Indian GDP Research Articles

Bayesian multiple linear regression model for GDP in India

Bayesian multiple linear regression model for GDP in India

Энергетическая политика Индии и сотрудничество с Россией

The relatively high growth rates of GDP and real incomes of the population compared to other Asian countries, combined with the ongoing policy of industrialization and urbanization, make India one of the most attractive markets for commodities. At the same time, India is characterized by extremely low levels of motorization and per capita consumption of many goods and services, including plastic products, which determines the potential for growth in consumption of primary energy sources. Due to the progressive increase in per capita GDP in India, the poverty level is decreasing, stimulating an increase in the number of relatively well-off citizens and, as a result, the consumption of electricity, petroleum products and other energy sources. However, due to the small reserves of fossil resources, India is in dire need of them, mainly oil and gas. Among the key areas of its economy are the oil and gas production and oil and gas processing industries. The subject of the study is India's energy policy, in particular its oil and gas market. The aim of the work is to establish prospects for cooperation between Russia and India due to the fact that the latter is a fast–growing economy and is an expanding market for fossil fuels for the needs of households and industry. The article identifies the peculiarities of the development of the fuel and energy sector of India, and establishes its energy needs. India's energy policy has been reviewed in the light of the implementation of the Paris Climate Agreement, its oil and gas reserves have been identified and directions for possible diversification of their supplies have been predicted. It is concluded that due to the sanctions imposed on Russian companies and the need to diversify the supply of natural resources, foreign economic cooperation with India is of particular interest to Russia.

Sustainability of the Service Sector of India

The paper examined the linear and non-linear trends of the share of the service sector as a percentage of GDP in India during 1960-2021 using the Regression Analysis and the Hamilton Regression Filter Model. It also studied the relationship between the service sector share and FDI, trade, total debt service and Inflation in India during 1970-2021. The paper verified the convergence of net state value added in services of Indian states from 2004/05-2021/22. The paper found a significant upward linear trend, and in nonlinear cases, the share of the services showed cycles, cyclical trends and seasonal variations. The share of the service sector positively affects trade, total debt service, inflation of the economy and FDI. The net state value added in services showed significant Sigma convergence and insignificant Beta convergence from 2004/05- 2021/22.

Jobless Growth: A Study on Unemployment And Real Economic Growth in India

According to the report of IMF survey, now India is the 5th largest Economy in the world overtaking UK in terms of GDP. But the Economic development of a country cannot be determined on the basis of GDP only. Even after becoming the 5th largest economy in the world the rate of Unemployment can Not be reduced, people's standard of living cannot be improved And still the Per Capita Income of India is only $2,500 while that of UK is $47,000. Is this a real economic growth for a nation? Thus, there arise the condition of 'Jobless Growth' in India. According to the report of Jagannathan (2018), every 1% increase in the GDP only rise 0.18% jobs in India. Thus this research paper tries to understand And analyze the condition of Unemployment in India And possible ways to overcome it. This research paper considers income inequality And Corruption as the main factors causing increased rates of Unemployment and other socio-economic problems in India. The contribution of manufacturing sector to the Indian GDP is only 13%. Thus it should be increased by improving the infrastructural facilities And funding. This research stresses the importance of women education And employment for economic development. It also put forward the need for a big revolution in the education sector for producing More skilled students who are the workers of tomorrow. This research highlights some of the positive steps taken by the Union Budget of 2023 (FY2023-24) that could improve employment opportunities in the country. The methodology to be applied for this research article is the study of major world journals and articles. Data interpretation and analysis for such collected data May highlight the real lag in the development of our people.

A Comparative Study on Contribution of Indirect Tax and GST towards GDP of India: An Empirical Analysis

India has adopted a dual GST which is imposed concurrently by the Centre and States, i.e., Centre and States simultaneously collect tax on goods and services. GST extends to whole of India including the State of Jammu and Kashmir. The Implementation of the Goods and Services Tax (GST) in India was a historical move, as it marked a significant indirect tax reform in the country. The amalgamation of large number of taxes (levied at the central and state level) into single tax is expected to have big advantages. The entire process of GST (from registration to filling returns) made online, and it is super simple. This has been made beneficial for start-ups especially, as they do not have to run from pillar to post to get different registrations such as VAT, excise, and service tax. Earlier, there was Central Excise duty and service tax, each of which had their own returns and compliances. This paper is intended to analyze and identify that is there any significant difference between GST Revenue that is collected by the Government post implementation of GST towards GDP when compared to indirect tax revenue.

