EFFECT OF COUNTY BUDGET DEFICITS ON GROSS COUNTY PRODUCT IN KENYA

Abstract

Globally, the performance of any economy is determined by the proportion of productive resources available to support its needs. Low resource base compared to needs of any economy, contribute to economic instability, which is a major concern for many countries. Since Kenya established county governments in 2013, these counties have been registering an increase in their budget deficits. Between 2013 to 2017, total county own sourced revenue deficit increased from 16,528 to 25,081 million shillings; total county development budget deficit increased from 48,701 to 68,993 million shillings; and total county recurrent budget deficits increased from 14,965 to 21,166 million shillings. These counties developed their County Integrated Development Plans (CIDPs 2013-2017) to guide their efforts towards economic growth. Within the period, the counties economies grew from 4,263,910 in 2013 to 7,524,710 million shillings as indicated in their Gross County Product -a geographic breakdown of Kenya’s GDP that gives an estimate of the size and structure of county economies. It was important to understand how each of these county budget deficits affect economic growth of counties in Kenya. However, literature shows no consensus whether budget deficits have negative or positive effect on economic growth. These studies, including those done in Kenya limited their scope to use of national level data set, with budget deficits not broken down to own sourced revenue deficit, development budget deficit or recurrent deficits. The purpose of this study was to analyze the effect of county budget deficits on Gross County Product in Kenya. Specific objectives were to; determine the effect of own sourced county revenue deficit on GCP, establish the effect of county development budget deficit on GCP, and examine the effect of county recurrent budget deficit on GCP. The study was modeled on neoclassical economic growth theory of Solow and Swan and correlational research design was employed. Secondary panel data from 2013 to 2017 for all 47 counties was used (235 observations), sourced from Kenya National Bureau of Statistics and Controller of Budget reports. The data was analyzed using panel estimation method of Random Effects model, which was preferred by the Hausman test and used to estimate and interpret results of autoregressive distributed lag model (ARDL). On the first objective, findings showed that own sourced county revenue deficit had a coefficient of -0.45 with a pvalue of 0.013, while the coefficient for its lagged value was-1.03 with a p-value of 0.003. This means that increase in growth rate of own sourced county revenue deficit in the past as well as in the present period have a negative effect on growth rate of Gross County Product. On the second objective, county development budget deficit reported a coefficient of 0.21 with p-value of 0.056 while the coefficient of its lagged value was 0.06 with a p-value of 0.001. This implies that growth in the rate of county development budget deficit of the past had a positive effect on growth rate of Gross County Product. Findings for the third objective showed that county recurrent budget deficit had a coefficient of -0.13 with a p-value of 0.022 and its lagged value had a coefficient of -0.07 with the p-value being 0.110. The results imply that growth in the rate of county recurrent budget deficit in the current period was having a negative effect on the growth rate of Gross County Product. Based on these findings, the study concluded that past as well as present increase in growth rate of own sourced county revenue deficit reduces growth rate of Gross County Product, an increase in growth rate of county development budget deficit in the past increases growth rate of Gross County Product and an increase in growth rate of county recurrent budget deficit in the present period lowers growth rate of Gross County Product. As such, this study recommended for policies that improve own sourced revenue collection, enhance development spending and reduce recurrent deficit spending at county levels.