The coronavirus disease 2019 (COVID-19) pandemic has affected vulnerable households’ livelihoods in developing countries. Using high-frequency phone survey data from the World Bank, we assess rural Indian households’ vulnerability and poverty status during the pandemic. Results reveal that over three-fifths of Indian rural households are vulnerable to poverty in the context of COVID-19, despite India’s evident progress in mitigating poverty in the pre-pandemic era. Poverty plays a major role in accounting for variations in household vulnerability; however, the impact of risks on household welfare is not negligible. On average, households with more members, older household heads, and more outmigrants are more vulnerable to poverty during the pandemic. The impacts of the gender of the household head, access to masks, consumption loans, and COVID-related information are nevertheless insignificant. Results stress the urgent necessity of deploying concerted interventions to strengthen household vulnerability in rural India.

The coronavirus disease 2019 (COVID-19) pandemic has affected vulnerable households’ livelihoods in developing countries. Using high-frequency phone survey data from the World Bank, we assess rural Indian households’ vulnerability and poverty status during the pandemic. Results reveal that over three-fifths of Indian rural households are vulnerable to poverty in the context of COVID-19, despite India’s evident progress in mitigating poverty in the pre-pandemic era. Poverty plays a major role in accounting for variations in household vulnerability; however, the impact of risks on household welfare is not negligible. On average, households with more members, older household heads, and more outmigrants are more vulnerable to poverty during the pandemic. The impacts of the gender of the household head, access to masks, consumption loans, and COVID-related information are nevertheless insignificant. Results stress the urgent necessity of deploying concerted interventions to strengthen household vulnerability in rural India.

The coronavirus disease 2019 (COVID-19) pandemic has affected vulnerable households’ livelihoods in developing countries. Using high-frequency phone survey data from the World Bank, we assess rural Indian households’ vulnerability and poverty status during the pandemic. Results reveal that over three-fifths of Indian rural households are vulnerable to poverty in the context of COVID-19, despite India’s evident progress in mitigating poverty in the pre-pandemic era. Poverty plays a major role in accounting for variations in household vulnerability; however, the impact of risks on household welfare is not negligible. On average, households with more members, older household heads, and more outmigrants are more vulnerable to poverty during the pandemic. The impacts of the gender of the household head, access to masks, consumption loans, and COVID-related information are nevertheless insignificant. Results stress the urgent necessity of deploying concerted interventions to strengthen household vulnerability in rural India. | Foresight and Policy Modeling (FPM); Transformation Strategies

The importance of gender norms in agricultural innovation processes has been recognized. However, the operational integration of these normative issues into the innovation strategies of agricultural interventions remains challenging. This article advances a replicable, integrative research approach that captures key local conditions to inform the design and targeting of gender-inclusive interventions. We focus on the gender climate across multiple contexts to add to the limited indicators available for assessing gender norms at scale. The notion of gender climate refers to the socially constituted rules that prescribe men’s and women’s behaviour in a specific geographic location—with some being more restrictive and others more relaxed. We examine the gender climate of 70 villages across 13 countries where agriculture is an important livelihood. Based on data from the GENNOVATE initiative we use multivariate methods to identify three principal components: ‘Gender Climate’, ‘Opportunity’ and ‘Connectivity’. Pairwise correlation and variance partitioning analyses investigate the linkages between components. Our findings evidence that favourable economic or infrastructure conditions do not necessarily correlate with favourable gender normative conditions. Drawing from two case-study villages from Nepal, we highlight opportunities for agricultural research for development interventions. Overall, our approach allows to integrate local knowledge about gender norms and other local conditions into the planning and targeting strategies for agricultural innovation.

