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Correctness of program transformations and translations in concurrent programming is the focus of our research. In this case study the relation of the synchronous pi-calculus and a core language of Concurrent Haskell (CH) with asynchronous communication is investigated. We show that CH embraces the synchronous pi-calculus. The formal foundations are contextual semantics in both languages, where may- as well as should-convergence are observed. We succeed in defining and proving smart properties of a particular translation mapping the synchronous pi-calculus into CH. This implies that pi-processes are error-free if and only if their translation is an error-free CH-program Our result shows that the chosen semantics is not only powerful, but can also be applied in concrete and technically complex situations. The developed translation uses private names. We also automatically check potentially correct translations that use global names instead of private names. As a complexity parameter we use the number of MVars introduced by the transformation, where MVars are synchronized 1-place buffers. The automated refutation of incorrect translations leads to a classification of potentially correct translations, and to the conjecture that one global MVar is insufficient.
We investigate translations from the synchronous pi-calculus
into a core language of Concurrent Haskell (CH). Synchronous messagepassing of the pi-calculus is encoded as sending messages and adding synchronization using Concurrent Haskell’s mutable shared-memory locations (MVars). Our correctness criterion for translations is invariance of may- and should-convergence. This embraces that all executions of a process are error-free if and only if this also holds for the translated program. We exhibit a particular correct translation that uses a fresh, private MVar per communication interaction and that is in addition adequate, and which is also fully abstract on closed expressions. A metaresult is that CH has the expressive power and the concurrency capabilities of the synchronous pi-calculus.
We also automatically check variants of translations of synchronous communication into an asynchronous calculus where only an a priori fixed number of MVars per channel (and not per communication interaction!) is available. We obtain non-correctness results for classes of small translations, and exemplary argue for the correctness (and adequacy) for two translations with a higher number of MVars. We introduce a classification of the potentially correct translations.
We consider matching, rewriting, critical pairs and the Knuth-Bendix confluence test on rewrite rules in a nominal setting extended by atom-variables. Computing critical pairs is done using nominal unification, and rewriting using nominal matching. We utilise atom-variables to formulate rewrite rules, which is an improvement over previous approaches, using usual nominal unification, nominal matching and nominal equivalence of expressions coupled with a freshness constraint. We determine the complexity of several problems in a quantified freshness logic. In particular we show that nominal matching is Πp2-complete. We prove that the adapted Knuth-Bendix confluence test is applicable to a nominal rewrite system with atom-variabes and thus, that there is a decidable test whether confluence of the ground instance of the abstract rewrite system holds. We apply the nominal Knuth Bendix confluence criterion to the theory of monads, and compute a convergent nominal rewrite system modulo alpha-equivalence.
A sound and complete algorithm for nominal unification of higher-order expressions with a recursive let is described, and shown to run in non-deterministic polynomial time. We also explore specializations like nominal letrec-matching for expressions, for DAGs, and for garbage-free expressions and determine their complexity. As extension a nominal unification algorithm for higher-order expressions with recursive let and atom-variables is constructed, where we show that it also runs in non-deterministic polynomial time.
As part of the Next Generation EU (NGEU) program, the European Commission has pledged to issue up to EUR 250 billion of the NGEU bonds as green bonds, in order to confirm their commitment to sustainable finance and to support the transition towards a greener Europe. Thereby, the EU is not only entering the green bond market, but also set to become one of the biggest green bond issuers. Consequently, financial market participants are eager to know what to expect from the EU as a new green bond issuer and whether a negative green bond premium, a so-called Greenium, can be expected for the NGEU green bonds. This research paper formulates an expectation in regards to a potential Greenium for the NGEU green bonds, by conducting an interview with 15 sustainable finance experts and analyzing the public green bond market from September 2014 until June 2021, with respect to a potential green bond premium and its underlying drivers. The regression results confirm the existence of a significant Greenium (-0.7 bps) in the public green bond market and that the Greenium increases for supranational issuers with AAA rating, such as the EU. Moreover, the green bond premium is influenced by issuer sector and credit rating, but issue size and modified duration have no significant effect. Overall, the evaluated expert interviews and regression analysis lead to an expected Greenium for the NGEU green bonds of up to -4 bps, with the potential to further increase in the secondary market.
