Electoral cycles in MPs’ salaries: evidence from the German states

Members of parliament (MPs) often set their own salaries. Voters dislike self-serving politicians, and politicians are keen to please voters. In line with political business cycle theories, politicians thus may delay giving themselves a salary increase until after elections. We investigate electoral cycles in the salary increases of German state MPs. Using data for 15 states over the period 1980–2014, we find no evidence that increases in MP salaries are influenced by election cycles. Politicians can increase their salaries at any point during the legislative period without negative consequences. We posit that this may be because even those voters who are most disenchanted with politics likely understand that all politicians benefit from a salary increase and thus do not punish the governing party at the polls.     

Student Access to Apprenticeships: Evidence from a Vignette Experiment

We identify the causal effects of student characteristics on the likelihood of being hired for an apprenticeship and explore the mechanisms underlying the employer’s decision. To this end, we perform a vignette experiment among human resources professionals in Belgium, focusing on less-qualified youth. Our results indicate that students with favorable educational records and students revealing being motivated are more likely to obtain an apprenticeship. Furthermore, we find that these characteristics are used by human resources professionals as signals of trainability, employability, and quit intentions.     

INFORMATION AND PRICE DISPERSION: THEORY AND EVIDENCE

Limited information is the key element generating price dispersion in models of homogeneous-goods markets. We show that the global relationship between information and price dispersion is an inverse-U shape. We test this mechanism for the retail gasoline market using a new measure of information based on commuter data from Austria. Commuters sample gasoline prices on their commuting route, providing us with spatial variation in the share of informed consumers. Our empirical estimates are in line with the theoretical predictions. We also quantify how information affects average prices paid and the distribution of surplus in the gasoline market.     

Extreme Uncertainty and Forward‐looking Disclosure Properties

This study investigates the effect of extreme uncertainty on disclosure behaviour by analyzing the quality and quantity of forward‐looking disclosures during the global financial crisis and pre‐crisis periods, controlling for other determinants of disclosure behaviour. Prior research has struggled to distinguish between the quality and quantity dimensions of forward‐looking disclosures. Also, the impact of the recent financial crisis on these forward‐looking disclosure attributes has not yet been examined systematically. We address this gap by exploiting the unique setting of German publicly traded firms. These firms must provide forward‐looking information within their audited financial statements, although relevant regulation is sufficiently vague to allow great variation in the quality, scope and quantity of forward‐looking disclosures actually observed. Using hand‐collected data from 2005 to 2009, we provide evidence of a significantly negative association between crisis and disclosure quality. This finding is robust to several different disclosure quality proxies and regression specifications. In contrast, we find no negative significant relation between crisis and disclosure quantity; rather, there is evidence that reported volume increases during the crisis. Our results are consistent with extreme uncertainty, as occurring during times of crisis, negatively affecting the quality of voluntary disclosures, while firms maintain or increase disclosure quantity, ultimately diluting the information density of forward‐looking disclosures.     

Stochastic covariance and dimension reduction in the pricing of basket options

This paper presents a tailor-made method for dimension reduction aimed at approximating the price of basket options in the context of stochastic volatility and stochastic correlation. The methodology is built on a modification to the Principal Component Stochastic Volatility (PCSV) model, a stochastic covariance model that accounts for most stylized facts in prices. The method to reduce dimension is first derived theoretically. Afterwards the results are applied to a multivariate lognormal context as a special case of the PCSV model. Finally empirical results for the application of the method to the general PCSV model are illustrated.     

The Optimal Timing of Open Market Stock Repurchases

Using a continuous-time real options approach we determine the conditions under which a value-maximizing company would conduct an open market stock repurchase to exploit the undervaluation of shares. We find the optimal timing of such repurchases as well as the optimal amount a company should repurchase and analyze how it depends on market parameters. Obtaining the announcement returns from the authorization of stock repurchases from our model allows us to derive testable empirical implications.     

The Refined Best Reply Correspondence and Backward Induction

Fixed points of the (most) refined best reply correspondence, introduced in Balkenborg et al. (2013), in the agent normal form of extensive form games with perfect recall have a remarkable property. They induce fixed points of the same correspondence in the agent normal form of every subgame. Furthermore, in a well‐defined sense, fixed points of this correspondence refine even trembling hand perfect equilibria, while, on the other hand, reasonable equilibria that are not weak perfect Bayesian equilibria are fixed points of this correspondence.     

Another Approach to Data Envelopment Analysis in Noisy Environments: DEA+

In this paper a DEA+ labeled approach for efficiency measurement in the stochastic case is presented along with a consistency proof and some preliminary evidence illustrating the small sample performance. DEA+ can basically handle multi-output technologies like standard DEA but allows to filter noise, that might have disturbed production and unlike a related approach does not require panel data. Consistency of DEA+ relies on the assumption of i.i.d. distributed and bounded noise and requires radial efficiency measurement. First Monte Carlo experiments show that a DEA+ based average inefficiency estimator performs well for samples of size n=100 in one-output, two-input settings compared to the corresponding Stochastic Frontier Estimator. Sensitivity of DEA+ performance with respect to parametrization of noise is weak, but higher noise contribution requires much larger sample size for satisfactory results.