The technological and institutional environment influences the way of doing research and the relationships between its participants. Intellectual property is a strategic issue to build the institutional framework of the new technological regime and therefore the dynamics of innovation in...

In this work we consider modeling the past volatilities through a Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model using the Bayesian approach. Asymmetries in the shocks are accommodated by smooth transition models for the variance. We discuss problems related to the...

In this paper, we develop and apply Bayesian inference for an extended Nelson-Siegel (1987) term structure model capturing interest rate risk. The so-called Stochastic Volatility Nelson-Siegel (SVNS) model allows for stochastic volatility in the underlying yield factors. We propose a Markov...

The globalisation on financial markets and the development of financial derivatives has increased not only chances but also potential risk within the banking industry. Especially market risk has gained major significance since market price variation of interest rates, stocks or exchange rates...

This paper introduces a new method for deriving covariance matrix estimators that are decision-theoretically optimal. The key is to employ large-dimensional asymptotics: the matrix dimension and the sample size go to infinity together, with their ratio converging to a finite, nonzero limit. As...

We use data on sequential water auctions to estimate demand when units are complements or substitutes. A sequential English auction model determines the estimating structural equations. When units are complements, one bidder wins all units by paying a high price for the first unit, thus...

In this paper we examine the asymptotic properties of the estimator of the long-run coefficient (LRC) in a dynamic regression model with integrated regressors and serially correlated errors. We show that the OLS estimators of the regression coefficients are inconsistent but the OLS-based...

We propose an iterative procedure to efficiently estimate models with complex log-likelihood functions and the number of parameters relative to the observations being potentially high. Given consistent but inefficient estimates of sub-vectors of the parameter vector, the procedure yields...

Operationalizing the capability approach (CA) is difficult due to the conceptual challenges it poses: its multidimensionality and the role it assigns to freedom of choice for human wellbeing. Therefore the operationalizability of the CA has been questioned. Despite this, a lot of empirical...

This paper uses the method developed by Bollerslev and Todorov (2011b) to estimate risk premia for extreme events for the US and the German stock markets. The method extracts jump tail measures from high-frequency futures price data and from options data. In a second step, jump tail...