Search

This paper examines the association between financial inclusion and economic growth in the context of the Indian economy. The Auto Regressive Distributive Lag (ARDL), Error Correction Mechanism (ECM), and impulse response function have been used for establishing the association between the two. Using panel data regression over the time period 2001 to 2019, the paper shows that there exists a positive, bidirectional association between financial inclusion and economic growth in the long run. However, there is a unidirectional relationship in the short run, i.e., only economic growth is the precondition for financial inclusion. Therefore, in the long run, economic growth helps to remove demand and supply side obstacles while financial inclusion reduces poverty and inequality, and hence promotes inclusive growth. [ABSTRACT FROM AUTHOR]

Purpose: Market efficiency leads to transparent and fair price discovery of commodity markets, thus enhancing the value chain for competitive benefit. The purpose of this paper is to investigate the market efficiency of Indian agricultural commodities at spot, futures and mandi markets apart from exploring price risk management in these markets. Design/methodology/approach: This study uses Johansen co-integration, vector error correction model and granger causality for analyzing market efficiency of the nine most liquid agricultural commodities across three markets, namely, spot, futures and mandi. All these nine commodities are traded on National Commodity and Derivatives Exchange. Findings: The statistical results indicate price discovery exists in the mandi market and spot market leading to futures prices. Mandi price returns are seen to negatively influence futures returns in the case of cotton seed, guar seed and spot returns in the case of jeera, coriander and chana. For castor seed, the three markets are seen to have no long run relationship. The results of Granger causality reveal short run relationship between all the three markets in the case of soybean seed and coriander. In these commodities, prices in all three markets are capable of predicting the prices in the other markets. For the case of cottonseed, Rape Mustard seed, jeera, guar seed, the results indicate unidirectional causality between the mandi markets and the other two markets. Research limitations/implications: These results shall facilitate policymakers to explore intervention through integrated agri-platform (IAP) in price discovery and market efficiency. Practical implications: The results of this study are useful in understanding the price discovery of mandi markets and its role in the spot and futures market. Agricultural commodities price discovery depends upon the integration of all these three markets. Introduction of IAP as described in the paper shall facilitate price risk management apart from improving the efficiency of price discovery. Originality/value: To the best of the knowledge, this is the first study considering mandi, spot and futures prices in the price discovery process in India. In addition, this study found the role of mandi markets in serving the economic function of price discovery and price risk management. Hence, suggests for policy intervention for Indian agricultural commodities to manage price risk. [ABSTRACT FROM AUTHOR]

The relationship between foreign direct investment and domestic investment is intriguing. An important question arises - does foreign direct investment crowd in or crowd out domestic investment? This paper examines this nexus in the post-1991 period in India, which is also considered as the post-reform period. It is during this era; the above-mentioned topic gains more impetus as the economy opened up for further foreign inflows. The time period taken for the paper was from 1990-91 to 2014-15. The data series were checked for stationarity and the presence of long run relationship between foreign direct investment and domestic investment was analysed using cointegration test. Thereafter, the vector error correction model was estimated. The results clearly show that foreign direct investment crowds out domestic investment in India in the post reform period. The findings have significant policy implications because there is a substituting relationship between foreign direct investment and domestic investment in India. [ABSTRACT FROM AUTHOR]

This paper uses cointegrated error-correction modeling to investigate the nature of Granger causality between corruption and foreign direct investment (FDI) in two rapidly emerging economic superpowers; namely, China and India. The results for China and India indicate that short-run Granger causality unidirectionally runs from FDI to corruption without feedback. These empirical findings (along with supporting theoretical arguments) dispute prior correlational-based studies which claim that corruption instigates changes in FDI. However, our results further support significant long-run causality running from corruption to FDI inflows, but only in India (not in China). This finding reinforces theoretical propositions of lower corruption arbitrariness in China as compared to India. Furthermore, short- and long-run causality between corruption and FDI in India appear dynamic in nature and time-sensitive implying some difficulties for policymakers in their fight against corruption. The paper discusses possible underlying reasons for the empirical results and draws several policy and Asian business implications. [ABSTRACT FROM AUTHOR]

The nexus of remittances and CO2 emission is very important and gathers a significant place in empirical research. This paper tries to find out the asymmetric relationship between carbon emissions, remittances, and financial development in India for the period 1980–2014. Based on the theoretical linkages, we develop a nonlinear ARDL model with the use of time series data in this study. The results of the NARDL bound test suggest that there is long-run cointegration among the variables. The findings show that positive shock in remittances causes an increase in CO2 emissions, where negative shock reduces it. The coefficient for financial development is positive but becomes statistically insignificant. Empirical results also support the existence of asymmetric long-run relationship among the variables. Based on the findings, the paper recommends the proper channelization of remittances and financial development towards environment-friendly energy sources and projects without compromising economic growth. [ABSTRACT FROM AUTHOR]

India's youth unemployment rose from 15.5% in 1991 to 23% in 2019. This period also witnessed a declining trend in India's youth to working-age population ratio from 33% to 27%. These statistics are aligned with the existing studies which postulate that if the working-age segment has a large proportion of youth in the age group of 15 to 24 years, it will lead to a high unemployment rate. Given such a context, this paper aims to examine and estimate the demographic, monetary and macroeconomic factors influencing India's rising youth unemployment, with the help of Autoregressive Distributed Lag (ARDL) approach to cointegration. This study also brings in a new dimension to the existing studies by providing an in-depth analysis of the role of millennials cohort, which entered the working-age segment in 1995, in contributing to India's rising youth unemployment. A disaggregated analysis of India's youth unemployment based on the criteria of education and gender has also been carried out. [ABSTRACT FROM AUTHOR]

