(English text below) Nell ambito del progetto di valorizzazione del territorio Lugano al verde, Città di Lugano, AIL SA, l'incubatore per la sostenibilità SINC (Università della Svizzera italiana, USI), Dipartimento della sanità e della socialità del Canton Ticino (DSS) e Associazione fontanieri ...
In competitive procurement auctions, bids often have the form of unit-price contracts (UPCs). We show that optimal bidding behavior in UPC auctions is typically non-monotonic, and therefore may lead to inefficient allocations. However, UPC auctions may still be desirable for the buyer when compared to efficient mechanisms such as the first-price auction. In a UPC auction, low types are subsidized, and the resulting stronger competition reduces the winning bidder's informational rent, which overcompensates the efficiency loss.
Promises are one of the oldest human-specific psychological mechanisms fostering cooperation and trust. Here, we study the neural underpinnings of promise keeping and promise breaking. Subjects first make a promise decision (promise stage), then they anticipate whether the promise affects the interaction partner's decision (anticipation stage), and are subsequently free to keep or break the promise (decision stage). Findings revealed that the breaking of the promise is associated with increased activation in the DLPFC, ACC, and amygdala, suggesting that the dishonest act involves an emotional conflict due to the suppression of the honest response. Moreover, the breach of the promise can be predicted by a perfidious brain activity pattern (anterior insula, ACC, inferior frontal gyrus) during the promise and anticipation stage, indicating that brain measurements may reveal malevolent intentions before dishonest or deceitful acts are actually committed.
We discuss a unified theory of directed technological change and technology adoption that can shed light on the causes of persistent productivity differences across countries. In our model, new technologies are designed in advanced countries and diffuse endogenously to less developed countries. Our framework is rich enough to highlight three broad reasons for productivity differences: inappropriate technologies, policy-induced barriers to technology adoption, and within-country misallocations across sectors due to policy distortions. We also discuss the effects of two aspects of globalization, trade in goods and migration, on the wealth of nations through their impact on the direction of technical progress. By doing so, we illustrate some of the equalizing and unequalizing forces of globalization.
This paper develops a DSGE model to examine the quantitative macroeconomic implications of counter-cyclical fiscal policy for France, Germany and the UK. The model incorporates real wage rigidity and consumption habits, as the particular market failures justifying policy intervention. We subject the model to productivity shocks and allow policy instruments to react to the output gap and the debt-to-output ratio. A welfare analysis reveals that the most effective instrument-target combination is to use public consumption to stabilize the output gap. Moreover, welfare gains from counter-cyclical fiscal policy are much stronger in the presence of wage rigidities compared with consumption habits. Finally, since active policy and automatic stabilizers are substitutes, it is possible that relatively undistorted economies may be in need of countercyclical fiscal action due to inadequate automatic stabilizers.
Neurophysiologische und bildgebende Verfahren zur Messung von Hirnaktivität, wie fMRI oder EEG, werden in den Neurowissenschaften eingesetzt, um Prozesse funktioneller Spezialisierung und funktioneller Integration im menschlichen Gehirn zu untersuchen. Funktionelle Integration kann auf zwei verschiedene Arten beschrieben werden: funktionelle Konnektivität und effektive Konnektivität. Während die funktionelle Konnektivität lediglich statistische Abhängigkeiten zwischen Zeitreihen beschreibt, erfordert das Konzept der effektiven Konnektivität ein mechanistisches Modell der kausalen Effekte, die den beobachteten Daten zu Grunde liegen. Dieser Artikel fasst die konzeptionellen und methodischen Grundlagen moderner Techniken für die Analyse funktioneller und effektiver Konnektivität auf der Basis von fMRI und elektrophysiologischen Daten zusammen. Ein besonderer Schwerpunkt liegt dabei auf dem Dynamic Causal Modelling (DCM), einem neuen Verfahren zur Analyse nichtlinearer neuronaler Systeme. Diese Methode besitzt ein vielversprechendes Potenzial für klinische Anwendungen, z. B. zur Entschlüsselung pathophysiologischer Mechanismen bei Hirnerkrankungen und zur Etablierung neurophysiologisch fundierter diagnostischer Klassifikationen.
Abstract
Neurophysiological and imaging procedures to measure brain activity, such as fMRI or EEG, are employed in neuroscience to investigate processes of functional specialisation and functional integration in the human brain. Functioal integration can be described in two distinct ways: functional connectivity and effective connectivity. Whereas functional connectivity merely describes the statistical dependence between two time series, the concept of effective connectivity requires a mechanistic model of the causative effects upon which the data to be observed are based. This article summarises the conceptual and methodological principles of modern techniques for the analysis of functional and effective connectivity on the basis of fMRI and electrophysiological data. Particular emphasis is placed on dynamic causal modelling (DCM), a new procedure for the analysis of non-linear neuronal systems. This method has a highly promising potential for clinical applications, e. g., for decoding pathological mechanisms in brain diseases and for the establishment of neurologically valid diagnostic classifications.
