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.