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The purpose of this paper is to evaluate the impact of access to production credit on the productivity of smallholder farmers.

Data for the study were drawn from the Agricultural Value Chain Facility (AVCF), which was implemented in the Northern Region of Ghana. This paper uses the Propensity Score Matching (PSM) to estimate the average treatment effect of access to production credit on the productivity of smallholder farmers. The rationale for the choice of this estimation technique is to control for selection bias since the treatment variable (access to production credit) was not randomised. The authors also test for the effect of hidden bias using “Rosenbaum bounds” sensitivity analysis. The study uses two control groups to examine the net effect of credit on productivity.

The results reveal that smallholder farmers with access to production credit increased productivity through investment in farm inputs. For the impact of credit on productivity using control Group 1, the result shows that farmers with access to credit increased their productivity by 0.170 metric tonnes per hectare and for control Group 2, the result shows an increase of 0.252 metric tonnes per hectare more than farmers who are without access to production credit.

The evidence as provided by this paper is that access to production credit is significant to meet the credit needs of smallholder farmers and therefore contributes to the policy debate on whether access to credit has impact on the productivity of smallholder farmers.

The paper shows the importance of production credit in augmenting the production function of smallholder farmers.

This study examines the impact of agricultural credit on rice farmers' technical efficiency (TE) in Côte d'Ivoire by considering the heterogeneity among credit sources.

A multistage sampling technique was used to collect data from 588 randomly sampled rice farmers in seven rice areas of the country. The authors use the endogenous stochastic frontier production (ESFP) model to account for the endogeneity of access to agricultural credit.

On the one hand, agricultural credit has a significant and positive impact on rice farmers' TE. Rice farmers receiving agricultural credit have an average of 5% increase in their TE, confirming the positive impact of agricultural credit on TE. On the other hand, the study provides evidence that the impact of credit on rice production efficiency differs depending on the source of credit. Borrowing from agricultural cooperatives and paddy rice buyers/processors positively and significantly influences the TE, while borrowing from microfinance institutions (MFIs) negatively and significantly influences the TE. Moreover, borrowing from relatives/friends does not significantly influence TE.

Future research can further explore the contribution of agricultural credit by including several agricultural productions and using panel data.

The study provides evidence that the impact of agricultural credit on agricultural production efficiency depends on the source of credit. This study contributes to the literature on the impact of agricultural credit and enlightens policymakers in the design of agricultural credit models in developing countries, particularly Côte d'Ivoire.

The purpose of this paper is to explore the factors that affect farmer’s decision to allocate credit for livestock production. The results are expected to contribute to the understanding of what motivates smallholders to allocate credit to agricultural production in general and livestock production in particular. A better understanding of the farmers’ behavior in allocating credit for livestock would provide useful information for project implementers and financial institutions that work with small-scale livestock producers.

A cross-section data set collected in 2014 from 5,000 households and 497 rural communities in the major highland regions of Ethiopia is examined. The authors developed a conceptual framework for credit allocation decision. Percentiles, means, and standard deviation as well as t, χ² and Fisher’s exact tests for association and Cramer’s V measure for strength of association have been used to describe the status of farmer’s access to credit and analyze credit utilization, while a three-stage probit model with double sample selection is used to identify factors that affect household’s decision to allocate credit for livestock production.

After controlling for potential selection biases, sex and literacy status of household head, land size, wealth and access to livestock centered extension service are found to have a statistically significant effect on farmers’ decision to allocate credit to livestock production. The results showed female-headed households, wealthy farmers, farmers with small plot of land and farmers that have access to livestock centered extension services are more likely to allocate the credit for livestock production. The results suggest that policies aimed at improving access to credit together with access to livestock focused extension service are more effective in increasing livestock production.

The study’s findings should be viewed with perspective and caution, as only households with excess demand for credit were the subject of the research.

The contribution of this paper is twofold. First, it is one of a very few empirical studies that try to identify factors that affect households credit allocation to livestock in systematic way that removed confounding effects using three-stage probit models. Given the emphasis on financial constraints in livestock development, new empirical insights on household credit allocation are essential to better inform development interventions. Second, the analysis relies on a comprehensive data set that represents the major agricultural system of the country.

The aim of the study is to attempt to analyze the trends and patterns of institutional credit flow, deployed by the CBs, SCBs and RRBs, for production and investment purposes in agriculture and allied activities in India in the light of banking sector reforms initiated in the early 1990s.

The study is based on secondary data collected from the Handbook of Statistics of Indian Economy, 2009‐2010 published by the Reserve Bank of India, Agricultural Statistics at a Glance, Economic Survey of India, etc. The data relating to institutional credit at the all India level were collected for 1971‐1972 to 2007‐2008. The period from 1971‐1972 to 1980‐1981 is considered as the beginning of multi‐agency approach and bank branch expansion, from 1981‐1982 to 1990‐1991 is regarded as the pre‐reform period, from 1991‐1992 to 2007‐2008, as the post‐reform period. In order to examine the extent of institutional credit flow for development of agriculture and allied activities, the indictors such as the average institutional credit per hectare cultivated area and as percentage of agricultural GDP were estimated, besides the CAGR during different periods.

