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: Economic Policy, Pakistan, uncertainty, consumer confidence, VECM, IRFs, VDCs.
JEL: E32, H00, H31.

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.
JEL: C33, F24.

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: Regional economic integration, ICT, Intensive Margin, Extensive Margin, Manufacturing Firms, South Asia.
JEL: F14, F23, D22.

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.
JEL: C53, E17, G11, G12.

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.
JEL: G34.

It is essential that policymakers consider cyclical changes in output. Monthly industrial production is one of the most important and commonly used macroeconomic indicators for this purpose. However, monthly estimates of industrial production are not available for Pakistan. Instead, policymakers rely on a large-scale manufacturing (LSM) index that accounts for only 10 percent of GDP. Another limitation of this index is that it accounts primarily for private sector industry, leaving out the direct public sector presence in industrial production. Economic policymakers rely heavily on the LSM index to gauge economic activity in Pakistan. In this study, we compute a new industrial production index (IPI) that extends to the whole industrial sector in Pakistan, incorporating additional information that the LSM index misses. Post-estimation, we build seven econometric models reflecting conditions in the real, financial, and external sectors to estimate year-on-year changes in the new IPI. Our results show that the root mean square error of the ARDL model reflecting financial conditions is lowest of the models tested, which included AR, VAR, and BVAR, across all horizons.
KEYWORDS: Economic indicator, industry studies, econometric forecasting, Pakistan.
JEL: L600, C80, C530.

Expanding home-ownership poses a fundament financial challenge arising out of the long-term nature of the asset, which calls for the development of institutions and markets to facilitate the flow of long-term funds. Development of the secondary mortgage market would alleviate classical maturity mismatch and liquidity issues. The public sector can provide an enabling environment with sound macroeconomic policies, corporate governance, rule of law, and enforceability of contracts. This study draws policy implications using the empirical evidence on the determinants of mortgage depth and penetration across countries. A large part of the variation in these two dimensions across countries is explained by the level of their financial development. Development of long-term sources of funds intermediated through specialized institutions seems particularly important, as we find that the development of pension funds, which are a source of long-term funding, is strongly associated with mortgage market development. Monetary and macro-economic stability, as indicated by a low and stable rate of inflation, appears to be a strong predictor of mortgage market development. We also detect a positive relationship between the degree of competition in the financial sector and mortgage market development.
KEYWORDS: House financing, mortgage markets, securitization, affordable housing, Pakistan.
JEL: G21, G28, G50.

This study investigates the impact of various fiscal policy instruments on the income inequality of Pakistan using an Auto Regressive Distributed Lag (ARDL) model on annual data. We find that direct taxes reduce income inequality, measured using the Gini index, while indirect taxes increase disparities. As the major portion of tax revenues are indirect taxes, the current tax regime of Pakistan does not achieve income redistribution. Similarly, development expenditures have significantly reduced income inequality, likely through the creation of employment opportunities. On the other hand, the overall fiscal deficit increases income inequality, due to a rising public debt financed by (regressive) indirect taxes. This study suggests that in the case of Pakistan, where direct taxes are low, a large shadow economy exists, and weak tax administration prevails, an increase in development expenditures and broadening of the tax base of direct taxes should be the main fiscal policy tools for income redistribution. Moreover, persistent high fiscal deficits in the long run should be avoided. Finally, governments should reduce educational inequalities and promote democratic values in the country in order to promote greater fairness in distribution of income.
KEYWORDS: Fiscal policy, Gini index, taxes, development expenditures, ARDL, Pakistan.
JEL: E62, D63, H27.

Emerging research in empirical economics posits a question on the relation between underlying risk preferences and reflective cognitive ability. In an experimental setting, a preliminary sample of 260 participants undergo a series of incentivized choice experiments to elicit risk preferences and a Cognitive Reflection Test (CRT) to obtain estimates of their reflective ability. We sidestep potential biases by using a Fechner error specification along with a contextualized version of the utility function. Individuals who are more likely to avoid risky outcomes have significantly lower scores on the CRT. The analysis validates a prominent relationship spanning the economics and psychology literature and suggests a potential direction of causal inference for future research.
KEYWORDS: Risk, cognitive reflective ability, behavioral economics, Pakistan.
JEL: C36, C91, D81.

Pomegranates are one of the most important fruits in the Kandahar province of Afghanistan, which is famous for its pomegranates around the world. Pomegranates play a vital role in the socio-economic life of those who grow them. This study empirically analyzed the value chain of pomegranate production in Kandahar using primary and secondary data. Primary data was collected from 200 pomegranate growers in the Dand, Panjwai, and Daman districts of Kandahar province. These growers were selected using a random sampling method and the data was collected using a structured, pre-tested questionnaire. The secondary data was collected from traders, local collectors, and exporters of pomegranates involving 30 pomegranate selling companies. The value chain analysis shows that from the main four chains of pomegranate production (farmer, collector, trader, and exporter), the main actors are the exporters who process pomegranate and add the greatest value by investing in marketing, shipment, and warehousing and receive highest profit margin among the stakeholders. Exporters of pomegranates to Europe earn an average of 66 Afghani per kg. The next greatest beneficiaries are the growers or farmers who earn an average of 23 AFN on each kg. Local collectors who buy pomegranates from farmers earn the least, at an average of 13 AFN per kg over the costs of processing and transportation.
KEYWORDS: Production, labor, cost, profit margin, farmers, Afghanistan.
JEL: D4, D46.