Ist der Fahrplan der Energiewende noch einzuhalten?

The German energy transition represents a policy-driven, sustainability-oriented restructuring of both supply- and demand-side components of the entire energy system by 2050. Whereas the development of renewable energies in the electricity sector is right on track, due to the feed-in tariffs of the German Renewable Energy Sources Act, many other crucial requirements for a successful transition are not, amongst others the improvement of energy effi ciency and the decarbonisation of the transport sector. Contrary to the public discussion, the primary future challenges do not consist in limiting electricity prices or abandoning feed-in support schemes, but rather in coordinating the variety of actors as well as appropriately matching the different system elements (grids, technologies, energy sectors, demand and supply side, etc.). Much remains to be done. By highlighting some examples like the need to take into account future implications of climate change for the energy sector, the consequences of the current crisis in the European Union’s emissions trading scheme and the need for a cautious adjustment of the EEG, the paper argues that the major challenges regarding the German energy transition mainly go beyond the current policy-driven and short-term discussion of energy prices. Germany’s pioneering attempt to integrate steadily increasing share of non-dispatchable electricity from renewable sources is challenging the stability of the system. Several characteristics in the current selfregulating system are identifi ed and analysed, which reveal themselves as potential weaknesses or shortcomings in the upcoming system.     

Dividend Stickiness,Debt Covenants,and Earnings Management

Consistent with the notion that dividends are very sticky, Daniel, Denis, and Naveen ( 2008 ) report evidence that firms manage earnings upward when pre‐managed earnings are expected to fall short of dividend payments. However, we find that this evidence is not robust when controlling for firms' tendency to manage earnings upward to avoid reporting earnings declines; only firms with high leverage exhibit a statistically weak tendency to manage earnings to close deficits of pre‐managed earnings relative to dividends. We further report that the decision to cut dividends depends on whether reported earnings fall short of past dividends, but not on earnings management that eliminates a shortfall in pre‐managed earnings relative to dividend payments. Overall, our evidence suggests that firms that face dividend constraints are more likely to cut dividends than to manage earnings to avoid dividend cuts.     

Did the Federal Crop Insurance Reform Act Alter Farm Enterprise Diversification?

We estimate how much United States farms changed enterprise diversification in response to a marked increase in crop insurance coverage brought about by the 1994 Federal Crop Insurance Reform Act, which substantially increased insurance subsidies. The analysis exploits farm‐level panel census data to compare farm‐specific changes in enterprise diversification over time. By examining diversification decisions of the same farms over time, we control for time‐invariant unobserved individual heterogeneity. We then use pooled cross‐sectional data from the United States Department of Agriculture (USDA) Agricultural Resource Management Survey to estimate the relationship between farm diversification and average returns. We find that the insurance subsidies caused a modest increase in enterprise specialisation and production efficiency. Estimated efficiency gains are far less than the subsidies.     

Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets

Using two newly available ultrahigh-frequency datasets, we investigate empirically how frequently one can sample certain foreign exchange and U.S. Treasury security returns without contaminating estimates of their integrated volatility with market microstructure noise. Using the standard realized volatility estimator, we find that one can sample dollar/euro returns as frequently as once every 15 to 20 s without contaminating estimates of integrated volatility; 10-year Treasury note returns may be sampled as frequently as once every 2 to 3 min on days without U.S. macroeconomic announcements, and as frequently as once every 40 s on announcement days. Using a simple realized kernel estimator, this sampling frequency can be increased to once every 2 to 5 s for dollar/euro returns and to about once every 30 to 40 s for T-note returns. These sampling frequencies, especially in the case of dollar/euro returns, are much higher than those that are generally recommended in the empirical literature on realized volatility in equity markets. The higher sampling frequencies for dollar/euro and T-note returns likely reflect the superior depth and liquidity of these markets.     

