Double coverage and demand for health care: Evidence from quantile regression

An individual experiences double coverage when he bene ts from more than one health insurance plan at the same time. This paper examines the impact of such supplementary insurance on the demand for health care services. Its novelty is that within the context of count data modelling and without imposing restrictive parametric assumptions, the analysis is carried out for di¤erent points of the conditional distribution, not only for its mean location. Results indicate that moral hazard is present across the whole outcome distribution for both public and private second layers of health insurance coverage but with greater magnitude in the latter group. By looking at di¤erent points we unveil that stronger double coverage e¤ects are smaller for high levels of usage. We use data for Portugal, taking advantage of particular features of the public and private protection schemes on top of the statutory National Health Service. By exploring the last Portuguese Health Survey, we were able to evaluate their impacts on the consumption of doctor visi

Stackelberg leadership with demand uncertainty in a differentiated duopoly

On a symmetric differentiated Stackelberg duopoly model in which there is asymmetric demand information owned by leading and follower firms, we show that the leading firm does not necessarily have advantage over the following one. The reason for this is that the second mover can adjust its output level after observing the realized demand, while the first mover chooses its output level only with the knowledge of demand distribution.

Quantity-setting competition under uncertain demand

We consider a quantity-setting duopoly model, and we study the decision to move first or second, by assuming that. the firms produce homogeneous goods and that. there is some demand uncertainty. The competitive phase consists of two periods, and in either period, the firms can make a production decision that is irreversible. As far as the firms are allowed to choose (non-cooperatively) the period they make the decision, we study the circumstances that favour sequential rather than simultaneous decisions.

Stackelberg duopoly with demand uncertainty

We consider a symmetric Stackelberg model in which there is asymmetric demand information owned by first and second movers. We analyse the advantages of leadership and flexibility, and prove that when the leading firm faces demand uncertainty, but the follower does not, the first mover does not necessarily have advantage over the second mover. Moreover, we show that the advantage of one firm over the other depends upon the demand fluctuation and also upon the degree of substitutability of the products.

Flexibility and leadership advantages in a model with uncertain demand

We consider a differentiated Stackelberg model with demand uncertainty only for the first mover. We study the advantages of flexibility over leadership as the degree of the differentiation of the goods changes.

Demand Response Programs Design and Use Considering Intensive Penetration of Distributed Generation

Further improvements in demand response programs implementation are needed in order to take full advantage of this resource, namely for the participation in energy and reserve market products, requiring adequate aggregation and remuneration of small size resources. The present paper focuses on SPIDER, a demand response simulation that has been improved in order to simulate demand response, including realistic power system simulation. For illustration of the simulator’s capabilities, the present paper is proposes a methodology focusing on the aggregation of consumers and generators, providing adequate tolls for the demand response program’s adoption by evolved players. The methodology proposed in the present paper focuses on a Virtual Power Player that manages and aggregates the available demand response and distributed generation resources in order to satisfy the required electrical energy demand and reserve. The aggregation of resources is addressed by the use of clustering algorithms, and operation costs for the VPP are minimized. The presented case study is based on a set of 32 consumers and 66 distributed generation units, running on 180 distinct operation scenarios.

A multi-objective model for scheduling of short-term incentive-based demand response programs offered by electricity retailers

In this paper, we formulate the electricity retailers’ short-term decision-making problem in a liberalized retail market as a multi-objective optimization model. Retailers with light physical assets, such as generation and storage units in the distribution network, are considered. Following advances in smart grid technologies, electricity retailers are becoming able to employ incentive-based demand response (DR) programs in addition to their physical assets to effectively manage the risks of market price and load variations. In this model, the DR scheduling is performed simultaneously with the dispatch of generation and storage units. The ultimate goal is to find the optimal values of the hourly financial incentives offered to the end-users. The proposed model considers the capacity obligations imposed on retailers by the grid operator. The profit seeking retailer also has the objective to minimize the peak demand to avoid the high capacity charges in form of grid tariffs or penalties. The non-dominated sorting genetic algorithm II (NSGA-II) is used to solve the multi-objective problem. It is a fast and elitist multi-objective evolutionary algorithm. A case study is solved to illustrate the efficient performance of the proposed methodology. Simulation results show the effectiveness of the model for designing the incentive-based DR programs and indicate the efficiency of NSGA-II in solving the retailers’ multi-objective problem.

