The DOI matches its Crossref record.
Measuring the Upstreamness of Production and Trade Flows
Open accessAbstract
We propose two distinct approaches to the measurement of industry upstreamness (or average distance from final use) and show that they yield an equivalent measure. Furthermore, we provide two additional interpretations of this measure, one of them related to the concept of forward linkages. We construct this measure for 426 industries using the 2002 US input-output Tables. We also construct our measure using data from selected countries in the OECD STAN database. Finally, we present an application of our measure that explores the determinants of the average upstreamness of exports at the country level using trade flows for 2002.
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
Cited by
Fajgelbaum, P. D., Goldberg, P. K., Kennedy, P. J., & Khandelwal, A. K. (2020) · The Quarterly Journal of Economics · doi:10.1093/qje/qjz036 · Cited by 1,030
Conceptual Aspects of Global Value Chains
Antràs, P. (2020) · The World Bank Economic Review · doi:10.1093/wber/lhaa006 · Cited by 538
Self-citationHOW GLOBAL ARE GLOBAL VALUE CHAINS? A NEW APPROACH TO MEASURE INTERNATIONAL FRAGMENTATION
Los, B., Timmer, M. P., & de Vries, G. J. (2015) · Journal of Regional Science · doi:10.1111/jors.12121 · Cited by 498
From Micro to Macro via Production Networks
Carvalho, V. M. (2014) · Journal of Economic Perspectives · doi:10.1257/jep.28.4.23 · Cited by 468
Internalizing Global Value Chains: A Firm-Level Analysis
Alfaro, L., Antràs, P., Chor, D., & Conconi, P. (2019) · Journal of Political Economy · doi:10.1086/700935 · Cited by 282
Self-citation
Metadata
- Authors
- Antràs, P., Chor, D., Fally, T., & Hillberry, R.
- Venue
- American Economic Review
- Publisher
- American Economic Association
- Published
- 2012-05-01
- Volume
- 102
- Issue
- 3
- Pages
- 412-416
- ISSN
- 0002-8282 (ISSN-L)
- OpenAlex
- W3125207107
- Cited by
- 864
- References
- 0
- FWCI
- 52.55
- Type
- journal article
- Language
- en
- Open access
- green
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: Measuring the Upstreamness of Production and Trade Flows. https://app.cochat.ai/papers/10.1257/aer.102.3.412
- The paper
- Antràs, P., Chor, D., Fally, T., & Hillberry, R. (2012). Measuring the Upstreamness of Production and Trade Flows. American Economic Review. https://doi.org/10.1257/aer.102.3.412
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.
