Interest in detection of factors consider responsible for uneven fluctuation in steady state growth of world economies is long standing. There has been an explosion of theoretical literature and empirical evidences which think about compassionate to resolve the issue. Hike in prices of goods and services and foreign exchange are two important aspects which believe to blame for such bumpy vacillation in economic growth of the world economies like all other political, social and economic factors. It is true that both factors have inimitable significance for economic growth, but inquiry about internal relationships of above said both variables still has research thirst.  The novelty of this research paper is, it provides the empirical evidence regarding the relationships between foreign exchange and inflation focusing on Pakistan experience since 1960. We use the Auto Regressive Distributive Lag Model (ARDL) proposed by Pesaran et al. (2001) in order to investigate the order of co-integration between inflation and foreign exchange through bound testing approach, and also use the OLS estimation to determine the long run relationship. Through econometric techniques, we trace the nature of relationship and speed of adjustment between concerned variables in response to fluctuation in level of foreign exchange. Empirical results indicate the negative correlation between the level of foreign exchange and rate of inflation in Pakistan during study period. 

In developing economies like Pakistan, the rising trend of women's labor participation has become the core indicator of growth and development. In this respect, the MDGs (Millennium Development Goals) relates to efficiency and equity, especially elimination of gender disparities in education, improvement of maternal health, lessening mortality rate among children and women empowerment are desirable goals. But still the representation of women in wage as well as in the self-employment sector is very low. The present study investigates the factors which influence women's participation in self-employment. Primary source of data is used for empirical analysis. Logistic regression technique is employed to estimate the women self-employment model. The findings indicate that age and experience positively affects women's self-employment. Further, it is concluded that education, location and number of dependents significantly reduce the women's work participation as self-employed worker. It is suggested that the government provide technical and vocational education to the women, and also give old age benefits just to minimize the dependency burden.Keywords: Women Self-employment, Experience, Logistic regression, Dependency burden, Higher Education, Per Capita Income. IntroductionThe population of Pakistan indicates a double faced phenomenon. On the one side, population of the country is considered as an asset and performs an integral role in the growth and development process of the country. On the other hand, the high growth rate of population is a great hindrance in way of economic prosperity and development of the country. For examining the role of human capital in economic development, it is imperative to study both the qualitative and quantitative aspects of the population. At the time of independence in 1947, the total population of Pakistan was 32.5 million. By the year 2006-07, the population reached 156.77 million. The population of Pakistan has grown at an average rate of 2.6 percent per year. The changes in the labor force and employment level are affected by the population growth rate and its composition. This high growth rate of population shows that Pakistan will become the eighth most populous country in the world by the year 2010 (Govt. of Pakistan Economic Survey 2006-07). Employment generation, poverty reduction and human resource development are the main features of Pakistan development policy. The employment led growth rate captures a central place in attaining the sustained development. Table 1 highlights the labor force participation (LFPR) among the region and gender based on crude activity rates in the years 1996-97 to 2005-06. The labor force of Pakistan was estimated at 50.05 million on the basis of participation rate of 32.2 percent during the year 2005-06. During the two years, this rate has increased from 45.23 million to the present level by adding 4.82 million, both men and women. The present situation nevertheless is the information about a high dependency ratio. From the table 1, ...

Contingent upon the empirical work done, the current study seeks to investigate the environmental load capacity factor (LCF) consequences of financial development in three different ways for 48 Asian economies. We used the two-step system generalized method of moments (GMM) technique to analyze the data from 1996 to 2020. Initially, we investigated the environmental consequences of financial development by considering six dimensions of financial development. Then, we modified the original environmental Kuznets curve (EKC) into the financial market-based EKC (FM-EKC) to compare short- and long-run environmental consequences of financial development. Ultimately, the study explores the intersecting marginal effects of financial development and institutional quality on environmental quality. Our results show that foreign direct investment (FDI), financial development, economic growth, and environmental quality (LCF) exhibit statistically significant long-run co-integrating relationships in the studied economies. This study demonstrated how FDI, financial development, and economic expansion contribute to environmental deterioration in 48 Asian countries. The nexus between finance and sustainability is moderated by the institutional quality and the regulatory environment, resulting in the FM-EKC idea. The key findings of system GMM analysis confirmed that Asian countries have an inverted U-shaped FM-EKC, which we attempt to explain with three different justifications. This study showed that the strong institutional structure in an economy guarantees the favorable environmental consequences of financial development in the long run. It also suggested that a healthier education structure of an economy can help improve the environmental quality of an economy.

The performance of an economy is generally measured by sustained rise in GDP growth over the period of time. The economic growth is the major goal of macroeconomics. According to neo-classical growth theory, the core factors of growth are labour and capital. In addition to these factors; technological progress, human capital development etc. are the most efficient factors of production. Development of technology and use of mechanisation in production process require energy at massive scale. So, energy has become a crucial factor of economic growth indirectly. Energy is widely regarded as a propelling force behind any economic activity and indeed plays a vital role in enhancing production. Therefore, highly important resources of energy will enhance the technology impact manifold. Quality energy resources can act as facilitator of technology while less worthy resources can dampen the power of new technology. Ojinnaka (1998) argued that the consumption of energy tracks with the national product. Hence, the scale of energy consumption per capita is an important indicator of economic modernisation. In general countries that have higher per capita energy consumption are more developed than those with low level of consumption.

This study aims to explore the socio-economic and demographic determinants of poverty in Southern Punjab by using the cross sectional data consisting of 785 household heads. Binary logistic regression  and ordinary least square method are used for estimation. The findings exhibit that the variables like family system, household size, presence of disease and status of employment of household head are positively and significantly related to  poverty whereas household head age, rural-to-urban migration,  years of schooling,  number of earners, women status of work, remittances, the physical assets value and ownership of house significantly and negatively influence the likelihood of poverty and positively influence the per capita income of the households in Southern Punjab. The study also provides the comparison of regional and division level. It is concluded that DG Khan division is the poorest among all the divisions of the southern Punjab. In DG Khan Division, the households have less education, high dependency ratio. In rural areas of southern Punjab, there is more poverty as compare to urban areas. The rural poverty is due to many factors like high dependency rate, lower level of education, adoption of profession, lower per capita income, dissaving. It is suggested that education should be promoted, employment opportunity should be provided so that dependency rate may be reduced, rural areas should be restructured by provision of basic necessities of life.