Micro-level Household Research Articles

Practical measurement of affordability: an application to medicines

To develop two practical methods for measuring the affordability of medicines in developing countries. The proposed methods--catastrophic and impoverishment methods--rely on easily accessible aggregated expenditure data and take into account a country's income distribution and absolute level of income. The catastrophic method quantifies the proportion of the population whose resources would be catastrophically reduced by spending on a given medicine; the impoverishment method estimates the proportion of the population that would be pushed below the poverty line by procuring a given medicine. These methods are illustrated by calculating the affordability of glibenclamide, an antidiabetic drug, in India and Indonesia. The results were validated by comparing them with the results obtained by using household micro data for India and Indonesia. When accurate aggregate data are available, the proposed methods offer a practical way to obtain informative and accurate estimates of affordability. Their results are very similar to those obtained with household micro data analysis and are easily compared across countries. The catastrophic and impoverishment methods, based on macro data, can provide a suitable estimate of medicine affordability when the household level micro data needed to carry out more sophisticated studies are not available. Their usefulness depends on the availability of accurate aggregated data.

The Impact of Population Ageing on House Prices: A Micro-Simulation Approach

This paper attempts to estimate the impact of population ageing on house prices. There is considerable debate about whether population ageing puts downwards or upwards pressure on house prices. The empirical approach differs from earlier studies of this relationship, which are mainly regression analyses of macro time-series data. A micro-simulation methodology is adopted that combines a macro-level house price model with a micro-level household formation model. The case study is Scotland, a country that is expected to age rapidly in the future. The parameters of the household formation model are estimated with panel data from the British Household Panel Survey covering the period 1999-2008. The estimates are then used to carry out a set of simulations. The simulations are based on a set of population projections that represent a considerable range in the rate of population ageing. The main finding from the simulations is that population ageing – or more generally changes in age structure – is not likely a main determinant of house prices, at least in Scotland.

Escaping Poverty: Rural Low-Income Mothers' Opportunity to Pursue Post-Secondary Education

Using human capital theory, this paper identifies the factors that may affect the opportunity for rural low-income mothers to pursue post-secondary education or training in order to escape poverty. Dependent variables used in the logistic regression model included micro-level household variables as well as the effects of state-wide welfare policies. Data for [the authors'] sample of rural low-income mothers came from two waves of a [United States Department of Agriculture] USDA-funded multistate, longitudinal project. The variables that were statistically significant in determining rural mothers' post-secondary educational opportunities included the tuition and fees for a community/technical college, whether or not the participant's father had a post-secondary education, whether or not the participant was living with a partner, the presence of a pre-school aged child, and whether or not the participant lived in a state that had strict Temporary Assistance for Needy Families program (TANF) work requirements.

Long‐Run Stockholder Consumption Risk and Asset Returns

ABSTRACTWe provide new evidence on the success of long‐run risks in asset pricing by focusing on the risks borne by stockholders. Exploiting microlevel household consumption data, we show that long‐run stockholder consumption risk better captures cross‐sectional variation in average asset returns than aggregate or nonstockholder consumption risk, and implies more plausible risk aversion estimates. We find that risk aversion around 10 can match observed risk premia for the wealthiest stockholders across sets of test assets that include the 25 Fama and French portfolios, the market portfolio, bond portfolios, and the entire cross‐section of stocks.

Economic Profiles of Morbidity: Measures and Illustrations for a Developing Country

This paper proposes measures to identify how prevalence of various diseases and disease groups vary by economic status of the household so as to permit categorization of diseases into those associated with deprivation and affluence respectively. For this purpose, the study estimates (i) pseudo-Lorenz ratio for distribution of morbidity (as measured by the number of household members reporting an ailment) with respect to the household's economic status (as measured by the household per capita consumption expenditure); and (ii) Engel elasticity of morbidity with respect to the household's economic status by disease, individually as well as broad group wise. The paper illustrates with economic gradients in morbidity disaggregated by disease using household level micro data from the 60th round of the National Sample Survey for the State of Kerala in India and for India, the country as a whole. Among the results, one noteworthy finding is that the rich have higher morbidity rates than the poor, although this varies by disease.

