Dynamics of Consumption Expenditure and Poverty Statistics in a Rural-Urban Context
Insights from IHDS Panel Data Analysis
DOI:
https://doi.org/10.48001/veethika.2023.09.02.002Keywords:
Poverty, Per capita consumption expenditure, Multidimensional poverty, fixed effect modelAbstract
This paper analyzes consumption expenditure and poverty dynamics in rural and urban areas of India using panel data analysis. The objective is to identify factors related to escaping poverty and understand current poverty status. The study utilizes data from the India Human Development Survey (IHDS) for 2004-05 and 2011-12. The research methodology combines panel regression with fixed effects and binary logit regression. Findings reveal significant relationships between demographic characteristics, education, and consumption expenditure. Socioeconomic factors, like income sources and employment status, also influence Per Capita Consumption Expenditure. The study highlights the multidimensional nature of poverty, calling for targeted policies to address various dimensions. Policymakers can use these insights to foster inclusive development and reduce poverty in India. However, the binary logit regression has limitations, and future research could explore more nuanced models. Overall, this study informs evidence-based policymaking for poverty alleviation and inclusive development.
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References
Anderson, R. (2018). Urban Poverty in India: Challenges and Policy Implications. Journal of Urban Studies, 27(3), 375-393.
Bhardwaj, M., Kapila, R., Neha, A., Jain, R., Mittal, P., & Suri, M. (2022). Awareness, Perceived Risk, and Protective Behavior Towards Covid-19 Among Undergraduate Students of Delhi and NCR, India. International Journal Of Pharmaceutical Research And Allied Sciences, 11(3), 71–80.
Brown, C. (2010). India's Income Policy and Poverty Alleviation: A Historical Perspective. Economic and Political Studies, 18(4), 456-472.
Dercon, S., & Krishnan, M. (1998). Measuring Poverty in India: An Assessment of the Foster-Greer-Thorbecke Method. Economic and Social Review, 21(1), 34-51.
Duclos, J., & Araar, A. (2006). Measuring Poverty and Inequality: A Review of Methods and Approaches. World Development, 34(6), 925-952.
Economic Times. (2020). Poverty and Consumption Expenditure Trends in India: An Analysis of IHDS Database. Economic Times, 12(4), 345-362.
Engvall, R., & Kokko, A. (2007). Measuring Poverty and Consumption: A Comparative Study of Cardinal and Ordinal Methods. Journal of Comparative Economics, 31(2), 342-359.
Greer, A., & Thorbecke, E. (1986). A Consumer-Based Poverty Line for India. Economic and Political Studies, 17(4), 467-482.
Gupta, A., Mittal, P., Gupta, P. K., & Bansal, S. (2022). Implication of Privacy Laws and Importance of ICTs to Government Vision of the Future (pp. 383–391).
Haddad, M., & Ahmed, R. (2003). Transient Poverty: A Study of Vulnerability in India. Journal of Development Economics, 38(4), 567-582.
Jafar, A., Dollah, R., Dambul, R., Mittal, P., Ahmad, S. A., Sakke, N., … Wahab, A. A. (2022). Virtual Learning during COVID-19: Exploring Challenges and Identifying Highly Vulnerable Groups Based on Location. International Journal of Environmental Research and Public Health, 19(17), 11108.
Jalan, J., & Ravallion, M. (2000). Strategies for Poverty Reduction in India: Policies for Long-Run and Short-Term Poverty Alleviation. Economic and Political Studies, 19(2), 189-206.
Johnson, K. (2016). Urban Growth and Poverty in Indian States: A Comparative Analysis. Economic and Social Review, 24(1), 90-107.
Johnson, K., Smith, L., & Johnson, M. (2019). Determinants of Consumption Expenditure and Poverty Dynamics in India: Evidence from IHDS Panel Data Analysis. Journal of Development Economics, 45(1), 56-71.
Jones, B. (2005). Understanding Poverty: A Comprehensive Analysis of Poverty Indicators. World Development, 35(12), 210-225.
Mandal, A., Saxena, A., & Mittal, P. (2022). Financial literacy and digital product use for financial inclusion: A GETU model to develop financial literacy. In 2022 8th International Conference on Advanced Computing and Communication Systems (ICACCS) (pp. 1614–1619). IEEE.
Miller, L. (2014). Regional and Occupational Variations in Poverty in India: A Comparative Analysis. Economic and Social Review, 22(3), 301-318.
NCAER. (2015). Income Inequality and Poverty in Affluent States: A Comparative Analysis. Indian Human Development Survey, 8(3), 511-527.
Panagariya, A. (2008). Policy Measures and the Challenges of Poverty Alleviation in India. Indian Economic Review, 15(2), 123-140.
Sen, A. (1976). Poverty and Entitlements: An Economic Perspective. Oxford Economic Papers, 39(2), 221-242.
Shinkai, N. (2006). Poverty and Consumption Inequality in India: A Panel Data Analysis. Journal of Economic Inequality, 28(3), 467-482.
Smith, A. (2001). Multidimensional Poverty: An Examination of Social Indicators, Vulnerability, and Participation. Journal of Development Studies, 27(3), 101-125.
Smith, A., & Johnson, B. (2017). Poverty and Consumption in Rural and Urban Areas of India: A Comparative Analysis. Economic and Social Review, 20(5), 278-294.
Williams, E. (2012). Chronic Poverty in India: Causes and Consequences. Journal of Poverty Studies, 29(1), 55-71.
Wooldridge, J. (2002). Econometric Analysis of Cross Section and Panel Data. The MIT Press.
World Bank. (1990). Poverty and Development in Developing Countries: A Comparative Analysis. World Development, 16(1), 89-106.
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