This paper exploits the regime-switching threshold cointegration approach to elicit the dynamics in the saving-investment relationship and capital mobility in India. Empirical results offer key insights into the threshold cointegration between the saving and investment rates. We find that the adjustment in investment rate in the upper regime is faster than in the lower regime, indicating the higher mobility of capital in the upper regime. Further, results reveal the absence of firm evidence of long-run vs. short-run asymmetries between saving and investment rates. However, results suggest that cumulative positive and negative sums of saving rates affect investment rates. We have made adjustments to cyclical and trend patterns in our data using Hamilton's (2018) filter and have produced robust results with regard to asymmetric cointegration. The posterior estimation results suggest that a downward trend in the saving rates substantially impacts the investment rates, and widening the gap between saving and investment rates facilitates huge mobility of international capital in the long run. [ABSTRACT FROM AUTHOR]

Using annual time series data for India, this research paper examines the presence of asymmetric cointegration and asymmetric causality between financial development and poverty reduction using nonlinear autoregressive distributed lag (NARDL) model and asymmetric causality test. The empirical findings support the existence of asymmetries in the short-run as well as long-run between poverty and financial development. The asymmetry reveals that negative financial development shocks leave a more profound impact on poverty alleviation than their positive equivalents. The result emanating from asymmetric causality test reveal a unidirectional asymmetric causality between negative shocks in financial development and poverty. Moreover, expansionary policies of financial development are found to serve as catalysts to spur poverty alleviation while contractionary policies of financial sector are found to exacerbate poverty in an asymmetric and nonlinear fashion. The findings of Wald's test also confirm the presence of asymmetric effects in the poverty-finance nexus. The asymmetric cumulative dynamic multipliers used to examine the behaviour of asymmetries and adjustments with respect to time lend credence to the results calculated using NARDL estimator and therefore demonstrate their robustness. The present study divulges the need for investigating asymmetry in finance-poverty nexus in order to draw policy-relevant conclusions. The authors conclude that financial development serves as a panacea and antidote to the scourge of extreme poverty in India. We recommend regulation of informal sources of credit, financial inclusion of poor, credit boost to small and medium enterprises employing rural poor and channelization of credit to productive sectors with high employment elasticity to be persistently encouraged for poverty alleviation in India. [ABSTRACT FROM AUTHOR]

Covid-19 pandemic has adversely affected the different industrial sectors of Indian economy. It has thus adversely disturbed the parameters of the sustainable development in this country. This paper shows how different macroeconomic sectors of India have reacted to the adverse impact in the Indian Economy differently. Some sectors are highly affected while some sectors are not appreciably affected by the pandemic. Few major sectors have been affected badly by the pandemic. For example the highest impact on industrial growth during the pandemic has been assessed for the sectors like, mining -26.9%, manufacturing -66.6%, infrastructure -37.9%, steel - 65.2%, cement - 40%, crude oil -5.22% etc. I have studied in this paper the impact of Covid-19 pandemic on different sectors and got different findings for different sectors. The study involved with the Cointegration and Vector Error Correction Estimation of Time Series Econometrics. It may be noted that the pandemic has been going on for one and half year and therefore it is expected to be a transitory phenomenon. We, therefore, cannot expect a very long run relationship between pandemic and other sectors of the economy. That's why, the Cointegration study has been indirectly established through the estimation of Vector Error Correction model. In the estimated VEC model it has been found that there is a strong relation between changes in macroeconomic parameters and the pandemic in the short run. I have found that the growth rate in manufacture, infrastructure and mining etc have been affected adversely by the pandemic. Growth rate of different sectors have been significantly related to the 1st and 2nd lag variation of the Covid-19 dataset. The Covid-19 dataset have been found to exert negative impact on the sectors under study. [ABSTRACT FROM AUTHOR]

The paper is an attempt to evaluate the direction of price discovery and hedging effectiveness of zinc futures traded at MCX, India. The period for the study is chosen for seven years, i.e., 2013 to 2020. The influential direction between the spot and futures for price discovery has remained an important phenomenon in commodity futures research. The results confirm that there exists unidirectional causality between the spot and futures market of zinc. In the long-run spot influences futures for price discovery and conversely, the futures market influences price discovery of the spot in the short run. The zinc futures market also indicate a lack of hedging effectiveness. As the results are based on only one base metal and the period is limited to seven years, it can be extended and expanded for further research. Moreover, future research can evaluate the cross-hedging strategies of the zinc futures market. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to investigate price responses and volatility spillovers between commodity spot and futures markets. The study ultimately seeks the evidence-based claims on the efficiency of the long run and short run horizontal price transmissions from futures markets to spot markets. Design/methodology/approach: This study used the most recent daily price series of pepper, cardamom and rubber, during the period 2004–2019, use "cointegration-ECM-GARCH framework" and verify the persisting validity of the "expectancy theory" of commodity futures pricing. Findings: The results offer overwhelming evidence of futures market dominance in the price discoveries and volatility spillovers in spot markets. However, this paper finds asymmetric responses between cash and futures prices across markets. The hedging efficiency of futures contracts is commodities specific' where spices futures are more efficient than the rubber futures. Practical implications: The study passes on vital information to the producers and traders of spices and rubber who have a potential interest in the use of futures contracts to make profits from arbitrage between futures and cash markets. Originality/value: The paper is unique in terms of understanding asymmetric price linkages in markets for plantation crops. [ABSTRACT FROM AUTHOR]