Exploring Economic Profiles of Morbidity: Measures and Illustrations with Indian Data

This paper proposes measures to identify how prevalence of various diseases and disease groups vary by economic status of the household so as to permit categorization of diseases into those associated with deprivation and affluence respectively. For this purpose, the study estimates (i) pseudo-Lorenz ratio for distribution of morbidity (as measured by the number of household members reporting an ailment) with respect to the household's economic status (as measured by the household per capita consumption expenditure); and (ii) Engel elasticity of morbidity with respect to the household's economic status by disease. The paper illustrates with economic gradients in morbidity disaggregated by disease using household level micro data from the 60 th round of the National Sample Survey for the state of Kerala in India and for India as a whole. Among the results, one particularly noteworthy is that the rich have higher morbidity rates than the poor, although this varies by disease.

Long-Run Stockholder Consumption Risk and Asset Returns

We provide new evidence on the success of long-run risks in asset pricing by focusing on the risks borne by stockholders. Exploiting micro-level household consumption data, we show that long-run stockholder consumption risk better captures cross-sectional variation in average asset returns than aggregate or non-stockholder consumption risk, and provides more plausible economic magnitudes. We find that risk aversion estimates around 10 can match observed risk premia for the wealthiest stockholders across sets of test assets that include the 25 Fama and French size and value portfolios, the market portfolio, bond portfolios, and the entire cross-section of stocks.

Is cigarette smoking in poorer nations highly sensitive to price?: Evidence from Russia and China

We examine cigarette demand in China and Russia using longitudinal micro-level household and community surveys. Previous developing-country price elasticity estimates of around −0.75 have been larger than United States estimates of about −0.4, but the former have relied primarily on aggregate data. In contrast, our micro-level price elasticity estimates in China and Russia range from 0 to −0.15. Thus, raising prices in poorer countries may not reduce smoking to the degree previously suggested.

Urban Form and Travel Behaviour: Micro-level Household Attributes and Residential Context

Many countries now have policies to reduce distances travelled by private car and to favour the use of public transport, cycling and walking. The development of compact urban forms and the design of urban communities which favour walking are seen as particularly effective strategies for reducing car dependency. The factors which determine travel behaviour are not fully understood, so that effective policies influencing travel patterns are difficult to formulate. Apart from urban form and design, personal attributes and circumstances have an impact on modal choice and distances travelled. People with higher incomes are more likely to own and use a private car than low-income households. Families with children use cars more often than one-person households. The purpose of a trip-work, shopping and leisure—also influences travel mode and distance. We used the Netherlands National Travel Survey (OVG) to explore some of these relationships in more depth. The relative importance of personal attributes and the characteristics of residential environments as determinants of modal choice and travel distance were explored. Both sets of factors maintain a clear, strong relationship with travel behaviour in multivariate models of travel behaviour.

Understanding Brand Competition Using Micro and Macro Scanner Data

Recent advances in data gathering through checkout scanners have produced vast amounts of data on the actual behavior of consumers in the marketplace, creating new opportunities for managers and researchers to understand competition and consumers’ response to the marketing mix. Previous analyses of this data in the literature have focused either at the household (micro) or store (macro) level. The authors propose a method of enriching the analysis of competitive behavior by combining the in-depth consumer information obtained from a micro-level household scanner panel with the comprehensive market data supplied by a macro-level retail-tracking panel. The approach offers the manager detailed information about consumers (e.g., identification of consumer segments in terms of brand preferences and socioeconomic characteristics) along with strategic diagnostics of the product-market (e.g., the sensitivity of the market to price promotions, impact of a brand's strategy on competitors, vulnerability of the brand to competitive actions).