A. Sanghi and D. Johnson than Kenya (Chen, Geiger, Fui 2015). Ethiopia’s manufacturing received 76 percent of total FDI for projects in operation, and China is the second largest investor in manufacturing, investing US $545 million between 2008 and 2013; it also has 196 projects in operation, the greatest number of projects among all investors (Chen, Geiger, Fui 2015).

Within manufacturing, Ethiopia’s textiles, clothing, and leather sub-sector attracted US $2.5 billion in investment. FDI in the textiles and clothing sub-sector is crucial for employment growth. In Ethiopia, 40,000 permanent jobs came from manufacturing FDI between 2008 and 2014, with 22,000 manufacturing jobs originating from the textiles, clothing, leather and shoemaking subsectors (Chen, Geiger, Fui 2015). But many jobs in textiles and clothing come from two major investors, China and India. Between 2008 and 2014, China created 24 percent and India created six percent of total jobs. If Kenya wishes to attract more manufacturing FDI from China and India, it will have to work towards lowering the cost of doing business to compete with Ethiopia’s more favorable investment climate (Chen, Geiger, Fui 2015). Kenya has preferential access to the US market under AGOA, and may attract more manufacturing FDI in textiles to create permanent jobs and boost exports to the US market.

# **2.5 What drives Kenya’s exports?**

## **2.5.1 Estimation**

We estimate a gravity equation to explain what influences Kenya’s exports, and if Kenya under or over exports to China relative to comparable countries. The model is analogous to the physical equation of gravity; just as the gravity is proportional to the mass of two planets and inversely proportional to the distance between them, so are exports positively related to the sizes of the two economies and negatively related to the distance between the two economies. The detailed model is in appendix A.1. Using a full set of bilateral trade flows between all pairs of countries as described in appendix B, we estimate a Poisson Quasi Maximum Likelihood regression model A. described in appendix

**Kenya exports less to China than to economies of similar size** Under the Poisson model in table 1, the coefficients on importer GDP per capita and distance are significant and have the expected signs: distance reduces trade and a higher GDP per capita of the importer increases trade. Distance deflects Kenya’s exports by a factor of 0.18. Kenya’s exports increase by a factor of 10.02 to countries that share a common border with Kenya. The China dummy coefficient is -1.74, so Kenya exports less to China by a factor of 0.18 compared to economies of similar size. If Kenya exports one million USD worth of goods to a country similar to China, it only exports 820,000 USD worth of goods to China. Kenya may export less to China after controlling for other independent variables, but the effect is constant over time —none of the China-year dummy coefficients are significant (table C8).

Table 1: Estimates of Kenya’s Trade Flows (1948-2014). Dependent variable: Kenya’s exports

|Poisson Quasi Ma|ximum Likelihood|
|---|---|
|Constant<br>_−_0.93|(0.41)<sup>_∗_</sup>|
|Kenya GDP per capita<br>0.00|(0.00)<sup>_∗∗∗_</sup>|

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