scholarly journals Rural Credit and Rural Development: Some Issues

1984 ◽  
Vol 23 (2-3) ◽  
pp. 273-285
Author(s):  
Sarfraz K. Qureshi ◽  
Kalbe Abbas ◽  
Ahmed Naeem Siddiqui ◽  
Ejaz Ghani
Keyword(s):  
Rural Areas ◽  
Green Revolution ◽  
Policy Instrument ◽  
Rapid Expansion ◽  
Working Capital ◽  
Occupational Groups ◽  
Policy Makers ◽  
Access To Credit ◽  
Rural Credit ◽  
Rural Income

Credit is an important instrument of acquiring command over the use of working capital, fixed capital and consumption goods. In the wake of Green Revolution, land and labour have receded into the background as predominant factors of growth. Use of capital and adoption of modern techniques of production which have become major sources of growth of agricultural output necessitate access to credit markets for financing their use. Institutional sources of credit have become quite significant during the last few years. The rapid expansion of credit from institutional sources can be seen from various indicators. The total disbursement of agricultural loans has gone up from Rs. 306.75 million in 1972-73 to Rs. 5,102.14 million in 1981-82. On a per acre basis, the loans increased from Rs. 7.33 in 1972-73 to Rs. 106.83 in 1981-82. In this perspective, the disparities in income and wealth in rural areas would crucially depend on the distribution of capital among farms of different sizes and occupational groups. Neglecting equitable distribution of credit as a policy instrument for rural income redistribution may be a serious omission by the policy makers interested in an improvement of rural equity.

scholarly journals Demographic Determinants of Access to Bank Credit

2020 ◽  
Vol 8 (5) ◽  
pp. 3272-3275
Keyword(s):  
Rural Areas ◽  
Banking Sector ◽  
Financial Inclusion ◽  
Bank Credit ◽  
Urban District ◽  
General Belief ◽  
Policy Makers ◽  
Access To Credit ◽  
Study Results ◽  
Gender Education

The main objective of the paper is to study the determinants of access to bank credit, an important dimension of Financial Inclusion in India. For this purpose we studied if access to bank credit depends on district, gender, education and literacy. The data was collected from Jogulamba with lower literacy rate and Ranga Reddy a semi urban district in the Telangana. A semi structured questionnaire was prepared for the data collection. Regression analysis has been used to analyze the data for the study. Results show that access to credit for districts is significant which is contrary to general belief that in rural areas the credit from banking sector is less. Education is also significant and positive which implies that educated people prefer credit from banks compared to uneducated. This has important implication for policy makers to focus more on education and Financial Inclusion will follow.

Rural credit input, labor transfer and urban–rural income gap: evidence from China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Guohua Yu ◽  
Zheng Lu
Keyword(s):  
Rural Areas ◽  
Industrial Structure ◽  
Content Type ◽  
Rural Credit ◽  
Income Gap ◽  
Rural Income ◽  
Urban Rural ◽  
Labor Transfer ◽  
Theoretical Mechanism ◽  
Agricultural Industries