Target date funds in corporate retirement plans grew from $5B in 2000 to $734B in 2018, partly because federal regulation sanctioned these as default investments in automatic enrollment plans. We show that adopters delegated pension investment decisions to fund managers selected by plan sponsors. Including these funds in retirement saving menus raised equity shares, boosted bond exposures, curtailed cash/company stock holdings, and reduced idiosyncratic risk. The adoption of low-cost target date funds may enhance retirement wealth by as much as 50 percent over a 30-year horizon.
A series of recent articles has called into question the validity of VAR models of the global market for crude oil. These studies seek to replace existing oil market models by structural VAR models of their own based on different data, different identifying assumptions, and a different econometric approach. Their main aim has been to revise the consensus in the literature that oil demand shocks are a more important determinant of oil price fluctuations than oil supply shocks. Substantial progress has been made in recent years in sorting out the pros and cons of the underlying econometric methodologies and data in this debate, and in separating claims that are supported by empirical evidence from claims that are not. The purpose of this paper is to take stock of the VAR literature on global oil markets and to synthesize what we have learned. Combining this evidence with new data and analysis, I make the case that the concerns regarding the existing VAR oil market literature have been overstated and that the results from these models are quite robust to changes in the model specification.
This paper sets up an experimental asset market in the laboratory to investigate the effects of ambiguity on price formation and trading behavior in financial markets. The obtained trading data is used to analyze the effect of ambiguity on various market outcomes (the price level, volatility, trading activity, market liquidity, and the degree of speculative trading) and to test the quality of popular empirical market-based measures for the degree of ambiguity. We find that ambiguity decreases market prices and trading activity; ambiguity leads to lower market liquidity through wider bid-ask spreads; and ambiguity leads to less speculative trading. We also find that popular market-based measures of ambiguity used in the empirical literature do not seem to correctly capture the true degree of ambiguity.
Several recent studies have expressed concern that the Haar prior typically imposed in estimating sign-identi.ed VAR models may be unintentionally informative about the implied prior for the structural impulse responses. This question is indeed important, but we show that the tools that have been used in the literature to illustrate this potential problem are invalid. Speci.cally, we show that it does not make sense from a Bayesian point of view to characterize the impulse response prior based on the distribution of the impulse responses conditional on the maximum likelihood estimator of the reduced-form parameters, since the the prior does not, in general, depend on the data. We illustrate that this approach tends to produce highly misleading estimates of the impulse response priors. We formally derive the correct impulse response prior distribution and show that there is no evidence that typical sign-identi.ed VAR models estimated using conventional priors tend to imply unintentionally informative priors for the impulse response vector or that the corre- sponding posterior is dominated by the prior. Our evidence suggests that concerns about the Haar prior for the rotation matrix have been greatly overstated and that alternative estimation methods are not required in typical applications. Finally, we demonstrate that the alternative Bayesian approach to estimating sign-identi.ed VAR models proposed by Baumeister and Hamilton (2015) su¤ers from exactly the same conceptual shortcoming as the conventional approach. We illustrate that this alternative approach may imply highly economically implausible impulse response priors.
Since the 1970s, exports and imports of manufactured goods have been the engine of international trade and much of that trade relies on container shipping. This paper introduces a new monthly index of the volume of container trade to and from North America. Incorporating this index into a structural macroeconomic VAR model facilitates the identification of shocks to domestic U.S. demand as well as foreign demand for U.S. manufactured goods. We show that, unlike in the Great Recession, the primary determinant of the U.S. economic contraction in early 2020 was a sharp drop in domestic demand. Although detrended data for personal consumption expenditures and manufacturing output suggest that the U.S. economy has recovered to near 90% of pre-pandemic levels as of March 2021, our structural VAR model shows that the component of manufacturing output driven by domestic demand had only recovered to 59% of pre-pandemic levels and that of real personal consumption only to 76%. The difference is mainly accounted for by unexpected reductions in frictions in the container shipping market.