Bootstrap Inference in Cointegrating Regressions: Traditional and Self-Normalized Test Statistics
协整回归的 Bootstrap 推断：传统与自归一化统计量
Traditional tests of hypotheses on the cointegrating vector are well known to suffer from severe size distortions in finite samples, especially when the data are characterized by large levels of endogeneity or error serial correlation.To address this issue, we combine a vector autoregressive (VAR) sieve bootstrap to construct critical values with a self-normalization approach that avoids direct estimation of long-run variance parameters when computing test statistics.To…