This paper examines the sustainability of the current account deficit (CAD) and validity of the intertemporal budget constraint of India for the period of 1980 to 2019. The cointegration results show that exports and imports are not cointegrated and the current account (CA) series is not mean reverting during the study period. Therefore, the results refute the sustainability of CAD and the validity of the intertemporal budget constraint in the Indian context. Furthermore, the study also emphasised the testing of the disaggregated CA and found that while the goods account is not sustainable, the services account found to be sustainable in the long run. Our findings thus indicate the potential for aggregation bias to have an impact on the overall CA sustainability results. Therefore, policies that help in achieving self‐sufficiency on the one hand and export promotion in goods on the other may eventually contribute to CA sustainability. [ABSTRACT FROM AUTHOR]

This paper intends to study and highlight the change in behavior of volatility of Indian stock market on the introduction of derivatives as a financial instrument, the announcement of union budget every year and the Lok Sabha (lower house of the Indian parliament) elections conducted during 1994-2012. Applying cointegration test between the S&P CNX Nifty and the FUTIDX index, it has been noticed that spot and futures markets are cointegrated with each other. Applying a dummy variable, TGARCH model, this paper aims to examine the impact of the above factors on the volatility of Nifty during the year 1994-2012. [ABSTRACT FROM AUTHOR]

This paper scrutinizes the relationship between gross domestic saving, gross capital formation and economic growth in India during a period from 1992 to 2018. The results of cointegration analysis reveal that there is a long-run relationship between selected variables; however, the observations from the results of the Granger causality test indicate a positive relationship between saving, investment and economic growth in India. The findings explicate that saving and investment directed growth is coming from the private sector. [ABSTRACT FROM AUTHOR]

This paper investigates the long-run and short-run impacts of government spending on inflation in three Asian emerging economies of India, China and Indonesia by applying the cointegration and Vector Error Correction Model to time series data from 1970 to 2010. The results confirm a cointegrating causal link between government spending and inflation in the long run in these countries, regardless of their institutional governance differences. In the short run, government spending (as a percentage of GDP) appears to have a negative impact on inflation in China, while a positive impact in Indonesia and India. The implication is that governments of emerging economies should be prudent with their decisions on government spending. [ABSTRACT FROM AUTHOR]

The attempt of this paper is to find an empirical relationship between Foreign Direct Investment and New Firms (Paid up Capital) and Gross Capital Formation (proxy for business growth) and Credit to Commercial Sector and Gross Capital Formation using the test of stationarity (ADF, PP, and KPSS methods), Johansen Cointegration and Granger's Causality. The results show that FDI crowds out creation of new firms and capital formation and it is the Credit flow to the commercial sector that causes Gross Capital Formation at current price. It shows domestic flow of credit is more influential in capital formation rather than foreign capital inflow. [ABSTRACT FROM AUTHOR]

Migration and remittances have always been an exciting arena of research for economists around the globe. Remittance flows have evolved as a significant economic variable over the past decade. In several developing countries, remittances exceed the other capital inflows and value of total exports. Thus, it is widely recognised as a potential funding source for economic development in emerging economies. The inflow of remittances to India has increased tremendously in the recent past making the country the highest recipient of remittances across the globe. Remittances are an essential component that contributes to narrowing the Current Account Deficit and has always been a stable constituent of the Balance of Payment. This paper is an attempt to explore the vital macroeconomic variables which determine the remittance flows to India. Notably, we enquire into the dominant motives of remittances in the Indian context. We employ an ARDL approach to cointegration to identify the macroeconomic determinants of remittances and find those crucial variables such as exchange rate, oil price, and domestic GDP substantially impact the flow of remittances. The results also indicate that the migrants are more vulnerable to the oil price shocks in host countries. The overall findings of our study are that (1) remittances are not countercyclical in the Indian context (2) remittances are subject to weak investment motive as opposed to the altruistic motive. [ABSTRACT FROM AUTHOR]

Technological advancements have been the driving factor responsible for the structural composition of the financial markets and the development of digital financial technologies. The widespread use of information and communication technology (ICT) and artificial intelligence in the operation of the global financial sector is the hallmark of this development. Access to and usage of financial services have changed significantly due to this revolution and, more recently, the pandemic, which embraced digital solutions. Digitization of the economy promotes economic growth through inclusivity, efficiency, and innovation. The availability of electronic payment systems triggers a positive economic impact through rising consumption and production, thereby creating more employment and income and, in turn, strengthening economic growth. It benefits consumers and merchants as these payment methods are safer and more efficient, convenient, transparent, and affordable. Many empirical studies support the idea that digital financial development is crucial for enhancing efficiency and productivity and promoting a country's economic growth. The study explores the relationship between gross value added, credit transfer, debit transfer, card payment, and prepaid instruments in India taking quarterly data from 2011 to 2019 and using the Autoregressive Distributive Lag (ARDL) model. The study reports a cointegrating relationship between the variables and discusses the implications of this relationship. [ABSTRACT FROM AUTHOR]

