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.     

A comparison among partial adjustment,rational expectations and error correction estimates of the canadian demand for money

Starting from a dynamic optimization principle, the currently most popular approaches to modelling money demand functions are derived. The partial adjustment/adaptive expectations, rational expectations, and error correction mechanism formulations are then estimated using a common data set. The error correction mechanism equation is found to dominate the others either because their implicit restrictions are rejected (rational expectations) or by employing the encompassing principle (partial adjustment/adaptive expectations). Surprisingly all three forms have similar long-run solutions. Since the short-run dynamics differ substantially, the results have important implications for the conduct of monetary policy.     

Microeconometric evidence on the neoclassical model of demand

The Rotterdam demand model is fit to microeconomic data on households in Belgium. Prices vary over time and across consumers. The symmetry and homogeneity properties associated with demand functions for an individual are not rejected in these data.     

The demand for M3 in the euro area

In this paper, an empirically stable money demand model for M3 in the euro area is constructed. Starting with a multivariate system, three cointegrating relationships with economic content are found: (i) the spread between the long‐term and the short‐term nominal interest rates, (ii) the long‐term real interest rate, and (iii) a long‐run demand for broad money M3. There is evidence that the determinants of M3 money demand are weakly exogenous with respect to the long‐run parameters. Hence, following a general‐to‐specific modelling approach, a parsimonious conditional error‐correction model for M3 money demand is derived which can be interpreted economically. For the conditional model, long‐run and short‐run parameter stability is extensively tested and not rejected. Copyright © 2001 John Wiley & Sons, Ltd.     

The pattern of demand in the United States.

The objective of this paper is to examine the demand for goods and services in the United States using the Almost Ideal Demand System (AIDS). The focus is on testing the theoretical properties of demand. The model fits the data well. The suggestion is that food, clothing, housing and transportation are necessities while medical care and recreation are luxuries. The notion of homogeneity is generally accepted while symmetry is soundly rejected. Finally, negativity is shown to hold.     

Commodity and asset demands with and without quantity constraints in the labour market

This paper reformulates the consumer's decision-making problem in a temporary framework with and without quantity constraints in the labour market in such a way as to define a complete demand system which includes consumption, labour and saving. Then, based on American and Canadian data (1948–1980), this extended complete demand system is estimated using a priori theoretical properties. Quantity constraints in the labour market cannot be rejected, and marginal propensities to consume out of labour income are very different from the marginal propensities out of non-labour income. Temporal separability is rejected and Slutsky conditions are preserved.     

Semiparametric estimation of consumer demand systems in real expenditure

Microdata concerning consumer demand typically show considerable variation in real expenditures, but very little variation in prices. We propose a semiparametric strategy for the consumer demand problem in which expenditure share equations are estimated nonparametrically in the real expenditure direction and estimated parametrically (with fixed or varying coefficients) in price directions. In our model, Engel curves are unrestricted: demands may have any rank. Because the demand model is derived from a cost function, it may be restricted to satisfy integrability and used for consumer surplus calculations. Since real expenditure is unobserved, but rather estimated under the model, we face a semiparametric model with a nonparametrically generated regressor. We show efficient convergence rates for parametric and nonparametric components. We illustrate the feasibility of our proposed strategy using Canadian expenditure and price data: Engel curves display curvature which cannot be encompassed by standard parametric models. We also find that the rationality restriction of Slutsky symmetry is rejected in the fixed‐coefficients model, but not in the varying‐coefficients model. Copyright © 2009 John Wiley & Sons, Ltd.     

Estimating the LQAC model with I(2) variables

This paper derives a method for estimating and testing the Linear Quadratic Adjustment Cost (LQAC) model when the target variable and some of the forcing variables follow I(2) processes. Based on a forward-looking error-correction formulation of the model it is shown how to obtain strongly consistent estimates of the structural parameters from both a linear and a non-linear cointegrating regression where first-differences of the I(2) variables are included as regressors (multicointegration). Further, based on the estimated parameter values, it is shown how to test and evaluate the LQAC model using a VAR approach. A simple easy interpretable metric for measuring the model fit is suggested. In an empirical application using UK money demand data, the non-linear multicointegrating regression delivers an economically plausible estimate of the adjustment cost parameter. However, the restrictions implied by the exact LQAC model under rational expectations are strongly rejected and the metric for model fit indicates a substantial noise component in the model. Copyright © 1999 John Wiley & Sons, Ltd.     

