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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, and participants at a seminar at the Fiscal Affairs Department of the International Monetary Fund. I also thank Rodica Blaja, Carolina Caro Correa, and Octavian Scerbatchi for assistance in data collection and management.
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, 2000; Fisman and Gatti, 2002; Martinez-Vasquez and McNab, 2006; Baskaran and Feld, 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; Zhang, 2006; 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.
The fiscal decentralization framework is being implemented on a pilot basis in 2014, with full implementation covering all SNGs planned from January 1, 2015.
While 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.
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 percent 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.
Implementing an idea originally proposed by Wooldridge (2002), Drukker (2003) developed an easy-to-use test for serial correlation in panel data based on the OLS residuals of the first-differenced model.
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.
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.
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).
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.