The study found that the annual growth rate of total institutional credit for agriculture and allied activities was much higher during the reform period as compared to that of pre‐reform period. The average institutional credit per hectare and as a percentage of agricultural GDP has gone up significantly during the reform regime. The RRBs followed by the SCBs registered highest growth rates of production credit as compared to that of CBs during the entire period; it was higher during the reform than the pre‐reform period. The growth rate of investment credit was highest for SCBs followed by the RRBs as against the CBs during the reform period. It has been observed that the CBs have lost their historical prime position in provision of agricultural credit. The growth pattern of production as well as investment credit constituted what can be described as the “U‐shaped” curve. This implies that the bulk of the increase in institutional credit for agriculture and allied activities during the reform period was attributed to the banking sector reforms initiated in the early 1990s.

The data on institutional credit provided by the SCARDBs and PCARDBs were not included under the co‐operative sector prior to 1999‐2000, and it covered credit by only PACs. Hence, the temporal comparability of data on institutional credit under the co‐operative sector for the period 1998‐1999 to 2007‐2008 with that of earlier periods may be erroneous.

Adequate and timely inflow of both production and investment credit for development of agriculture and allied activities through further reforms in the banking sector would go a long way in sustained growth of agriculture and food security for a great majority of the rural masses in India.

The study establishes the “U‐shaped” curve for the growth pattern of institutional credit for development of agriculture and allied activities in India. This follows that the increase in the growth rates of institutional credit during 1991‐1992 to 2007‐2008 was largely due to the banking sector reforms.

This paper aims to compare and analyze the effect of the dual-credit policy and product substitution rate on the automakers’ operational strategies under different production modes (e.g. centralized and independent), and further illustrate which production mode is more conducive to improving new energy vehicle (NEV) development.

The decision-making models for a centralized production mode where an integrated automaker produces both NEVs and fuel vehicles (FVs) and for independent production mode where an NEV automaker faces competition from a traditional FV automaker were formulated. The equilibrium solutions of each production mode were obtained by extreme value and game theory methods. The conclusions of the theoretical analysis were further verified with numerical analyses using IBM-MATLAB R2019a. Some management insights could be obtained by comparison analysis.

Under the dual-credit policy, an increase in the NEV credit trading price will always raise production quantity of NEVs, but only in an independent production mode where a higher trading price will also bring higher total profits to NEV automakers. In addition, only when the NEV credit trading price is high enough, a rising product substitution rate will be more favorable to NEV production and restrain FV production. Furthermore, an independent production mode is more favorable for the initial production of NEVs, but as each of the two vehicle types captures a certain amount of market share, a centralized production mode will be more conducive to the full replacement of FVs by NEVs.

The main contributions of this study include the formulation of decision-making models for FVs and NEVs in not only a centralized production mode but also an independent production mode. Moreover, this paper comprehensively analyzes how the dual-credit policy and product substitution relationship affect automakers’ production and pricing decisions. Then, the specific conditions under which each production mode is more conducive to NEV production and sales are summarized. The results proposed in this study provide scientific managerial insights for automakers and policy makers.

Much attention has been paid to farm credit access with less focus on determining the actual credit amount needed to bring about a specified increase in productivity relative to the finance being sought. The paper aims to discuss this issue.

Using 2016 cross-sectional data of plantain farmers, the authors employ the Cobb–Douglas stochastic frontier production function to determine the technical efficiency (TE) of each farmer. Current plantain quantity produced by farmers and the TE are then used to estimate plantain quantity at a target efficiency. The finance needed to produce at the target efficiency is estimated using the Harrod–Domar (HD) growth equation and the authors then subtract the farmers’ savings from the estimated amount to determine the financing gap of the farmers.

Results of this study show that the actual amount required to improve the productivity of farmers to target levels of TE can be estimated and that credit amount granted to farmers can be tied to a specific production efficiency. Credit schemes with interest rates below 9 per cent are more beneficial to farmers while access to credit is determined by interest rate, education, credit process duration, land ownership and asset value in the study area.

The implication of this research is that it opens up the possibility of further exploring the application of the HD theory at the micro level.

The findings in this study have important implications on the provision of agricultural credit to small farmers. The first is that the TE of farmers plays a very critical role in determining the actual amount of credit needed to bridge the farm-level financing gap and impact positively on productivity. Second, while it is important to bridge the farm-level financing gap, this can only be beneficial to the farmers at single-digit interest rates below 7 per cent. Finally, granting of credit to farmers can be tied to specific production increase target to reduce indiscipline and mismanagement in credit use.

The findings of this study will go along in helping to prevent mismanagement and indiscipline in the use of scarce financial resources in agricultural production.

