This paper considers identification and estimation of structural interaction effects in a social interaction model. The model allows unobservables in the group structure, which may be correlated with included regressors. We show that both the endogenous and exogenous interaction effects can be identified if there are sufficient variations in group sizes. We consider the estimation of the model ...

Frölich (2004) compares the finite sample properties of reweighting and matching estimators of average treatment effects and concludes that reweighting performs far worse than even the simplest matching estimator. We argue that this conclusion is unjustified. Neither approach dominates the other uniformly across data generating processes (DGPs). Expanding on the Frölich’s (2004) analysis, this ...

This article considers quasi-maximum likelihood estimations (QMLE) for two spatial panel data regression models: mixed effects model with spatial errors and transformed mixed effects model (where response and covariates are transformed) with spatial errors. One aim of transformation is to normalize the data, thus the transformed models are more robust with respect to the normality assumption co...

This paper demonstrates a method for estimating treatment effects in spatial tests, utilizing a second control group to measure unexplained spatial phenomena. The technique is implemented on two innovations in Ugandan microfinance, and we measure the ways in which concurrent shocks such as an ebola outbreak and a contentious presidential election altered outcomes differentially across regions. ...

This paper proposes to reexamine the GATT/WTO membership effect on bilateral trade flows, using nonparametric methods including pair-matching, permutation tests, and a Rosenbaum (2002) sensitivity analysis. Taken together in a coherent manner, these methods provide an estimation framework that is robust to misspecification biases, allows general forms of heterogeneous treatment effects, and add...

This paper provides preliminary evidence that interest groups reduce both the level and the volatility of returns on a national stock market. These findings are robust to model specifications that include traditional growth regression “policy” variables as well as political, economic, and financial institutions variables. The estimated magnitude of the relationship between interest group activi...

Nonlinear regression with measurement error is important for estimation from microeconomic data. One approach to identification and estimation is a causal model, where the unobserved true variable is predicted by observable variables. This paper is about estimation of such a model using simulated moments and a flexible disturbance distribution. An estimator of the asymptotic variance is given f...

We implement an endogeneous switching-regression model for labour productivity and firms’ decision to use business–to–business (B2B) e–commerce. Our approach allows B2B usage to affect any parameter of the labour productivity equation and to properly take account of strategic complementarities between the input factors and B2B usage. Empirical evidence from 1,394 German firms shows that firms u...

A Martingale Representation for Matching Estimators Matching estimators are widely used in statistical data analysis. However, the distribution of matching estimators has been derived only for particular cases (Abadie and Imbens, 2006). This article establishes a martingale representation for matching estimators. This representation allows the use of martingale limit theorems to derive the asym...

Using many valid instrumental variables has the potential to improve efficiency but makes the usual inference procedures inaccurate. We give corrected standard errors, an extension of Bekker (1994) to nonnormal disturbances, that adjust for many instruments. We find that this adujstment is useful in empirical work, simulations, and in the asymptotic theory. Use of the corrected standard errors ...