Rural Household Multi-Indicator Survey (RHoMIS)

Permanent URI for this collectionhttps://hdl.handle.net/10568/105618

RHoMIS was designed to improve the process of gathering information from farming households in the rural developing world. Household surveys are very widely carried out, but the data is rarely comparable, and so the opportunities for learning between individual projects are limited. For these reasons, the tool balances standardisation with flexibility.

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The Rural Household Multiple Indicator Survey (RHoMIS) data of 13,310 farm households in 21 countries
(Dataset, 2019) Wijk, Mark T. van; Hammond, James; Gorman, Leo; Adams, Sam; Ayantunde, Augustine A.; Baines, David; Bolliger, Adrian M.; Bosire, Caroline K.; Carpena, Pietro; Chesterman, Sabrina; Chinyophiro, Amon; Daudi, Happy; Dontsop Nguezet, Paul M.; Douxchamps, Sabine; Fraval, Simon; Fonte, Steven J.; Hok, Lyda; Kiara, Henry K.; Kihoro, Esther; Korir, Luke; Lamanna, Christine; Long, Chau T. M.; Manyawu, Godfrey J.; Mehrabi, Zia; Mengistu, Dejene Kassahun; Mercado, Leida; Meza, Katherin; Mora, Vesalio; Mutemi, Jacob; Ng'endo, Mary; Njingulula, Paulin; Okafor, Chris; Pagella, Tim; Phengsavanh, Phonepaseuth; Rao, E.J.O.; Ritzema, Randall S.; Rosenstock, Todd S.; Skirrow, Tom; Steinke, Jonathan; Stirling, Clare M.; Suchini, Jose Gabriel; Teufel, Nils; Thorne, Peter J.; Vanek, Steven J.; Etten, Jacob van; Vanlauwe, Bernard; Wichern, Jannike; Yameogo, Viviane
The Rural Household Multiple Indicator Survey (RHoMIS) is a standardized farm household survey approach which collects information on 753 variables covering household demographics, farm area, crops grown and their production, livestock holdings and their production, agricultural product use and variables underlying standard socio-economic and food security indicators like the Poverty Probability Index, the Household Food Insecurity Access Scale and dietary diversity. These variables are used to quantify more than 40 different aggregate indicators on farm household characteristics, welfare, productivity and economic performance. Between 2015 and the beginning of 2018, the survey instrument has been applied in 21 countries in Central America, sub-Saharan Africa and Asia. The data presented here cover the raw data, the indicator calculation code and the resulting indicator values, and can be used to quantify on- and off-farm pathways to food security, diverse diets and reduced poverty of rural smallholder farm households. (2019-10-31)
The Rural Household Multiple Indicator Survey - RHoMIS A standardised and flexible tool to monitor livelihoods, farm management, and food security
(Poster, 2020-06-08) Hammond, James; Wijk, Mark T. van
The Rural Household Multiple Indicator Survey, data from 13,310 farm households in 21 countries
(Journal Article, 2020) Wijk, Mark T. van; Hammond, James; Gorman, Leo; Adams, Sam; Ayantunde, Augustine A.; Baines, David; Bolliger, Adrian M.; Bosire, Caroline K.; Carpena, Pietro; Chesterman, Sabrina; Chinyophiro, Amon; Daudi, Happy; Dontsop Nguezet, Paul M.; Douxchamps, Sabine; Emera, Willy Desire; Fraval, Simon; Fonte, Steven; Hok, Lyda; Kiara, Henry K.; Kihoro, Esther; Korir, Luke; Lamanna, Christine; Long, Chau T. M.; Manyawu, Godfrey J.; Mehrabi, Zia; Mengistu, Dejene Kassahun; Mercado, Leida; Meza, Katherin; Mora, Vesalio; Mutemi, Jacob; Ng'endo, Mary; Njingulula, Paulin; Okafor, Chris; Pagella, Tim; Phengsavanh, Phonepaseuth; Rao, E.J.O.; Ritzema, Randall S.; Rosenstock, Todd S.; Skirrow, Tom; Steinke, Jonathan; Stirling, Clare; Suchini, Jose Gabriel; Teufel, Nils; Thorne, Peter J.; Vanek, Steven J.; Etten, Jacob van; Vanlauwe, Bernard; Wichern, Jannike; Yameogo, Viviane
The Rural Household Multiple Indicator Survey (RHoMIS) is a standardized farm household survey approach which collects information on 758 variables covering household demographics, farm area, crops grown and their production, livestock holdings and their production, agricultural product use and variables underlying standard socio-economic and food security indicators such as the Probability of Poverty Index, the Household Food Insecurity Access Scale, and household dietary diversity. These variables are used to quantify more than 40 different indicators on farm and household characteristics, welfare, productivity, and economic performance. Between 2015 and the beginning of 2018, the survey instrument was applied in 21 countries in Central America, sub-Saharan Africa and Asia. The data presented here include the raw survey response data, the indicator calculation code, and the resulting indicator values. These data can be used to quantify on- and off-farm pathways to food security, diverse diets, and changes in poverty for rural smallholder farm households.
