A dynamic model for disaster response considering prioritized demand points

This paper addresses the problem of distributing relief supplies after the occurrence of a disaster. We develop a dynamic model to serve demand, while prioritizing the response, according to the level of urgency of demand points. Our model is thought to be applied during a planning horizon and it considers dynamic demand, capacity constraints and priorities. To evaluate the applicability of our model, we use a real case study of a flood occurred in Colombia. We also test the computational solvability of our model and we propose and test different solution methodologies for solving larger instances of our problem.     

Estimation of a dynamic demand function for gasoline with different schemes of parameter variation

In this article we explore the consumer demand for gasoline within the framework of the household production function model. Working with a time series of regional cross-sections, we find the parameters in the gasoline demand model varying across states. Random coefficient model is utilized to analyze temporal cross-section data.     

Economies with a mean demand function

The present paper shows one way to look at G. Debreu and W. Hildenbrand's conjecture that certain atomless economies have mean demand functions. We conclude within the continuity framework that an economy gives rise ‘in general’ to a continuous mean demand function, and that the class of all atomless economies is ‘big’ in the space of all economies with a continuous mean demand function. The same problems are reconsidered within the framework of a space of differentiable preferences at the end.     

Estimation of a continuous-time dynamic demand system

A continuous-time dynamic model of consumers' demand, explicitly taking account of the roles of depreciation, interest rates, habits, and stocks, is estimated using recently developed techniques from discrete quarterly UK data on three broad commodity groupings. The results suggest that, whilst being a significant determinant of demand, the actual magnitude of the influence of changes in interest rates may be relatively small in the long run. The cross-price effects of durable goods are also found to be statistically significant, and symmetry of long-run compensated price responses is not rejected.     

Optimum,market and second-best land use patterns in a von Thünen city with congestion

This paper constructs a von Thünen type model with traffic congestion and two production inputs. A comparison between optimum and market land use patterns is presented. The second-best problem in which congestion tolls are not allowed is also considered. The policy variable in the analysis is the allocation of land between production and transportation. The result is examined in a cost-benefit analysis based on market rent.     

Optimal advertising for selling a product with a nondifferentiable demand function

We consider a firm which seeks the maximum profit by selling a product and assume that the firm can advertise its product in order to improve the firm goodwill and affect the product demand positively. In particular the good demand is zero when the goodwill is less than a fixed threshold. The problem is formulated in terms of optimal control theory. We show that there exists a unique optimal solution and sketch an algorithm to determine it.     

A two-period newsvendor model for prepositioning with a post-disaster replenishment using Bayesian demand update

Humanitarian aid agencies usually resort to inventory prepositioning to mitigate the impact of disasters by sending emergency supplies to the affected area as quickly as possible. However, a lack of replenishment opportunity after a disaster can greatly hamper the effectiveness of the relief operation due to uncertainty in demand. In this paper, a prepositioning problem is formulated as a two-period newsvendor model where the response phase is divided into two periods. The model acknowledges the demand to be uncertain even after the disaster and utilises the Bayesian approach to revise the demand of the second period. Based on the revised demand, an order is placed at the beginning of the second period to be replenished instantaneously. A two-stage solution methodology is proposed to find the prepositioning quantity and post-disaster replenishment quantity, which minimise the total expected costs of relief operations. A numerical example is presented to demonstrate the solution methodology, and sensitivity analysis is performed to examine the effect of model parameters. The results highlight the indifferent characteristics shown by the replenishment quantity with the variation in model parameters.     

