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Unobservable Selection and Coefficient Stability: Theory and Evidence
Taylor & Francis Verlag | 2019| -
Why High-Order Polynomials Should Not Be Used in Regression Discontinuity Designs
Taylor & Francis Verlag | 2019| -
The Promise and Pitfalls of Differences-in-Differences: Reflections on 16 and Pregnant and Other Applications
Taylor & Francis Verlag | 2020| -
Forecasting Inflation in a Data-Rich Environment: The Benefits of Machine Learning Methods
Taylor & Francis Verlag | 2021| -
Time-Varying Systemic Risk: Evidence From a Dynamic Copula Model of CDS Spreads
Taylor & Francis Verlag | 2018| -
Small-Sample Methods for Cluster-Robust Variance Estimation and Hypothesis Testing in Fixed Effects Models
Taylor & Francis Verlag | 2018| -
Using Heteroscedasticity to Identify and Estimate Mismeasured and Endogenous Regressor Models
Taylor & Francis Verlag | 2012| -
Poorly Measured Confounders are More Useful on the Left than on the Right
Free accessTaylor & Francis Verlag | 2019| -
Do Oil Prices Help Forecast U.S. Real GDP? The Role of Nonlinearities and Asymmetries
Taylor & Francis Verlag | 2013| -
Forecasting Value at Risk and Expected Shortfall Using a Semiparametric Approach Based on the Asymmetric Laplace Distribution
Taylor & Francis Verlag | 2019|
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