Predicting risk of credit default using discriminant aproach:A study of tribal dairy darmers from Jharkhand

The study has identified the factors that discriminate defaulters from non-defaulters in the credit market using the survey data from 240 households. A discriminant function was employed to examine the relative importance of different socio-economic factors making borrowers to default. The magnitude of coefficient of the function is an indicator of the relative importance of individual variable. The study has suggested that higher per-capita income from crop production (38.72%), higher per-capita income from dairying (31.62%), percentage of expenditure in total income (16.87%), off-farm income sources (6.43%) and more earning adults in the family (6.36%) are the important factors to make the borrowers non-defaulters and vice versa for defaulters. Further, the confusion matrix of the derived classification analysis has cross-verified the predicted variable and has found the group classified correctly by 68.3 per cent. Hence, the model can be regarded to be valid in predicting a defaulter precisely based on the localized social factors. The study will help in addressing the concern of the credit institutions in assessing the credit risk capital and risk adjusted outcome for serving a larger group of smallholders community

Predicting risk of credit default using discriminant aproach:A study of tribal dairy darmers from Jharkhand

The study has identified the factors that discriminate defaulters from non-defaulters in the credit market using the survey data from 240 households. A discriminant function was employed to examine the relative importance of different socio-economic factors making borrowers to default. The magnitude of coefficient of the function is an indicator of the relative importance of individual variable. The study has suggested that higher per-capita income from crop production (38.72%), higher per-capita income from dairying (31.62%), percentage of expenditure in total income (16.87%), off-farm income sources (6.43%) and more earning adults in the family (6.36%) are the important factors to make the borrowers non-defaulters and vice versa for defaulters. Further, the confusion matrix of the derived classification analysis has cross-verified the predicted variable and has found the group classified correctly by 68.3 per cent. Hence, the model can be regarded to be valid in predicting a defaulter precisely based on the localized social factors. The study will help in addressing the concern of the credit institutions in assessing the credit risk capital and risk adjusted outcome for serving a larger group of smallholders community

Predicting risk of credit default using discriminant aproach:A study of tribal dairy darmers from Jharkhand

The study has identified the factors that discriminate defaulters from non-defaulters in the credit market using the survey data from 240 households. A discriminant function was employed to examine the relative importance of different socio-economic factors making borrowers to default. The magnitude of coefficient of the function is an indicator of the relative importance of individual variable. The study has suggested that higher per-capita income from crop production (38.72%), higher per-capita income from dairying (31.62%), percentage of expenditure in total income (16.87%), off-farm income sources (6.43%) and more earning adults in the family (6.36%) are the important factors to make the borrowers non-defaulters and vice versa for defaulters. Further, the confusion matrix of the derived classification analysis has cross-verified the predicted variable and has found the group classified correctly by 68.3 per cent. Hence, the model can be regarded to be valid in predicting a defaulter precisely based on the localized social factors. The study will help in addressing the concern of the credit institutions in assessing the credit risk capital and risk adjusted outcome for serving a larger group of smallholders community

Predicting risk of credit default using discriminant aproach:A study of tribal dairy darmers from Jharkhand

The study has identified the factors that discriminate defaulters from non-defaulters in the credit market using the survey data from 240 households. A discriminant function was employed to examine the relative importance of different socio-economic factors making borrowers to default. The magnitude of coefficient of the function is an indicator of the relative importance of individual variable. The study has suggested that higher per-capita income from crop production (38.72%), higher per-capita income from dairying (31.62%), percentage of expenditure in total income (16.87%), off-farm income sources (6.43%) and more earning adults in the family (6.36%) are the important factors to make the borrowers non-defaulters and vice versa for defaulters. Further, the confusion matrix of the derived classification analysis has cross-verified the predicted variable and has found the group classified correctly by 68.3 per cent. Hence, the model can be regarded to be valid in predicting a defaulter precisely based on the localized social factors. The study will help in addressing the concern of the credit institutions in assessing the credit risk capital and risk adjusted outcome for serving a larger group of smallholders community

Incidence and impacts of clinical mastitis in dairy cattle farms: case of Maharastra farmers

A cross sectional farm sample survey was conducted to assess the consequences of mastitis on farmer’s economy. Daily milk records of 187 animals from 28 farms were investigated by personal interview methods. Extra-resources used for the treatment and reduced revenues in terms of production were quantified and aggregated. The overall loss of mastitis from dairy animals was recorded Rs.1390.46 per lactation, in which 48.53 percent was from milk loss followed by veterinary expenses (36.57%), and additional cost of labour. Greater loss in crossbred due to its high production yield affected during the mastitis period. The cost of treating an animal is Rs. 508.52, includes cost of medicine (31.10 %) and services (5.47%). In farmer’s perception, inadequate sanitation, hygiene and veterinary services were the major factors responsible for occurrence of the disease. Therefore effective extension strategy suggested to make farmer aware to reduce incidence and improving profit margin of the farmer

