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Household’s Saving Behaviour in Pakistan: A Micro-Data Analysis

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  • Naeem Akram

Abstract

Savings play a very crucial role in the economic development of a country by financing investment needs. Household savings are the major and dominant component of national savings in Pakistan. The present study aims to analyse the impact of various socio-economic factors in determining the household savings in Pakistan by using the data of Household Integrated Income and Consumption Survey (HIICS) 2015–2016. It has been found that household’s savings tend to increase with income, living in nucleus family, house ownership, receiving remittances from abroad and being involved in agriculture; and saving tends to decrease with an increase in dependency ratio; and wealth has an insignificant role in determining savings in both urban and rural households. However, education and female labour force participation had a positive relationship with saving among urban households but the relationship is insignificant in rural households. Similarly, age of household head hurts saving in urban households and the relationship is insignificant in rural households. JEL Classifications: E21, D91, C31

Suggested Citation

  • Naeem Akram, 2023. "Household’s Saving Behaviour in Pakistan: A Micro-Data Analysis," Studies in Microeconomics, , vol. 11(2), pages 139-156, August.
    • Handle: RePEc:sae:miceco:v:11:y:2023:i:2:p:139-156
    DOI: 10.1177/23210222211024377
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    References listed on IDEAS

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    More about this item

    Keywords

    Household saving; income and expenditure; microdata; Pakistan;
    All these keywords.

    JEL classification:

    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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