Contents

• Ombir Singh : Analysis of Inter-State and Inter-Region Beta- Convergence Growth Rates in India in Post Reform Period

• Satrughan Behera, Sachidananda Sa, Rathi Kanta Kumbhar, Rahul Kumar & Sapan Kumar Pradhan : Prevalence and Determinants of Multimorbidity Among the Elderly People of Rural Odisha: A Case Study of Bhadrak District

• Alok Kumar Pandey, Bhartendu Kumar Chaturvedi & Pawan Kumar Singh : Time-Series Forecasting of Four Cryptocurrencies Market Using Machine Learning Models

• Divya Singh, Vishal Kumar Singh & Amit Gautam : Determinants of Export Pricing and Moderation Effect of Export Market Turbulence

• Charu Grover Sharma : Impact of Green Network, Environmental Regulation, and Firm Relocation on Consumer Choice under Vertical Product Differentiation

• Kakali Majumdar & Alisha Mahajan : Mediating Role of FDI and R&D in Trade–Stringency Relation: A Study in Context of Sensitive Goods Sector in G7

• Raja Srivastava, N V Muralidhar Rao, Devesh Kumar Shukla & Shambhavi Mishra : Examining Impact of Socioeconomic Factors on Road Accident Victims: A Study of Uttar Pradesh

• Sunday Oseiweh Ogbeide : Carbon Foot Print and Financial Performance of Listed Firms in Nigeria

• Amit Kundu & Barendra Nath Chakroborty : Financial Development and Economic Growth in India - An Econometric Analysis

Analysis of Inter-State and Inter-Region Beta-
Convergence Growth Rates in India
in Post Reform Period

Ombir Singh ¹

There is a long standing debate among the scholars over the convergence versus divergence of regional growth rate of per capita income in India. The present study tries to resolve this debate in the light of latest available data by using Beta- convergence analysis in panel data framework. The results indicate to the presence of unconditional divergence and conditional convergence in case of both inter-state and inter- region analysis, which indicates that the unconditional divergence may be due to the presence of omitted variable bias. The results also indicates that the primary sector contributes in the reduction of interstate as well as inter- region income inequality, while the growth of tertiary sector has a significant contribution in increasing interstate and inter-region income inequality. Therefore, the findings of the study imply that the phenomenon of service led growth in post reforms period is mainly responsible for the widening gap in the growth of various states and regions of India.

1. Assistant Professor, Department of Economics, Govt. P.G. College, Ambala Cantt., Haryana, India. Email: ombirhalwasia@gmail.com

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Prevalence and Determinants of Multimorbidity Among
the Elderly People of Rural Odisha: A Case Study of
Bhadrak District

Satrughan Behera¹
Sachidananda Sa²
Rathi Kanta Kumbhar³
Rahul Kumar⁴
Sapan Kumar Pradhan⁵

In India as well as the rest of the world, the proportion of elderly people is continuously increasing. The increasing elderly population poses its own challenges, one of the major challenges is multimorbidity. Multimorbidity is defined as the co-existence of more than two diseases or illnesses in the same individual at the same time.This study examines the prevalence of multimorbidity among the elderly in the Bhadrak District of Odisha and estimates the socio-economic determinants associated with multimorbidity.This study was conducted among elderly people aged 60 years and above in the Bhadrak district of Odisha from May 2020 to July 2020. The study people were chosen through a multi-stage random sampling technique. The results of the study show that poor health behaviours and very low socioeconomic situations among elderly people increase the higher risk of multimorbidity. The Binary logistic regression result shows that Age, Caste, living arrangement, and Income are significantly affecting the morbidity status of the elderly people in the study area, whereas other factors had no significant influence on the morbidity status of the elderly people.The number of elderly people and their multiple chronic conditions among them in rural areas of Odisha is rising. To address this issue, it is required to furnish specialized aging health care services for old age people, as well as to control the most frequent health issues seen in rural settings, and to give particular training to health care providers.

