Investigating symmetrical influence of economic expansion, oil price, and industrial production on trade deficit: a policy pathway toward three neighboring Asian states

The intense objective of the present study is to investigate the symmetrical effectiveness of economic expansion, inflation rate, oil price, interest rate, and industrial production on trade deficit of the three neighboring states (China, Pakistan, and India). Westerlund bootstrap LM (Lagrange multiplier) panel co-integration test, Dumitrescu Herlin method, PMG-ARDL model, quantile regression, and quarterly data of last 15 years (2006Q1 to 2020Q4) have been utilized to envisage outcomes. Initial measurements validate the existence of stable co-integration and uni-directional causality among variables. Nevertheless, PMG-ARDL measures evaluates that in both long and short span of time, except industrial production all other regressors (economic expansion, inflation rate, oil price, and interest rate) positively influences the trade deficit in three neighboring states. Furthermore, robust estimates of quantile regression also authenticate the correctness of the above discuss relationship in study economies by evaluating positive (negative) impact of economic expansion, inflation rate, oil price, and interest rate (industrial production) on trade deficit. Thus, in policy pint of view, to lessen trade deficit hazard in studied economies, it is necessarily needed to encourage industrial production, replaced fossil fuel using outdated gadgets with advance green technology instruments, control inflation, and interest rate in single digit through strong budgetary and monetary policies and maintain economic expansion with appropriate and comprehensive taxation system.

Nobel prize in physiology or medicine by the Indian medical education system: How far and how close?

Every year, Nobel prizes are announced, recognizing the unique contributions of individuals and organizations across the globe. Currently, India hosts the largest medical education system in the world with 650 medical colleges spread all over India and capacity to train 100,000 MBBS medical doctors a year. India is also a hub of cost-effective pharmaceutical industries and dubbed as the 'pharmacy of the world'. However, the cost of care is still out of reach of a large section of the population. If India is to become a global economic power, such aspirations cannot be solely based on the consumer market-driven economy but on achieving supremacy in 'new knowledge' creation as well. The research capacity needs to be optimized and capable of translating research work into the domestic monopoly and control over newer knowledge, technologies, products, and services for global consumers. Cost of care for more than 1 billion people, even if it is through universal health coverage, can be significantly reduced by supporting research activities and creating domestic intellectual properties in the healthcare sector.

A dissection of Indian growth using a DSGE filter

In order to build a strong and sustainable recovery post the COVID-19 pandemic, we need to draw important observations from the growth experience of the past. In this context, this paper uses a dynamic stochastic general equilibrium (DSGE) model that takes into account persistent growth rate shocks to decompose the Indian GDP into potential output and output gap. Apart from analysing the trajectory of potential output-output gap, it also examines their underlying drivers. The results suggest that a combined deceleration in neutral and investment-specific technology growth post 2016, brought down the potential growth to around 6 per cent in 2020Q1. The output gap also witnessed a persistent decline since 2018Q1, primarily due to weak demand and a rise in investment adjustment costs reflecting heightened stress in the investment and financial sectors. A forecasting exercise is also undertaken which shows that the estimates of output gap from the model possess competing inflation forecasting ability compared to HP filtered output gap.

Goods and Services Tax (GST) Implementation in India: A SAP-LAP-Twitter Analytic Perspective

In a federal structure, India's determination to much-needed fiscal reforms has been widely applauded at its face value when she relinquished her previous complex and inefficient tax regime to embrace the long-awaited Goods and Services Tax (GST). It has been a significant economic move post-independence and requires validation of facts after its introduction. The present study aims to present a general macroeconomic analysis of the extent to which the adoption of GST has improved existing tax administration and resultant general economic well-being of a democratic political economy like India in light of innovation implementation theoretical perspective. Further, the study tried to determine how the stakeholders perceived such big-bang reform even after the three years of its adoption. The study attempted to assess to what extent the adoption of GST has indeed influenced the economy in general and citizens and/or consumers in particular while using a case-based qualitative inquiry. The present research applied the situation-actor-process; learning-action-performance analysis framework for the case analysis. The facts reveal that India has observed a tremendous increase in tax base vis-à-vis revenue collection. Yet, some efforts are desired to improve the low tax to GDP ratio, skewed GST payers base, negative stakeholders' perception of GST (revealed through Twitter sentiment analysis), and the evil of tax evasion. The other merits realized by the economy are presented as benefits to the consumers, MSMEs, improved ease of doing business ranking, and foster make-in-India and AatmanirbharBharat move by the government.

