Nonparametric Engel Curves and Revealed Preference

This paper applies revealed preference theory to the nonparametric statistical analysis of consumer demand. It exploits the idea that price-taking individual households in the same market face the same relative prices, in order to smooth across the demands of individuals for each common price regime. This is shown to provide a stochastic structure within which to examine the consistency of household level data and revealed preference theory. An application is made to a long time series of repeated cross-sections from the 1974-1993 UK Family Expenditure Surveys. The consistency of this data with revealed preference theory is examined. Where rejections do occur, suitable adjustments to prices for quality or taste changes are explored. For periods of consistency with revealed preference bounds are placed on true cost of living indices.consumer demands; nonparametric regression; revealed preference

Best Nonparametric Bounds on Demand Responses

This paper uses revealed preference inequalities to provide tight nonparametric bounds on consumer responses to price changes. Price responses are allowed to vary nonparametrically across the income distribution by exploiting micro data on consumer expenditures and incomes over a finite set of discrete relative price changes. This is achieved by combining the theory of revealed preference with the semiparametric estimation of consumer expansion paths (Engel curves). We label these expansion path based bounds as E-bounds. Deviations from revealed preference restrictions are measured by preference perturbations which are shown to usefully characterise taste change.demand responses; relative prices; revealed preference; semiparametric regression; changing tastes

Revealed preference analysis of characteristics models

Characteristics models have been found to be useful in many areas of economics. However, their empirical implementation tends to rely heavily on functional form assumptions. In this paper we develop a revealed preference approach to characteristics models. We derive the necessary and sufficient empirical conditions under which data on the market behaviour of heterogeneous, price-taking consumers are nonparametrically consistent with the consumer characteristics model. Where these conditions hold, we show how information may be recovered on individual consumer’s marginal valuations of product attributes. In some cases marginal valuations are point identified and in other cases we can only recover bounds. Where the conditions fail we highlight the role which the introduction of unobserved product attributes can play in rationalising the data. We implement these ideas using consumer panel data on the Danish milk market.Product characteristics, revealed preference

Nonparametric methods for the characteristic model

Characteristics models have been found to be useful in many areas of economics. However, their empirical implementation tends to rely heavily on functional form assumptions. In this paper we develop a revealed preference-based nonparametric approach to characteristics models. We derive the minimal necessary and sufficient empirical conditions under which data on the market behaviour of individual, heterogeneous, pricetaking consumers are nonparametrically consistent with the consumer characteristics model. Where these conditions hold, we show how information may be recovered on individual consumer's marginal valuations of product attributes. In some cases marginal valuations are point identi- fied and in other cases we can only recover bounds. Where the conditions fail we highlight the role which the introduction of unobserved product attributes can play in rationalising the data. We implement these ideas using consumer panel data on the Danish milk market.Product characteristics, revealed preference

The age-period cohort problem: set identification and point identification

"Only entropy comes easily" - Anton Chekhov Various methods have been used to overcome the point identification problem inherent in the linear age-period-cohort model. This paper presents a set-identification result for the model and then considers the use of the maximum-entropy principle as a vehicle for achieving point identification. We present two substantive applications (US female mortality data and UK female labor force participation) and compare the results from our approach to some of the solutions in the literature.

Revealed preference analysis of characteristics models

Characteristics models have been found to be useful in many areas of economics. However, their empirical implementation tends to rely heavily on functional form assumptions. In this paper we develop a revealed preference approach to characteristics models. We derive the necessary and sufficient empirical conditions under which data on the market behaviour of heterogeneous, price-taking consumers are nonparametrically consistent with the consumer characteristics model. Where these conditions hold, we show how information may be recovered on individual consumer's marginal valuations of product attributes. In some cases marginal valuations are point identified and in other cases we can only recover bounds. Where the conditions fail we highlight the role which the introduction of unobserved product attributes can play in rationalising the data. We implement these ideas using consumer panel data on the Danish milk market.product characteristics; revealed preference

Best nonparametric bounds on demand responses

This paper uses revealed preference inequalities to provide tight nonparametric bounds on consumer responses to price changes. Price responses are allowed to vary nonparametrically across the income distribution by exploiting microdata on consumer expenditures and incomes over a finite set of discrete relative price changes. This is achieved by combining the theory of revealed preference with the semiparametric estimation of consumer expansion paths (Engel curves). We label these expansion path based bounds as E-bounds. Deviations from revealed preference restrictions aremeasured by preference perturbations which are shown to usefully characterise taste change.Demand responses, relative prices, revealed preference, semiparametric regression, changing tastes

A nonparametric characteristics model of the demand for milk

Characteristics models in demand analysis capture the idea that people value goods not For the commodity itself but for the characteristics (or attributes) or embodied in the good. For example, agents may care about the fat content and the taste of different sorts of milk but not the actual type of milk. When we have fewer characteristics than types of good the theory imposes restrictions on observables. We present a revealed preference characteristics model analysis of the demand for milk in Denmark

Insider Threat Detection on the Windows Operating System using Virtual Machine Introspection

Existing insider threat defensive technologies focus on monitoring network traffic or events generated by activities on a user\u27s workstation. This research develops a methodology for signaling potentially malicious insider behavior using virtual machine introspection (VMI). VMI provides a novel means to detect potential malicious insiders because the introspection tools remain transparent and inaccessible to the guest and are extremely difficult to subvert. This research develops a four step methodology for development and validation of malicious insider threat alerting using VMI. Six core use cases are developed along with eighteen supporting scenarios. A malicious attacker taxonomy is used to decompose each scenario to aid identification of observables for monitoring for potentially malicious actions. The effectiveness of the identified observables is validated through the use of two data sets, one containing simulated normal and malicious insider user behavior and the second from a computer network operations exercise. Compiled Memory Analysis Tool - Virtual (CMAT-V) and Xen hypervisor capabilities are leveraged to perform VMI and insider threat detection. Results of the research show the developed methodology is effective in detecting all defined malicious insider scenarios used in this research on Windows guests

Two adaptation processes in auditory hair cells together can provide an active amplifier

The hair cells of the vertebrate inner ear convert mechanical stimuli to electrical signals. Two adaptation mechanisms are known to modify the ionic current flowing through the transduction channels of the hair bundles: a rapid process involves calcium ions binding to the channels; and a slower adaptation is associated with the movement of myosin motors. We present a mathematical model of the hair cell which demonstrates that the combination of these two mechanisms can produce `self-tuned critical oscillations', i.e. maintain the hair bundle at the threshold of an oscillatory instability. The characteristic frequency depends on the geometry of the bundle and on the calcium dynamics, but is independent of channel kinetics. Poised on the verge of vibrating, the hair bundle acts as an active amplifier. However, if the hair cell is sufficiently perturbed, other dynamical regimes can occur. These include slow relaxation oscillations which resemble the hair bundle motion observed in some experimental preparations.Comment: 13 pages, 6 figures,REVTeX 4, To appear in Biophysical Journa