Nonparametric Demand Analysis Research Articles

Revealed Preference Analysis with Normal Goods: Application to Cost-of-Living Indices

We present a revealed preference methodology for nonparametric demand analysis under the assumption of normal goods. Our methodology is flexible in that it allows for imposing normality on any subset of goods. We show the usefulness of our methodology for empirical welfare analysis through cost-of-living indices. An illustration to US consumption data drawn from the Panel Study of Income Dynamics (PSID) demonstrates that mild normality assumptions can substantially strengthen the empirical analysis. It obtains considerably tighter bounds on cost-of-living indices and a significantly more informative classification of better-off and worse-off individuals after the 2008 financial crisis. (JEL D11, D12, E31, G01)

To the Problem of Constructing Analytical Indexes of Market Demand: A Variative Approach

The article develops methods for constructing economic (analytical) indexes in the framework of the holistic theory of market demand, built in recent years. By this, the economic indexes presented in the world literature within the framework of the theory of individual demand and, accordingly, related to households, acquire practical value.The introduction provides a brief overview of the main problems of modern indexology and the implementation of an economic approach dating back to the classical work of 1924 by the Soviet statistician A.A. Konüs. The properties of the most well-known «formula» indexes of Laspeyres, Paasche, and Fischer with respect to the fulfillment of the Fisher test criteria are described. These indexes play an important role in the methods proposed by the authors for constructing analytical indexes, which are determined through the function of consumer expenditures. The latter is determined by a utility function that rationalizes trade statistics. The rationalizing utility function is constructed ambiguously, and the corresponding task should be specified. Methods for its solution are proposed, developed within a non-parametric demand analysis of Afriat-Varian. The core of this analysis is the system of linear Afriat’s inequalities that determine the values of the utility function and marginal utility corresponding to statistical demand. This system can be inconsistent and unstable with respect to variations of non-exact demand statistics. In the case of compatibility, inequalities have many solutions, and the choice of different solutions of inequalities gives different values of analytical indexes. The authors suggest three types of tasks for the stable solution of Afriat’s inequalities, which define indexes with characteristics of optimism (low price indexes and high quantity indexes), pessimism (vice versa) and objectivity.Therefore, the problem of increasing the objectivity of consumer demand indexes receives a theoretically justified toolbox methods for calculating analytical market demand indexes that take into account, in contrast to formula indices, consumer preferences.

Revealed Preference Analysis With Normal Goods: Application to Cost of Living Indices

We present a revealed preference methodology for nonparametric demand analysis under the assumption of normal goods. Our methodology is flexible in that it allows for imposing normality on any subset of goods. We show the usefulness of our methodology for empirical welfare analysis through cost of living indices. An illustration to US consumption data drawn from the Panel Study of Income Dynamics (PSID) demonstrates that mild normality assumptions can substantially strengthen the empirical analysis. It obtains considerably tighter bounds on cost of living indices, and a significantly more informative classification of better-off and worse-off individuals after the 2008 financial crisis.

Моделирование рыночного потребительского спроса и анали тические индексы спроса

The paper describes the essence of crisis state of the neoclassical theory of consumer demand and a way to overcome the crisis based on the concept of statistical «assembly» of consumers as an origin of the theory of aggregate market demand. Market demand is modeled via utility maximization problem elaborated in frame of the neoclassical paradigm for an individual consumer. The nonparametric demand analysis is used for testing the adequacy of such a model to the trade statistics. Analytical index numbers of consumers' demand and their variants, invariant and quasi-invariant indices, are presented. The use of nonparametric demand analysis is based on real trade statistics of food products in the Russian Federation, and the quasi-invariant indices are constructed.

Nonparametric Demand Analysis of U.K. Personal Sector Decisions on Consumption, Leisure, and Monetary Assets: A Reappraisal

This paper utilizes a new data set to test for utility maximizing behavior and weakly separable subutility functions in the context of a utility function comprising durables, nondurables, services, leisure, and monetary asset holdings for the U.K. personal sector. All the data sets analyzed demonstrated consistency with respect to utility maximizing behavior. The weak separability results prove to be relatively invariant to the degree of aggregation over goods but highly sensitive to the assump-tion made regarding the representative consumer. Per-household scaling of the data produced a utility function that is weakly separable in goods, services and leisure, and in monetary assets.

