PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
April 22, 20260 citationsOpen Access

Vertical Fiscal Imbalance, Transfer Dependence, and Sub-National Soft Budget Constraints: Bi-Directional Lessons From Nigeria and Malaysia

View Full Paper
OIOmokhagbo Mike ImafidorUJUdanga Agom JarigbeQUQUADRI FARUQ UMAR

Key Points

  • This analysis examines the relationship between vertical fiscal imbalance and transfer dependence in Nigeria and Malaysia, focusing on subnational borrowing.
  • Systematic comparative analysis of subnational fiscal data from Nigeria and Malaysia.
  • Application of System Generalized Method of Moments (System-GMM) to control for endogeneity.
  • Structural decomposition of fiscal imbalances into distinct components.
  • In Nigeria, a 10% increase in transfer dependence raises deficit-to-GDP ratios by 1.84%, compared to 0.92% in Malaysia.
  • Despite differences in fiscal outcomes, both countries show similar vulnerabilities to fiscal stress.
  • Identified risks in Malaysia could lead to fiscal crises similar to Nigeria's under adverse conditions.

Abstract

Abstract Vertical fiscal imbalance (VFI), which is the structural gap between subnational governments' assigned expenditure responsibilities and their own-revenue capacity is a defining feature of federal fiscal architecture in both Nigeria and Malaysia. When subnational governments depend overwhelmingly on intergovernmental transfers rather than own revenues, the soft budget constraint (SBC) problem emerges: lower tiers of government borrow excessively or overspend in the expectation of central government bailouts, because they bear only a fraction of the political cost of their fiscal decisions. This paper provides the first systematic bidirectional comparative analysis of VFI, transfer dependence, and subnational borrowing dynamics in Nigeria and Malaysia. Using subnational panel data for Nigeria's 36 states and the Federal Capital Territory (2000–2023) and Malaysia's 13 states (2000–2022), we employ System Generalized Method of Moments (System-GMM) estimation to identify the causal effect of VFI and transfer dependence on subnational fiscal deficits and debt accumulation, controlling for endogeneity through appropriate instrument selection. We complement the GMM analysis with a structural decomposition of subnational fiscal imbalances into transfer-driven, own-revenue-driven, and expenditure-driven components, enabling us to isolate the specific channels through which VFI translates into fiscal stress. Our findings reveal a striking paradox: Nigeria's extreme VFI (states depend on federal transfers for an average of 84% of revenue) has produced visible subnational debt crises, while Malaysia's more moderate but structurally similar VFI (states depend on federal transfers for an average of 68% of revenue) has not yet produced a crisis — but exhibits the same underlying vulnerability. System-GMM estimates show that a ten-percentage-point increase in transfer dependence raises subnational deficit-to-GDP ratios by 1.84 percentage points in Nigeria and 0.92 percentage points in Malaysia — a difference explained primarily by Malaysia's stronger borrowing approval controls and political accountability mechanisms, not by fundamentally different fiscal structures. Critically, we identify three latent risks in Malaysia's subnational fiscal architecture — Sabah and Sarawak's negotiated transfer arrangements, the declining own-revenue capacity of Peninsular states, and the growth of contingent liabilities through state-owned enterprises — that, if unaddressed, could generate Nigerian-style fiscal stress under an adverse revenue shock. We derive specific reform recommendations for both countries that are grounded in the comparative evidence. JEL Classification: H71, H72, H74, H77, E62, O23, R51

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Imafidor et al. (2026) studied this question.

synapsesocial.com/papers/69e867356e0dea528ddeb800https://doi.org/10.5281/zenodo.19663082
Ask AI
Helpful
Bookmark
Share
View Full Paper