Contributions in Merlin

Most popular models for Conditional Higher Moments of stock return processes are imposing a specific assumption on their parametric structure. This paper studies the issue of predicting Conditional Higher Moments of stock return processes and the associated Probability Densities with only making an assumption on the appropriate filtration. A Parameter Free Approach to Predictions for that purpose is introduced, that relies on Nonparametric Probability Estimations and the concept of Maximum Likelihood. The Prediction Approach is tested with artificial data from standard models for Conditional Volatility and Conditional Skewness as well as for observed market data. It is able to understand the properties of those standard models and is able to follow them, in case of the GARCH model unfortunately only with a slight bias. In case of observed market data the Approach is able to recognize some of the stylized facts, which are observed with Conditional Volatility. Furthermore it confirms the proposed property, that Conditional Skewness is reversely correlated with the lagged return.

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We propose a new modeling framework to study the asset pricing implications of learning under ambiguity aversion. In a continuous time partial information Lucas economy, we characterize analytically equilibrium equity returns and make the following observations. First, learning under ambiguity aversion implies an equilibrium discount for ambiguity, if and only if relative risk aversion is below one or, equivalently, the elasticity of intertemporal substitution (EIS) is above one. In this case, ambiguity aversion increases conditional equity premia and volatilities. Second, equilibrium interest rates are lower, irrespective of risk aversion. Third, no time-invariant relation between excess returns and conditional variances exists. Therefore, estimated relations between excess returns and equity conditional variances are highly time varying and have an indeterminate sign. Fourth, estimates of the EIS based on standard Euler equations for equity returns are strongly downward biased in a setting of learning and ambiguity aversion. Therefore, an EIS well above one can be consistent with estimates of EIS well below one. Fifth, ambiguity does not resolve asymptotically. Finally, using realistic model parameters, we show that a low risk aversion and a moderate amount of ambiguity are consistent with the equity premium, the low interest rate, and the excess volatility puzzles.

The current downsizing literature has neglected the cognitions and behaviors of layoff agents. In this article, layoff agents are defined as employees who assist in the implementation of layoffs in their employing organizations. The article develops a theoretical framework that focuses on the cognitions and perceptions of those individuals. This framework suggests that layoff agents have the potential to experience cognitive dissonance as a result of their layoff agency activities, and under some conditions they will seek to reduce that dissonance by altering their perceptions of organizational downsizing. The framework specifies variables that moderate the relationship between layoff agency and cognitive dissonance and also variables that moderate the relationship between layoff agency—induced cognitive dissonance and agent perceptions of organizational downsizing. The moderating effects of these variables are captured in a set of propositions suitable for testing in future empirical research on the psychology of layoff agents.

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In this paper we show that the recent model by Gilles Duranton [Duranton, G., 2007. Urban evolutions: The fast, the slow, and the still. American Economic Review 97, 197–221] performs remarkably well in replicating the city size distribution of West Germany, much better than the simple rank-size rule known as Zipf's law. The main mechanism of this theoretical framework is the “churning” of industries across cities. Little is known in urban economics about the determinants of local industry turnover so far. We present an empirical analysis of the excess churning index for West German cities, which describes the strength of intra-city industry reallocations over time. We find that urban growth and industry turnover are not notably correlated: Some, but not all fast-growing cities have notably changed. Secondly, human capital is positively related to growth and turnover, but only among successful cities. Industrial change within unsuccessful cities is driven by the disappearance of old-fashioned and declining sectors such as agriculture or mining. On a more general level our results suggest that the recent model by Duranton is a powerful description of the urban growth process. Still there are some aspects that are not captured by that model, which are at the core of other theories of urban growth.