Women employed in informal sectors are integral to a nation’s overall economic growth, and to better development outcomes. This study aims to examine the capabilities of these women not only in terms of personal empowerment, but in the context of sustainable development via social inclusion. Previous studies have only focused on microcredit as a “magic wand” for increasing women's empowerment and their standard of living, without the inclusion of feminist theory. The inclusion of feminist theory and social inclusion in the discussion concerning the provision of financial support to women in Pakistan, allows us to properly examine the role of sustainable development and women's empowerment in Pakistan. This study is quantitative and descriptive. Using a survey questionnaire on the cross-sectional data source, the 118 women borrowers of Lahore, Pakistan, have been investigated by stratified random sampling technique. The Multinomial logit and Probit regression models have been used for data analysis. The study's results supported the actuality that women need to be financially and personally empowered, in order to benefit from greater social inclusion.
KEYWORDS: Social inclusion, sustainable development, microfinance, women's personal empowerment, informal sector.

JEL: O40, O17.

This study investigates the socioeconomic, administrative, and service quality determinants of electricity theft in Pakistan. The effect of service quality standards on electricity theft is estimated using panel data from eight electricity distribution utilities from 2006 to 2018. The results of utilizing the One-step system Generalized Method of Moments estimator confirm the statistically significant impact of social, administrative, and service quality variables on the illegal use of electricity. Based on the findings, Pakistan's National Electric Power Regulatory Authority is advised to take measures to improve the quality of services. In contrast, the nation’s Central Power Purchasing Agency is advised to improve administrative structure by separating retail function from distribution by electric distribution.
KEYWORDS: Pakistan, Electricity theft, Distribution utilities;, Service quality.

JEL: C33, O14.

This study examines the uncertainty of consumer inflation expectations in Pakistan using the data collected by the State Bank of Pakistan (SBP) through the Consumer Confidence Survey (CCS). CCS has been conducted every second month since January 2012. The research employs round numbers to calculate inflation expectation uncertainty and finds it countercyclical and positively correlated with inflation. Further, it also displays a weakly positive correlation with inflation disagreement, inflation volatility, and the Economic Policy Uncertainty (EPU) index. The study also reveals that inflation expectation uncertainty is higher for female, less educated, and young respondents compared to businessmen, males, older people, and educated. The study suggests asymmetric behavior of inflation expectations uncertainty for high and low inflation levels, where uncertainty is high when inflation is high. The study also suggests that inflation uncertainty is significantly related to food inflation. Lastly, the study establishes that inflation expectation uncertainty affects the consumption of durable goods by influencing consumer spending attitudes.
KEYWORDS: uncertainty, environmental resources, Inflation Expectations, Consumer.

JEL: E31, D18.

This paper introduces the monthly State Bank of Pakistan’s EasyData, for conducting empirical macroeconomic analysis and forecasting for Pakistan's economy. For this purpose. We perform a forecasting exercise using the conventional econometric models and the most recent machine-learning algorithms. We find that the machine- learning models outperform the benchmark and regression models based on observed factors. Furthermore, the dataset has a higher ability to predict the external variables, a possible outcome of Pakistan's economy and its persistent balance of payment problem. The focus of policy has been to address this issue.
KEYWORDS: Pakistan, forecasting, EasyData, factors, machine learning, machine-learning.

JEL: F47, C55.

This study examines the supply and demand shocks in Pakistan that affected occupations and industries during the COVID-19 pandemic. We use the remote labor index and essential scores for undertaking work activities from home across occupations proposed by del Rio-Chanona et al. (2020). To estimate demand shocks, we follow del RioChanona et al. (2020), who employed estimates from the US Congressional Budget Office (2006) that attempted to forecast how the US economy would be affected at the industry level if a severe influenza epidemic occurred. We document that demand shocks most significantly affect the transport and food services industries. In contrast, the manufacturing, mining and quarrying, and handicraft and printing industries are likely to be impacted by supply shocks. Food services and restaurants experience a bigger combined shock. Relative to the pre-pandemic period, aggregate shocks suggest a decrease in the output of Pakistan’s economy by one-fifth if the pandemic were to seriously affect the economy, threatening 21 percent of jobs and lowering total wage income by 18 percent. Considering a second wave and a new variant of coronavirus, we estimate that aggregate shocks may continue, and the economy's output could deteriorate by one-fourth if the region experiences a significant outbreak. Finally, we compare our findings with the US economy and find differences between supply and demand shocks in both economies.
KEYWORDS: wages, financing shocks, value-added, COVID-19, employment.

