Economics and Finance

This research note examines the conditions which will induce a prospect theory type investor, whose reference level is set by ‘playing it safe’, to invest in a risky asset. The conditions indicate that this type of investor requires a large equity premium to invest in risky assets. However, once she does invest because of a large risk premium, she becomes aggressive and buys/sells till an externally imposed upper/lower bound is reached.

We consider Bayesian estimation of restricted conditional moment models with linear regression as a particular example. The standard practice in the Bayesian literature for semiparametric models is to use flexible families of distributions for the errors and assume that the errors are independent from covariates. However, a model with flexible covariate dependent error distributions should be preferred for the following reasons: consistent estimation of the parameters of interest even if errors and covariates are dependent; possibly superior prediction intervals and more efficient estimation of the parameters under heteroscedasticity. To address these issues, we develop a Bayesian semiparametric model with flexible predictor dependent error densities and with mean restricted by a conditional moment condition. Sufficient conditions to achieve posterior consistency of the regression parameters and conditional error densities are provided. In experiments, the proposed method compares favorably with classical and alternative Bayesian estimation methods for the estimation of the regression coefficients.

Beer sales in Germany are confronted for several years with a shrinking market share in the market of alcoholic beverages. I use the approach of sales response function (SRF) models as in Polasek and Baier (2010) and adapt it to time series observation of beer sales for simultaneous estimation. I propose a new class of growth sales (gSRF) models having endogenous and exogenous variables as in Polasek (2011) together with marketing efforts that follow a sustained growth allocation principle. This approach allows to model growth rates in markets that are exposed to fierce competition and where marketing efforts cannot be evaluated directly. The class of gSRF models has the property that it models supply (i.e. marketing efforts) and demand factors jointly in a log-linear regression model that are correlated over time. The estimated model can explain the relative success of marketing expenditures for the shrinking beer market in the period 1999-2010.

This research examines capital income taxation for a loss averse investor under some acceptable in the literature reference levels relative to which are the changes in the level of wealth valued. Depending on the reference level, some results indicate that it could be possible for a capital income tax increase not to stimulate risk taking even if the tax code provides the attractive full loss offset provisions. However, risk taking can be stimulated if the investor interprets part of the tax as a loss instead as a reduced gain. Then investor becomes risk seeking and moves away from the discomfort zone of relative losses. This later response to taxation causes private risk taking to increase which is contrary to what evolves from assuming an expected utility model. Finally, a number of other reference standards are examined as well.

This paper considers Bayesian nonparametric estimation of conditional densities by countable mixtures of location-scale densities with covariate dependent mixing probabilities. The mixing probabilities are modeled in two ways. First, we consider finite covariate dependent mixture models, in which the mixing probabilities are proportional to a product of a constant and a kernel and a prior on the number of mixture components is specified. Second, we consider kernel stick-breaking processes for modeling the mixing probabilities. We show that the posterior in these two models is weakly and strongly consistent for a large class of data generating processes.

We study the relationship between education and fertility, exploiting compulsory schooling reforms in Europe as source of exogenous variation in education. Using data from 8 European countries, we assess the causal effect of education on the number of biological kids and the incidence of childlessness. We find that more education causes a substantial decrease in childlessness and an increase in the average number of children per woman. Our findings are robust to a number of falsification checks and we can provide complementary empirical evidence on the mechanisms leading to these surprising results.

We study the contribution of health-related behaviors to the health-education gradient by distinguishing between short-run and long-run mediating effects:while in the former only current or lagged behaviors are taken into account, in the latter we consider the entire history of behaviors. We use an empirical approach that addresses the endogeneity of education and behaviors in the health production function. Focusing on self-reported poor health as our health out-come, we find that education has a protective effect for European males and females aged 50+. We also find that the mediating effects of health behaviors - measured by smoking, drinking, exercising and the body mass index – account in the short run for 17% to 31% and in the long run for 23% to 45% of the entire effect of education on health, depending on gender.

We investigate the impact of self-organized reputation versus certification by an independent institution on demand for online shops. Using data from a large Austrian price comparison site, we show that quality seals issued by a credible and independent institution increase demand more than feedback-based reputation. This result is important for markets where the market-maker must deal with issues of asymmetric information concerning the quality of goods and services in the market.

The authors investigate the employment consequences of minimum wage regulation in 16 OECD countries, 1970-2008. Their treatment is motivated by Neumark and Wascher’s (2004) seminal cross-country study. Apart from the longer time interval examined, a major departure is the authors’ focus on prime-age females, a group often neglected in the minimum wage literature. Another is their deployment of time-varying policy and institutional regressors. The average effects they report are consistent with minimum wages causing material employment losses among the target group. Their secondary finding is that minimum wage increases are more associated with (reduced) participation rates than with elevated joblessness. Further, although the authors find common ground with Neumark and Wascher as regards the role of some individual labor market institutions and policies, they do not observe the same patterns in the institutional data. Specifically, prime-age females do not exhibit stronger employment losses in countries with the least regulated markets.

The Hodrick-Prescott (HP) method is a popular smoothing method for economic time series to get a smooth or long-term component of stationary series like growth rates. We show that the HP smoother can be viewed as a Bayesian linear model with a strong prior using differencing matrices for the smoothness component. The HP smoothing approach requires a linear regression model with a Bayesian conjugate multi-normal-gamma distribution. The Bayesian approach also allows to make predictions of the HP smoother on both ends of the time series. Furthermore, we show how Bayes tests can determine the order of smoothness in the HP smoothing model. The extended HP smoothing approach is demonstrated for the non-stationary (textbook) airline passenger time series. Thus, the Bayesian extension of the HP model defines a new class of model-based smoothers for (non-stationary) time series and spatial models.