Francisco Álvarez

Maternal Exposure to Δ 9 -Tetrahydrocannabinol (Δ 9 -THC) Alters Indolamine Levels and Turnover in Adult Male and Female Rat Brain Regions

Abstract Perinatal exposure to Δ 9 -THC has been shown to produce effects on brain development. In this study we evaluated the changes induced by maternal exposure to Δ 9 -THC (5 mg/kg per day) from gestational day 5 to postnatal day 24 in eight discrete brain areas on the central serotoninergic system in both adult male and female rats. These result show that maternal exposure to Δ 9 -THC from gestational day 5 to postnatal day 24 affects development of the various central indoleaminergic system of the offsprings brain. Perinatal exposure to Δ 9 -THC decreased the levels of 5-HT in hypothalamus and rostral neostriatum in exposed males, and also decreased the levels of 5-HT in ventral hippocampus, septum, and midbrain raphe nuclei in both exposed males and females. Perinatal exposure to Δ 9 -THC increased the levels of 5-HIAA in dorsal hippocampus, hypothalamus, septum, midbrain raphe nuclei, and rostral neostriatum in exposed males and females. We have also found differences between nonexposed males and females in several brain regions. Our results confirm a regional and sexual specificity in endogenous levels of indoleamine after perinatal Δ 9 -THC treatment, being the midbrain raphe nuclei the most affected area.

Auctioning vs. Grandfathering in Cap-and-Trade Systems with Market Power and Incomplete Information

We compare auctioning and grandfathering as allocation mechanisms of emission permits when there is a secondary market with market power and the firms have private information. Based on real-life cases such as the EU ETS, we consider a multi-unit, multi-bid uniform auction, modelled as a Bayesian game of incomplete information. At the auction each firm anticipates his role in the secondary market, which affects the firms’ valuation of the permits (that are not common across firms) as well as their bidding strategies and it precludes the auction from generating a cost-effective allocation of permits, as it would occur in simpler auction models. Auctioning tends to be more cost-effective than grandfathering when the firms’ costs are asymmetric enough, especially if the follower has lower abatement costs than the leader and uncertainty about the marginal costs is large enough. If market power spills over the auction, the latter is always less cost-effective than grandfathering. One central policy implication is that the specific design of the auction turns out to be crucial for cost-effectiveness. The chances of the auction to outperform grandfathering require that the former is capable of diluting the market power that is present in the secondary market.

Numerical analysis of a time allocation model accounting for choice overload

The cost of time has been suggested as a factor associated with the choice overload problem. This term refers to the discomfort or paralysis experienced by individuals when facing a choice within a large set of alternatives, as it has been evidenced in experiments by behavioural and social psychologists. We introduce a rational model of time allocation to analyse how increasing the number of options of a given product may change consumers allocation of time and in turn affect her welfare. Under some standard assumptions, the numerical analysis of the model reproduces two key experimental findings, namely choice paralysis – i.e. the choice problem is abandoned if the number of options is too large – and choice dissatisfaction – that is, the apparent paradox that increasing the number of considered options beyond certain limit, in turn choosing better, eventually diminishes welfare. The model analysis provides specific threshold values for the occurrence of both phenomena.

Comparing the Spanish and the discriminatory auction formats: A discrete model with private information

Abstract The Spanish Treasury is the only Treasury in the world that uses a hybrid system of discriminatory and uniform price auctions to sell government debt: winning bidders pay their bid price for each unit if this is lower than the weighted average price of winning bids (WAP), and pay the WAP otherwise. Following Gordy [Gordy, M., 1996. Multiple bids in a multiple-unit common-value auction. Board of Governors of the Federal Reserve System], we model the Spanish auction as a common value auction of multiple units with private information, allowing for multiple bids. Numerical analysis shows that bidders spread their bids more in the Spanish than in the discriminatory auction and bid higher for the first unit, and that the expected seller’s revenue is higher in the Spanish than in the discriminatory auction within a reasonable set of parameter values.