Reappraising the Role of Eplerenone in the Management of Heart Failure

Background: In India, the prevalence of heart failure (HF) is increasing at 1.2/1,000 people according to a study in northern India, and the mortality rate at 1 year (INTERnational Congestive Heart Failure [INTER-CHF]) is 37%. Due to the diverse phenotypes of HF, nonadherence to guideline-directed medical therapy (GDMT), resistance to uptitration of medication and underuse of mineralocorticoid receptor antagonists (MRAs), such as eplerenone, a uniform management approach may not be feasible. This review is aimed at assessing the burden of HF, reasons for underutilization of MRAs in treatment, evaluating the evidence and reappraising the disease-modifying role of eplerenone in HF management. Methods: An electronic database search was performed to identify relevant literature. Results: The review details various studies that demonstrate the role of MRA eplerenone as a disease-modifying agent in patients with mild-to-moderate hypertension and those with acute myocardial infarction (MI) complicated by left ventricular dysfunction and HF. It also outlines different patient profiles for eplerenone use and ways to handle minor side-effects. Conclusions: Eplerenone shows a promising effect in selectively blocking aldosterone receptors to suppress fibrosis and reverse cardiac remodeling

Income Dynamics in Odisha: Evidence from micro level study

Micro level evidences suggest that per capita income of interior villages of Balangir is slightly better that Dhenkanal district. The variation in the income observed due to diversification in agriculture lead by vegetable production as second crop. The labour class recorded high per capita income in Bilaikani village. Salaried class income was relatively higher in dhenkanal villages over Balangir. Watershed development and irrigation management during rabi season crop holds the key for income diversification in the study area

Poverty and Agricultural development Scenario in Orissa: A Regional Analysis

The preliminary study of meso data at the district level and panel data of the sampled viI/ages made under the project ViIlage Dynamics Studies in South Asia(VDSA) in the two sampled districts of Orissa reveal interesting pictures with respect to poverty incidence, asset holding pattern, size class-wise land holding pattern, agricultural productivity, livestock owning and natural resource endowment. Poverty in Orissa, an eastern coastal state of India has been a matter of great concern for successive governments and planning authorities at the national and state levels. The eastern state has been under scrutiny by the national planning authorities and a number of poverty alleviation programme launched in the country have focused Orissa as a test case of impact of development initiatives. However, the state has failed to catch up with national poverty reduction efforts due to plethora of socio-economic, historical, political, administrative and natural reasons. It is estimated that during 2004-05, the incidence of rural poverty was 47 and for urban Orissa it was 44 as against the average poverty incidence of 26 for India. The social grouping of people under poverty in the state reflects that the poor scheduled tribes constitute as high as 76 in rural areas and 65 in the in urban areas respective category of population. The region-wise break up of rural and urban poverty in the stare indicates that the southern Orisso suffers from highest incidence of poverty followed by western, northern and eastern Orissa. The districts like Nuapoda, Balangir, Kalahandi, Koraput are grouped under highest poverty incidence region in the state. The two district sampled for study namely Bolangir (48.79 of population below poverty) under Western Orissa and Dhenkanal (47.53 of population below poverty) under north eastern high lands reveal different scenarios of poverty under different social groupings. The analysis of Ginni coefficient and Theil entropy measures in one of the sampled villages in Dhenkanal district under the project were found to be 0.7and 0.9 respectively. There is differential pattern of land holdings which highly skewed in favour of large farmers in all the study villages. The occupational composition of population, sex ratio, the age group distribution of population, farm mechanization, agricultural productivity and migration pattern also reveal diversified pattern under different size class and social groups

Dynamics of Poverty and Food Insecurity in Orissa:Macro Analysis and Case Studies

Based on meso data, study analyses the causes of poverty and food insecurity. It seeks to identify who is food insecure and where they are, why they risk food insecurity and what options exist to reduce their vulnerability. Using the sustainable livelihoods framework and collecting qualitative and quantitative data from two selected districts of Balangir and Dhenkanal under Village Level Studies Project, the paper looks at five livelihood groups, notably marginal and small scale farming households, labouring rural households, mining worker households, rural artisan households and scheduled tribal households. Even though Orissa is virtually self-sufficient in food grains, there is a significant prevalence of food insecurity in the state and around 9 percent of the population are classified as extremely food insecure consuming less than 1,800 kcal per day. The situation varies significantly within the state: 15 percent of the population in the southern region are extremely food insecure compared to 3 percent of the population living in the coastal areas. The study finds that food insecurity and vulnerability are mainly caused by a limited physical as well human asset base, slow economic growth, limited or no access to welfare provisions and public services, lack of land reform and difficulties in accessing credit institutions. Based on the findings of the analysis, the paper identifies key interventions to address the immediate food needs of the most vulnerable and to stimulate rural development, in particular promoting agriculturally linked livelihoods. Proposed interventions include increased investment in agricultural research, improved watershed development, developing financial services and promoting small scale industries as well as micro enterprises and strengthening anti-poverty programmes within the state. The two district sampled, where more or less half population are under poverty. Livelihood options are limited and skewed towards large farmers in the study villages. Differential land holding, occupational diversification, migratory pattern and agricultural productivity hold key factors of poverty across farmer category and size holding

Income Dynamics in Odisha: Evidence from micro level study

Micro level evidences suggest that per capita income of interior villages of Balangir is slightly better that Dhenkanal district. The variation in the income observed due to diversification in agriculture lead by vegetable production as second crop. The labour class recorded high per capita income in Bilaikani village. Salaried class income was relatively higher in dhenkanal villages over Balangir. Watershed development and irrigation management during rabi season crop holds the key for income diversification in the study area