Farm Size, Modern Technology Adoption, and Efficiency of Small Holdings in Developing Countries: Evidence from Kenya

By Nyariki, Dickson M. | The Journal of Developing Areas, Fall 2011 | Go to article overview

Farm Size, Modern Technology Adoption, and Efficiency of Small Holdings in Developing Countries: Evidence from Kenya


Nyariki, Dickson M., The Journal of Developing Areas


ABSTRACT

Low efficiency is a problem in most developing agriculture, and is one of the reasons for food insecurity. This paper provides information on smallholder production efficiency in one of the developing Sub-Saharan Countries: Kenya. It applies Data Envelopment Analysis (DEA) to farm-level seasonal panel data. The estimated indexes indicate high levels of inefficiency between farm sizes, seasons, and adopters and non-adopters of 'modern' farming technologies. A comparison of various farming practices shows that use of modern inputs and livestock-based capital could significantly improve farmers' performance. Tobit estimations show that the major factors influencing performance are the level of education, gender, market access and off-farm capital. Thus, policies aimed at improving education, rural infrastructure as well as assuring farmers of income through improved livelihood opportunities, and therefore reduced perceived uncertainty, could improve farm-level efficiency. The findings also provide support for prioritizing issues of farm production associated with women in policymaking.

JEL Classifications: C23, D13, D24, O13, Q12, Q16

Keywords: Farm-level technical efficiency, Food security, Smallholder farming, Sub-Saharan Africa

(ProQuest: ... denotes formulae omitted.)

INTRODUCTION

Evidence abounds that agricultural production systems in Sub-Saharan Africa (SSA) are still characterized by low efficiency and productivity, although a few studies have reported isolated cases to the contrary (Hyden, 1986; Nyariki and Thirtle, 2000; Thirtle et al., 1993; Wiggins, 1995). The low efficiency and productivity growth in smallholder agriculture in SSA is manifested in the cumulative discrepancy between African production rates and those of the rest of the world.

In the case of Kenya, the country experienced a rapid expansion in agricultural production whose contribution to GDP grew by more than four percent in the first decade. The introduction and widespread adoption of new technologies led to a steady increase in food production. These developments, however, slowed down after the early 1970s (ROK, 1994; Nyariki, 1997). Because of this, government objectives during the 1970s and 1980s were geared towards increased food production from less productive lands, growth in agricultural employment, and resource conservation to improve food security.

The poor performance of agriculture in Kenya reflects a serious problem because this sector is the mainstay of the economy. The sector accounts for approximately 25 percent of GDP, provides employment for close to 70 percent of the population, contributes roughly 40 percent of export earnings, and provides most of the country's food supply (ROK, 2008). Slowing growth rates coupled with high population growth and limited arable land raise serious questions as to how this sector will meet the challenges of sustained per capita growth.

Kenya's past development plans have proposed to reduce the area under food production in order to release land to more valued export crops, which would then improve the per capita value of agricultural production. This meant that increases in the basic foodstuffs had to come from higher yields, and by implication higher efficiency of farm resource use. However, the efficiency of smallholder farms must first be enhanced to optimize the returns from the use of enhanced technology.

The lack of adequate information on the patterns and sources of efficiency of smallholder farms has become an important issue because the country faces household food insecurity (Nyariki et al., 2002). Thus, this paper analyzes the efficiency of smallholder farms and the factors influencing efficiency in one of the medium to low potential areas of Kenya. The next section briefly describes the farming area, followed by details of how data were collected and the variables used. The next section outlines the model used to derive efficiency indexes and discusses the results at this stage.

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