Econometrics
Statistical methods for economic data, causal inference, and forecasting.
econ.EM · 119 papersNonparametric Identification and Estimation of Causal Effects on Latent Outcomes
This paper introduces a nonparametric framework for identifying and estimating causal effects on latent outcomes, addressing comparability issues.
The Condition-Number Principle for Prototype Clustering
A new geometric framework and condition number link objective accuracy to structural recovery in prototype clustering, providing robust recovery guarantees.
Identification in (Endogenously) Nonlinear SVARs Is Easier Than You Think
This paper demonstrates that identifying endogenously nonlinear SVARs is as straightforward as linear SVARs, simplifying their application.
Assessing Sensitivity to IV Exclusion and Exogeneity without First Stage Monotonicity
This paper introduces new sensitivity analyses for instrumental variable assumptions, accommodating heterogeneity and relaxing first-stage monotonicity.
Identification in Dynamic Dyadic Network Formation Models with Fixed Effects
This paper establishes identification results for dynamic dyadic network formation models, incorporating fixed effects, time-varying covariates, and local network statistics.
Better Measurement or Larger Samples? Data Collection for Policy Learning with Unobserved Heterogeneity
This paper explores how to optimize data collection for policy learning, balancing measurement precision of latent traits with sample size to maximize welfare.
Representativeness and Efficiency in Overidentified IV
This paper introduces the Representative Targeting (RT) estimator to address efficiency and interpretability issues in GMM for overidentified IV models.
Seasonality in Mixed Causal-Noncausal Processes
This paper shows seasonal roots in Mixed Causal-Noncausal Autoregressive (MAR) models can be isolated, preventing new joint seasonal effects.
Testing for Monotone Equilibrium Strategies in Games of Incomplete Information
A new statistical framework tests for monotone Bayesian Nash equilibrium strategies in incomplete information games, enabling detection of cartels in auctions.
A Large-Scale Empirical Comparison of Meta-Learners and Causal Forests for Heterogeneous Treatment Effect Estimation in Marketing Uplift Modeling
This paper benchmarks CATE estimators on a large marketing dataset, finding S-Learner performs best and identifying key HTE drivers.
Sequential Audit Sampling with Statistical Guarantees
This paper presents a sequential audit sampling framework with statistical guarantees for finite populations, controlling decision error probabilities ex ante.
Generalized Poisson Dynamic Network Models
Introduces Generalized Poisson dynamic network models to accurately capture under- and overdispersion in count-weighted temporal networks.
You've Got to be Efficient: Ambiguity, Misspecification and Variational Preferences
A new framework for robust statistical decisions under ambiguity and misspecification shows optimal choices often align with correct specification.
Estimating Long Run Welfare Outcome in Rotating Panel with Grouped Fixed Effects: Application to Poverty Dynamics in Peru
This paper applies Grouped Fixed Effects to rotating panel data to accurately estimate long-run poverty dynamics and mobility, outperforming existing methods.
Dynamic Factor Stochastic Volatility-in-Mean VAR for Large Macroeconomic Panels
This paper introduces a Dynamic Factor Stochastic Volatility-in-Mean VAR model, improving macroeconomic forecasting, especially during crises.
Unified Mixture Sampler for State-Space Models: Application to Stochastic Conditional Duration Models
A unified mixture sampler (UMS) offers a universal, efficient framework for nonlinear state-space models, outperforming conventional methods.
Nonparametric Identification and Estimation of Production Functions Invariant to Productivity Dynamics
This paper introduces a new nonparametric method for estimating production functions that avoids bias from productivity dynamics, yielding more accurate markups and policy impact assessments.
Confidence Sets under Weak Identification: Theory and Practice
This paper introduces new, reliable, and efficient methods for constructing confidence sets in linear IV models, robust to weak identification.
UK Income Inequality and Taxation, 2000--2023: A $κ$-generalised Distribution Analysis
This paper analyzes UK income inequality (2000-2023), finding income redistribution with the top 1% gaining and the tax base driven by non-top earners.
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