Search Results (8)

Poultry farming is a significant source of revenue generation for small farmers in developing countries. It plays a vital role in fulfilling the daily protein requirements of humans through meat and eggs consumption. The recently emerged pandemic Coronavirus Disease-19 (COVID-19) impacts the poultry production sector. Although the whole world is affected, these impacts may be more severe in developing countries due to their dependency on exporting necessary supplies such as feed, vaccines, drugs, and utensils. In this review, we have discussed poultry production in developing countries under the COVID-19 crisis and measures to regain the loss in the poultry industries. Generally, due to the lockdown, trade limitations have negatively impacted poultry industries, which might exacerbate global poverty. Coordinated activities have to be taken at the private and government levels to arrange soft loans so that these farms can restore their production and marketing to normal levels. In addition, here, we have focused on the supply of farm input, feed, other raw materials, management system, improved breeding efficiency, veterinary services, and marketing of egg and meat, which have to be ensured to secure a sustainable poultry production chain. Full article

The rapid development of online lending in the past decade, while providing convenience and efficiency, also generates large hidden credit risk for the financial system. Will removing financial intermediaries really provide more efficiency to the lending market? This paper used a large dataset with 251,887 loan listings from a pioneer P2P lending platform to investigate the efficiency of the credit-screening mechanism on the P2P lending platform. Our results showed the existence of a TYPE II error in the investors’ decision-making process, which indicated that the investors were predisposed to making inaccurate diagnoses of signals, and gravitated to borrowers with low creditworthiness while inadvertently screening out their counterparts with high creditworthiness. Due to the growing size of the fintech industry, this may pose a systematic risk to the financial system, necessitating regulators’ close attention. Since, investors can better diagnose soft signals, an effective and transparent enlargement of socially related soft information together with a comprehensive and independent credit bureau could mitigate adverse selection in a disintermediation environment. Full article

In terms of economic development and feeding the world’s populations, the importance of the agricultural sector is well known. However, agriculture and its related sectors are also known for contributing more than one-quarter of the world’s GHG emissions. To address this issue, we evaluate the performance of agriculture and its related firms in India from 2013 to 2019 with its environmental efficiency under the paradigm shift promoted by the National Agroforestry Policy in 2014. To evaluate the feasibility of this paradigm shift in agricultural policy, the non-radial slack-based measure (SBM) is utilized in the first stage, and Tobit regressions are used to assess the determinants of efficiency (or sources of inefficiency) measures at the second stage. The results from non-radial SBM show that Indian agricultural firms (foreign direct investment, private, and public) show huge potential with 32.2% on average to enhance their performance if they move toward the frontier of the production possibility curve. This suggests that Indian policymakers should regulate much stronger regulations for firms, especially for the use of agricultural inputs such as energy (fertilizers), with performance-oriented financial measures for sustainable agriculture. To determine the strategic variables for these firms to enhance their performance, Tobit regressions showed that fertilizers use (−3.350%) appears to have the highest negative impact on environmental efficiency. On the other hand, credit access (2.710%) has the highest positive impact on environmental efficiency, implying that policymakers should provide subsidies to firms in the form of soft loans (or credit access) for the purchase of high-quality fertilizers and to adopt energy-saving equipment/technology to minimize the use of chemical fertilizers in India. Full article

Credit scoring is a process of determining whether a borrower is successful or unsuccessful in repaying a loan using borrowers’ qualitative and quantitative characteristics. In recent years, machine learning algorithms have become widely studied in the development of credit scoring models. Although efficiently classifying good and bad borrowers is a core objective of the credit scoring model, there is still a need for the model that can explain the relationship between input and output. In this work, we propose a novel partially interpretable adaptive softmax (PIA-Soft) regression model to achieve both state-of-the-art predictive performance and marginally interpretation between input and output. We augment softmax regression by neural networks to make it adaptive for each borrower. Our PIA-Soft model consists of two main components: linear (softmax regression) and non-linear (neural network). The linear part explains the fundamental relationship between input and output variables. The non-linear part serves to improve the prediction performance by identifying the non-linear relationship between features for each borrower. The experimental result on public benchmark datasets shows that our proposed model not only outperformed the machine learning baselines but also showed the explanations that logically related to the real-world. Full article