The paper assesses the long-run relationship between India's exports and imports with its 21 major trading partners using bootstrap autoregressive distributed lag bounds test procedure with a Fourier function. The study uses monthly data for the period 2014 (Month 01) to 2020 (Month 02). The empirical results show cointegration for 6 countries if imports are used as the dependent variable but not when exports are used as a dependent variable. However, for the remaining countries, no cointegration between exports and imports was found. This indicates that India's efforts to reduce its bilateral imbalances through trade policies with these countries may not be appropriately targeted. Having established a long-run relationship, the study estimates a disaggregated bilateral import demand function by employing a linear and nonlinear autoregressive distributed lag model to investigate the asymmetric impact of the relative price changes on the import demand of India with her trading partners. Marshall–Lerner condition is satisfied for India's trade with Kuwait and Germany in case of linear autoregressive distributed lag model and with Qatar, Kuwait and Germany in case of nonlinear autoregressive distributed lag model. Cumulative asymmetries are established for Indo-Kuwait trade. [ABSTRACT FROM AUTHOR]

This paper investigates the association among energy consumption, carbon‐dioxide emission, and India's economic growth along with supplemental variables including foreign direct investment, population density, inflation, and agricultural land. An autoregressive distributive lag model is applied over annual time‐series data from 1985 to 2019. Further, the robustness and novelty of the model are confirmed by applying fully modified ordinary‐least‐square, dynamic ordinary‐least‐square, canonical co‐integrating regression, variance decomposition, and impulse response function. The analysis results indicate that a cointegration association exists among variables. In the short run, the profound determinants of economic development are energy consumption, carbon‐dioxide emission, inflation, and agricultural land. In the long run, both inflation and agricultural land significantly negatively influence economic growth while carbon emission drives a positive impact. Interestingly, a one‐way Granger causality runs from economic growth towards energy consumption, carbon emission, and agricultural land. The new research presents a comprehensive understanding of economic growth indicators, aiding policymakers, and advancing existing literature. Consequently, as a recommendation, the policymakers should constitute explicit goals for renewable energy consumption to stimulate sustainable economic growth with carbon emission reduction. [ABSTRACT FROM AUTHOR]

This paper investigates the volatility persistence in sovereign bond yields of India and China during study period of 2010–2018. For that purpose, the researcher has applied the Engle and Lee (in: Engle and Lee (eds) Cointegration, causality, and forecasting: a Festschrift in honour of Clive WJ Granger, Oxford University Press, Oxford, pp 475–497, 1999) C-GARCH model to decompose the volatility of 10-year sovereign bond yields of India and China into permanent and transitory components. The results reveal that permanent conditional volatility shows long memory with long-run component's half-life decay ranges from 91 to 97 days for India and China, respectively. However, the temporary component of volatility much smaller with short-run component's half-life decay ranges from.70 to.75 for India and China, respectively. [ABSTRACT FROM AUTHOR]

The main purpose of the paper is to investigate whether and to what extent the Bombay Stock Exchange (BSE), India is integrated with the major mature markets in the US, UK, Germany and Japan. The dataset has been divided into: post Asian Crisis but before Euro Emerged (July 1997-January 2002); after Euro but before US Subprime Crisis (February 2002-November 2007); from the US Subprime Crisis before Modi's emergence as national leader (December 2007-April 2014); and after Modi's emergence (May 2014-July 2016). The study uses unit root test, Johansen-Juselius test, GARCH(p, q) model estimation, and Granger causality test for the purpose. [ABSTRACT FROM AUTHOR]

This paper examines the dynamic relationship between inflation and openness from 1970 to 2014 in the Indian context. In the first of its kind, this paper investigates the relationship within a nonlinear framework by employing NARDL cointegration test due to Shin, Yu, and Greenwood Nimmo (2014). The empirical results show that there is asymmetry in the relationship between openness and inflation both in short-run as well as in long-run. However, overall a positive relation (though weak) holds between inflation and openness and hence refutes well known Romer (1993) hypothesis that inflation falls with openness. The results further showed a positive relation between inflation and other variables in the study. The overall response of inflation towards the positive and negative changes in explanatory variables differed significantly. [ABSTRACT FROM PUBLISHER]

