{"title":"Factors determining cassava farmers’ accessibility to loan sources: Evidence from Lampung, Indonesia","authors":"A. Suryani, Masyhuri, Lestari Rahayu Waluyati","doi":"10.1515/opag-2022-0209","DOIUrl":null,"url":null,"abstract":"Abstract Credit accessibility is crucial for sustainable agricultural development. However, the difficulty in accessing credit has caused farmers to take many considerations when taking a loan. This research aims to determine the factors determining access and credit sources for cassava farmers in Lampung Province, Indonesia. Central Lampung was chosen as the research location because it had a total cassava production share of 36%. This study used Isaac’s and Michael’s formulae to determine the total samples. The data were collected by interviewing 263 respondents. Of 263 farmers, only 109 (41.4%) had access to loans. Data were analysed using the Multinomial Logit Regression Model to examine the factors determining access and credit sources for cassava farmers. Marginal effect analysis was also used to determine the probability of changes in independent variables. Regression results showed that the type of credit sources chosen by the farmers was determined by age, income, agribusiness experience, land size, education, organisation membership, and credit experience (R 2 = 89.1%). Partially, age, income, land size, education, credit experience, and business experience significantly influence the funding source. The results indicate that age, agribusiness experience, and land size are the main factors in choosing the types of credit. Land size has the biggest positive influence on farmers’ access to formal banks (11.49%).","PeriodicalId":45740,"journal":{"name":"Open Agriculture","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Agriculture","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/opag-2022-0209","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract Credit accessibility is crucial for sustainable agricultural development. However, the difficulty in accessing credit has caused farmers to take many considerations when taking a loan. This research aims to determine the factors determining access and credit sources for cassava farmers in Lampung Province, Indonesia. Central Lampung was chosen as the research location because it had a total cassava production share of 36%. This study used Isaac’s and Michael’s formulae to determine the total samples. The data were collected by interviewing 263 respondents. Of 263 farmers, only 109 (41.4%) had access to loans. Data were analysed using the Multinomial Logit Regression Model to examine the factors determining access and credit sources for cassava farmers. Marginal effect analysis was also used to determine the probability of changes in independent variables. Regression results showed that the type of credit sources chosen by the farmers was determined by age, income, agribusiness experience, land size, education, organisation membership, and credit experience (R 2 = 89.1%). Partially, age, income, land size, education, credit experience, and business experience significantly influence the funding source. The results indicate that age, agribusiness experience, and land size are the main factors in choosing the types of credit. Land size has the biggest positive influence on farmers’ access to formal banks (11.49%).
期刊介绍:
Open Agriculture is an open access journal that publishes original articles reflecting the latest achievements on agro-ecology, soil science, plant science, horticulture, forestry, wood technology, zootechnics and veterinary medicine, entomology, aquaculture, hydrology, food science, agricultural economics, agricultural engineering, climate-based agriculture, amelioration, social sciences in agriculuture, smart farming technologies, farm management.