JEL: J21, O49, I15.

Compensation structures of public sector employees have significant implications for public service delivery and employment. If public sector employees get relatively lower pay, then the government can face difficulties in retaining trained and qualified workers. However, if public sector employees receive higher salaries it is possible that younger people may prefer to join the public sector. If this is accompanied by limited job absorption capacity in the public sector, it is possible for there to be substantial unemployment. This study has analysed the wage differentials by using the data from the Pakistan Labour Force Survey 2020-21. Blinder-Oaxaca decomposition suggests that at the executive level, public sector workers are facing wage penalties, while other occupational groups in the public sector are enjoying wage premiums. The highest wage premiums are for clerical staff followed by unskilled workers, services, technician, professionals and agricultural workers.
KEYWORDS: public sector, private sector, wages, employment.

JEL: E24, J31, J45, L32.

This study examines the role of foreign aid and governance in Pakistan’s human development from 1991 to 2021 utilizing the autoregressive distributed lag (ARDL) technique. It not only explores the individual impact of foreign aid and governance but also investigates how good governance affects human development. A governance indicator has been constructed by employing Principal Component Analysis based on six different governance dimensions. It is found that both good governance and foreign aid have significant and positive relationships with human development in Pakistan and good governance facilitates and reinforces the contribution of foreign aid in advancing human development. The results show that trade openness, income growth, and government expenditure also have a positive impact on human development. The Granger Causality test further verifies the causality running from foreign aid and governance to human development. The analysis implies that enhancing governance quality is important to optimizing the positive impact of foreign aid on human development. Likewise, policies to stimulate trade openness, boost government expenditure on social sectors, and more consistent income growth can play an important role in improving human development in Pakistan.
KEYWORDS: Aid, Governance, Development.

JEL: F35, O1, D73.

This study compares the prices of selected food items across three political administrations in Pakistan. We have taken monthly data from July 2008 to October 2021 of the prices of selected food items from the Pakistan Bureau of Statistics, the Ministry of Finance (Pakistan)’s Pakistan Economic Survey, and Index Mundi. Thirteen food items were selected: Wheat, Basmati Rice, Basmati Super Rice, Basmati Broken Rice, Sindh/Punjab Rice, Tinned Vegetable Ghee, Loose Vegetable Ghee, Whole Masoor Pulse, Washed Masoor Pulse, Washed Mong Pulse, Washed Mash Pulse, Gram Pulse and Refined Sugar. We theorize that an increase in prices will be independent of changes in political administration, as prices are determined purely based on economic factors in the market. We provide graphical and regression analysis, with our study pointing to a consecutive rise in the absolute price of selected food items across all three administrations. Increasing real prices of selected food items are specific to each administration.
KEYWORDS: Political administration, selected food items, nominal prices, real prices, food inflation, ARDL model.

JEL: Q11, L66, N70.

This study aims at identifying the main determinants of the annual trade flows of Pakistan with its top trade partners, including those with which the country has signed trade agreements. Given the present economic conditions of the country, it is important to identify the main determinants of trade so that the country can benefit from trade openness around the world. In addition to identifying trade determinants, the impact of adherence to a particular trade agreement was also examined. The results indicate that FTA signed by Pakistan with China and other trade partners has created trade opportunities for participating countries, highlighting the importance of trade liberalization for the long-run development of the country. Besides, the trade potential of Pakistan with selected trade partners has also been estimated.
KEYWORDS: Pakistan, gravity model, panel data, total trade, trade potential.

JEL: C23, P45, F10.

This study examines the trade potential of Pakistan with the countries of the Gulf Cooperation Council (GCC). Trade potential is estimated using the RCA (Revealed Comparative Advantage) index technique, utilizing HS-8 tariff line level data from 2007 to 2021. Our findings identify 102 products at the tariff line where Pakistan enjoys a comparative advantage. These products span various sectors, including copper, iron, steel, minerals, wood, pharmaceutical, paper, tobacco, sugar, and plastic. Furthermore, the paper discusses the trade hindering effect of factors such as the absence of effective trade agreements, shortage and high energy prices, and other high input costs.
KEYWORDS: Trade potential, Pakistan, Gulf Cooperation Council, HS-8, revealed comparative advantage.

JEL: F10, C61.

