Search results

1 – 2 of 2
Per page
102050
Citations:
Loading...
Access Restricted. View access options
Article
Publication date: 19 January 2021

Masaood Moahid, Ghulam Dastgir Khan, Yuichiro Yoshida, Keshav Lall Maharjan and Imran Khan Wafa

This research measures the causal effects of pertinent agricultural credit policy attributes on farmers' participation probability and their willingness to pay (WTP) for…

206

Abstract

Purpose

This research measures the causal effects of pertinent agricultural credit policy attributes on farmers' participation probability and their willingness to pay (WTP) for agricultural credit and its associated services.

Design/methodology/approach

A randomized conjoint field experiment is conducted in three districts of Nangarhar Province, Afghanistan, capturing stated-preference data of 300 farmers. Each survey participant was provided with two hypothetical choices and one opt-out option to generate rankings based on their preferences. The levels of six attributes—namely, the credit service provider's location, the time required to obtain credit, the frequency of installments, the type of loan security, the provider of the credit services and the annual membership fee to participate in the proposed policy—are randomly assigned to produce the alternative choices.

Findings

The results reveal that farmers support the suggested agricultural credit services policy (ACSP), and the lower bound of their WTP for participation in the policy is as high as 5% of their average annual income.

Practical implications

This study provides evidence-based policy input for designing effective agricultural credit policies in Afghanistan, which can be extended to other countries with a similar context.

Originality/value

This is the first study estimating the causal effects of formal agricultural credit policy attributes on farmers' participation probability. Further, this study nonparametrically measures farmers' WTP for participation in the proposed policy.

Details

Agricultural Finance Review, vol. 81 no. 4
Type: Research Article
ISSN: 0002-1466

Keywords

Access Restricted. View access options
Article
Publication date: 27 May 2022

Masaood Moahid, Ghulam Dastgir Khan, M.D. Abdul Bari and Yuichiro Yoshida

Natural calamities impair agricultural households' ability to invest in their farms. Facilitating access to agricultural credit may assist farmers in the face of negative revenue…

335

Abstract

Purpose

Natural calamities impair agricultural households' ability to invest in their farms. Facilitating access to agricultural credit may assist farmers in the face of negative revenue shocks. The aim of this study is to investigate the impact of agricultural credit on the agricultural input expenditure of disaster-affected farmers in Bangladesh.

Design/methodology/approach

The study utilizes data on 2,519 disaster-affected farming households from Bangladesh's Household Income and Expenditure Study (HIES) 2016–2017, which employs a nationwide representative five-year interval survey. Further, propensity score matching (PSM) identification strategy is used to estimate the average treatment effect on the treated (ATET), and Mahalanobis distance matching (MDM) is used for the robustness test. In addition, heterogeneous analysis has been conducted to explore the impact of agricultural credit on different types of farming households.

Findings

The findings reveal that access to agricultural credit has a favorable and significant effect on farm input expenditure for disaster-affected farmers. Therefore, agricultural credit accessibility could be utilized as a policy tool to assist disaster-affected farmers in improving their investment capacity, and hence, agricultural output.

Originality/value

This study, using a quasi-experimental design of access to agricultural credit on agricultural input expenditures of the disaster-affected farming households in coastal areas of Bangladesh to estimate the causal effect.

Details

Agricultural Finance Review, vol. 83 no. 1
Type: Research Article
ISSN: 0002-1466

Keywords

1 – 2 of 2
Per page
102050