This study analyzes the effect of government domestic borrowing on private investment using Gross fixed capital formation as a dependent variable. The study uses the data from 1975 to 2014 of Domestic debt, financial development, gross domestic savings, real interest rate and GDP per capita. The Auto Regressive Distributed Lag (ARDL) technique was used to find the long-run and short-run Co-integration relationship of the model between the independent variables and Gross fixed capital formation. Stability functions also tested using CUSUM and CUSUMSQ. The results show that Domestic Debt has a negative and significant relationship with Gross fixed capital formation even though this relationship diminishes in the long run. Financial Development (FD) proxied as Domestic credit to private sector has positive and significant relationship with gross fixed Domestic capital formation in Kenya in short run and long run. This suggests that an increase in increase in Domestic credit to private sector leads to increase investments in Kenya. These results confirm that excessive domestic borrowing by the government can negatively affect investment and eventually hurt the economy. If this persists Kenya's economy can be hurt eventually affect the future investment and economic growth. This means government need to come up with policies to govern domestic borrowing and interest rates and also come up with policies that encourage financial development through boosting Small and Micro enterprises lending to encourage local investment.
In this paper, two models of forecasting are used the Box-Jenkins procedure employing the SARIMA and the Holt-Winters triple exponential smoothing. Published Consumer Price Index Data from Kenya National Bureau of Statistics (KNBS) for the period November 2011 to October 2016 was used. This paper we equate the forecasted values of both the models and we choose the best model based on the least mean Absolute square error (MASE), mean absolute error (MAE) and mean absolute percentage error (MAPE). The three step model building for Box-Jenkins was first employed, followed by the Hold-Winters triple exponential smoothing. The study found the SARIMA Model was a better model than the Holt-winters triple exponential smoothing as per the obtained results using MASE, MAE and MAPE.
Food Prices accounts for about 36% of the overall consumer price index in Kenya and it's the single largest of the 12 components that make up the index. Therefore, shocks in food prices could considerably be transmitted to the overall consumer price index. While Kenya agricultural production is heavily rain-fed, external pressures from and shocks from crude oil price, international trade are transmitted inwards and pile more pressure on food prices as well. While inflation tend to follow all the available information in the market and business per the rational expectations' theory, price factors are a key determinant of business cycles, because price stickiness tend to drive demand. Therefore, demand for food products could be driven by several market features including internal food prices, oil prices, productions and importation costs. The objective of this research was to analyze the effect of Trade openness on food inflation in Kenya with a view of establishing if Romer's hypothesis holds in Kenya. The second objective is to establish the effect of crude oil prices on food inflation in Kenya. The study employed Autoregressive Distributed Lag (ARDL) cointegrating technique to estimate both short-run and long run estimates. The study findings indicate that trade openness significantly has a reducing influence on food inflation hence confirming the existence of Romer's hypothesis in Kenya. Secondly, crude oil prices have a positive and significant effect on food inflation. Interestingly, the study found that money supply does not have significant influence on food inflation. The study recommends embracing and adopting international free trade agreements to further leverage on imports prices, increase buffer storage to cushion against food demand and hence stabilize food prices. Secondly the government should enhance further price controls on oil prices to reduce spillovers to food production and supply costs. In addition, Kenya should develop technologies to improve agricultural farm production to leverage dependence of rain-fed agricultural sector.
This paper examined Market Micro-structure interrelations between Stocks, Bonds and Foreign Exchange Markets. The Study analyzed both unconditional correlation, dynamic relationship and volatility spillovers effects between the markets. The analysis used the asymmetric dynamic conditional correlation (aDCC) using Exponential Generalized Autoregressive Conditional Heteroskedastic model (EGARCH). Using monthly data from Kenyan market during the period January 2004 -June 2017, results indicate that there is significant market interactions and interlinkages and existence time varying variance correlation between any bivariate set in the three markets in Kenya. While, the conditional correlations are positive, the unconditional correlation reveal, a negative correlation between Foreign exchange markets and the Bonds as well as stocks. The study proposes policy makers like the government through treasury, capital markets authority (CMA) and Nairobi securities exchange (NSE) to encourage more Kenyan investors to invest in bond market by marketing the bond market through educational forums, conferences. For the Proposal to take effect, appropriate authorities should stabilize the Kenyan currency through monetary interventions.
The financial stability objective of any financial system authority is to maintain confidence, and promote the safety and soundness of the domestic financial system. Financial stability has been defined as the resilience of the financial system in the face of adverse shocks to enable the continued smooth functioning of the financial intermediation process. The Kenyan Financial service providers are diverse and they include 42 commercial banks, 49 insurance companies, 12 deposits taking microfinance banks, and 199 registered savings and credit cooperatives (SACCOs). This paper examined financial intramarket linkages (dynamic relationship and volatility spillovers) effects between the Commercial banks and other financial sector segments (Insurance and Capital Markets) in Kenya and the impact of this transmission on financial inclusion. The study evaluated the effect of intra-market linkages on financial inclusion using Bayesian Vector Autoregressive (BVAR) using monthly data from the Kenyan market during the period January 2004-December 2016. Impulse-response analysis and forecast error variance decomposition were used to investigate these intra-market linkages and their causal effect to financial inclusion. Results show that there are significant market interactions and interlinkages with significant shocks transmission moving from banks to other markets. Interest rates shock transmission affected all markets. This means that monetary policy transmission as expected trickles down to the entire financial sector. The study also found out that, positive shocks from credit impacts positively on lending rate and the capital markets performance implying banking mechanism to reward increased loan uptake at cheaper prices and hence creating cash-flow that spills over to more investment on the Nairobi Securities Exchange. The study recommends that policy makers design policies that help minimize the adverse impact of volatility/shocks but create opportunities for growth on each market to foster price stability and increase investments through financial inclusion.
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