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This paper aims to focus on scrutinizing the economics of greenhouse gas (GHG) emissions in Vietnam's rice production sector.

Using surveyed data from household rice producers, the smallest available production scale, the author delves into the economics of GHG emissions, constructs a data-driven bottom-up marginal abatement cost curve for Vietnam’s rice production, and evaluates the impacts of carbon pricing on production outputs and GHG emissions.

The author’s estimates reveal that the average profit earned per tonne of GHG emissions is $240/tCO2. Notably, the profit earning per tonne of GHG emissions varies substantially across producers, indicating significant opportunities for improvement among low-efficiency producers. The analysis suggests that a reasonable carbon price would yield a modest impact on the national rice output. The quantitative analysis also reaffirms that the primary driver of GHG emissions in Vietnam’s rice production stems from non-energy inputs and industrial processes rather than the utilisation of energy inputs, emphasizing the importance of improving cultivation techniques.

This research is original.

This study examined the impact of the Input Credit Scheme (ICS) by the Integrated Water Management and Agriculture Development (IWAD) on the productivity and food security of smallholder rice farmers in Ghana.

Cross-sectional data from 250 rice farming households in the Mamprugu Moagduri district of the North East Region obtained from a multi-stage sampling technique were used for the study. Inverse Probability Weighted Regression Adjustment (IPWRA), Propensity Score Matching (PSM) and Kendall's coefficient of concordance were the methods of analysis employed.

Empirical results show that education, rice farming experience, dependency ratio, FBO membership, farm size and farm age were the significant factors influencing participation in the input credit scheme (ICS). Also, participants had an average rice productivity of 1,476.83 kg/ha, whereas non-participants had 1,131.81 kg/ha implying that participants increased their productivity by about 30%. In addition, the study revealed that participant households increased their household dietary diversity (HDDS) by 0.45 points amounting to about 8% diversity in their diets. High-interest rates associated with credit received, the short periods of credit repayment and the high cost of inputs provided under the scheme were the most challenging constraints associated with partaking in the ICS.

The available literature on agricultural interventions have predominantly emphasized input credit as a key factor for improving cropt productivity and food security of smallholders. This study provides compelling evidence that participation in ICSs can result in substantial benefits for agricultural development, as evidenced by increased productivity leading to improved food security. The significance of these findings is highlighted by the fact that, through participation in input credit schemes, smallholder rice farmers in many developing countries see substantial improvement in their capacity to access productive resources, thereby improving their productivity, while simultaneously reducing food insecurity.

Leveraging on the improved productivity of participants in the ICS, this study advocates that such input credit schemes should scale up to more food-insecure farming communities in Ghana.

The study uses a doubly robust econometric approach to evaluate the impact of ICS on smallholder rice farmers' productivity and food security in Ghana, making it the first of its kind. The findings offer a solid basis for future research and provide guidance for policymakers looking to boost agricultural development in Ghana.

This study assessed the heterogeneous impact of the Anchor Borrower Program (ABP) on the welfare distribution of rice farming households in Nigeria.

Self-selection bias and treatment endogeneity were accounted for by employing the Instrumental Variable Quantile Regression (IVQR) model. The estimates obtained from the IVQR model were further compared with those from the conventional quantile regression, and quantile regression using Propensity Score Matching. This was to highlight the extent to which endogeneity bias has been purged from the treatment, in order to establish a consistent causal link between participation in the ABP and the welfare of a cross-section of rice farming households.

ABP farmers had significantly higher rice yields across all quantiles of the yield distribution under treatment exogeneity assumption, and in only two quantiles upon controlling for observable confounders. However, this yield gain did not translate to higher Per capita Consumption Expenditure (PCE). The estimates of the more robust IVQR model provided further evidence that the rice yield and PCE of ABP farmers are not statistically different from that of non-ABP farmers across all quantiles of the welfare distribution.

The negligible impact of ABP was relatively higher for lower-yielding households. Thus, implying that, although the ABP is a pro-poor development intervention, the program has not been sufficiently implemented to significantly improve the welfare of the dominant resource-poor farming households in Nigeria.

This study assessed the impact of ABP beyond the conventional potential mean outcome framework by accounting for heterogeneity in treatment effect.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2023-0083

In the past three decades, remote sensing-based models for estimating crop yield have addressed critical problems of general food security, as the unavailability of grains such as rice creates serious worldwide food insecurity problems. The main purpose of this study was to compare the potential of time-series Landsat-8 and Sentinel-2 data to predict rice yield several weeks before harvest on a regional scale.

