School of Management & Entrepreneurship

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IIT Jodhpur

Blockchain is a technology that provides a secure and distributed mechanism to record transactions. The technology has been applied in various domains, most notably in cryptocurrencies. This chapter outlines the potential of blockchain technology in the public health domain. Privacy and security, interoperability, and immutable audit trails are some of the key benefits of blockchain when applied to electronic health records management. The benefits are made possible by the use of public key encryption and P2P architecture, using public or private blockchain networks. The chapter also presents a use case from Estonia where the health service is using blockchain to keep track of all access/changes made to electronic health records. The chapter also includes potential challenges of blockchain implementation in public health. © 2020 Elsevier Inc. All rights reserved.

World University root node

Computational Intelligence and Its Applications in Healthcare

Blockchain for public health: Technology, applications and a case study

We investigate the evidence of convergence/divergence in global value chain (GVC) participation across 61 countries from 2005 to 2015, employing the panel club convergence technique. The findings do not support evidence of absolute convergence, but evidence of club convergence. Seven clubs and a non-convergent group are identified, signifying that the types of activities are not uniform across countries, each club following a unique transition path. Further, we examine convergence in the forward and backward participation of GVCs. The findings reveal similar evidence of club convergence. Policies targeting GVCs need to consider the transition path of each club for better outcomes. © 2020 CEPII (Centre d'Etudes Prospectives et d'Informations Internationales), a center for research and expertise on the world economy

International Economics

Cross-country convergence in global value chains: Evidence from club convergence analysis

This paper studies a manufacturer-retailer channel selling complementary green products under the cap-and-trade policy and analyzes strategic decisions in these settings. While the manufacturer faces government mandated cap-and-trade norm, the retailer invests in corporate social responsibility through selling of green products. In this study, we conduct a comparative analysis of the players’ decisions under centralized and decentralized scenarios and explore the role of cap-and-trade policy in influencing decision outcomes. Further, three contracts are proposed to improve channel performance, namely, the two-part tariff, corporate social responsibility (CSR) effort sharing, and green cost sharing contracts. The results show that collaboration among the supply chain players through contracts supports green initiatives vis-à-vis the decentralized channel. However, given a choice of contracts, the channel prefers those contracts from which the manufacturer accrues direct benefits because he incurs greening costs. The results further demonstrate that carbon markets play an important role in influencing green initiatives, particularly, under high trading prices, where manufacturers are incentivized to improve their product offerings. Further, the cap-and-trade policy influences retailers to work toward building higher reputation and brand value through investments in higher CSR effort. From a retail price perspective, we find that consumers benefit under higher trading prices because the benefits of carbon surplus and higher revenues of the supply chain players result in lowering the prices for consumers. However, it is in contrast to studies on the decentralized channel outcomes or environmental taxation because in both the scenarios, greening or CSR costs get transferred to the consumers in the form of higher prices. © 2019 Elsevier B.V.

International Journal of Production Economics

Do cap-and-trade policies drive environmental and social goals in supply chains: Strategic decisions, collaboration, and contract choices

Purpose: The purpose of this paper is to investigate long-run commonality in liquidity using multiple proxies computed from limited order book data of NIFTY50 stocks. The findings indicate the existence of systematic liquidity or commonality on NIFTY50 market and comprising industries. Design/methodology/approach: The sample comprises all intraday transactions corresponding to NIFTY 50 stocks for April 2015. The study runs firm by firm time series regressions to test the concept of long-run commonality, while controlling other effects. Findings: Strong evidence is found in support of long-run commonality across three liquidity measures. On the basis of significance (10%) of long-run commonality beta (βLR), the strength of long-run commonality is found to be highest in natural resources and infrastructure sector. Portfolios having greater exposure to these sectors will face diversification risk to a great extent. Practical implications: Knowledge of long-run commonality helps portfolio managers in formulating diversification strategies and reshuffling the portfolio over the period. Commonality risk being non-diversifiable is a policy concern for regulators and central bankers. Its empirical evidence will assist in managing exchange organization and thus preventing market crashes because of sudden liquidity evaporation. Originality/value: Although there are recent studies documenting commonality in short run, little empirical work has been done on commonality in the long run and in emerging markets such as India. This research contributes to the literature by testing concept of commonality in long-run on NIFTY50 stocks using detailed transaction data from National Stock Exchange. © 2020, Emerald Publishing Limited.

Journal of Indian Business Research

Long run commonality in Indian stocks: empirical evidence from national stock exchange of India

This study utilizes data for the period 2006–2015 to estimate the determinants of road fatality rates in the Indian states. We employ baseline regression, where the total traffic fatalities, total traffic injuries, rural road fatalities, and urban road fatalities are the functions of human errors in driving, weather conditions, and some control variables. This paper is exclusively focussed upon different sets of human-driven factors in influencing the road fatality across the Indian states. Our empirical results show that reckless driving, defective motor conditions, bad weather, and reckless driving by bus, truck, and car drivers are found to cause road accidents. We further find that the increase in motorization rates and rash driving are the primary causes behind the road fatalities, and bad weather play a major role in causing road fatalities and injuries in urban areas. However, road fatalities are increasing; still, cases of under reporting, lack of proper road safety regulation, improper investigation procedures, increasing vehicle usages, and higher urbanization have made the matters quite worse in India. © 2019 John Wiley& Sons, Ltd.

