scholarly journals Federalism, Grants, and Fiscal Equalization

1999 ◽  
Vol 52 (2) ◽  
pp. 239-260
Author(s):  
Peter Mieszkowski ◽  
Richard A. Musgrave
Keyword(s):  
1994 ◽  
Vol 47 (1) ◽  
pp. 185-197 ◽  
Author(s):  
ANDREW RESCHOVSKY

2018 ◽  
Vol 67 (2) ◽  
pp. 189-218
Author(s):  
Thomas Brenner ◽  
Thomas Döring

Abstract Within the local fiscal equalization system of North Rhine-Westphalia, anticipated financial needs of municipalities are estimated by the use of regression analysis. In the recent past the previously exercised regression approach shows unexpected results concerning the main parameters determining intra-system allocation of general grants. Against this background the paper analyses the reasons for these parameter variations in order to identify an alternative approach to achieve regression results with higher accuracy and time stability both of which are of particular importance from a fiscal equalization policy perspective. It will be shown that the so-called robust regression is such an alternative method which leads – in case of its implementation – to divergent distributional effects compared to the status quo.


Studia BAS ◽  
2021 ◽  
Vol 1 (65) ◽  
pp. 21-41
Author(s):  
Elżbieta Malinowska-Misiąg ◽  
Wojciech Misiąg

The article deals with the problem of adjusting the revenues of Polish local government units (LGUs) to their tasks. The problem was analysed both from the point of view of the possibility of increasing LGU revenues and designing an effective system of fiscal equalization. The authors discussed the external factors which limit the possibilities of introducing such a desirable system. Next, based on the presented analysis, they drew conclusions regarding the necessary revision of the existing scheme. The article concludes with specific recommendations for a new system of financing LGUs, assuming, in particular, far-reaching changes in the algorithms for determining and dividing general subsidies, as well as a fundamental reduction in the scope of the so-called commissioned tasks.


Author(s):  
Kai Kaiser ◽  
Bert Hofman ◽  
Bambang Suharnoko Sjahrir ◽  
Keyword(s):  

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