Abstract-This paper will examine the factors that influence foreign direct investment (FDI) flows into African countries. FDI flows are important for African nations as they promote economic development. Estimation results using the Least Squares Dummy Variable model also known as the fixed effects model indicate that i) a high economic risk has a negative and significant effect on FDI flows into Africa ii) both political risk and financial risk have a negative but insignificant impact on FDI inflows iii) there is a positive and significant relationship between the commodity price index performance and FDI inflows iv) the good performance of stock markets in developed countries has a positive and significant impact on FDI inflows v) an increase in the infrastructure of a country has a positive and significant effect on FDI inflows vi) an increase in openness to trade has a positive and significant effect on FDI inflows vii) the amount of FDI received in the previous year by African countries is significant in influencing the FDI flows that come into the African continent in the current year. Annual data from 1984 until 2010 using 35 African countries is used for this panel study.Index Terms-Africa, foreign direct investment, long term capital movements, panel data.
Climate change and economic growth are closely connected. Climate change has the potential to reduce economic growth in developing countries due to their limited ability to respond to the negative impacts of a changing climate. A better understanding of weather variability can enhance climate change policies, which would help to support economic growth in these countries. As such, this research sought to examine if there is a long-run relationship between sectoral output and weather variables (temperature and rainfall) and to analyze the effect of weather variability on sectoral output using a panel of 13 sectors in Kenya.A Pedroni cointegration test was carried out to find out if there exists a long-run relationship among the variables and thereafter, a fully modified ordinary least squares regression was conducted to establish the effect of weather variability on sectoral output. The results indicate that there is a long-run relationship between temperature and sectoral output. Moreover, temperature has a larger effect on sectoral output compared to rainfall. With the evidence gathered from this research, it can be concluded that weather variability has an economic effect on sectoral output in Kenya. Given this, the Kenyan government needs to take a keen interest in understanding the effect of weather variability on the economy and in the broader picture, take steps to mitigate climate change.
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