Post-COVID Recovery and Long-Run Forecasting of Indian GDP with Factor-Augmented Error Correction Model (FECM)

Post-COVID Recovery and Long-Run Forecasting of Indian GDP with Factor-Augmented Error Correction Model (FECM)

India as Growth Pole in South Asia

This paper aims at assessing the spill over effects of Indian economic growth on its regional neighbours, the short run and long run co-movements of Indian GDP, food inflation and overall inflation against the corresponding macroeconomic fundamentals of its regional trading partners are explored. The short- and long-run association between the models variables is investigated by employing modern time-series econometric estimators including Impulse Response Functions (IRFs) and Autoregressive Distributed Lag (ARDL) approach to Cointegration. The results reveal that during short run, South Asian (SA) macroeconomic variables respond significantly towards Indian variables in the event of Indian economy receiving positive exogenous shocks. There is relatively weak evidence in favor of Indian growth spill overs when we test the hypothesis country-by-country, through ARDL model. This lack of support is more visible when SA exports are regressed on Indian GDP. However, for two cases of inflation, one obtains reasonable amount of support. On contrary, the long-run association amongst SA exports and Indian GDP established through two Panel cointegration tests, there is strong support in favor of proposed hypothesis, emphasizing the fact that Indian economic growth bears strong spill over effects in short- as well as in long-run towards its regional trading partners.

Effects of Fiscal Variables on External Sector Deficit of Nepal with Reference to Indian Factors

The basic intent of this paper is to examine the effects of fiscal variables on trade and the current account deficit of Nepal considering the Indian factors. Using the time series data of 48 years of the study period from 1975 to 2022, Engle-Granger’s co-integration and error correction models are used to examine the fiscal effects on the trade deficit, and the ARDL model is used to examine the effects on current account deficit. The basic variables used in the analysis are government expenditure to GDP ratio, budget deficit to GDP ratio, trade deficit to GDP ratio, broad money supply to GDP ratio, trade openness, real exchange rate, and real per-capita Indian GDP. Data are taken from the Ministry of Finance, Nepal Rastra Bank, and World Development Indicators. The findings show that the government expenditure to GDP ratio and trade openness positively affect the trade deficit as domestic factors, while real per-capita Indian GDP positively affects the trade deficit as an external factor. Also, the budget deficit to GDP ratio has a positive effect, while the broad money supply to GDP ratio has a negative effect on the current account deficit as domestic factors. The real exchange rate is negatively and real Indian per-capita GDP are positively driving the Nepal’s current account deficit as external factors. This study identifies the real exchange rate with Indian rupees, Indian real per-capita GDP, and financial development as novel explanatory variables of current account deficit and therefore provides additional evidence on external deficit in the context of Nepal.

An Empirical Investigation of the Impact of Foreign Direct Investment on Indian Economy

The present paper is an attempt to highlight the impacts of FDI inflows to India on Indian GDP. The study is purely based on secondary data which covers 10 financial years (2011-12 to 2021-22), and the analysis of which was made through the application of Karl Pearson’s coefficient of Correlation and Multi Regression OLS model (Ordinary Least Square). The study exhibited a strong positive correlation between foreign direct investment and GDP (r= 0.870) and indicated that FDI is the most important predictor of GDP with R square value of 0.757 which showed that FDI accounts for 75.7 per cent of variations in GDP; and b-value {Unstandardized co-efficient (B=39.679)} indicated that as FDI increases by one unit (1 billion), GDP increases by 39.679 units. It was further indicated through the results that if impact of FDI remain constant, then there are other factors which are explaining GDP up to 28571.885 units.

Trends in CPI and GDP of India

Trends in CPI and GDP of India

The Impact of Crude Oil Price Fluctuations on Indian Economy

Abstract: The importance of Crude Oil has been on a rise in almost every single economy around the world. As economies grow, the requirement of this very vital resource is also fattening at a rapid pace. The Indian economy is rapidly expanding, as is its reliance on crude oil. For the period 2001-02 to 2020-21, the article investigates the reasons for changes in Crude Oil prices, as well as their implications for Indian Economic Development and GDP Growth. Because of the spike in crude prices, India's fuel and diesel prices have reached all-time highs. The current Indian economy is thriving despite rising trade disparities and persistent inflation. The goal of this study is to see how speculation and variations in crude oil prices affect Indian economic development, GDP growth, retail gasoline prices, financial markets (BSE), currency, and government finances. The study looked at how changes in oil prices affect Indian economic development via a variety of networks, including GDP, trade and investment characteristics, and other macroeconomic indicators.

