Does political competition matter for public goods provision? Evidence from Russian regions Olga Vasilyeva Amur State University

Does political competition matter for public policies under conditions of unfair elections and autocracy?

Which mechanisms of government accountability give better results under conditions of suppressed political competition? –Formal vs informal

What does the literature tell? Topic 1: Political competition –Besley and Burgess (2002) –Careaga and Weingast (2001) –Acemoglu and Robinson (2006) –But implicit assumption about democracy! Topic 2: Efficiency of accountability mechanisms – formal vs informal –Sonin (2010) –Zhuravskaya and Persson (2011)

Stylized facts Stylized facts: Russian regions 90s- early 2000s Political monopoly of local elite: weak central government and political parties mid-2000s Transition from the monopoly of local elite to the monopoly of federal elite Late 2000s Political monopoly of the federal elite: strong central government and the ruling party- United Russia

Stylized facts Stylized facts: Russian regions the law regulating political parties activities –44 political parties (2003) –7 political parties (2009) the new elections law –majoritarian rule was replaced by a mixed-proportional rule or proportional rule (2007) 2005 replacement of governors elections by their appointments

Stylized facts Stylized facts: Russian regions Two kinds of political competition –Between local and federal elites –Between political parties – still weak at regional level !!! No platforms! Cares of private benefits only Two kinds of governors –New bureaucrats represent interests of national ruling party and federal elite –Old bureaucrats – have two contracts: Explicit with federal elite and national ruling party Implicit with local elite

Conceptual Framework A new governor An old governor

Conceptual Framework S0S0

Tested hypotheses

Hypotheses governors-new bureaucrats provide less public goods than old bureaucrats if the share of the ruling party is very small or very big governors- old bureaucrats provide less public goods than new bureaucrats if the share of the ruling party is not too small or big

Data and estimation strategy Unbalanced panel for 74 regions : 216 observations –Fixed effects for regions and years Linear specification Quadratic specification –SUR

Data Public goods provision Dependent variable: Public goods provision INPUTS -Education -Public spending per capita in region -Share of education in total public expenditures in region -Health care -Public spending per capita in region -Share of health care in total public expenditures in region Source of Data: Rosstat

Data Public goods provision Dependent variable: Public goods provision OUTCOMES -Infrastructure -share of paved roads -share of the paved roads with improved surface -density of paved roads -Health care -infant mortality rate -total mortality rate -Education -Score for Final state exam – not yet Source of Data: Rosstat

Data Public goods provision Dependent variable: Public goods provision OUTPUTS -Education -number of students per teacher -number of students per class -number of computers per 100 students -Health care -number of inhabitants per doctor -number of inhabitants per a bed in public hospitals Source of Data: Rosstat

BUT… Changing the share of spending on a public good might be due to increase of other kinds of spending Observations only for few years –It is hard to believe that mortality rate or quality of education might be affected by policies for 2- 3 years Outputs as well as outcomes might be determined not by regional policies but federal policies – in Russia public health care is financed by regional governments as well as federal government

Data Political variables Independent variables: Political variables Dummy for new bureaucrat/old bureaucrat Share of the ruling party among representatives elected by party list in regional legislature (S) –Logarithm of the Herfindahl–Hirschman Index (HHI) Linear interaction term between the dummy and the share of the ruling party –Linear interaction term between the dummy and HHI Quadratic interaction term between the dummy and the share of the ruling party –Linear interaction term between the dummy and HHI Source of Data: Central Election Commission of the Russian Federation, The Inter-Regional Electoral Network of Assistance in Russia

Political variables: Elections in regional legislatures The share of the ruling party The share of the ruling party: Mean 50% Max 92% (Tatarstan in ) Min 17% (Amur region in )

Political variables: Governors

Data Controls Independent variables: Controls –Log total budget spending per capita –Share federal budget transfers in regional budget –Household income per capita Source of Data: Rosstat –Governors characteristics Age Duration of keeping office Outsiders (non resident)/ insiders (resident) Politicians / businessmen Source of Data: collected by author

Governors characteristics

Specification Y it - measure of public goods provision S i(t-k) - share of the ruling party NG i(t-k) - dummy for governors-new bureaucrats X i(t-1) - set of control variables α i and ρ t - regions and year fixed effects The effect of governors –new bureaucrats is defined by:

Results: Quadratic specifications spending per capita onshare of spending on health care education health care education Dummy for a new governor 0.32 (1.59) -6.50* (3.61) 7.01** (3.12) 3.39 (2.35) Dummy for a new governor x share of the ruling party 1.57 (7.63) 43.03*** (17.28) (14.95) (11.26) Dummy for a new governor x share of the ruling party (7.42) *** (16.82) (14.55) (10.96) Time fixed effectyes Regional fixed effectyes Number of observations216

Results: Linear specifications spending per capita onshare of spending on health careeducationhealth careeducation Dummy for a new governor 1.39 (0.76) 3.40* (1.79) 3.54** (1.50) 1.24 (1.13) Dummy for a new governor x share of the ruling party -4.22*** (1.28) *** (3.00) -5.58** (2.52) -4.37** (1.89) Time fixed effectyes Regional fixed effectyes Number of observations216

Results: Quadratic specifications spending per capita onshare of spending on health care education health care education Dummy for a new governor 0.32 (1.59) -6.50* (3.61) 7.01** (3.12) 3.39 (2.35) Dummy for a new governor x share of the ruling party 1.57 (7.63) 43.03*** (17.28) (14.95) (11.26) Dummy for a new governor x share of the ruling party (7.42) *** (16.82) (14.55) (10.96) Time fixed effectyes Regional fixed effectyes Number of observations216 Max 41% 20% - 63%

Results: Outputs and outcomes total mortality rate share of the paved roads with improved surfaces students per class Dummy for a new governor 1.67*** (0.56) 1.80 (1.30) -2.06* (1.11) Dummy for a new governor x share of the ruling party -9.67*** (2.68) -6.21*** (2.19) 6.62*** (2.25) Dummy for a new governor x share of the ruling party *** (2.61) -- Time fixed effectyes Regional fixed effectyes Number of observations216

Results: Outputs and outcomes total mortality rate share of the paved roads with improved surfaces students per class Dummy for a new governor 1.67*** (0.56) 1.80 (1.30) -2.06* (1.11) Dummy for a new governor x share of the ruling party -9.67*** (2.68) -6.21*** (2.19) 6.62*** (2.25) Dummy for a new governor x share of the ruling party *** (2.61) -- Time fixed effectyes Regional fixed effectyes Number of observations216 Max 45 % 23% - 68%

Further work Reverse causality –IV approach a share of the ruling party in federal elections 2003, 2007 in a region; Putin/Medvedev share in Presidents election in 2004, 2008 Spending on infrastructure