Employment diversification depicts a dynamic socio-economic process where domestic workers widen the range of employment sources. Whereas, the prospect is usually based on a mix of Part-time and Full-time employment. Employment decisions significantly derive from the economic incentives such as wage differentials and the growth rates in different sub-sectors of economic activity. Research at hand summarizes and analyses Employment Diversification Patterns in Pakistan and the motives behind the labor shift. Time series data has been collected from various sources for 1990-2018. The Seemingly unrelated regression model has been applied for empirical estimations. The current analysis of employment pattern diversification concluded that part-time and full-time wages rates have a significant impact on the part and full-time employment in different sub-sectors of economic growth. Variation in wage rates in one sub-sector varies the employment level in different sectors. The estimates elaborated the significant rise in part-time employment these sub-sectors. Moreover, the dynamic interrelation between part-time and full-time employment is examined in the Agriculture, Construction, Electricity, Manufacturing, Wholesale and Retail Trade, Transport, Storage and Communication. These estimates show the quick adjustment of part-time employment within and across the sectors. Policies are needed to enhance labor mobility as one wants to diversify the employment one can do it to enhance the economic productivity.

Abstract. Urbanized areas are typically the most significant sources of environmental degradation, thus, an urban assessment criteria tools aiming at equally adapted sustainability dimensions need to be firmly embedded in benchmarking planning and design framework and upon occupancy. The need for integral systematic rating is recognized in order to evaluate the performance of sustainable neighborhood and to promote sustainable urban development. In this study, Green Building Index Township Assessment Criteria (GBI-TAC) will be measure on holistic sustainable dimension pillar (SDP) adaptation in order to assess and redefine the current sustainability assessment criteria for future sustainable neighborhood development (SND). The objective of the research is to find-out whether the current GBI-TAC and its variables fulfilled the holistic SDP adaptations towards sustainable neighborhood development in Malaysia. The stakeholderinclusion approached is used in this research in order to gather professional's stakeholders' opinions regarding the SDP adaptations for sustainable neighborhood development. The data were analysed using IBM SPSS AMOS22 Structural Equation Modelling. The findings suggested an adaptation gap of SDP in current GBI-TAC even though all core-criteria supported SDP adaptation, hence lead to further review and refinement for future Neighborhood Assessment Criteria in Malaysia.

This study addresses the linkage between the gross domestic product and infrastructure in Pakistan. The time frame taken for this study is from 1977-2019. The information utilized in this study is taken from reliable sources; World Bank. ARDL method is utilized in this study with the assistance of E-VIEWS 10 programming. To consider the effect of infrastructure on GDP; the factors are utilized, for example, gross fixed capital formation, health expenditures, total generation age of power, life expectancy, and government expenditure on education. These factors are utilized as the intermediary of the framework. Gross Domestic Product is taken as the dependent variable while net fixed capital arrangement, health consumption, complete age of power, future, and government uses on schooling are taken as autonomous factors in this paper. The consequences of this study show that the gross fixed capital formation, wellbeing consumption, and workforce have a positive connection to GDP. Then again, the total generation of electricity and government expenditures on schooling adversely affect the economy of Pakistan. The infrastructure is one of the principals and fundamental variables for the improvement of the economy of Pakistan. The helpless state of infrastructure in Pakistan is probably the greatest deterrent in the advancement of the country. The public authority should zero in on the upgrading of the approaches in regards to the infrastructure area, for instance; enhancements in the health sector, progression in the energy area, abilities advancement preparing places for the workforce, and upgrades in the schooling area. All the previously mentioned steps can assist with improving economic development through infrastructural improvement.

This study intended to explore the linkage between education, poverty rates, and economic growth in Pakistan. Data for various variables have been collected from 1973 to 2017.  After establishing the stationary process by utilizing the Augmented Dickey-Fuller Test the research used the (ARDL) Auto-Regressive Distributed Lag methodology to estimate the empirical relationships. This study took GDP as a dependent variable whereas independent variables are literacy, health, inflation, headcount ratio, export. The result concluded that Inflation and poverty are the determinants to hinder economic growth while Health, Exports, and literacy are statically significant and have a positive impact on economic growth. It is suggested that a keen focus should put to enhance the educational and health facilities so that higher growth can be achieved. Anti-poverty policies must be made that make them more productive so this will lead to the growth process.

Employment growth (part-time and full-time) in Sub-sectors of economic activity is not only determined by the output growth in this sector but the time lag is also involved, in addition to this the wage elasticity of employment is also critical in determining employment diversification and labor mobility between sectors, varied widely in different sectors of the economy. This paper endeavors to illustrate the role of part-time and full-time employment elasticity among sectors along with employment diversification. Furthermore, the empirical analysis is carried out on time series data for 1990 to 2019. By utilizing Seemingly Unrelated regression and by estimating wage elasticity of employment with modified two factor Cobb-Douglas function for full time and part-time employment, the results have been illustrated, by carefully considering the reliability, consistency, and accuracy of the findings, this study demonstrates an increased sectoral output tends to enhance employment in respective sectors. For the manufacturing sector and construction sector, both sectoral output and total output were found to have comparable responses that suggest employment for both sectors tends to increase in line with the output. Therefore, the conclusions of the study establish that an effective way to enhance employment is to create flexibility in the wages as an efficient approach to enhance sectoral employment.