Discrete choice models of family labour supply

Choice Theory;Labour Supply

Health and Wealth of Elderly Couples: Causality Tests Using Dynamic Panel Data Models

A positive relationship between socio-economic status (SES) and health, the so-called \health-wealth gradient", is repeatedly found in most industrialized countries with similar levels of health care technology and economic welfare. This study analyzes causality from health to wealth (health causation) and from wealth to health (wealth or social causation) for elderly couples in the US. Using six biennial waves of couples aged 51-61 in 1992 from the Health and Retirement Study, we compare the recently developed strategy using Granger causality tests of Adams et al.(2003, Journal of Econometrics) with tests for causality in dynamic panel data models incorporating unobserved heterogeneity. While Adams et al. tests reject the hypothesis of no causality from wealth to husband's or wife's health, the tests in the dynamic panel data model do not provide evidence of wealth-health causality.On the other hand, both methodologies lead to strong evidence of causal e®ects from both spouses' health on household wealth.health;wealth;panel data;inequality;ageing

Family Structure and Female Labour Supply in Mexico City

This paper investigates labour supply of the wives of the heads of households in Mexico City, with a focus on the impact of family structure. A static neoclassical structural model is used. We assume that each woman chooses her labour supply and corresponding income so that her utility is maximized, conditional upon her husband’s labour supply and earnings. We use a direct translog specification, and include family composition variables as taste shifters. Also taken into account are fixed costs of working, nonlinear taxes, unobserved preference variation, prediction errors in wages of nonworkers, and potential endogeneity of wages. The models are estimated by smooth simulated maximum likelihood using data from Mexico’s Urban Employment Survey drawn in 1992. We find income elasticities of labour supply of about -0.35, and wage elasticities of about 0.5. The latter is substantially overestimated if wage rate endogeneity is not taken into account. The results are robust with respect to other specification choices. We find that the impact of family structure variables on participation is different from that on hours worked, so that their total effect is ambiguous.Female labour supply;family structure;discrete regression

Infant Mortality in Rural Bangladesh: State Dependence vs. Unobserved Heterogeneity

Using longitudinal data of the Health and Demographic Surveillance System (HDSS) in Matlab, Bangladesh, covering the time period 1982 – 2005, and exploiting dynamic panel data models, we analyze siblings’ death at infancy, controlling for unobserved heterogeneity and a causal effect of death of one child on survival chances of the next child. Matlab is a rural area split into two: a “treatment” area where along with standard government services extensive maternal and child health interventions are available, and a “comparison” area where only the standard government services are available. The observed infant mortality rates are 50 per 1,000 live births in the treatment area and 67.4/1,000 in the comparison area. We use separate models for the two areas and analyze the differences in infant mortality between the two areas using several decompositions. Our model predicts that in the comparison area, the likelihood of infant death is about 30% larger if the previous sibling died at infancy than if it did not, and the estimates suggest that, in the absence of this “scarring” effect, the infant mortality rate among the second and higher order births would fall by 6.2%. There is no evidence of such a scarring effect in the treatment area, perhaps because learning effects play a larger role with the available extensive health interventions. We find that distance to the nearest health clinic can explain a substantial part of the gap in infant mortality between the two areas.childhood mortality;millennium goals;death clustering;dynamic panel data models

Mode and Context Effects of Measuring Household Assets

Differences in answers in Internet and traditional surveys can be due to selection, mode, or context effects. We exploit unique experimental data to analyze mode and context effects controlling for arbitrary selection. The Health and Retirement Study (HRS) surveys a random sample of the US 50+ population, with CAPI or CATI core interviews once every two years. In 2003 and 2005, random samples were drawn from HRS respondents in 2002 and 2004 willing and able to participate in an Internet interview. Comparing core and Internet survey answers of the same people, we analyze mode and context effects, controlling for selection. We focus on household assets, for which mode effects in Internet surveys have rarely been studied. We find some large differences between the first Internet survey and the other three surveys which we interpret as a context and question wording effect rather than a pure mode effect.Internet surveys;CAPI;CATI;portfolio choice

A Test for Anchoring and Yea-Saying in Experimental Consumption Data

In the experimental module of the AHEAD 1995 data, the sample is randomly split into respondents who get an open-ended question on the amount of total family consumption - with follow-up unfolding brackets (of the form: is consumption $X or more?) for those who answer don't know' or refuse' - and respondents who are immediately directed to unfolding brackets. In both cases, the entry point of the unfolding bracket sequence is randomized. These data are used to develop a nonparametric test for whether people make mistakes in answering the first bracket question, allowing for any type of selection into answering the open-ended question or not. Two well-known types of mistakes are considered: anchoring and yea-saying (or acquiescence). While the literature provides ample evidence that the entry point in the first bracket question serves as an anchor for follow-up bracket questions, it is less clear whether the answers to the first bracket question are already affected by anchoring. We reject the joint hypothesis of no anchoring and no yea-saying at the entry point. Once yea-saying is taken into account

Does Income Taxation Affect Partners’ Household Chores?

We study the impact of income taxation on both partners‟ allocation of time to market work and unpaid house work in households with two adults. We estimate a structural household utility model in which the marginal utilities of leisure and house work of both partners are modelled as random coefficients, depending on observed and unobserved characteristics of the household and the two partners. We use a discrete choice model with choice sets of 2,401 points for each couple, distinguishing seven market work intervals and seven house work intervals for each partner. The model is estimated using data for France, which taxes incomes of married couples jointly, like, for instance, Germany and the US. We find that both partners‟ market and non-market time allocation decisions are responsive to changes in the tax system or other policy changes that change the financial incentives. Women‟s time allocation is more responsive to the own and the partner‟s wage rate than men‟s. Tax policy simulations suggest that moving from joint taxation for married couples to separate taxation of each spouse would go a small step in the direction of equalizing market and non-market work of spouses. Selective taxation with smaller tax rates for women than for men would magnify these effects.time use;taxation;labour supply;discrete choice models

The Fixed-Effects Zero-Inflated Poisson Model with an Application to Health Care Utilization

Response variables that are scored as counts and that present a large number of zeros often arise in quantitative health care analysis. We define a zero-in flated Poisson model with fixed-effects in both of its equations to identify respondent and health-related characteristics associated with health care demand. This is a new model that is proposed to model count measures of health care utilization and account for the panel structure of the data. Parameter estimation is achieved by conditional maximum likelihood. An application of the new model is implemented using micro level data from the 2004-2006 Survey of Health, Ageing and Retirement in Europe (SHARE), and compared to existing panel data models for count data. Results show that separately controlling for whether outcomes are zero or positive in one of the two years does make a difference for counts with a larger number of zeros.Count Data;Zero-In ated Poisson Model;Fixed-effects;SHARE

Female labour supply in farm households: Farm and off-farm participation

Female Workers;Farms;Labour Supply

Parametric and semi-parametric modelling of vacation expenditures

Consumer Choice;Recreation