Interpersonal dependency of preferences

Standard decision theoretic models disregard the phenomenon of interpersonal dependency of preferences. In this paper it is argued that interpersonal dependency of preferences is a serious challenge for standard utility theory. First we sketch the more philosophical aspects of the problem and then, using a simple, formal model for the two-person case, we show that interpersonal dependency of preferences generally results in indeterminacy of preferences (resp. of subjective utility).     

Saving and consumption patterns of the elderly

The paper provides an empirical analysis of saving and consumption choices of the elderly in Germany, based on the German income and expenditure surveys 1978 and 1983. Main feature of these data is the large sample size making it possible to analyze saving and consumption patterns of the very old (aged 75 and above).The observed age-consumption profiles are very different from those predicted by the pure life-cycle theory. Although wealth is declining between age 60 and 70, it increases again after 70, such that the very old have the highest savings rates among all age groups and accumulate wealth rather than decumulate it. These profiles are not confounded by cohort effects and mortality differences. The corresponding expenditure data suggest the following explanation: due to the generous German pension system and the almost complete coverage of health expenses by the mandatory health insurance in Germany, the declining consumption n very old age cannot exhaust the annuity income of the elderly such that wealth is being accumulated in old age.Research in this paper was supported by the National Institute on Aging, grant no. 3 PO1 AG05842-01. I appreciate the helpful comments by Doug Bernheim, Angus Deaton, Daniel McFadden, Jonathan Skinner, Konrad 'Stahl and David Wise, and two anonymous referees. I am indebted to Hermann Buslei and Johannes Velling who provided most valuable and able assistance.     

Percentile Related Bounds and Estimator for the Mean of the Negative Binomial Distribution

Upper and lower bounds are obtained for the mean of the negative binomial distribution. These bounds are simple functions of a percentile determined by the shape parameter. The result is then used to obtain a robust estimate of the mean when the shape parameter is known.     

Inference on Causal Effects in a Generalized Regression Kink Design

We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of interest is a known, deterministic, but kinked function of an observed assignment variable. We characterize a broad class of models in which a sharp “Regression Kink Design” (RKD or RK Design) identifies a readily interpretable treatment‐on‐the‐treated parameter (Florens, Heckman, Meghir, and Vytlacil (2008)). We also introduce a “fuzzy regression kink design” generalization that allows for omitted variables in the assignment rule, noncompliance, and certain types of measurement errors in the observed values of the assignment variable and the policy variable. Our identifying assumptions give rise to testable restrictions on the distributions of the assignment variable and predetermined covariates around the kink point, similar to the restrictions delivered by Lee (2008) for the regression discontinuity design. Using a kink in the unemployment benefit formula, we apply a fuzzy RKD to empirically estimate the effect of benefit rates on unemployment durations in Austria.     

Implementing Monte Carlo tests with p-value buckets

Software packages usually report the results of statistical tests using p-values. Users often interpret these values by comparing them with standard thresholds, for example, 0.1, 1, and 5%, which is sometimes reinforced by a star rating (***, **, and *, respectively). We consider an arbitrary statistical test whose p-value p is not available explicitly, but can be approximated by Monte Carlo samples, for example, by bootstrap or permutation tests. The standard implementation of such tests usually draws a fixed number of samples to approximate p. However, the probability that the exact and the approximated p-value lie on different sides of a threshold (the resampling risk) can be high, particularly for p-values close to a threshold. We present a method to overcome this. We consider a finite set of user-specified intervals that cover [0, 1] and that can be overlapping. We call these p-value buckets. We present algorithms that, with arbitrarily high probability, return a p-value bucket containing p. We prove that for both a bounded resampling risk and a finite runtime, overlapping buckets need to be employed, and that our methods both bound the resampling risk and guarantee a finite runtime for such overlapping buckets. To interpret decisions with overlapping buckets, we propose an extension of the star rating system. We demonstrate that our methods are suitable for use in standard software, including for low p-value thresholds occurring in multiple testing settings, and that they can be computationally more efficient than standard implementations.     

The Ambivalent Appraisal of Job Demands and the Moderating Role of Job Control and Social Support for Burnout and Job Satisfaction

Social Indicators Research - Within an extended challenge–hindrance framework, it is assumed that job demands are subjectively appraised both as challenges (that is, as working conditions...     

Stochastic Forecasting of Labor Supply and Population: An Integrated Model

This paper presents a stochastic model to forecast the German population and labor supply until 2060. Within a cohort-component approach, our population forecast applies principal components analysis to birth, mortality, emigration, and immigration rates, which allows for the reduction of dimensionality and accounts for correlation of the rates. Labor force participation rates are estimated by means of an econometric time series approach. All time series are forecast by stochastic simulation using the bootstrap method. As our model also distinguishes between German and foreign nationals, different developments in fertility, migration, and labor participation could be predicted. The results show that even rising birth rates and high levels of immigration cannot break the basic demographic trend in the long run. An important finding from an endogenous modeling of emigration rates is that high net migration in the long run will be difficult to achieve. Our stochastic perspective suggests therefore a high probability of substantially decreasing the labor supply in Germany.     

Urban and peri-urban agriculture and its implication on food and nutrition insecurity in northern Ghana: a socio-spatial analysis along the urban–rural continuum

Food and nutrition insecurity remains a challenge in sub-Saharan Africa. Several studies have examined food and nutrition insecurity in urban or rural areas but have not captured the whole continuum. Between November and December 2013, 240 households were surveyed along the urban–rural continuum in Northern Ghana. The study objective was to understand the socio-spatial dynamics of household food and nutrition insecurity and to investigate the role played by urban, peri-urban and rural agriculture. The study found that there was more involvement in agriculture in rural areas compared to peri-urban areas and urban areas. Households from urban areas were more food insecure (HFIAS >?11) compared to their counterparts in peri-urban and the rural areas. Stunting increased by 3.4 times (p?=?0.048) among households located in the peri-urban area. Wasting was reduced by 0.16 times among household that produced staple food or vegetables (p?=?0.011). Overweight was reduced by 0.04 times among households that produced livestock (p?=?0.031). The results reveal a socio-spatial dimension of food and nutrition insecurity that is related to agricultural activities.