The purpose of this study is to explore the nature of the association and the possible existence of a shortrun and long-run relationship between the stock-market indices of South Africa, India and the USA. The idea behind this combination is to know how the stock markets of these three prominent countries are related to each other. The study employs monthly data from the stock indices, namely JALSH (South Africa), NIFTY (India) and NASDAQ (USA) composite from April 2004 to March 2014. After testing for the normality of the data distribution and the stationarity of the time series data, this paper discovered a strong correlation between the stock market indices of South Africa, India and the USA. The correlation among the stock markets is high, particularly between South Africa and India. In addition, the paper attempts to discover the presence of any predictive ability among these markets by applying the Granger causality test. The result indicates that the NASDAQ index has no predictive ability as far as the JALSH and NIFTY indices are concerned. However, the JALSH index has a predictive ability on the NIFTY index. After testing the Granger cause relationship, the existence of a long-run and short-run relationship is tested. The long-run relationships among the stock market indices are analysed, following the Johansen and Juselius multivariate cointegration approach. The result suggests the absence of a long-run relationship among the three stock market indices. Short-run relationship is investigated with the Vector Autoregression (VAR) model, and the outcome obtained shows that both the USA and the South African stock markets are predicted only by their own past lags. However, the Indian stock market is seen to be a function of its own past lags and the past lags of the South African stock index. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to examine the impact of female human capital on economic growth in the Indian economy during 1970-2014.Design/methodology/approach The paper employs Ng-Perron unit root test to check the order of integration of the variables. The study also used ARDL-bounds testing approach and the unrestricted error-correction model to investigate co-integration in the long run and short run; Granger’s causality test to investigate the direction of the causality; and variance decomposition test to capture the influence of each variable on economic growth.Findings The study constructed a composite index for both male and female human capitals by taking education and health as a proxy for human capital. The empirical findings reveal that female human capital is significant and positively related to economic growth in both short run and long run, while male human capital is positive but insignificant to the economic growth; same is the case for physical capital, it implies that such investment regarding female human capital needs to be reinforced. Further, there is an evidence of a long-run causal relationship from female human capital, male human capital and physical capital to economic growth variable. The results of variance decomposition show the importance of the female human capital variable is increasing over the time and it exerts the largest influence in change in economic growth.Research limitations/implications The empirical findings suggest that the Indian economy has to pay attention equally on the development of female human capital for short-run as well as long-run growth of the economy. This implies that the policy makers should divert more expenditure for developing support for female education and health.Originality/value To the best of authors’ knowledge, this is the first attempt to study the relationship between female human capital and economic growth in the context of the Indian economy. [ABSTRACT FROM AUTHOR]

This paper investigates the relationship between financial development and access to electricity for rural and urban India by incorporating economic growth, trade, and foreign direct investment in energy production function. In doing so, we have applied autoregressive distributed lag bounds testing to examine long run cointegration between the variables by accommodating structural break(s) stemming in the series. Our empirical results indicate the presence of cointegration association between access to electricity and its determinants. We note that financial development enhances access to electricity in rural India but declines it in urban India. Economic growth has positive effect on access to electricity. Trade openness and foreign direct investment lower access to electricity in rural India. In urban India, trade openness and foreign direct investment increase access to electricity. The association between financial development and access to electricity is inverted-U shaped for rural and urban India. This paper would present new policy direction for Indian government to enhance access to electricity by using financial development as an economic tool. • Financial development and access to electricity have a strong linkage. • In India financial development enhances access to electricity in rural area but has adverse effect in urban area. • Rise in economic growth of India has increased the access to electricity. • Growth of Trade Openness and Foreign Direct investment increase access to electricity. [ABSTRACT FROM AUTHOR]

The paper explores the relationship between Central bank independence (CBI) and fiscal deficit in India. Moreover, the study tries to assess the impact of CBI on the levels of fiscal deficit. The study incorporates other variables like Gross Domestic Product, financial development, and trade openness to analyze their impact on the fiscal deficit. The study employed Auto-regressive distributed lag model (ARDL) Bounds test developed by Pesaran, Shin, and Smith (2001) to examine the long-run relationship between CBI and fiscal deficit. The study also employs a legal index for measuring CBI developed by Jasmine et al (2019) as well as an actual measure of independence developed by Cukierman (1992) to measure CBI in India. The study confirms the long-run relationship between the CBI and fiscal deficit as well as among other variables. An increase in the levels of CBI leads to falling in the levels of fiscal deficit. The other explanatory variables used in the study also confirm the long-run relationship and impact fiscal deficit negatively except for trade openness, which positively impacts the fiscal deficit. [ABSTRACT FROM AUTHOR]

This paper tries to trace the relationship between finance and growth. There are several indicators which represent the degree of financial intermediation such as M3, Real Rate of Interest (RR) and economic growth. In this paper, we have used Time-series methodology such as Unit Root (ADF and Phillips-Perron Tests), Cointegration (developed by Johansen and Juselius), and Granger Pairwise causality. We have checked the presence of unit roots in the data, and all the three variables-Financial Development, RR and Growth Rate-are found to be integrated at first difference. Secondly, Johansen cointegration test results confirm the presence of long-run equilibrium relationship among the variables. Finally, the Granger causality supports the hypothesis of 'Finance-led Growth' indicating that the finance is a leading sector in India and is poised for development. This result supports the supply-leading hypothesis for Indian economy for the sample period. These findings have important implications for the conduct of economic policies in India. [ABSTRACT FROM AUTHOR]

The objective of this paper is to determine the relationship between inflation rate and stock price indices (NSE Nifty). The duration of the study is from January 1, 2008 to March 31, 2019. The data is analyzed for cointegration and causality by using Johansen cointegration test, Vector Error Correction Model (VECM) and Granger causality test. For determining the relationship between the variables, Pearson correlation test has been used. The ADF test results show that the variables are non-stationary at level and are integrated of order one. The correlation results show a negative relationship between stock market indices and inflation rate in India. Johansen cointegration test results indicate cointegration between the variables. The Granger causality test shows that inflation rate does not affect the stock market indices, and stock market indices are not affected by the inflation rate. The VECM model and Wald test results show that there is no long run and short run causality between the variables. [ABSTRACT FROM AUTHOR]

