EFFECTS OF OFF-FARM WORK ON TECHNICAL EFFICIENCY AND PRODUCTION RISK AMONG RICE FARMERS IN ENUGU STATE

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EFFECTS OF OFF-FARM WORK ON TECHNICAL EFFICIENCY AND PRODUCTION RISK AMONG RICE FARMERS IN ENUGU STATE

ABSTRACT

The study analysed the effects of off-farm work on technical efficiency and production risks among rice farmers in Enugu State, Nigeria. Ninety respondents were selected using multi-stage sampling technique. Data for the study were collected by the use of well structured questionnaire. Descriptive statistics and stochastic production frontier model were used to analyse the data. Results showed that the two groups of rice farmers had similar socio-economic characteristics. Technical efficiency scores for the farmers ranged from 0.579 to 1.000 and 0.0606 to 1.000 for the rice farmers without and with off-farm work respectively. The average efficiencies are 0.964 and 0.871 for rice farmers without and with off-farm work, respectively. This suggests that off-farm work has a negative effect on farmers’ technical efficiency. The result of the student t-test conducted at 5% significance level showed that there is a significant difference in the mean technical efficiency of the two groups of rice farmers. For rice farmers without off-farm work average number of farmers associations (0.646), age (0.328), education (3.838) and extension access (3.144) significantly and positively influenced technical inefficiency effects while for their counterpart age (0.159) and extension access (4.727) significantly and positively influenced technical inefficiency effects and household size (-0.970) was significant but negative. For farmers without off-farm work, family labour (1.287) has a positive and significant effect on production risk, meaning that family labour is a risk increasing factor. Depreciated value of equipment (-12.255) used has a negative and significant effect on production risk which indicates that investment on equipment will decrease the production risk in rice production. For rice farmers with off-farm work none of the factors was significant even though they all had negative sign. The constraints faced by the farmers were inaccessible road, high cost of transportation, inadequate credit, birds’ invasion, inadequate extension support, inaccessibility to cheap farm inputs ranked in ascending order of importance.

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TABLE OF CONTENTS

Title……………………………………………………………………………………………………………………………i

Certification……………………………………………………………………………………………………………….ii

Dedication…………………………………………………………………………………………………………………iii

Acknowledgement………………………………………………………………………………………………………iv

Abstract…………………………………………………………………………………………………………………….v

Table of contents……………………………………………………………………………………………………….vi

List of tables…………………………………………………………………………………………………………….viii

CHAPTER ONE: INTRODUCTION

Background of the Study………………………………………………………………………………………..1

Problem Statement…………………………………………………………………………………………………5

Objectives of the Study…………………………………………………………………………………………..8

Hypotheses of the study………………………………………………………………………………………….8

Justification of the Study………………………………………………………………………………………..9

CHAPTER TWO: REVIEW OF RELATED LITERATURE

2.1 Characteristics of Nigeria’s Rice Production Systems ………………………………………………11

2.2. Off-Farm Work by Farm Households…………………………………………………………………….12

2.3 Determinants of choice of off farm work…………………………………………………………………13

2.4 Interrelationship between off-farm work and efficiency…………………………………………….14

2.5 Agricultural risk…………………………………………………………………………………………………..15

2.5.1 Classifications of Agricultural Risks…………………………………………………………………….16

2.6 Efficiency…………………………………………………………………………………………………………..17

2.7 Determinants of production efficiency…………………………………………………………………….20

2.8 Measures of Efficiency………………………………………………………………………………………….21

2.8.1 The non-parametric programming approach …………………………………………………………22

2.8.2 Deterministic production frontier models and technical efficiency…………………………..22

2.8.3 Stochastic production frontier models and technical efficiency……………………………….24

2.8.4 Stochastic Frontier model estimation–The Maximum Likelihood Estimation Method…………………………………………………………………………………………………………………….27

2.9 Estimating Production Risk and Inefficiency Simultaneously…………………………………..28

2.10 Review of Related Empirical Studies…………………………………………………………………….29

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2.11 Theoretical Framework……………………………………………………………………………………….33

