*Md. Tanvir Ahmed,
Department of Agricultural Economics, University of the Philippines, Los Banos, Philippines.
Humnath Bhandari
Scientist, Social Sciences Division, International Rice Research Institute, Philippines
Prudenciano U. Gordoncillo,
Department of Agricultural Economics, University of the Philippines, Los Banos, Philippines.
Cesar B. Quicoy
Department of Agricultural Economics, University of the Philippines, Los Banos, Philippines.
Gideon P. Carnaje
Department of Agricultural Economics, University of the Philippines, Los Banos, Philippines.
Livelihood diversification, Simpson index, Rural Bangladesh
Socio-economic and Policy
Income generation
Data Source and Sampling Design: A multi-stage random sampling technique was used to select sample villages. Eleven districts were purposively selected to represent large geographical area and diverse livelihoods of the country. In 10 districts, one sub-district from each district, one union from each sub-district, and one village from each union were selected randomly. In one largest district in the country, two sub-districts, one union from each sub-district, and one village from each union were selected randomly. Thus, 12 villages were randomly selected from 11 districts and four geographical regions (northern, middle, south-eastern and western) of the country. Finally, 45 rural households were randomly chosen from each selected village making a total sample of 540 households. Only 500 households were included in the analysis as some households’ data were incomplete. The study used primary data collected through interview schedule and pre-tested questionnaires; and the information used were for 2012–2013 period. Information elicited from the responded are demography, land ownership, primary and secondary occupations of household members, migrations and remittances, assets ownership, labor force, on-farm activities, off-farm activities, non-farm activities, credit and savings, agricultural prices, income from different sources, and living conditions. The study used households’ net income by deducting total cost from total returns. The share of income from different sources was the basis to assess their livelihood diversification. Operational Definitions: The major variables used in the study are defined below. Dependency ratio. It is the ratio of economically inactive persons - people younger than 18 or older than 59 - over the active persons - those ages 18-59 - of a household expressed in percentage. Adult literacy rate. It represents the percentage of adult people (aged >14 years) who can read and write. Operated landholding. It is classified into four groups based on the cultivated land: (1) functionally landless (less than 0.2 hectare (ha)), (2) small (0.21-0.80 ha), (3) medium (0.81-1.50 ha) and (4) large (over 1.50 ha). Income source. Households’ income sources are grouped in nine. 1) Rice crop (net income from all rice crops in a year), 2) Non-rice crops (net income from all non-rice crops in a year), 3) Non-crop agriculture (income from livestock, fishery and forestry), 4) Agricultural laborer (labor employed in agricultural sectors), 5) Non-agricultural laborer (included both formal and informal types of employment), 6) Business and caste occupation, 7) Salaried job and services, 8) Remittance income (received from family members presently living outside the family: both domestic and abroad), and 9) Transfer payment. Analytical Methods Simple descriptive analysis (average, mean, median, percentage etc.) along with the ANOVA test were carried out to describe the socio-economic characteristics, distribution of household income from different sources and their share across the regions. Tabular analysis was also employed to compare various household well-being indicators of different study areas. Livelihood Diversification Index: The most common measure of livelihood diversification is the vector of income share associated with different income sources. Besides, livelihood diversification is measured using different indicators and indices, such as Simpson index, Herfindahl index, Ogive index, Entropy index, Modified Entropy index, and Composite Entropy index. This study used Simpson index because of its computational simplicity, robustness and wider applicability.
Journal of Agricultural Economics and Rural Development Vol. 2(2), pp. 032-038, July, 2015. © www.premierpublishers.org, ISSN: 2167-0477
Journal