Learning-by-Doing Under Uncertainty

Empirical research indicates that learning-by-doing may be one of the main causes of falling production costs. A number of authors like Arrow, Fudenberg and Tirole, Dasgupta and Stiglitz, have focused on the theoretical implications of learning-by-doing. However, a complete framework incorporating learning, stock building as well as uncertainty, is lacking in the literature. In this paper we broaden earlier theoretical work in two ways. First, we present a theoretical model of learning-by-doing in which the unit-cost structure is not fully known to the firm. The firm has to estimate its stochastic cost structure during the production process. Second, the model allows for the firm to keep a stock which adds to the complexity of the learning process. Through monte carlo techniques we derive the optimal production and sales quantities for multiple cost structures.

Analytical solution for a class of learning by doing models with multiplicative uncertainty

We find the closed form optimal solution for a class of learning by doing models, where multiplicative uncertainty is introduced in a piecewise linear cost reduction function. Previous literature does not find the closed form optimal solution for these models. We consider a monopolist, facing a linear demand function. The optimal policy for the resulting problem is shown to be piecewise linear and continuous. The optimal output increases with unit cost for certain values of the latter. Numerical examples are provided.

Choice Overload, Satisficing Behavior, and Price Distribution in a Time Allocation Model

Recent psychological research indicates that consumers that search exhaustively for the best option of a market product—known as maximizers—eventually feel worse than consumers who just look for something good enough—called satisficers. We formulate a time allocation model to explore the relationship between different distributions of prices of the product and the satisficing behavior and the related welfare of the consumer. We show numerically that, as the number of options becomes large, the maximizing behavior produces less and less welfare and eventually leads to choice paralysis—these are effects of choice overload—whereas satisficing conducts entail higher levels of satisfaction and do not end up in paralysis. For different price distributions, we provide consistent evidence that maximizers are better off for a low number of options, whereas satisficers are better off for a sufficiently large number of options. We also show how the optimal satisficing behavior is affected when the underlying price distribution varies. We provide evidence that the mean and the dispersion of a symmetric distribution of prices—but not the shape of the distribution—condition the satisficing behavior of consumers. We also show that this need not be the case for asymmetric distributions.

Learning by doing in a T-period production planning: Analytical solution

Abstract The firms in many industries shift down the production cost function as they accumulate experience (learning by doing). The intertemporal production decision of the firm under learning by doing can be formulated as a Dynamic Optimization problem. Though properties of the solution to that problem are known, in general this analytical solution has not been presented in the literature. In this paper we present the analytical solution for a class of discrete time T-period learning by doing problems. This allows us to gain insight into practical aspects such as determining when current losses are expected to occur or when the firm will become fully efficient. Examples are provided.

Consumer's response to price distribution and σ -overload under time allocation

It has been recently suggested that both the number of options considered by consumers and their satisfaction when shopping respond to changes in the mean and spread of market prices. A structured analysis of those responses is provided in this paper. A new adverse effect related with consumers welfare is presented here, namely a consumer that searches exhaustively among all market options-called maximizer-experiences welfare loss when the dispersion of prices is too high. In fact, her welfare exhibits an inverted- U shape with respect to the standard deviation ? of prices so that an increase in price spread produces more welfare for small values of ? but it has a negative effect for larger values of ? . This new phenomenon is termed ? -overload. It is also shown that a consumer that is content with shopping from a reduced sample of options-a satisficer-avoids ? -overload by adapting her search behavior to the increase in spread. A quantitative assessment of consumers behavior and welfare with respect to changes in the mean and dispersion of prices under different scenarios is also provided.

Some Software Engineering and Knowledge Representation Principles for the Design and Construction of Ontology-Based Linguistic Resources

Nowadays, ontologies have become a common component of natural language processing systems as well as of many others. Nevertheless, in spite of the existing explosion of ontological resources, they have been developed without a rigorous methodological approach. Furthermore the usage of semantic relations between concepts has been so subjective that has led to errors affecting the coherence of these ontologies. In this article, we introduce a methodology for the construction of ontological linguistic resources based on software engineering, and develop the first of its 3 stages, introducing notions of knowledge organization and control of semantic relations for the gradual and systematic development of well-designed and coherent ontologies.