PurposeThe purpose of this study is to elaborate the theoretical mechanism of rural credit input affecting the urban–rural income gap from the perspective of labor transfer, and use a dynamic panel mediation model to test the transmission mechanism of rural credit input affecting the urban–rural income gap through labor transfer, so as to provide an empirical basis for narrowing the urban–rural income gap in China.Design/methodology/approachThis paper constructs a mechanism analysis framework for rural credit input affecting the urban–rural income gap. From the perspective of resource allocation and labor transfer, the authors expound the transmission path of rural credit input to the urban–rural income gap and analyze the theoretical mechanism of rural credit input that affects the urban–rural income gap through labor transfer. Based on this, this paper uses the dynamic panel mediation model to test the effect relationship between rural credit input, labor transfer and urban–rural income gap in 31 provinces of China from 2009 to 2018.FindingsIn theory, increasing rural credit input can ease the financial constraints on the development of “agriculture, rural areas and farmers” and provide capital accumulation for the development of rural non-agricultural industries. The development of rural non-agricultural industries can provide more jobs for rural surplus labor, thereby increasing the labor rate of return in rural areas, and ultimately conducive to narrowing the urban–rural income gap. Further, increasing rural credit input can improve the development level of rural non-agricultural industries, thereby promoting the transfer of agricultural labor. At the same time, rural credit input based on the intermediary variable of labor transfer has a significant inhibitory effect on the urban–rural income gap.Research limitations/implicationsThis study mainly focuses on the relationship between rural credit input, labor transfer and urban–rural income gap, so it is impossible to use micro-level data to further verify the impact of rural credit input on labor transfer. At the same time, the collection of indicators of rural credit investment in the China Financial Yearbook only started in 2009, which limited the number of samples to a certain extent.Practical implicationsThis paper assumes that the economy is mainly composed of urban and rural economic sectors. Therefore, labor can flow freely between urban and rural areas. However, in the near future, China's rural secondary and tertiary industries may develop rapidly, especially with the in-depth implementation of rural revitalization strategy, it is very important to pay attention to the current situation of rural industrial structure and incorporate the factors such as rural industrial structure into the existing model.Social implicationsThis study attempts to provide a new perspective and inspiration for rural credit input, the optimal allocation of labor force and narrowing the urban–rural income gap under China's rural revitalization strategy.Originality/valueBased on the analysis framework of neoclassical economic theory, this paper uses the constant elasticity of substitution production function to establish an urban–rural two-sector nested model that includes credit supply variables and analyzes the mechanism of rural credit input affecting the urban–rural income gap through labor transfer.

scholarly journals Credit for Rural Poor in Pakistan

1995 ◽  
Vol 34 (4II) ◽  
pp. 769-778
Author(s):  
Sarfraz Khan Qureshi
Keyword(s):  
Interest Rates ◽  
Rural Areas ◽  
Financial Services ◽  
Local Level ◽  
Green Revolution ◽  
Adverse Side Effect ◽  
Rural Poor ◽  
Rural Credit ◽  
Interest Policy ◽  
Credit Institutions

Farmers, large and small, and the non-farm population in rural areas all suffer from the liquidity constraint. Credit is needed to acquire command over the use of working capital, fixed capital, and consumption goods. The Green Revolution technologies have increased the credit requirement for modern inputs and farm investment. A new expanded role of rural credit institutions has emerged in the wake of the technology revol~tion in rural areas. Two distinct approaches have been used to provide the financial services to the rural poor. The most widely favoured approach in the past was the use of subsidised interest rates with a portion of credit reserved for the poor. The low interest policy was based on the premise that it would induce farmers, large and small, to use modern' inputs on a larger scale. One of the adverse side-effect of this policy was the introduction of an element of financial unsustainability in the loan portfolios of the credit institutions. The recent view about the delivery of rural credit consists of using market interest rates and using a mixture of 'bottom-up initiatives' at the local level, using non-government groups and 'top-down initiatives' by the formal credit institutions in terms of the simplification of the procedures and decentralisation of the credit operation for credit supply to the rural poor. In this paper, an attempt is made to evaluate the efficacy of these two approaches in the case of Pakistan for delivering credit to the rural poor.

