The issue of twin imbalances is at the forefront of fiscal policy concerns in the South Asian region, fuelled by an ever-going budget deficit and current account deficit over the last five decades. A standard approach is to assume a model in which budget balance influences the current account. We relax this assumption by using a panel data vector autoregression model comprising five South Asian countries. The results show that both budget deficit and current account deficit are mutually causative, which contrasts the unidirectional causality running from fiscal deficit to current account deficit found in prior studies. Further, this bi-causality relationship is also demonstrated in the impulse response analyses. Budget balance in South Asian economies re- sponds positively to a one standard deviation positive shock in the current account balance. Likewise, external balance increases to a one standard deviation positive shock in internal bal- ance. Higher fiscal debt impedes economic growth, which in turn impacts negatively on the budget balance. Our findings lead us to reject ’fiscal policy only’ recommendations to address the twin deficits.
keywords: کسری دوقلو | مدل P-VAR | آزمون علیت پانل گرنجر | تابع پاسخ ضربه ای | آسیای جنوبی | Twin deficits | P-VAR model | Panel Granger causality test | Impulse response function | South Asia

This In the present globalized smart ecosystem, various suggestions of using data as a new tool for the development of the economy are still going on to be presented. Hence, developed countries are trying to pursue different policy measures to develop the big data industry, including promoting big data R&D sector and investment in human resources to retain the pace of this global trend. The government of Pakistan has supported liberal policies to activate the IT its applications such as big data, Internet of Things (IOT) and electronic government (e-government). We used the Analytic Network Process (ANP) model to prioritize policy measures and find out its implications for Pakistan. This study will convey an important lesson for developing countries and particularly for South Asian countries to establish policies for developing big data as a new tool for economic growth in the context of smart ecosystem environment.
Keywords: Big data; Internet of things; IOT; Analytic network process; Ecosystem

In this era, energy is essential to life and its continuous and ubiquitous supply brings much needed economic growth and prosperity to a region. Energy Management (EnM) contributes to the controlling and monitoring of energy and has recently become the subject of great significance. EnM involves analysis, conservation and imperative actions that leads to the minimization of the system losses for efficient use of available conventional and renewable energy resources of the region. This study evaluates the energy management in South Asia (SA) region, as it houses one-fourth of the worlds total population with India, Pakistan and Bangladesh being the most populous countries. The study accesses the regional energy mix, distributed generation strategy plans, and present the trends in EnM over the past few decades. South Asian Countries (SACs), especially Pakistan, India and Bangladesh have a huge potential of coal i.e. 17,550, 90,085 and 884 Million Tonnes, respectively. India has rightly explored nearly 70% of its coal potential, whereas Pakistan and Bangladesh despite having the largest potential of the coal have focused on oil (35.4%) and natural gas (91.5%) exploration respectively. It is im portant to note that India experiences the highest technical losses of 23.5%, followed by 17% percent and 14.11% losses by Pakistan and Bangladesh respectively. Energy Intensity (EI) values for Afghanistan, Bhutan and Sri Lanka have listed these countries as low EI terrain region. Pakistan, India and Bangladesh have EI values ranging between 10,000 and 20,000 btu per $2000 constant. SACs countries have monopolistic electricity markets, however steps are taken to partially implement competition and monopoly regulation by privatization and ensuring equal conditions for all vendors. Analysis show that the SACs are presently far behind to meet their energy demands. The paper also recommends introduction and implementation of effective EnM policies along with large scale utilization of non-conventional energy resources, which will bring necessary changes and will help SACs to overcome economic challenges. The study also concludes that the inclusion of renewable energy resources and development of competitive electricity markets would overall improve the EnM in SA.
Keywords: South Asia ، Energy management ، Energy market ، Energy policies ، Energy mix

This study examines the dynamic causal links and volatility spillovers of inflation, output growth and their uncertainties in four South Asian countries, namely, Pakistan, India, Bangladesh and Sri Lanka by utilizing asymmetric GARCH family models. Our empirical evidence supports a number of important conclusions. There is an overwhelming support for Friedman-Ball hypothesis of positive inflation-uncertainty trade-off for all countries excluding India and Sri Lanka. The Cukierman-Meltzer’s idea that inflation uncertainty generates inflation, hold for Bangladesh and Sri Lanka only and the Holland’s hypothesis of negative influence of inflation uncertainty on level inflation is supported by India only. The positive influence of output uncertainty on inflation (Devereux (1989) hypothesis) is supported by all countries excluding Bangladesh while nominal uncertainty (real uncertainty) has negative (positive) effect on output growth in Pakistan (Bangladesh). Output growth is reducing real uncertainty in all countries excluding Sri Lanka and nominal uncertainty in Pakistan only. There is significant negative relationship between inflation and output growth for Pakistan only while real uncertainty is positively (negatively) related with nominal uncertainty in India (Bangladesh). The estimated results are almost robust with the simultaneous estimation procedure for testing the main hypotheses. In general, there is asym metric effect and persistence of the GARCH parameters for all countries. The study suggests that the concerned central banks should pay more attention to the effects of macroeconomic un certainty and should focus their monetary policy strategy on stabilizing both output growth and inflation.
Keywords: Inflation | Output growth | Inflation uncertainty | Output uncertainty | South Asia

Introduction: Substance abuse and criminality share a complex relationship. The rates of substance use among the prisoners, and that of criminal acts among substance users in community setting are high. Data from South Asian countries, including from India are inadequate. This study aimed to assess the pattern of criminal acts among opioid-dependent subjects and their substance use pattern in the month before, during and after imprisonment. Methods: Using a cross-sectional study design and purposive sampling, opioid-dependent subjects (n = 101) attending two community drug treatment clinics who have had any contact with the law were assessed using a specifically-designed tool to record criminal acts and substance use before, during and after last imprisonment. Results: Most subjects (93%) had committed illegal acts in their lifetime. Physical assault was the most common illegal act, while 23% reported selling drugs and 9% reported committing serious crimes. About 95% were arrested and 92% had spent time in police lockups. About 29% were arrested for drugs possession or drug use, and 3% of injecting drug users arrested for carrying injection equipment. About 85% had been imprisoned at least once, of whom 88% used psychoactive substances in the 1-month period before their last imprisonment. Opioids were the most common substances used daily (68%), followed by cannabis (34%) and alcohol (22%). Ninetyseven percent reported the availability of substances in prisons, and 65% also used substances during their last imprisonment. Cannabis (35%) was the most common substances used in prison followed by opioids (19%). Seventy-six percent used substances soon after prison release, and 13% of opioid users experienced opioid overdose soon after prison release. Use of cannabis, injecting drugs, and opioid use before imprisonment were predictors of substance use in prison. Conclusion: Opioid-dependent people have various contacts with the law, including imprisonment. Many users are dependent on substances during prison-entry, which is an important reason for their continued substance use in prisons. There is a need to provide substance abuse treatment across all stages of criminal justice system.
Keywords: Criminality | Opioid-dependence | Incarceration