Mandatory Financial Reporting Processes and Outcomes

In an extension to the mandatory financial reporting literature, we consider compliance and applicability as intermediate stages in the disclosure decision process, and investigate to what extent these measures explain any variance in the quantity of disclosure. We use financial instruments disclosures as our empirical context because of the level of complexity and diversity of the mandatory requirements. We find that neither applicability nor compliance show statistically significant association with disclosure quantity. By contrast we find that a firm's financial instruments management programme is an important determinant of both applicability and quantity. Finally, we demonstrate the economic consequences of applicability, compliance and quantity through their association with audit fees. For companies that use financial instruments management programmes to a greater extent, audit fees are higher. In contrast, the quantity of financial instruments disclosures appears to reduce audit fees.     

WHAT DRIVES CAPITAL FLOWS TO EMERGING MARKETS? A SURVEY OF THE EMPIRICAL LITERATURE

This paper reviews the rapidly growing empirical literature on the drivers of capital flows to emerging markets. The empirical evidence is structured based on the recognition that the drivers of capital flows vary over time and across different types of capital flows. The drivers are classified using the traditional distinction between ‘push’ and ‘pull’ drivers, which continues to serve as a useful framework. Push factors like global risk aversion and external interest rates are found to matter most for portfolio debt and equity flows, but somewhat less for banking flows. Pull factors such as domestic output growth, asset returns and country risk matter for all three capital flows components, but most for banking flows.     

Grid Load Contributions Through Electric Vehicles and Their Uncertainties

With the numbers of electric vehicles on the increase, their additional electricity demand can no longer be neglected. From a power systems’ perspective, it is the time dependent electricity consumption that matters. In particular, the peak demand is increased in the case of uncontrolled charging, imposing additional stress on the system. Unfortunately, since there is an absence of representative electric vehicle driving patterns, a quantification of such temporal charging requirements is challenging. To overcome this problem, we developed a detailed model, which maps combustion engine vehicles onto electric vehicle equivalents. The model’s main strengths are the consideration of the diversity within the vehicle fleet as well as the differentiation into the boundary cases of pure battery electric vehicles and plug-in hybrid electric vehicles. Applied to a German traffic study, load curves for these two cases were generated. In addition, the existing uncertainty in between was quantified using Monte Carlo method. We show that the peak energy demand through electric vehicles is much greater on working days than on weekend days. Moreover, we find that the distinction between pure and plug-in-hybrid electric vehicles matters, at least for the time being. Apart from the numerical results, the model is well suited to generate input for more sophisticated investigations of charging strategies within energy system simulations.     

The empirics of granular origins: some challenges and solutions with an application to the UK

Journal of Productivity Analysis - We study the effects of firm-level microeconomic fluctuations on aggregate productivity in the United Kingdom. We show that a standard measure of residual...