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Targeting Social Transfers to the Poor in Mexico
Mexico's main social support program, Oportunidades, combines two methods to target cash to poor households: an initial self-selection by households who acquire knowledge about the program and apply for benefits, followed by an administrative determination of eligibility based on a means test. Self-selection improves targeting by excluding high-income households, while administrative targeting does so mainly by excluding middle-income households. The two methods are complementary: expanding program knowledge across households substantially increases applications from non-poor households, thus reinforcing the importance of administrative targeting. The paper shows that targeting can be further improved through redesigning the means test and differentiating transfers according to demographic characteristics.
eBook
Determinants of residential water consumption: Evidence and analysis from a 10-country household survey
Household survey data for 10 countries are used to quantify and test the importance of price and nonprice factors on residential water demand and investigate complementarities between household water‐saving behaviors and the average volumetric price of water. Results show (1) the average volumetric price of water is an important predictor of differences in residential consumption in models that include household characteristics, water‐saving devices, attitudinal characteristics and environmental concerns as explanatory variables; (2) of all water‐saving devices, only a low volume/dual‐flush toilet has a statistically significant and negative effect on water consumption; and (3) environmental concerns have a statistically significant effect on some self‐reported water‐saving behaviors. While price‐based approaches are espoused to promote economic efficiency, our findings stress that volumetric water pricing is also one of the most effective policy levers available to regulate household water consumption. Key Points Average water price is the best predictor of differences in h/hold consumption Environmental attitudes do not significantly effect h/hold water consumption Average water price is an effective lever to manage h/hold water demand
Journal Article
How well do different dietary and nutrition assessment tools match? Insights from rural Kenya
Various indicators and assessment tools exist to measure diets and nutrition. Most studies eventually rely on one approach. Relatively little is known about how closely results match when different tools are used in the same context. The present study compares and correlates different indicators for the same households and individuals to better understand which indicators can be used as proxies for others.
A survey of households and individuals was carried out in Kenya in 2015. Seven-day food consumption and 24 h dietary recalls were administered at household and individual level, respectively. Individual height and weight measures were taken. Different indicators of food access (energy consumption, household dietary diversity scores), dietary quality (individual dietary diversity scores, micronutrient intakes) and nutrition (anthropometric indicators) were calculated and correlated to evaluate associations.
Rural farm households in western Kenya.ParticipantsData collected from 809 households and 1556 individuals living in these households (782 female adults, 479 male adults, 295 children aged 6-59 months).
All measures of food access and dietary quality were positively correlated at individual level. Household-level and individual-level dietary indicators were also positively correlated. Correlations between dietary indicators and anthropometric measures were small and mostly statistically insignificant.
Dietary indicators from 7d food consumption recalls at the household level can be used as proxies of individual dietary quality of children and male and female adults. Individual dietary diversity scores are good proxies of micronutrient intakes. However, neither household-level nor individual-level dietary indicators are good proxies of individual nutritional status in this setting.
Journal Article
Generating Synthetic Electricity Load Time Series at District Scale Using Probabilistic Forecasts
Thanks to various European directives, individuals are empowered to share and trade electricity within Renewable Energy Communities, enhancing the operational efficiency of local energy systems. The digital transformation of the energy market enables the integration of decentralized energy resources using cloud computing, the Internet of Things, and artificial intelligence. In order to assess the feasibility of new business models based on data-driven solutions, various electricity consumption time series are necessary at this level of aggregation. Since these are currently not yet available in sufficient quality and quantity, and due to data privacy reasons, synthetic time series are essential in the strategic planning of smart grid energy systems. By enabling the simulation of diverse scenarios, they facilitate the integration of new technologies and the development of effective demand response strategies. Moreover, they provide valuable data for assessing novel load forecasting methodologies that are essential to manage energy efficiently and to ensure grid stability. Therefore, this research proposes a methodology to synthesize electricity consumption time series by applying the Box–Jenkins method, an intelligent sampling technique for data augmentation and a probabilistic forecast model. This novel approach emulates the stochastic nature of electricity consumption time series and synthesizes realistic ones of Renewable Energy Communities concerning seasonal as well as short-term variations and stochasticity. Comparing autocorrelations, distributions of values, and principle components of daily sequences between real and synthetic time series, the results exhibit nearly identical characteristics to the original data and, thus, are usable in designing and studying efficient smart grid systems.
Journal Article
Comparison between household food purchase and individual food consumption in Brazil
The present study aimed to compare Household Budget Survey (HBS) data on food purchasing and individual food consumption, collected in the same nationwide survey.
Food purchase information for each household was collected by a seven-day collective acquisition diary, applied to 55 970 households. Food consumption information was obtained from household members over 10 years old by the application of two non-consecutive food records in a sub-sample of the HBS. Cooking and correction factors were applied when necessary, and all food items reported were grouped into twelve main food groups. Food purchase and consumption data were presented as absolute weight (g/person per d) and as relative contribution to energy intake (%) for the overall study population, which was stratified according to household income.
