This book explored the relationship between regional disparity, inequality and economic growth for the period 1972-2007 of Bangladesh. Except from others, it deals with two distinct but related issues. First, it investigates the relationship between inequality and economic growth in the situation where consideration of the effects of household final consumption expenditure, per capita and urban population growth in Bangladesh. Second, the study looks into the issue of regional disparity within the country. Data over the different periods in the last two decades were employed to identified the affected regional factors e.g. size of public expenditure, variations of receiving remittance, incidence of poverty, distribution of poor, intensity and severity of poverty, GDP and GDP per capita and per capita income and consumption expenditure by stratum in this part of analysis. Lastly, this study tried to make a link with economic growth, inequality and regional disparity in the context of Bangladesh.

This research examines the important issue of labor market dynamics of Bangladesh during 1987-2009. First, it investigates the relevance of Phillips curve and analyzes the two important extension of original Phillips Curve i.e. expectation augmented and supply shock augmented Phillips curve.The analysis derives the Non-Accelerating Inflation Rate of Unemployment (NAIRU) of Bangladesh following the Ball-Mankiw approach. Second, it looks the issue of wage inequality in manufacturing, construction and agriculture sector of Bangladesh in various dimensions. Result shows that the theme of Phillips curve is consistent in Bangladesh economy. Unemployment rate, unemployment gap, change in exchange rate are negatively related with inflation whereas lagged inflation and change in international price of crude oil is positively related. Inflation lag has a relatively higher impact on inflation dynamics. With sectoral wage disparity there is large wage gap between skilled and unskilled labor. The urban-rural wage differential is severe in manufacturing sector as compared to construction and agriculture sector.