A multi-stage stochastic programming approach for pre-positioning of relief supplies considering returns

A dynamic pre-positioning problem is proposed to efficiently respond to victims’ need for relief supplies under uncertain and dynamic demand in humanitarian relief. The problem is formulated as a multi-stage stochastic programming model that considers pre-positioning with the dynamic procurement and return decisions about relief supplies over a time horizon. To validate the advantages of dynamic pre-positioning, three additional pre-positioning strategies are presented: pre-positioning with one-time procurement and without returns, pre-positioning with one-time procurement and returns, and pre-positioning with dynamic procurement and without returns. Using data from real-world disasters in the United States in the Emergency Events Database, we present a numerical analysis to study the applicability of the proposed models. We develop a sample average approximation approach to solving the proposed model in large-scale cases. Our main contribution is that we integrate dynamic procurement and return strategies into pre-positioning to decrease both costs and shortage risks in uncertain and dynamic contexts. The results illustrate that dynamic pre-positioning outperforms the other three strategies in cost savings. It also indicates that a higher return price is particularly helpful for decreasing unmet demand. The proposed models can help relief agencies evaluate and choose the solutions that will have the greatest overall effectiveness in the context of different relief practices.     

Econometric Analysisof Collusive Behaviorin a Soft-Drink Market

This paper proposes an empirical methodology for studying various (implicit or explicit) collusive behaviors on two strategic variables, which are price and advertising, in a differentiated market dominated by a duopoly. In addition to Nash or Stackelberg behaviors, we consider collusion on both variables, collusion on one variable and competition on the other, etc. Using data on the Coca-Cola and Pepsi-Cola markets from 1968 to 1986, full information maximum likelihood estimation of cost and demand functions are obtained allowing for various collusive behaviors. The collusive hypothesis is not rejected, and the best form of collusive behavior is selected via nonnested testing procedures. Using the best model, Lerner indices are computed for both duopolists to provide summary measures of market power. Finally, our approach is contrasted with the conjectural variation approach and is shown to give superior results.     

The empirical determination of technology and expectations: A simplified procedure

This paper makes three principal contributions to the growing body of empirically oriented research on dynamic factor demand systems that are based on the adjustment cost model of the firm. First, a simplified procedure is described for deriving demand and supply functions which are amenable to empirical estimation and which are consistent with intertemporal expected profit maximization and a general expectations formation process for future prices. Second, it is pointed out that estimation of a complete system of demand and supply functions permits the empirical identification of both the firm's technology and its expectations formation process. Finally, the procedure is applied to aggregate annual U.S. manufacturing data for the 1947-1977 period and the consistency of the data with the theoretical framework is investigated.     

Models of regional growth: An empirical evaluation

Cross section data are used to test two types of regional growth models: the demand and the supply based models. While the demand based model explained twice as much of the interregional variations in growth rates as did the supply model, we found that the basic element of the supply model, factor mobility, contributes significantly to the determination of regional growth. A model combining both demand and supply is developed and fitted tothe data. The performance of this model as judged by goodness of fit and dynamic simulations is remarkable. Long-run implications are derived from dynamic simulations.     

Metonymy and cross-section demand

Cross-section consumer expenditure data are frequently used to draw conclusions about consumer demand behavior. Such conclusions, however, are justified only under certain assumptions, which are often left unstated in the empirical demand literature. An assumption of this type, the metonymy hypothesis, was stated rigorously and exploited by Härdle et al. when analyzing the monotonicity of aggregate demand functions. The purpose of the present paper is to examine the metonymy hypothesis in more detail. We prove that the distribution of demand vectors derived from a not necessarily metonymic population is identical with the distribution derived from some metonymic population. This implies, in particular, that the metonymy hypothesis cannot be rejected or confirmed on the basis of data from a single cross-section.     

