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Nonparametric Engel curves and revealed preference

机译:非参数恩格尔曲线和揭示的偏好

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摘要

This paper applies revealed preference theory to the nonparametric statistical analysis of consumer demand. Knowledge of expansion paths is shown to improve the power of nonparametric tests of revealed preference. The tightest bounds on indifference surfaces and welfare measures are derived using an algorithm for which revealed preference conditions are shown to guarantee convergence. Nonparametric Engel curves are used to estimate expansion paths and 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 Family Expenditure Survey for Britain. The consistency of these data with revealed preference theory is examined. For periods of consistency with revealed preference, tight bounds are placed on true cost of living indices.
机译:本文将揭示偏好理论应用于消费者需求的非参数统计分析。扩展路径的知识被证明可以提高显示偏好的非参数测试的能力。冷漠表面和福利测度上的最严格界限是使用一种算法得出的,该算法显示了揭示的偏好条件以确保收敛。非参数恩格尔曲线用于估计扩张路径,并提供一种随机结构,用于检验家庭水平数据和揭示的偏好理论的一致性。英国家庭支出调查对较长时间的重复截面系列进行了应用。这些数据与揭示的偏好理论的一致性得到了检验。在具有显示出的偏好的一致性期间,对真实生活成本指数设置严格的界限。

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