Global Journal of Human Social Science, E: Economics, Volume 21 Issue 4

being implemented through successive five-year medium-term plans, has three pillars: an economic pillar that aims to achieve GDP growth of 10 percent per annum; a social and environmental pillar that aims to build a society enjoying equitable social development in a clean and secure environment; and a political pillar that aims to build a people-centered, results-oriented, accountable democratic political system (Word bank, 2019). The costs of international transport services are a crucial determinant of a developing country’s export competitiveness. Shipping costs often represent a more binding constraint to greater participation in international trade than tariffs and other trade barriers. Across economies, a doubling of shipping costs is associated with slower annual growth of more than one-half of a percentage point. Transport costs determine the potential access to foreign markets, which, in turn, explains up to 70 percent of variations in countries’ gross domestic product (GDP) per capita (World bank, 2019). Kenya depends quite heavily on external trade for sustaining her economy and also for her economic growth and development. Despite the extensive hinterland the port commands, and the recent commencement of SGR Freight services in 2018, its overall performance remains significantly below international standards. Kenya Ports Authority, a Maritime State corporation which manages Mombasa port, is underperforming in terms of turn-around time despite the heavy infrastructural inputs as depicted in table 1.1. Table 1.1: Average Turn-around Time Port Waiting Time Mombasa 62.4 hours Namibia 18 hours Djibouti 3 hours Source: Kenya Ports Authority (2020) As depicted in table 1.1, the port of Mombasa has one of the longest ship waiting time with turnaround time of an average of 2.6 days compared to Djibouti’s 3 hours, Namibia 18 hours and Durban 16 hours. While this can lead to underperforming of volumes of handling of cargo and consequently reduce the value of contribution to the national gross domestic, the other fundamental issue is to establish whether the delay is as a result of monopoly structure of maritime sector. II. M aterials and M ethods The research design of this study was explanatory which used panel data to analyze effect of labor productivity on Maritime sector performance in enhancing economic growth in Kenya. In order to analyze the effect of labor on maritime performance in Kenya, this research utilized Simple Regression Analysis and Dynamic Stochastic General Equilibrium (DSGE) employing Generalized Method of Moments (GMM) modeling. Using simple regression analysis was used to estimated regression equation is, R2 was found, which simply the square of correlation coefficient. This measure was also called the coefficient of determination of a regression equation and it took value between 0 and 1(both values inclusive). It would indicate the explanatory power of the regression model. The test for the significance of R2 would be carried out using the F statistics. The Simple Regression Model was employed in analysis of determinant of maritime output which were labor productivity in maritime sector in Kenya as depicted by equation 2.1. t t t t Lbr Y Y ε β φ β + + + = − 2 )1 ( 1 0 ……2.1 Where t t t t Lbr YY ε β , , , 2 )1 ( − represents output, lagged output, labor productivity and the random error term respectively. In GMM, a population moment condition is that a vector of observed variables, , and unknown parameter vector with true value which satisfy a element vector of conditions: ( ) [ ] 0 , = θ t vfE for all .………....2.2 The method of moment estimator is used to solve the analogous sample moment conditions given as: ( ) ( ) 0 , * 1 * = = ∑ − T t T T vf T g θ θ …...2.3 Where is the size of the sample. Therefore, under the usual regularity conditions, , where is the solution for equation 2.3, in which there are unknowns and equations leading to unique solution. Suppose that f is a 1 qx vector and k q > meaning there are unknowns and equations implying that there is no unique solution. GMM picks a value for such that it approaches closest to satisfy equation 2.3. The closeness can be defined by the following criterion function: Where is the weighting matrix, converges to a positive definite matrix as grows large. The GMM estimator depends on the weight matrix ( ) T GMM W Q which becomes the GMM estimator of 0 θ (true value) given as ∧ θ can be obtained by finding Volume XXI Issue IV Version I 27 ( E ) Global Journal of Human Social Science - Year 2021 © 2021 Global Journals Effect of Foreign Exchange Rate on Maritime Sector Performance in Enhancing Economic Growth in Kenya ( ) ( ) [ ] ( ) [ ] ( ) ( ) θ θ θ θ θ T T T t T t T gW g vf TW vf T Q ' 1 ' 1 , , = = ∑ ∑ − − …...2.4 T W 0 * θ θ → T T