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Purpose -This paper aims to investigate the impact of FDI on the stock market development in Pakistan, both aggregate as well as sector wise, the reason being that no such work has been carried out in this context. Design/methodology/approach -The study is based on secondary data for the period 1985-2011. Johansen co-integration approach is used for determining relationship among variables for aggregate stock market development in long run. Granger causality test is also applied to check the causal relation between the variables. Correlation analysis and regression analysis has been used for examining the relationship of sector wise development, FDI and economic growth in Pakistan. Findings -The results support the positive role of FDI in boosting the aggregate stock market development in long run. Bi-directional causality between FDI and economic growth has been found along with the uni-directional causality between aggregate stock market development and economic growth. For sector wise development the relationship of FDI is positive in the sectors where FDI concentration is high in recent years whereas and negative in other sectors. Originality/value -Co-integration coefficients showed a positive and statistically strong relationship between FDI and aggregate market capitalization thus reflecting the complementary role of FDI in the stock market development of Pakistan.

Environmental quality indicators are crucial for responsive and cost-effective policies. The objective of the study is to examine the relationship between environmental quality indicators and financial development in Malaysia. For this purpose, the number of environmental quality indicators has been used, i.e., air pollution measured by carbon dioxide emissions, population density per square kilometer of land area, agricultural production measured by cereal production and livestock production, and energy resources considered by energy use and fossil fuel energy consumption, which placed an impact on the financial development of the country. The study used four main financial indicators, i.e., broad money supply (M2), domestic credit provided by the financial sector (DCFS), domestic credit to the private sector (DCPC), and inflation (CPI), which each financial indicator separately estimated with the environmental quality indicators, over a period of 1975-2013. The study used the generalized method of moments (GMM) technique to minimize the simultaneity from the model. The results show that carbon dioxide emissions exert the positive correlation with the M2, DCFC, and DCPC, while there is a negative correlation with the CPI. However, these results have been evaporated from the GMM estimates, where carbon emissions have no significant relationship with any of the four financial indicators in Malaysia. The GMM results show that population density has a negative relationship with the all four financial indicators; however, in case of M2, this relationship is insignificant to explain their result. Cereal production has a positive relationship with the DCPC, while there is a negative relationship with the CPI. Livestock production exerts the positive relationship with the all four financial indicators; however, this relationship with the CPI has a more elastic relationship, while the remaining relationship is less elastic with the three financial indicators in a country. Energy resources comprise energy use and fossil fuel energy consumption, both have distinct results with the financial indicators, as energy demand have a positive and significant relationship with the DCFC, DCPC, and CPI, while fossil fuel energy consumption have a negative relationship with these three financial indicators. The results of the study are of value to both environmentalists and policy makers.

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The objective of the study is to empirically examine the air pollution, greenhouse gas (GHG) emissions and low birth weight in Pakistan through the cointegration and error correction model over a 36-year time period, i.e., between 1975 and 2012. The study employed the Johansen cointegration technique to estimate the long-run relationship between the variables, while an error correction model was used to determine the short-run dynamics of the system. The study was limited to the following variables, including carbon dioxide emissions, methane emissions, nitrous oxide emissions, GHG emissions, and low birth weight in order to manage robust data analysis. The results reveal that air pollution and GHG emissions significantly affects the low birth weight in Pakistan. In the long run, carbon dioxide emissions act as a strong contributor for low birth weight, as the coefficient value indicates there is a more elastic relationship (i.e., -1.214, p<0.000) between them, whereas in the short run, this results has been evaporated. Subsequently, in the short run, GHG emissions have a one-to-one corresponding relationship with the low birth weight in Pakistan. Nitrous oxide emissions, both in the short and long run, have a significant and less elastic relationship (i.e., -0.517 with p<0.001 and -0.335 with p<0.090). Methane emissions have no significant relationship with the low birth weight in Pakistan.