Mandeep Bhardwaj, S. Mahapatra, T. Dutta, Jyotsana Bhangu
{"title":"Growth and Potential of Intra-Industry Trade of India in Agriculture among the BIMSTEC Nations","authors":"Mandeep Bhardwaj, S. Mahapatra, T. Dutta, Jyotsana Bhangu","doi":"10.1177/00194662231159854","DOIUrl":"https://doi.org/10.1177/00194662231159854","url":null,"abstract":"The unification and development of crawling Asian countries is the burning issue after the declaration of failure of the SAARC (South Asian Association for Regional Cooperation) region. Besides, a small bubble in the ocean of agreements is ‘BIMSTEC’ (Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation), which has not been flourishing to date due to the lack of interest of a dominating country like India, whose focus is on other successful regional blocs. However, recent studies have shown that though it starts late but contributing significantly towards the trade among BIMSTEC countries. And, second, almost all the countries have shared similar cultures, languages and levels of per-capita income except Myanmar and Thailand, which will favour the trade among the region. Thus, the main focus of the study is to analyse the revealed comparative advantage of countries in BIMSTEC, their trade competitiveness and contribution made to the country’s growth before and after formation by the region. Under the study, it was observed that the intra-industry trades of India in Agriculture among the BIMSTEC nations have shown very less potential for trade in all 24 agriculture chapters. Thus, economies need to reframe the policies as required and identify the potential products in agricultural-related goods that can significantly improve the trade balance of the countries. JEL Codes: F14, F15, F19, F53","PeriodicalId":85705,"journal":{"name":"The Indian economic journal : the quarterly journal of the Indian Economic Association","volume":"71 1","pages":"561 - 580"},"PeriodicalIF":0.0,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44424218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Sharma, G. Narayanan, Adeet Dobhal, Raihan Akhter
{"title":"Evaluating the Reasons for India’s Withdrawal from RCEP: A General Equilibrium Analysis","authors":"S. Sharma, G. Narayanan, Adeet Dobhal, Raihan Akhter","doi":"10.1177/00194662231159847","DOIUrl":"https://doi.org/10.1177/00194662231159847","url":null,"abstract":"This study identifies and rationalises some of India’s issues and concerns with the signing of the RCEP. By analysing the existing trade balance, import surge trends, dumping and agricultural sensitivities, among other factors, the study justifies India’s decision to remain outside of this mega-FTA. Further, it predicts the impact of tariff elimination under RCEP on various macroeconomic variables of the RCEP member countries by using the GTAP model under two scenarios: (i) India does not join the RCEP and (ii) India joins the RCEP. Results show that India’s GDP would be adversely affected if it joins this agreement, and its overall trade deficit may further deteriorate after joining the RCEP. In terms of the bilateral trade balance, India’s trade deficit with ASEAN and China will grow steeply if it joins the agreement. The study also finds that an RCEP without India may lose its shine as the GDP of most of the other members of the RCEP would be negatively impacted by India’s decision to stay out. JEL Codes: F13, F15, F17, F61, O53","PeriodicalId":85705,"journal":{"name":"The Indian economic journal : the quarterly journal of the Indian Economic Association","volume":"71 1","pages":"508 - 531"},"PeriodicalIF":0.0,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45190513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Spatial Market Integration, Price Transmission and Transaction Costs in Major Onion Markets of India","authors":"Mumtaz Ahmed, Naresh Singla","doi":"10.1177/00194662231159851","DOIUrl":"https://doi.org/10.1177/00194662231159851","url":null,"abstract":"The price information is one of the prime objectives of marketing strategies, and the farmers are unable to determine the marketing strategies without knowing the price movements of the agricultural commodities. In this context, the study has examined the spatial price integration among four major onion markets using the threshold vector error correction model (TVECM) that takes into account transaction costs in the price adjustment process. Augmented Dickey–Fuller and Phillips–Perron tests for unit root suggest that the time series is I(1). The application of the Johansen cointegration technique supports the presence of long-run price association and equilibrium in all pairs of onion markets. The Granger Causality test unveils that Bengaluru Granger causes all the markets except Kolkata. The Hansen and Seo supreme Lagrange Multiplier (SupLM) test of linearity suggests that non-linear TVECM with one threshold and two regimes is best fit for the underlying data for three pairs of markets. While the rest of the three pairs, the SupLM test rejects the null of linearity, therefore, linear vector error correction model (VECM) is estimated. Finally, VECM and TVECM results reveal that Mumbai and Bengaluru are dominant markets in price formation in rest of the markets. Against these findings, it is suggested that the prices should be stabilised in the dominant markets so that the price shocks are not transferred