Macroeconomic time series often involve a threshold effect in their ARMA representation, and exhibit long memory features. In this paper we introduce a new class of threshold ARFIMA models to account for this. The threshold effect is introduced in the autoregressive and/or the fractional...

Quantile regression (QR) models have been increasingly employed in many applied areas in economics. At the early stage, applications in the quantile regression literature have usually used cross-sectional data, but the recent development has seen an increase in the use of quantile regression in...

Quantile regression (QR) models have been increasingly employed in many applied areas in economics. At the early stage, applications took place usually using cross-section data, but recent development has seen a surge of the use of quantile regression in both time-series and panel datasets....

We propose a (trend) stationarity test with a good finite sample size even when a process is (trend) stationary with strong persistence; this is useful for distinguishing between a (trend) stationary process with strong persistence and a unit root process. It could be considered as a modified...

We show that the CUSUM and LM tests for structural change in the volatility process enjoy monotonic power. The framework is general including many recently proposed non-stationary GARCH-type models. The result is in contrast to the well-known issue of non-monotonic power for the CUSUM-based...

Detecting structural changes in volatility is important for understanding volatility dynamics and stylized facts observed for financial returns such as volatility persistence. We propose modified CUSUM and LM tests that are built on a robust estimator of the long-run variance of squared series....

Spurious regression phenomenon has been recognized for a wide range of Data Generating Processes: driftless unit roots, unit roots with drift, long memory, trend and broken-trend stationarity, etc. The usual framework is Ordinary Least Squares. We show that the spurious phenomenon also occurs in...

This paper analyses the asymptotic and finite sample implications of different types of nonstationary behavior among the dependent and explanatory variables in a linear spurious regression model. We study cases when the nonstationarity in the dependent and explanatory variables is deterministic...

This paper advances a new analysis technology path of estimation and test for long memory time series. I propose the definitions of time scale series, strong variance scale exponent and weak variance scale exponent, and prove the strict mathematical equations that strong and weak variance scale...

The spurious regression phenomenon in Least Squares occurs for a wide range of Data Generating Processes, such as driftless unit roots, unit roots with drift, long memory, trend and broken-trend stationarity. Indeed, spurious regressions have played a fundamental role in the building of modern...