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On the empirical estimator of the boundary in inverse first-exit problems
Full text linkFirst-exit problems for the Brownian motion (W(t)) or general diffusion processes, have important applications. Given a boundary b(t), the distribution of the first-exit time τ has to be computed, in most cases numerically. In the inverse first-passage-time problems, the distribution of τ is given and the boundary b has to be found. The boundary and the density of τ satisfy a Volterra integral equation. Again numerical methods approximate the solution b for given distribution of τ. We propose and analyze estimators of b for a given sample τ1,…,τn of first-exit times. The first estimator, the empirical estimator, is the solution of a stochastic version of the Volterra equation. We prove that it is strongly consistent and we derive an upper bound for its asymptotics convergence rate. Finally, this estimator is compared to a Bayesian estimator, which is based on an approximate likelihood function. Monte Carlo experiments suggests that the empirical estimator is simple, computationally manageable and outperforms the alternative procedure considered in this paper
Financialisation of Nature
Full text linkThe ‘financialisation of nature’ is related to a shift in environmental governance—from regulation to
marked-based approaches—involving strong state support to facilitate the establishment of
‘innovative financial instruments’ and markets related to nature. Although innovative finance got a
bad reputation after the 2008 financial crisis, they are strongly encouraged in the environmental
policy domain and supported by actors such as UNEP or the CBD. This paper explains the
theoretical underpinning and the process of establishing such financial instruments, focusing in
particular on offsetting and related ideas such as ‘net-zero’ calculations and ‘nature-based
solutions’. It explains how natural entities are converted into abstract units of equivalence to allow
the establishment of schemes for tradable ‘nature credits’ (supposedly) compensating damage
across time and space. The financialisation of nature is then analysed and critiqued with respect to
its lack of environmental effectiveness, its problematic socio-economic consequences and its
impact on human-nature relationships. Instead of dealing with the environmental problems at hand,
the conversion of nature into financial assets simply turns nature into objects of investment and
speculation, while simultaneously creating a potential for financial bubbles.Series: SRE - Discussion Paper
JEFE-Vi III: Contribuciones a las terceras Jornadas de Español para Fines Específicos de Viena
Full text linkExploring the long-term effect of strategy work: The case of Sustainable Sydney 2030
Full text linkStrategy has become an important concern and practical tool in urban management and governance, with the literature highlighting implementation as a hallmark of effective strategy. Whilst such a strategy–action link (which we label here as ‘implementation nexus’) has been well estab-lished, other long-term effects have been documented in less detail. Our study of Sustainable Sydney 2030 finds that strategy was effective to the extent to which it changed the institutional apriori of what a collective of actors engaged in city-making knows, what it can articulate and how its members relate to each other. We capture this effect as ‘institution nexus’ and theorise ourfindings with Ludwik Fleck’s concept of ‘thought style’ of a focal ‘thought collective’ – notions that also centrally influenced Mary Douglas’ work on ‘how institutions think’. We contribute to extant research by adding the institution nexus as a long-term effect of urban strategy as well as by advancing strategy theory in urban studies to foreground its ability to shape institutions
Public preferences for heritage conservation strategies: a choice modelling approach
Full text linkStudies aiming at valuing cultural and natural heritage projects are often focussed on one or only a few sites, whereas planning decisions concerning the allocation of public funds to heritage conservation deal with classes of heritage rather than single sites. In addition, such planning decisions are almost always concerned with non-monetary values that need to be incorporated into assessment procedures if the total value of alternative strategies is to be estimated. In this paper, we put forward and estimate models to address both of these issues within a choice-modelling frame-work. The method is developed in the context of conservation of a particular class of cultural heritage, namely major historic buildings in a city or country. We report results from a discrete choice experiment to assess public preferences in which the choices are alternative conservation programs and the attributes are dimensions of the programs’ cultural and economic value. The model is estimated from survey data using several flexible econometric specifications. We show that the methods developed can be used to obtain robust estimates of the economic value of this category of buildings. We also find a significant contribution of all aspects of cultural value to the formation of conservation preferences and the public’s willingness to pay
