PurposeThis article aims at analysing the factors influencing the adoption of green economy practices across different sizes of firms in India.Design/methodology/approachThis study is based on the World Bank Enterprise Survey 2022, covering 9,376 firms in India. The Poisson Count Regression Model has been used to analyse the factors affecting the adoption of green economy practices.FindingsAbout 83 % of firms reported adopting at least one green practice in their business related to energy conservation, water management, pollution control and waste management and recycling. Research results reveal a significant association between the size of the firm and adoption of green economy practices. The impact of enterprise characteristics varies by firm size. For instance, female ownership positively affects adoption in large firms but negatively in small and medium-sized enterprises (SMEs). However, lean operations, research and development (R&D) spending and international quality certification positively influence green practices adoption for both SMEs and large firms. Perceived business obstacles show similar implications on green practices adoption by size of firms except access to finance, business licencing, tax rate and law and order affect SMEs while labour regulations, tax administration and political instability affect large firms.Practical implicationsThis paper suggests implications for strengthening the adoption of green economy practices across firm sizes and provides opportunities for future research.Originality/valueThis study is based on a unique dataset derived from the World Bank Enterprise Survey 2022, which has included green economy indicators for the first time.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2023-0918.

This paper aims at analysing the level of awareness of the symptoms and the methods of protection from COVID‐19 based on the Rural Impact Survey of the World Bank, collected from 5200 households belonging to six states in India that is, Andhra Pradesh, Bihar, Jharkhand, Madhya Pradesh, Rajasthan, and Uttar Pradesh. Data has been analysed using chi‐square test and regression analysis. Results of the analysis indicate that about 70.8% rural households are aware of the symptom of coronavirus, and 81.9% are aware of the preventive measures for controlling the spread of COVID‐19. Analysis indicates a significant association between awareness level on symptoms and prevention of COVID‐19 and socio‐demographics and location. The study further analyses the key determinants of awareness of COVID‐19 symptoms and preventive measures using the logistics regression model, indicating that age, gender, education, income, poverty status, access to information, cash relief and medical services are the determining factors of health awareness on COVID‐19 pandemic among rural households in India. Considering the importance of self‐protecting measures in fighting the pandemic, this paper highlights the importance of strengthening public awareness for containing the spread of the COVID‐19 pandemic.

Purpose The purpose of this study is to examine the club convergence of Financial integration (FI) in the case of 60 countries from 1970 to 2015. FI plays a vital role in economic growth through sharing the risk between countries, cross-border capital association, investment and financial information. It also leads to the efficient allocation of capital and capital accumulation, thereby improving the systematic growth and productivity of the economy. Literature on examining the convergence hypothesis of FI is scarce. Design/methodology/approach This study applies the clustering algorithm to identify club convergence, advanced by the Phillips and Sul test, which enables the identification of multiple steady states or club convergence, unlike beta and sigma convergences. Findings The findings indicate the non-convergence when all 60 countries were taken together. This highlights that the selected countries' have unique transition paths in terms of FI. Hence, the authors implement the clustering algorithm, and the estimation shows that 56 countries are categorised into three different clubs. However, for the rest of four countries, the results are sort of ambiguous, favouring neither convergence nor divergence. Practical implications On the basis of three country clubs, Club 1 presents the model countries such as the Netherlands, Singapore and Switzerland. The Club 2 and Club 3 countries can start making moves towards the model countries by making policy adaptations for trade, finance and business facilitation. Originality/value The existing literature provides a plethora of studies investigating the convergence of stock markets, exchange rates and equity markets, but studies on the convergence of FI, particularly across the countries, are scarce. This study contributes by bridging this gap. The study is unique in its type as it takes into account the multiple steady states or club convergence. This study also contributes in policymaking by suggesting Club 1 countries (the Netherlands, Singapore and Switzerland) as the model ones for the FI.

The present research aims at analyzing the determinants of trade in forest products across BRICS and EU nations by using forest cover as one of the determining factors. For this purpose, a gravity model has been utilized for the country panel of BRICS and EU from 1996 to 2020. Five product categories corresponding to the forest trade (at HS-2 level) have been considered for the analysis. Further, Poisson pseudo maximum likelihood method has been used to estimate the gravity model. The study found that the forest cover of the trading nations from BRICS and EU has affected bilateral exports of primary wood products, wood pulp products, and related items significantly. The control variables included in the gravity model have resonated the results of existing literature. The study provides good policy insights on promoting trade in forest products by adopting appropriate forest conservation policies and other interventions that can help countries in increasing their respective forest covers.

For the rapid development of the economy and equal distribution of the development, Indian government has created special economic zones. These economic zones will act as a catalyst for the overall development of the region. Depending upon the resources and location each economic zone has been provided with the project. For the development of the region, it is must to know the strengths and weaknesses of the region. This study utilizes SWOT analysis to determine various internal and external factors which will impact Nagpur to be developed as the cargo hub for India. Thus provide a list of priorities for the organization and also help them to develop a strategic plan, keeping the external and internal factors in mind.

Gravity model of international trade established a fact that international trade of an economy is highly affected by the trade costs incurred locally and across borders.These costs are the difference between production cost of a traded commodity and its price paid by the ultimate buyers.The present study calculates the trade costs of Indian economy with its Asian trading partners.The study is developed in three stages: It measures the trade costs for India with its trading partners from the Asian region; it also estimates the determinants of trade costs by using the data on the available trade cost proxies; and thereafter, it decomposes the growth of Indian trade into the contribution of growth in income, the contribution of the decline in bilateral trade costs, and the contribution of the decline in multilateral resistance.It is found that the trade costs of India with all its Asian partners have declined throughout the whole study period (1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013).The decline in Indian trade costs was the highest in West Asia followed by Southeast Asia, East Asia, South Asia, and Central Asia.The variables, used as determinants of trade costs, namely: contiguity, distance, tariffs, non-tariff barriers, exchange rate, and port infrastructure, behaved according to the theoretical expectations.Furthermore, the decomposition of the growth of Indian trade with Asian partners revealed that the decline in the relative bilateral trade costs was the driving force of growth of Indian trade with all the Asian regions.

Neutrality hypothesis, which holds that there is no causality (in either direction) between these two variables.

PurposeThe present study is an attempt to evaluate the impact of the proposed India-China free trade agreement (FTA) in goods trade on both countries under a static general equilibrium framework.Design/Methodology/ApproachThe study has utilized the Global Trade Analysis Project (GTAP) model of world trade with the presence of skilled and unskilled unemployment in the world. For analysis purposes, 57 GTAP sectors, representing the whole regional economy, have been aggregated into 43 sectors and 140 GTAP regions, representing the whole world, have been aggregated into 19 regions. The study has also used the updated tariff rates provided by the World Trade Organization for better results.FindingsThe preliminary analysis using trade indicators depicted that by utilizing their own comparative advantage, both of the countries can maximize their gains by exporting more to the world. The simulation results from the GTAP analysis revealed that a tariff reduction in all goods trade would be more beneficial for both the countries than the tariff reduction in each other's specialized products. All other regions lose in terms of shifting the Indian imports towards China in a post-simulation environment. Regions with a significant loss are: the European Union (28 members), Southeast Asia, the Unites States, Japan, Korea, West Asia, and the European Free Trade Association (EFTA).Originality/ValueThe disaggregated sector-wise analysis has been performed using the latest available GTAP database, version 9.