Parametric and semi-parametric estimation of the binary response model of labour market participation

This paper compares the familiar probit model with three semiparametric estimators of binary response models in an application to labour market participation of married women. This exercise is performed using two different cross-section data sets from Switzerland and Germany. For the Swiss data the probit specification cannot be rejected and the models yield similar results. In the German case the probit model is rejected, but the coefficient estimates do not vary substantially across the models. The predicted choice probabilities, however, differ systematically for a subset of the sample. The results of this paper indicate that more work is necessary on specification tests of semiparametric models and on simulations using these models.     

Demand and supply estimation biases due to omission of durability

We build a dynamic equilibrium model of a durable goods oligopoly with a competitive secondary market to evaluate the bias in estimating the structural parameters of demand and supply when durability is omitted. We simulate data from our dynamic model and use them to estimate the model’s static counterpart. We find that the static estimate of the elasticity of demand is an overestimate of the true elasticity and that the static estimate of the markup is an underestimate. Our results provide a benchmark on the magnitude and sign of the bias when static models are used for economic inference.     

Monitoring structural change in dynamic econometric models

The classical approach to testing for structural change employs retrospective tests using a historical data set of a given length. Here we consider a wide array of fluctuation‐type tests in a monitoring situation—given a history period for which a regression relationship is known to be stable, we test whether incoming data are consistent with the previously established relationship. Procedures based on estimates of the regression coefficients are extended in three directions: we introduce (a) procedures based on OLS residuals, (b) rescaled statistics and (c) alternative asymptotic boundaries. Compared to the existing tests our extensions offer ease of computation, improved size in finite samples for dynamic models and better power against certain alternatives, respectively. We apply our methods to three data sets, German M1 money demand, US labour productivity and S&P 500 stock returns. Copyright © 2005 John Wiley & Sons, Ltd.     

Utilization of ambulatory care studies: testing the assumptions

A linear regression procedure is usually used to estimate the effect of a set of predictors on utilization of ambulatory health care. The implicit assumptions embedded in the linear regression model have never been examined. Here, with utilization data of a sample of 48292 patients from the file of the Québec National Health Plan, four implicit hypotheses embedded in the linear regression model are tested: (1) the transition from the state of utilization to the state of no utilization, and vice-versa, depends on the level of the transition rates, (2) the effect of independent variables depends on the transitions being predicted from or to the state of utilization, (3) the transition is time dependent, and (4) the system of transitions from one state to another is not at equilibrium. The analysis shows that the first three hypotheses cannot be rejected. Thus, the use of the familiar linear regression procedure in this study to estimate the effect of a set of factors on utilization would have yielded biased estimates.     

Exact tests in single equation autoregressive distributed lag models

For hypotheses on the coefficient values of the lagged-dependent variables in the ARX class of dynamic regression models, test procedures are developed which yield exact inference for given (up to an unknown scale factor) distribution of the innovation errors. They include exact tests on the maximum lag length, for structural change and on the presence of (seasonal or multiple) unit roots, i.e. they cover situations where usually asymptotic and non-exact t, F, AOC, ADF or HEGY tests are employed. The various procedures are demonstrated and compared in illustrative empirical models and the approach is critically discussed.     

Testing for homogeneity in demand systems when the regressors are nonstationary

An implication of optimizing theory is that demand functions are homogeneous of degree zero in prices and nominal income. Evidence based on estimations of demand systems has repeatedly found this restriction to be rejected by the data. However, the hypothesis is often formulated in terms of regressors that are non-stationary. This paper re-examines the evidence for homogeneity in light of recent developments in time-series econometrics with special emphasis on the treatment of trends. We find the demand system to be stochastically but not deterministically cointegrated. Using techniques developed for estimating cointegrating vectors in the presence of deterministic trends, we re-estimate the demand system and find that homogeneity holds in many cases.     

The dynamic Laurent flexible form and the demand for money

I derive the dynamic full Laurent model to estimate economic models that assume a dynamic process. The application in this paper is to use the dynamic full Laurent to estimate a system of dynamic asset demand equations. The main results are that the dynamic full Laurent rejects its static version and the estimated elasticities are variable over time. Results from a Monte Carlo analysis, using a dynamic data-generating process, show that the prediction errors from the dynamic full Laurent are much smaller than those from the static version. Thus when the data are generated by a dynamic process, inferences from the static full Laurent model can be severely biased. © 1997 John Wiley & Sons, Ltd.