Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 667

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Causality Tests for Cross‐Country Panels: a New Look at FDI and Economic Growth in Developing Countries

Nair‐Reichert, Usha, Weinhold, Diana·2001·Oxford Bulletin of Economics and Statistics

Abstract

The remarkable increase in FDI flows to developing countries over the last decade has focused attention on whether this source of financing enhances overall economic growth. We use a mixed fixed and random (MFR) panel data estimation method to allow for cross country heterogeneity in the causal relationship between FDI and growth and contrast our findings with those from traditional approaches. We find that the relationship between investment, both foreign and domestic, and economic growth in developing countries is highly heterogeneous and that estimation methods which assume homogeneity across countries can yield misleading results. Our results suggest there is some evidence that the efficacy of FDI in raising future growth rates, although heterogeneous across countries, is higher in more open economies.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1111/1468-0084.00214

Cites

3 of 3 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 3 references

Cited by

See all 667

Metadata

Authors
Nair‐Reichert, U., & Weinhold, D.
Venue
Oxford Bulletin of Economics and Statistics
Publisher
Wiley
Published
2001-05
Volume
63
Issue
2
Pages
153-171
ISSN
  • 0305-9049 (ISSN-L)
  • 1468-0084
OpenAlex
W2135957862
Cited by
667
References
3
FWCI
49.11
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: Causality Tests for Cross‐Country Panels: a New Look at FDI and Economic Growth in Developing Countries. https://app.cochat.ai/papers/10.1111/1468-0084.00214
The paper
Nair‐Reichert, U., & Weinhold, D. (2001). Causality Tests for Cross‐Country Panels: a New Look at FDI and Economic Growth in Developing Countries. Oxford Bulletin of Economics and Statistics. https://doi.org/10.1111/1468-0084.00214

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.