The importance of gender norms in agricultural innovation processes has been recognized. However, the operational integration of these normative issues into the innovation strategies of agricultural interventions remains challenging. This article advances a replicable, integrative research approach that captures key local conditions to inform the design and targeting of gender-inclusive interventions. We focus on the gender climate across multiple contexts to add to the limited indicators available for assessing gender norms at scale. The notion of gender climate refers to the socially constituted rules that prescribe men's and women's behaviour in a specific geographic location-with some being more restrictive and others more relaxed. We examine the gender climate of 70 villages across 13 countries where agriculture is an important livelihood. Based on data from the GENNOVATE initiative we use multivariate methods to identify three principal components: 'Gender Climate', 'Opportunity' and 'Connectivity'. Pairwise correlation and variance partitioning analyses investigate the linkages between components. Our findings evidence that favourable economic or infrastructure conditions do not necessarily correlate with favourable gender normative conditions. Drawing from two case-study villages from Nepal, we highlight opportunities for agricultural research for development interventions. Overall, our approach allows to integrate local knowledge about gender norms and other local conditions into the planning and targeting strategies for agricultural innovation.

The importance of gender norms in agricultural innovation processes has been recognized.However, the operational integration of these normative issues into the innovation strategies of agricultural interventions remains challenging. This article advances a replicable, integrative research approach that captures key local conditions to inform the design and targeting of gender-inclusive interventions. We focus on the gender climate across multiple contexts to add to the limited indicators available for assessing gender norms at scale. The notion of gender climate refers to the socially constituted rules that prescribe men’s and women’s behaviour in a specific geographic location—with some being more restrictive and others more relaxed. We examine the gender climate of 70 villages across 13 countries where agriculture is an important livelihood. Based on data from the GENNOVATE initiative we use multivariate methods to identify three principal components: ‘Gender Climate’, ‘Opportunity’ and ‘Connectivity’. Pairwise correlation and variance partitioning analyses investigate the linkages between components. Our findings evidence that favourable economic or infrastructure conditions do not necessarily correlate with favourable gender normative conditions. Drawing from two case-study villages from Nepal, we highlight opportunities for agricultural research for development interventions. Overall, our approach allows to integrate local knowledge about gender norms and other local conditions into the planning and targeting strategies for agricultural innovation.

The importance of gender norms in agricultural innovation processes has been recognized. However, the operational integration of these normative issues into the innovation strategies of agricultural interventions remains challenging. This article advances a replicable, integrative research approach that captures key local conditions to inform the design and targeting of gender-inclusive interventions. We focus on the gender climate across multiple contexts to add to the limited indicators available for assessing gender norms at scale. The notion of gender climate refers to the socially constituted rules that prescribe men’s and women’s behaviour in a specific geographic location—with some being more restrictive and others more relaxed. We examine the gender climate of 70 villages across 13 countries where agriculture is an important livelihood. Based on data from the GENNOVATE initiative we use multivariate methods to identify three principal components: ‘Gender Climate’, ‘Opportunity’ and ‘Connectivity’. Pairwise correlation and variance partitioning analyses investigate the linkages between components. Our findings evidence that favourable economic or infrastructure conditions do not necessarily correlate with favourable gender normative conditions. Drawing from two case-study villages from Nepal, we highlight opportunities for agricultural research for development interventions. Overall, our approach allows to integrate local knowledge about gender norms and other local conditions into the planning and targeting strategies for agricultural innovation.

Local value-addition in developing countries is often aimed at for upgrading of agricultural value chains, since it is assumed that doing so will make farmers better off. However, transmission of the added value through the value chain and constraints to adoption of value-adding activities by farmers are not well understood. We look at this issue in the case of coffee in Ethiopia–the country’s most important export product–and value-addition in the coffee value-chain through ‘washing’ coffee, which is done in wet mills. Washed coffee is sold internationally with a significant premium compared to ‘natural’ coffee but the share of washed coffee in Ethiopia’s coffee exports has stagnated. Relying on a unique primary large-scale dataset and a combination of qualitative and quantitative methods, we examine the reasons for this puzzle. The reasons seemingly are twofold. First, labor productivity in producing red cherries, which wet mills require, is lower than for natural coffee, reducing incentives for adoption, especially for those farmers with higher opportunity costs of labor. Second, only impatient, often smaller, farmers sell red cherries, as more patient farmers use the storable dried coffee cherries as a rewarding savings instrument, given the negative real deposit rates in formal savings institutions.

