Designs in Time and Space

• In Event: Causal Inference with Time-Series - Cross-Sectional Data

Brief Overview

We assess the viability of causal inference designs and commonly used time-series-cross-sectional models across various data-generating processes (DGPs). We evaluate this both analytically and through Monte Carlo simulations.

Authors

• Guy D. Whitten, Texas A & M University-College Station

• Ali Kagalwala, Texas A & M University

• Ana Dutra, Texas A&M

• Sunhee Kim, Texas A&M University - College Station