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Book part
Publication date: 23 July 2007

Per Hjertstrand

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Functional Structure Inference
Type: Book
ISBN: 978-0-44453-061-5

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Book part
Publication date: 2 November 2009

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Measurement Error: Consequences, Applications and Solutions
Type: Book
ISBN: 978-1-84855-902-8

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Book part
Publication date: 2 November 2009

Per Hjertstrand

Weak separability is an important concept in many fields of economic theory. This chapter uses Monte Carlo experiments to investigate the performance of newly developed…

Abstract

Weak separability is an important concept in many fields of economic theory. This chapter uses Monte Carlo experiments to investigate the performance of newly developed nonparametric revealed preference tests for weak separability. A main finding is that the bias of the sequentially implemented test for weak separability proposed by Fleissig and Whitney (2003) is low. The theoretically unbiased Swofford and Whitney test (1994) is found to perform better than all sequentially implemented test procedures but is found to suffer from an empirical bias, most likely because of the complexity in executing the test procedure. As a further source of information, we also perform sensitivity analyses on the nonparametric revealed preference tests. It is found that the Fleissig and Whitney test seems to be sensitive to measurement errors in the data.

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Measurement Error: Consequences, Applications and Solutions
Type: Book
ISBN: 978-1-84855-902-8

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Book part
Publication date: 2 November 2009

Abstract

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Measurement Error: Consequences, Applications and Solutions
Type: Book
ISBN: 978-1-84855-902-8

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Book part
Publication date: 2 November 2009

Barry E. Jones and David L. Edgerton

Revealed preference axioms provide a simple way of testing data from consumers or firms for consistency with optimizing behavior. The resulting non-parametric tests are…

Abstract

Revealed preference axioms provide a simple way of testing data from consumers or firms for consistency with optimizing behavior. The resulting non-parametric tests are very attractive, since they do not require any ad hoc functional form assumptions. A weakness of such tests, however, is that they are non-stochastic. In this paper, we provide a detailed analysis of two non-parametric approaches that can be used to derive statistical tests for utility maximization, which account for random measurement errors in the observed data. These same approaches can also be used to derive tests for separability of the utility function.

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Measurement Error: Consequences, Applications and Solutions
Type: Book
ISBN: 978-1-84855-902-8

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Book part
Publication date: 2 November 2009

Abstract

Details

Measurement Error: Consequences, Applications and Solutions
Type: Book
ISBN: 978-1-84855-902-8

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Book part
Publication date: 2 November 2009

Abstract

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Measurement Error: Consequences, Applications and Solutions
Type: Book
ISBN: 978-1-84855-902-8

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Book part
Publication date: 2 November 2009

Adrian R. Fleissig and Gerald A. Whitney

A new nonparametric procedure is developed to evaluate the significance of violations of weak separability. The procedure correctly detects weak separability with high…

Abstract

A new nonparametric procedure is developed to evaluate the significance of violations of weak separability. The procedure correctly detects weak separability with high probability using simulated data that have violations of weak separability caused by adding measurement error. Results are not very sensitive when the amount of measurement error is miss-specified by the researcher. The methodology also correctly rejects weak separability for nonseparable simulated data. We fail to reject weak separability for a monetary and consumption data set that has violations of revealed preference, which suggests that measurement error may be the source of the observed violations.

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Measurement Error: Consequences, Applications and Solutions
Type: Book
ISBN: 978-1-84855-902-8

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Book part
Publication date: 2 November 2009

Vincent A. Schmidt and Jane M. Binner

This chapter introduces a mechanism for generating a series of rules that characterize the money-price relationship for the United States, defined as the relationship…

Abstract

This chapter introduces a mechanism for generating a series of rules that characterize the money-price relationship for the United States, defined as the relationship between the rate of growth of the money supply and inflation. Monetary Services Indicator (MSI) component data is used to train a selection of candidate feedforward neural networks. The selected network is mined for rules, expressed in human-readable and machine-executable form. The rule and network accuracy are compared, and expert commentary is made on the readability and reliability of the extracted rule set. The ultimate goal of this research is to produce rules that meaningfully and accurately describe inflation in terms of the MSI component dataset.11Paper cleared for public release AFRL/WS–07–0848.

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Measurement Error: Consequences, Applications and Solutions
Type: Book
ISBN: 978-1-84855-902-8

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Book part
Publication date: 2 November 2009

Logan J. Kelly

In this chapter, I will examine the problems created by incorrectly using a simple sum monetary aggregate (SSUM) to measure the monetary stock. Specifically, I will show…

Abstract

In this chapter, I will examine the problems created by incorrectly using a simple sum monetary aggregate (SSUM) to measure the monetary stock. Specifically, I will show that SSUM confounds the current stock of money (CSM) with the investment stock of money (ISM) and that this confounding leads the SSUM to report an artificially smooth monetary stock. This smoothing causes important information about the dynamic movements of the monetary stock to be lost. This may offer at least a partial explanation of why so many studies find that money has little economic relevance. To that end, we will conclude the chapter by examining a reduced form backward looking IS equation to determine whether monetary aggregates contain information about real GDP gap. This chapter differs from previous work in monetary aggregation in that it focuses on smoothing of the monetary stock data caused by the use of simple sum methodology, where the previous work focuses on the bias exhibited by SSUMs.

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Measurement Error: Consequences, Applications and Solutions
Type: Book
ISBN: 978-1-84855-902-8

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