عوامل تعیین کننده در نرخ رشد بلندمدت در کنیا چیست؟

This paper examines the determinants of total factor productivity (TFP) in Kenya. We utilized the theoretical insights from the Solow (1956) growth model and its extension by Mankiw, Romer and Weil (1992) and followed Senhadji's (2000) growth accounting procedure. We find that growth in Kenya, until the 1990s was mainly due to factor accumulation. Since then, TFP has made a small contribution to growth. Our findings imply that while variables like overseas development aid, foreign direct investment and progress of financial sector improves TFP, trade openness is the key determinant. Consequently, policy makers should focus on policies that improve trade openness if the long run growth rate is to be raised.

Lifting the long run growth rate is, arguably, the pursuit of every economy. Since there are a number of policies designed to promote productivity growth and stability in Kenya, it is important to ask: which is best and how good is it in enhancing the long run growth rate? It is obvious that this is a difficult question given the recent economic turmoil, external pressure from donors, and oil crisis and economic mismanagement. Evidence shows that progress in the liberalization of the trade regime in Kenya has been sporadic, with periods of significant progress followed by slower movement and even reversals; see Odhiambo and Otieno (2006, p. 11).

In this article, we examined the determinants of TFP in Kenya using time series data for the period 1977–2008. We utilized theoretical insights from the Solow (1956) growth model and its extension by Mankiw, Romer and Weil (1992) and followed Senhadji's (2000) growth accounting procedure. To the best of our knowledge, this is the first study to use these frameworks for the purpose of investigating the potential factors driving the long run growth rate in Kenya. Our growth accounting exercise showed that growth in Kenya, until the 1990s was mainly due to factor accumulation. Since then, TFP has made a small contribution to growth. We next employed the ARDL, EG and FMOLS techniques to estimate the factor shares of output, and all three methods of estimation pointed towards the capital share of output in Kenya being approximately 0.4.