Birth Spacing and Neonatal Mortality in India: Dynamics, Frailty and Fecundity

fertility;birth spacing;childhood mortality;health;dynamic panel data models;siblings

Household Portfolios in the Netherlands

We describe and analyse the portfolio structure of Dutch households using micro panel data from the CentER Savings Survey, 1993-1998.The data allows for a distinction between many types of assets.Moreover, we have information on mortgage debt, consumer debt, etc.We analyse the composition of household portfolios and the level of portfolio diversification, and its relation to age, birth cohort, and education level.We compare the ownership rates and amounts held in our survey data with published statistics derived from National Accounts and administrative data.Using discrete choice models and selection models, we relate asset ownership and asset shares to background variables such as age, household composition, education, etc.Moreover, we include subjectively measured explanatory variables reflecting attitudes towards risk and the degree of information the respondent has on financial assets.We consider static as well as dynamic panel data models.Portfolio Choice;Panel Data

Household portfolio allocation in the Netherlands: Saving accounts versus stocks and bonds

This paper analyzes the portfolio structure of households in the Netherlands. It considers the allocation of financial wealth to two major asset categories, namely saving accounts on the one hand and stocks and bonds on the other hand. The latter category is considered to be more risky than the former. We analyze the impact of the overall level of wealth, the marginal tax rate, and other variables on the allocation between assets, using cross-section data drawn in 1988 that provide detailed information on the structure of household wealth, not only on ownership but also on the amounts of wealth held in the respective asset categories. The econometric specification is a trivariate tobit type model. One equation explains the total level of wealth, a second one explains individual threshold values below which no wealth is held. The third equation explains the share of wealth invested in stocks and bonds. The model is estimated using Full Information Maximum Likelihood. Limited information provided by the data (non reporting) is explicitly taken into account. Results show that wealth and the marginal tax rate are major determinants of the allocation between safe and risky assets.Portfolio Investment;Bonds;Household Economics;Savings;Stocks;microeconomics

Ownership of Stocks and Mutual Funds: A Panel Data Analysis

In many industrial countries, ownership rates of risky assets have risen substantially over the past decade.This trend has potentially wide-ranging implications for the intertemporal and cross-sectional allocation of risk, and for the macro economy, establishing the need for understanding ownership dynamics at the micro level.This paper offers one of the first such analyses using representative panel survey data.We focus on the two main types of risky financial assets, mutual funds and individual stocks.We extend existing univariate dynamic binary choice models to the multivariate case and take account of interactions between the two types of assets.The models are estimated on data from the 1993-1998 waves of the Dutch CentER Savings Survey.We find that both unobserved heterogeneity and state dependence play a large role for both types of assets.Most of the positive relation between ownership of mutual funds in one period and ownership of individual stocks in the next period or vice versa, is explained by unobserved heterogeneity: if we account for correlation between the household specific effects in the two binary choice equations, we find a negative effect of lagged ownership of stocks on the ownership of mutual funds.These findings can be explained by adjustment costs that make it optimal to stick to one type of asset.stock ownership;investment trusts;panel data

Actions and Beliefs: Estimating Distribution-Based Preferences Using a Large Scale Experiment with Probability Questions on Expectations

We combine the choice data of proposers and responders in the ultimatum game, their expectations elicited in the form of subjective probability questions, and the choice data of proposers ("dictator") in a dictator game to estimate a structural model of decision making under uncertainty.We use a large and representative sample of subjects drawn from the Dutch population.Our results indicate that there is considerable heterogeneity in preferences for equity in the population.Changes in preferences have an important impact on decisions of dictators in the dictator game and responders in the ultimatum game, but a smaller impact on decisions of proposer's in the ultimatum game, a result due to proposers subjective expectations about responders' decisions.The model which uses subjective data on expectations has better predictive power and lower noise level than a model which assumes that players have rational expectations.ultimatum game;inquity aversion;subjective expectations

Preferences, Intentions, and Expectations: A Large-Scale Experiment With a Representative Subject Pool

We specify and estimate an econometric model which separately identifies distributional preferences and the effects of perceived intentions on responder behavior in the ultimatum game. We allow the effects of perceived intentions to depend, among other things, on the subjective probabilities responders attach to the possible offers. We estimate the model on a large representative sample from the Dutch population. We find that the relative importance of distributional preferences and perceived intentions depends significantly on the socioeconomic characteristics of responders. Strong inequity aversion to the other player’s disadvantage is found for lower educated and older respondents. Responders tend to punish unfavorable offers more if they expect that fair proposals will occur with higher probability.Inequity aversion;intentions;subjective expectations

The Perception of Small Crime

Violations of social norms can be costly to society and they are, in the case of large crimes, followed by prosecution. Minor misbehaviors — small crimes — do not usually result in legal proceedings. Although the economic consequences of a single small crime can be low, such crimes generate substantial losses in the aggregate. In this paper we measure perceptions of incorrect behavior or ‘small crime’, based on a questionnaire administered to a large representative sample from the Dutch population. In the questionnaire we ask the respondents to rate the severity and justifiability of a number of small crimes. We present short questions that only state the nature of the small crime, as well as vignette questions, describing in detail the fictitious person committing the small crime and other factors related to the circumstances in which the small crime is committed. We find that the perceived severity of small crimes varies systematically with characteristics of the respondent as well as of the person committing the crime. Small crimes are considered less serious if committed by someone with lower income. Also, the association between respondent characteristics and perceived seriousness changes if the respondents are given more information about the offender and the circumstances of the offense.Crime seriousness;Social norms;Vignettes

Peer Reporting and the Perception of Fairness

Economic motives are not the only reasons for committing a (small) crime. People consider social norms and perceptions of fairness before judging a situation and acting upon it. If someone takes a bundle of printing paper from the office for private use at home, then a colleague who sees this can either report it or not: peer reporting. We investigate how fairness perception influences peer reporting in this situation of incorrect behavior.Peer reporting;Perception;Social norms;Fairness;Employee theft;Victimization