Impact of COVID 19 on Indian Migrant Workers: Decoding Twitter Data by Text Mining

The Coronavirus pandemic has induced a huge economic crisis. The norms of social distancing and consequent lockdown to flatten the curve of this infection has brought economic activity across the globe to a standstill. A mass exodus of workers from major urban centres of India to their native villages started. Mental, financial and emotional agony inflicted due to job-loss, lack of job and livelihood opportunities led to this. A massive macroeconomic crisis for the country with serious ramifications has consequently exploded. The present study explores and captures the diffusion and discovery of information about the various facets of reverse migration in India using Twitter mining. Tweets provide extensive opportunities to extract social perceptions and insights relevant to migration of workers. The massive Twitter data were analysed by applying text mining technique and sentiment analysis. The results of the analysis highlight five major themes. The sentiment analysis confirms the confidence and trust in the minds of masses about tiding through this crisis with government support. The study brings out the major macroeconomic ramifications of this reverse migration. The study's findings indicate that a concentrated joint intervention by the State and Central Governments is critical for successfully tiding through this crisis and restoring normalcy. The subsequent policy measures announced by the government are being critically gauged. In addition, the authors have proposed measures to ameliorate this damage on the formal and informal sectors.

Migrant in my own country: The long march of migrant workers in India during the COVID-19 pandemic 2020-Failure of postcolonial governments to decolonize Bihar and rebuild Indian civilization after 1947

The world is passing through the unprecedented crisis of COVID 19 pandemic. A large section of the global population has been living under mandatory mass quarantine, the lockdown, as a strategy towards slowing down the expansion of the pandemic. This lockdown is being eased out across world in a phase wise manner. India being one of the most populous countries is hardest hit by the pandemic and soon the number of positive cases is likely to touch one million mark. One of the most significant phenomenons observed during the Indian lockdown, has emerged as the long march of migrant workers from cities to their native places. Bihar, one of the Indian provinces is the major provider of migrant labourers for Indian agriculture and the industry sectors. As depicted on social media and television, the plight of migrants was disturbing and exposed modern Indian democracy's vulnerabilities. Many of them had to walk on foot for thousands of kilometers, with their hungry families, from the industrial cities to their native places. Nothing has changed for the migrant workers through the past three centuries, including the first century of postcolonial India. Why are they called migrant workers? Are they not citizens of India? How come being Bihari-a native of Bihar province, one of the primary sources of migrant workers in India, become a stigma? So how did the historical symbol of the most significant accomplishments of Indian history, literature, science, and culture come to be identified with poor migrant workers' image? Bihar's underdevelopment is often blamed on corrupt local politicians and caste politics. However, the history of migrant workers from Bihar and eastern Uttar Pradesh states of India is worth a closer attention for possible solutions. The phenomenon has a historical linkage with the fall of once upon a time the great Indian civilization; centuries of occupation, colonization, slavery, and indentured servitude. India has made steady progress in economic terms since 1947, India's independence from the British empire. The economy's size and rise in gross domestic product (GDP) are meaningless if ordinary citizens continue to be disfranchised, not protected, and liberated from the colonial processes. For India's sovereign economic development, there is no option but to invest in long-term and rebuild the civilization and build a system of the indigenous Indian knowledge economy based on the core principles and values of the Indian civilization.