External validity of economic experiments on Agri-environmental scheme design

The use of laboratory experiments to study issues in agricultural policy has grown in prominence within the fields of agricultural and environmental economics. Such experiments are often conducted with university students and framed in an abstract manner. This raises questions about whether the findings of these experiments provide reliable insights on the behaviour of actual agents in real settings. We contribute to this methodological debate by analysing the impacts of sample population and framing on behaviour in the experiment and on two policy effects: the direction and the magnitude of the policy impact. We also examine the channels through which differences in results may occur. For this, we test if behaviour is correlated with a set of covariates collected from our samples, including socio-demographics, social and risk preferences. Our main finding is that the type of subject significantly affects the magnitude of the policy impact. The two populations differ substantially in the representation of key characteristics and preferences, which in consequence affects behaviour in the experiment. We find no significant impact of framing on behaviour.     

Restatement costs and reporting bias

Financial restatements are costly, but frequent, events and many firms restate several times. We explore why rational managers engage in misreporting despite the costly consequences. To guide our analysis, we build a parsimonious model of reporting bias and the cost of restating. In our model, the observed cost of a restatement conveys information about the true cost of biasing financial statements, which the manager incorporates into the optimal choice of bias. A restatement hence offers managers an opportunity to learn about the true cost of reporting bias, which allows them to update their biasing strategy if the observed cost differs from the expected. We test the model's predictions by analyzing how firms' accruals quality changes after observing the costs attached to restating, which we measure as the market loss following a restatement scaled by the restatement's net income effect. We find that future accruals quality is increasing in the cost of restating and the change in the cost of restating. Consistent with our stylized model, our results indicate that rational managers use the insights from prior restatements to improve their future bias strategy.     

Nonparametric estimation for i.i.d. paths of a martingale-driven model with application to non-autonomous financial models

Finance and Stochastics - This paper deals with a projection least squares estimator of the function $J_{0}$ computed from multiple independent observations on $[0,T]$ of the process $Z$ defined by...     

Pro-cyclicality beyond business cycle

We show that pro-cyclicality is inherent in risk measure estimates based on historical data. Taking the example of VaR, we show that the empirical VaR measure is mean-reverting over a 1-year horizon when the portfolio is held fixed. It means that a capital requirement rule based on historical measurements of VaR tends in calm times to understate future required capital and tends in volatile times to overstate it. To quantify this pro-cyclicality, we develop a simple and efficient methodology, which we apply to major equity market indices. We make the interesting point that the pro-cyclicality property holds true even in a world with constant volatility, though the empirical magnitude of the mean-reversion is greater than what would be observed in that special case.