Using technology to improve the management of development impacts on biodiversity

The mitigation hierarchy (MH) is a prominent tool to help businesses achieve no net loss or net gain outcomes for biodiversity. Technological innovations offer benefits for business biodiversity management, yet the range and continued evolution of technologies creates a complex landscape that can be difficult to navigate. Using literature review, online surveys, and semi-structured interviews, we assess technologies that can improve application of the MH. We identify six categories (mobile survey, fixed survey, remote sensing, blockchain, data analysis, and enabling technologies) with high feasibility and/or relevance to (i) aid direct implementation of mitigation measures and (ii) enhance biodiversity surveys and monitoring, which feed into the design of interventions including avoidance and minimization measures. At the interface between development and biodiversity impacts, opportunities lie in businesses investing in technologies, capitalizing on synergies between technology groups, collaborating with conservation organizations to enhance institutional capacity, and developing practical solutions suited for widespread use.     

In Search of the Transmission Mechanism of Fiscal Policy in the Euro Area

This paper applies the DSGE‐VAR methodology to assess the size of fiscal multipliers in the data and the relative contributions of two transmission mechanisms of government spending shocks, namely hand‐to‐mouth consumers and Edgeworth complementarity. Econometric experiments show that a DSGE model with Edgeworth complementarity is a better representation of the transmission mechanism of fiscal policy as it yields dynamic responses close to those obtained with the flexible DSGE‐VAR model (i.e. an impact output multiplier larger than one and a crowding‐in of private consumption). The estimated share of hand‐to‐mouth consumers is too small to replicate the positive response of private consumption. Copyright © 2016 John Wiley & Sons, Ltd.     

Breaking Collusion in Auctions through Speculation: An Experiment on CO2 Emission Permit Markets

The European Emission Trading Scheme (EU‐ETS) has chosen to adopt an auctioning procedure to initially allocate CO₂ emission permits. Free allocation of permits will become an exception for the third phase (2013–2020) and most firms will have to buy all their permits on the market or via auctions. The ability of bidders to collude is a key concern about the design of the auction format. To counter collusion, the auction can be open to bidders without compliance obligations (speculators). This paper aims at studying experimentally speculation as a collusion‐breaking device in two different auction mechanisms: the uniform‐price sealed‐bid auction and the ascending clock auction. Our results suggest that a uniform sealed‐bid auction open to speculators should be chosen from a revenue maximization point of view. In this mechanism, compliance agents adopt an aggressive strategy toward speculators. This strategy significantly increases the seller's revenue, compared to the more collusive clock auction. In the latter, on the contrary, bidders accommodate speculators, letting them buy permits in the auction and buying their necessary permits on the secondary market. However, as opening the auction to speculators deteriorates efficiency, the regulator faces a trade‐off between these two objectives.     

Estimation of physical intensity models for default risk

The estimation of physical intensity processes in the context of default risk is investigated here. Using data from Moody's Corporate Bond Default Database, a term structure of default probabilities for different rating classes is constructed each year from 1970 to 2001. Two specifications used for modeling the dynamics of the (risk‐neutral) intensity process in the bond‐pricing literature are then examined empirically: the Ornstein–Uhlenbeck and square‐root cases. The results reveal that the Ornstein–Uhlenbeck case is not an adequate modeling alternative with a rejection of this specification in five out of seven credit classes and nonsignificant mean reverting behavior for all credit classes. The square‐root case obtains better results with four credit classes out of seven for which this specification cannot be rejected and significant mean reversion parameters in many cases. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 29:95–113, 2009     

“Work is my passion”: The different affective,behavioural, and cognitive consequences of harmonious and obsessive passion toward work

This study applies the dualistic model of passion (Vallerand et al., 2003) to the work setting and examines the relationships between harmonious passion (characterized by a strong but controllable desire to engage in an activity), obsessive passion (characterized by an internal pressure to carry out an activity), and optimal functioning outcomes at work. Harmonious passion associated positively with: mental health; three elements of flow (i.e., concentration, control, and autotelic experience); vitality, and affective commitment. These relationships were partly mediated by satisfaction of the basic psychological needs of autonomy, competence, and relatedness. In contrast, obsessive passion directly and negatively predicted mental health and weakly but positively predicted autotelic experience. Theoretical and applied implications are discussed. Copyright ©2010 ASAC. Published by John Wiley & Sons, Ltd.     

A regime-switching term structure model with observable state variables

The paper proposes in a regime-shift framework, an arbitrage-free term structure model based on the target and Fed Funds Rates. Empirical observations suggest that a three-state regime-shift environment associated with FOMC monetary actions is justified. Then, a closed-form solution for zero-coupon bonds is derived where regime-shift risk is priced. The solution is flexible enough to incorporate additional state variables.     

Identification, weak instruments, and statistical inference in econometrics

Abstract.  We discuss statistical inference problems associated with identification and testability in econometrics. We consider inference in non-parametric models and weakly identified structural models (weak instruments). We point out that many ill‐defined statistical problems, such as non‐testable hypotheses, occur in these areas and are typically associated with asymptotic approximations. In non‐parametric models, such problems include testing moments and inference under heteroscedasticity or serial dependence of unknown form. For weakly identified structural models, difficulties are typically associated with improper pivots, and we review recent developments aimed at proposing more reliable procedures, including alternative proposed statistics, bounds, projection, split‐sampling, conditioning, Monte Carlo tests. JEL classification: C1, C12, C14, C15, C3, C5