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.     

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 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.     

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 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 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 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.     

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.     

Estimation of a dynamic multi-level factor model with possible long-range dependence

A dynamic multi-level factor model with possible stochastic time trends is proposed. In the model, long-range dependence and short memory dynamics are allowed in global and local common factors as well as model innovations. Estimation of global and local common factors is performed on the prewhitened series, for which the prewhitening parameter is estimated semiparametrically from the cross-sectional and local average of the observable series. Employing canonical correlation analysis and a sequential least-squares algorithm on the prewhitened series, the resulting multi-level factor estimates have centered asymptotic normal distributions under certain rate conditions depending on the bandwidth and cross-section size. Asymptotic results for common components are also established. The selection of the number of global and local factors is discussed. The methodology is shown to lead to good small-sample performance via Monte Carlo simulations. The method is then applied to the Nord Pool electricity market for the analysis of price comovements among different regions within the power grid. The global factor is identified to be the system price, and fractional cointegration relationships are found between local prices and the system price, motivating a long-run equilibrium relationship. Two forecasting exercises are then discussed.     

基于农产品需求供给的一个模型

我国农民收入过低是“三农”问题中一个突出的问题．需要从多方面进行探讨，可以通过建立农产品需求供给模型提供一种解决思路。它证明解决农民收入低的问题单靠名义收入量的增加不仅是行不通的，而且在某种条件下还会使农户家庭实际生活境况恶化。提高农民收入的一条途径是调整农产品与非农产品的价格比，促使农户家庭修正消费这两种产品的比例，从而改善农户家庭实际生活境况，达到更高的消费层次。     

Short-run labor productivity in a dynamic model

A classic empirical finding is that the short-run output elasticity of demand is smaller than unity and is less than in the long run. This phenomenon is called ‘short-run increasing returns to labor’ (SRIRL). In this paper we analyze SRIRL using a dynamic factor demand model for variable and quasi-fixed inputs, where the latter incur increasing marginal internal adjustment costs. Speeds of adjustment of quasi-fixed inputs are endogenous and variable, not constant parameters. Labor hoarding is shown to be neither necessary nor sufficient for SRIRL. These results are illustrated empirically using annual U.S. manufacturing data, 1952-71.     

The demand for deductibles in private health insurance: A probit model with sample selection

In this paper we analyse the decision to prefer a health insurance with a deductible to one with complete coverage. We focus on health, medical consumption, and on socio-economic characteristics like age, income, education and family size. The analysis is based on a sample of 8000 privately insured families; about 60 percent of them did not wish to have a health insurance policy with a deductible. A corrective method for sample selectivity, analogous to Heckman's (1979) method, has been applied in probit analysis; the estimation results are compared with the maximum-likelihood estimates. Health, medical consumption and income are found to have a significant influence on the decision with respect to the type of insurance. Our results give an indication of the degree of adverse selection that may take place if health insurance policies are offered with the option to take a deductible in exchange of a premium reduction.     

A simple dynamic decentralized leadership model with private savings and local borrowing regulation

This paper considers a simple dynamic decentralized leadership model with local borrowing and regional productivity-enhancing investment. In this model, the central government is benevolent but cannot commit to ex post intergovernmental transfer policies, while local governments act strategically after accounting for the ex post motives of the central government. We then investigate inefficiency in the subgame perfect equilibrium. We analyze the effect of central control on local borrowing and show that central control is of no benefit because ex ante local taxation works to offset it. We find the model yields different policy implications that central control is effective when extended to the case of residential mobility.     

A neural network demand system with heteroskedastic errors

In this paper we consider estimation of demand systems with flexible functional forms, allowing an error term with a general conditional heteroskedasticity function that depends on observed covariates, such as demographic variables. We propose a general model that can be estimated either by quasi-maximum likelihood (in the case of exogenous regressors) or generalized method of moments (GMM) if the covariates are endogenous. The specification proposed in the paper nests several demand functions in the literature and the results can be applied to the recently proposed Exact Affine Stone Index (EASI) demand system of [Lewbel, A., Pendakur, K., 2008. Tricks with Hicks: The EASI implicit Marshallian demand system for unobserved heterogeneity and flexible Engel curves. American Economic Review (in press)]. Furthermore, flexible nonlinear expenditure elasticities can be estimated.     

Identification of the dynamic shock-error model with autocorrelated errors

The paper gives (necessary and sufficient) conditions for the local identifiability of dynamic regression models with autocorrelated errors in the variables. The conditions are simple counting rules combining the order parameters of a model and directly generalize the results of Maravall and Aigner. A new method of identification is presented allowing a compact derivation of the results.