to other markets. The threshold parameter, which is analogous to transaction cost, reveals the high transaction costs between the selected markets pairs, especially Mumbai and Delhi. One of the reasons for the high transaction costs may be the inefficiencies in infrastructure and communication. While a more correct explanation for this difference can be attributed to the differences in marketing fees, taxes, commission charges, license fees, etc., across the spatially separated agricultural markets. JEL Codes: Q1, Q13, D4, C22, D23","PeriodicalId":85705,"journal":{"name":"The Indian economic journal : the quarterly journal of the Indian Economic Association","volume":"71 1","pages":"532 - 547"},"PeriodicalIF":0.0,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47797236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Capturing the Growth of Chinese Investment in India","authors":"R. Choudhury","doi":"10.1177/00194662231159843","DOIUrl":"https://doi.org/10.1177/00194662231159843","url":null,"abstract":"Chinese foreign direct investment inflows in India increased from just US $1 million in 2010 to the US $173 million in 2019, while the total private equity investment was US $3,423 million in the same period. Chinese companies emerged as majority shareholders in several Indian start-ups, particularly in the technology sector. In contrast to this economic development, there has been a constant clash among the borders, noticeably in the Dokhlam and Galwan valleys with a few other minor clashes in different areas. Both nations are experiencing a booming economic alliance and shrinking political and diplomatic relations at the same time. In this background, the current article attempts to explore the key factors influencing the Chinese to invest in India. This article also attempts to analyse the nature of Chinese investment and explain why many countries look at Chinese investment with suspicion. Applying the regression model, the study finds that various policy variables played a significant role in attracting Chinese investors to India. JEL Codes: P33, F10, F50","PeriodicalId":85705,"journal":{"name":"The Indian economic journal : the quarterly journal of the Indian Economic Association","volume":"71 1","pages":"548 - 560"},"PeriodicalIF":0.0,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44578110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Foreign Capital Inflow, Exportability and the Indian Economy","authors":"Dibyendu Maiti, Prakash J. Singh","doi":"10.1177/00194662221137838","DOIUrl":"https://doi.org/10.1177/00194662221137838","url":null,"abstract":"The article investigated the effect of foreign direct investment (FDI) on Indian exports using aggregate and disaggregate data to capture macro- and micro-channels. India registers a steady rise in FDI during 1980–2018 in absolute terms but not in terms of GDP share. At the aggregate level, FDI is found to have significantly influenced Indian exports (both manufacturing and services) during 1980–2018 by suppressing its adverse effect on currency appreciation. Even at the firm-level analysis using the World Bank Enterprise Survey database, it is evident that higher participation of foreign ownership, a proxy of FDI measure, seems to have encouraged their export decisions. However, more than 50% of the capital inflows are received from two three countries which is also on limited service-related activities. The lower FDI share on manufacturing has limited the export rise. JEL Codes: F16, L11","PeriodicalId":85705,"journal":{"name":"The Indian economic journal : the quarterly journal of the Indian Economic Association","volume":"71 1","pages":"581 - 597"},"PeriodicalIF":0.0,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44327868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An Empirical Analysis of Supply Response of Food Grains to Changes in Price: Evidence from India","authors":"Jincy Mathew M., Vishwanatha","doi":"10.1177/00194662221138122","DOIUrl":"https://doi.org/10.1177/00194662221138122","url":null,"abstract":"The issue of food production is very important as it affects growth, food security and poverty. Stable food grain price is also important to have a stable food grain market. This article attempts to study the impact of food price fluctuations on food production based on the annual data from 1962 to 2019 by using Non-linear Auto Regressive Distributed Lag model. The results show that changes in food grain price affects grain production and it is statistically significant. Furthermore, the result of asymmetric cointegration test shows that there is a long-run asymmetric relationship that exists between food production and food grain price. JEL Codes: Q11, C01, C32","PeriodicalId":85705,"journal":{"name":"The Indian economic journal : the quarterly journal of the Indian Economic Association","volume":"71 1","pages":"598 - 611"},"PeriodicalIF":0.0,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44360565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Financial Incentives and Fertility Choices: Evidence from India","authors":"Tirtha Chatterjee, Ritika Jain","doi":"10.1177/00194662221139337","DOIUrl":"https://doi.org/10.1177/00194662221139337","url":null,"abstract":"This article estimates the impact of a maternity cash transfer programme, Indira Gandhi Matritva Sahyog Yojana, implemented in India since 2011, on