The DOI matches its Crossref record; 50 of the 50 references it cites were found in a registry or an index.
Nonparametric Engel Curves and Revealed Preference
Abstract
This paper applies revealed preference theory to the nonparametric statistical analysis of\nconsumer demand. Knowledge of expansion paths is shown to improve the power of nonparametric\ntests of revealed preference. The tightest bounds on indifference surfaces and\nwelfare measures are derived using an algorithm for which revealed preference conditions\nare shown to guarantee convergence. Nonparametric Engel curves are used to estimate\nexpansion paths and provide a stochastic structure within which to examine the consistency\nof household level data and revealed preference theory. An application is made to a long\ntime series of repeated cross-sections from the Family Expenditure Survey for Britain. The\nconsistency of these data with revealed preference theory is examined. For periods of consistency\nwith revealed preference, tight bounds are placed on true cost of living indices.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Density Estimation for Statistics and Data Analysis
Silverman, B. W. (2018) · Routledge eBooks · doi:10.1201/9781315140919 · Cited by 15,796
Deaton, A. (1980) · Oxford University Research Archive (ORA) (University of Oxford) · Cited by 4,258
Applied nonparametric regression
(1991) · Choice Reviews Online · doi:10.5860/choice.29-0364 · Cited by 2,580
Root-N-Consistent Semiparametric Regression
Robinson, P. M. (1988) · Econometrica · doi:10.2307/1912705 · Cited by 2,475
Applied Nonparametric Regression
Härdle, W. (1990) · Cambridge University Press eBooks · doi:10.1017/ccol0521382483 · Cited by 2,457
Exact and superlative index numbers
Diewert, W. E. (1976) · Journal of Econometrics · doi:10.1016/0304-4076(76)90009-9 · Cited by 2,170
Quadratic Engel Curves and Consumer Demand
Banks, J., Blundell, R., & Lewbel, A. (1997) · Review of Economics and Statistics · doi:10.1162/003465397557015 · Cited by 1,794
Self-citation(2009) · American Economic Review · doi:10.1257/aer.99.1.i · Cited by 1,712
Design-adaptive Nonparametric Regression
Fan, J. (1992) · Journal of the American Statistical Association · doi:10.1080/01621459.1992.10476255 · Cited by 1,268
Irrational Behavior and Economic Theory
Becker, G. S. (1962) · Journal of Political Economy · doi:10.1086/258584 · Cited by 1,156
Cited by
Quadratic Engel Curves and Consumer Demand
Banks, J., Blundell, R., & Lewbel, A. (1997) · Review of Economics and Statistics · doi:10.1162/003465397557015 · Cited by 1,794
Self-citationEfficient Estimation of Models with Conditional Moment Restrictions Containing Unknown Functions
Ai, C., & Chen, X. (2003) · Econometrica · doi:10.1111/1468-0262.00470 · Cited by 726
Estimation of semiparametric models when the criterion function is not smooth
Chen, X., Linton, O., & Van Keilegom, I. (2003) · Econometrica · doi:10.1111/1468-0262.00461 · Cited by 411
Endogeneity in nonparametric and semiparametric regression models
Powell, J. L., & Blundell, R. (2001) · Working Paper Series · doi:10.1920/wp.cem.2001.0901 · Cited by 362
Self-citationChoi, S., Kariv, S., Müller, W., & Silverman, D. (2014) · American Economic Review · doi:10.1257/aer.104.6.1518 · Cited by 277
Metadata
- Authors
- Blundell, R. W., Browning, M., & Crawford, I. A.
- Venue
- Econometrica
- Publisher
- The Econometric Society
- Published
- 2003-01
- Volume
- 71
- Issue
- 1
- Pages
- 205-240
- ISSN
- 0012-9682 (ISSN-L)
- 1468-0262
- OpenAlex
- W2099125273
- Cited by
- 263
- References
- 50
- FWCI
- 26.25
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Nonparametric Engel Curves and Revealed Preference. https://app.cochat.ai/papers/10.1111/1468-0262.00394
- The paper
- Blundell, R. W., Browning, M., & Crawford, I. A. (2003). Nonparametric Engel Curves and Revealed Preference. Econometrica. https://doi.org/10.1111/1468-0262.00394
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.