Structural Change and Dynamics of Labor Markets in Bangladesh by Selim Raihan

Author:Selim Raihan
Language: eng
Format: epub, pdf
ISBN: 9789811320712
Publisher: Springer Singapore

In the above regression model, the dependent variable is the informal intensity of any sector, i.e., the percentage of informal participation in a particular industry type out of total employed persons in that industry type. This variable can thus be termed as the informal sector participation. The variables that affect the decision of participation in the informal sector can include both individual and family characteristics. To capture the effect of individual and family characteristics, years of schooling (edu), individual age, dependency ratio (deprto), measured as the ratio of number of dependents in the family to total members of the family, and gender (female dummy) are introduced as explanatory variables. The square term of age (age_sqr) is also included in the regression to capture the nonlinearity in the effect of age on the informal sector participation. The financial condition of the workers’ household may also affect the decision to enter in the informal sector. The land holding (land), measured in acres, was used as a proxy of the financial condition of the household. Furthermore, an employed person may be a wage employed (wage), self-employed (self), or may be an unpaid worker (unpaid) as per the LFS (Labor Force Survey) classification. We, therefore, have introduced dummies representing these three groups in the regression to see whether there is any association between informal sector participation and employment types after controlling for other factors. The category of wage employed (wage) is omitted from the regression as we are taking this group as the base category.

By taking the average for each cohort, we are able to construct a pseudo panel where each of the observation represents a particular industry type. The interpretations of the independent variables in the context of the pseudo panel are the following:

The variable representing education level of the workers is interpreted as average years of schooling of the labor employed in a particular industry type.

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