Local value-addition in developing countries is often aimed at for upgrading of agricultural value chains, since it is assumed that doing so will make farmers better off. However, transmission of the added value through the value chain and constraints to adoption of value-adding activities by farmers are not well understood. We look at this issue in the case of coffee in Ethiopia–the country’s most important export product–and value-addition in the coffee value-chain through ‘washing’ coffee, which is done in wet mills. Washed coffee is sold internationally with a significant premium compared to ‘natural’ coffee but the share of washed coffee in Ethiopia’s coffee exports has stagnated. Relying on a unique primary large-scale dataset and a combination of qualitative and quantitative methods, we examine the reasons for this puzzle. The reasons seemingly are twofold. First, labor productivity in producing red cherries, which wet mills require, is lower than for natural coffee, reducing incentives for adoption, especially for those farmers with higher opportunity costs of labor. Second, only impatient, often smaller, farmers sell red cherries, as more patient farmers use the storable dried coffee cherries as a rewarding savings instrument, given the negative real deposit rates in formal savings institutions. | PR | IFPRI3; 3 Building Inclusive and Efficient Markets, Trade Systems, and Food Industry; CRP2; ISI | Development Strategies and Governance (DSG); Transformation Strategies; PIM | CGIAR Research Program on Policies, Institutions, and Markets (PIM)

Local value-addition in developing countries is often aimed at for upgrading of agricultural value chains, since it is assumed that doing so will make farmers better off. However, transmission of the added value through the value chain and constraints to adoption of value-adding activities by farmers are not well understood. We look at this issue in the case of coffee in Ethiopia–the country’s most important export product–and value-addition in the coffee value-chain through ‘washing’ coffee, which is done in wet mills. Washed coffee is sold internationally with a significant premium compared to ‘natural’ coffee but the share of washed coffee in Ethiopia’s coffee exports has stagnated. Relying on a unique primary large-scale dataset and a combination of qualitative and quantitative methods, we examine the reasons for this puzzle. The reasons seemingly are twofold. First, labor productivity in producing red cherries, which wet mills require, is lower than for natural coffee, reducing incentives for adoption, especially for those farmers with higher opportunity costs of labor. Second, only impatient, often smaller, farmers sell red cherries, as more patient farmers use the storable dried coffee cherries as a rewarding savings instrument, given the negative real deposit rates in formal savings institutions.

Over the last fifteen years, Payments for Environmental Services (PES) schemes have become very popular environmental policy instruments, but the academic literature has begun to question their additionality. The literature attempts to estimate the causal effect of these programs by applying impact evaluation (IE) techniques. However, PES programs are complex instruments and IE methods cannot be directly applied without adjustments. Based on a systematic review of the literature, this article proposes a framework for the methodological process of designing an IE for PES schemes. It revises and discusses the methodological choices at each step of the process and proposes guidelines for practitioners. (Résumé d'auteur)

Over the last fifteen years, Payments for Environmental Services (PES) schemes have become very popular environmental policy instruments, but the academic literature has begun to question their additionality. The literature attempts to estimate the causal effect of these programs by applying impact evaluation (IE) techniques. However, PES programs are complex instruments and IE methods cannot be directly applied without adjustments. Based on a systematic review of the literature, this article proposes a framework for the methodological process of designing an IE for PES schemes. It revises and discusses the methodological choices at each step of the process and proposes guidelines for practitioners.

Over the last fifteen years, Payments for Environmental Services (PES) schemes have become very popular environmental policy instruments, but the academic literature has begun to question their additionality. The literature attempts to estimate the causal effect of these programs by applying impact evaluation (IE) techniques. However, PES programs are complex instruments and IE methods cannot be directly applied without adjustments. Based on a systematic review of the literature, this article proposes a framework for the methodological process of designing an IE for PES schemes. It revises and discusses the methodological choices at each step of the process and proposes guidelines for practitioners.

