This study examines the impact of Economic Policy Uncertainty (EPU) on the consumer confidence index (CCI) in Pakistan. Using a sample from the start of 2012 up to February 2020, a vector error-correction model is used to gauge the impact of EPU on CCI. Our results show that a shock to EPU in Pakistan affects CCI negatively and significantly. The shock persists for a span of more than 20 forecast horizons, informing economic policy makers in Pakistan that sudden changes in the stance without proper communication can deteriorate consumer confidence. This is important as consumer confidence in Pakistan accounts for not only the current economic situation, but expected changes in key macroeconomic variables which is usually a key consideration when forward-looking policies are devised. Our results remain robust to alternate Choleski specifications and lag lengths in the model.
KEYWORDS: Pakistan, economic policy uncertainty consumer confidence VECM IRFs VDCs

This paper examines the impact of remittances on output volatility through the channel of financial development using data for 158 countries from 1971 to 2017. We estimate the role of financial development by looking at multiple features of financial institutions, such as depth, access and efficiency. We used multiple indicators as a proxy of financial development in the remittance-output volatility nexus and employed System Generalized Method of Moments (GMM) and Fixed Effects Instrumental Variable (FEIV) models. Our findings are robust across specifications. We find a significant positive impact of all indicators of financial development on the remittance-output volatility relationship. The findings suggest that multifaceted financial development is needed for the effective management of output volatility through remittance inflows.
KEYWORDS: Output volatility remittances financial developmen remittance-output volatility nexus

International trade plays a pivotal role in growth and development. The use of ICT is profoundly changing the landscape for international trade and expands opportunities especially for developing countries. The key objective of this study is to investigate the effects of different ICT capacities on the extensive and intensive margins of firm-level exports using micro-data of manufacturing firms operating in selected South Asian countries. We employ the Probit and fractional response models as estimation techniques. Findings of the study reveal that different ICT capacities are positively associated with both the extensive and intensive margins of firm-level exports, and our results are robust to the alternative empirical specifications. These results have important implications for designing the export promotion policies in selected South Asian countries. Hence, policy practitioners in these countries should encourage firms to invest in ICT capacities to boost their export performance.
KEYWORDS: ICT Intensive Margin Extensive Margin Manufacturing Firms South Asia

Predicting the ebb and flow of stock markets is a complex and challenging exercise owing to the disruptive and uncertain behavior of stock prices. The COVID-19 pandemic is an example of an event that, had a drastic impact on global stock markets, due to business activities and trading being severely affected. It is important, therefore, to be able to predict how stock markets behave in a crisis period. We find that stock markets obtain the worst returns in countries where there are higher reported positive cases of coronavirus. This study employs adaptive neuro-fuzzy inference systems (ANFIS), comprising of a controller and the stock market process, to predict the behavior of selected stock indices. After training ANFIS and evaluating the resultant data, we estimate statistical errors and found that 100 training epochs provide marginally better results. To test the accuracy of our results, we used hit rate success and report that the neuro-fuzzy system predicts stock market trends with an average accuracy of 65.84%, an improvement over earlier techniques reported in the literature. Finally, we compute the rate of return using a buy-and-hold strategy and a neuro-fuzzy system, and identify that market indices outperform by employing the proposed method.
KEYWORDS: Stock market index COVID-19 Neuro-fuzzy forecasting

With rising growth rates and per capita income levels on the Indian subcontinent, foreign direct investment in the region, especially through mergers and acquisitions, has increased over the past decade. Using transaction data regarding the industry affiliation of the target and acquiring firms, deal size, deal structure, and deal completion rates from a worldwide M&A database compiled by Thomson Reuters’ Financial Services, this article aims to provide contemporary and comparative information on merger and acquisition (M&A) activity in India, Pakistan, Bangladesh, and Sri Lanka over the last decade, 2010-2019. The largest numbers and values of mergers occurred in India. Surprisingly, Sri Lanka had the second largest number of M&A deals, followed by Pakistan and Bangladesh. Pakistan accounted for the second highest transaction value, followed by Bangladesh and Sri Lanka. The Sri Lankan M&A market had a high ratio (60 percent) of Sri Lankan firms acquiring other Sri Lankan firms, while in Bangladesh, non-Bangladeshi companies accounted for ninety-three percent of the value of all large M&A deals. Future trends, important caveats, policy issues, and implications for managers planning M&A deals in the region are presented.
KEYWORDS: Pakistan Mergers and Acquisitions transaction data