AMBITIONS AND OPPORTUNITIES FOR ASSESSING MILITARY PERFORMANCE IN CRISIS RESPONSE OPERATIONS

This paper addresses the issue of measuring armed forces’ performance in crisis response operations. By means of interviews (17 respondents) and a large scale survey (1,253 respondents) field and general officers of the Netherlands Armed Forces (NAF) have been questioned on perceived organisational success in crisis response operations. The Dutch officers assess the NAF's performance positively. A number of senior officers are hesitant about the usefulness of measuring the performance of crisis response operations. According to them the context in which the operations are being executed is too complex. Most interviewees, however, are convinced that measuring performance is useful and should be improved. These military leaders express a strong need for criteria to assess their performance on the job.     

On Conformity Testing and the Use of two Stage Procedures

Conformity testing is a systematic examination of the extent to which an entity conforms to specified requirements. Such testing is performed in industry as well as in regulatory agencies in a variety of fields. In this paper we discuss conformity testing under measurement or sampling uncertainty. Although the situation has many analogies to statistical testing of a hypothesis concerning the unknown value of the measurand there are no generally accepted rules for handling measurement uncertainty when testing for conformity. Usually the objective of a test for conformity is to provide assurance of conformity. We therefore suggest that an appropriate statistical test for conformity should be devised such that there is only a small probability of declaring conformity when in fact the entity does not conform. An operational way of formulating this principle is to require that whenever an entity has been declared to be conforming, it should not be possible to alter that declaration, even if the entity was investigated with better (more precise) measuring instruments, or measurement procedures. Some industries and agencies designate specification limits under consideration of the measurement uncertainty. This practice is not invariant under changes of measurement procedure. We therefore suggest that conformity testing should be based upon a comparison of a confidence interval for the value of the measurand with some limiting values that have been designated without regard to the measurement uncertainty. Such a procedure is in line with the recently established practice of reporting measurement uncertainty as “an interval of values that could reasonably be attributed to the measurand”. The price to be paid for a reliable assurance of conformity is a relatively large risk that the procedure will fail to establish conformity for entities that only marginally conform. We suggest a two‐stage procedure that may improve this situation and provide a better discriminatory ability. In an example we illustrate the determination of the power function of such a two‐stage procedure.     

The uncertainty challenge of contingent collaboration

Contingent knowledge workers will play an increasingly important role in organisational success as workers transition in and out of project‐based innovation teams with more frequency. Our research finds that collaborators in the contingent, high‐skill workforce face uncertainty challenges to their work that are unique from the independent, contingent professionals more often studied. The article proposes a theoretical framework of uncertainty to guide us in understanding collaborative contingent knowledge workers’ work experience. Interviews with postdoctoral researchers reveal four findings about the influence of these highly uncertain work environments on collaborative contingent knowledge workers – collaboration isolation, frustrated independence, performance anxiety and internalised blame. Perhaps most concerning is that the workers internalise the negative impacts as personal failings instead of recognising them as consequences of a poorly designed work environment. This study argues for the need to manage and mitigate different sources of uncertainty to avoid creating an unnecessary burden on contingent knowledge workers, and to enable a sustainable, contingent knowledge workforce.     

Trader Anonymity, Price Formation and Liquidity

Using data from the Frankfurt Stock Exchange we analyze price formationand liquidity in a non-anonymous environment with similarities to thefloor of the NYSE. Our main hypothesis is that the non-anonymity allows the specialist to assess the probability that atrader trades on the basis of private information. He uses this knowledgeto price discriminate. This can be achieved by quoting a large spread and granting price improvement to traders deemed uninformed.Consistent with our hypothesis we find that price improvement reflects loweradverse selection costs but does not lead to a reduction in the specialist's profit. Further, the quote adjustmentfollowing transactions at the quoted bid or ask price is more pronounced than the quote adjustment aftertransactions at prices inside the spread. Our results indicate that anonymity comes at the cost ofhigher adverse selection risk.     

Heuristic learning and the discovery of specialization and exchange

I develop and calibrate an agent-based model of boundedly rational, adaptive agents in a two-good production and exchange economy to replicate human-subject outcomes in the same eight-person experimental economy. To test agents’ ability to capture human behavior, I extend the model and use its output to make predictions about a second experimental environment in which the group of eight agents is slowly constructed by merging smaller groups. This environment improves human-subject performance in the specialization and exchange task, and commensurate improvement emerges for some parameterizations of the agent-based model. This iterative process yields incremental improvement of decision-level theories about economic discovery.