The 26th NISPAcee Annual Conference

Conference photos available

Conference photos available

In the conference participated 317 participants

Conference programme published

Almost 250 conference participants from 36 countries participated

Conference Report

The 28th NISPAcee Annual Conference cancelled

The 29th NISPAcee Annual Conference, Ljubljana, Slovenia, October 21 - October 23, 2021

The 2020 NISPAcee On-line Conference

The 30th NISPAcee Annual Conference, Bucharest, Romania, June 2 - June 4, 2022

An opportunity to learn from other researchers and other countries' experiences on certain topics.

G.A.C., Hungary, 25th Conference 2017, Kazan

Very well organised, excellent programme and fruitful discussions.

M.M.S., Slovakia, 25th Conference 2017, Kazan

The NISPAcee conference remains a very interesting conference.

M.D.V., Netherlands, 25th Conference 2017, Kazan

Thank you for the opportunity to be there, and for the work of the organisers.

D.Z., Hungary, 24th Conference 2016, Zagreb

Well organized, as always. Excellent conference topic and paper selection.

M.S., Serbia, 23rd Conference 2015, Georgia

Perfect conference. Well organised. Very informative.

M.deV., Netherlands, 22nd Conference 2014, Hungary

Excellent conference. Congratulations!

S. C., United States, 20th Conference 2012, Republic of Macedonia

Thanks for organising the pre-conference activity. I benefited significantly!

R. U., Uzbekistan, 19th Conference, Varna 2011

Each information I got, was received perfectly in time!

L. S., Latvia, 21st Conference 2013, Serbia

The Conference was very academically fruitful!

M. K., Republic of Macedonia, 20th Conference 2012, Republic of Macedonia

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 Paper/Speech Details of Conference Program  

for the  26th NISPAcee Annual Conference
  Program Overview
V. Public Finance and Management
Author(s)  Pawel Swianiewicz 
  Wroclaw University of Enviornmental and Life Sciences
Wroclaw  Poland
Kalcheva Desislava, Kurniewicz Anna,  
 
 Title  Political Business Cycle in Policies of Tariffs for Local Public Services: Comparison of Poland and Bulgaria
File   Paper files are available only for conference participants, please login first. 
Presenter  Pawel Swianiewicz
Abstract  
  
The concept of political cycle was formulated in relation to decision making of governments and parliaments on a national level. But starting from the end of 1980s there has been also studies using that theoretical frame in order to study local financial decision making (Mouritzen 1989, Balis and Nadeau 1992, Rosenberg 1992). Most of those empirical studies focused on public expenditures (studying relationship between their size and electoral cycle), but later there has been also studies investigating local tax policies.

So far the concept has been very rarely used in studies focusing on countries of Central and Eastern Europe. There are no available studies of this phenomenon in Bulgaria. In Poland Herczyński and Sobotka (2013) noted the impact of electoral cycle on decisions related to changes in rural school network. Swianiewicz (2011) noted the relationship with local budget operating surplus, which indirectly suggested higher expenditures in years of local elections. But Łukomska and Swianiewicz (2015) found no impact on tax policies.

We argue that in Central and Eastern Europe the meaning of local taxes is relatively limited, since local budgets are to a large extent based on shares in taxes which rates are determined on a central level and transfers from central government. In Poland that share of autonomous taxes in local budget revenues is just above 20%, and in Bulgaria it is ca. 17%. In several other countries of the region the relevant share is even lower. Consequently, tax policies are not a very hot issue in local politics. That is why in our paper we apply the political cycle concept to policies related to tariffs for local public services. The importance of fees and charges for family budgets is significantly higher than of local taxes.

The first research question is: can we find traces of political business cycle in policies related to tariffs? The second research question concerns factor increasing (or decreasing) likelihood of political cycle – why political cycle is more likely to be found in some local governments, but not in others? We expect that the relevant explanatory factors might include:
- Affluence of local communities (measured by per capita own budget revenues)
- Population size of local government
- Intensity of electoral competition (measured by: margin of victory in mayoral election preceding the relevant term in office)

Both research questions in Poland are empirically tested against fees for water provision and in Bulgaria against fees for waste collection. Formally speaking tariffs for water provision in Poland are calculated on the basis of actual costs. Similarly the level of fee for waste collection in Bulgaria should be related to actual costs of service delivery. In both cases the process looks very technocratic, leaving not much space for political decisions. But we argue that practice often deviates from that normative picture. First, some elements of costs calculation may be subject of political negotiations. Second, in situation where city holds majority of shares of the water company, the mayor has a power of informal influence on the shape of the tariff calculation to be submitted by the company to the local council.

We concentrate on mid-size and large cities. In Poland the test is conducted for 104 cities over 30,000 population, which are county capitals. In Bulgaria our data base includes 71 municipalities with population size over 20,000. Bulgarian data cover 2005-2016 period (3 full electoral cycles) and Polish data 2009-2017 (2 full electoral cycles).
The difficult methodological problem is how to distinguish between the impact of electoral cycle from the impact of other factors, such as inflation or changes in economic situation of local governments related i.e. to economic growth rate. Our empirical strategy is to control those potential explanatory variables through multivariate panel regression models.