Estimating willingness to pay for medicare using a dynamic life-cycle model of demand for health insurance

Medicare is the largest health insurance program in the US. This paper uses a dynamic random utility model of demand for health insurance in a life-cycle human capital framework with endogenous production of health to calculate the individual willingness to pay (WTP) for Medicare. The model accounts for the feature that the demand for health insurance is derived through the demand for health, which is jointly determined with the production of health over the life-cycle. The WTP measure incorporates the effects of Medicare insurance on aggregate consumption through effects on medical expenditures and mortality, and consumption utility of health. The model is estimated using panel data from the Health and Retirement Study. The average WTP or change in lifetime expected utility resulting from delaying the age of eligibility to 67 is found to be $ 24,947 in 1991 dollars ($ 39,435 in 2008 dollars). However, there is considerable variation in the WTP, e.g., in 1991 dollars the WTP of individuals who have less than a high school education and are white is $ 28,347 ($ 44,810 in 2008 dollars), while the WTP of those with at least a college degree and who are neither white nor black is $ 15,584 ($ 24,635 in 2008 dollars). More generally, the less educated have a higher WTP to avoid a policy change that delays availability of Medicare benefits. Additional model simulations imply that the primary benefits of Medicare are insurance against medical expenditures with relatively smaller benefits in terms of improved health status and longevity. Medicare also leads to large increases in medical utilization due to deferring of medical care prior to eligibility.     

A dynamic almost ideal demand system incorporating consumer expectations

In this paper a theoretical framework is presented for the analysis of the effects of psychological, perceptual or expectational factors on household expenditure within a complete demand system. The model was estimated using the Consumer Sentiment Index, which represents an index of consumer perceptions of economic conditions. Evidence was found for significant expectational effects on five of nine expenditure categories—food at home, alcohol, housing, durables and other services. The direct expectation effects were found to be small in size. The results demonstrate the model's potential usefulness as a framework for modelling consumer behavioral responses to expectations and for evaluating the welfare implications of policy-induced changes in expectations.     

Time‐varying intercepts and equilibrium analysis: an extension of the dynamic almost ideal demand model

Demographic effects and user costs in demand systems have usually been modelled explicitly. A more robust approach is a state space formulation of the demand system, where time‐varying intercepts account for the effects of unobservable variables. The author embeds such a system in a vector autoregressive distributed lag model, with a Bayesian hierarchical prior. The model is estimated by a Markov chain Monte Carlo method on samples involving quarterly US and UK data. In the US case, the results are compared with a previously published cointegration analysis of the same data. Copyright © 2002 John Wiley & Sons, Ltd.     

A model of local demand for education

A careful modeling of the spending behavior of local school districts in New Jersey is presented. The theoretical model relies on the common hypothesis of political competition leading to a median outcome as well as the assumption that school superintendents act as budget maximizers. The model is estimated for a sample of 177 school districts under three different aid formulas. Pooling of the cross sections suggests that the response of school expenditures to changes in variables other than those associated with school aid parameters has remained constant over time. The results are discussed in the context of recent theories regarding the effect of intergovernmental aid on the level of public expenditure.     

A dynamic model of urban land use with externalities

A dynamic model of the urban land and building market is proposed which explicitly incorporates endogenous spatial externalities. Using stochastic optimization the model estimates for each period first the supply of building space and then the spatial allocation of activities. Prices for buildings and land are endogenous. The development of the urban area depends on the demand for labor in basic industries. The dynamics of the system is controlled also by the lagged response to endogenous variables. Thus, both the level of externalities, which affect the allocation of activities, and rents, which influence the location of the building supply, are based on the results of the preceding period.     

Predicting recessions with a composite real-time dynamic probit model

In this paper we propose a composite indicator for real-time recession forecasting based on alternative dynamic probit models. For this purpose, we use a large set of monthly macroeconomic and financial leading indicators from the German and US economies. Alternative dynamic probit regressions are specified through automated general-to-specific and specific-to-general lag selection procedures on the basis of slightly different initial sets. The resulting recession probability forecasts are then combined in order to decrease the volatility of the forecast errors and increase their forecasting accuracy. This procedure features not only good in-sample forecast statistics, but also good out-of-sample performances, as is illustrated using a real-time evaluation exercise.     

