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This paper aims to investigate the relationship between firm size and growth under the framework of Law of Proportionate Effect (LPE) for Asian firms.

An unbalanced panel data for about 12,001 unique non-financial listed and active firms from 1995 to 2016 for 12 industrial and emerging Asian economies was examined. Total assets and net sales were used as size variables. Firm-specific variables such as return on equity, leverage and liquidity ratio were used along with macroeconomic variables such as GDP growth and two financial development indicators. The fixed effects and random effects approach were used to estimate the dynamic growth model after taking into account econometric issues such as correlation between the cross-country-specific error component and the regressors and heteroscedasticity.

The estimated coefficient of firm size was found to be always significant and negative rejecting the Gibrat’s law for Asian firms confirming that the small-sized firms are growing faster than larger-sized firms. Also, the persistence of growth coefficient suggested that a positive persistence of firm growth does not exist for the selected Asian firms. Gibrat’s LPE was also rejected across small, medium- and large-sized companies. For the aggregate sample, the coefficient of leverage was found to be negative and significant, whereas liquidity ratio, GDP growth, banking sector and stock market variables are found to have positive and significant relationship with growth of firms. For individual economies, a mix of positive and negative (significant and insignificant) estimated coefficient was observed.

At macro-level, the examination of firm growth is likely to have significant policy implications for the regulators and various government agencies as firm growth may increase economic activity in general and employment opportunities in particular. The policymakers can control economic and employment activity by designing specific firm growth policies. At micro-level, the study will have significant implications for managerial decision-making.

To the best of the authors’ knowledge, this is one of the first studies to test the validity of Gibrat’s LPE for large Asian economies and firms using recent data under a dynamic growth framework using firm-specific and macroeconomic variables. Also, persistence of growth of firms under LPE (that growth does not persist from one period to the next) is uniquely examined for Asian firms.

This paper examines the determinants of concurrent adoption of farm risk management strategies by rice growers in two different ecosystems of Telangana agriculture-irrigated and rainfed ecosystems.

The primary data have been collected from the rice growers in two different ecosystems, and after checking the variance inflation factor (VIF) for controlling multicollinearity, a multinomial logit model has been used to examine the determinants of concurrent adoption of coping strategies by rice growers.

The study finds that adopting one risk management strategy persuades farmers to embrace other strategies, reducing the risk in agriculture between the two ecosystems. Among the determinants, farmers' age, education, contact with extension services, irrigation sources, livestock income, total farm income, crop loss reasons, and crop insurance awareness significantly influence the adoption of various risk management measures. However, considerable heterogeneity is found among the driving forces across the rice ecosystems.

The major policy implications that can be drawn from the analysis are increased access to information through government-funded extension services and the provision of alternative risk management technologies, such as drought-resistant or flood-resistant seeds, farmers' field schools and increased provision of crop insurance, farmer-friendly agriculture extension services, and farm investment support, are critical for assisting farmers managing risks. In addition, however, there should be ecosystem-specific policies to tackle the ecosystem heterogeneity.

This paper is very timely and entails some relevant policy implications for the development of Indian agriculture.

This paper aims to evaluate the effects of climate variables on the mean yield and yield variability of major pulse crops in the Telangana state of India.

Authors have estimated the Just and Pope (1978, 1979) production function using panel data at the district level of four major pulses in nine former districts of Telangana for 36 years during 1980–2015. A three-stage feasible generalized least squares estimation procedure has been followed. The mean yield and yield variance functions have been estimated individually for each of these study crops, namely, Bengal gram, green gram, red gram and horse gram.

Results have shown that changes in climatic factors such as rainfall and temperature have significant influences on the mean yield levels and yield variance of pulses. The maximum temperature is observed to have a significant adverse impact on the mean yield of a majority of pulses, and it is also a risk-enhancing factor for a majority of pulses except horse gram. However, the minimum temperature is positively related to the mean yields of the study crops except for Bengal gram, and it is having a risk-reducing impact for a majority of study crops. Rainfall is observed to have a negative impact on the mean yields of all pulses, but it is a risk-enhancing factor for only one crop, i.e. Bengal gram. Thus, rising temperatures and excess rainfall are not favorable to the productivity of pulses in study districts.