Assessment of Regional Inequality in Female Work Participation: Measurement of Disparity and Determinants

2020 ◽  
Vol 3 (1-2) ◽  
pp. 1-10
Author(s):  
Sheuli Ray ◽  
Manoj Debnath
Keyword(s):  
Gender Gap ◽  
Rural Areas ◽  
Agricultural Sector ◽  
Green Revolution ◽  
Work Force ◽  
Middle Part ◽  
Work Participation ◽  
Secondary Sources ◽  
Participation Of Women ◽  
Female Work Participation

The regional difference of complex Indian social structure and customs have a different impact on the nature of women’s work participation. The present study aims at unravelling the influence of social, cultural and economic forces in differentiating the level of women work participation in different eco-regions of West Bengal. The study is based purely on secondary sources and data have been collected from the Census of India. It is in the rural areas that the female work participation is directly linked to agriculture and allied activities and the study confines itself to an understanding of work participation of women only in the rural areas. The modern technological implication as a result of green revolution has a worse impact on women work participation particularly in the South Bengal plain and some parts of East Rarh Plain region. The high gender gap is noticed in Nadia district located in the middle part of South Bengal Plain causes very high withdrawn of female from there. Effect of socioeconomic variables, work participation of Scheduled component in main economic activity is also varied from the non-scheduled component. Non-scheduled worker participated more in non-agricultural sector rather than the scheduled counter parts. Subsequently, the low growth rate of female work participation represents a distress picture in work force structure which is a cause of worried also.

Developing and Validating a Scale of Tourism Gentrification in Rural Areas

2021 ◽  
pp. 109634802110149
Author(s):  
Chaohui Wang ◽  
Yumei Xu ◽  
Tingting (Christina) Zhang
Keyword(s):  
Rural Areas ◽  
Living Standards ◽  
Rural Tourism ◽  
Measurement Scale ◽  
Community Culture ◽  
Policy Makers ◽  
Qualitative And Quantitative ◽  
Cultural Appreciation ◽  
Great Progress ◽  
Development And Validation

In recent years, tourism gentrification has made great progress in rural areas and has had significant impacts on these areas’ development, specifically in the domains of the economy, living standards, community, culture, and environment. Tourists play a key role in developing tourism gentrification in rural areas, but research investigating tourism gentrification in rural areas from the tourist perspective is scarce. To fill this gap, we focus on tourism gentrification and develop a measurement scale from the tourist perspective through multiple qualitative and quantitative steps. Our findings confirm that tourism gentrification in rural areas from the tourist perspective comprises eight dimensions: economic growth, enhanced environment, enhanced living standards, individual civilization, improved communication, promoted social environment, cultural appreciation, and improved individual quality. Through development and validation of the scale, we hope to offer a comprehensive referencing index of tourism gentrification in rural areas to policy makers and rural tourism practitioners.

scholarly journals Changes in Tobacco Use Patterns during COVID-19 and Their Correlates among Older Adults in Bangladesh

2021 ◽  
Vol 18 (4) ◽  
pp. 1779
Author(s):  
Sabuj Kanti Mistry ◽  
Armm Mehrab Ali ◽  
Md. Ashfikur Rahman ◽  
Uday Narayan Yadav ◽  
Bhawna Gupta ◽  
...  
Keyword(s):  
Older Adults ◽  
Tobacco Use ◽  
Rural Areas ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Policy Makers ◽  
Use Patterns ◽  
Telephone Interviews ◽  
Related Information ◽  
Structured Questionnaire

The present study explored the changes in tobacco use patterns during the COVID-19 pandemic and their correlates among older adults in Bangladesh. This cross-sectional study was conducted among 1032 older adults aged ≥60 years in Bangladesh through telephone interviews in October 2020. Participants’ characteristics and COVID-19-related information were gathered using a pretested semi-structured questionnaire. Participants were asked if they noted any change in their tobacco use patterns (smoking or smokeless tobacco) during the COVID-19 pandemic compared to pre-pandemic (6 months prior to the survey). Nearly half of the participants (45.6%) were current tobacco users, of whom 15.9% reported increased tobacco use during the COVID-19 pandemic and all others had no change in their tobacco use patterns. Tobacco use was significantly increased among the participants from rural areas, who had reduced communications during COVID-19 compared to pre-pandemic (OR = 2.76, 95%CI:1.51–5.03). Participants who were aged ≥70 years (OR = 0.33, 95% CI: 0.14–0.77), widowed (OR = 0.36, 95% CI: 0.13–1.00), had pre-existing, non-communicable, and/or chronic conditions (OR = 0.44, 95% CI: 0.25–0.78), and felt themselves at the highest risk of COVID-19 (OR = 0.31, 95% CI: 0.15–0.62), had significantly lower odds of increased tobacco use. Policy makers and practitioners need to focus on strengthening awareness and raising initiatives to avoid tobacco use during such a crisis period.

