This paper examines persistence, structural breaks and non-linearities in the case of five European stock market indices, namely the FTSE100 (UK), DAX30 (Germany), CAC40 (France), IBEX35 (Spain) and FTSE MIB40 (Italy), using fractional integration methods. The empirical results provide no...

We propose an estimation strategy that accounts for two major problems raised in the empirical literature testing for the prevalence of the inverted U-shaped relation between environmental degradation and economic activity, namely the Environmental Kuznets Curve (EKC) hypothesis. First, we use...

This note puts forward a new modelling approach that includes both fractional integration and autoregressive processes in a unified framework. The proposed model is very general and includes other more standard approaches such as the AR(F)IMA models. Some Monte Carlo evidence shows that the...

This paper investigates output convergence for the G7 countries using multivariate time series techniques. We consider both the null hypotheses of no convergence and convergence. It is shown that inferences on output convergence depend on which one of the two null hypotheses is considered....

This paper analyses the stochastic properties of UK nominal and real wages over the period 1750-2015 using fractional integration techniques. Both the original series and logged ones are analysed. The results generally suggest that nominal wages exhibit a higher degree of persistence, which...

This article is our personal perspective on the IPS test and the subsequent developments of unit root and cointegration tests in dynamic panels with and without cross-section dependence. In this note, we discuss the main idea behind the test and the publication process that led to Im, Pesaran...

This paper examines persistence and nonlinearities in the US Federal Funds rate over the period from July 1954 to April 2025 by using fractional integration methods. More precisely, a general model including both deterministic and stochastic components is estimated under alternative assumptions...

We develop a regime switching vector autoregression where artificial neural networks drive time variation in the coefficients of the conditional mean of the endogenous variables and the variance covariance matrix of the disturbances. The model is equipped with a stability constraint to ensure...