The present study is based on the secondary data at the district level and is considering only one state. Season-wise primary data, including farm-specific characteristics, could have been better. The projected climate change and its impact on the mean yields and yield variance of pulses need to be considered in a future study.

According to the best of our knowledge, this is the first study to empirically evaluate the impact of climatic variables on the mean yields and yield variability of major pulses in Telangana using a panel data for major pulses and nine districts of 36 years time-series during 1980–2015. The study has given useful policy recommendations.

This work aims to empirically investigate the effects of financial development on crop productivity of India.

Time series data such as crop production index, International Monetary Fund’s (IMF) financial development index, gross domestic product (GDP) per capita, arable land, rural population, trade openness and physical capital from 1980 to 2020 was used. The autoregressive distributed lag (ARDL) bounds testing approach of cointegration was used to determine the long-run equilibrium relationship between the selected time series. Also, ARDL long- and short-run coefficients were estimated to examine the effects of selected variables on crop productivity. Furthermore, to establish the robustness of results, long-run estimators such as fully modified least squares and the dynamic least squares were also used. Finally, using the vector error-correction model, causality between the selected time series was examined.

The ARDL cointegration test confirmed the existence of long-run equilibrium relationship among agricultural productivity, financial development, capital formation, GDP per capita, arable land, rural population and trade openness. The estimated long-run elasticities from all the three techniques and the short-run elasticities of ARDL have consistently suggested that the elasticity of financial development is higher (1.55% and 1.40%, respectively) in explaining the crop productivity of India. The short-run causality estimates indicated the presence of positive bidirectional causality between crop productivity and financial development and seven positive unidirectional causal relationships between the selected variables.

Agricultural credit being an important non-land input and essential for overall growth and sustenance of agricultural sector, the policymakers should ensure the overall development of its financial sector which will reduce the intermediation, informational and other transactional costs associated with agricultural credit. This will possibly result in timely availability and access to adequate and low-cost credit from institutional sources.

Though extensive research is available on the effects of financial development on economic growth, limited research is available concerning the impact of financial development on crop productivity, especially for an emerging economy like India. For India, predominantly studies have investigated the impact of farm credit on crop productivity but have not exclusively examined the effects of financial development on agricultural productivity. Therefore, this study not only adds to the empirical literature but also provides new evidence on the nexus between financial development and crop productivity by examining the effects of financial development on crop productivity using the composite financial development index developed by the IMF using the ARDL bounds test for cointegration and other econometric estimators.

This study conducts an analysis of the interplay between governance quality, environmental expenditure of the government, and pollution emissions (measured as CO2 emissions) within the BRIC economies.

Utilizing the FMOLS model and marginal effects, we investigate the influence of governance quality and environmental expenditure on environmental quality (CO2 emissions) over the period 1996–2020. We took data for Brazil, Russia, India and China. We excluded South Africa due to its due to its small economic size relative to other BRIC economies, sluggish industrial growth and deteriorating foreign trade which gives contrast outliers to our data.

Results indicate that government investments in environmental protection contribute to a reduction in CO2 emissions. However, the effectiveness of these expenditures is contingent upon the quality of governance. This underscores the significance of robust governance for realizing meaningful reductions in air pollution through environmental spending. Further, increase in GDP per capita and the industrial sector's share of GDP are associated with a significant rise in CO2 emissions across BRIC economies. Conversely, FDI and trade openness exhibit a negative impact on CO2 emissions, with this effect gaining greater resilience when accounting for governance factors.

