| dc.description.abstract | This thesis analyses the dynamics and investment behavior of Ethiopian manufacturing firms in post-reform period using establishment level industrial census panel data from 1996 to 2003. Three related topics such as firm turnover and productivity differentials, determinants of firm growth, and the effect of adjustment cost and irreversibility on firm investment decisions are investigated empirically.
Essay I provides empirical evidence on firm turnover and productivity differentials in Ethiopian manufacturing using firm-level census data from 1996 to 2003 and tries to address the following research questions. Are the forces of market selection at work in Africa? How successful are markets in these economies to sort out firms on efficiency basis following the sequence of reforms to liberalize and particularly to transform some of the previous command economies to market oriented ones? What is the pattern of entry and exit in the manufacturing sector and how does it affect industry productivity growth? This is the first attempt to analyze firm turnover and productivity differentials using industrial census data in sub-Saharan Africa. The Ethiopian manufacturing sector exhibits high firm turnover rate that declines with size. Exit is particularly higher among new entrants; 60 percent exit within the first three years in business. Our study consistently shows a significant difference in productivity across different groups of firms, which is reflected in turnover pattern where the less productive exit while firms with better productivity survive. We also found higher aggregate productivity growth over the sample period, mainly driven by firm turnover.
Essay II examines the relationships between firm growth and firm size, age, and labor productivity, using annual census based panel data on Ethiopian manufacturing firms. Unlike most previous studies in sub-Saharan Africa, this study explicitly addresses the ongoing statistical concerns in the firm growth models such as sample censoring, regression to the mean, and unobserved heterogeneity. Overall, our empirical results indicate that firm growth decreases with size. This relation is not affected by fluctuations or measurement error in size and by controlling unobserved heterogeneity. It is also robust after correcting for sample censoring and explicitly considering the growth rate of exit firms to be -100 percent in the exit period. This suggests not only that smaller firms have faster rates of employment growth than larger firms, but also that growth rates of the smaller firms are large enough to compensate for their attrition rates. The negative relation between growth and age predicted by the learning process is found to impact only younger firms at the early stage of their life cycles. Labor productivity affects firm growth positively. This is consistent with the passive learning model prediction and provides evidence of market selection process through growth differential. Capital intensity, location in the capital city, and public ownership also affect firm growth positively.
Essay III investigates the effect of irreversibility and non-convexities in adjustment costs on firm investment decision based on 1996-2002 firm level data from the Ethiopian manufacturing. It relies on a rich census based panel data set that gives the advantage of disaggregating investment into different types of fixed assets. We document evidence of a large percentage of inaction intermitted with lumpy investment, which is consistent with irreversibility and fixed costs but not with the standard convex adjustment costs. The inaction is higher and investment lumpier for small firms. We complement the descriptive analysis with two econometric methods: a capital imbalance approach and machine replacement model. With the capital imbalance approach we estimate the investment response of firms to their capital imbalance using a non-parametric Nadaraya-Watson kernel smoothing method. With the machinery replacement approach using a proportional hazard model that takes unobserved heterogeneity into account, we estimate the probability of an investment spike conditional on the length of the interval from last investment spike. | swe |
