Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 678

The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.

Career concerns and multitasking local bureaucrats: Evidence of a target-based performance evaluation system in China

Chen, Yvonne Jie, Li, Pei, Lu, Yi·2018·Journal of Development Economics

Abstract

This paper examines whether a target-based performance evaluation system can properly motivate local bureaucrats to implement an environmental regulation policy at the cost of slow economic growth. In late 2005, the Chinese central government made cutting sulfur dioxide (SO2) emissions the main performance evaluation criterion for prefectural city mayors and Party secretaries. Using a difference-in-differences framework, we find that the performance evaluation system caused a significant decrease in SO2 emissions, as well as in the GDP growth rate. Our mechanism analyses further corroborate that local bureaucrats in Two Control Zone cities were willing to trade off GDP growth to achieve the more stringent emissions reductions goal. Our findings contribute to the understanding of multitasking agency problems for government agents.

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 · 10.1016/j.jdeveco.2018.02.001

Cites

43 of 43 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 43 references

Metadata

Authors
Chen, Y. J., Li, P., & Lu, Y.
Venue
Journal of Development Economics
Publisher
Elsevier BV
Published
2018-07
Volume
133
Pages
84-101
ISSN
0304-3878 (ISSN-L)
OpenAlex
W2793759314
Cited by
678
References
43
FWCI
41.75
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: Career concerns and multitasking local bureaucrats: Evidence of a target-based performance evaluation system in China. https://app.cochat.ai/papers/10.1016/j.jdeveco.2018.02.001
The paper
Chen, Y. J., Li, P., & Lu, Y. (2018). Career concerns and multitasking local bureaucrats: Evidence of a target-based performance evaluation system in China. Journal of Development Economics. https://doi.org/10.1016/j.jdeveco.2018.02.001

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.