A tool developed by ILRI to help researchers monitor progress of various agricultural interventions towards climate change adaptation and mitigation is becoming widely adopted
(News Item, 2019-05-01) Kasyoka, Sarah
Experiences and drivers of food insecurity in Guatemala's dry corridor: insights from the integration of ethnographic and household survey data
(Journal Article, 2019-08-22) Beveridge, Louise; Whitfield, Stephen; Fraval, Simon; Wijk, Mark T. van; Etten, Jacob van; Mercado, Leida; Hammond, James; Cortéz, Luz Davila; Suchini, Jose Gabriel; Challinor, Andrew J.
Eradicating hunger is a complex and multifaceted challenge, requiring evidence bases that can inform wide scale action, but that are also participatory and grounded to have local relevance and effectiveness. The Rural Household Multi-Indicator Surveys (RHoMIS) provides a broad assessment of household capabilities and food security outcomes, while ethnographic approaches evidence how individuals' perceptions, experiences and local socio-political context shape food security experiences and intervention outcomes. However, integrating these research approaches presents methodological and ontological challenges. We combine a quantitative approach with life history interviews to understand the drivers, experiences and outcomes of food insecurity in Guatemala's dry corridor region. We also reflect on the effectiveness and challenges of integrating the two methods for purposes of selective sampling, triangulating evidence, and producing a cohesive analyses of food insecurity in the region. Variables with a statistically significant association with severe food insecurity in the region are: coffee cultivation (when market participation is low), dependence on agricultural labor income, and poverty level. Drivers of food insecurity experiences most commonly identified by participants are: consecutive drought; ill health and displacement of income for medicine; social marginalization; high start-up costs in production; absence or separation of a household head; and a lack of income and education opportunity. Ethnographic approaches identify a broader range of drivers contributing to food insecurity experiences, and add explanatory power to a statistical model of severe food insecurity. This integrated analysis provides a holistic picture of food insecurity in Guatemala's dry corridor region.