Brazil.ParticipantsNational estimates of food consumption and purchase for Brazil.
The greatest differences between purchase and consumption data (purchase minus consumption) were observed for meat (-168 g), beans/legumes (-48 g), roots/tubers (-36 g) and fruits (-31 g). When expressed in terms of energy contribution, the highest differences were found for cereals (13 %) and oils and fats (11 %). Differences between purchase and consumption data were generally lower in the highest compared with the lowest household income quintile; and were lower for most main food groups when considering only foods reported as being eaten at home.
With few exceptions, food purchase expressed as relative energy contribution, as opposed to absolute weight, can provide a good picture of actual consumption in the Brazilian population.
Journal Article
Awareness and Adoption of Soil and Water Conservation Technologies in a Developing Country: A Case of Nabajuzi Watershed in Central Uganda
Soil and water conservation technologies have been widely available in most parts of Uganda. However, not only has the adoption rate been low but also many farmers seem not to be aware of these technologies. This study aims at identifying the factors that influence awareness and adoption of soil and water conservation technologies in Nabajuzi watershed in central Uganda. A bivariate probit model was used to examine farmers’ awareness and adoption of soil and water conservation technologies in the watershed. We use data collected from the interview of 400 households located in the watershed to understand the factors affecting the awareness and adoption of these technologies in the study area. Findings indicate that the likelihood of being aware and adopting the technologies are explained by the age of household head, being a tenant, and number of years of access to farmland. To increase awareness and adoption of technologies in Uganda, policymakers may expedite the process of land titling as farmers may feel secure about landholding and thus adopt these technologies to increase profitability and productivity in the long run. Incentive payments to farmers residing in the vulnerable region to adopt these considered technologies may help to alleviate soil deterioration problems in the affected area.
Journal Article
Determination of household electricity expenditures using quantile regression with Kennedy approach
The electrical energy expenditure of households in Turkey has been increasing over the years, and households account for one-fifth of the overall electrical energy consumption. For this reason, it is of vital importance to determine the factors that affect household electricity expenditure, reveal consumption patterns for different consumer groups, and propose suggestions for the efficient use of electrical energy. In the present study, determinants of household electricity expenditure were analyzed with the quantile regression approach using the Household Budget Survey published by the Turkish Statistical Institute. In conclusion, it was determined that demographic, economic, and residential factors had significant effects on the electricity expenditures of households. The present study will serve as a guide for policymakers and decision-makers in developing strategies and conducting studies toward reducing the electricity expenditures of households, which is an important factor for energy usage.
Journal Article
Socioeconomic Differences of Intimate Partner Violence among Married Women in Indonesia: Does Poverty Matter?
Background:
Society placed women living in the men's world as inferior. Poverty as a stressor for men has the opportunity to make women victims of violence from their partners. The study aimed to analyze the effects of poverty on the risk of intimate partner violence among married women in Indonesia.
Materials and Methods:
The samples used were married women aged 15-49 years old. The weighted sample size was 34,086 women. Besides intimate partner violence as the dependent variable, other variables analyzed as independent variables were wealth status, residence, age, education, employment, living with in-laws, and recent sexual activity. The study employs binary logistic regression to determine intimate partner violence risk in the final stage.
Results:
The results show the poorest married women were 1.382 times more likely than the richest married women to experience intimate partner violence. Married women with wealthy status in the lower category were 1.320 times more likely than the richest married women to experience intimate partner violence. Married women with a wealthy group in the middle class were 1.262 times more likely than the richest married women to experience intimate partner violence. Married women with wealthy status in the more decadent category were 1.132 times more likely than the richest married women to experience intimate partner violence.
Conclusion:
The study concluded that poverty was a risk factor for intimate partner violence among married women in Indonesia. The lower the socioeconomic status, the greater the risk of intimate partner violence.
Journal Article
Transient and persistent energy efficiency in the US residential sector: evidence from household-level data
In this paper, we measure the energy efficiency implicit in residential energy consumption using a panel dataset comprised of 40,246 observations from US households observed over 1997–2009. We fit a stochastic frontier model of the minimum input of energy needed to meet the level of energy services demanded by the household. This benchmarking exercise produces a transient and a persistent efficiency index for each household and each time period. We estimate that the US residential sector could save approximately 10% of its total energy consumption if it reduced persistent inefficiencies and 17% if it were possible to eliminate transient inefficiencies. These figures are in line with recent economy-wide assessments for the USA. Our results suggest that savings in energy use and associated emissions of greenhouse gases may benefit from both policy measures that attain short-run behavioral changes (e.g., nudges, social norms, display of real-time information about usage, and real-time pricing) as well measures aimed at the long run, such as energy-efficiency regulations, incentives on the purchase of high-efficiency equipment, and incentives towards a change of habits in the use of the equipment.
Journal Article