Volume 241, Issue 4

Based on an incentivized non-anonymous trust game with 230 elementary school pupils aged between 6 and 11 years, we investigate the development of trust and trustworthiness across age groups. Trust increases with age, thereby increasing the profits of both the trustor and the trustee. The trustee keeps most of the profits. These results replicate the findings of Sutter and Kocher (2007) in that trust increases with age and trustworthiness exists in all age groups that are examined in our study; however, the amounts transferred between subjects in our experiment are substantially higher, a result which is likely to be driven by the non-anonymity in our setting.

The compilation of commercial property price indices (CPPIs) is challenging. Policymakers urge for timely, reliable and comprehensive data. In Germany, lack of data prevents the calculation of official figures by the national statistical authority. Different applications of price indices need different definitions of commercial real estate. CPPIs according to these definitions are constructed on the basis of existing data for 127 German towns and cities (that cover about one-third of German population). The overall price developments revealed by the various indices are rather similar in terms of central time series characteristics, while differences in detail can be explained by their specific compositions. Price increases for all definitions have been strongest in the seven largest cities. The definitions tend to lead to more marked differences for medium-sized towns.

This work presents novel results obtained by the application of global optimization techniques to the design of finite, normal form games with mixed strategies. To that end, the Fuzzy ASA global optimization method is applied to several design examples of strategic games, demonstrating its effectiveness in obtaining payoff functions whose corresponding games present a previously established Nash equilibrium. In other words, the game designer becomes able to choose a convenient Nash equilibrium for a generic finite state strategic game and the proposed method computes payoff functions that will realize the desired equilibrium, making it possible for the players to reach the favorable conditions represented by the chosen equilibrium. Considering that game theory is a very useful approach for modeling interactions between competing agents and Nash equilibrium represents a powerful solution concept, it is natural to infer that the proposed method may be very useful for strategists in general. In summary, it is a genuine instance of artificial inference of payoff functions after a process of global machine learning, applied to their numerical components.

We examine the notion of a price index as the solution to the problem of minimizing the distance between the index values and the vector of price ratios. To do so, the choice of a suitable distance function is of crucial importance. We use a generalized least-squares criterion for this purpose and show that the generalized quasilinear functions are the only solutions to the problem of minimizing the distance thus defined. There are numerous special cases that are obtained for specific choices of the requisite functions and weights. In particular, we show that, in addition to the well-established indexes of Laspeyres, Paasche, Marshall-Edgeworth, Walsh, and Törnqvist, the arithmetic-current-period index, the arithmetic-hybrid index, the harmonic-base-period index, and the harmonic-hybrid index can be obtained with suitably chosen distance functions. Furthermore, the logarithmic least-squares criterion is employed to obtain indexes that are based on geometric means.

Vector autoregressions (VARs) are richly parameterized time series models that can capture complex dynamic interrelationships among macroeconomic variables. However, in small samples the rich parametrization of VAR models may come at the cost of overfitting the data, possibly leading to imprecise inference for key quantities of interest such as impulse response functions (IRFs). Bayesian VARs (BVARs) can use prior information to shrink the model parameters, potentially avoiding such overfitting. We provide a simulation study to compare, in terms of the frequentist properties of the estimates of the IRFs, useful strategies to select the informativeness of the prior. The study reveals that prior information may help to obtain more precise estimates of impulse response functions than classical OLS-estimated VARs and more accurate coverage rates of error bands in small samples. Strategies based on selecting the prior hyperparameters of the BVAR building on empirical or hierarchical modeling perform particularly well.

This article highlights the potentials for migration research using the German Socio-Economic Panel Study (SOEP), a longitudinal panel dataset of private households in Germany running since 1984. We provide a concise overview of its basic features, describe the survey contents and research potentials, and demonstrate opportunities to link external data sources to the SOEP thereby presenting its diverse and impactful applications in migration research.