Household-level drivers of dietary diversity in transitioning agricultural systems: Evidence from the Greater Mekong Subregion
(Journal Article, 2019-11) Ritzema, Randall S.; Douxchamps, Sabine; Fraval, Simon; Bolliger, Adrian M.; Hok, L.; Phengsavanh, P.; Long, C.T.M.; Hammond, James; Wijk, Mark T. van
Over the past four decades, agricultural systems in the Greater Mekong Subregion (GMS) have largely evolved from a subsistence orientation toward commercial production, but the multi-faceted changes behind this evolution vary in substance and degree. Despite connoting economic progress, effects of these changes on household welfare indicators such as dietary diversity have been unclear. By taking a comprehensive view of the farm household, this study discerns the drivers of household dietary diversity in this transitional context by linking the Household Dietary Diversity Score (HDDS), as an indicator of dietary diversity, to key household characteristics, livelihood strategies and indicators of farm performance in three study sites in Cambodia, Laos and Vietnam. The Rural Household Multi-Indicator Survey (RHoMIS) tool, a combined survey and analysis platform, was employed to collect data from over 1300 farm households. HDDS is found to increase among the sites in a way that is roughly associated with their state of agricultural transition, though differing combinations of market orientation, specialisation, and intensification traits that describe such a transition suggest that the pathway to commercialisation, and dietary diversity, is not a linear one. Drivers of dietary diversity vary markedly between the sites. In the Laos site, HDDS is most closely correlated to a set of variables closely linked with agricultural transition, while in the Cambodia site it is associated more with other farm and household characteristics. In the Vietnam site, dietary diversity is correlated to the overall value of crop production. Findings point to the need to contextualise site-specific knowledge of linkages between dietary diversity and ongoing agricultural transition in the GMS, as well as policy and interventions seeking to improve dietary diversity in the face of such transition.
Update on Africa RISING RHoMIS survey carried out in Ethiopia, April 2018
(Presentation, 2019-05-21) Hammond, James
Household-specific targeting of agricultural advice via mobile phones: Feasibility of a minimum data approach for smallholder context
(Journal Article, 2019-07) Steinke, Jonathan; Onyango Achieng, Jerusha; Hammond, James; Kebede, Selamawit S.; Mengistu, Dejene Kassahun; Mgimiloko, Majuto Gaspar; Mohammed, Jemal N.; Musyoka, Joseph; Sieber, Stefan; Gevel, Jeske M.J, van de; Wijk, Mark T. van; Etten, Jacob van
In recent years, agricultural extension services in developing countries have increasingly introduced modern information and communication technologies (ICT) to deliver advice. But to realize efficiency gains, digital applications may need to address heterogeneous information needs by targeting agricultural advisory contents in a household-specific way. We explore the feasibility of an automated advisory service that collects household data from farmers, for example through the keypads of conventional mobile phones, and uses this data to prioritize agricultural advisory messages accordingly. To reduce attrition, such a system must avoid lengthy inquiry. Therefore, our objective was to identify a viable trade-off between low data requirements and useful household-specific prioritizations of advisory messages. At three sites in Ethiopia, Kenya, and Tanzania in-dependently, we collected experimental preference rankings from smallholder farmers for receiving information about different agricultural and livelihood practices. At each site, we identified socio-economic household variables that improved model-based predictions of individual farmers’information preferences. We used the models to predict household-specific rankings of information options based on 2–4 variables, requiring the farmer to answer between 5 and 10 questions through an ICT interface. These predicted rankings could inform household-specific prioritizations of advisory messages in a digital agro-advisory application. Household-specific “top 3” options suggested by the models were better-fit to farmers’preferences than a random selection of 3 options by 48–68%, on average. The analysis shows that relatively limited data inputs from farmers, in a simple format, can be used to increase the client-orientation of ICT-mediated agricultural extension. This suggests that household-specific prioritization of agricultural advisory messages through digital two-way communication is feasible. In future digital agricultural advisory applications, collecting little data from farmers at each interaction may feed into learning algorithms that continuously improve the targeting of advice.
Efficient data collection from rural households – is RHOMIS for you?