1. Research Scholar, Department of Economic Studies and Policy, Central University of South Bihar, Gaya, India. Email: satrughan@cusb.ac.in
2. Assistant Professor, P.G Department of Social Science, Fakir Mohan University, Balasore, Odisha, India
3. Professor, Department of Economic Studies and Policy, Central University of South Bihar, Gaya, India
4. Research Scholar, Department of Economic Studies and Policy, Central University of South Bihar, Gaya, India
5. Research Scholar, Zakir Husain Centre for Educational Studies, Jawaharlal Nehru University, New Delhi, India

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Time-Series Forecasting of Four Cryptocurrencies
Market Using Machine Learning Models

Alok Kumar Pandey¹
Bhartendu Kumar Chaturvedi²
Pawan Kumar Singh³

With the innovation of machine learning and artificial intelligence, numerous methods have been proposed to study and predict cryptocurrencies price, such as Artificial Neural Networks, Recurrent Neural Networks, Long Short-Term Memory (LSTM), FBProphet, Convolutional Neural Network sliding window, etc., but their accuracy level varies from each other. The current study aims to predict the price of cryptocurrencies and compare the results obtained using LSTM, FBProphet, and Extreme gradient boosting (XGBoost). Comparing the above three models will help investors, financial traders, and speculators explain the accurate prediction of cryptocurrencies. Cryptocurrencies datasets were collected from yahoo finance and have been categorised into training and test data. Three accuracy measures indicators, viz, MAPE, MSE, and RMSE, show that the application of the Prophet model to predict different cryptocurrencies is significantly better than LSTM and XGBoost in the current study. This study finds that the prophet model performs better for all cryptocurrencies (BTC, BNC, XRP, and ETH) and is consistent for all datasets. Finally, this study shows that implementing the Prophet approach to predict cryptocurrencies provides relevant results.

Keywords : Bitcoin, LSTM, Prophet, XGBoost, Mean Square Error (MSE), Root Mean Square Error (RMSE).

1. Centre for the Integrated and Rural Development, Banaras Hindu University, India.
   E-mail: alokpandey@bhu.ac.in
2. Associate Professor, Department of Economics, University of Allahabad, India,
   E-mail: bkchaturvedi.eco@gmail.com
3. Department of Economics, Lakshmibai College, University of Delhi, India.
   E-mail: pksecobhu@gmail.com

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Determinants of Export Pricing and Moderation Effect
of Export Market Turbulence

Divya Singh¹
Vishal Kumar Singh²
Amit Gautam³

The study attempts to address the disparity of unionizing the export prices within the firm as export pricing is a significant element for the success of a firm in an international setting. With the use of structural equation modelling, the study analyses the factors determining the export prices within a firm- export intensity, information asymmetry, structure of pricing authority and internal price coordination with a moderating effect of export market turbulence. The findings of the study suggest that the identified factors as determinants have a significant impact on export pricing which is further strengthened in the presence of export market turbulence. It also proposes a model with the practicality of implementation of the identified determinants while determining export prices. Furthermore, the study provides insights regarding the significance of internally organising the export prices to the owners and managers who are closely conversant with the strategic decision making.

Keywords : Export intensity, information asymmetry, internal pricing coordination, structure of pricing authority, export market turbulence.

1. Doctoral Fellow, Banaras Hindu University, Varanasi, Uttar Pradesh, 221005.
   E-mail: divyasingh@fmsbhu.ac.in
2. Assistant Professor, School of Management Sciences (SMS), Varanasi, Uttar Pradesh, 221011,
   E-mail: vishalkrsingh@fmsbhu.ac.in
3. Professor, Banaras Hindu University, Varanasi, Uttar Pradesh, 221005,
   E-mail: amitgautam@fmsbhu.ac.in

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Impact of Green Network, Environmental Regulation,
and Firm Relocation on Consumer Choice
under Vertical Product Differentiation

