Abstract Motivated by the long‐lasting debate on whether United States Department of Agriculture's (USDA's) World Agricultural Supply and Demand Estimates (WASDE) forecasts are optimal, we employ an unknown loss method for ex post evaluation which assumes that USDA forecasters' function is unknown. We conduct optimality tests WASDE corn, soybeans, wheat published during 1988–2019. Our results s...

The purpose of this paper is to develop an output oriented methodology for calculating productivity growth by using Malmquist productivity index (MPI) and two different data envelopment analysis (DEA) views (optimistic and pessimistic) simultaneously, and apply it to five Iranian Commercial Banks over the four time period (2009-2013). Consequently, we have proposed a new approach called the dou...

This paper constructs a composite leading index for business cycle prediction based on vine copulas that capture the complex pattern of dependence among individual predictors. This approach is optimal in the sense that the resulting index possesses the highest discriminatory power as measured by the receiver operating characteristic (ROC) curve. The model specification is semi-parametric in nat...

This paper proposes a new method to forecast S&P 500 return distribution by combining quantile regression models using macro-finance variables with volatility-based models including various standard EGARCH and stochastic volatility specifications. 30 density forecasting models are compared and combined in an out-of-sample forecasting exercise. Using macro-finance variables is found to help subs...

This paper shows that out-of-sample forecast comparisons can help prevent data mining-induced overfitting. The basic results are drawn from simulations of a simple Monte Carlo design and a real data-based design similar to those in Lovell (1983) and Hoover and Perez (1999). In each simulation, a general-to-specific procedure is used to arrive at a model. If the selected specification includes a...

We forecast quarterly US in‡ation based on the generalized Phillips curve using econometric methods which incorporate dynamic model averaging. These methods not only allow for coe¢ cients to change over time, but also allow for the entire forecasting model to change over time. We …nd that dynamic model averaging leads to substantial forecasting improvements over simple benchmark regressions and...

This Working Paper should not be reported as representing the views of the IMF. The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate. This paper forecasts inflation in Sudan following two methodo...