Global trade competitiveness of Indian buffalo meat: Trends and determinants

The study examines the performance of buffalo meat (HS-020230) trade globally and from India, assesses the export competitiveness of buffalo meat export, and identifies the determinants of export growth of buffalo meat from India. The study’s empirical finding reveals that India has approximately 54% of the world’s buffalo population and is one of the major buffalo meat suppliers to the international market. India’s proportion of worldwide buffalo meat exports has increased from 3.34% in 2000 to 11.23% in 2020. During TE 2020, India exported 3052.4 million USD worth of buffalo meat to the rest of the globe, and the single-largest reported destination for India’s buffalo exports was Vietnam, contributing 34% of India’s buffalo meat export. The study determines India’s competitiveness in the buffalo meat sector, and the results showed that China has RCA value greater than one, clearly indicating the strength of India in exporting meat to China. Buffalo population, total livestock population, and GDP of India have been identified as important determinants of the export of buffalo meat from India.

Supply chains create global benefits from improved vaccine accessibility

Ensuring a more equitable distribution of vaccines worldwide is an effective strategy to control global pandemics and support economic recovery. We analyze the socioeconomic effects - defined as health gains, lockdown-easing effect, and supply-chain rebuilding benefit - of a set of idealized COVID-19 vaccine distribution scenarios. We find that an equitable vaccine distribution across the world would increase global economic benefits by 11.7% ($950 billion per year), compared to a scenario focusing on vaccinating the entire population within vaccine-producing countries first and then distributing vaccines to non-vaccine-producing countries. With limited doses among low-income countries, prioritizing the elderly who are at high risk of dying, together with the key front-line workforce who are at high risk of exposure is projected to be economically beneficial (e.g., 0.9%~3.4% annual GDP in India). Our results reveal how equitable distributions would cascade more protection of vaccines to people and ways to improve vaccine equity and accessibility globally through international collaboration.

Unicorn Start-ups in India: A Brief Study

Unprecedented levels of innovation and disruption are taking place today, fuelled by the explosion of start-up businesses that are ready to take on the world with ground-breaking goods, business strategies, and funding. India became the global "software centre" around the turn of the century. It sparked a technological revolution that led to several Indian start-ups developing cutting-edge technology. These start-ups quickly developed into Unicorns in several cases. In terms of the number of unicorns, India is currently third, only after the USA and China. A confluence of factors, such as its enormous market, growing economic position, shifting consumer preferences, and technological capabilities, shapes hyperlocal inventions that are also computationally efficient. We shall briefly explore the "unicorn revolution", the growth of new businesses in India, contribution in employment and GDP of India by Unicorns and the initiatives taken by government for start-ups in this paper.

Impact of Russia-Ukraine War on Sustainable Development Goals: A Study through Indian Financial Market Perspective

This study measures impact of geopolitical crisis concerning Russia Ukraine War with reference to Sustainable development Goal 8. The researchers have analyzed the variables such as Indian stock market performance, MCX crude oil and Indian GDP Indices to calculate the linear interdependencies among crude oil, Indian stock market performance and Gross Domestic Product using monthly data from January 2016 to May 2022 using a Vector Autoregressive (VAR) model. Time series stationarity is checked using Augmented Dickey-Fuller test. The time series used for the analysis are MCX iCOMDEX crude oil Index, Nifty 50 Index, and GDP Index. Correlation is measured using the Granger Causality Test and VAR model. The outcome demonstrates that the lagged values of the Nifty and crude oil prices indexes are very effectively used to explain the GDP Index. Granger’s Causation Matrix shows that past value of NIFTY Index causes change in GDP Index similarly past value of Nifty Index causes change in MCX Crude oil Index, whereas MCX crude oil does not cause much change in GDP Index. Further research could be done using a detailed time series for a longer period to find any impact of crude oil prices on GDP.

IMPACT OF STARTUPS IN INDIAN GDP IN 2022

Indian start-ups have made their mark on the global stage. The ecosystems rapid growth and maturity have unleashed a tremendous appetite for scalability, alternative funding options, global market expansion, and the ability to enable millions of jobs. This meteoric rise of start-ups has made India the worlds third largest start-up ecosystem, and it has had a significant impact on the Indian economy, demonstrating the ability to contribute approximately 4-5 percent of Indias GDP. This report aims to highlight the impact of start-ups on the Indian economy, as well as the ecosystems inherent ability to foster inclusivity, sustainability, and growth. Start-ups do not exist in isolation; rather, they are part of a larger corporate environment dedicated to developing solutions with significant social and economic impact. Because start-ups are incubators for cutting-edge inventions, they create jobs, which means more career opportunities; more employment leads to a stronger economy, and a stronger economy has a direct impact on the growth of cities where start-ups are located. KEYWORDS: GDP- Gross domestic product; Start-ups; Unicorn; Financial benefits; Indian economy; Macroeconomics; Impact on economy; Indian business.