Copyright of Industria Textila is the property of Institutul National de Cercetare-Dezvoltare pentru Textile si Pielarie and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper examines the impact of tax reform on the economic growth of India over the period 1975–2017. In order to measure the impact of tax reform on the economic growth, we have used various econometric tools like Maki and combined cointegration tests and the rolling-window causality test in this study. The study revealed that a stable long-run parameter stability relationship exists the series on tax reform but unable to obtain the short-run relationship. Results also revealed that growth-led taxation effects and tax-led-growth do not exist in India. Hence, India needs more policies which will help to remove inefficiencies created by the existing heterogeneous taxation system, revenue rate and inclusion of petroleum products, electricity, liquor and real estate and policymakers should adopt some policies for direct tax which reduce the imbalance in class. [ABSTRACT FROM AUTHOR]

Estimating the demand for money in an economy and understanding its relationship with various macroeconomic variables is an essential element in the planning of the issue and distribution of currency (Nachane et al., 2013). The penetration of several innovative instruments in the financial sector has changed the behavior and relationship of demand for money. Understanding the significance of estimating money demand function in this evolving financial innovation era, this paper attempts to analyze the major determinants of demand for money via M1 for India for the period 2005-06 to 2014-15. The demand for M1 was estimated applying the Johansen's Cointegration Technique and the estimated results revealed that there existed long run relationship among the explanatory variables of the function, with specific reference to debit cards that form the major substitute for cash in the country. The findings suggests that the financial innovations in the banking sector have influenced the demand for money, specifically M1, indicating that the transaction demand for money in India is influenced by the innovations. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to investigate the linkages between Indian stock markets with other Asian stock markets namely, Hong Kong, Indonesia, Japan, South Korea, Malaysia, Taiwan and China. Such a study is particularly important because if the level of integration among the markets is high, then investing in different markets will not generate long term gains from portfolio diversification or reduction in risk. Design/methodology/approach – The paper applies unit root test in the presence of endogenous structural breaks that uses a Lagrange Multiplier (LM) test statistics and the Gregory and Hansen cointegration technique that allows for endogenous determined structural break in the relationship have been applied. Findings – The results suggest that the Indian stock markets are not integrated with any of the Asian markets either individually or collectively, and conclude that Indian markets are not sensitive to the dynamics in these markets in the long run. Originality/value – Since the level of integration has been studied keeping in mind the different economical phases like recession and boom, the study has incorporated the possibility of existence of structural breaks in the individual stock return series as well as in their relationship. The lack of evidence on interlinkage of Indian stock markets with other Asian markets suggests that the trend of Indian markets is not in sync with other markets, possibly due to difference in macroeconomic structure. Since the level of integration has been studied keeping in mind the different economical phases like recession and boom, the study has incorporated the possibility of existence of structural breaks in the individual stock return series as well as in their relationship. The lack of evidence on interlinkage of Indian stock markets with other Asian markets suggest that the trend of Indian markets is not in sync with other markets, possibly due to difference in macroeconomic structure. [ABSTRACT FROM AUTHOR]

The paper investigates the determinants of long run finance development in India over the period of April 1994 to April 2011. The investigation is carried out by unit root, cointegration, ARDL bound test approach and VECM. The ARDL finds the existence of long run equilibrium relationship between finance development and economic growth. The VECM confirms the existence of bidirectional causality between finance development and economic growth. It also confirms the existence of unidirectional causality from stock market development to economic growth and from finance development to inflation. The paper at the end suggests that financial development should be considered as the policy variable to enhance economic growth in the Indian economy, especially during the globalization era of 1990s. [ABSTRACT FROM AUTHOR]

This paper investigates whether the commodities market in India follows the random walk process and whether they deviate from the random walk theory (mean reversion). Daily log returns of commodity future index (MCXCOMDEX) and three sectoral indices are examined using the Augmented Dickey-Fuller test (ADF), GARCH, and E-GARCH model to test the random walk theory. This study confirms the existence of random walk for commodity index prices over the period January 2009 to December 2020. ADF test is used for investigating random walk behaviour. From the ADF test we conclude that the series has unit root problem and the index series is nonstationary. The results clearly show that the data is non-stationary possessing a unit root. The GARCH model was used to cater for volatility clustering, which is more pronounced in commodity prices. From the results obtained, it is observed that futures prices are showing volatility clustering and non-stationarity behaviour, which is in line with our research objective of finding the random walk in commodity index; there is a positive result of the existence of random walk. [ABSTRACT FROM AUTHOR]

This study investigates the nexus between India's current and capital accounts using threshold cointegration and asymmetric error-correction approaches. The results validate the threshold cointegration between the current account (CA) and India's capital account (KA). The asymmetric error correction-based results support the unidirectional Granger causality from KA to CA. Further, results reveal that KA's cumulative sum of positive and negative deviation substantially impacts the CA. Finally, results of equilibrium adjustment path asymmetric effect from CA to KA suggest that KA reverts to equilibrium in the short run when CA decreases. [ABSTRACT FROM AUTHOR]

The objective of this paper is to explore the nexus of innovation–environment and economic growth in the context of the Indian economy. To achieve the study objective, we explored the role of technological innovation, FDI, trade openness, energy use, and economic growth toward carbon emissions. Using the data of 1985–2017, the study employed ARDL bound testing and vector error correction model (VECM) methods to capture the effects of technological innovation, trade openness, FDI, energy use, and economic growth on CO2 emissions. Empirical estimation has confirmed the existence of long-run cointegration. Similarly, in the long run, it is found that trade openness, energy use, and economic growth positively reinforce CO2 emissions. In contrast, technological innovation and FDI negatively reinforce CO2 emissions in the long run. Furthermore, VECM indicates that the relationship among innovation, trade openness, and energy use is bidirectional in the long run. Whereas, unidirectional relation has been found that is coming from GDP to carbon emissions, FDI, innovation, trade, and energy use. In the short run, unidirectional link found which is coming from FDI, innovation, and energy use to carbon emission. However, the association between emissions and trade openness is bidirectional. The conclusions put forward policy implications that innovation is a way to reduce environmental degradation. [ABSTRACT FROM AUTHOR]

