Household Composition and Savings: An Overview

In recent years the literature on household saving behavior has been enriched by a number of contributions focusing on the problem of modeling a household as a single decision unit. It has reasonably been argued that with respect to household consumption and saving behavior the simple approach of modeling households as one representative decider could involve major mistakes. Thus the literature has enriched the basic model by incorporating variables that describe the composition of a household examples being the number and age of children, household member�s life expectancies and the intra-household distribution of income. This paper reviews these developments and empirical results in the latest literature, with a particular focus on intra-household income distributions.

On the Equivalence of Common Approaches to Cross Sectional Weights in Household Panel Surveys

The computation of cross sectional weights in household panels is challenging because household compositions change over time. Sampling probabilities of new household entrants are generally not known and assigning them zero weight is not satisfying. Two common approaches to cross sectional weighting address this issue: (1) "shared weights" and (2) modeling or estimating unobserved sampling probabilities based on person-level characteristics. We survey how several well-known national household panels address cross sectional weights for different groups of respondents (including immigrants and births) and in different situations (including household mergers and splits). We show that for certain estimated sampling probabilities the modeling approach gives the same weights as fair shares, the most common of the shared weights approaches. Rather than abandoning the shared weights approach when orphan respondents (respondents in households without sampling weights) exist, we propose a hybrid approach; estimating sampling weights of newly orphan respondents only.BHPS, HILDA, PSID, SOEP, modeled weights, shared weights, fair shares

Equivalence Scale and Poverty Assessment in a Poor Country

Mainly due to the dearth of available data, this article empirically illustrates that the practice of using household expenditures/incomes in assessing aggregate poverty tends to its overestimation. In the absence of reliable equivalence estimates, household size should be normalized to improve the estimation results.poverty, econometric modeling

Poverty and Income Distribution in a CGE-Household Micro-Simulation Model: Top-Down/Bottom Up Approach

This paper highlights the idea of combining CGE modeling with a micro-household model (micro-simulation) to generate a convergent solution, thus providing the basis to perform counterfactual analysis of trade and fiscal policies, and their impact on poverty. In recent years, a number of papers have presented differen approaches using CGE models to analyze poverty. Among them, the standard CGE models, which generates changes in the income of representative households in order to allow poverty analysis, albeit with no intra-group changes in the distribution; CGE models with high levels of household disaggregation (3200) and the micro-simulation approach to modeling (with no feedback effect to the CGE model). In this paper, we provide an alternative to these methods that allows a richer micro-household modeling than the first two approaches, while keeping the properties of standard CGE (feedback effect of household behavior) which is usually simplified in micro-simulation context. We also introduce segmented labor markets, with waiting unemployment, inspired by Magnac (1991), which provides a basis for important changes in household income (i.e. when a worker leaves unemployment or becomes unemployed). Global and decomposable poverty analysis and income distribution indicators are computed at base year and after a 50% reduction in trade.Computable general equilibrium models, estimation, personal income and wealth distribution, measurement and analysis of poverty

On Modeling Household Labor Supply With Taxation

Discrete choice models of labor supply easily account for nonlinearity and nonconvexity in budget sets caused by tax-benefit systems. As a result, they have become very popular for ex ante evaluations of policy reforms. In this paper, we question whether the degree of flexibility and the implicit household representation in these models are satisfying when confronted to the data. First, we show that attempts to interpret discrete models structurally lead to unnecessary parametric restrictions in most studies. We suggest instead a fully flexible model that retains usual assumptions on economic rationality except regularity conditions on leisure. Indeed, coefficients may account for both tastes and costs of work, possibly making 'preferences' appear nonconvex. Second, we show that the static unitary representation, implicit in most tax policy analyses, is rejected against a more general model with price- and income- dependent preferences. The latter can be rationalized in terms of collective or intertemporal models and offers promising perspectives in these directions. Simulations show that the magnitude of predicted labor supply responses to tax-benefit reforms is sensitive to the underlying household representation.multinomial logit, household labor supply, tax reform, unitary model, collective model

A HOUSEHOLD PRODUCTION ANALYSIS OF FUELWOOD DEMAND IN RHODE ISLAND

A model analyzing household substitution of fuelwood for other heating fuels is needed to clarify the relationship between energy prices and patterns of forest resource utilization. This paper employs the household production methodology to model fuelwood demand in Rhode Island. Data from a cross-sectional survey of 515 households are employed to test a discrete-choice model of household participation in wood-burning and a four-equation system modeling household production of heat and aesthetic benefits from fuelwood and stove capital. Control of selection bias via inclusion of an appropriate instrument allows analysis of aggregate demands. Some broad policy prescriptions applicable to the Northeast generally are presented.Resource /Energy Economics and Policy,