Charu Grover Sharma¹

The paper models a vertical product differentiation framework with two countries - Home and Foreign Country and two firms. A three-stage game is considered, where in the first stage firms decide on location- Home Country or Foreign Country, in the second stage firms choose environmental quality and in the third stage firms choose prices. It analyzes the impact of the green network effect and output tax on market outcomes - environment quality, prices, quantity, and profits. It shows that an increase in the green network effect decreases environmental quality and prices under all location scenarios, while it increases the market share and profits of the environmental quality firm under all location scenarios. The environmental regulation in form of a tax on output has no impact on the environmental quality of both firms. Relocation costs are an important factor in firms’ relocation decisions. If relocation costs are in the intermediate range, a separating equilibrium exists, where one firm stays in the home country and the other firm relocates to a foreign country. However, if relocation costs are low, a pooling equilibrium where both firms remain in the same country exists.

Keywords- Environmental Regulation; Green Network Effect; Relocation; Pollution Haven; Vertical differentiation.

1. Assistant Professor, Indian Institute of Foreign Trade, New Delhi
   Email: charu@iift.edu

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Mediating Role of FDI and R&D in Trade–Stringency
Relation: A Study in Context of Sensitive
Goods Sector in G7

Kakali Majumdar¹
Alisha Mahajan²

Background
In the era of global trade, based on the stringency level, different macro variables play mediating role that influences the strategic behaviour of the countries’ international trade. Foreign Direct Investment (FDI) and Research and Development (R&D) are the two most important mediators that influence the trade-stringency relation in global context. The Group of Seven (G7) is aimed to promote free trade in cooperation with the developing nations and contribute to a significant percentage of global trade. In the present time it is an important area of research to investigate the strategic responses of these countries with regard to trade stringency integration vis-a-vis the role of the mediators. The present study is an attempt in this direction.

Methodology
Time series data for G7 countries from 1990 to 2019 have been used for the analysis. Single and Multiple mediator models are used to study the mediating effect of FDI and R&D between export of environmental sensitive goods and environmental policy stringency Index with the theoretical base of Pollution and Porter Hypothesis. Dynamic Ordinary Least Square (DOLS) method, a robust single equation technique that covers regressor leads and lags and explanatory factors, are employed for estimation of the mediator models. Because of the coverage of complexities in terms of stationarity, endogeneity, serial correlation, sample bias etc.

Finding
Results suggests that FDI has insignificant role in influencing the trade-stringency relation in G7 as all most all the countries are developed country. Significant level of technological development has been taken place in these countries. All G7 countries except Italy are experiencing Porter Hypothesis indicating significant contribution of R&D.

Novelty
This study investigates one of the most contentious areas of academic inquiry, namely the interrelationships between environmental stringency and global trade flows in the G7 nations.

Keywords: Environmentally sensitive goods, Environmental Stringency, G7, Export of Sensitive Goods, Pollution Haven Hypothesis, Porter Hypothesis.

JEL Classification: F1, F2, Q5

1. Associate Professor, School of Economics, Shri Mata Vaishno Devi University, Kakryal, Katra, Dist: Reasi, Jammu and Kashmir, India.
   Email: kakoli.majumdar@smvdu.ac.in
2. PhD Student, School of Economics, Shri Mata Vaishno Devi University, Kakryal, Katra, Jammu and Kashmir, India

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Examining Impact of Socioeconomic Factors on Road
Accident Victims: A Study of Uttar Pradesh