Purpose: Price discovery and spillover effect are prominent indicators in the commodity futures market to protect the interest of consumers, farmers and to hedge sharp price fluctuations. The purpose of this paper is to investigate empirically the price discovery and volatility spillover in Indian agriculture spot and futures commodity markets. Design/methodology/approach: This study uses Granger causality, vector error correction model (VECM) and exponential generalized autoregressive conditional heteroskedasticity (EGARCH) to examines the price discovery and spillover effects for nine most liquid agricultural commodities in spot and futures markets traded on National Commodity and Derivatives Exchange (NCDEX). Findings: The VECM results show that price discovery exists in all the nine commodities with futures market leading the spot in case of six commodities, namely soybean seed, coriander, turmeric, castor seed, guar seed and chana. Whereas in case of three commodities (cotton seed, rape mustard seed and jeera), price discovery takes place in the spot market. The Granger causality tests indicate that futures markets have stronger ability to predict spot prices. Supporting these, the results from EGARCH volatility test reveal that there exist mutual spillover effects on futures and spot markets. Thus, it could be inferred that futures market is more efficient in price discovery of agricultural commodities in India. Research limitations/implications: These results can help the market participants to benefit by hedging out the uncertainty and the policymakers to design futures contracts to improve the efficiency of the agricultural commodity derivatives market. Practical implications: The findings provide fresh view on lead–lag relationship between future and spot prices using the latest data confirming that futures market indeed is dominant in price discovery. Originality/value: There are very few studies that have explored the efficiency of the agricultural commodity spot and futures markets in India using both price discovery and volatility spillover in a detailed manner, especially at the individual agriculture commodity level. [ABSTRACT FROM AUTHOR]

This paper investigates the long-run equilibrium relationship between economic growth and trade openness in India during the period 1960–2018 using the asymmetric error-correction model with threshold cointegration. To evaluate the robustness impact of trade openness on economic growth under different regimes, we divide the full sample period into two sub-periods, i.e., pre-trade reforms period 1960–1990, and post-trade reforms period 1991–2018. The study indeed confirms the evidence of asymmetric cointegration between economic growth and trade openness in India during the period under evaluation and over the different sub-periods. The estimated asymmetric error-correction model exhibits a different speed of adjustment in trade openness in response to positive and negative economic growth shocks in the short-run. More specifically, during the pre-reforms period, deviations from the long-run equilibrium due to a relative increase in economic growth have a lower speed of adjustment in comparison to deviations caused by a corresponding decrease in economic growth in India. [ABSTRACT FROM AUTHOR]

This article examined whether the Wagner's law that represents the long-run relationship between income and public expenditure holds at the subnational level in India. It also examines whether the Wagner's law is revenue expenditure specific or capital expenditure specific in the context of Indian sub-nationals. The paper covers 21 Indian States and a time period of 40 years, from 1980-81 to 2019-20. In this study we have assessed six pairs of relationships among state-level income, public expenditures, revenue expenditure, capital outlay, public expenditure on economic services, public expenditure on social services, and expenditure on the developmental sector. The validity of the law was examined for nine different panels of states broadly under income categories and geographical regions. Unlike first-generation panel techniques, which fail to account for the aspects of cross-sectional independence and heterogeneity, the present study tests the validity of the Wagner's law using the second-generation panel unit root method and cointegration approach. The analysis adopted Panel Dynamic Ordinary Least Square to test the evidence of Wagner's law hypothesis. The findings reveal that Indian states are heterogeneous in terms of public expenditure, and there exists cross-sectional dependence. There also exists a long-run cointegrating relation between state-level income and state-level public expenditure. For the full sample, while this study finds holding Wagner's law, there is a mixed validity of the law in different panels across income categories and regions. In addition, it is observed that the validity of Wagner's law in the Indian Subnational context is mainly driven by the high-income major states, and it is more capital outlay centric. To conclude, these responsive affiliations comprehend the effectiveness of public expenditure as a fiscal policy instrument in stimulating economic growth and the contribution of economic growth in the budget exercise at the subnational level. Therefore, subnational governments need to be more strategic to ensure growth momentum as the public expenditure indirectly and directly causes the living standard and welfare of the people in the economy. It must be acknowledged that India adopted fiscal rules in 2005, which may limit the procyclical fiscal policy during the swings in the business cycle, and thus have implications for budget exercises at the subnational level. [ABSTRACT FROM AUTHOR]

Using the public (government) health expenditure data of sixteen states in India from 1980 to 2013, the paper examines the long-run relationship between an increase in public health expenditure and income. We use real GSDP and real per capita GSDP as proxy for income. We apply Westerlund (2007) error correction based cointegration test for estimating the long-run relationship and panel dynamic OLS (DOLS) method for estimating the long-run coefficient of health expenditure. The empirical result shows that public health expenditure and income is cointegrated in the long-run. There is a positive and significant impact of income on growth of public health expenditure whereas the elasticity of public health expenditure is less than one in the long- run. It has also been found that there is a bidirectional causality between income and public health expenditure in the short-run while being unidirectional in the long-run. These research findings would serve as effective policy instruments aiming at achieving universal health coverage by generating more additional resources for health sector and minimizing the state level disparity in the growth of public health expenditure in India [ABSTRACT FROM AUTHOR]

