Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects

Jiti Gao (), Fei Liu () and Bin Peng ()

No 44/20, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: In this paper, we investigate binary response models for heterogeneous panel data with interactive fixed effects by allowing both the cross sectional dimension and the temporal dimension to diverge. From a practical point of view, the proposed framework can be applied to predict the probability of corporate failure, conduct credit rating analysis, etc. Theoretically and methodologically, we establish a link between a maximum likelihood estimation and a least squares approach, provide a simple information criterion to detect the number of factors, and achieve the asymptotic distributions accordingly. In addition, we conduct intensive simulations to examine the theoretical findings. In the empirical study, we focus on the sign prediction of stock returns, and then use the results of sign forecast to conduct portfolio analysis. By implementing rolling-window based out–of– sample forecasts, we show the finite–sample performance and demonstrate the practical relevance of the proposed model and estimation method.

Keywords: binary response; heterogeneous panel; interactive fixed effects; portfolio analysis (search for similar items in EconPapers)
JEL-codes: C18 C23 G11 (search for similar items in EconPapers)
Pages: 49
Date: 2020
New Economics Papers: this item is included in nep-for and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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