Jointness in Bayesian Variable Selection with Applications to Growth Regression

• Tác giả: Eduardo Ley
• Ngôn ngữ: eng
• Ký hiệu phân loại: 511.4 Approximations formerly also 513.24 and expansions
• Thông tin xuất bản: 2012
• Bộ sưu tập: Tài liệu truy cập mở
• ID: 309066
• Chủ đề: 1. BENCHMARK; 2. BLACK MARKET; 3. BLACK MARKET PREMIUM; 4. CALIBRATION; 5. CIVIL LIBERTIES

Tóm tắt

The authors present a measure of jointness to explore dependence among regressors in the context of Bayesian model selection. The jointness measure they propose equals the posterior odds ratio between those models that include a set of variables and the models that only include proper subsets. They show its application in cross-country growth regressions using two data-sets from the model-averaging growth literature.