This study investigates the income and price elasticities of gasoline demand for a fuel subsidizing country case, applying three different time-varying coefficient approaches to the data spanning the period from January 2002 to June 2018. The empirical estimations concluded a cointegration relationship between gasoline demand, income, and gasoline price. The income elasticity found ranges from 0.10 to 0.29, while the price elasticity remains constant over time, being −0.15. Income elasticity increases over time, slightly decreasing close to the end of the period, which is specific for a developing country. In the short run, gasoline demand does not respond to the changes in income and price. The policy implications are discussed based on the findings of the study. Research results show that since the income elasticity of demand is not constant, the use of constant elasticities obtained in previous studies might be misleading for policymaking purposes. An increase in income elasticity might be the cause of the inefficiency of the existing vehicles. The small price elasticity allows to say that if policy makers plan to reduce gasoline consumption then increasing its price would not substantially reduce the consumption. The current situation can be utilized to increase energy efficiency and implement eco-friendly technologies. For this purpose, the quality of existing transport modes can be improved. Meanwhile, to meet households’ needs, policies such as providing soft auto loans need to be formed to balance the recent drop in car sales. Full article

Financial inclusion is the process of including the people who lack formal financial services. The concept of financial inclusion emerged globally in the times of millennium and is defined as the availability and usage of formal financial services. It essentially facilitates economic growth; the financially included individuals can invest in business, education, and entrepreneurship, which can pave way to poverty alleviation and economic development. In the context of Pakistan, a developing economy of South Asia, the financial landscape presents a grim picture of financial inclusion where only 16 percent of the population is financially included. Despite the current focus of policies and regulations devoted to enhancing access to finance in Pakistan from the supply side, the current state of financial inclusion is limited. Therefore, this study investigates the financial inclusion process for Pakistan from the supply side. We analyze the supply-side dimension of access by employing econometric technique of autoregressive distributive lag (ARDL) and using time series data of banking sector of Pakistan. Our empirical findings suggest that the greater the size, geographic outreach, and demographic outreach of the banks, the greater the contribution to the financial inclusion. Additionally, improvement in soft consumer loans and increase in small-sized advances reinforces the financial inclusion process. Full article

For more than five decades, developing countries (including Cameroon) have been primary beneficiaries of donor-funded projects targeting many sectors, including agriculture and rural development. Cameroon’s rural landscape witnessed a series of project interventions which emphasized sustainability. Although research efforts have been directed towards understanding the planning, implementation and impacts of donor-funded projects, not enough scientific information exists on the determinants, challenges and prospects of sustaining donor-funded projects in rural communities in Cameroon. For this study, the Investment Fund for Communal and Agricultural Micro-projects (FIMAC I) scheme, was used to diagnose the determinants, challenges and prospects for sustaining development projects in the North West Region (NWR) of Cameroon. A representative sample of 150 beneficiaries drawn from 20 farming groups in the NWR was conducted, to generate data which was complemented by interviews. The binary logistic regression results reveal the following: Although there is a significant change in the level of incomes for the FIMAC I project beneficiaries, its sustainability (mirrored through continuity) is dependent upon a myriad of socio-economic factors including family size, length of stay in the community, gender, education and the status of the beneficiary. Furthermore, the less transparent loan application process and the lack of collateral security were the main challenges faced by project beneficiaries. We argue that the introduction of soft loans with minimal demands for collateral security could increase beneficiary participation in projects, while beneficiary groups should further diversify their sources of capital and productive activities. The study does not only contribute to existing theoretical constructs on sustainable rural development, but also makes a succinct request for future studies to unbundle the conditions, under which donor-funded projects are rendered sustainable in rural contexts. Full article

The purpose of this article was to conduct an empirical evaluation of the Czech public programme START, which was funded from the European Regional Development Fund. The programme lasted from 2007–2011, and supported new entrepreneurs through the zero interest soft loans and credit guarantees. The counterfactual analysis (using three matching techniques: propensity score, nearest neighbour, and kernel) was conducted on the firm level and investigated the changes in financial performance (net profits, return on assets (ROA), return on equity (ROE), sales, assets turnover, and debt ratio) of the supported firms four years after the end of intervention. The obtained findings could not support the hypothesis assuming a positive impact of the programme on the firm’s performance. On the contrary, supported companies reported on average lower sales and lower return on assets, when compared to the control group. The remaining variables could not prove any statistically significant impact of the programme. Indicators measuring firm’s profitability (net profit, return on assets, and return on equity) suggested a negative influence of the programme and the variable representing debt ratio further indicated that firms that were supported by the programme reported on average higher debt ratio in comparison with the control group. Several policy implications are discussed in the study. Full article