https://ir.vidyasagar.ac.in/jspui/handle/123456789/5401 Sun, 26 Apr 2026 01:47:28 GMT 2026-04-26T01:47:28Z https://ir.vidyasagar.ac.in/jspui/handle/123456789/5412 Title: Efficiency of Indian Textile Manufacturing Sector and its Determinants: Evidence Based on Non Parametric Data Envelopment Analysis Authors: De, Sanchita; Ghose, Arpita Abstract: This paper estimates technical efficiency (TE) of Indian textile firms (ITF) using nonparametric Data-Envelopment- Approach and exploring CMIE data for the period 1995-2016. It finds out the determinants of TE considering the effect of R&D- intensity, firms-size , export-intensity, marketing-intensity, advertising-intensity, total import-intensity and its different components like import of raw materials, stores and spares , capital goods in a panel regression framework. Whether TE improves after the withdrawal of multi-fiber-trade-agreement since 2005 is tested. The average level of TE over the sample years is 0.864, only 17% of the total sample firms are efficient, indicating prevalence of high technical-inefficiency. After 2005, the TE level increases but the TE curve became flatter, implying a decline in the rate of change of TE. Since ITF import a lot of textile-yarn and also re-export it, export and import data are correlated. Separate panel regressions are resorted with export and import as separate regressor. Considering all the factors, the impact of (i) Advertising is positive and linear,(ii) R&D, export and firm size are non-linear with positive marginal effects, (iii) total-import is positive;(iv) imports of capital goods (IMCAP) is insignificant, with significant positive and negative marginal effects of import of stores and spare (IMSTR) and raw materials (IMRAW) respectively; implying positive effect of IMSTR dominates over negative effect of IMRAW, so that on balance total import produces positive effects, (v)net export is negative implying effect of imports dominates over exports. Mon, 01 Jan 2018 00:00:00 GMT https://ir.vidyasagar.ac.in/jspui/handle/123456789/5412 2018-01-01T00:00:00Z https://ir.vidyasagar.ac.in/jspui/handle/123456789/5411 Title: Financial Inclusion in India and its Impact on Development and Poverty Authors: Ahuja, Kanhaiya; Phatak, Sujay S Abstract: This paper aims at analysing the situation of financial inclusion in India. For this purpose, an index is developed which suggests presence of vast inter-state variations in financial inclusion in India.The study further reaches out to seek whether financial inclusion affects growth and standard of living in different states of the country. The results suggest that the level of financial inclusion is very poor in most of the states and further analysis points a direct relation of financial inclusion with growth and standard of living while a negative relation with poverty. Mon, 01 Jan 2018 00:00:00 GMT https://ir.vidyasagar.ac.in/jspui/handle/123456789/5411 2018-01-01T00:00:00Z https://ir.vidyasagar.ac.in/jspui/handle/123456789/5410 Title: Construction of Education Index for the Blocks of Paschim Medinipur District: An Appraisal through the Application of Average Correlation Method Authors: Pattanayek, Sanjoy Kumar; Mookherjee, Subikash; Mondal, Debasish Abstract: This article is carrying the objective to assess the role of education as a development indicator for all the 29 blocks of undivided Paschim Medinipur district for a selected period of 2005–06 to 2014–15. This purpose is fulfilled through the construction of Education Index (EI) in which the weights of the underlying indicators are determined by the application of Iterative Average Correlation Method (Mondal, Mookherjee & Pattanayek, 2017; International Journal of Management and Development Studies, 6[10], 28–36). The EI, thus constructed, is observed to have data-driven weights of 35.35% for gross enrolment index (GEI) and 64.65% for adult literacy index (ALI). Moreover, this EI is experiencing high inter-block and high inter-temporal variations for the said period. These variationsare explained by some of the selected factors of educational attainment, namely, by applying fixed effect model and random effect model in the panel data framework and by applying pooled data model to obtain their relative statistical importance on the basis of their ortho-partial correlation (Mondal, 2008; Communication in Statistics—Simulation and Computation, 37[4], 713–730) and average correlation values. From the pooled regression results, it appears that the SCSTR is the most important factor with the relative importance of 0.3336 out of 0.7888. Mon, 01 Jan 2018 00:00:00 GMT https://ir.vidyasagar.ac.in/jspui/handle/123456789/5410 2018-01-01T00:00:00Z https://ir.vidyasagar.ac.in/jspui/handle/123456789/5409 Title: India’s Public Healthcare System in Different Dimensions: An Econometric Review across Major Indian States from 1981-2015 Authors: Mukherjee, Sovik; Basumallik, Soumak Abstract: The objective of this paper is to take a closer look at the liaison between the two focus variables viz. growth and public healthcare expenditure, and the associated implications for public health infrastructure development and related health inequality. We make use of panel cointegration and causality in a Vector Error Correction Mechanism (VECM) framework using panel data from 1981-2015. Though reducing health inequalities is an important policy agenda, till now research on health inequality has been mostly concentrating on the developed countries and there is a very scant literature in the Indian context and herein lies our contribution to the existing literature. India, being a developing country, now has comprehensive datasets for some socio-economic health indicators like, — Life Expectancy Rates, Infant Mortality Rates, Total Fertility Rates, etc. and their related disparities. Hence, research on health inequalities could be instrumental in drawing attention to the health of socio-economically vulnerable groups. In this endeavour, we have tried to examine the inequality in two crucial health related variables, ‘life expectancy at birth’ and ‘infant mortality rates’ for 23 major states in India. To do this, we have used the tool of the Concentration Index (CI), a frequently used indicator of the socio-economic inequality of health. To give more tangible policy directions on the position of public healthcare infrastructure vis-à-vis health inequalities, we have used Euclidean distance function approach to construct a public health infrastructure index (PHII) across 23 major states in India for two terminal time points i.e. 2005-06 and 2014-15. This index will be serving as a measure for evaluating the variations in the inter-state performance in public healthcare infrastructure and related implications thereof. Mon, 01 Jan 2018 00:00:00 GMT https://ir.vidyasagar.ac.in/jspui/handle/123456789/5409 2018-01-01T00:00:00Z