Purpose of the study: This study investigates Short-run, Long-run, and Casual relationships in the Asian Developed and Emerging stock market indices for the period of 19 years weekly data of stock market indices of Asian Developed and Emerging Markets which are Japan (Nikkei 225), South Korea (KOSPI), Pakistan (KSE 100), China (SSE Composite), Sri Lanka (ASPI), India (BSE 200) and Malaysia (KLSE composite) from January 2001 to December 2019. Methodology: To analyze long-run and short-run relationships among the Asian developed and emerging stock markets, this study practices Descriptive Statistics, Correlation Matrix, Unit Root Test, Johansen Co-Integration Test, Vector Error Correction Model, Granger Causality test, Variance Decomposition and Impulse Response Function (IRF). Main findings: By employing the ADF and P.P. tests, the results specify that the entire variables' data are non-stationary and stationary in exact order, which is 1st difference. The Johnson Co-integration test found one cointegration relationship, where the results are consistent with Granger causality, Variance Decomposition, and Impulse Response Function (IRF). Application of the study: As the current research has focused on finding out the comovements in the Asian developed and emerging markets. So, the applications are that the survey found short-run and long-run relationships in these countries' stock markets. The study's originality: The current study has selected seven Asian developed and emerging stock markets and weekly updated time series data to investigate short-term and long-term linkages. So, this study found long-run comovements in these stock indices, which contributes to the literature. In addition, these stock markets have limited diversification benefits for international investors, while short-term diversification benefits may exist.

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This paper analyzes the dynamics of social protection expenditures in the context of structural and institutional characteristics across provinces in Pakistan. A rank and regression analysis is employed on a panel dataset for four provinces of Pakistan namely Khyber Pakhtunkhwa(KP), Balochistan, Sindh, and Punjab; over a period of 1988 to 2014.The analysis shows that KP gave more preference to education, health and, social security and welfare, and rank at the top in the respective social protection parameter. However, considering the structural and institutional features, KP shows a better performance in all social protection categories except social security and welfare. Punjab is in worst condition with respect to fiscal space generation, structural and institutional features in all social protection channels. Balochistan has better fiscal budget for subsidies and transfers but hasthe least structural and institutional features in utilizing these funds optimally. The Sindh province has the better structural and institutional performance for social protection provision but has comparatively low fiscal space for them. Theregression analysis results indicate that most of the structural and institutional features played a significant role in the determination of fiscal space for the concerned provinces. For Policy prospects, Sindh government needs to enhance the fiscal space for social protection purposes, whereas KP and Balochistan need to improve the required structural and institutional performance. In the case of Punjab, there is a need to enhance their fiscal space for social protection along with improved structural and institutional performances.

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