Nowcasting India's Quarterly GDP Growth: A Factor-Augmented Time-Varying Coefficient Regression Model (FA-TVCRM).

Governments, central banks, private firms and others need high frequency information on the state of the economy for their decision making. However, a key indicator like GDP is only available quarterly and that too with a lag. Hence decision makers use high frequency daily, weekly or monthly information to project GDP growth in a given quarter. This method, known as nowcasting, started out in advanced country central banks using bridge models. Nowcasting is now based on more advanced techniques, mostly dynamic factor models. In this paper we use a novel approach, a Factor Augmented Time Varying Coefficient Regression (FA-TVCR) model, which allows us to extract information from a large number of high frequency indicators and at the same time inherently addresses the issue of frequent structural breaks encountered in Indian GDP growth. One specification of the FA-TVCR model is estimated using 19 variables available for a long period starting in 2007-08:Q1. Another specification estimates the model using a larger set of 28 indicators available for a shorter period starting in 2015-16:Q1. Comparing our model with two alternative models, we find that the FA-TVCR model outperforms a Dynamic Factor Model (DFM) model and a univariate Autoregressive Integrated Moving Average (ARIMA) model in terms of both in-sample and out-of-sample Root Mean Square Error(RMSE). Further, comparing the predictive power of the three models using the Diebold-Mariano test, we find that FA-TVCR model outperforms DFM consistently. In terms of out-of-sample forecast accuracy both the FA-TVCR model and the ARIMA model have the same predictive accuracy under normal conditions. However, the FA-TVCR model outperforms the ARIMA model when applied for nowcasting in periods of major shocks like the Covid-19 shock of 2020-21.

Measurement of the contribution of financial factors to GDP: Evidence from India

To measures the contribution of various indicators of financial market and financial institution to GDP in India for the period of 2000 to 2020. This research measures the contribution with the help of augmented dickey fuller (ADF) test, cointegration test and vector error correction model (VECM). Given results suggest that financial factors are having major effect on GDP in long-run. Indicators of financial market and financial institutions has a contribution in the growth of GDP. Following research measuring the contribution of various factors on GDP. Up to what extent each indicator contributes in the growth of GDP in India. Prior studies emphasized the consequences of financial issues together on the expansion of the economy.

IMPACT OF GOVERNMENT EXPENDITURE, UNEMPLOYMENT, INFLATION AND HOUSEHOLDS CONSUMPTION ON ECONOMIC GROWTH IN INDIA

The impact of government expenditure, unemployment, inflation, and household consumption on the economic growth of India over the period 1990-2021 has been examined in this paper. The ordinary least squares (OLS) regression analysis was performed by observing the assumptions of the classical linear model. Augmented Dickey-Fuller (ADF) and Philips-Perron (PP) tests were carried out for stationarity of the concerned variables. The study found that increasing government expenditure has a strong positive influence on the growth of national income and consumption and a negative influence on unemployment in India. The study recommends increasing government expenditure that could accelerate economic growth and create employment opportunities that also have a positive impact on improving consumption. Results indicate that inflation significantly depresses economic performance in India because of uncertainty and reduces investment, employment, and consequently output and consumption level. Unemployment has not significantly impacted the real GDP in India. Investment in physical capital and human capital has significantly promoted economic performance in India because investment in human capital improves the productivity of the labor forces and hence increases output and investment in physical capital increases the amount of capital per unit of labor and these have the potency of increasing productivity per worker. The overall effect is the increase in output and therefore economic performance. The study recommends increasing government expenditure as it boosts aggregate demand which could accelerate economic growth and create employment opportunities and enhance the consumption level of the public.

Machine Learning-Based Electricity Load Forecast for the Agriculture Sector

A large section of the population has a source of income from the agriculture sector, but their share in the Indian GDP is low. Thus, there is a need to forecast energy to improve and increase productivity. The main sources of energy in agriculture are electricity, coal, and diesel. Among them, electricity plays an important role in land irrigation. Power forecasting is also essential for demand response management. Thus, any process that dissolves future consumption is favorable. This article presents a time series-based technique for forecasting medium-term load in agriculture. The aim is to find the peak periods of power consumption by months and seasons using statistical and machine learning-based techniques. The result shows that SARIMA has lower RMSE and exponential smoothing has lower RMSPE error than random forest and LSTM, which makes the statistical approach more efficient than intelligent approach for historical datasets. The season-wise peak demand occurs during the Rabi season. Finally, five-year ahead load in the agriculture sector was determined using the best models.