fertility choices. Since the scheme restricts the benefits to the first two births, we ask whether there is an impact on the likelihood of birth post implementation and if this behaviour is driven by son preference. We also test whether the scheme has affected the likelihood of female births. Our results give evidence in support of ‘stopping rule’ and we find that treated households reduce births only when their first two births are sons. However, we do not find any statistically significant impact of the likelihood of a female birth. We further find that post the implementation of the scheme, mothers and children are less likely to get better care for higher order births. JEL Codes: J13, J18","PeriodicalId":85705,"journal":{"name":"The Indian economic journal : the quarterly journal of the Indian Economic Association","volume":"71 1","pages":"673 - 688"},"PeriodicalIF":0.0,"publicationDate":"2023-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46188306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"What are the Key Determinants of Child Malnutrition in India? Empirical Evidence from NFHS-4","authors":"P. Seth, Palakh Jain","doi":"10.1177/00194662221137853","DOIUrl":"https://doi.org/10.1177/00194662221137853","url":null,"abstract":"India hosts the highest number of malnourished children in the world. Tackling this challenge requires urgent implementation of targeted policies. However, the current research is not clear on which specific interventions the policymakers should undertake to yield the biggest improvement in child malnutrition in India. Hence, our study aims to contribute to the existing literature by using a novel regression decomposition technique, called the Shapley–Owen decomposition which can estimate the relative contribution of the factors influencing malnutrition. Using the NFHS-4 data, we classify the drivers of child undernutrition (besides age and gender) into different groups, such as infections and medicines, birth characteristics, food intake, child’s environment, mother’s anthropometry, her characteristics, environment, and socio-economic factors. The decomposition informs us that the child’s age and the mother’s anthropometry are the most important determinants of child height and weight outcomes (respectively). This means that access to adequate nutritional provision during the early years of the child’s life is critical to reducing the burden of malnutrition in India. Further, targeting young girls as the beneficiaries of the welfare schemes will improve their anthropometry, which will ensure healthier children in the future. Given the rising challenge of malnutrition in India, there has been a push to enhance investment in a combination of interventions that ensure optimal food intake, its absorption, adequate sanitation, betterment of maternal nutrition as well as education and access to social safety nets. It is in this context that our study is among the first to provide rigorous econometric analysis to determine which among these is the most important. Hence, this guides policymakers to the specific sectors they could target to improve the nutritional well-being of children in India. JEL Codes: C01, D69, I15, I30, O20, P46","PeriodicalId":85705,"journal":{"name":"The Indian economic journal : the quarterly journal of the Indian Economic Association","volume":"71 1","pages":"729 - 747"},"PeriodicalIF":0.0,"publicationDate":"2023-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47177967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Gravity Model Approach: An Empirical Application with Implications for BRICS Countries","authors":"S. H. Wani","doi":"10.1177/00194662221137267","DOIUrl":"https://doi.org/10.1177/00194662221137267","url":null,"abstract":"This article aims to identify the main determinants of annual export flow among BRICS countries through the estimation of panel data from 1992 to 2018. The estimated results suggest that gross domestic product (GDP) and trade openness among other factors can explain export flow among BRICS countries. The most important finding of the study is that the formation of BRICS has exercised a negative and significant impact on bilateral trade among member countries. This study also found that the intra-industry trade dominates the intra-BRICS trade. Finally, the study found that the geographical distance between countries might be a factor for impeding trade among member countries. Thus, this study highlights the importance of increasing economic cooperation among these countries in terms of developing infrastructure, signing of free trade agreement (FTA) and increasing people-to-people contacts. JEL Codes: F00, F15, C23, F13","PeriodicalId":85705,"journal":{"name":"The Indian economic journal : the quarterly journal of the Indian Economic Association","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46671475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Editorial","authors":"S. Bhushan","doi":"10.1177/00194662231155955","DOIUrl":"https://doi.org/10.1177/00194662231155955","url":null,"abstract":"","PeriodicalId":85705,"journal":{"name":"The Indian economic journal : the quarterly journal of the Indian Economic Association","volume":"71 1","pages":"283 - 284"},"PeriodicalIF":0.0,"publicationDate":"2023-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43256407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}