infonet-economy

In this study, Markowitz mean-variance portfolio theory is applied to electricity-generating technologies of the United States and Switzerland. Both an investor (focused on changes in return) and a current user (focused on return in levels) view are adopted to determine efficient frontiers of electricity generation technologies in terms of expected return and risk as of 2003. Since shocks in generation costs per kWh (the inverse of returns) are correlated, Seemingly Unrelated Regression Estimation (SURE) is used to filter out the systematic components of the covariance matrix. Results suggest that risk-averse investors and risk-neutral current users in the United States are considerably closer to their efficiency frontier than their Swiss counterparts. This may be due to earlier and more thorough deregulation of electricity markets in the United States.

In this contribution, portfolio theory is applied to power technologies of the United States and Switzerland. A current user view is adopted to determine the efficient frontier of generation technologies in terms of expected return and risk. Since shocks in generation costs per kWh (the inverse of expected returns) are correlated, seemingly unrelated regression estimation (SURE) is applied to filter out the systematic components of the covariance matrix. Since some of the portfolios of particular interest (minimum variance, maximum expected return) call for a high share of one technology, security of supply becomes an issue. Shannon-Wiener and Herfindahl-Hirschman indices
are calculated to see the trade-off between efficiency and security of supply. Results suggest that riskaverse
utilities (and ultimately, consumers) in the United States would have gained from adopting a feasible portfolio containing more coal, gas and oil at a price of a somewhat reduced security of supply. In the case of Switzerland, the realistic portfolio consists of nuclear, storage hydro, run of river and solar, with shares identical to those of the actual portfolio in 2003. Therefore, the current mix of
Swiss generating technologies in Switzerland may be deemed efficient.

This chapter describes how economic theory (and experience) of the demand for insurance predicts that risk-averse individuals purchase coverage if available at so-called fair premiums, which amount to no more than the expected value of the loss to be covered. In the case of health, additional fi nancial means (provided by coverage) may be even more important when a person is ill than when he or she is healthy. If so, demand for health insurance, even in
low-income countries, could be high.

Every insurer needs to charge a “loading” for administrative expense, compensation for risk, and profi t (in the case of a public insurer, the loading amounts
to the effi ciency loss caused by taxation needed to finance the insurer’s operations). Therefore, the behavior of health insurance suppliers becomes of crucial importance. The loading contained in their premiums (or contributions) is just one of several supply dimensions, which include comprehensiveness of benefits, amount of risk selection effort, degree of vertical integration with health
services providers, and degree of seller concentration in the market. This chapter addresses these dimensions of supply and the powerful effect on them of moral hazard (the tendency of consumers to underinvest in prevention, choose
the most intensive treatment alternative, and push for application of the latest medical technology). In the presence of marked moral hazard effects, health
insurers are well advised to include only a few items in their benefi t list, because each of these items tends to increase in price, quantity, and hence expenditure. Moreover, premium regulation induces risk selection efforts. If allowed to charge contributions according to true risk, health insurers will set premiums such that
high and low risks yield the same contribution margin on expectation. In that event, risk selection (“cream skimming”) is not worthwhile. These phenomena hold not only for private health insurance in low-income countries but also for community-based and public health insurance.

Because little empirical data on the supply of health insurance exist, case studies, mainly of low-income countries, are used to illustrate theoretical predictions.
On the whole, the limited empirical evidence suggests that the theory developed in this chapter may be suffi ciently descriptive to provide some guidelines for policy.

This paper applies the five modified standard criteria generally used in economics for assessing system performances to gauge the contribution of Managed Care to the performance of three health care systems, viz. Germany, the Netherlands and the United States. The maximum contribution of Managed Care to the performance of the health care system is found for the United States and the Netherlands. The Health Maintenance Organization (U.S.) and the gatekeeper model (the Netherlands) score 10 and 9 out of 15 points, respectively, importantly due to a market-oriented environment. By way of contrast, the so-called ‘structured treatment programs’ of the German health care system score only 4 out of 15 points. Not only the more tightly regulated environment but also the lack of consideration of consumer preferences and of incentives for service providers to participate in the programs contributed to poor performance.

Im Aufleben neuer Industrien auf der traditionellen Industriebasis sieht Beat Hotz-Hart, ausserordentlicher Professor für Volkswirtschaftslehre und Wirtschaftspolitik
an der Universität Zürich, eine Chance auch für den Kanton Zürich.

Studying social behavior often requires the simultaneous interaction of many subjects. As yet, however, no painless, noninvasive brain stimulation tool existed that allowed the simultaneous affection of brain processes in many interacting subjects. Here we show that transcranial direct current stimulation (tDCS) can overcome these limits. We apply right prefrontal cathodal tDCS and show that subjects’ propensity to punish unfair behavior is reduced significantly.

We describe a Bayesian inference scheme for quantifying the active physiology of neuronal ensembles using local field recordings of synaptic potentials. This entails the inversion of a generative neural mass model of
steady-state spectral activity. The inversion uses Expectation Maximization (EM) to furnish the posterior probability of key synaptic parameters and the marginal likelihood of the model itself. The neural mass model
embeds prior knowledge pertaining to both the anatomical [synaptic] circuitry and plausible trajectories of neuronal dynamics. This model comprises a population of excitatory pyramidal cells, under local interneuron inhibition and driving excitation from layer IV stellate cells. Under quasi-stationary assumptions, the model can predict the spectral profile of local field potentials (LFP). This means model parameters can be optimised given real electrophysiological observations. The validity of
inferences about synaptic parameters is demonstrated using simulated data and experimental recordings from the medial prefrontal cortex of control and isolation-reared Wistar rats. Specifically, we examined the maximum a posteriori estimates of parameters describing synaptic function in the two groups and tested predictions derived from
concomitantmicrodialysismeasures.Themodelling of theLFP recordings revealed (i) a sensitization of post-synaptic excitatory responses, particularly marked in pyramidal cells, in the medial prefrontal cortex of socially isolated rats and (ii) increased neuronal adaptation. These
inferences were consistent with predictions derived from experimental microdialysis measures of extracellular glutamate levels.