Minimum Sliced Distance Estimation in a Class of Nonregular Econometric Models

• Tác giả: Yanqin Fan, Hyeonseok Park
• Ngôn ngữ: eng
• Ký hiệu phân loại: 511.4 Approximations formerly also 513.24 and expansions
• Thông tin xuất bản: 2024
• Bộ sưu tập: Metadata
• ID: 205210

Tóm tắt

This paper proposes minimum sliced distance estimation in structural econometric models with possibly parameter-dependent supports. In contrast to likelihood-based estimation, we show that under mild regularity conditions, the minimum sliced distance estimator is asymptotically normally distributed leading to simple inference regardless of the presence/absence of parameter dependent supports. We illustrate the performance of our estimator on an auction model.