This paper analyses how firm-specific forecast errors derived from survey data of German manufacturing firms over 2007–2011 affect firms’ investment propensity. Understanding how forecast errors affect firm investment behaviour is key to mitigate economic downturns during and after crisis periods in which forecast errors tend to increase. Our findings reveal a negative impact of absolute forecast errors on investment. Strikingly, asymmetries arise depending on the size and direction of the forecast error. The investment propensity declines if the realised situation is worse than expected. However, firms do not adjust investment if the realised situation is better than expected suggesting that the uncertainty component of the forecast error counteracts positive effects of unexpectedly favorable business conditions. Given that the fraction of firms making positive forecast errors is higher after the peak of the recent financial crisis, this mechanism can be one explanation behind staggered economic growth and slow recovery following crises.

Refugee integration requires broad support from the host society, but only a minority of the host population is actively engaged. Given that most individuals reciprocate kind behaviour, we examine the idea that the proportion of supporters will increase as a reciprocal response to refugees’ contributions to society through volunteering. Our nationwide survey experiment shows that citizens’ intentions to contribute time and money rise significantly when they learn about refugees’ pro-social activities. Importantly, this result holds for individuals who have not been in contact with refugees. We complement this investigation with experiments in the lab and the field that confirm our findings for actual behaviour.

This paper illustrates how audio-visual data from pre-play face-to-face communication can be used to identify groups which contain free-riders in a public goods experiment. It focuses on two channels over which face-to-face communication influences contributions to a public good. Firstly, the contents of the face-to-face communication are investigated by categorising specific strategic information and using simple meta-data. Secondly, a machine-learning approach to analyse facial expressions of the subjects during their communications is implemented. These approaches constitute the first of their kind, analysing content and facial expressions in face-to-face communication aiming to predict the behaviour of the subjects in a public goods game. The analysis shows that verbally mentioning to fully contribute to the public good until the very end and communicating through facial clues reduce the commonly observed end-game behaviour. The length of the face-to-face communication quantified in number of words is further a good measure to predict cooperation behaviour towards the end of the game. The obtained findings provide first insights how a priori available information can be utilised to predict free-riding behaviour in public goods games.

In this paper, we document the forecasting performance of estimated basic dynamic stochastic general equilibrium (DSGE) models and compare this to extended versions which consider alternative expectation formation assumptions and financial frictions. We also show how standard model features, such as price and wage rigidities, contribute to forecasting performance. It turns out that neither alternative expectation formation behaviour nor financial frictions can systematically increase the forecasting performance of basic DSGE models. Financial frictions improve forecasts only during periods of financial crises. However, traditional price and wage rigidities systematically help to increase the forecasting performance.

In this paper, we document the forecasting performance of estimated basic dynamic stochastic general equilibrium (DSGE) models and compare this to extended versions which consider alternative expectation formation assumptions and financial frictions. We also show how standard model features, such as price and wage rigidities, contribute to forecasting performance. It turns out that neither alternative expectation formation behaviour nor financial frictions can systematically increase the forecasting performance of basic DSGE models. Financial frictions improve forecasts only during periods of financial crises. However, traditional price and wage rigidities systematically help to increase the forecasting performance.

In a public good experiment, the paper analyses to which extent individuals with economic education behave differently in a second-order dilemma. Second-order dilemmas may arise, when individuals endogenously build up costly institutions that help to overcome a public good problem (first-order dilemma). The specific institution used in the experiment is a communication platform allowing for group communication before the first-order public good game takes place. The experimental results confirm the finding of the literature that economists tend to free ride more intensively in public good games than non-economists. The difference is the strongest in the end-game phase, yielding in the conclusion that the magnitude of the end-game effect depends on the share of economists in the pool of participants. When it comes to the building-up of institutions, the individual efficiency gain of the institution and its inherent cost function constitute the driving forces for the contribution behaviour. Providing an investment friendly environment yields in economists contributing more to the institution than non-economists. Therefore, we make clear that first-order results of a simple public good game cannot be simply applied for second-order incentive problems.

Any organisation that needs to restructure, cut wages, or make layoffs needs to know how the employees who are not affected will respond. This column presents a field experiment which revealed that the perception that employers are unfair – in this case, as a result of layoffs – reduces the performance of employees who have not been not directly affected. As part of the experiment, experienced HR managers were able to successfully anticipate the consequences of unfair employer behaviour on unaffected workers.

Recent empirical research generally finds evidence of positive economic effects of works councils, for example with regard to productivity and – with some limitations – to profits. This makes it necessary to explain why employers’ associations have reservations against works councils. On the basis of an in-depth literature analysis, we show that beyond the generally positive findings, there are important heterogeneities in the impact of works councils. We argue that those groups of employers that tend to benefit little from employee participation in terms of productivity and profits may well be important enough to shape the agenda of their employers’ organisation and even gained in importance within their organisations in recent years. We also discuss the role of deviations from profit-maximising behaviour like risk aversion, short-term profit maximisation, and other non-pecuniary motives, as possible reasons for employer resistance.

We develop a model that reproduces the return and volatility spread between sin and non-sin stocks, where investors trade off dividends with the ethical assessment of companies. We relax the assumption of boycott behaviour and investigate the role played by the dividend share of sin stocks on their return and volatility spread relative to non-sin stocks. We empirically show that the dividend share predicts a positive return and volatility spread. This pattern is reproduced by our model when dividends and ethicalness are complementary goods and investors are sufficiently risk averse.

Starting from well-known empirical stylized facts of financial time series, we develop dynamic portfolio protection trading strategies based on econometric methods. As a criterion for riskiness, we consider the evolution of the value-at-risk spread from a GARCH model with normal innovations relative to a GARCH model with generalized innovations. These generalized innovations may for example follow a Student t, a generalized hyperbolic, an alpha-stable or a Generalized Pareto distribution (GPD). Our results indicate that the GPD distribution provides the strongest signals for avoiding tail risks. This is not surprising as the GPD distribution arises as a limit of tail behaviour in extreme value theory and therefore is especially suited to deal with tail risks. Out-of-sample backtests on 11 years of DAX futures data, indicate that the dynamic tail-risk protection strategy effectively reduces the tail risk while outperforming traditional portfolio protection strategies. The results are further validated by calculating the statistical significance of the results obtained using bootstrap methods. A number of robustness tests including application to other assets further underline the effectiveness of the strategy. Finally, by empirically testing for second-order stochastic dominance, we find that risk averse investors would be willing to pay a positive premium to move from a static buy-and-hold investment in the DAX future to the tail-risk protection strategy.