Forecasting

In this paper it is shown theoretically and in simulations that under a variety of different unobserved factor structures, Partial Least Squares (PLS) and Bayesian regressions provide a better fit for a target variable relative to Principal Components (PC) regrssion. Empirically, PLS and Bayesian regressions usually have better out-of-sample performances than PC regression. Published in Computational Statistics & Data Analysis, 2016.

This posts reviews the key challenges in inflation forecasting and discusses some recent developments that attempt to deal with these challenges. Published on Liberty Street Economics, November 05 2014.

I discuss the latest developments in commodity price forecasting using a variety of predictors in the context of the paper ‘Forecasting Commdity Price Indexes Using Macroeconomic and Financial Predictors’. Published in the International Journal of Forecasting, 2014.

In this paper we seek to produce forecasts of commodity price movements that can systematically improve on naive statistical benchmarks, including factor-augmented models, and revisit the forecasting performance of changes in commodity currencies as efficient predictors of commodity prices. Published in NBER East Asia Seminar on Economics: Commodity Prices and Markets, 2011.

This paper reexamines predictability of nominal exchange rate returns by means of fundamental models. Published in Empirical Economics, 1999.