Modeling Unobserved Consideration Sets for Household Panel Data

We propose a new method to model consumers' consideration and choice processes. We develop a parsimonious probit type model for consideration and a multinomial probit model for choice, given consideration. Unlike earlier models of consideration ours is not prone to the curse of dimensionality, while we allow for very general structures of unobserved dependence in consideration among brands. In addition, our model allows for state dependence and marketing mix effects on consideration.Unique to this study is that we attempt to establish the validity of existing practice to infer consideration sets from observed choices in panel data. To this end, we use data collected in an on-line choice experiment involving interactive supermarket shelves and post-choice questionnaires to measure the choice protocol and stated consideration levels. We show with these experimental data that underlying consideration sets can be successfully retrieved from choice data alone and that there is substantial convergent validity of the stated and inferred consideration sets. We further find that consideration is a function of point-of-purchase marketing actions such as display and shelf space, and of consumer memory for recent choices.Next, we estimate the model on IRI panel data. We have three main results. First, compared with the single-stage probit model, promotion effects are larger and are inferred with smaller variances when they are included in the consideration stage of the two-stage model. Promotion effects are significant only in the two-stage model that includes consideration, whereas they are not in a single-stage choice model. Second, the price response curves of the two models are markedly diferent. The two-stage model offers a nice intuition for why promotional price response is different from regular price response. In addition and consistent with intuition, the two-stage model also implies that merchandizing has more effect on choice among those who did not buy the brand before than among those who already did. It is explained why a single-stage model does not harbor this feature. In fact, the single-stage model implies the opposite for smaller or more expensive brands. Third, we find that the consideration of brands does not covary greatly across brands once we take account of observed effects. Managerial implications and future research are also discussed.Consideration;choice;probit models

Modeling within-household associations in household panel studies

Household panel data provide valuable information about the extent of similarity in coresidents' attitudes and behaviours. However, existing analysis approaches do not allow for the complex association structures that arise due to changes in household composition over time. We propose a flexible marginal modeling approach where the changing correlation structure between individuals is modeled directly and the parameters estimated using second-order generalized estimating equations (GEE2). A key component of our correlation model specification is the 'superhousehold', a form of social network in which pairs of observations from different individuals are connected (directly or indirectly) by coresidence. These superhouseholds partition observations into clusters with nonstandard and highly variable correlation structures. We thus conduct a simulation study to evaluate the accuracy and stability of GEE2 for these models. Our approach is then applied in an analysis of individuals' attitudes towards gender roles using British Household Panel Survey data. We find strong evidence of between-individual correlation before, during and after coresidence, with large differences among spouses, parent-child, other family, and unrelated pairs. Our results suggest that these dependencies are due to a combination of non-random sorting and causal effects of coresidence

Car Road Charging: Impact Assessment on German and Austrian Households

The authors apply a computable general equilibrium (CGE) modeling framework to carry out a two-country comparison for Austria and Germany assessing the impact of road charging (RC). The pricing policy measure is introduced for the private motorized transport mode and applies to the overall road network. To derive and compare distributional effects of passenger car RC, the mode-specific travel demand of private households is integrated into the CGE model. Furthermore, the modeling framework accounts for different household categories with respect to disposable net income and the corresponding travel demand profiles introduced in terms of behavioral mobility parameters as well as household travel expenditures. Comparing the country-specific results, we find country-specific differences in the impact of RC on household categories, as well as similarities. The differences that we find indicate the importance of particular parameters for the evaluation of infrastructure pricing policy reforms. We can relate differences to prevalent country-specific differences in sociodemographic characteristics, land use structure, territorial population distribution, as well as macroeconomic indicators. To add substance to the two-country impact assessment, a sensitivity analysis is carried out, introducing different RC revenue use schemes. We find differences in distributional effects under equity concerns to be closely related to the revenue use pattern as well as to country- and household-specific travel demand profiles.Computable general equilibrium model, redistributive effects, road charging

Impacts of household sources on air pollution at village and regional scales in India

Approximately 3 billion people worldwide cook with solid fuels, such as wood, charcoal, and agricultural residues. These fuels, also used for residential heating, are often combusted in inefficient devices, producing carbonaceous emissions. Between 2.6 and 3.8 million premature deaths occur as a result of exposure to fine particulate matter from the resulting household air pollution (Health Effects Institute, 2018a; World Health Organization, 2018). Household air pollution also contributes to ambient air pollution; the magnitude of this contribution is uncertain. Here, we simulate the distribution of the two major health-damaging outdoor air pollutants (PM2:5 and O3) using state-of-thescience emissions databases and atmospheric chemical transport models to estimate the impact of household combustion on ambient air quality in India. The present study focuses on New Delhi and the SOMAARTH Demographic, Development, and Environmental Surveillance Site (DDESS) in the Palwal District of Haryana, located about 80 km south of New Delhi. The DDESS covers an approximate population of 200 000 within 52 villages. The emissions inventory used in the present study was prepared based on a national inventory in India (Sharma et al., 2015, 2016), an updated residential sector inventory prepared at the University of Illinois, updated cookstove emissions factors from Fleming et al. (2018b), and PM2:5 speciation from cooking fires from Jayarathne et al. (2018). Simulation of regional air quality was carried out using the US Environmental Protection Agency Community Multiscale Air Quality modeling system (CMAQ) in conjunction with the Weather Research and Forecasting modeling system (WRF) to simulate the meteorological inputs for CMAQ, and the global chemical transport model GEOS-Chem to generate concentrations on the boundary of the computational domain. Comparisons between observed and simulated O3 and PM2:5 levels are carried out to assess overall airborne levels and to estimate the contribution of household cooking emissions