The classic papers by Newey and West (1987) and Andrews (1991) spurred a large body of
work on how to improve heteroscedasticity-and autocorrelation-robust (HAR) inference in …

Trend elimination and business cycle estimation are analyzed by finite sample and
asymptotic methods. An overview history is provided, operator theory is developed, limit …

The concept of relative convergence, which requires the ratio of two time series to converge
to unity in the long run, explains convergent behavior when series share commonly …

Heteroskedasticity‐and autocorrelation‐robust (HAR) inference in time series regression
typically involves kernel estimation of the long‐run variance. Conventional wisdom holds …

A semiparametric triangular systems approach shows how multicointegrating linkages occur
naturally in an I (1) cointegrated regression model when the long run error variance matrix in …

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 …

This paper develops fixed-b asymptotic results for heteroskedasticity autocorrelation robust
(HAR) Wald tests for high frequency data using the continuous time framework of Chang et …

The aims of this study is to investigate the relationship between real exchange rate and
innovation in China for the period spanning from 1985 to 2020 using an annual time series …

This paper proposes tests of linear hypotheses when the variables may be continuous-time
processes with observations collected at a high sampling frequency over a long span …

The theory of heteroskedasticity and autocorrelation-robust (HAR) inference in time series
regression has made tremendous progress since the classic papers by Newey and West …