Often researchers find parametric models restrictive and sensitive to deviations from the
parametric specifications; semi-nonparametric models are more flexible and robust, but lead …

As large language models (LLMs) like GPT become increasingly prevalent, it is essential
that we assess their capabilities beyond language processing. This paper examines the …

This chapter reviews recent advances in nonparametric and semiparametric estimation, with
an emphasis on applicability to empirical research and on resolving issues that arise in …

How should we measure changes in consumer welfare given observed data on prices and
expenditures? This article proposes a nonparametric approach that holds under arbitrary …

We provide a practical method to estimate the payoff functions of players in complete
information, static, discrete games. With respect to the empirical literature on entry games …

This study examines the incentives for content contribution in social media. We propose that
exposure and reputation are the major incentives for contributors. Besides, as more and …

This paper considers the nonparametric and semiparametric methods for estimating
regression models with continuous endogenous regressors. We list a number of different …

We provide easy to verify sufficient conditions for the consistency and asymptotic normality
of a class of semiparametric optimization estimators where the criterion function does not …

We utilize graphical representations of Dictator Games which generate rich individual-level
data. Our baseline experiment employs budget sets over feasible payoff-pairs. We test these …

Revealed preference theory offers a criterion for decision-making quality: if decisions are
high quality then there exists a utility function the choices maximize. We conduct a large …