Many macroeconomic variables undergo business cycle episodes (fluctuations), which makes the variables change dramatically. Hence, the causality between these variables could be hidden by the presence of structural breaks, regime change, reforms, or crises in general. Therefore, fitting a linear model may not capture the entire characteristics of the data. To this end, the study employs the Markov-switching Vector Autoregressive (MS-VAR) model, which allows for time-dependent regime shift to reexamine the energy-growth nexus in Ghana from 1971-2020. This model account for the non-linearity in the data, and the coefficients depend on the state of the economy. Contrary to linear models such as the Vector Error Corrections (VEC) and the VAR models that assume a linear and stable relationship, the MS model argues that the relationship could be different in each regime. The results from the MSIAH (2)-VAR (1) model indicates that economic growth Granger causes electricity consumption only in regime 1 during 1978-1984, 1998-2007 and 2016-2020. This regime shows the period of the energy crises in 1980-1984, 1997-1998, 2003, and 2016-2020 and the recession in the 1980s and early 2000. In regime 2, however, no Granger causality was found between the variables. Policy recommendations are provided based on the findings of the study.
Unraveling the effect of gender dimensions and wood fuel usage on household food security: evidence from Ghana
EfD Authors
Country
Sustainable Development Goals
Publication reference
Adjei-Mantey, K., Kwakwa, P. A., & Adusah-Poku, F. (2022). Unraveling the effect of gender dimensions and wood fuel usage on household food security: evidence from Ghana. Heliyon, 8(11), e11268. https://doi.org/10.1016/j.heliyon.2022.e11268