Economic Studies - Mphil Thesis

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    Growing urbanization and economic development in india: The role of middle class
    (Central University of Punjab, 2013) Jindal, Neha; Singla, Naresh
    In the present study entitled "Growing Urbanization and Economic Development in India: The Role of Middle Class", examined that the growing urbanization leads to economic development by creating new rising middle class. The assessment is based mainly on secondary data which is analyzed using correlation, multiple regression analysis by testing of improvement of fit, path analysis and simple averages. The determinants of the size and growth of the middle class and role of middle class in economic development are also examined in this study. Size of middle class is associated with growing urbanization, higher school enrollment, higher share of service and industrial sector in GDP than agriculture sector and lower fertility. Using the definition of middle class given by NCAER and data on various determinants of middle class spanning the period 1990-2010, the multiple regression analysis by testing the improvement of fit, has been carried out to know the significant variables. And find that a larger middle class influenced through the growing urbanization and tertiary school enrollment. It was also found out that middle plays a positive role in economic development by regressing the size of middle class on HDI, GDP per capita and gross capital formation (parameters of ii economic development). The estimates show the positive and significant relation between them. Further through path analysis technique the significance of direct and indirect paths between various variables is analyzed. A casual model is proposed showing that the growing urbanization and tertiary school enrollment leads to rising new middle class and further the higher size of middle class leads to effect positively the HDI, GDP per capita, gross capital formation. The model coming out to be over identified and the estimates revealed that variables in the model are significant and the R2 in every path is high. Showing that each variable in the model has its own significant importance important. But the overall model is coming out to be bad fit. This is the limitation of the study and may be due to less number of observation and paths taken in the model.