Do hospitals react to random demand pressure by early discharges?

This project tries to assess whether hospitals react to random demand pressure by discharging patients earlier than expected. As a matter of fact, combining an unpredictable demand for medical services with limited and, to some extent, fixed medical resources, generates strong incentives to discharge patients earlier than expected when demand is high − increasing the risk of readmission and decreasing the benefit from treatment. This work was conducted as a way to determine whether those incentives actually affect discharging decisions. Analysis of Portuguese hospitals data shows that hospital utilization levels at the time of admission, prior to the admission and post admission do have a negative impact over the length of stay in hospital, although this impact is quantitatively irrelevant. More than that, larger utilization levels have a positive impact over the probability of being discharged at certain days of the week, indicating that an early discharges problem may exist.

Estimating demand for primary health care services

Primary health services exist with the purpose of providing basic health care to every person at a cost they can afford. But is it fully available to everyone? The objective of this work project is to estimate the demand for primary health care services having into account that in some regions the citizens are not using as much health care as they would like due to supply side constraints. Using the number of consultations as proxy for demand, and applying an econometric tool called switching regression, the demand for primary health care services will be estimated.

Control in distribution networks with demand side management

The way in which electricity networks operate is going through a period of significant change. Renewable generation technologies are having a growing presence and increasing penetrations of generation that are being connected at distribution level. Unfortunately, a renewable energy source is most of the time intermittent and needs to be forecasted. Current trends in Smart grids foresee the accommodation of a variety of distributed generation sources including intermittent renewable sources. It is also expected that smart grids will include demand management resources, widespread communications and control technologies required to use demand response are needed to help the maintenance in supply-demand balance in electricity systems. Consequently, smart household appliances with controllable loads will be likely a common presence in our homes. Thus, new control techniques are requested to manage the loads and achieve all the potential energy present in intermittent energy sources. This thesis is focused on the development of a demand side management control method in a distributed network, aiming the creation of greater flexibility in demand and better ease the integration of renewable technologies. In particular, this work presents a novel multi-agent model-based predictive control method to manage distributed energy systems from the demand side, in presence of limited energy sources with fluctuating output and with energy storage in house-hold or car batteries. Specifically, here is presented a solution for thermal comfort which manages a limited shared energy resource via a demand side management perspective, using an integrated approach which also involves a power price auction and an appliance loads allocation scheme. The control is applied individually to a set of Thermal Control Areas, demand units, where the objective is to minimize the energy usage and not exceed the limited and shared energy resource, while simultaneously indoor temperatures are maintained within a comfort frame. Thermal Control Areas are overall thermodynamically connected in the distributed environment and also coupled by energy related constraints. The energy split is performed based on a fixed sequential order established from a previous completed auction wherein the bids are made by each Thermal Control Area, acting as demand side management agents, based on the daily energy price. The developed solutions are explained with algorithms and are applied to different scenarios, being the results explanatory of the benefits of the proposed approaches.

What do broadband consumers want? Design and execution of a questionnaire on demand for bundled services on the Portuguese telecomunications market

The report addresses the question of what are the preferences of broadband consumers on the Portuguese telecommunication market. A triple play bundle is being investigated. The discrete choice analysis, adopted in the study, base on 110 responses, mainly from NOVA students. The data for the analysis was collected via manually designed on-line survey. The results show that the price attribute is relatively the most important one while the television attribute is being overlooked in the decision making process. Main effects examined in the research are robust. In addition, "extras" components are being tested in terms of users' preferences.

Optimal behavior of responsive residential demand considering hybrid phase change materials

Due to communication and technology developments, residential consumers are enabled to participate in Demand Response Programs (DRPs), control their consumption and decrease their cost by using Household Energy Management (HEM) systems. On the other hand, capability of energy storage systems to improve the energy efficiency causes that employing Phase Change Materials (PCM) as thermal storage systems to be widely addressed in the building applications. In this paper, an operational model of HEM system considering the incorporation of more than one type of PCM in plastering mortars (hybrid PCM) is proposed not only to minimize the customerâ s cost in different DRPs but also to guaranty the habitantsâ  satisfaction. Moreover, the proposed model ensures the technical and economic limits of batteries and electrical appliances. Different case studies indicate that implementation of hybrid PCM in the buildings can meaningfully affect the operational pattern of HEM systems in different DRPs. The results reveal that the customerâ s electricity cost can be reduced up to 48% by utilizing the proposed model.

International trade, technical change and the demand for skills : how important is trade in quality differential products?

Magdeburg, Univ., Fak. für Wirtschaftswiss., Diss., 2012

A Grid Supercomputing Enviroment for High Demand Computational Applications

Despite the huge increase in processor and interprocessor network performace, many computational problems remain unsolved due to lack of some critical resources such as floating point sustained performance, memory bandwidth, etc... Examples of these problems are found in areas of climate research, biology, astrophysics, high energy physics (montecarlo simulations) and artificial intelligence, among others. For some of these problems, computing resources of a single supercomputing facility can be 1 or 2 orders of magnitude apart from the resources needed to solve some them. Supercomputer centers have to face an increasing demand on processing performance, with the direct consequence of an increasing number of processors and systems, resulting in a more difficult administration of HPC resources and the need for more physical space, higher electrical power consumption and improved air conditioning, among other problems. Some of the previous problems can´t be easily solved, so grid computing, intended as a technology enabling the addition and consolidation of computing power, can help in solving large scale supercomputing problems. In this document, we describe how 2 supercomputing facilities in Spain joined their resources to solve a problem of this kind. The objectives of this experience were, among others, to demonstrate that such a cooperation can enable the solution of bigger dimension problems and to measure the efficiency that could be achieved. In this document we show some preliminary results of this experience and to what extend these objectives were achieved.