Like any other studies, the present study also suffers from some limitations. First, besides air quality, environmental quality encompasses multiple dimensions and various characteristics such as water purity, noise pollution, open space access, visual effects of buildings etc. But the present study included only CO2 (air quality) as a proxy of environmental quality due to various problems of data and methods. Second, CO2 (carbon dioxide) emission, which is the dependent variable in our model, is actually influenced by various quantitative and qualitative (both natural and man-made) factors. We included only nine independent variables. However, we could not include many variables due to lack of consistent data. Third, this study included only four countries – Brazil, Russia, India and China (BRIC) and excluded South Africa which is a member of the BRICS block due to its economic size, sluggish industrial growth and deteriorating foreign trade which gives contrast outliers to our data set of the four BRIC countries. Therefore, the future research may be carried out by addressing those issues for better understanding of the environmental problems, governance and policies thereon.

(i) Establish environmental governance committees – The four BRIC countries including South Africa should form a committee comprising government, civil society, and private sector representatives for comprehensive oversight and collaboration in environmental governance. (ii) Invest in capacity building for environmental institutions – Allocate resources to enhance environmental institutions' capacity through training, data improvement, and enforcement strengthening. (iii) Implement green procurement policies – Encourage green procurement in government agencies to drive demand for eco-friendly products and services, promoting sustainable practices. (iv) Incentivize green technology development – Offer tax credits or subsidies to stimulate green technology adoption, including renewable energy and sustainable agriculture. (v) Promote sustainable urban development – Prioritize sustainable urban strategies like public transportation investment and green space promotion to mitigate urbanizations' environmental impacts. (vi) Enhance cross-border cooperation – Foster collaboration on transboundary environmental issues among four BRIC nations including South Africa, including joint research and policy responses. (vii) Promote green finance and investment – Mobilize green finance to support sustainable development projects through instruments like green investment funds and bonds.

This study distinguishes itself by offering a unique analysis of both individual and combined effects of governance and environmental expenditure on environmental quality. Additionally, it encompasses various dimensions of governance, an aspect rarely explored in the BRIC countries.

The purpose of this paper is to empirically examine the impact of financial integration on macroeconomic volatility for developing and emerging economies of Asia.

The effects of financial integration and dynamics of macroeconomic volatility over time and across different groups of Asian economies vis-à-vis advanced economies are investigated using four different variables such as consumption, output, income and the ratio of consumption to income. Further, an empirical link between the degree of international financial integration and macroeconomic volatility for Asian economies is econometrically investigated using generalized method of moments (GMM) system one-step estimator.

Macroeconomic volatilities of per capita output and consumption growth tend to be lower for advanced economies compared to Asian economies. The computed cross-sectional median of the volatility of consumption, output, income and the ratio of consumption volatility to income suggested that the volatility of advanced economies is lower compared to all the regions of Asia. GMM results suggested that the financial openness, trade openness and broad money are negatively and significantly associated with macroeconomic volatility whereas inflation is positively and significantly associated with macroeconomic volatility but the magnitude of trade openness is found to be negligible.

The present study has not included the effects of other country-specific variables (such as fiscal policy volatility) and other external factors to understand macroeconomic volatility.

High integration of economies promote economic growth, reduce macroeconomic volatility and reduce vulnerability to external shocks. This implies that policy makers should thrive to reform and create institutional infrastructure to deepen the integration.

The paper is an important empirical contribution toward examining the effects of financial integration on dynamics of macroeconomic volatility for a large number of Asian developing and emerging economics over time and across different groups using recent data and latest analytical framework and techniques.

The main purpose of this paper is to examine the relationship between financial inclusion and financial stability in South Asian countries.

To measure the financial inclusion, a multidimensional time-varying index is constructed following the Human Development Index method. The long-run relationship between financial inclusion and financial stability is examined by using the panel cointegration test, fully modified ordinary least squares and dynamic ordinary least squares approaches to show the long-run elasticity of explanatory variables on dependent variables. Further, Dumitrescu-Hurlin panel causality test is used to find the direction of causality between financial inclusion and financial stability. Data set is of annual frequency of seven countries for the period from 2004 to 2018.

