Non-Farm Employmentand Production Efficiency of Farm Household in Bangladesh

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Non-Farm Employmentand Production Efficiency of Farm Household in Bangladesh Bangladesh J. Agric. Econs. XXXVII, 1&2 (2014, 2015) 55-68 NON-FARM EMPLOYMENTAND PRODUCTION EFFICIENCY OF FARM HOUSEHOLD IN BANGLADESH Shakila Salam1 Siegfried Bauer2 ABSTRACT This article attempts to examine the effect of non-farm employment on rural farm household’s technical efficiency in Bangladesh. Cobb-Douglas production function through stochastic frontier modelwith single stage estimation procedure is used to estimate farm efficiencies. The study was based on primary data collected from a cross-section of 153 farm households, drawn by multi-stage purposivesampling from three districts of Bangladesh. Part-time farmers are less technically efficient than the full-time farmers which indicate negative influence of non-farm employment on farm efficiency. A mixed influence on technical efficiency is found when non-farm employment is broken down into different sources. Compared toother types of non-farm activities, self-employment increases the farm technical efficiency. Results indicate that numbers of active household members, household head age, farm size, and ownership of agricultural machines are important factors for reducing the inefficiency level of part-time agricultural households. Key words: Non-farm employment; Technical efficiency; Stochastic frontier; Farm household; and Bangladesh I. INTRODUCTION The movement of labour out of agriculture has significantly witnessed in many developing countries like Bangladesh. Participation in part-time farming or multiple jobholding is not a recent phenomenon in the world. Many developed and developing countries (e.g., Germany, Japan, Ireland, England, Korea, China, etc.) promoted part-time farming for structural transformation and development of the economy (Pfeffer, 1989; Johnston, 1962; Cawley, 1983; Zhou et al, 2001; and Kimhi, 2000). Part-time farming is commonly defined as a special case of multiple job-holding, which implies the combination of a small amount of farming practices along with an occupation outside of agriculture (Shishko andRostker, 1976; and Salter, 1936). The increasing nature of unemployment in Bangladesh is a result of high population growth rate, extreme landlessness and seasonal nature of agriculture. Besides, wide-spread use of modern technologies, especially in land preparation, irrigation and post- harvesting has also released a considerable amount of labour from agriculture. Moreover, less 1Assistant Professor, Institute of Agribusiness and Development Studies, Bangladesh Agricultural University, Mymensingh-2202. E-mail: [email protected] 2Professor, Department of Regional and Project Planning, Justus-Liebig University, Giessen, Germany. 56 The Bangladesh Journal of Agricultural Economics profitable farming business contributed to the deep pervasiveness of poverty in rural farm households. Therefore, rural households are losing their interest on farming and compelled to join in some sort of non-farm activities. Households are generally engaged in self- employment based activities (such as, business, cottage industry, transportation services, retail trading, etc.), wage based activities (non-agricultural labour work, service in government and non-government organizations, industrial labour and so on) and migrating to urban or overseas countries. As agriculture in Bangladesh is still characterized by subsistence farming, most of the farmers are not interested to leave farming as a whole. Therefore, part-time farming has emerged as an alternative livelihood strategy for surviving land-scarce poor farm households. However, participation in non-farm activities has direct and indirect influence on agricultural production. Existing studies on different countries, for instance studies on Bulgaria, Romania, Ukraine, Kosovo, Ethiopia, and China reveal that involvement in different types of non-farm activities might have a considerable impact on rural areas (Dittrich and Jeleva, 2009; Surd, 2010; Peacock, 2012; Sauera et al, 2015; Abebe, 2014; and Jin et al, 2014). Particularly, farm income of part-time farmer is insufficient and it is considered as one of the important threats to achieve production efficiency in agriculture (Jervell, 1999). Therefore, the consequence of non-farm employment on agricultural production efficiency is still under farm policy debate. This situation leads to an important query about the impact of non-farm activities on agricultural efficiency. This studyfocuses on the effect of non-farm income on farm technical efficiency in Bangladesh. Another objective of this research is to identify the factors causing variations in technical efficiency of part-time farming households. A Stochastic frontier model with single stage estimation procedure is