In Pakistan, essential food items are exempted from indirect taxes to avoid any subsequent increase in their prices, with the goal of protecting the poor from a regressive tax burden. Taxes on inputs such as on fuel and energy, however, are transferred to consumer prices and, due to cascading effects, can exert a burden on households. This study investigates the incidence of indirect taxes on essential and nonessential food items across households in Pakistan. To do so, we follow an input‒output multiplier- based approach that allows the measurement of the cascading effect of taxes. It employs the latest available edition of the Household Integrated Economic Survey (HIES) 2018- 19 in order to observe household food expenditures. Our analysis establishes that there is an effective tax even on items that are ostensibly tax-exempt, implying that households pay taxes indirectly even on those items. The incidence of these indirect taxes on essential food items is regressive across all household deciles and the incidence of indirect taxes on nonessential items is progressive at high expenditure deciles but proportional in the lower-ranking expenditure deciles.
KEYWORDS: Tax Incidence, Distribution of Tax Burden, Tax Burden, Indirect Taxes, Pattern of Incidence, Pakistan.

JEL: E31, H22, H23.

The prime objective of this study is to examine how agglomeration affects the productivity of firms by location. Using different spatial econometrics on geo-referenced data of textile manufacturers in Pakistan, the study confirmed the presence of spatial autocorrelation in firm productivity. Results show that highly productive textile firms appear to be clustered in the regions of Lahore and Faisalabad, while low productivity textile firms appear to be clustered in Karachi and the Federal areas of Pakistan. Although the spread of clusters varies a bit with the use of different weight matrices, similar hotspots and cold spot patterns are observable. Furthermore, spatial error and spatial lag models find that younger textile firms tend to be more productive than older ones and firm size, exports, quality assurance certifications, and R&D spending are the key spatial correlates of textile firm productivity.
KEYWORDS: Firm Productivity, Agglomeration, Spatial Analysis, Textile, Pakistan.

JEL: D22, D24, L25.

This paper investigates whether consumer confidence improves the prediction of GDP growth over what are popularly construed as fundamental economic variables. We use monthly data concerning Consumer Confidence Index (CCI) and its sub-indices to forecast GDP growth for Pakistan. Employing a set of univariate and multivariate models and comparing their forecasting performance against the Naïve mean model, we find that adding the consumer sentiments with fundamental economic variables improves the forecast of GDP growth. Vector autoregressive model with current economic conditions index and economic fundamentals, we find, performs the best. The results have potential policy implications in terms of tackling unemployment and inflation, for economic growth stimulation.
KEYWORDS: Consumer Confidence Index, Forecasting, GDP growth, AR, ARMA, VAR.

JEL: C53, E17, C32, D12.

The objective of this article is to evaluate the impact of Pakistan-Sri Lanka Free Trade Agreement (FTA) on Pakistan's and Sri Lanka's macroeconomic structures. The FTA is operational since June 2005. For this purpose, the Computable General Equilibrium (CGE) Model has been used and simulations have been conducted by using the Global Trade Analysis Project (GTAP) model, which measures the effect of FTA on Pakistan. The GTAP is a General Equilibrium modeling structure of the multiple economies. The finding of this study reflects that Pakistan has positive impact on real GDP, trade and welfare, while Sri Lanka has negative impact on the same factors. Moreover, the results of this study are coherent with the international trade theories. This research assists the trade policy makers to adopt appropriate policies for future FTAs with South Asian economies to obtain more gains for Pakistan.
KEYWORDS: Pakistan, Sri Lanka, FTA, General Equilibrium, GTAP.

JEL: F15.

Our study enriches the growing literature on cost stickiness in the context of an emerging economy. The study examines the relationship between cost stickiness and dividend payout behavior in Pakistan, and the possibility of their being a moderating role of family ownership. Empirically, we employed 4,567 firm-year observations of non-financial firms listed on the Pakistan Stock Exchange, over the period 2006-2021, and used ordinary least squares regression method to test our hypotheses. Additionally, we used generalized method of moments techniques (GMM) to test the robustness of our results. Using the lens of agency theory, we find that cost stickiness is associated with higher dividend payouts. Further, family ownership moderates the relationship between cost stickiness and dividend payout. Overall, our results support cost stickiness in our sample of firms and a positive correlation of family ownership with dividend payout.
KEYWORDS: Cost stickiness, dividend payout, agency theory.

JEL: G32.

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.