2.11.1 The Production Function, Risk, and Technology………………………………………………….33

2.11.2 Farm Household’s Maximization Problem………………………………………………………….33

2.11.3 Production Economics Theory…………………………………………………………………………. 36

2.12 Analytical Framework…………………………………………………………………………………………38

2.12. 1. Estimating the stochastic frontier model with risk………………………………………………38

CHAPTER THREE: RESEARCH  METHODOLOGY

3.1 The Study Area…………………………………………………………………………………………………….41

3.2 Sampling Procedure……………………………………………………………………………………………..42

3.3 Data Collection…………………………………………………………………………………………………….42

3.4 Data Analysis………………………………………………………………………………………………………43

3.4.1 Model Specification…………………………………………………………………………………………..43

3.4.1.1 Stochastic frontier production function………………………………………………………………43

3.5.1.2 Likert Scale Rating Technique………………………………………………………………………….47

CHAPTER FOUR: RESULTS AND DISCUSSION

4.1 Socio-economic Characteristics of Respondents………………………………………………………48

4.2 Rice production in the study area……………………………………………………………………………54

4.3 Comparing the distributions of the technical efficiency scores between the two groups of

rice farmers…………………………………………………………………………………………………………55

4.4 Estimation of the Stochastic Production Frontier Model……………………………………………57

4.5 Constraints faced by rice farmers……………………………………………………………………………60

4.6 Test of hypotheses………………………………………………………………………………………………..61

CHAPTER FIVE:SUMMARY, CONCLUSION AND RECOMMENDATION

……………………………………………………………………………………………………………63

………………………………………………………………………………………………………….64

……………………………………………………………………………………………….64

REFERENCES………………………………………………………………………………………………………..67

viii

LIST OF TABLES

Tables                                                                                                                             Pages 4.1   Socio-economic characteristics of respondents……………………………………………………….52

4.2   Stochastic Production Frontier Estimates………………………………………………………………57

4.3   Distributions of technical efficiency………………………………………………………………………58

4.4   Constraints faced by rice farmers………………………………………………………………………….59

4.5   Generalized likelihood ratio test……………………………………………………………………………60

4.6   T-test result……………………………………………………………………………………………………….60

CHAPTER ONE

INTRODUCTION

1.1 BACKGROUND OF THE STUDY

The struggle for food is desperate for the 240 million people of West Africa: one of every three of who is a Nigerian (West Africa Rice Development Association (WARDA), 2002). Rice (Oryza sativa) is the staple food of approximately half of the world’s population (International Rice Research Institute (IRRI), 1997). It has traditionally been an important basic food commodity for certain populations in sub-Saharan Africa (SSA), and West Africa in particular. Recent important and major changes have led to a structural increase in rice consumption in the sub-region. Since 1973, regional demand has grown at an annual rate of 6%, driven by a combination of population growth and substitution away from traditional coarse grains (WARDA, 2001). The consumption of traditional cereals, mainly sorghum and millet, has fallen by 12 kg per capita, and their share in cereals used as food decreased from 61% in the early 1970s to 49% in the early 1990s. In contrast, the share of rice in cereals consumed has grown from 15% to 26% over the same period (Akpokodje, Lancon and Erenstein, 2001). Also it was observed that between 1961and 2005, the annual increase in rice consumption was 4.52% in SSA (WARDA, 2007). Growth in regional rice consumption remains high.

The demand for rice has been increasing at a much faster rate in Nigeria than in other West African countries since the mid 1970s (WARDA, 2001). For example, during the 1960’s Nigeria had the lowest per-capita annual consumption of rice in the sub-region (average of 3 kg). Since then, Nigeria’s per capita consumption levels have grown significantly at 7.3% per annum (Ogundele and Okoruwa, 2006). Consequently, per-capita consumption during the 1980s averaged 18 kg and reached 22 kg in 1995-1999. In an apparent move to respond to the increased per capita consumption of rice in Nigeria, local production boomed, averaging 9.3% per annum (Ogundele and Okoruwa, 2006). These increase in local production have been traced to vast expansion of rice area at an annual average of 7.9% and to a lesser extent to increase in rice yield of 1.4% per annum. The reality is that Nigeria has not been able to attain self-sufficiency in rice production despite increasing hectares put into production annually (CBN, 2000). Consequently, Nigeria has depended heavily on imported rice to meet her consumption needs and has become the World’s largest importer of rice (WARDA, 2003). According to Okorji and Onwuka (1994) the rice import bill for Nigeria was N123.61 million in 1980 and has since continued to rise. That Nigeria has remained a net importer of rice with well over ₦150.15 billion spent annually (FOS, 2000) is indicative of the declining self-sufficiency. This constitutes a huge drain on Nigeria’s foreign reserve and a major bottleneck in the balance of payments (Egbuna, 2003).