Agriculture Biomaterial Industry in Romania

2021 ◽  
Vol 10 (1) ◽  
pp. 32-44
Author(s):  
Irina Bancescu
Keyword(s):  
Rural Development ◽  
Rural Areas ◽  
Urban Areas ◽  
Rural Poverty ◽  
Value Added ◽  
Poverty Rate ◽  
Economic Implications ◽  
Income Gap ◽  
Rural Income ◽  
Urban Rural

Rural areas in Romania are underdeveloped, with the main economic activity being agriculture. Urban-rural income gap and poverty levels are indicative of an underdeveloped rural area. Urban-rural absolute income gap for average monthly income increased from 352 RON in 2007 to 663 RON in 2017. Moreover, the work poverty rate is higher in rural areas than in urban areas. Economic rural development can be achieved by improvements of the labour market and introduction of new value-added products. Agricultural and non-agricultural activities are dependent on each other for a successful rural development leading to poverty alleviation. An industry that combines the two types of economic activities is agriculture biomaterial industry. In this paper, the authos investigates the factors influencing rural poverty and analyses the current stage of the bioplastics market in Romania and its economic implications. Bioplastics industry can reduce urban-rural income gaps and poverty in rural areas.

scholarly journals Effect of Microcredit on Poverty Reduction among Rural Farm Households in Northeast, Nigeria

2019 ◽  
pp. 1-9
Author(s):  
S. U. Nwibo ◽  
T. O. Okonkwo ◽  
A. V. Eze ◽  
B. N. Mbam ◽  
N. E. Odoh
Keyword(s):  
Rural Areas ◽  
Poverty Reduction ◽  
Negative Influence ◽  
Farm Households ◽  
Policy Framework ◽  
Rural Credit ◽  
North East ◽  
Multi Stage ◽  
Northeast Nigeria ◽  
Structured Questionnaire

The paucity of empirical evidence to show the correlation between microcredit and poverty reduction in North-East, Nigeria led to the study on the effect of microcredit on poverty reduction among rural farm households. Multi-stage random and purposive sampling techniques were employed to select 200 farm households who constituted the sample size. Data were collected primarily using structured questionnaire and analysed with the aid of descriptive and inferential statistics. The results showed informal microcredit as the major source of credit for farm households. The result further indicated that 46% of the loan applied for was disbursed, resulting to 47% rise in farm household’s income. Meanwhile, 62% of farm households surveyed were poor with poverty depth of 0.43 and poverty severity at 0.38. The regression analysis on the effect of microcredit on the income of the farm households revealed that the coefficient of income was positive and statistically significant at 1% probability. The effect of microcredit on the poverty profile of farm households revealed that microcredit exerts negative influence on poverty profile of farm households in the study area. The study recommends: the establishment of robust rural credit scheme in rural areas; and institution of policy framework that will enable poor rural households without appropriate collateral to access funds for farm and non-farm activities.

scholarly journals Early Marriage as a Determinant of Poverty in Nigeria

2021 ◽  
Vol 65 (1) ◽  
pp. 102-119
Author(s):  
Adenuga Adekoya ◽  
◽  
Gbenro Sokunbi ◽  
Keyword(s):  
Higher Education ◽  
Social Welfare ◽  
Granger Causality ◽  
Low Income ◽  
Early Marriage ◽  
Easy Access ◽  
Annual Data ◽  
Policy Makers ◽  
Access To Credit ◽  
Long Run

