Abstract
Using a novel municipality-level panel dataset, this paper investigates the empirical characteristics of vertical fiscal imbalances (VFIs) in Moldova over the period 2005–2013. The results show that the extent of variation in VFIs across 898 municipalities can be explained by the level of per capita income, fiscal capacity, and demographic characteristics, as well as the central government’s fiscal behavior that reflects fiscal constraints and policy preferences at the national level. Political affiliation does not appear to be a significant factor, but the results show lower VFIs when the mayor of a municipality belongs to the same party ruling the central government. Altogether, these findings underscore the need for well-coordinated reforms to create economies of scale, enhance revenue collection, and improve the composition of spending at the subnational level.
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Notes
Quantifying the economic impact of fiscal decentralization is beyond the scope of this paper, but cross-country studies have found mixed evidence (see, for example, Davoodi and Zou 1998; Treisman 2003; Fisman and Gatti 2002; Martinez-Vazquez and McNab 2006; Baskaran 2009). This may partly be because of incomparable measures of decentralization across countries (Treisman 2003), as well as structural and institutional conditions that affect the potential effectiveness of fiscal decentralization (De Mello 2000; King and Ma 2001; Neyapti 2010; Tanzi 2008; Kyriacou and Sagales 2009).
There is no unambiguous definition of VFI, but the literature usually measures it as a mismatch between expenditure responsibilities and own-source revenues at the subnational level. Sharma (2012) provides an overview of the literature on VFIs.
Transnistria is a breakaway region of Moldova that has not been recognized internationally as an independent state, whereas Gagauzia has a special legal status with its own governor and local parliament.
World Bank (2014) provides a comprehensive overview of public finance functions of local governments in Moldova.
World Bank (2014) provides a detailed analysis of Moldova’s system of intergovernmental fiscal transfers for general and special purposes.
The estimation results do not change when I exclude shared revenues in calculating the VFI.
It should be noted that although these VFI measures gauge the degree to which SNGs rely on central government transfers, they do not distinguish what proportion of central government transfers is conditional (specific) versus general purpose. Furthermore, data constraints prevent the construction of VFI measures as a share of SNG’s own spending excluding expenditures mandated by the central government.
A negative value for central government transfers is a result of reverse transfers to the central government by SNGs that have revenues in excess of 20 % of per capita expenditure. Out of 898 municipalities, only three municipalities—Chisinau, Codru and Vatra—had reverse transfers during the sample period.
The unit root test results are available upon request.
Instead of contemporaneous observations, the lagged values of CGBAL are used in the estimations to avoid the problem of endogeneity.
Since the standard estimations may be sensitive to outliers, I also estimate the models excluding observations that are greater than the 97.5 percentile or less than the 2.5 percentile of the distribution. Omitting outliers, however, does not lead to major changes in the estimation results in terms of size and statistical significance.
Since panel data tend to have complex error structures and the standard estimation techniques do not explicitly take care of temporally and spatially correlated errors, static models may yield inefficient coefficient estimates with biased standard errors. The Wooldridge (2002) and Drukker (2003) test indeed detects the presence of first-order serial correlation in the panel data used in this analysis. I estimate static models using the fixed effects and random effects models with AR(1) disturbances as developed by Baltagi and Wu (1999), as well as a Prais–Winsten regression with panel-corrected standard errors (PCSE), as suggested by Beck and Katz (1995). The findings based on the static models, presented in Appendix Table 3, are broadly in line with the baseline estimation results using dynamic modeling.
To avoid the problem of instrument proliferation in the GMM estimations, I follow the best practice and use the minimal number of instruments by collapsing the instrument set as suggested by Roodman (2009). The goodness-of-fit statistics for the static models are satisfactory; the diagnostics of the system GMM estimations reject the presence of serial correlation and confirm the validity of the set of instruments used in the analysis.
Ideally, a municipality’s actual own-source revenues should be compared to the predicted value of its revenue potential (capacity) using a regression-based approach. Due to the lack of municipality-level data on tax base and rates, I proxy a municipality’s revenue effort with the ratio of its per capita own-source revenues relative to the average level of per capita own-source revenues across all municipalities.
The baseline estimation results do not materially change when the lagged central government budget balance is excluded from the regressions to avoid any endogeneity concern.
I also estimate the models including the squared term of population to test if population has a non-linear threshold effect on the VFI. The results are not robust, but indicate an inverted U-shaped relationship, with a positive coefficient on population and a negative coefficient on its square term.
Administrative-territorial rationalization is not just a matter of economic considerations. There are political and social considerations. In this context, the fiscal decentralization strategy can provide incentives for voluntary amalgamation and greater cooperation among SNGs by adjusting the transfer formulas according to the population size.
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Acknowledgments
This paper benefited from helpful comments and suggestions by Max Alier, Mark De Broeck, Luc Eyraud, Armine Khachatryan, Koralai Kirabaeva, Jorge Martinez-Vazquez, Ivohasina Razafimahefa, Andrey Timofeev, participants at a seminar at the Fiscal Affairs Department of the International Monetary Fund (IMF), and two anonymous referees. The author would also like to thank Rodica Blaja, Carolina Caro Correa, and Octavian Scerbatchi for assistance in data collection and management. The views expressed herein are those of the authors and should not be attributed to the IMF, its executive Board, or its management.
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Cevik, S. Size matters: fragmentation and vertical fiscal imbalances in Moldova. Empirica 44, 367–381 (2017). https://doi.org/10.1007/s10663-016-9325-7
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DOI: https://doi.org/10.1007/s10663-016-9325-7