The empirical findings of this study confirm that financial inclusion has a positive and statistically significant impact on financial stability. These results suggest that South Asian countries can attain long-run financial stability by improving the coverage of financial inclusion. Further, panel causality test shows a unidirectional causality from financial inclusion to financial stability.

The major limitation of the study is the availability of time series data for all important variables. Various socioeconomic variables can be used to measure financial stability, but this study included only the Z-score as the proxy for financial stability. Due to the data constraint, this study is unable to use the time series econometric analysis.

As the study confirms that financial inclusion is one of the main drivers of financial stability, it is suggested that the policymakers should emphasize on financial sector reforms to enjoy financial stability in the long run, especially in developing countries. So governments and policymakers of study countries need to address the issues involved in access to financial services to increase financial stability. Furthermore, it is also important to remove limitations of access to formal financial services for marginalized sections of the society with proper supervisions.

This is a new contribution on the present topic. This study has constructed a new multidimensional financial inclusion index (FII) following the Human Development Index method for South Asian countries based on annual data and using ten indicators of formal financial services related to availability, accessibility and usage. To the best of the authors’ knowledge and information, this is the first study on South Asian countries to construct and apply the new multidimensional FII. Further, the study examines the long-run elasticity of financial inclusion on financial stability employing FMOLS and DOLS approach.

Traditional statistical methods to study the financial performance of any industry have many barriers and limitations in terms of the statistical distribution of the financial ratios, and, in particular, it considers only its positive values of it. The purpose of this paper is to estimate the financial performance of 24 Indian life insurance companies for the period from 2013 to 2016 using Grey relational analysis (GRA) proposed by Deng (1982) that accommodates the negative values in the analysis.

Financial performance of 24 Indian life insurance companies for the years from 2013–2014 to 2015–2016 is examined using a total of 14 indicators from capital adequacy ratios, liquidity ratios, operating ratios and profitability ratios (PR). The methodology used is GRA to obtain the Grey grades to rank the performance indicators, where higher relational grade shows better financial performance, and a lower score depicts the scope for improving the performance.

The results rank the insurance companies according to their financial performance in which Shriram insurance stands first with higher relational grade score, followed by the companies like IDBI Insurance, Sahara Insurance and Life Insurance Corporation of India. The main finding is that PR which have negative values are playing a crucial role in determining the financial performance of Indian life insurance companies.

This study has far-reaching practical implications in twofold: first, for the Indian life insurance industry, they have to concentrate more on PR for better financial health and, second, for any financial performance analysis, ignoring negative value ratios produce biased inference and GRA can be used for better inference.

This study is the first attempt to evaluate the financial performance of Indian life insurance using the GRA methodology. The advantage of GRA is that there is no restrictions on the statistical distribution of the data and it also accommodates the negative values, whereas all the other traditional methods insist on the statistical distribution of data, and, more importantly, they cannot handle negative values in the performance analysis.

The purpose of this paper is to examine the market response of apple growers to price and price risk along with weather factors and weather risk in the state of Jammu & Kashmir. In other words, it tries to find the both short-run and long-run price elasticities of apples' market arrival and also the elasticity with respect to price-risk and weather-risk variables.

This paper uses the bound test approach of “auto-regressive distributed lag” (ARDL) model. Monthly data on market arrival of apples and respective prices along with other nonprice factors are used.

The bound test approach of ARDL confirms the existence of long-run relationship between the market arrival of apples and price and nonprice factors. The market response to price is found to be inelastic both in shortrun and longrun. The risk coefficients are negative indicating that apple growers are risk averse. However, they do respond strongly to weather risk than price risk.

Weather insurance must be provided to the apple growers to safeguard their production loss due to weather risks. Proper infrastructure in the form of storage facilities, marketing information, transport and communication to local markets should be provided to them. Unavailability of data at the district level poses a great difficulty to have a panel data analysis. But future research can be initiated to bridge this gap.

This paper considers the market response of apple growers under both price risk and weather risk which is first in its nature. The authors have not found any other paper discussing this in the case of apple in India.