Capital stranding cascades: The impact of decarbonisation on productive asset utilisation
Full text linkThe aim of this article is to assess the exposure of economic systems to the risk of physical capital stranding following a reduction of fossil fuel production and use. We calculate cross-sectoral and cross-country ‘marginal stranding multipliers’ for 43 regions, and study how supply-side capital stranding might propagate via international production networks. We show how the fossil industry has the potential of creating significant stranding cascades affecting downstream sectors and the economic system as a whole. We then focus on cross-country stranding impacts and rank countries according to their external stranding potential and to their exposure to external strandingrisk. Finally, we analyse more in depth the origins and transmission channels of the stranding links affecting the most exposed countries (US, China and Germany). Our results confirm the relevance of including multi-regional production networks and physical capital stranding into the ongoing effort to assess the macro-financial implications of a low-carbon transition.Series: Ecological Economic Paper
A comparison of optimization solvers for log binomial regression including conic programming
Full text linkRelative risks are estimated to assess associations and effects due to their ease of interpretability, e.g., in epidemiological studies. Fitting log-binomial regression models allows to use the estimated regression coefficients to directly infer the relative risks. The estimation of these models, however, is complicated because of the constraints which have to be imposed on the parameter space. In this paper we systematically compare different optimization algorithms to obtain the maximum likelihood estimates for the regression coefficients in log-binomial regression. We first establish under which conditions the maximum likelihood estimates are guaranteed to be finite and unique, which allows to identify and exclude problematic cases. In simulation studies using artificial data we compare the performance of different optimizers including solvers based on the augmented Lagrangian method, interior-point methods including a conic optimizer, majorize-minimize algorithms, iteratively reweighted least squares and expectation-maximization algorithm variants. We demonstrate that conic optimizers emerge as the preferred choice due to their reliability, lack of requirement to tune hyperparameters and speed
Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol
Full text linkStochastic volatility (SV) models are nonlinear state-space models that enjoy increasing popularity for fitting and predicting heteroskedastic time series. However, due to the large number of latent quantities, their efficient estimation is non-trivial and software that allows to easily fit SV models to data is rare. We aim to alleviate this issue by presenting novel implementations of four SV models delivered in two R packages. Several unique features are included and documented. As opposed to previous versions, stochvol is now capable of handling linear mean models, heavy-tailed SV, and SV with leverage. Moreover, we newly introduce factorstochvol which caters for multivariate SV. Both packages offer a user-friendly interface through the conventional R generics and a range of tailor-made methods. Computational efficiency is achieved via interfacing R to C++ and doing the heavy work in the latter. In the paper at hand, we provide a detailed discussion on Bayesian SV estimation and showcase the use of the new software through various examples
Moving from non-financial to sustainability reporting: analyzing the EU Commission's proposal for a Corporate Sustainability Reporting Directive (CSRD)
Full text linkEinflussfaktoren auf Studienerfolg: Heterogene Effekte nach Studienfachgruppe?
Full text linkDieser Beitrag untersucht Einflussfaktoren auf den Studienerfolg – als wichtigen Indikator für Studierbarkeit – unter besonderer Berücksichtigung der Studienfachgruppen. Dazu werden die Effekte verschiedener Merkmale auf die Studienabschlusswahrscheinlichkeit mittels logistischer Regressionsmodelle, auf Basis der österreichischen Hochschulstatistik, geschätzt (N = 481.320). Die Ergebnisse zeigen u. a., dass sich die soziale Herkunft und das Geschlecht je nach Fachgruppe unterschiedlich, jedoch gering, auswirken. Ein höheres Alter hat fächerübergreifend einen starken negativen Effekt, allerdings liegt eine Wechselwirkung mit der Vorbildung vor. Maßnahmen zur Verbesserung der Studierbarkeit sollten fachspezifische Bedingungen berücksichtigen