Contributions in Merlin

We examine whether firms increase their employment of R&D personnel in response to an expansion of tertiary education institutions, i.e., a supply shock of skilled labor. We use the staggered introduction of Universities of Applied Sciences (UASs) in Switzerland as a quasi-natural experiment to identify causal effects. Firms located near a new UAS campus experience an education-driven labor supply shock in the form of UAS graduates newly entering the local labor market. Using a large representative firm survey and applying a difference-in-differences model, we find that this labor supply shock has positive effects: first, on the percentage of R&D personnel relative to total employment and, second, on the percentage of total wages paid to them. These effects are driven by both very small firms (five to nine employees) and very large ones (5,000 or more). Our findings suggest that a tertiary education expansion can stimulate innovation activities by increasing the personnel resources devoted to R&D.

The paper analyzes the relationship between bank competition and stability, with a specific focus on the Middle East and North Africa. Price competition has a positive effect on bank liquidity, as it induces self-discipline incentives on banks for the choice of bank funding sources and for the holding of liquid assets. On the other hand, price competition may have a potentially negative impact on bank solvency and on the credit quality of the loan portfolio. More competitive banks may be less solvent if the potential increase in the equity base—due to capital adjustments—is not large enough to compensate for the reduction in bank profitability. Also, banks subject to stronger competitive pressures may have a higher rate of nonperforming loans, if the increase in the risk-taking incentives from the lender’s side overcomes the decrease in the credit risk from the borrower’s side. In both cases, country-specific policies for market entry conditions—and for bank regulation and supervision—may significantly affect the sign and the size of the relationship. The paper suggests policy reforms designed to improve market contestability and to increase the quality and independence of prudential supervision.

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We develop a method to analyze the effects on financial stability of the interplay between climate policy shocks and market conditions. We combine the frameworks of the Climate Stress-test with the framework of the network valuation of financial assets, in which the valuation of interbank claims accounts for market volatility as well as for endogenous recovery rates consistent with the network of obligations. We also include the dynamics of common asset contagion involving not only banks but also investment funds, which are key players in the low carbon transition. We then apply the model to a unique supervisory data-set of banks and investment funds at the firm level in order to assess the impact for financial stability of shocks deriving from the disorderly alignment of energy and utility sectors in a range of climate policy scenarios. While under mild shock scenarios systemic losses are contained, we identify the climate policy scenarios and market conditions under which systemic losses can pose a threat to financial stability.

Germany is in the midst of a radical transformation of its power sector, which in 2016 led two of its main electric utilities, EON and RWE, to undertake dramatic restructurings. EON spun off its fossil fuel and trading segments, while RWE carved out its renewable energy, retail and grid business. The paper examines the drivers of these divestitures. Building on corporate finance literature, the paper uses a mix of comparative descriptive statistics, interviews and event studies to test four groups of hypotheses. The evidence rejects drivers related to operations and management, biased investment and investor preferences and instead points to financing-related drivers. Among the financing-related drivers, debt overhang and risk contamination seemed to have played the main role. Utilities restructured to save their healthy assets (renewables and grid infrastructure) from losses at their conventional power generation business (fossil fuel and nuclear plants). Already weakened from record losses in their fossil fuel powered generation fleet due to low electricity prices, after 2011 the nuclear exit emerged as an additional challenge to the utilities. Investors doubted the adequacy of utilities provisions for decommissioning nuclear power plants and storing toxic waste, and feared major cost increases for which the utilities would be unlimitedly liable. The paper uses existing research on divestitures in an empirical case that has implications for the evolution of European power markets. The results suggest that exiting conventional technologies as part of the transition to a more renewable energy mix might cause substantial costs. If these are not clarified and allocated ex ante, policy makers might find themselves forced to either burden tax payers or endanger utilities that are of systemic relevance to the energy sector.

We propose a novel intraday instantaneous volatility measure which utilises sequences of drawdowns and drawups non-equidistantly spaced in physical time as indicators of high-frequency activity of financial markets. The sequences are re-expressed in terms of directional-change intrinsic time which ticks only when the price curve changes the direction of its trend by a given relative value. We employ the proposed measure to uncover market microstructure weekly volatility seasonality patterns of three Forex and one Bitcoin exchange rates as well as a stock market index. We demonstrate the long memory of instantaneous volatility computed in directional-change intrinsic time. The provided volatility estimation method can be adapted as a universal multiscale risk-management tool independent of the discreteness and the type of analysed large high-frequency data.

This paper explores the performance of mixed-frequency predictive regressions for stock returns from the perspective of a Bayesian investor. We develop a parameter learning approach for sequential estimation, allowing for belief revisions. Empirically, we find that mixed-frequency models improve predictability, not only because of the combination of predictors with different frequencies but also due to the preservation of the time-variation in the volatility of predictors. Mixed-frequency models produce higher volatility timing benefits, compared to temporally aggregate models. Therefore, our results highlight the importance of consistently incorporating predictors of mixed frequencies and correctly specifying the volatility dynamics in predictive regressions.

Are options on exchange-traded products (ETPs) and indexes consistently priced internationally? The cross-section of international option returns exhibits a mispricing by sorting on ex-ante volatility returns. In addition, selling international ETP options and buying their corresponding index options commands a positive risk premium. Both empirical findings are economically large and pervasive internationally, whereas they are comparably small domestically. While volatility hedge funds are exposed towards domestic option products, they neglect the possibility of engaging in foreign volatility arbitrage. These findings entail that alpha seekers may expand their horizon towards international derivatives which at first glance are similar, but institutionally are not.

Identifying economic regimes is useful in a world of time-varying risk premia. We apply regime switching models to common factors proxying for the macroeconomic regime and show that the ensuing regime factor is relevant in forecasting the equity risk premium. Moreover, the relevance of this regime factor is preserved in the presence of fundamental variables and technical indicators which are known to predict equity risk premia. Based on multiple predictive regressions and pooled forecasts, the macroeconomic regime factor is deemed complementary relative to the fundamental and technical information sets. Finally, these forecasts exhibit significant out-of-sample predictability that ultimately translates into considerable utility gains in a mean-variance portfolio strategy.

Non-convexities and discrete choices have become important modeling tools in modern macro-economics. Unfortunately, existence of competitive equilibria in the presence of such non-convexities is not always ensured and most results on the existence of equilibrium that can be found in the literature consider a very general model and are not directly applicable to the macro-models used in the literature. In this paper we explain the three main problems one needs to face when proving existence and give simple sufficient conditions for the existence of competitive equilibria in stochastic OLG models with discrete choices and non-convex preferences. We also consider a version of the model without aggregate uncertainty but with bankruptcy and default and prove existenceof a steady state equilibrium.