(Presentation, 2018-11-23) Hammond, James; Pagella, Tim; Rosenstock, Todd S.; Gorman, Leo; Adams, Sam; Etten, Jacob van; Teufel, Nils; Wijk, Mark T. van
Prioritizing options for multi-objective agricultural development through the Positive Deviance approach
(Journal Article, 2019-02-25) Steinke, Jonathan; Mgimiloko, Majuto Gaspar; Graef, Frieder; Hammond, James; Wijk, Mark T. van; Etten, Jacob van
Agricultural development must integrate multiple objectives at the same time, including food security, income, and environmental sustainability. To help achieve these objectives, development practitioners need to prioritize concrete livelihood practices to promote to rural households. But trade-offs between objectives can lead to dilemmas in selecting practices. In addition, heterogeneity among farming households requires targeting different strategies to different types of households. Existing diversity of household resources and activities, however, may also bear solutions. We explored a new, empirical research method that identifies promising options for multi-objective development by focusing on existing cases of strong multi-dimensional household performance. The “Positive Deviance” approach signifies identifying locally viable livelihood practices from diverse households that achieve stronger performance than comparable households in the same area. These practices are promising for other local households in comparable resource contexts. The approach has been used in other domains, such as child nutrition, but has not yet been fully implemented for agricultural development with a focus on the simultaneous achievement of multiple objectives. To test our adapted version of the Positive Deviance approach, we used a quantitative survey of over 500 rural households in South-Eastern Tanzania. We identified 54 households with outstanding relative performance regarding five key development dimensions (food security, income, nutrition, environmental sustainability, and social equity). We found that, compared to other households with similar resource levels, these “positive deviants” performed strongest for food security, but only slightly better for social equity. We then re-visited a diverse sub-sample for qualitative interviews, and identified 14 uncommon, “deviant” practices that plausibly contributed to the households’ superior outcomes. We illustrate how these practices can inform specific recommendations of practices for other local households in comparable resource contexts. The study demonstrates how, with the Positive Deviance approach, empirical observations of individual, outstanding households can inform discussions about locally viable agricultural development solutions in diverse household context.
Intensifying inequality? Gendered trends in commercializing and diversifying smallholder farming systems in East Africa
(Journal Article, 2019-02-27) Tavenner, Katie; Wijk, Mark T. van; Fraval, Simon; Hammond, James; Baltenweck, Isabelle; Teufel, Nils; Kihoro, Esther; Haan, Nicoline C. de; Etten, Jacob van; Steinke, J.; Baines, D.; Carpena, Pietro; Skirrow, T.; Rosenstock, Todd S.; Lamanna, C.; Ng'endo, M.; Chesterman, Sabrina; Namoi, N.; Manda, L.
While the commercialization and diversification of agricultural and livestock systems have been identified as key global strategies for climate change adaptation and mitigation, less is known as to the large-scale gendered impacts that are implicated in these transformations among smallholder crop and livestock farmers. This study explores these gender impacts across different farming systems and gender-respondent-household typologies using data from the Rural Household Multiple Indicator Survey (RHoMIS) in 2,859 households in three East African countries—Ethiopia, Kenya, and Tanzania. Female control scores over incomes or foodstuffs produced through both on and off farm activities were highest in farming systems that had more land and more livestock. However, increasing commercialization—defined herein as the increasing importance of crop and livestock sales to farm households—resulted in an overall decline in female control across all farming systems and gender-respondent-household typologies. In contrast, crop and livestock diversification were positively associated with female control across gender-respondent-household typologies. Analysis of specific crops and livestock products across farming systems and respondent typologies revealed women have far greater control over decisions related to consumption than decisions related to sales, although the gap between the two were less pronounced in lesser-valued livestock products (chickens, eggs). However, the analyses suggest that as sale of crops and livestock increase, female control over these areas could likely diminish, regardless of specific activity. The authors conclude that approaches to adapt to or mitigate climate change that rely on increasing market orientation of smallholder production will likely intensify men's control over benefits from production, whereas diversification will likely have a more positive impact on female control. Thus, climate adaptation strategies promoting increased diversification will likely have a more positive impact on women smallholders than commercialization alone. The authors recommend that when commercialization is the target intervention, it must be accompanied by a gender differentiated analysis of trade-offs and risks to mitigate the potential negative consequences shown in this study.
