Pub Date : 2015-06-30DOI: 10.1002/9781119705222.ch10
Jasmeet Kaur
Income distribution in India is largely divided into two major sectors- i.e. .primary and secondary. The percentage share of agriculture to India’s gross domestic product (GDP) has seen a steady decline in recent years and currently stands at 15%. This is attributable to the high growth rates in the industrial and services sectors of the economy. This chapter addresses the spatial pattern of sustainable agricultural development as a Composite Index of Agricultural Development (CIAD) and its relationship with rural poverty in India. The regression analysis leads to various findings through model building and analyzing the overall structure of poverty in India. The models represent various indicators of rural poverty and sustainable agricultural development and justify the relationship between the two. The vital feature is that the states having vast agricultural potential, such as Madhya Pradesh, Kerala and Orissa have remained at the lower rung of the development ladder due to their geographical configuration and social composition of the population (i.e. having a high percentage of scheduled castes (SC) and scheduled tribes (ST) in the population) along with poor irrigational facilities, which has been a constraint to the rapid diffusion of technological innovation in the agricultural sector. In these states, agriculture is still of subsistence nature and has not been commercialized. With the lowest composite scores, Assam suffers from unfavorable conditions for agriculture which are land availability, irrigation facility, high concentration of ST population, remote setting and low level of interaction with the more developed regions of the country. All this has acted as a major constraint to achieving a high a level of agricultural development. The CIAD model of rural poverty and related indices reveal that there is a higher concentration of rural poor in the slow-growing states like Bihar, Orissa, Madhya Pradesh and Uttar Pradesh. In these states, there still exists semi-feudal agrarian relation in the rural areas with a high concentration of SC and ST. On the contrary poverty is much lower in the prosperous regions of Punjab, Haryana, Andhra Pradesh, Kerala etc, resulting into relatively higher variability in regional distribution of rural poverty. These statistics demonstrate the need for India to urgently strive to break the cycle of poverty, credit burden and environmental degradation and improve the livelihood of farmers.
{"title":"Sustainable Agricultural Development and Rural Poverty in India","authors":"Jasmeet Kaur","doi":"10.1002/9781119705222.ch10","DOIUrl":"https://doi.org/10.1002/9781119705222.ch10","url":null,"abstract":"Income distribution in India is largely divided into two major sectors- i.e. .primary and secondary. The percentage share of agriculture to India’s gross domestic product (GDP) has seen a steady decline in recent years and currently stands at 15%. This is attributable to the high growth rates in the industrial and services sectors of the economy. This chapter addresses the spatial pattern of sustainable agricultural development as a Composite Index of Agricultural Development (CIAD) and its relationship with rural poverty in India. The regression analysis leads to various findings through model building and analyzing the overall structure of poverty in India. The models represent various indicators of rural poverty and sustainable agricultural development and justify the relationship between the two. The vital feature is that the states having vast agricultural potential, such as Madhya Pradesh, Kerala and Orissa have remained at the lower rung of the development ladder due to their geographical configuration and social composition of the population (i.e. having a high percentage of scheduled castes (SC) and scheduled tribes (ST) in the population) along with poor irrigational facilities, which has been a constraint to the rapid diffusion of technological innovation in the agricultural sector. In these states, agriculture is still of subsistence nature and has not been commercialized. With the lowest composite scores, Assam suffers from unfavorable conditions for agriculture which are land availability, irrigation facility, high concentration of ST population, remote setting and low level of interaction with the more developed regions of the country. All this has acted as a major constraint to achieving a high a level of agricultural development. The CIAD model of rural poverty and related indices reveal that there is a higher concentration of rural poor in the slow-growing states like Bihar, Orissa, Madhya Pradesh and Uttar Pradesh. In these states, there still exists semi-feudal agrarian relation in the rural areas with a high concentration of SC and ST. On the contrary poverty is much lower in the prosperous regions of Punjab, Haryana, Andhra Pradesh, Kerala etc, resulting into relatively higher variability in regional distribution of rural poverty. These statistics demonstrate the need for India to urgently strive to break the cycle of poverty, credit burden and environmental degradation and improve the livelihood of farmers.","PeriodicalId":340978,"journal":{"name":"International Journal of Research in Commerce, Economics and Management","volume":"263 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122905035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The study was conducted in Eastern Hararghe Zone of the Harari Regional State, Ethiopia. This study is intended to assess factors affecting loan repayment performance of Harari Microfinance Institution. The survey was conducted in three Kebele Associations having the maximum number of borrowers, by selecting 120 sample households through systematic random sampling between defaulters and non-defaulters of the MFI. Out of 120 borrowers, 50% were defaulters, and the remaining half was non-defaulters. Pre-tested structured interview schedule was used to collect primary and secondary data. Key informant interviews and focus group discussions were used to generate the necessary qualitative data. The collected data were analyzed by employing descriptive statistics and logistic regression (binary logit). A total of fifteen explanatory variables were included in the empirical model and out of these, nine were found to be statistically significant to influence the dependent variable. These significant variables are: Saving habit of borrowers, loan size, perception of borrowers on repayment period, source of income, availability of training, business experience, business type, family size, and the purpose of saving were found influencing loan repayment performance as evidenced from the model statistic (significant at 1, 5 and 10%). The econometric result revealed that the probability of default increases as the family size increases, when the borrower has negative perception on repayment period, less training, low business experience, poor saving habit and only single source of income. On the basis of the study findings, some recommendations were made to improve loan repayment performance in the study area. The strategy would be: Reducing family size through expanding family planning program, increasing borrower’s perception on repayment period through training, selecting business-experienced borrowers. The study also recommends a plan to assist borrowers in the study area to increase their business entrepreneurs’ skills through appropriate infrastructure, enhanced lendable funds in the microfinance institutions and business training for borrowers, enhanced loan amount and addressing challenges facing the microfinance institution. Key words: Binary logit, loan repayment, microfinance, performance, policy makers.
