos, 2013. Should macroeconomic forecasters use daily financial data and how? Journal of Business and Economic Statistics, 31, 240-251.
• Downey, A. B., 2013. Think Bayes: Bayesian Statistics Made Simple. Green Tea Press, Needham MA.
• Espejo, M. R., M. D. Pineda, and S. Nadarajah, 2013. Optimal unbiased estimation of some population central moments. Metron, 71, 39-62.
• Giacomini, R., D. M. Politis, and H. White, 2013. A warp-speed method for conducting Monte Carlo experiments involving bootstrap estimators. Econometric Theory, 29, 567-589.
• Hayter, A. J., 2013. A new procedure for the Behrens-Fisher problem that guarantees confidence levels. Journal of Statistical Theory and Practice, 7, 515-536.
• Ouysse, R., 2013. Forecasting using a large number of predictors: Bayesian model averaging versus principal components regression. Australian School of Business Working Paper 2013 ECON 04, University of New South Wales.
• Pinkse, J., 2013. The ET interview: Herman Bierens. Econometric Theory, 29, 590-608.
• Stigler, S. M., 2007.  The epic story of maximum likelihood. Statistical Science, 22, 598-620.
• Yu, P., 2013. Inconsistency of 2SLS estimators in threshold regression with endogeneity. Economics Letters, in press.

© 2013, David E. Giles