Making the most of imperfect data: A critical evaluation of standard information collected in farm household surveys
(Journal Article, 2019-04) Fraval, Simon; Hammond, James; Wichern, Jannike; Oosting, Simon J.; Boer, Imke J.M. de; Teufel, Nils; Lannerstad, Mats; Waha, Katharina; Pagella, Tim; Rosenstock, Todd S.; Giller, Kenneth E.; Herrero, Mario; Harris, David; Wijk, Mark T. van
Household surveys are one of the most commonly used tools for generating insight into rural communities. Despite their prevalence, few studies comprehensively evaluate the quality of data derived from farm household surveys. We critically evaluated a series of standard reported values and indicators that are captured in multiple farm household surveys, and then quantified their credibility, consistency and, thus, their reliability. Surprisingly, even variables which might be considered ‘easy to estimate’ had instances of non-credible observations. In addition, measurements of maize yields and land owned were found to be less reliable than other stationary variables. This lack of reliability has implications for monitoring food security status, poverty status and the land productivity of households. Despite this rather bleak picture, our analysis also shows that if the same farm households are followed over time, the sample sizes needed to detect substantial changes are in the order of hundreds of surveys, and not in the thousands. Our research highlights the value of targeted and systematised household surveys and the importance of ongoing efforts to improve data quality. Improvements must be based on the foundations of robust survey design, transparency of experimental design and effective training. The quality and usability of such data can be further enhanced by improving coordination between agencies, incorporating mixed modes of data collection and continuing systematic validation programmes.
Smallholder farmers, food security, and livelihoods: Exploring trade offs and synergies using farm household characterization data
(Case Study, 2018-10-15) Wijk, Mark T. van; Hammond, James; Frelat, Romain; Fraval, Simon; Teufel, Nils; Tavenner, Katie; Henderson, Benjamin B.
The Rural Household Multiple Indicator Survey (RHOMIS)
(Presentation, 2018-10-03) Wijk, Mark T. van; Hammond, James
Livelihoods and food security in an urban linked, high potential region of Tanzania: Changes over a three year period
(Journal Article, 2018-02) Fraval, Simon; Hammond, James; Lannerstad, Mats; Oosting, Simon J.; Sayula, George; Teufel, Nils; Silvestri, Silvia; Poole, Elizabeth J.; Herrero, Mario; Wijk, Mark T. van
The Rural Household Multi-Indicator Survey (RHoMIS): A rapid, cost-effective and flexible tool for farm household characterisation, targeting interventions and monitoring progress towards climate-smart agriculture
(Brief, 2016-10-15) Wijk, Mark T. van; Hammond, James; Etten, Jacob van; Pagella, Tim; Ritzema, Randall S.; Teufel, Nils; Rosenstock, Todd S.
RHoMIS is a rapid, cheap, digital farm household-level survey and analytical engine for characterizing, targeting and monitoring agricultural performance. RHoMIS captures information describing farm productivity and practices, nutrition, food security, gender equity, climate and poverty. RHoMIS is action-ready, tested and adapted for diverse systems in more than 7,000 households across the global tropics. Want more info? See: http://rhomis.net/
When less is more: Innovations for tracking progress toward global targets
(Journal Article, 2017-06) Rosenstock, Todd S.; Lamanna, Christine; Chesterman, Sabrina; Hammond, James; Kadiyala, Suneetha; Luedeling, Eike; Shepherd, Keith D.; DeRenzi, Brian; Wijk, Mark T. van
Accountability and adaptive management of recent global agreements such as the Sustainable Development Goals and Paris Climate Agreement, will in part rely on the ability to track progress toward the social and environmental targets they set. Current metrics and monitoring systems, however, are not yet up to the task. We argue that there is an imperative to consider principles of coherence (what to measure), standardization (how to measure) and decision-relevance (why to measure) when designing monitoring schemes if they are to be practical and useful. New approaches that have the potential to match the necessary scale of monitoring, with sufficient accuracy and at reasonable cost, are emerging; although, they represent a significant departure from the historical norm in some cases. Iterative review and adaptation of analytical approaches and available technology will certainly be needed to continuously design ways to best track our progress.