{"title":"DETERMINANTS OF LOAN REPAYMENT PERFORMANCE: THE CASE STUDY OF HARARI MICROFINANCE INSTITUTIONS","authors":"Firafis Haile","doi":"10.5897/JAERD2014.0622","DOIUrl":"https://doi.org/10.5897/JAERD2014.0622","url":null,"abstract":"The study was conducted in Eastern Hararghe Zone of the Harari Regional State, Ethiopia. This study is intended to assess factors affecting loan repayment performance of Harari Microfinance Institution. The survey was conducted in three Kebele Associations having the maximum number of borrowers, by selecting 120 sample households through systematic random sampling between defaulters and non-defaulters of the MFI. Out of 120 borrowers, 50% were defaulters, and the remaining half was non-defaulters. Pre-tested structured interview schedule was used to collect primary and secondary data. Key informant interviews and focus group discussions were used to generate the necessary qualitative data. The collected data were analyzed by employing descriptive statistics and logistic regression (binary logit). A total of fifteen explanatory variables were included in the empirical model and out of these, nine were found to be statistically significant to influence the dependent variable. These significant variables are: Saving habit of borrowers, loan size, perception of borrowers on repayment period, source of income, availability of training, business experience, business type, family size, and the purpose of saving were found influencing loan repayment performance as evidenced from the model statistic (significant at 1, 5 and 10%). The econometric result revealed that the probability of default increases as the family size increases, when the borrower has negative perception on repayment period, less training, low business experience, poor saving habit and only single source of income. On the basis of the study findings, some recommendations were made to improve loan repayment performance in the study area. The strategy would be: Reducing family size through expanding family planning program, increasing borrower’s perception on repayment period through training, selecting business-experienced borrowers. The study also recommends a plan to assist borrowers in the study area to increase their business entrepreneurs’ skills through appropriate infrastructure, enhanced lendable funds in the microfinance institutions and business training for borrowers, enhanced loan amount and addressing challenges facing the microfinance institution. \u0000 \u0000 \u0000 \u0000 Key words: Binary logit, loan repayment, microfinance, performance, policy makers.","PeriodicalId":340978,"journal":{"name":"International Journal of Research in Commerce, Economics and Management","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128502821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The fate of human settlement and development has taken place either through agriculture or it is largely affected by agriculture. The farmers are the only producers providing materials for other sectors to thrive on the demand and supply of basic raw material clearly evident from backward and forward linkages. In the recent economic system too each and every activity pertaining to Agriculture and Allied Activities has close relation with market environment. Recent surging food prices could be the best example of serious repercussions of broken link of farmers and the channel members such as wholesaler, retailer and other middle men in which wholesale price index for food articles has risen 17.5% since March 2009 and pulses by a steep 41.5%. Had the linkage among farmers and other marketing networks been incidentally appropriate, price of food products should have been accommodating with the contemporary market forces. The paper brings forth the issue of farmer to market linkage with the comprehensive look at the problem of participation of village community in the peri-urban industries and tapping of unutilized potential of rural markets and resources.
{"title":"Farmer to Market Linkages: Revamping Under the Emerging Value-Chain System","authors":"A. Bhadauria","doi":"10.2139/SSRN.2232629","DOIUrl":"https://doi.org/10.2139/SSRN.2232629","url":null,"abstract":"The fate of human settlement and development has taken place either through agriculture or it is largely affected by agriculture. The farmers are the only producers providing materials for other sectors to thrive on the demand and supply of basic raw material clearly evident from backward and forward linkages. In the recent economic system too each and every activity pertaining to Agriculture and Allied Activities has close relation with market environment. Recent surging food prices could be the best example of serious repercussions of broken link of farmers and the channel members such as wholesaler, retailer and other middle men in which wholesale price index for food articles has risen 17.5% since March 2009 and pulses by a steep 41.5%. Had the linkage among farmers and other marketing networks been incidentally appropriate, price of food products should have been accommodating with the contemporary market forces. The paper brings forth the issue of farmer to market linkage with the comprehensive look at the problem of participation of village community in the peri-urban industries and tapping of unutilized potential of rural markets and resources.","PeriodicalId":340978,"journal":{"name":"International Journal of Research in Commerce, Economics and Management","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130895475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}