Foreign direct investment is an important part of a country's strategy towards growth and development. This is especially true of developing countries, which take several steps to attract foreign direct investment to gain easy access to capital, and advanced technology. Hence, the relationship between economic growth and foreign direct investment must be examined to see if foreign direct investment is having a positive impact on economic growth of a country. This paper examines the nexus between economic growth and foreign direct investment in India for the period 1990-2014. Co-integration analysis and error correction mechanism are used to estimate the causal relationship between economic growth and foreign direct investment. Our empirical findings suggest that causality runs from economic growth to foreign direct investment. The robustness of the above findings is confirmed by the use of granger causality tests and residual diagnostics for the VECM model. For the period under study, we could not find a statistically significant causal relationship running from foreign direct investment to economic growth. [ABSTRACT FROM AUTHOR]

Purpose: This study presents time-series data estimations on the association between the indicators of institutional environment and inward foreign direct investment (FDI) in India utilizing a comprehensive data set from 1996 to 2021. Design/methodology/approach: The study employs the nonlinear autoregressive distributive lag (NARDL) model. The asymmetric ARDL framework evaluates the existence of cointegration among the factors under study and highlights the underlying nonlinear effects that may exist in the long and short run. Findings: The significance of coefficients of negative shock to "control of corruption" and positive shock to "rule of law" is greater when compared to "government effectiveness, regulatory quality, political stability/absence of violence." The empirical outcomes suggest the positive influence of rule of law, political stability and government effectiveness on FDI inflows. A high "regulatory quality" is observed to deter foreign investment. The "voice and accountability" index and negative shocks to the "rule of law" are exhibited to have no substantial impact on the amount of FDI that the country receives. Originality/value: This study empirically examines the institutional determinants of FDI in India for a comprehensive period of 1996–2021. The study's findings imply that quality of the institutional environment has a significant bearing on India's inward FDI. Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0375 [ABSTRACT FROM AUTHOR]

Copyright of International Research Journal of Business Studies is the property of Prasetiya Mulya Publishing, Universitas Prasetiya Mulya and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Foreign Direct Investment (FDI) is the important means of promoting export. There has been an increase in the FDI in India depicting that Indian economy is an attractive place to invest in and operate business. In this paper, an attempt has been made to analyze the causal relationship between FDI and export in India. Using data from 1990 to 2013 for FDI and export from DBIE (website of RBI), the analysis is done using unit root testing, Johansen cointegration test and Granger causality test through Eviews. The paper concludes that neither FDI Granger-causes export nor export Granger-causes FDI. [ABSTRACT FROM AUTHOR]

Notable accomplishments in export have made India's software sector conspicuous. This paper attempts to discuss the determinants of software exports from India. The study notes that-besides dynamic elements of economic development across the world-the policy measures and actions of the Indian government have played proactive and facilitating roles in the growth of the software sector. The study uses the autoregressive distributed lag (ARDL) approach to estimate the impact of various explanatory variables on software exports from India. Since causality is found running in both directions for many variables, the study attempts to examine the determinants of software exports from India through the regression equation in first difference. The results suggest that changes in openness index, human capital, and the GDP of high-income OECD countries have exercised positive impact on change in software exports from India. The study finds a stable long run relationship among variables. [ABSTRACT FROM AUTHOR]

Infrastructure sector is a key driver for the Indian economy. Infrastructure may be termed as physical infrastructure which may include social infrastructure. Importance of infrastructure in economic growth cannot be overemphasized. Infrastructure is the lifeline of an economy and the fate of the economy is intricately linked to the development or otherwise of its infrastructure. The objective of the paper is to examine the effect of infrastructure investment on economic growth of India. Gross Capital Formation (GCF) and Gross Domestic Product (GDP) are considered as infrastructural development macroeconomic variable and economic growth variable respectively. The data have been collected for a period of 57 years i.e. 1960 - 2016 (World Bank). Different charts and graphs have been used to analyse the status of infrastructure investment during the study period. Short run and long run relationships between infrastructure investment and economic growth have been examined using time series econometric tools like VECM and Cointegration test. It is found that infrastructure investment and economic growth of India is integrated in long run which implies that there is a long run relationship between them. [ABSTRACT FROM AUTHOR]

There exists an enormous interest in clarification of the relationship between education and economic growth. Over the past 30 years, there have been conducted studies by economists about the connection between education and economic growth. There are actually many publications which provide strong evidence that suggests a correlation between the two. This paper attempts to build upon previous publications and to introduce a unique insight along with contemporary evidence about the relationship between education and economic growth in India from 1975 to 2016 by foc using on primary, secondary and tertiary levels of education. The relationships are examined by utilization of econometric estimations with the Granger Causality Method and the Cointegration Method. These methods are used to create models that could shed light on the claim that education plays a central and significant role in economic growth of India which could consequently be used as an example for similar countries in Asia or around the world. The findings of this work show that there is compelling evidence proving a positive connection between education levels and economic growth in India which might influence governmental actions and shape the future of India. [ABSTRACT FROM AUTHOR]