Livability is a concept that assesses the quality of life and relative performance of different regions and communities, based on various qualitative and quantitative factors. The assessment of urban livability is a complex and multidimensional task, which is of utmost importance for informed and transparent policy and decision making. The present study aimed to develop a road map for cities’ ranking on the bases of their livability. We have used a case study of eight major cities of Punjab, Pakistan. Indicators of cities’ sustainability considered for the cities’ ranking were spatial planning and growth, individual wellbeing, urban economy, connectivity and infrastructure, quality of life, and the urban environment. In the first stage, after the consolidation of socio-economic, environmental, and other indicators, they are converted into dimension indices by taking geometric means. In the second stage, the Analytical Hierarchical Process (AHP) has been employed for assigning weights to each dimension into a composite index. The results of the study depict the disparities among cities through a multidimensional analysis. Lahore is ranked as first overall from the bottom. Thus, the study recommends that, despite the high standing of Lahore on the livability ladder, it must address the issue of connectivity and traffic congestion and per capita needs of the public infrastructure for a growing mega metropolitan city of over 10 million people. Similarly, Rawalpindi is ranked as the second-best city with regard to livability in Punjab. The main contributing factors for Rawalpindi city are ‘individual well-being’, ‘urban economy’, and ‘urban environment’. Moreover, the current study also suggests important policy implications for decision makers to highlight the areas that must be reconsidered for improvement in terms of the selected indicators and dimensions.

This paper studies the relationship between GDP fluctuations and long-run economic growth through using macro-panel approach (with small N and large T) in a panel of five selected South Asian countries (SSAC) including Bangladesh, India, Nepal, Pakistan and Sri Lanka over a period of 1980-2010. For this purpose, modern non-stationary panel techniques such as cross section dependence test, unit root test under cross sectional dependence, panel cointegration and Group Mean Fully Modified OLS (GM-FMOLS) estimation are applied. This study finds a significant long-run cointegrating relationship between GDP fluctuations and long-run growth in the SSAC and GM-FMOLS estimates show that this link is negative. It indicates that GDP fluctuations have a significant negative impact on long-run growth in the SSAC and these fluctuations of GDP may be detrimental for long-run growth in developing countries. Therefore, the governments of such countries shouldn’t rely on growth-oriented policies only but should equally focus on managing these fluctuations in GDP to achieve sustained and stable growth rate.

This study examines the relationship between GDP fluctuations and private investment through employing macro panel approach in a panel of five selected South As