In a bid to address the demand-supply gap for rice, governments have at various times come up with policies and programmes. However, these policies according to WARDA (2001) have not been consistent due mostly to oscillating import tariffs and import restrictions. For instance, from 1986 to the mid-1990s imports were illegal. In 1995 imports were allowed at a 100% tariff. In 1996 the tariff was reduced to 50% but increased to 85% in 2001. The erratic rice import policy reflects the dilemma of securing cheap rice for consumers and a fair price for producers. Notwithstanding the various policy measures, domestic rice production has not increased sufficiently to meet the increased demand. Even during the rice import ban period, Nigeria was still importing several hundred thousand tons of rice per year through illegal trade. With the removal of the rice import ban, consumption resumed its rapid growth taking advantage of the downward trends of rice price on the world market.

This fluctuation and limited capacity of the Nigerian rice economy to match the domestic demand has raised a number of pertinent questions both in the policy circle and amongst researchers. Such questions include: what are the factors explaining the lag in domestic rice production vis-a-vis demand for the commodity in Nigeria? Which strategy could lead to a sustainable contribution of the Nigerian rice economy to the national food security within a competitive and open economy? Central to this explanation is the issue of efficiency of the rice farmers in the use of resources. West African Rice Development Association (WARDA) in collaboration with the Nigerian Institute for Social and Economic Research (NISER) suggested this strategy of increasing efficiency at producer level as one of the key components to revitalize the rice sector in Nigeria (WARDA, 2003).

Efficiency is a very important factor of productivity growth in an economy where resources are scarce and opportunities for new technologies are lacking. Inefficiency studies have shown that it is possible to raise productivity by improving efficiency without increasing the resource base or developing new technology (Adedapo, 2008). Farrel (1957) decomposed economic efficiency into technical efficiency and allocative efficiency. Technical efficiency is the ability to produce a given level of output with a minimum quantity of inputs under a given technology (Tijani, 2006). Allocative efficiency refers to the ability to choose optimal input levels for given factor prices.

All production is subject to uncertainty, but the risks associated with agricultural production are particularly salient. Crop yields may be affected by the amount and timing of rainfall, temperatures during the growing season, pests, diseases, hailstorms and fire among many other factors (Nauges, O’Donnell and Quiggin, 2011). However, stud­ies have shown that the effect of these uncertainties on production can be investigated through the choice of inputs on the output variance, otherwise known as production risk in inputs (Jaenicke, Frechette and Larson 2003; Bokusheva and Hockmann 2006; Villano and Fleming 2006).  This is because some inputs increase while others reduce the level of output variance (production risk). Assessment of the efficiency of biological production sectors (such as rice production)  distils important policy implications, provided such assessment takes into account the effects of input use on output variance (production risk), as this is vital for agricultural development planning (Jaenicke, Frechette and Larson 2003; Villano and Fleming 2006). The implication of this is that it is important to incorporate production risk in the measurement of the effi­ciency of rice farmers.

Off-farm work by farm households is a persistent phenomenon throughout the world, both in less developed and developing countries, and the dependence of farm families on the income from off-farm work has increased steadily over the years (Chang and Wen, 2011) . The importance of off-farm work has also been acknowledged in many countries. For example, by using a random farmer survey in rural Ghana, Jolliffe (2004) reported that approximately 74% of the farm households engaged in some form of off-farm work. Similar evidence has also been found in Taiwan. Based on the statistics summarized from the Agricultural Census data in 2001, approximately 75% of the farm households have reported off-farm income.