The Rural Household Multi-Indicator Survey (RHoMIS) for rapid characterisation of households to inform climate smart agriculture interventions: Description and applications in East Africa and Central America
(Journal Article, 2017-02) Hammond, James; Fraval, Simon; Etten, Jacob van; Suchini, Jose Gabriel; Mercado, Leida; Pagella, Tim; Frelat, Romain; Lannerstad, Mats; Douxchamps, Sabine; Teufel, Nils; Valbuena, Diego; Wijk, Mark T. van
Achieving climate smart agriculture depends on understanding the links between farming and livelihood practices, other possible adaptation options, and the effects on farm performance, which is conceptualised by farmers as wider than yields. Reliable indicators of farm performance are needed in order to model these links, and to therefore be able to design interventions which meet the differing needs of specific user groups. However, the lack of standardization of performance indicators has led to a wide array of tools and ad-hoc indicators which limit our ability to compare across studies and to draw general conclusions on relationships and trade-offs whereby performance indicators are shaped by farm management and the wider social-environmental context. RHoMIS is a household survey tool designed to rapidly characterise a series of standardised indicators across the spectrum of agricultural production and market integration, nutrition, food security, poverty and GHG emissions. The survey tool takes 40–60 min to administer per household using a digital implementation platform. This is linked to a set of automated analysis procedures that enable immediate cross-site bench-marking and intra-site characterisation. We trialled the survey in two contrasting agro-ecosystems, in Lushoto district of Tanzania (n = 150) and in the Trifinio border region of Guatemala, El Salvador and Honduras (n = 285). The tool rapidly characterised variability between farming systems at landscape scales in both locations identifying key differences across the population of farm households that would be critical for targeting CSA interventions. Our results suggest that at both sites the climate smartness of different farm strategies is clearly determined by an interaction between the characteristics of the farm household and the farm strategy. In general strategies that enabled production intensification contributed more towards the goals of climate smart agriculture on smaller farms, whereas increased market orientation was more successful on larger farms. On small farms off-farm income needs to be in place before interventions can be promoted successfully, whereas on the larger farms a choice is made between investing labour in off-farm incomes, or investing that labour into the farm, resulting in a negative association between off-farm labour and intensification, market orientation and crop diversity on the larger farms, which is in complete opposition to the associations found for the smaller farms. The balance of indicators selected gave an adequate snap shot picture of the two sites, and allowed us to appraise the ‘CSA-ness’ of different existing farm strategies, within the context of other major development objectives.
Drivers of household food availability in sub-Saharan Africa based on big data from small farms
(Journal Article, 2016-01-12) Frelat, Romain; López Ridaura, Santiago; Giller, Kenneth E.; Herrero, Mario; Douxchamps, Sabine; Djurfeldt, Agnes Andersson; Erenstein, Olaf; Henderson, Benjamin B.; Kassie, Menale; Paul, Birthe K.; Rigolot, Cyrille; Ritzema, Randall S.; Rodríguez, Daniel; Asten, Piet J.A. van; Wijk, Mark T. van
We calculated a simple indicator of food availability using data from 93 sites in 17 countries across contrasted agroecologies in sub- Saharan Africa (>13,000 farm households) and analyzed the drivers of variations in food availability. Crop production was the major source of energy, contributing 60% of food availability. The off-farm income contribution to food availability ranged from 12% for households without enough food available (18% of the total sample) to 27% for the 58% of households with sufficient food available. Using only three explanatory variables (household size, number of livestock, and land area), we were able to predict correctly the agricultural determined status of food availability for 72% of the households, but the relationships were strongly influenced by the degree of market access. Our analyses suggest that targeting poverty through improving market access and off-farm opportunities is a better strategy to increase food security than focusing on agricultural production and closing yield gaps. This calls for multisectoral policy harmonization, incentives, and diversification of employment sources rather than a singular focus on agricultural development. Recognizing and understanding diversity among smallholder farm households in sub-Saharan Africa is key for the design of policies that aim to improve food security.
A rapid, quantitative assessment of household level food security: description of the data collection tool and the analysis
(Working Paper, 2014-12-12) Wijk, Mark T. van; Ritzema, Randall S.; Valbuena, Diego; Douxchamps, Sabine; Frelat, Romain

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