🔧 What Was Developed

A method to estimate spatial-lag duration models when the outcome is subject to right censoring, the most common form of censoring in duration data. This fills a gap because existing spatial duration models do not account for censoring in the likelihood function.

🔍 How the Method Works

• Adapts Wei and Tanner's (1991) imputation algorithm for censored (non-spatial) regression to spatially interdependent duration models.
• Treats unobserved duration outcomes as censored values and alternates between:
• multiple imputation of the incomplete (right-censored) duration values, and
• estimation of the spatial-lag duration model using those imputed values.
• Focuses on an estimator for log-normal duration outcomes within a spatial-lag framework.

🧪 How the Approach Was Tested

• Performance evaluated via Monte Carlo simulations.
• Simulations vary the degree of right censoring to assess estimator behavior under different censoring levels.

🌍 Empirical Application

• Provides empirical examples by estimating spatial dependence in states' entry dates into World War I.

📌 Why It Matters

• Enables researchers to account for right censoring when modeling interdependent durations, improving the fidelity of spatial duration inference.
• Makes it possible to combine spatial dependence modeling with standard techniques for handling censored duration data.