The Instrumental voter goes to the news-agent: demand for information, election closeness, and the media

This paper studies the impact of instrumental voting on information demand and mass media behaviour during electoral campaigns. If voters act instrumentally then information demand should increase with the closeness of an election. Mass media are modeled as profit-maximizing firms that take into account information demand, the value of customers to advertisers and the marginal cost of customers. Information supply should be larger in electoral constituencies where the contest is expected to be closer, there is a higher population density, and customers are on average more profitable for advertisers. The impact of electorate size is theoretically undetermined. These conclusions are then tested with comfortable results on data from the 1997 general election in Britain.

Do market conditions affect gift exchange? Evidence from experimental markets with excess supply and excess demand

We study whether people's behavior in unbalanced gift exchange markets with repeated interaction are affected by whether they are on the excess supply side or the excess demand side of the market. Our analysis is based on the comparison of behavior between two types of experimental gift exchange markets, which vary only with respect to whether first or second movers are on the long side of the market. The direction of market imbalance could influence subjects' behavior, as second movers (workers) might react differently to favorable actions by first movers (firms) in the two cases. While our data show strong deviations from the standard game-theoretic prediction, we find mainly secondary treatment effects. Wage offers are not higher when there is an excess supply of firms, and workers do not respond more favorably to a given wage when there is an excess supply of labor. The state of competition does not appear to have strong effects in our data. We also present data from single-period sessions that show substantial gift exchange even without repeated interactions.

Asymmetric demand information in uniform and discriminatory call auctions: an experimental analysis motivated by electricity markets

We study the outcomes of experimental multi-unit uniform and discriminatory auctions with demand uncertainty. Our study is motivated by the ongoing debate about market design in the electricity industry. Our main aim is to compare the effect of asymmetric demand-information between sellers on the performance of the two auction institutions. In our baseline conditions all sellers have the same information, whereas in our treatment conditions some sellers have better information than others. In both information conditions we find that average transaction prices and price volatility are not significantly different under the two auction institutions. However, when there is asymmetric information among sellers the discriminatory auction is significantly less efficient. These results are not in line with the typical arguments made in favor of discriminatory pricing in electricity industries; namely, lower consumer prices and less price volatility. Moreover, our results provide some indication that discriminatory auctions reduce technical efficiency relative to uniform auctions.

Hausman tests for inefficient estimators: application to demand for health care service (revised)

The Hausman (1978) test is based on the vector of differences of two estimators. It is usually assumed that one of the estimators is fully efficient, since this simplifies calculation of the test statistic. However, this assumption limits the applicability of the test, since widely used estimators such as the generalized method of moments (GMM) or quasi maximum likelihood (QML) are often not fully efficient. This paper shows that the test may easily be implemented, using well-known methods, when neither estimator is efficient. To illustrate, we present both simulation results as well as empirical results for utilization of health care services.

Likelihood-based approaches to modeling demand for medical care

We review recent likelihood-based approaches to modeling demand for medical care. A semi-nonparametric model along the lines of Cameron and Johansson's Poisson polynomial model, but using a negative binomial baseline model, is introduced. We apply these models, as well a semiparametric Poisson, hurdle semiparametric Poisson, and finite mixtures of negative binomial models to six measures of health care usage taken from the Medical Expenditure Panel survey. We conclude that most of the models lead to statistically similar results, both in terms of information criteria and conditional and unconditional prediction. This suggests that applied researchers may not need to be overly concerned with the choice of which of these models they use to analyze data on health care demand.

The demand elasticity on tolled motorways

This paper analyses the elasticities of demand in tolled motorways in Spain with respect to the main variables influencing it. The demand equation is estimated using a panel data set where the cross-section observations correspond to the different Spanish tolled motorways sections, and the temporal dimension ranges from the beginning of the eighties until the end of the nineties. The results show a high elasticity with respect to the economic activity level. The average elasticity with respect to petrol price falls around -0.3, while toll elasticities clearly vary across motorway sections. These motorway sections are classified into four groups according to the estimated toll elasticity with values that range from -0.21 for the most inelastic to -0.83 for the most elastic. The main factors that explain such differences are the quality of the alternative road and the length of the section. The long-term effect is about 50 per cent higher than the short term one; however, the period of adjustment is relatively short.

Demand and revenue implications of an integrated public transport policy: the case of Madrid

One of the most popular options for promoting public transport use is the provision of an integrated and high quality public transport system. This was the strategy adopted by the regional government in Madrid in 1986 and since then public transport patronage has increased by more than 50%. This paper has two objectives. The first is to identify the factors underlying the significant increase in the demand for public transport in Madrid. To do this we estimate an aggregate demand function for bus and underground trips, which allows us to obtain the demand elasticities with respect to the main attributes of public transport services and also to calculate the long-term impact of changes in those explanatory variables on patronage. The second objective is to evaluate the impact on revenue derived from the introduction of the travel card scheme, and to discuss the consequences on revenue of changes in the relative fare levels of different types of ticket without substantially affecting patronage. This latter issue is addressed by estimating a matrix of own and cross-price elasticities for different ticket types.