Date of Completion


Embargo Period



Inverse relationship hypothesis, random parameters stochastic production frontier, sub-Saharan Africa, technical efficiency, total factor productivity

Major Advisor

Boris E. Bravo-Ureta

Associate Advisor

Nathan Fiala

Associate Advisor

Nicholas Rada

Field of Study

Agricultural and Resource Economics


Doctor of Philosophy

Open Access

Open Access


Agricultural productivity is critical for the development of many sub-Saharan African (SSA) countries where the farming sector plays a key role in the economy. An important issue concerns evidence of the inverse relationship between farm size and productivity in developing countries, which has been documented over many decades. Despite the accumulated evidence, this relationship, which has been attributed to a variety of factors, remains a puzzle for development economists.

This dissertation provides new evidence concerning the inverse relationship (IR) hypothesis by addressing several shortcomings found in the literature and applying state-of-the-art stochastic frontier methods, such as the true random effects model (Greene, 2005a) and a random parameters stochastic frontier (RP–SPF) model (Tsionas, 2002; Greene, 2005b) to account for time-varying inefficiency and unobserved heterogeneity. This dissertation also offers novel analyses concerning agricultural productivity differences between male and female farmers in Malawi, Tanzania, and Uganda using a multiple-step methodology. The analysis focuses on productivity and efficiency gaps as well as on testing land and labor market imperfections for both groups of farmers.