PERSONAL SECTOR MONEY DEMAND IN THE UK

Nonparametric demand analysis is utilized to establish weakly separable subsets of monetary assets for the U.K. personal sector in the context of a utility function consisting of durable and nondurable consumption goods, services, leisure, and monetary assets. The admissible collections of assets are then combined using Divisia aggregation in order to produce monetary aggregates that are consistent with economic aggregation theory. The authors investigate the money demand properties of the aggregates and find relatively simple, stable long-run money-demand functions for the U.K. personal sector with well determined error correction dynamics. Copyright 1997 by Royal Economic Society.

Relative Prices in the UK Personal Sector Money Demand Function

Nonparametric demand analysis is used in order to establish admissible monetary aggregates and also to establish a potential role for relative prices in the money demand function. A conventional money demand specification is then contrasted with a money demand function which contains the relative prices of durables, nondurables, and services as additional regressors. Evidence from long-run cointegration analysis, short-run error correction models, and nonnested testing all confirm a role for relative prices in the U.K. personal sector's money demand function. Copyright 1996 by Royal Economic Society.

The power of non-parametric demand analysis when applied to British meat and fish consumption data

It is possible to estimate the power of non-parametric demand analysis when applied to a particular data set using the budget hyperplanes and alternative definitions of irrational behaviour. The paper has two objectives: to identify the number of drawings needed, and to calculate the power statistic, under four alternative irrationality models, for five British meat and fish data sets that have been used elsewhere for parametric and non-parametric analysis. The mean and variance of the estimated power statistics indicate that at least 1000 drawings have to be made if an accurate figure for the power statistic is to be obtained. This is larger than that used in earlier work. The estimated power statistics also throw some light on earlier empirical results obtained using these data sets. Copyright 1994 by Oxford University Press.

Efficiency of Weighted Average Derivative Estimators and Index Models

Weighted average derivatives are useful parameters for semiparametric index models and nonparametric demand analysis. This paper gives efficiency results for average derivative estimators, including formulating estimators that have high efficiency. Our analysis is carried out in three steps. First, we derive the efficiency bound for weighted average derivatives of conditional location functionals, such as the conditional mean and median. Second, we derive the efficiency bound for semiparametric index models, where the location measure depends only on indices, or linear combinations of the regressors. Third, we compare the bound for index models with the asymptotic variance of weighted average derivative estimators of the index coefficients. We characterize the form of the optimal weight function when the distribution of the regressors is elliptically symmetric. In more general cases, we discuss how to combine estimators with different weight functions to achieve efficiency. We derive a general condition for approximate efficiency of pooled (minimum chi square) estimators for index model coefficients, based on weighted average derivatives. Finally, we discuss ways of selecting the type and number of weighting functions to achieve high efficiency.

Accounting for Changes in Tastes

Health concerns are thought by many to have shifted consumption away from red meats, though econometric evidence is mixed. Testing for structural change is difficult, especially when one time series is used for both estimating demand equations and testing their stability. Specification errors may suggest a shift where none has occurred. Using nonparametric demand analysis, we find that meat consumption patterns in the United States and Australia can be explained using only relative prices and expenditures. Only imposing particular functional forms can reverse the conclusion, suggesting that specification errors in econometric demand studies can account for findings of taste changes.

The Changing Empirical Definition of Money: Some Estimates from a Model of the Demand for Money Substitutes

Interest-bearing checkable deposits are examined to test whether they should be included in measures of the U.S. money stock. Both Divisia and traditional simple-sum aggregates are constructed on the basis of tests for weak separability in a model of the demand for financial assets. Using nonparametric demand analysis, we find that several groups of assets are compatible with aggregation theory. We find empirical support for a narrow measure consisting of the components of current MIA. In tests based on a St. Louis equation and in terms of controllability, a Divisia aggregate performs better than the simple-sum MIA measure.