This study is the first of its kind, using TE and bringing the HD equation down to the farm level to estimate the exact amount required by farmers to bring about specific increase in production, determining the credit amount beyond which mismanagement may set in.

The purpose of this paper is to examine the effect of credit constraints on agricultural productivity in China.

Using data from a rural financial survey, a switching regression model is used to account for endogeneity and heterogeneity. Carter presents three ways that credit might affect the production functions; a shift along a given production surface by allowing an optimal level of inputs, a shift the production surface out by allowing the purchase of more efficient inputs, and the third is to increase net revenue by more intensive use of fixed inputs and resources. Thus, the effects of factors on agricultural productivity may not be independent of credit status; therefore, separate functions for credit‐constrained and non‐constrained households are examined.

Empirical estimates of the impacts of credit constraints on agricultural productivity are provided for the Heilongjiang province, a major agricultural production area, in Northeast China. By removing credit constraints, average agricultural productivity was estimated to be increased by 75 percent. Under credit constraints, labor inputs, along with a farmers' education, cannot be fully employed because of an inappropriate mix of inputs.

Young farmers may not be able to leverage their comparative advantage for physically intensive farm work under credit constraints. Because of data limitations, the research does not include information on informal credit in the estimation, which may underestimate the effects of credit constraints.

This study provides an analysis of the impacts of credit constraints on rural household productivity for the Heilongjiang province, a major agricultural production region, in Northeast China.

The purpose of this paper is to evaluate the impact of a Brazilian rural credit program, The National Program for Strengthening Family Farming (PRONAF), on small family farming production.

The method is based on a quasi-experimental approach (propensity score matching) applied to 4.1m family farmers in Brazil.

Results show that farmers accessing PRONAF tended to be positively selected in terms of several observable characteristics, such as land size and agricultural practices. Moreover, PRONAF had positive and differentiated impacts on agricultural production. The impact was larger in the poorest region when compared to the regions characterized by intensive and commercial farming.

The rural credit information was restricted to one crop year, making impossible to analyze the mid- and long-term impacts of the credit program on agricultural production.

The study provides some practical implications for policies of rural development. First, rural credit does matter for agricultural production of small family farmers. Nonetheless, since credit programs are large subsidized by the rest of the population, further studies are still needed the aggregate costs and benefits of these schemes. Results also revealed that PRONAF may have contributed to reduce regional inequalities, since the impact was larger in the poorest NE region.

This study provides a comprehensive analysis of how rural credit has impacted small-farm agricultural production, using large and representative data – the whole population of Brazilian family farmers.

Production credit is essential for enhancing the technical efficiency (TE) and the welfare of smallholder farmers in Africa. The purpose of this paper is to examine the impact of credit on smallholders’ TE using cross-sectional data from 223 maize-producing households in Northern Ghana.

Due to the exogenous assignment of credit and assumption of homogeneity in farm technologies, the propensity score matching (PSM) analysis was used to compare the average difference in TE between farmers that had received credit and those that had not.

The results revealed that production credit impacts positively on smallholder farmers’ TE. Access to production credit is significantly influenced by access to markets and extension services, distance to market, asset index and land fragmentation. The provision of credit enhances the timely purchase and efficient allocation of farming inputs to produce the maximum possible output. Per capita income and land fragmentation also play important roles in reducing smallholders’ TE.

To increase efficiency gains, credit programs for agricultural interventions should target resource-poor smallholder farmers. The efficiency gains can be sustained through stronger partnerships with financial institutions. Policy interventions aimed at increasing smallholder farmers’ access to production credit (e.g. through the creation of a conducive investment environment that lowers the lending rate and collateral requirements) must be vigorously pursued.

To the best of authors’ knowledge, this is one of the only recent studies to examine the impact of credit on the TE of farming households by applying the translog stochastic frontier production function and the PSM approaches.

This paper examines the US opera sector as a means for interrogating how varying forms of non-standard work shape gender inequality in the creative industries.

The authors draw on 16 seasons of opera production data from Operabase.com to conduct a gender-based exploratory data analysis of the key creative roles of conductor, director and designers, as well as the hiring networks through which teams are formed, at the 11 largest opera companies in the United States.

The authors find that women, as a group, experienced gender-based disadvantage across the key creative roles of opera production, but particularly in the artistic leadership roles of conductor and director. The authors also find that women's exclusion in the field is being further perpetuated by the sector's non-standard and overlapping employment structures, which impacts women practitioners' professional visibility and career opportunities.

The study can help organizations implement strategic hiring practices that acknowledge the relationship between gender inequality and varying forms of non-standard work with the aim of increasing women's representation.

This study work establishes the scale of gender inequality operating within a sector that has received minimal scholarly attention as a site of employment. The study analysis also offers important insight for the wider creative industries and highlights opportunities to redress gender inequality in other sectors where project-based work is prevalent.