Using information from singletons in fixed-effects estimation: xtfesing

In this article, we describe the xtfesing command. The command implements a generalized method of moments estimator that allows exploiting singleton information in fixed-effects panel-data regression as in Bruno, Magazzini, and Stampini (2020, Economics Letters 186: Article 108519).

Corruption and outbound business travels

This article investigates the effect of corruption on growth of outbound business travels (OBT), after controlling other relevant determinants of demands for OBT. The model is empirically tested for 62 countries from 2007 to 2016. Using a panel fixed effects estimation method, the results show that higher levels of corruption lead to the growth of OBT. We also find that the impact of corruption on OBT is more apparent in emerging economies than developed countries.

Fixed Effects Estimation of Large-TPanel Data Models

This article reviews recent advances in fixed effects estimation of panel data models for long panels, where the number of time periods is relatively large. We focus on semiparametric models with unobserved individual and time effects, where the distribution of the outcome variable, conditional on covariates and unobserved effects, is specified parametrically while the distribution of the unobserved effects is left unrestricted. In contrast to existing reviews on long panels, we discuss models with both individual and time effects, split-panel jackknife bias corrections, unbalanced panels, distribution and quantile effects, and other extensions. Understanding and correcting the incidental parameter bias caused by the estimation of many fixed effects are our main focuses, and the unifying theme is that the order of this bias is given by the simple formula p/ n for all models discussed, with p being the number of estimated parameters and n the total sample size.

The Reputation Effect

This paper proposes an empirical analysis of the role of memory in determining the size of credits granted by the European Bank for Reconstruction and Development (EBRD) during 1991–2003. We first build an original database from information associated with the number and contract types granted by clients, after which we develop an empirical strategy for capturing the role of memory, namely by defining three different indicators to approximate each client’s reputation. These indicators rely on the client’s identity and, when available, information associated with previous EBRD-financed investment projects. With the fixed-effects estimation technique, our results unambiguously show that the value of the first investment project financed by the EBRD, as a proxy for reputation, is the most effective indicator for established clients to determine the size of the credits they receive to finance further investments.