Migration can be categorized into different types depending on different aspects. Based on time period, migration can be temporary, permanent and seasonal, on the basis of purpose it can be labour migration, forced migration, migration can be categorized as internal and international on the basis of location, and legal and illegal migration with processes involved in migration (Maharjan, 2010). In the present study, only international labour migration is considered. The study was conducted to explore the factors influencing labour migration and impact of remittance on the living standard of the farm households left behind members. To understand the materials and methods used in this research, this section is discussed in the following aspects: study area and sampling design, data collection, and empirical method used for analyzing the determinants of labour migration and remittance use behaviour of the farm households.
Study area and sampling design: This study was conducted at two upazila of Bogura districts namely Gabtoli and Shahjahanpur. These study areas were selected purposively considering the migration situation and agricultural practices of the areas. To identify the sample farm household at first the purposive sampling technique was applied. The sample households with migrant and households without migrant were randomly selected from the list of population in the study area. This study was based on both primary and secondary sources of data and information. Sample survey method was used for primary data collection. The secondary sources of information include government annual reports, official statistical abstracts and researches undertaken in the study area. Moreover, data published in different public books, policy document about farm and non-farm sectors as well as research journals was also important to accomplish the research. The research data were collected from the BBS, BER, Country Profile and various published papers and journals.
Data collection: The primary data were collected from 30 households with migrant and 30 households without migrant. Required data were collected through interviewing the head of each non-migrant household and other family member of the migrant household. Economic profile of households with migrant and households without migrant, socioeconomic profile of expatriate, amount of remittance, expenditure, savings and investment related information, income and employment related information, agricultural activities of the farmers, agricultural technology use in the farm and finally problems and constrains were included in the interview schedule. The data were collected during the period from February to April, 2018. A questionnaire was used to interview for the selected group of household with migrant and household without migrant. Each respondent was given a brief description about the aim and objectives of the study before beginning the interview. The questions were asked in a simple manner and friendly environment with explanation where it was felt necessary. The information supplied by the respondent was recorded directly on the interview schedule. The filled-in questionnaires were checked after the interview in order to avoid errors and omission. Data were collected in local unit, which were converted into standard units while processing and editing the data.
Analytical techniques: In the present study several analytical methods were undertaken to meet particular research objectives. Descriptive statistics were taken into account to analyze data and to describe socioeconomic characteristics of respondents, types of occupation, household’s income and expenditure etc. In order to investigate the extent of influence of the determinants on the decision making status of labour migration, logistic regression analysis (Logit model) was used. In Logit model, all the regressors are involved in computing the changes in probability (Guzarati, 2004). This model predicts the probability of an outcome that can only have two values (i.e., a dichotomy). The prediction is based on the use of one or several predictors (numerical and categorical). A logistic regression produces a logistic curve, which is limited to values between 0 to 1. In the present research, the following logit model was used to identify the influencing factors of labour migration in the study area: Zi = ln [Pi÷(1- Pi)] = β0 + β 1Q1 + β 2Q2 + β 3Q3 + β 4Q4 + β 5Q5+ Ui Where, Pi is the probability of households with migrant and households without migrant; Pi = 1 indicates households with migrant and Pi = 0 indicates households without migrant; Dependent variables: Zi= probability of households with migrant; Independent variables: Q1 = Age of the household’s head (years); Q2=Educational level of household head; Q3 = Household size (no.); Q4 = Land (Farm size in ha); Q5 = Number of educated member in the household; β0 = Intercept; β1 to β5= Regression coefficients of the dependent variables; and Ui= Error term.