used to address the objectives of the research. Moreover, the study contributes to the development literature by finding out the actual relation among non- farm income, part-time farming, and technical efficiency. The findings of Bojnec and Ferto (2011), Yue and Sonoda (2012), and Abebe (2014) confirmed the positive association between off-farm income and technical efficiency in case of Slovenian, Chinese, and Ethiopian farmers, respectively. On the other hand, Kumbhakar et al (1991) found that farmers without off-farm wage are more efficient than those with off-farm wage on Utah dairy farm households. Although there has been much research on the efficiency measurement, but very few research are done to find out this type of non-farm income effect on farm efficiency in Bangladesh. Therefore, analysing the impact of non-farm income on farm technical efficiency is of greater importance and aims to fill the gap in this area. II. METHODOLOGY 2.1 Data Sources The required data for this study was derived from a cross-sectional primary data set, collected through a farm household survey from 3 districts, namely Mymensingh, Comilla and Dinajpur districts of Bangladesh. Among these districts, Comilla is a district where non-farm employment and migration rate is too high and 39.41 percent of households fully depend on Non-Farm Employment and Production 57 non-agricultural activity for their livelihood (BBS, 2011). According to latest available data, Mymensingh added the highest gross value to agriculture, while Comilla added comparatively lower value in 2005 (BBS, 2006). Bhaluka and Haluaghat Upazilas under Mymensingh, BoruraUpazila under Comilla and BirolUpazila under Dinajpur district were selected as study areas. Finally, multi-stage purposivesampling procedure was employed to identify the 153 sample households from four villages. Sample households were categorized into farm households (income source is only agricultural activities), and farm and non-farm income earning households or part-time farming households (income source is both agriculture and non-farm activities) consisting of 59 and 94 households respectively (Appendices Table A1). Data were collected through a key information and questionnaire survey with farm households during July to November 2014. For gathering qualitative information, knowing the actual situation and crosschecking the data, Focus Group Discussion (FGD) with the farmers was conducted in each of the selected villages. 2.2 Empirical model The term technical efficiency (TE) measures the degree to which a producer maximize possible outputs using a given set of inputs, or producing a given level of output by using possible minimum inputs. The first definition leads to the term of output-oriented efficiency measures, whereas the next one indicates input-oriented efficiency measures (Coelli et al, 2005a). In this analysis, an output-oriented efficiency measure is used because it is mostly practiced in developing country’s agricultural production system.There are two approaches for measuring technical efficiency: (i) the parametric and (ii) the non-parametric approach. Like many other previous studies, this study considered parametric approach for estimating TE and its determinants in a single-equation procedure (Kumbhakar et al, 1991; Huang and Lui, 1994; Battese and Coelli, 1995; Kilic et al, 2009; Anik, 2012; andKabir et al, 2015). This single-equation approach is widely used and less objectionable from a statistical point of view, as it provides more efficient inference regarding included parameters. As based on a certain point of production frontier (where technical efficiency is zero) the ratio between observed (actual) output and potential output calculates the degree of technical efficiency of each agricultural household; stochastic frontier approach is best suited to this situation (Coelli et al, 2005b; and Kilic et al, 2009). Thus, the amount by which an agricultural household actual production level drops below the frontier level is measured by technical inefficiency. Mathematically, TE can be expressed as, Yi TEi = …………………………………………….(1) vi f (X i ;β )*e th Where, Yi and Xi indicate output and vector of inputs used in the production by i household v respectively, β is a vector of frontier parameters to be estimated and e i implies random shocks.This value of efficiency lies between zero and one. The efficiency score 1 implies achievement of potential production level and less than 1 indicates existence of technical inefficiency. 58 The Bangladesh Journal of Agricultural Economics Cobb-Douglas (CD) and Translog (TL) models are mostly used for frontier analysis in the previous studies. In this research, both of these models are specified and finally selected most relevant one by using log-likelihood ratio test. The test statistic is presented as: LR = -2{ln [L(H0)/L(H1)]}
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