To this end, the sum of normalized difference vegetation index (NDVI)-based models created the best agreement with actual yield data at the golden time window of six weeks before harvest when rice grains were in milky and mature growth stages. The application of nine other vegetation indicators was also investigated in the golden time window in comparison to NDVI.

The findings of this study demonstrate the viability of identifying locations with poor and superior performance in terms of production management approaches through a rapid and economical solution for early rice grain yield assessment. Results indicated that while some of those, such as enhanced vegetation index (EVI) and optimized soil adjusted vegetation index, were able to estimate rice yield with high accuracy, NDVI is still the best indicator to predict rice yield before harvest. However, experiments can be conducted in different regions in future studies to evaluate the generalizability of the approach.

To achieve this objective, the authors considered the following purposes: using Sentinel-2 time-series data, determining the appropriate growth stage for estimating rice yield and evaluating different vegetation indices for estimating rice yield.

Improving the competitiveness of East Africa's rice industries necessitates increased and viable production of rice of the quality desired by consumers. This paper aims to understand consumer preferences for rice quality attributes in Uganda and Kenya to inform the countries' rice breeding programs and value chain development interventions.

Rice samples are obtained from retail markets in various districts/counties across the two countries. The samples are analyzed in a grain quality laboratory for the rice's physicochemical characteristics and the resulting data are used to non-parametrically estimate hedonic price functions. District/county dummies are included to account for potential heterogeneity in consumer preferences.

Ugandan consumers are willing to pay a price premium for rice with a relatively high proportion of intact grains, but the consumers discount chalkiness. Kenyan consumers discount high amylose content and impurities. There is evidence of heterogeneity in consumer preferences for rice in Mbale, Butaleja and Arua districts of Uganda and in Kericho and Busia counties of Kenya.

The study makes a novel contribution to the literature on consumer preferences for rice in East Africa by applying a hedonic pricing model to the data generated from a laboratory analysis of the physicochemical characteristics of rice samples obtained from the market. Rather than base our analysis on consumers' subjective sensory assessment of the quality characteristics of rice, standard laboratory methods are used to generate the data, which enables a more objective assessment of the relationship between market prices and the quantities of attributes present in the rice samples.

The purpose of the present research is to examine the comparative values that urban Vietnamese consumers place on attributes of rice that is produced using environmentally friendly methods. The authors consider the impacts that this may have on the livelihoods of rural Vietnamese small farmers. Rice is an “impure public good” that includes both “private” and “public” attributes that consumers consider in their purchase decisions. Consumers make tradeoffs between environmentally and socially beneficial practices (public goods) and perceptions of product quality (private goods). The authors used latent class modeling to investigate the values associated with attributes of rice that is produced using sustainable farming practices.

The authors used a discrete choice experimental design in which consumers stated their choices among combinations of rice attributes. The survey provided responses from 360 urban Vietnamese consumers and allowed to estimate the preferences and nonpecuniary values for rice grown using different levels of environmentally beneficial production methods.

The results identify two segments of rice consumers: one group of consumers who are sensitive to price and the other group who are sensitive to environmental issues. The individual characteristics are reflected in the choices of production methods and in the willingness to pay for environmentally beneficial outcomes of those methods.

Given the number of independent variables measured, the sample was relatively small, such that confirmatory statistical methods were inconclusive. However, the authors used multiple analytical tools that provide corroboration of the significant determinants of the utility functions for the two segments.

The results provide directions for production of rice at a national level, as well as practical implications for consumer-oriented communications.

Results suggest that the emerging middle class of Vietnamese consumers are willing to pay more for rice that is produced using methods that are beneficial to the environment. Results also indicate challenges to provide sustainably-produced rice to poorer groups of consumers.

The study provides important context for consumer preferences within emerging economies. This also adds to a growing literature that uses the choice experiment method to estimate consumer valuation of the outcomes of various agricultural practices.

The aim of this study is to estimate the technical efficiency of the massive and economically important crop of rice in Ecuador, and then conduct a comparison between groups of farmers with and without insurance.

The authors use an input-oriented data envelopment analysis approach (DEA) to estimate technical efficiency scores. The DEA is combined with the double bootstrap approach in Simar and Wilson (2007) to study factors that may affect technical efficiency. This method overcomes the traditional two-stage DEA approach frequently used in the efficiency literature. The authors thus research the role of insurance on rice efficiency production using this technique and sizeable field-level survey data from 376 rice farmers distributed in five provinces during the 2019 winter cycle in Ecuador.