Raja Srivastava¹
N V Muralidhar Rao²
Devesh Kumar Shukla³
Shambhavi Mishra⁴

Despite changes in transport legislation, it has been seen that there are many more established, broader societal elements that are influencing the number of road traffic accidents, including injuries, fatalities, and the socioeconomic effects of RTAs in Uttar Pradesh, India. The paper highlights the disparate impacts of collisions based on class, gender, and location as well as the paucity of efforts to comprehend the repercussions of collisions in the state. Data from 1810 victims was utilizes quantitative data analysis techniques such as Principal Component Analysis, binary logistic regression, and examine the challenges faced by victims and their dependents in accessing support systems. The study results in the identification of numerous socio- demographic factors that could influence the type and cause of accidents. From the first model, we concluded that road accident victims who are illiterate and living alone are more prone to fatal accidents. Likewise, the second model suggested that victims who are illiterate, living in either a joint or a nuclear family, and belonging to high economic status suffer more from accidents caused by rash driving. The socioeconomic effects on traffic accident victims and the challenges they face in accessing support networks. It highlights the broader impact of accidents beyond physical injuries, emphasizing the role of driving behaviour, medical assistance, and road infrastructure. Financial burdens and bureaucratic complexities hinder timely assistance. The study provides insights for policymakers and healthcare professionals, advocating for a holistic approach to victim support.

1. Research Scholar, Department of Economics and Finance, Birla Institute of Technology and Science (BITS), Pilani, Rajasthan 333031
2. Senior Professor, Department of Economics and Finance, Birla Institute of Technology and Science (BITS) Pilani, Rajasthan.
   Email: nvmrao@pilani.bits-pilani.ac.in
3. Ram Manohar Lohia Institute of Medical Sciences, Uttar Pradesh- 226010.
   Email: devesh.9oct@gmail.com
4. Assistant Professor, Department of Statistics, University of Lucknow, Uttar Pradesh- 226007,
   Email: shambhavimishra.lko@gmail.com

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Carbon Foot Print and Financial Performance of Listed
Firms in Nigeria

Sunday Oseiweh Ogbeide¹

This study examined the relationship between a firm's carbon footprint and its financial performance within the context of Nigeria. The pressing global issue of climate change and increasing environmental concerns have led to a growing emphasis on corporate sustainability practices. As Nigeria grapples with environmental challenges and strives to achieve economic growth, it is imperative to understand how a firm's carbon footprint affects its financial standing. The research employed the causal-effect research design; whilethe population of the study consisted of listed firms in manufacturing as well as oil and sector in Nigeria. The sample size of the study is thirty (30) firms. The data were obtained from the World Bank Development Indicators (WBDI) database and financial statements of the sampled firms between 2018 and 2022. The data was analyzed using descriptive statistics, correlation matrix, and the generalized method of moment (GMM) estimation method. The study found that that carbon foot print influence firm financial performance. Carbon emission and electricity consumption exerted a positive and no significant effect on firms’ financial performance in the context of Nigeria. The study therefore recommended that firms should invest in energy-efficient technologies and practices so as to reduce energy consumption and, consequently, carbon emissions as this can lead to cost savings and improved financial performance. Firms should consider transitioning to renewable energy sources such as solar or wind power.

Keywords : Carbon Foot Print, Carbon Emission, Electricity Consumption, Financial Performance.

1. Department of Accounting and Finance, Faculty of Humanities, Social and Management Sciences Elizade University, Ilara- Mokin, Ondo State, Nigeria. E-mail: sunnyogbeide2017@gmail.com

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Financial Development and Economic Growth in India -
An Econometric Analysis

Amit Kundu¹
Barendra Nath Chakroborty²

The stock market's impact on economic development is unquestionable. In this article, prime focus has been given to the relationship between economic growth and stock market performance keeping FDI as an instrumental variable. It is found that all the variables (GDP, Nifity 50, FDI) under this study are stationary at 1st difference. Johansson Cointigration test supports that there is no cointigration among variables, VAR results depict that the economy of India was marked by the absence of causality between GDP growth and Nifty 50 growth in two-way direction over the period of study. The economy of India was marked by the presence of unidirectional causality running from Indian stock market to FDI over the research period.

Keywords: Nifty 50, GDP, FDI, Cointegration, VAR.

JEL Codes: E44, F43, C01

1. Associate Professor, Department of Commerce, Cooch Behar Panchanan Barma University, Cooch Behar, West Bengal, India.
   Email: prof.amitkundu@gamil.com
2. 4^th Semester student, Department of Economics, Cooch Behar Panchanan Barma University, Cooch Behar, West Bengal, India.
   Email: shashwata.chakraborty1999@gmail.com

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