Right-wing extremism is a serious problem in many societies. A prominent hypothesis states that unemployment plays a crucial role for the occurrence of right-wing extremist crime. In this paper we empirically test this hypothesis. We use a previously not used data set which includes all officially recorded right-wing criminal acts in Germany. These data are recorded by the German Federal Criminal Police Office on a monthly and state level basis. Our main finding is that there is in fact a significant positive relation between unemployment and right-wing criminal activities. We show further that the big difference in right-wing crime between East and West German states can mostlynbe attributed to differences in unemployment. This finding reinforces the importance of unemployment as an explanatory factor for right-wing crime and questions explanations based solely on the different socialization in former communist East Germany and the liberal West German states. Our data furthernallow us to separate violent from non-violent right-wing crimes. We show that unemployment is closelynrelated to both types of crimes, but that the association with non-violent crimes is much stronger. Since right-wing crime is committed particularly by relatively young males, we also explore whethernthe youth unemployment rate is a better predictor for right-wing crime than total unemployment. This hypothesis can be rejected: given total unemployment, a higher share of youth unemployment does not affect right-wing extremist crime rates.
Base-rate neglect is a robust experimental finding that individuals do not update their prior beliefs according to the Bayes' rule and, typically, underestimate their posterior probabilities. Another empirical finding is that individuals often do not acquire information even when there are no strategic considerations and the cost of new information is justifiableneconomically. This paper combines these two different fields of research. Specifically, it is demonstrated that base-rate neglect may lead to imperfectninformation acquisition. An application to the pricing of new financial assets as well as general implications for the socially optimal pricing of information are discussed.
Risk management and asset pricing benefit from simple functional descriptions of the distribution of real asset returns. Recently, several authors have proposed that asset returns in real stock markets are distributed according to a hyperbolic distribution. While asset returns are generated by trades over time, the natural question is: What does economic theory imply concerning return distributions? We propose a simple model of price formation and, thus, return distribution which is based on economic reasoning. The market’s behavior is represented by a pair consisting of a time-constant strategy and a dynamical trading strategy generating a flow between funds. Simulations of the price dynamics generate returns with fat-tail behavior in line with that of a hyperbolic distribution, and also volatility clustering, which is a mayor stylized fact of asset returns.
This paper proposes a new model that explains the violations of expected utility theory throughnthe role of random errors. The paper analyzes decision making under risk when individuals makenrandom errors when they compute expected utilities. Errors are drawn from the normal distribution, which is truncated so that the stochastic utility of a lottery cannot be greater (lower) than the utility of the highest (lowest) possible outcome. The standard deviation of random errors is higher for lotteries with a wider range of possible outcomes. It converges to zero for lotteries converging to a degenerate lottery. The model explains all major stylized empirical facts such as the Allais paradox and the fourfold pattern of risk attitudes. The model fits the data from tennwell-known experimental studies at least as good as cumulative prospect theory.
It is well known that ex-ante randomization can improve uponnsecond best contracts in principal-agent problems. In this note, we show that even the first-best can be dominated by a random contract. Our example isncast in a standard textbook set-up with two effort levels and two states of nature.
"The most influential theory of corporate governance, principal agency theory, does not take intonconsideration that the key task of modern corporations is to generate and transfer firm-specific knowledge. It proposes that, in order to overcome the widespread corporate scandals, the interests of top management and directors should be increasingly aligned to shareholder interests by making the board more responsible to shareholders, and strengthening the monitoring of top management by independent outside directors. Corporate governance reform needs to go in another direction altogether. Firm-specific knowledge investments are, like financial investments, not ex ante contractible, leaving investors open to exploitation by shareholders. Employees therefore refuse to make firm-specific investments. To gain a sustainable competitive advantage, there must be an incentive to undertake such firm-specific investments. Three proposals are advanced to deal with this conflict: (1) The board should rely more on insiders. (2) The insidersnshould be elected by those employees of the firm making firm-specific knowledge investments.(3) The board should be chaired by a neutral person. These proposals have major advantages: they provide incentives for knowledge investors; they countervail the dominance of executives; they encourage intrinsic work motivation and loyalty to the firm by strengthening distributive andnprocedural justice, and they ensure diversity on the board while lowering transaction costs. These proposals for reforming the board may help to overcome the crisis corporate governance is in. At the same time, they connect agency theory with the knowledge-based theory of the firm."