A greater percentage of women in developing countries married before their 18th birthday. Early marriage serves as a threat to a child's future development. This is because it is difficult to have access to quality education and higher education, and it limits the ability to secure a good job. Also, girls involved in early marriage face acute poverty conditions. This research examined the link between early marriage and poverty in Nigeria. Annual data is sourced from 1970 to 2017. Granger causality is used to determine the nature of causality. Autoregressive Distributed Lagged Model is further used to estimate the data. The result showed that a bi-directional Granger causality exists between early marriage and poverty as well as for low-income and early marriage. In the long-run estimation, early marriage, secondary education and low-income increase poverty. Also, social welfare and access to credit facilities reduce poverty. The policy makers are therefore encouraged to improve social welfare for girls in early marriage and provide easy access to credit facilities for them to pursue higher education or entrepreneurship skills, in a bid to gradually move them out of poverty.

scholarly journals Leave No Child Behind: Using Data from 1.7 Million Children from 67 Developing Countries to Measure Inequality Within and Between Groups of Births and to Identify Left Behind Populations

2020 ◽  
Author(s):  
Antonio P. Ramos ◽  
Robert E. Weiss ◽  
Martin Flores
Keyword(s):  
Risk Factors ◽  
Socioeconomic Status ◽  
Mortality Risk ◽  
Rural Areas ◽  
Socioeconomic Group ◽  
Policy Makers ◽  
Socioeconomic Groups ◽  
Mortality Risks ◽  
Multiple Risk Factors ◽  
Left Behind

Background: Goal 3.2 from the Sustainable Development Goals (SDG) calls for reductions in national averages of Under-5 Mortality. However, it is well known that within countries these reductions can coexist with left behind populations that have mortality rates higher than national averages. To measure inequality in under-5 mortality and to identify left behind populations, mortality rates are often disaggregated by socioeconomic status within countries. While socioeconomic disparities are important, this approach does not quantify within group variability since births from the same socioeconomic group may have different mortality risks. This is the case because mortality risk depends on several risk factors and their interactions and births from the same socioeconomic group may have different risk factor combinations. Therefore mortality risk can be highly variable within socioeconomic groups. We develop a comprehensive approach using information from multiple risk factors simultaneously to measure inequality in mortality and to identify left behind populations. Methods: We use Demographic and Health Surveys (DHS) data on 1,691,039 births from 182 different surveys from 67 low and middle income countries, 51 of which had at least two surveys. We estimate mortality risk for each child in the data using a Bayesian hierarchical logistic regression model. We include commonly used risk factors for monitoring inequality in early life mortality for the SDG as well as their interactions. We quantify variability in mortality risk within and between socioeconomic groups and describe the highest risk sub-populations. Findings: For all countries there is more variability in mortality within socioe- conomic groups than between them. Within countries, socioeconomic membership usually explains less than 20% of the total variation in mortality risk. In contrast, country of birth explains 19% of the total variance in mortality risk. Targeting the 20% highest risk children based on our model better identifies under-5 deaths than targeting the 20% poorest. For all surveys, we report efficiency gains from 26% in Mali to 578% in Guyana. High risk births tend to be births from mothers who are in the lowest socioeconomic group, live in rural areas and/or have already experienced a prior death of a child. Interpretation: While important, differences in under-5 mortality across socioeconomic groups do not explain most of overall inequality in mortality risk because births from the same socioeconomic groups have different mortality risks. Similarly, policy makers can reach the highest risk children by targeting births based on several risk factors (socioeconomic status, residing in rural areas, having a previous death of a child and more) instead of using a single risk factor such as socioeconomic status. We suggest that researchers and policy makers monitor inequality in under-5 mortality us- ing multiple risk factors simultaneously, quantifying inequality as a function of several risk factors to identify left behind populations in need of policy interventions and to help monitor progress toward the SDG.

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