In the transformation of agri-food systems in developing countries, we usually see rapid changes in the dairy sector. However, good data for understanding patterns and inclusiveness of this transformation are often lacking. This is important given implications for policy design and service and technology provision towards better performing dairy sectors in these settings. Relying on a combination of unique diverse large-scale datasets and methods, we analyze transformation patterns in the dairy value chain supplying Addis Ababa, the capital of Ethiopia, the second most populous country in Africa. Over the last decade, we note a rapid increase in expenditures on dairy products by urban consumers, especially among the better-off. Relatedly, the number of dairy processing firms in Ethiopia tripled over the same period, supplying a significant part of these dairy products, especially pasteurized milk, to the city’s residents. Upstream at the production level, we find improved access to livestock services, higher adoption of cross-bred cows, an increase in milk yields, expanding liquid milk markets, a sizable urban farm sector supplying almost one-third of all liquid milk consumed in the city, and an upscaling process with larger commercial dairy farms becoming more prevalent. However, average milk yields are still low and not all dairy farmers are included in this transformation process. Small farms with dairy animals as well as those in more remote areas benefit less from access to services and adopt less these modern practices. For these more disadvantaged farmers, stagnation in milk yields and even declines–depending on the data source used–are observed.

In the transformation of agri-food systems in developing countries, we usually see rapid changes in the dairy sector. However, good data for understanding patterns and inclusiveness of this transformation are often lacking. This is important given implications for policy design and service and technology provision towards better performing dairy sectors in these settings. Relying on a combination of unique diverse large-scale datasets and methods, we analyze transformation patterns in the dairy value chain supplying Addis Ababa, the capital of Ethiopia, the second most populous country in Africa. Over the last decade, we note a rapid increase in expenditures on dairy products by urban consumers, especially among the better-off. Relatedly, the number of dairy processing firms in Ethiopia tripled over the same period, supplying a significant part of these dairy products, especially pasteurized milk, to the city’s residents. Upstream at the production level, we find improved access to livestock services, higher adoption of cross-bred cows, an increase in milk yields, expanding liquid milk markets, a sizable urban farm sector supplying almost one-third of all liquid milk consumed in the city, and an upscaling process with larger commercial dairy farms becoming more prevalent. However, average milk yields are still low and not all dairy farmers are included in this transformation process. Small farms with dairy animals as well as those in more remote areas benefit less from access to services and adopt less these modern practices. For these more disadvantaged farmers, stagnation in milk yields and even declines–depending on the data source used–are observed. | PR | IFPRI3; ISI; DCA; ESSP; CRP2; 3 Building Inclusive and Efficient Markets, Trade Systems, and Food Industry; 4 Transforming Agricultural and Rural Economies; Feed the Future Innovation Lab for Livestock Systems (LSIL) | DSGD; PIM | CGIAR Research Program on Policies, Institutions, and Markets (PIM)

In the transformation of agri-food systems in developing countries, we usually see rapid changes in the dairy sector. However, good data for understanding patterns and inclusiveness of this transformation are often lacking. This is important given implications for policy design and service and technology provision towards better performing dairy sectors in these settings. Relying on a combination of unique diverse large-scale datasets and methods, we analyze transformation patterns in the dairy value chain supplying Addis Ababa, the capital of Ethiopia, the second most populous country in Africa. Over the last decade, we note a rapid increase in expenditures on dairy products by urban consumers, especially among the better-off. Relatedly, the number of dairy processing firms in Ethiopia tripled over the same period, supplying a significant part of these dairy products, especially pasteurized milk, to the city’s residents. Upstream at the production level, we find improved access to livestock services, higher adoption of cross-bred cows, an increase in milk yields, expanding liquid milk markets, a sizable urban farm sector supplying almost one-third of all liquid milk consumed in the city, and an upscaling process with larger commercial dairy farms becoming more prevalent. However, average milk yields are still low and not all dairy farmers are included in this transformation process. Small farms with dairy animals as well as those in more remote areas benefit less from access to services and adopt less these modern practices. For these more disadvantaged farmers, stagnation in milk yields and even declines–depending on the data source used–are observed.