In light of the increasing importance of off-farm income as a crucial determinant of farm household well-being, a considerable body of literature has examined the roles of household characteristics, the human capital of the farm operator and spouse, as well as farm programs related to off-farm labour participation (e.g., El-Osta and Morehart, 2008; El-Osta, Mishra and Morehart, 2007, 2008; Huffman and Lange, 1989; Lass, Findeis and Hallberg, 1991; Mishra and Goodwin, 1997). Attention has also been paid to the interaction between the farm practice and the off-farm work of the farm household (e.g., Phimister and Roberts, 2006). It is expected that the increased reliance on off-farm employment affects the allocation of family labour, and thus exerts an influence on farm productivity. On the other hand, off-farm work provides an opportunity for farm households to stabilize household income and reduce the uncertainty associated with agricultural production. It is a generally held belief that off-farm employment provides a risk management tool to reduce the income variability associated with the farm household (El-Osta and Morehart, 2008; El-Osta et al., 2007). Hence, this study becomes crucial in examining the interconnection among off farm work, technical efficiency and rice production risk since increased output and productivity are directly related to production efficiency and production risk.

1.2 PROBLEM STATEMENT

Rice is an important food crop in Nigeria and its consumption is growing particularly among urban dwellers. Domestic production of this commodity has been inadequate and unable to bridge the increasing demand-supply gap. Government efforts of making the country self sufficient has not yielded the required results and thus the resort to importation of the commodity. This constitutes a great drain in the country’s foreign reserve. Government’s goal of achieving self sufficiency in rice production to a large extent will depend on the level of farmers’ productivity which can be determined by rates of adoption of improved technologies and efficiency of resource use. However, with the difficulties encountered by farmers in developing countries for developing and adopting improved technologies due to resource poverty, efficiency has become a very significant factor in increasing productivity (Ali and Chandry, 1990).

Numerous studies (Obwona, 2006; Ogundele and Okoruwa 2006; Tijani, 2006;   Al-hassan, 2008; Nwaru and Iheke, 2010, Onoja, and Achike, 2010;) have attempted to determine technical efficiencies of farmers in developing countries including Nigeria because determining the efficiency status of farmers is important for policy purposes. However, few of these studies took account of the presence of risk and the farmers’ responses to it, considering the common knowledge that economic units make their decisions under uncertainty. This presents a research gap that needs to be filled. The presence of risk influences not only production output but also producers’ behaviour, primarily with regard to input use. If risk mitigation plays a principal role in decision-making, then a farm’s technical efficiency score may alter significantly. Therefore, technical efficiency assessment considering a producer’s response to uncertainty is not the same in a setting where no effect of risk on input-use decisions is taken into account. Thus, when uncertainty is pervasive, the theoretical framework for studying technical efficiency is to be extended with respect to risk and producers’ responses to risk. In this study, production risk is assumed to be an important factor that influences production decisions of farmers. Hence, the present study aims to estimate the magnitudes of both technical inefficiency and production risk in rice production in Enugu State.

