arbiter
JournalsAccount

Inefficiency unveiled: a Bayesian DSGE analysis of public investment in China

Juha Tervala & Timothy Watson

Macroeconomic Dynamics2026https://doi.org/10.1017/s1365100525100795article
AJG 2ABDC A
Weight
0.50

Abstract

This study utilizes a Bayesian Dynamic Stochastic General Equilibrium model, calibrated with Chinese data, to assess the impact of public investments, which account for about 16.2% of China’s GDP. Despite an expected public capital stock of 256% of GDP, based on a 4.6% depreciation rate and a 0.73 efficiency rate of public investment (emerging-economy estimate), the actual figure stands at 152%. This significant discrepancy underscores the inefficiencies in public investments, with 43% of public investment expenditures enhancing the capital stock. The output elasticity (productivity) of public capital is estimated at just 3%, substantially lower than the previously estimated 8% for emerging economies, and has declined to 2% in the post-2008 period. Simulations based on these efficiency and productivity metrics reveal that the output multiplier of public investment is 0.7. China’s public investments reduce TFP, crowd out private investment, and raise the public debt-to-GDP ratio in the medium term.

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.1017/s1365100525100795

Or copy a formatted citation

@article{juha2026,
  title        = {{Inefficiency unveiled: a Bayesian DSGE analysis of public investment in China}},
  author       = {Juha Tervala & Timothy Watson},
  journal      = {Macroeconomic Dynamics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1017/s1365100525100795},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Inefficiency unveiled: a Bayesian DSGE analysis of public investment in China

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.