Vector Error Correction Model: Prediction of Bi-Directional Causality between Gross Domestic Product and Wage Growth in Kenya

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  •   Mburu S. Njoroge

  •   Gladys G. Njoroge

  •   Adolphus Wagala

Abstract

Economic growth and wage growth are very prominent macroeconomic variables in all countries in the World. These two variables are the main signposts signaling the current trends in an economy. To determine the recent behavior of the economy, the government must study and analyze these major variables. The increase in aggregate production in the Kenyan economy has been deteriorating due to the steady rise in the wage bill, especially since the year 2012, in conjunction with the devolved government. An increase in wage rate motivates workers and, in turn, increases the production capacity of a country hence economic growth. An increase in recurrent expenditure implies that the development expenditure will be condensed, which will alter the growth of the economy. The primary goal of this research was to fit vector error correction model on gross domestic product and wage growth data so as to identify the bidirectional causality effects between the two variables. VEC model is superior since it distinguishes between long run and short run relationship among underlying variables in a large sample size. The linear Granger causality test was used to evaluate the causal relationship between the system's variables; hence a causal research design was adopted in this study. This research employed secondary data, which was analyzed using Eviews and STATA statistical software. Data on these target variables was acquired from the World Bank and Central Bank of Kenya. Lastly, this study used yearly time series data for the period 1979 to 2019. It was found that wage growth and GDP granger causes each other and also have a long run relationship since their respective p values were less than 5% significance level. VECM1 (effects of wage growth on GDP) had AIC of -0.2953, RMSE of 1.0039 while the R-squared was 0.7241. Subsequently, effects of GDP on wage growth (VECM2) was found to have an R-squared of 0.7452, AIC of -8.2270 and RMSE of 0.08363. Based on the foregoing findings, it was determined that GDP has more influence on wage growth both in the short and long run. This study thus recommends that the government should keep inflation under control, increase development expenditure to finance projects and fostering a favorable business environment for Small and Medium-sized Enterprises (SMEs) to upsurge total output (productivity) which will in turn, lead to a rise in wage growth, thus a high standard of living for the millions of unemployed Kenyans. Finally, the findings of the current study are expected to be of significance to academicians and also provide appropriate policy options that will help in harmonizing the wage rates, thus managing recurrent expenditure in Kenya.

Keywords: Bidirectional causality, co-integration, economic growth, Johansen Approach, Vector Error Correction Model, Wage Growth

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How to Cite
Njoroge, M. S., Njoroge, G. G., & Wagala, A. (2022). Vector Error Correction Model: Prediction of Bi-Directional Causality between Gross Domestic Product and Wage Growth in Kenya. European Journal of Mathematics and Statistics, 3(4), 6–16. https://doi.org/10.24018/ejmath.2022.3.4.127