This paper develops a nonparametric model that represents how sequences of outcomes and treatment choices influence one another in a dynamic manner. In this setting, we are interested in identifying the average outcome for individuals in each period, had a particular treatment sequence been...

We provide a complete asymptotic distribution theory for clustered data with a large number of groups, generalizing the classic laws of large numbers, uniform laws, central limit theory, and clustered covariance matrix estimation. Our theory allows for clustered observations with heterogeneous...

In a 'smart' electricity distribution network, flexible distribution resources (FDRs) can be coordinated to improve efficiency. But coordination enables whoever controls such resources to exercise market power. The paper establishes the following efficiency rankings of market structures:...

In a seminal paper, Feenstra (1994) developed an instrumental variable estimator which is becoming increasingly popular for estimating demand elasticities. Soderbery (2015) extended this estimator and created a routine which was shown to be more robust to data outliers when the number of time...

This paper estimates demand for residential solar photovoltaic (PV) systems using a new approach to address three empirical challenges that often arise with count data: excess zeros, unobserved heterogeneity, and endogeneity of price. Our results imply a price elasticity of demand for solar PV...

In this study, we provide a guideline for dealing with endogenous inputs and environmental variables in Battese and Coelli's (1995) stochastic frontier model. Our Monte Carlo simulations show that our estimators perform well

This study provides a guideline for dealing with endogenous inputs and environmental variables in Battese and Coelli's (1995) stochastic frontier model, which has been used in a vast number of empirical studies. The presence of endogenous variables in Battese and Coelli's model leads to...

In this paper, a control function approach is developed to deal with endogeneity issue in estimating panel data models with ordered response. This methodology is characterized by a two-step procedure, requiring only standard regression to be implemented in each step. To demonstrate the...

This paper considers transformations of nonlinear semiparametric mean functions that yield moment conditions for estimation. Such transformations are said to be information equivalent if they yield the same asymptotic efficiency bound. I derive a unified theory of algebraic equivalence for...

This paper introduces a panel GMM framework for identifying and estimating demand elasticities via heteroscedasticity. While existing panel estimators address the simultaneity problem, the state-ofthe-art Feenstra/Soderbery (F/S) estimator suffers from inconsistency, inefficiency, and lacks a...