In this paper, we look at conventional methods for removing endogeneity bias in regression models, including the linear model and the probit model. The usual Heckman two-step procedure should not be used in the probit model: from a theoretical perspective, this procedure is unsatisfactory, and likelihood methods are superior. However, serious numerical problems occur when standard software pack...

The competitive and cooperative relationships between suppliers enterprises have important implications for enterprise strategy operational decisions. Using data from listed manufacturing companies in China 2007 to 2020, this paper empirically examines the impact of supplier concentration on corporate risk taking its underlying mechanism. results support view industrial organizations a supply c...

The use of adaptive designs in conjoint analysis has been shown to lead to an endogeneity bias in part-worth estimates using sampling experiments. In this paper, we re-examine the endogeneity issue in light of the likelihood principle. The likelihood principle asserts that all relevant information in the data about model parameters is contained in the likelihood function. We show that adhering ...

Abstract. We model costly interactions (contracts) between managers and investors. We suggest that globalization of production and favorable technology shock of the 1990s altered economic environment of managerinvestor interactions. These changes exacerbate agency conflict due to the increased managerial gains from ex post reneging, and, simultaneously, decreased costs of managerial reneging. I...

This paper develops a nonparametric approach to identification and estimation of treatment effects on censored outcomes when treatment may be endogenous and have arbitrarily heterogeneous effects. Identification is based on an instrumental variable that satisfies the exclusion and monotonicity conditions standard in the local average treatment effects framework. The paper proposes a censored qu...

T are many critical concerns (including the accounting for endogeneity) when one is properly estimating response functions. However, it is sometimes (certainly not always) better to leave some variables exogenous when building mathematical models intended to help decision makers. The exogenous variables allow the decision maker to better adapt the mathematical model to different situations and ...