23 citations · 42 across the 10 of their papers we have counts for
12 papers
Uniform Validity of the Subset Anderson-Rubin Test under Heteroskedasticity and Nonlinearity
Atsushi Inoue, Òscar Jordà, Guido M. Kuersteiner
We consider the Anderson-Rubin (AR) statistic for a general set of nonlinear moment restrictions. The statistic is based on the criterion function of the continuous updating estima…
Differential Test Performance and Peer Effects
Guido Kuersteiner, Ingmar Prucha, Ying Zeng
We use variation of test scores measuring closely related skills to isolate peer effects. The intuition for our identification strategy is that the difference in closely related sc…
Overidentification in Shift-Share Designs
Jinyong Hahn, Guido Kuersteiner, Andres Santos +1
This paper studies the testability of identifying restrictions commonly employed to assign a causal interpretation to two stage least squares (TSLS) estimators based on Bartik inst…
Inference for Local Projections
Atsushi Inoue, Òscar Jordà, Guido M. Kuersteiner
Inference for impulse responses estimated with local projections presents interesting challenges and opportunities. Analysts typically want to assess the precision of individual es…
Efficient Bias Correction for Cross-section and Panel Data
Jinyong Hahn, David W. Hughes, Guido Kuersteiner +1
Bias correction can often improve the finite sample performance of estimators. We show that the choice of bias correction method has no effect on the higher-order variance of semip…
Efficient Peer Effects Estimators with Group Effects
Guido M. Kuersteiner, Ingmar R. Prucha, Ying Zeng
We study linear peer effects models where peers interact in groups, individual's outcomes are linear in the group mean outcome and characteristics, and group effects are random. Ou…
Limit Theorems for Data with Network Structure
Guido M. Kuersteiner
This paper develops new limit theory for data that are generated by networks or more generally display cross-sectional dependence structures that are governed by observable and uno…
Joint Time Series and Cross-Section Limit Theory under Mixingale Assumptions
Jinyong Hahn, Guido Kuersteiner, Maurizio Mazzocco
In this paper we complement joint time series and cross-section convergence results of Hahn, Kuersteiner and Mazzocco (2016) by allowing for serial correlation in the time series s…
Dynamic Spatial Panel Models: Networks, Common Shocks, and Sequential Exogeneity
Guido M. Kuersteiner, Ingmar R. Prucha
This paper considers a class of GMM estimators for general dynamic panel models, allowing for weakly exogenous covariates and cross sectional dependence due to spatial lags, unspec…
Central Limit Theory for Combined Cross-Section and Time Series with an Application to Aggregate Productivity Shocks
Jinyong Hahn, Guido Kuersteiner, Maurizio Mazzocco
Combining cross-section and time series data is a long and well established practice in empirical economics. We develop a central limit theory that explicitly accounts for possible…
Invariance Principles for Dependent Processes Indexed by Besov Classes with an Application to a Hausman Test for Linearity
Guido M. Kuersteiner
This paper considers functional central limit theorems for stationary absolutely regular mixing processes. Bounds for the entropy with bracketing are derived using recent results i…
Estimation with Aggregate Shocks
Jinyong Hahn, Guido Kuersteiner, Maurizio Mazzocco
Aggregate shocks affect most households' and firms' decisions. Using three stylized models we show that inference based on cross-sectional data alone generally fails to correctly a…