Contributions in Merlin

By applying the inventory theory to hiring skilled workers under uncertainty, the authors explain how firms decide on their optimum investment in an "inventory of skills." This paper investigates the conditions under which firms are willing to make investments in a skilled workforce themselves rather than relying on skills produced within the education system or by other companies. By applying inventory theory to investments into apprenticeship training, the authors explain how firms decide on producing an optimum "inventory of skills" today to meet future demand. The authors derive hypotheses on how much firms are willing to invest in having a larger inventory of skilled worker depending on different types of inventory costs (overage cost, underage costs, demand structure). The authors use data from the BIBB Cost-Benefit-Survey 2012/2013, which comprises detailed information on different costs and benefits of training investments from the firm's perspective. The study applies a negative binomial estimation model. Results are threefold: firms are willing to invest in a larger inventory of skilled workers, i.e., to train more apprentices, first, if the costs of producing and retaining an excessive number of skilled workers (overage costs) are lower, second, if the costs of being short of skilled workers (underage costs) are higher, and third, given an identical cost structure, if it is more likely that the demand for skilled worker may be high in the future. Even more important is the relationship of the three: the combination of a firm's critical ratio (underage costs in relation to overage costs) with its demand structure (industry volatility) is associated with a higher inventory of skills. The findings (particularly the relation of underage and overage costs, in combination with the demand structure) have important policy implications for firms' incentives to invest in apprenticeship training.

Is the American put option in the Black-Scholes model simply an incognito European one? In this paper, we develop a numerical procedure, in the context of the Black-Scholes model, to approximate the payoff of a European type option that generates prices that are equal to the prices of the American put option in the continuation region. The resulting equivalent European payoff is a sum of power payoffs and therefore the price and the hedging indicators can be computed in closed form. For a given set of model parameters (interest rate, dividend rate and volatility) the computation of the equivalent European payoff reduces to solving a linear optimization problem. We conduct a numerical experiment spanning a wide range of model parameters and contract characteristics and, overall, the method produces American option prices with a relative RMSE less than 0.01% compared to a benchmark.

Under short sales prohibitions, no free lunch with vanishing risk (NFLVR-S) is known to be equivalent to the existence of an equivalent supermartingale measure for the price processes (Pulido, 2014). For two given price processes, we translate the property (NFLVR-S) in terms of so called structure conditions and we introduce the concept of fun- damental supermartingale measure. When a certain condition necessary to the construction of the fundamental martingale measure is not fulfilled, we provide the corresponding arbi- trage portfolios. The motivation of our study lies in understanding the particular case of converging prices, i.e., that are going to cross at a bounded random time.

In classical contagion models, default systems are Markovian conditionally on the observation of their stochastic environment, with interacting intensities. This necessitates that the environment evolves autonomously and is not influenced by the history of the default events. We extend the classical literature and allow a default system to have a contagious impact on its environment. In our framework, contagion can either be contained within the default system (i.e., direct contagion from a counterparty to another) or spill from the default system over its environment (indirect contagion). This type of model is of interest whenever one wants to capture within a model possible impacts of the defaults of a class of debtors on the more global economy and vice versa.

We build a general model for pricing defaultable claims. In addition to the usual absence of arbitrage assumption, we assume that one defaultable asset (at least) looses value when the default occurs. We prove that under this assumption, in some standard market filtrations, default times are totally inaccessible stopping times; we therefore proceed to a systematic construction of default times with particular emphasis on totally inaccessible stopping times. Surprisingly, this abstract mathematical construction, reveals a very specific and useful way in which default models can be built, using both market factors and idiosyncratic factors. We then provide all the relevant characteristics of a default time (i.e. the Az\'ema supermartingale and its Doob-Meyer decomposition) given the information about these factors. We also provide explicit formulas for the prices of defaultable claims and analyze the risk premiums that form in the market in anticipation of losses which occur at the default event. The usual reduced-form framework is extended in order to include possible economic shocks, in particular jumps of the recovery process at the default time. This formulas are not classic and we point out that the knowledge of the default compensator or the intensity process is not anymore a sufficient quantity for finding explicit prices, but we need indeed the Az\'ema supermartingale and its Doob-Meyer decomposition.

We assess the quantitative implications of the re-use of collateral on financial market leverage, volatility, and welfare within an infinite-horizon asset-pricing model with heterogeneous agents. In our model, the ability of agents to re-use frees up collateral that can be used to back more transactions. Re-use thus contributes to the build-up of leverage and significantly increases volatility in financial markets. When introducing limits on re-use, we find that volatility is strictly decreasing as these limits become tighter, yet the impact on welfare is non-monotone. In the model, allowing for some re-use can improve welfare as it enables agents to share risk more effectively. Allowing reuse beyond intermediate levels, however, can lead to excessive leverage and lower welfare. So the analysis in this paper provides a rationale for limiting, yet not banning, re-use in financial markets.

This paper provides a unique snapshot of the exposures of EU banks to shadow banking entities within the global financial system. Drawing on a rich and novel dataset, the paper documents the cross-sector and cross-border linkages and considers which are the most relevant for systemic risk monitoring. From a macroprudential perspective, the identification of potential feedback and contagion channels arising from the linkages of banks and shadow banking entities is particularly challenging when shadow banking entities are domiciled in different jurisdictions. The analysis shows that many of the EU banks’ exposures are towards non-EU entities, particularly US-domiciled shadow banking entities. At the individual level, banks’ exposures are diversified although this diversification leads to high overlap across different types of shadow banking entities.

This study focuses on how firms form and sequentially adapt their inter organizational knowledge sourcing structures within research and development (R&D) alliances and how this process impacts their innovation performance. In contrast to the previous literature that mainly ignores the dynamic aspects of how firms adapt their search strategies, our approach accounts for sequential adaptation. Our proposed framework explores the role of simultaneous diversification and sequential adaptation of collaboration partners within R&D alliances according to specific innovation outcomes. The results emphasize that firms should not remain within the same search activities indefinitely, as non-adapting interorganizational knowledge transfer structures lead to inferior performance. Notably, this study highlights important partner-type selectivity and identifies appropriate simultaneous diversification and sequential adaptation strategies in relation to specific innovation outcomes and firm sizes.