The Relationship Between Urbanization and Precipitation in Kisumu City: Co-Integration Analysis

Abstract

The work done in this study thesis is by empirical analysis. If two series are integrated of the same order, then the two series are said to be co-integrated and this is shown in the two series where the population series being non stationary is made stationary by third differencing and the stationary rainfall series subjected to the same order of differencing to achieve the co-integration rule. The OLS method was used and then the model parameters tested for adequacy. A linear Error Correction Model was fitted and evidence that a short term relationship between the rainfall and population series is seen to exist. Also, a high threshold value is observed at the second lag. A high R squared value of 0.9881 is an indication that the model fits well to the data.  A small p-value also indicates that the model is highly significant. Hence, it is recommended that a close analysis of population growth rates be analyzed to aid in the prediction of the rainfall rates movements.

Keywords: OLS, Co-integrated, differencing, Error Correction Model, p-value.