In recent times farm families in general and small farm operators in particular have been seeking off-farm employment in increasing numbers. A number of studies exist which try to explain the reasons for this phenomenon. Some of the reasons observed by Lanjouw (1999) include declining farm incomes and desire to insure against agricultural production risk. In the beginning, increasing off-farm work by farm operators was viewed only as a transitional phenomenon, but in recent years researchers have concluded that this change is rather permanent. Economists have since turned their attention towards developing models of multiple job holding (Bollman, 1979; Shiskhko and Bernard, 1976). Little attention has been given to estimating the relative efficiency of rice farmers who take up off-farm work viz a viz their counterpart who do not especially in Nigeria. While there is a growing realization that part-time farming is becoming an integral part of Nigerian agriculture, these farms are also likely to have the most staying power since they do not depend solely on farm income for their viability. Some studies have also documented the impacts of off-farm work on farm productivity (Bagi, 1984; Kumbhakar et al., 1989; Sherlund et al., 2002; Smith, 2002). On the other hand, studies on production risk in agricultural production have been extensive over several decades and research interest in agricultural risk continues to grow. The relationship between farmers’ off-farm work and production risks has also been examined. Mishra & Goodwin (1997), for example, have demonstrated that farm households may treat off-farm work as a vehicle to stabilize their income due to farm commodity prices being more variable than off-farm wages. As predicted by production theory, a risk-averse farmer will allocate labour and other resources to the less risky income sources (i.e., the off-farm work) until the expected marginal returns between available activities are equal to each other. As a result, the reduction in farm production risk may lead farmers to participate in the off-farm labour market. In spite of this inter-relationship between off- farm work, production risk and technical efficiency available literature reviewed showed that little or no study have been done in Nigeria with particular emphasis on Enugu State to examine these connections. This study intends to fill this gap. Also, there is need to assess the current levels of technical efficiency of rice farmers in Enugu State and identify factors that affect their technical efficiency. More importantly there is need to determine whether off- farm work improves efficiency, whether there are differences between rice farmers with and without off- farm work, and why.

This study will contribute to previous studies on off farm work by accommodating technical efficiency and production risk simultaneously. The joint consideration of risk, efficiency and off-farm work is important since the technical efficiency of each farmer, as well as production risk, may affect the output response of crop production.

This study in a bid to fill the above-mentioned gaps will provide answers to the following research questions:

How does off-farm work influence technical efficiency and production risk of rice farmers in Enugu State;

Are there factors that affect the technical efficiency and production risk of rice farmers with and without off-farm work and

What are the constraints faced by rice farmers in the study area.

1.3 OBJECTIVE OF THE STUDY

The broad objective of this study is to examine the effects of off-farm work on technical efficiency and production risk among rice farmers in Enugu State, Nigeria. The specific objectives are to:

describe the socio-economic characteristics of rice farmers with and without off-farm work;

describe rice production in the study area;

determine the technical efficiency of rice farmers with and without off-farm work;

compare the technical efficiency of rice farmers with and without off-farm work;

ascertain factors that affect technical efficiency and production risk of the two groups of rice farmers;

identify the constraints faced by the rice farmers in the study area and

make policy recommendations based on the findings.

1.4 HYPOTHESES OF THE STUDY

farmers in the study are not technically efficient;

production risk effects are not present in the model;

there is no significant difference in the technical efficiency of farmers with and without off-farm work and

socio-economic characteristics do not affect the technical efficiency of the two groups of rice farmers.

1.5 JUSTIFICATION OF THE STUDY

Efficiency studies help countries to determine the extent to which they can raise productivity by improving the neglected source, i.e., efficiency, with the existing resource base and available technology (Al- Hassan, 2008). Such studies could support decisions on whether to improve efficiency first or to develop a new technology in the short run. More importantly, enhanced technical efficiency will not only enable farmers to increase the use of productive resources, it will also give direction for the adjustments required in the long run to achieve food sustainability.

It is now widely accepted that to meet the challenges of future agricultural policy design in the future, we must understand farm household behaviour in a more complex policy context that recognizes the diverse nature of farms with respect to farm size, farm production and business organization. We must also recognize the increasing interconnection between decisions made by farm businesses and farm households, and their effects on the well-being of farm families (Kuhn and Offutt 1999; Offutt, 2002). Recommendations suggested from such would boost the effectiveness and success of policies and programmes targeted at increasing productivity. Given the increasing number of farm families taking up off-farm work, the increasing rice demand-supply gap and the risk associated with rice production the need for this study is justified.  The recommendations from this study are expected to give direction to policy makers in designing appropriate policies to increase rice productivity in Enugu State and Nigeria as a whole. This is because more knowledge about whether farm productivity and efficiency are affected by part-time farming could help policy makers introduce better rural development policies.

Also, farmers will find this work very useful as it will help increase their productivity as they gain understanding of the interconnection between off-farm work, technical efficiency and rice production risk. Moreover, the results from this study will provide baseline information to researchers who want to undertake further studies in this area. Other stakeholders who can benefit from the results of this study are donor agencies, research stations and even extension workers.

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