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Research Article Open access CC BY 4.0

Effects of Different Socio-economic Characteristics of Rural Households on Their Saving Decision in Pabna District of Bangladesh: A Binary Logistic Regression Analysis

Md. Al-Amin

Asian Journal of Economics, Business and Accounting · pp. 14–20 · Published 9 Dec 2020

10.9734/ajeba/2020/v20i230320

Abstract

Household saving ensures a smooth future by softening the potential insecurities arise from uncertainty at the cost of present consumption. Moreover, the volume of national investment determines the actual health of an economy which is intensively associated with national savings. This study aimed at determining the effects of different socio-economic characteristics of rural households on their saving decision in Pabna district of Bangladesh. This research used a set of cross-sectional data from 250 households from three upazilas in Pabna district namely Pabna Sadar, Iswardi and Sujanagar on the relevant variables for the empirical analysis. A multistage random sampling technique involving simple, purposive and stratified random sampling was used to draw the sample. The study employed a binary logistic regression model to assess the influences of different socio-economic and demographic characteristics of rural household on their saving decision. The findings of the current study asserted that gender, family size and dependency ratio of household have significant and negative effects on their decision to start saving or not to start saving. Contrarily, the effects of the variables age, education level, marital status, income, secondary earner and liabilities on the decision of households to participate in saving were positive and significant. Moreover, the results revealed that social status has a strong but insignificant effect, but the variables access to bank and credit facilities have almost no significant effect on the household saving decisions. Since, private savings is essential for both the micro and macro level of an economy, therefore the study tried to suggest some recommendations with a view to increase private savings.

Household saving saving decision binary logistic regression dependency ratio

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