The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
Income variance dynamics and heterogenity
Abstract
Recent theoretical work has shown the importance of measuring microeconomic uncertainty for models of both general and partial equilibrium under imperfect insurance. In this paper the assumption of i.i.d. income innovations used in previous empirical studies is removed and the focus of the analysis placed on models for the conditional variance of income shocks, that is related to the approporiate measure of risk emphasized by the theory. We first discriminate amongst various models of earnings determination that separate income shocks into idiosyncratic transitory and permanent components. We allow for education-specific differences in the stochastic process for earnings and for measurement error. The conditional variance of the income shocks is then modelled as a parsimonious autoregressive process with both observable and unobserved heterogeneity. The empirical analysis is conducted on data drawn from the 1967-1991 Panel Study of Income Dynamics.
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
Arellano, M., & Bond, S. (1991) · The Review of Economic Studies · doi:10.2307/2297968 · Cited by 33,272
Engle, R. F. (1982) · Econometrica · doi:10.2307/1912773 · Cited by 20,795
Initial conditions and moment restrictions in dynamic panel data models
Blundell, R., & Bond, S. (1995) · Working Paper Series · doi:10.1920/wp.ifs.1995.9517 · Cited by 14,755
Large Sample Properties of Generalized Method of Moments Estimators
Hansen, L. P. (1982) · Econometrica · doi:10.2307/1912775 · Cited by 13,467
Biases in dynamic models with fixed effects
Nickell, S. (1981) · Econometrica · doi:10.2307/1911408 · Cited by 8,735
Instrumental Variables Regression with Weak Instruments
Staiger, D., & Stock, J. (1994) · doi:10.3386/t0151 · Cited by 5,302 · cited 1×
“Windmeijer (2000) provides a small sample correction for the standard errors of two step GMM procedures, whose asymptotic approximation is known to be heavily biased.”
MethodEstimating Vector Autoregressions with Panel Data
Holtz-Eakin, D., Newey, W., & Rosen, H. S. (1988) · Econometrica · doi:10.2307/1913103 · Cited by 4,239
Bound, J., Jaeger, D. A., & Baker, R. M. (1995) · Journal of the American Statistical Association · doi:10.1080/01621459.1995.10476536 · Cited by 3,618
Wage Inequality and the Rise in Returns to Skill
Juhn, C., Murphy, K. M., & Pierce, B. (1993) · Journal of Political Economy · doi:10.1086/261881 · Cited by 2,799
U.S. Earnings Levels and Earnings Inequality: A Review of Recent Trends and Proposed Explanations
Murnane, R. J., & Levy, F. S. (1992) · Journal of Economic Literature · Cited by 1,397
Cited by
A simple panel unit root test in the presence of cross‐section dependence
Pesaran, M. H. (2007) · Journal of Applied Econometrics · doi:10.1002/jae.951 · Cited by 12,787
A Simple Panel Unit Root Test in the Presence of Cross Section Dependence
Pesaran, M. H. (2003) · SSRN Electronic Journal · doi:10.2139/ssrn.457280 · Cited by 1,310
The Consumption Response to Income Changes
Jappelli, T., & Pistaferri, L. (2010) · Annual Review of Economics · doi:10.1146/annurev.economics.050708.142933 · Cited by 704
Self-citationConsumption Inequality and Family Labor Supply
Blundell, R., Pistaferri, L., & Saporta-Eksten, I. (2016) · American Economic Review · doi:10.1257/aer.20121549 · Cited by 462
Self-citationHousehold Finance: An Emerging Field
Guiso, L., & Sodini, P. (2013) · Handbook of the Economics of Finance · doi:10.1016/b978-0-44-459406-8.00021-4 · Cited by 437
Metadata
- Authors
- Pistaferri, L., & Meghir, C.
- Venue
- Working Paper Series
- Publisher
- Institute for Fiscal Studies
- Published
- 2001-04-04
- ISSN
- 1369-4685 (ISSN-L)
- 1742-0415
- OpenAlex
- W3121391630
- Cited by
- 438
- References
- 37
- Type
- paratext
- 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: Income variance dynamics and heterogenity. https://app.cochat.ai/papers/10.1920/wp.ifs.2001.0107
- The paper
- Pistaferri, L., & Meghir, C. (2001). Income variance dynamics and heterogenity. Working Paper Series. https://doi.org/10.1920/wp.ifs.2001.0107
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.