Induced Labor– Is There an Increased Risk of Perinatal Infection?

Objectives: To assess induced labor-associated perinatal infection risk at Hospital D.Estefânia from January to June of 2010 at Hospital de D. Estefânia’s delivery rooms, reviewing the indications for inducing labor as well as the techniques used. Material and Methods: Performing an historical prospective study searching the clinical processes as well as the mother and newborn’s computer database from January to June of 2010. An exposed and an unexposed group were created; the first group comprises pregnant women and their newborns whose labor was induced. The unexposed group is constituted by newborns and pregnant women whose labor was spontaneous. Labor induction was performed using intra-vaginal prostaglandins in women who didn’t start it spontaneously; perinatal infection was defined either clinically or using blood tests. The gestational age was ≥ 37 weeks for both groups. 19 variables were studied for both groups. Results: A total of 190 mother-newborn pairs were included: 55 in the exposed group and 135 in the unexposed group. 3 cases of perinatal infection were reported, two in the exposed group and one in the unexposed group. Preliminary data resulted in a perinatal infection rate of 3.6% in the exposed group and 0.7% in the unexposed group; preliminary data suggest that the risk of perinatal infection may be increased in up to 5-fold when labor is inducted. Conclusions: A larger series of patients and a multivariable analysis using logistic regression are both necessary in order to perform a more thorough assessment of labor induction’s role in perinatal infection risk. One must also try to distinguish labor inducing- and clinical practicesrelated factors.

Performance of state space and ARIMA models for consumer retail sales forecasting

Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.

Effects of Local Anesthetic on the Time Between Analgesic Boluses and the Duration of Labor in Patient-Controlled Epidural Analgesia: Prospective Study of Two Ultra-Low Dose Regimens of Ropivacaine and Sufentanil

BACKGROUND: Patient-controlled epidural analgesia with low concentrations of anesthetics is effective in reducing labor pain. The aim of this study was to assess and compare two ultra-low dose regimens of ropivacaine and sufentanil (0.1% ropivacaine plus 0.5 μg.ml-1 sufentanil vs. 0.06% ropivacaine plus 0.5 μg.ml-1 sufentanil) on the intervals between boluses and the duration of labor. MATERIAL AND METHODS: In this non-randomized prospective study, conducted between January and July 2010, two groups of parturients received patient-controlled epidural analgesia: Group I (n = 58; 1 mg.ml-1 ropivacaine + 0.5 μg.ml-1 sufentanil) and Group II (n = 57; 0.6 mg.ml-1 ropivacaine + 0.5 μg.ml-1 sufentanil). Rescue doses of ropivacaine at the concentration of the assigned group without sufentanil were administered as necessary. Pain, local anesthetic requirements, neuraxial blockade characteristics, labor and neonatal outcomes, and maternal satisfaction were recorded. RESULTS: The ropivacaine dose was greater in Group I (9.5 [7.7-12.7] mg.h-1 vs. 6.1 [5.1-9.8 mg.h-1], p < 0.001). A time increase between each bolus was observed in Group I (beta = 32.61 min, 95% CI [25.39; 39.82], p < 0.001), whereas a time decrease was observed in Group II (beta = -1.40 min, 95% CI [-2.44; -0.36], p = 0.009). The duration of the second stage of labor in Group I was significantly longer than that in Group II (78 min vs. 65 min, p < 0.001). CONCLUSIONS: Parturients receiving 0.06% ropivacaine exhibited less evidence of cumulative effects and exhibited faster second stage progression than those who received 0.1% ropivacaine.

The effect of demand information sharing in a supply chain under demand uncertainty: a simulation study

Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial

Energy efficiency in energy policy: Empirical evidence of direct rebound effect in Portuguese households' demand for electricity

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

Do hospitals react to random demand pressure by early discharges?

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

Estimating demand for primary health care services

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

Hospital costs and random demand

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics