The Power of Nonparametric Tests of Preference Maximization

Bronars, Stephen G.

doi:10.2307/1913608

Cited by 245 publications

(219 citation statements)

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“…Our revealed preference tests are quite powerful according to Bronars' (1987) test (for a detailed discussion of various measures of the power of revealed preferences tests see Andreoni and Harbaugh (2005)). Ex-ante, our experiment offers many opportunities to display an inconsistent behavior.…”

Section: Dictators' Rationalitymentioning

confidence: 99%

Impure altruism in dictators' giving

Korenok

Millner

Razzolini

2013

Journal of Public Economics

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Abstract:We design an experiment to test whether incomplete crowding out in dictator games can be rationalized by the impurely altruistic preferences. By giving the recipients an endowment of varying levels, we create an environment in which crowding out may occur. We find that the behavior of 66 percent of the dictators can be rationalized by the impurely altruistic utility function.Keywords: Dictator Game, Impure Altruism, Incomplete Crowding Out JEL Classifications: C91, D01, D64, H30, H41 * We would like to thank Asen Ivanov for patience and many helpful comments and insights. We would also like to thank Rachel Croson, Doug Davis, Catherine

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Section: Dictators' Rationalitymentioning

confidence: 99%

Impure altruism in dictators' giving

Korenok

Millner

Razzolini

2013

Journal of Public Economics

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“…For example, as the weak separability model is nested within the standard utility maximization model, the former model will have a lower pass rate than the latter model by construction. Indeed, Bronars (1987) and, more recently, Andreoni and Harbaugh (2008) and Beatty and Crawford (2011) -rather convincingly-argue that revealed preference test results (indicating pass or fail of the data for some behavioral condition) should be complemented with power measures to obtain a fair empirical assessment of the rationalizability conditions under evaluation. Here, power is measured as the probability of rejecting the revealed preference test given that the model does not hold.…”

Section: Comparing Alternative Behavioral Modelsmentioning

confidence: 99%

“…is measure quanti es discriminatory power in terms of the probability to detect random behavior, and is based on Bronars (1987). More precisely, we simulated 1000 random series of eight consumption choices by drawing, for each of the eight observed household budgets, a random quantity bundle from a uniform distribution on the given budget hyperplane for the corresponding prices and total expenditure.…”

Section: Comparing Alternative Behavioral Modelsmentioning

confidence: 99%

Revealed preference tests for weak separability: An integer programming approach

Cherchye

Demuynck

Rock

et al. 2015

Journal of Econometrics

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We focus on the revealed preference conditions that characterize the collection of nite data sets that are consistent with the maximization of a weakly separable utility function. From a theoretical perspective, we show that verifying these revealed preference conditions is a difficult problem, i.e. it is np-complete. From a practical perspective, we present an integer programming approach that can verify the revealed preference conditions in a straightforward way, which is particularly attractive in view of empirical analysis. We demonstrate the versatility of this integer programming approach by showing that it also allows for testing homothetic separability and weak separability of the indirect utility function. We illustrate the practical usefulness of the approach by an empirical application to Spanish household consumption data. In this application we also include two statistical tests in which we account for measurement error. JEL Classi cation: C14, C60, D01, D10.Keywords: weak separability, revealed preference, integer programming * We thank Ian Crawford for generously providing us the data of the Encuesta Continua de Presupestos Familiares (ECPF), which we use in our empirical study. We are also grateful to Adrian Fleissig, James Swofford and Gerald Whitney for helpful comments. is paper is a merger of two working papers, Cherchye, Demuynck, and De Rock (2011c) and Hjertstrand (2011

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“…Typically, in a revealed preference setting, we specify the measure F i as the probability law that randomly samples datasetss i = {p i t ,q i t } t∈T whereq i t is obtained by a uniform draw from the hyperplane {q ∈ R n + |p i t q = p i t q i t }. This is analogue to the way that the Bronars (1987) power is computed.…”

Section: Illustrationmentioning

confidence: 99%

“…This measure of predictive success is frequently used experimental studies 2 and has recently been advocated for use with revealed preference tests by Beatty and Crawford (2011). 3 In revealed preference studies, the area is usually quantified as one minus the Bronars (1987) power, which gives the probability that a randomly generated datasets (obtained from a uniform distribution on the budget hyperplanes) will fail the revealed preference test.…”

Section: Introductionmentioning

confidence: 99%

Statistical inference for measures of predictive success

Demuynck

2015

Theory Decis

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We provide statistical inference for measures of predictive success. These measures are frequently used to evaluate and compare the performance of different models of individual and group decision making in experimental and revealed preference studies. We provide a brief illustration of our findings by comparing the predictive success of different revealed preference tests for models of intertemporal decision making. This demonstrates that it is possible to compare the predictive success of different models in a statistically meaningful way.

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The Power of Nonparametric Tests of Preference Maximization

Cited by 245 publications

References 2 publications

Impure altruism in dictators' giving

Impure altruism in dictators' giving

Revealed preference tests for weak separability: An integer programming approach

Statistical inference for measures of predictive success

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