A test of cross section dependence for a linear dynamic panel model with regressors

This paper proposes a new testing procedure for detecting error cross section dependence after estimating a linear dynamic panel data model with regressors using the generalised method of moments (GMM). The test is valid when the cross-sectional dimension of the panel is large relative to the time series dimension. Importantly, our approach allows one to examine whether any error cross section dependence remains after including time dummies (or after transforming the data in terms of deviations from time-specific averages), which will be the case under heterogeneous error cross section dependence. Finite sample simulation-based results suggest that our tests perform well, particularly the version based on the [Blundell, R., Bond, S., 1998. Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics 87, 115–143] system GMM estimator. In addition, it is shown that the system GMM estimator, based only on partial instruments consisting of the regressors, can be a reliable alternative to the standard GMM estimators under heterogeneous error cross section dependence. The proposed tests are applied to employment equations using UK firm data and the results show little evidence of heterogeneous error cross section dependence.     

A dynamic model of training transfer

We expand our understanding of the training transfer process by developing the Dynamic Transfer Model (DTM). We develop and examine linkages between intentions to transfer, the initial attempts to utilize training, and the integration of feedback received from the transfer attempt. We propose that this process repeats itself over time in subsequent transfer attempts to impact work behavior and performance. Implications for transfer criteria, the dynamic interaction between the trainee and context, and the personalization of transfer are discussed. Based on the DTM, we suggest future research directions that can enrich our understanding of transfer as well as derive practical implications for improving training effectiveness.     

A component model for dynamic correlations

We propose a model of dynamic correlations with a short- and long-run component specification, by extending the idea of component models for volatility. We call this class of models DCC-MIDAS. The key ingredients are the Engle (2002) DCC model, the Engle and Lee (1999) component GARCH model replacing the original DCC dynamics with a component specification and the Engle et al. (2006) GARCH-MIDAS specification that allows us to extract a long-run correlation component via mixed data sampling. We provide a comprehensive econometric analysis of the new class of models, and provide extensive empirical evidence that supports the model’s specification.     

A bivariate count data model for household tourism demand

Households' choice of the number of leisure trips and the total number of overnight stays is empirically studied using Swedish tourism data. A bivariate hurdle approach separating the participation (to travel and stay the night or not) from the quantity (the number of trips and nights) decision is employed. The quantity decision is modelled with a bivariate mixed Poisson lognormal model allowing for both positive as well as negative correlation between count variables. The observed endogenous variables are drawn from a truncated density and estimation is pursued by simulated maximum likelihood. The estimation results indicate a negative correlation between the number of trips and nights. In most cases own price effects are as expected negative, while estimates of cross‐price effects vary between samples. Copyright © 2005 John Wiley & Sons, Ltd.     

A dynamic model of housing production

This paper derives the optimal development strategy for a housing producer with perfect foresight in a steady-state environment where dwellings deteriorate as they age. Under the assumption of zero demolition costs, the optimal strategy is an infinite sequence of identical buildings. Building abandonment is shown to be possible with positive demolition costs. A solution highlighting the model's spatial properties is computed using Cobb-Douglas functions.     

Applying a hidden Markov chain model in quality function deployment to analyze dynamic customer requirements

This study applies a hidden Markov chain model in quality function deployment to analyze dynamic customer requirements from probabilities viewpoints. In reality, the needed probabilities can be computed based upon the experts’ opinions for economic conditions as well as the customers’ surveys by asking customers’ preferences under different economic conditions. Each customer requirement can be analyzed as time goes by. In addition, the changes for each technical measure can be closely examined from time to time. More importantly, when new customers’ surveys are conducted and available as well as the new economic conditions analyzed by experts have been updated, both customer requirements and technical measures can be adjusted in a timely basis to reflect and fulfill the dynamic customer requirements. As a result, this proposed approach provides a decision maker to analyze and satisfy both past and present customer needs early on such that a better strategy can be made based upon the most updated customers’ surveys and economic conditions.     

The demand for computer services: A disaggregate decision model

Pricing schedules for computer resources have traditionally been based on ‘cost-recovery’ principles. While economists have begun to address pricing based on marginal congestion costs, most models take demand to be exogenous and given. Discrete alternatives are inadequately treated, and aggregation of data precludes any assessment of the impact of transaction size on consumers' decisions. Using disaggregated data, this paper derives empirical results confirming that consumers are strongly influenced by transaction sizes. Simulation experiments demonstrate that price incentives designed to modify the use of computer resources are considerably more effective if the distribution of demand is weighted towards large transactions.