The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A Cross-Country, Cross-Industry Comparison of Productivity Growth
Abstract
This paper presents evidence on the nature of productivity growth for five major industries in six countries. Output growth is found to be more correlated across countries than productivity growth. In addition, productivity growth is more correlated across industries within one country than across countries within one industry. Using an error-components model, I find that a substantial fraction of changes in annual productivity can be attributed to nation-specific factors that are common across industries. The evidence suggests that short-run productivity growth is similar across industries in a nation but less similar across countries in any specific industry.
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
Technical Change and the Aggregate Production Function
Solow, R. M. (1957) · The Review of Economics and Statistics · doi:10.2307/1926047 · Cited by 12,259
Cited by
Easterly, W. (2001) · The World Bank Economic Review · doi:10.1093/wber/15.2.177 · Cited by 1,443
International Risk Sharing and the Transmission of Productivity Shocks
CORSETTI, G., DEDOLA, L., & LEDUC, S. (2008) · Review of Economic Studies · doi:10.1111/j.1467-937x.2008.00475.x · Cited by 648
The tourism–economy causality in the United States: A sub-industry level examination
Tang, C.-H. (., & Jang, S. (. (2009) · Tourism Management · doi:10.1016/j.tourman.2008.09.009 · Cited by 254
Finance and Efficiency: Do Bank Branching Regulations Matter?
Acharya, V. V., Imbs, J., & Sturgess, J. (2011) · Review of Finance · doi:10.1093/rof/rfq009 · Cited by 58
Metadata
- Authors
- Costello, D. M.
- Venue
- Journal of Political Economy
- Publisher
- University of Chicago Press
- Published
- 1993-04
- Volume
- 101
- Issue
- 2
- Pages
- 207-222
- ISSN
- 0022-3808 (ISSN-L)
- 1537-534X
- OpenAlex
- W2054459676
- Cited by
- 175
- References
- 1
- FWCI
- 20.03
- 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: A Cross-Country, Cross-Industry Comparison of Productivity Growth. https://app.cochat.ai/papers/10.1086/261873
- The paper
- Costello, D. M. (1993). A Cross-Country, Cross-Industry Comparison of Productivity Growth. Journal of Political Economy. https://doi.org/10.1086/261873
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.
