The Autoregressive Conditionally Heteroscedastic (ARCH) model is useful for handling volatilities in economical time series phenomena that ARIMA models are unable to handle. The ARCH model has been adopted in many applications that contain time series data such as financial market prices,...

This study employs the bootstrap autoregressive distributed lag (ARDL) approach alongside the dynamic ARDL simulations technique to investigate the non-linear effect of public debt on public expenditure in Nigeria during the 1981-2020 period. The result of the bootstrap bounds test illustrates...

Principal components analysis (PCA) is often used as a dimensionality reduction technique. A small number of principal components is selected to be used in a classification or a regression model to boost accuracy. A central issue in the PCA is how to select the number of principal components....

Purpose The study aims to determine whether there is a bidirectional causality relationship between health expenditures and per capita income in Brazil, Russia, India, China, South Africa and Turkey (BRICS+T). Design/methodology/approach For that purpose, the 2000-2018 period data of the...

In this paper, we propose a simple dependent wild bootstrap procedure for us to establish valid inferences for a wide class of panel data models including those with interactive fixed effects. The proposed method allows for the error components having weak correlation over both dimensions, and...