Arfat Ahmad Sofi and Raja Sethu Durai S.
The purpose of this paper is to investigate convergence hypothesis in a balanced panel of 22 Indian states for the time period of 1980-81 to 2010-11 by applying nonparametric…
Abstract
Purpose
The purpose of this paper is to investigate convergence hypothesis in a balanced panel of 22 Indian states for the time period of 1980-81 to 2010-11 by applying nonparametric model setting in a panel framework.
Design/methodology/approach
The present study uses nonparametric and semi-parametric panel data methods to test the absolute and conditional convergence, respectively, and examines the income convergence using nonparametric panel data methods with state specific effects taken into consideration. These models are being estimated by the iterative process for a balanced panel of state wise per capita income and other conditioning variables for the time period of 1980-81 to 2010-11. For removing the fixed effects, the authors follow within transformation procedure according to the feasibility of the problem. Since convergence is estimated by regressing dependent variable on initial level of independent variable (as growth rate of income and per capita income in this case). So using usual transformation for removing the fixed effects is not feasible because by doing so the authors may end up with singular matrices on both sides of the regression model.
Findings
The results reject the null of parametric specification for both absolute as well as conditional convergence model. As to the outcome of the empirical analysis, the findings reveal that the Indian states are diverging in absolute sense and converging on conditional basis. Convergence happens to be consistent and conditional upon public expenditure, power generation share of primary and tertiary sector to Gross State Domestic Product.
Originality/value
The originality of the study is in its application of advanced methodology to highlight the model misspecifications while testing the convergence hypothesis in earlier literature.
Details
Keywords
Anandarao Suvvari, Raja Sethu Durai S. and Phanindra Goyari
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Practical implications
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.
Originality/value
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.
Details
Keywords
Arfat Ahmad Sofi and S. Raja Sethu Durai
This study aims to analyse the patterns of growth and income disparities and to have a future insight about its behaviour across 22 Indian states for the period from 1980-1981 to…
Abstract
Purpose
This study aims to analyse the patterns of growth and income disparities and to have a future insight about its behaviour across 22 Indian states for the period from 1980-1981 to 2010-2011.
Design/methodology/approach
This paper uses a three-stage methodological procedures to arrive at the results. First, the distributional aspect of per capita income has been analyzed by using Kuznets’s Inverted-U Hypothesis. Second, to analyse the relative performance across India states, the Shift Analysis Technique has been utilized. Finally, analyzing the future aspect of the growth and disparities among the low-, middle- and high-income states a catch process has been performed.
Findings
The empirical results rejects the Kuznets’s hypothesis for both aggregate and sectoral incomes across Indian states. The relative performance of Indian states shows signs of decreasing the income disparities over the time with a positive shift. Finally, the catch-up process among the low-, middle- and high-income states suggests different time bands for each group to narrow down or eliminate the income disparities in future.
Originality/value
This study contributes to the literature in three ways. First, examining the sectoral growth and disparities across Indian states by testing the Kuznets’s Inverted-U Hypothesis to highlight the specification issue; second, to measure the relative performance of Indian states over the time that can help us to find out the individual states that are purely responsible for income disparities in India. Finally, estimates of catch-up speed among Indian states provide a prediction about their behaviour to eradicate the disparities in future.
Details
Keywords
Priyanka Nayak and Pratap Kumar Jena
The purpose of this paper is to investigate how the rising domestic food price inflation in India is influenced by global macroeconomic factors like crude oil, exchange rate…
Abstract
Purpose
The purpose of this paper is to investigate how the rising domestic food price inflation in India is influenced by global macroeconomic factors like crude oil, exchange rate, foreign aid, global food prices and trade openness from January 1993 to December 2022.
Design/methodology/approach
The study has employed the structural break, autoregressive distributed lag cointegration tests to assess the stationarity and long-term relationship between the variables and the Toda–Yamamoto Granger causality test to demonstrate the causal relationship between the variables.
Findings
The study highlights the long-term relationships among variables, shedding light on the influence of global macroeconomic factors on domestic food price inflation in India. It reveals that food price inflation in India is positively influenced by crude oil prices and global food prices while being negatively affected by currency rates, foreign direct investment and trade openness.
Originality/value
Based on the findings, the study suggests that initiatives to reduce demand for crude oil and imported food products could help mitigate domestic food price inflation in India. Addressing the depreciation of the exchange rate is crucial to combat significant inflation in domestic food prices, calling for specific government interventions. Furthermore, promoting trade liberalization and foreign direct investment in the agricultural sector could help alleviate domestic food price inflation, emphasizing the importance of reducing customary trade barriers to encourage investment and trade openness.