Most uninsured rice farmers operate with increasing returns to scale, which means that farms improve their resource use efficiency by increasing their size. However, since scale efficiencies are relatively high, it appears that inefficiencies are explained by inadequate input use. Also, the authors find evidence that insured farmers have a negative relationship with technical efficiency in rice production. In other results, when exploring the influence of additional variables on efficiency, the authors find that parameters related to transplanting, high education, farm size and some locations are positive and statistically significant.

The results of this work are relevant for policymakers interested in evaluating technology performance, risk management instruments and farm efficiency in an industry in a developing country such as rice production in Ecuador.

This paper is the first attempt to estimate farm-level technical efficiency employing the double bootstrap approach to assess the efficiency and its determinants of Ecuadorian rice producers.

This paper presents the systematic process framework to develop the suitable crop insurance for each agriculture farming region which has individual differences of associated crop, climate condition, including applicable technology to be implemented in crop insurance practice. This paper also studies the adoption of new insurance scheme to assess the willingness to join crop insurance program.

Crop insurance development has been performed through IDDI conceptual framework to illustrate the specific crop insurance diagram. Area-yield insurance as a type of index-based insurance advantages on reducing basis risk, adverse selection and moral hazard. This paper therefore aims to develop area-yield crop insurance, at a provincial level, focusing on rice insurance scheme for the protection of flood. The diagram demonstrates the structure of area-yield rice insurance associates with selected machine learning algorithm to evaluate indemnity payment and premium assessment applicable for Jasmine 105 rice farming in Ubon Ratchathani province. Technology acceptance model (TAM) is used for new insurance adoption testing.

The framework produces the visibly informative structure of crop insurance. Random Forest is the algorithm that gives high accuracy for specific collected data for rice farming in Ubon Ratchathani province to evaluate the rice production to calculate an indemnity payment. TAM shows that the level of adoption is high.

This paper originates the framework to generate the viable crop insurance that suitable to individual farming and contributes the idea of technology implementation in the new service of crop insurance scheme.

After a long observation of the high rate of rice importation and low productivity in Côte d’Ivoire, the certified rice seed was introduced and encouraged to be used by the local farmers. This study evaluates the profitability of rice production and the impact of certified seed usage on the yield and income of farmers in Côte d’Ivoire.

Data were collected from 265 rice farmers. Descriptive statistics were used to identify the challenges faced in using certified seeds. Profitability analysis was used to examine the profitability of rice production. To eliminate bias due to the counterfactuals, the endogenous switching regression was employed to investigate the impact of the certified seeds on income and yield.

The difficulties faced by the rice farmers in the procurement of certified seeds were the unavailability of seeds, the high cost of seeds and poor credit access. Furthermore, rice farmers using certified seeds get a higher net income (USD 263.74/ha) than those using farmers' seeds (USD 212.31/ha). The average treatment on the treated was 1.61 for the yield and 574.75 for the income. The average treatment on the untreated was 1.20 for the yield and 422.59 for the income. These indicate a higher yield and income among adopters of certified rice seed.

Certified rice seed usage is profitable and enhances the output and income of rice farmers. The study advocates the creation of a stronger relationship between the farmers and the extension agents to encourage the use of certified seeds and increase the profit of the farmers.

There is scant information on the profitability of certified rice seed usage and how it affect yield and income. Therefore, this study serves as empirical evidence for policymakers to develop strategies that are required to enhance certified seed usage, boost rice productivity and achieve food security.

Weaknesses in the grades and standards system in low-income countries across Sub-Saharan Africa undermine the transparency of agricultural markets. In the Democratic Republic of the Congo (DRC), Ghana and Mozambique rice is predominately sold in open bags and if rice price does not reflect its quality, then inefficiencies may lead to consumer welfare losses. Importantly, it is possible that impoverished communities are priced out of the market due to inflated and inefficient prices. The objective of this study is to examine determinates of rice price by estimating the impact of selected rice quality attributes on rice prices in Democratic Republic of the Congo, Ghana and Mozambique.

We collected 363 rice samples from open air markets in Bukavu (DRC), Nampula (Mozambique) and across Ghana in 2019. Each rice sample was analyzed in a food science lab for the quality attributes: percentage of chalk and brokens, chalk impact, length and length-to-width ratio. We used multiple regression analysis to estimate if and to what extent quality attributes were the drivers of price.

Findings suggest that there are irregularities in the Ghanaian market for broken rice and that regardless of quality, imported rice is priced higher than domestic rice. In the DRC and Mozambique, our results indicate price is driven by length and length-to-width ratio in the former and length-to-width ratio in the latter.

Rice samples were purchased from market vendors and thus consumer preferences for attributes were not revealed.

These results provide valuable insight to policymakers regarding the need for proper labeling and regulation of open bag rice sales in an effort to increase consumer welfare and improve food security.