Markov-Perfect Nash Equilibria in Models With a Single Capital Stock

Many economic problems can be formulated as dynamic games in which strategically interacting agents choose actions that determine the current and future levels of a single capital stock. We study necessary conditions that allow us to characterize Markov perfect Nash equalibria (MPNE) for these games. These conditions result in an auxilary system of ordinary differential equations that helps us to explore stability, continuity and differentiability of MPNE. The techniques are used to derive detailed properties of MPNE for several games including the exploitation of a finite resource, the voluntary investment in a public capital stock, and the inter-temporal consumption of a reproductive asset.

Markov-perfect Nash equilibria in models with a single capital stock (Revised version, August 2008)

Many economic problems can be formulated as dynamic games in which strategically interacting agents choose actions that determine the current and future levels of a single capital stock. We study necessary conditions that allow us to characterise Markov perfect Nash equilibria for these games. These conditions result in an auxiliary system of ordinary differential equations that helps us to explore stability, continuity and differentiability of these equilibria. The techniques are used to derive detailed properties of Markov-perfect Nash equilibria for several games including the exploitation of a finite resource, the voluntary investment in a public capital stock, and the inter-temporal consumption of a reproductive asset.

Sovereign bond risk premiums

Credit risk has become an important factor driving government bond returns. We therefore introduce an asset pricing model which exploits information contained in both forward interest rates and forward CDS spreads. Our empirical analysis covers euro-zone countries with German government bonds as credit risk-free assets. We construct a market factor from the first three principal components of the German forward curve as well as a common and a country-specific credit factor from the principal components of the forward CDS curves. We find that predictability of risk premiums of sovereign euro-zone bonds improves substantially if the market factor is augmented by a common and an orthogonal country-specific credit factor. While the common credit factor is significant for most countries in the sample, the country-specific factor is significant mainly for peripheral euro-zone countries. Finally, we find that during the current crisis period, market and credit risk premiums of government bonds are negative over long subintervals, a finding that we attribute to the presence of financial repression in euro-zone countries

A Dynamic Theory of Conjectural Variations

Series: Department of Economics Working Paper Serie

Cyclical Consumption Patterns and Rational Addiction

Series: Department of Economics Working Paper Serie

International Pollution Control: Cooperative Versus Noncooperative Strategies

Series: Department of Economics Working Paper Serie

Asset Price Dynamics in a Model of Investors Operating on Different Time Horizons

We present a dynamic asset pricing model based on a heterogenous class of traders. These traders are homogenous in the sense that they are fundamentalists who base their investment decisions on an exogenoulsy given fundamental value. They are heterogenous in the sense that each trader is working with a different frequency of the underlying price data. As a result we have a system of interacting investors who together influence the market price. We derive a system that characterizes out-of-equilibrium dynamics of prices in this market which is structurally equivalent to the Nosé-Hoover thermostat equation in non-equilibrium thermodynamics. We explore the time series properties of these prices and find that they exhibit fat tails of returns distributions, volatility clustering and power laws.Series: Working Papers SFB "Adaptive Information Systems and Modelling in Economics and Management Science

Non-linear versus non-gaussian volatility models

One of the most challenging topics in financial time series analysis is the modeling of conditional variances of asset returns. Although conditional variances are not directly observable there are numerous approaches in the literature to overcome this problem and to predict volatilities on the basis of historical asset returns. The most prominent approach is the class of GARCH models where conditional variances are governed by a linear autoregressive process of past squared returns and variances. Recent research in this field, however, has focused on modeling asymmetries of conditional variances by means of non-linear models. While there is evidence that such an approach improves the fit to empirical asset returns, most non-linear specifications assume conditional normal distributions and ignore the importance of alternative models. Concentrating on the distributional assumptions is, however, essential since asset returns are characterized by excess kurtosis and hence fat tails that cannot be explained by models with suffcient heteroskedasticity. In this paper we take up the issue of returns' distributions and contrast it with the specification of non-linear GARCH models. We use daily returns for the Dow Jones Industrial Average over a large period of time and evaluate the predictive power of different linear and non-linear volatility specifications under alternative distributional assumptions. Our empirical analysis suggests that while non-linearities do play a role in explaining the dynamics of conditional variances, the predictive power of the models does also depend on the distributional assumptions. (author's abstract)Series: Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science