Typical of the AIDS epidemics is that governments in developing countries under-invest inndrugs production because of the possible appearance of a curative vaccine. We design a set ofnfinancial tools allowing to hedge against this event and achieving full risk-sharing. We shownthat the introduction of those assets increase social welfare in developing countries, as well asnthe number of treated patients and the provision of public good.
Inspired by findings of low–dimensional nonlinearities and the Theorem of Takens (1983) forecasting models of financial time series are often built upon nonparametric, i.e. universal nonlinear, univariate relationships. Empirical investigations, however, are seriously contaminated by the problem of overfitting. Since statistical model selection theory in the nonlinear case is still in its infancy we would like to suggest the application of economic model selection criteria. It is a method of combining the flexibility of nonparametric regressions and important structural information in dynamic economic models. Therefore, conditions of economic models are imposed on the embedded nonlinear dynamical system to be estimated nonparametrically. In our empirical investigations we apply an univariate nonparametric forecasting model of stock returns, implemented via the Local Linear Maps of Ritter (1991), by an economic model selection criterion based on a discretized form of a continuous–time dynamic model on the interaction of real activity and asset markets. The dynamic economic model is estimated based on the Maximum Entropy inference since unobservable variables are involved. Results for monthly U.S. data show that nonparametric model selection is improved by this economic model selection criterion. On the other hand this result may be interpreted as support for the economic model.
Economic research of the last decade linking macroeconomic fundamentals to asset prices has revealed evidence that standard intertemporal asset pricing theory is not successful in explaining (unconditional) first moments of asset market characteristics such as the risk-free interest rate, equity premium and the Sharpe-ratio. Subsequent empirical research has pursued the question whether those characteristics of asset markets are time varying and, in particular, varying over the business cycle. Recently intertemporal asset pricing models have been employed to replicate those time varying characteristics. The aim of our contribution is (1) to relax some of the assumptions that previous work has imposed on underlying economic and financial variables, (2) to extend the solution technique of Marcet and Den Haan (1990) for those models by nonparametric expectations and (3) to propose a new estimation procedure based on the above solution technique. To allow fornnonparametric expectations in the expectations approach for numerically solving the intertemporal economic model we employ the Local Linear Mapsn(LLMs) of Ritter, Martinetz and Schulten (1992) to approximate conditional expectations in the Euler equation. In our estimation approach based on non-parametric expectations we are able to use full structural information and,nconsequently, Monte Carlo simulations show that our estimations are less biased than the widely applied GMM procedure. Based on quarterly U.S. data we also empirically estimate structural parameters of the model and explore its time varying asset price characteristics for two types of preferences, power utility and habit persistence. We in particular focus on the Sharpe-ratio and find indication that the model is able to capture the time variation of thenSharpe-ratio.
"The most fundamental solution concepts in Game Theory – Nash equilibrium, backward induction, and iterated elimination of dominated strategies – are based on the assumption that people are capable of predicting others' actions. These concepts require people to be able to view the game from the other players’ perspectives, i.e. to understand others’ motives and beliefs. Economists still know little about what enables people to put themselves into others’nshoes and how this ability interacts with their own preferences and beliefs. Social neuroscience provides insights into the neural mechanism underlying our capacity to represent others' intentions, beliefs, and desires, referred to as ""Theory of Mind"" or ""mentalizing"", and the capacitynto share the feelings of others, referred to as ""empathy"". We summarize the major findings about the neural basis of mentalizing and empathizing and discuss some implications for economics."
