Relationship between budget deficit financing and economic growth in Kenya
The study main objective is to establish the This study seeks to find out the relationship between budget deficit financing and economic growth in Kenya. for Kenya, the central government budget deficit shows double digit levels in almost each year since 1963. These budget deficits and a host of other factors could be some of the causes of low investment and slow economic growth. Study used descriptive research design. A descriptive study is concerned with finding out who, what, where, when, or how much (Cooper and Schindler, 2006). This research was descriptive because it was concerned with discussing Relationship between Budget Deficit Financing and Economic Growth in Kenya affects. The data collection of this study was secondary data. The data collection of secondary data involved analysis of Kenya’s budget from year 2005 – 2014, The researcher also utilized reports from office of the controller of Budget, Parliamentary Budget reports and the researcher also surfed the internet and websites in order to find more information and gather the electronic journals or articles that helped the researcher to do the research well. The study found out that Findings of the study indicate that Inflation was at lowest point in 2010 at 0.03%. From the findings the higher the Budget deficit the higher the inflation this is well seen in 2007 when the budget deficit was high at 5.3% and inflation was at 31%. Figure 4.2 indicate that The exchange in 2005 was 7.2% drop to 6.7% in 2009 and begin to trade highly at above Ksh. 80 in the period between 2012 to 2014. Government Budget in Kenya averaged 2.93 percent of GDP from 1998 until 2014, in 2005 the BD was 0.01% raised to 2.6% in 2007, drop to 0.2% in 2009 sharply increased to 5.2% in 2010 and recording highest Budget deficit equal to 8 percent of the country's Gross Domestic Product in 2014. The Coefficient of Determination (R2) of 0. 843 (see table 4.2) shows that the independent variables included in the model explains 73% of the variations in the dependent variable. Therefore the model is a good fit to the relationship. The result has F-Statistics produced (F=1.242) was significant at 0 per cent level (Sig. F<.000) thus confirming the fitness of the model.