Journal of Public Affairs

Identifying the causes of road traffic accidents in India: An empirical investigation

Stochastic precedence order is a natural type of comparison for random variables in numerous engineering applications (e.g., for the stress-strength modeling). In this note, we show that, for a k-out-of-n system, redundancy at the component level is superior to that at the system level with respect to the stochastic precedence order. Cases of active and cold redundancy are considered. Similar results for other stochastic orders were previously discussed in the literature. © 2020 Taylor &amp; Francis Group, LLC.

Department of Mathematics

Communications in Statistics - Theory and Methods

A note on the stochastic precedence order between component redundancy and system redundancy for k-out-of-n systems

Purpose: The purpose of this study is to examine whether the electricity consumption patterns across Indian states do converge. Design/methodology/approach: This study considers 18 Indian states spanning over the period 1970-1971 and 2014-2015, using the recently developed Phillips and Sul panel convergence technique that accounts the multiple steady states. Findings: The results provide the following insights. First, the authors find evidence of convergence in electricity consumption among all Indian states. This suggests that electricity consumption patterns for Indian states are converging to a common steady state. Second, to provide broader insights, we further investigate the convergence in electricity consumption among user groups such as agriculture, industry, commercial, domestic and miscellaneous. The results reveal that commercial, domestic and miscellaneous groups are also converging. Third, the non-convergence patterns in agriculture and industry enable us to investigate the possibility of clubs or the multiple common steady states. The results indicate the occurrence of three clubs in case of agriculture and two clubs in case of the industry. Fourth, this study also inspects the relative speed of convergence among the user groups. The results reveal the higher speed of convergence in case of the domestic user group. Practical implications: The findings enable policymakers to formulate an appropriate energy policy to accommodate the future electricity demand across Indian states and prioritize low electricity consumption states so that they receive a greater share. Originality/value: This is the first study that examines the convergence in electricity consumption across Indian states at aggregate and user groups using a new panel club convergence technique. © 2019, Emerald Publishing Limited.

International Journal of Energy Sector Management

Convergence in electricity consumption across Indian states: a disaggregated analysis

Purpose: The primary purpose of this study is to examine whether the classification of industries into the tradable and nontradable matters for the Balassa–Samuelson (BS) effect. Design/methodology/approach: The study uses annual data for 38 countries from 1995 to 2014. To examine whether the classification of industries matter, the study proceeds with two approaches, that is, “traditional” and “benchmark”. Findings: First, by applying panel cointegration tests of Pedroni and Westerlund, the results validate the BS hypothesis. However, the coefficients of long-run elasticities show appreciation of real exchange rate (RER) due to increase in productivity in the case of “traditional approach”, whereas depreciation of RER in the case of “benchmark approach”. Second, by applying the Dumitrescu-Hurlin panel Granger causality test, the results reveal the bi-directional causality among RER and productivity for both the approaches. Further, to provide more insights, the study employs a fixed-effects panel threshold model. The results indicate that increase in productivity leads to both appreciation and depreciation of RER depending on threshold regimes. Practical implications: The study ascertains that the evidence of BS effect depends on the choice of approach considered. However, irrespective of the classification, there exists a BS effect beyond a threshold. Originality/value: Although the BS effect is well established in the literature; there is no study examining the importance of classification of industries at a disaggregated level. Furthermore, there is no consideration of threshold effects. © 2020, Emerald Publishing Limited.

Journal of Economic Studies

Does productivity drive the real exchange rate movements? A re-examination of the Balassa–Samuelson hypothesis

Purpose: The purpose of this paper is to examine the effects of the global value chain (GVC) participation and the associated improvements in labour productivity and employment among 16 Asia-Pacific countries. Design/methodology/approach: First, the indicators of GVC participation are computed using annual multi-region input-output tables over the period 1990-2014. Second, the study examines the long-run association between GVCs and labour productivity through Pedroni (2004) and Westerlund (2007) panel cointegration techniques. Then in the third step, the long-run elasticities are estimated using dynamic ordinary least squares (DOLS) and fixed-random effects models. Finally, the direction of causality is examined using the Dumitrescu and Hurlin (2012) panel causality technique. Findings: The result shows an increasing participation of GVCs among Asia-Pacific countries. The findings also show the long-run relationship between GVCs and labour productivity. The long-run elasticities suggest the positive association of GVCs with labour productivity and employment. Further, the categorization of Asia-Pacific countries based on income groups reveals that improvement in labour productivity and employment outcomes is significantly greater in the case of middle-income countries. Finally, the results from panel causality infer that the direction of causality runs from GVCs to labour productivity and GVCs to employment. Practical implications: The findings enable policymakers to formulate appropriate policies in Asia-Pacific countries to keep the momentum of increasing their participation in GVC for boosting labour productivity and employment gains. Originality/value: To the author’s knowledge, this is the first empirical study examining the spillover effects of GVC on labour productivity and employment in case of Asia-Pacific countries. © 2020, Emerald Publishing Limited.