City objectives and monopoly franchising. An empirical analysis of - - PowerPoint PPT Presentation

City objectives and monopoly franchising. An empirical analysis of calls for tenders in Italian gas distribution

Riccardo Marzano

Infraday 2010 – 8/9 October

Outline

• Introduction
• Gas distribution in Italy
• Background
• Data and variables
• The model
• Results
• Conclusions

2

Introduction

• Aims of the paper
• Objectives pursued by Italian municipalities in franchising the gas

distribution service

• Testing the taxation by regulation effect (Posner, 1971-1972)
• Empirical analysis on a sample of 174 calls for tenders

(2001-2008 period)

• Empirical methodology:
• Linear simultaneous equations model
• 3SLS estimation

3

Gas distribution in Italy (1/2)

• Legislative Decree n. 164/2000 (Letta’s Decree)
• compulsory competitive bidding procedures in selecting utility

management units, designed by local governments, which are entrusted with functions of programming and control

• definition of an upper bound to the franchise duration (12 years)
• price (tariffs) regulation entrusted to the AEEG, the Italian energy

regulator

• property of infrastructures going back to the local authority at the

end of the franchising term

4

Gas distribution in Italy (2/2)

• “Most economically advantageous tender” approach
• Scoring rules
• Example

Three dimensional scoring (Scores A B C)

Upper bound on score A = 50 Ai = [bidi(A)/bidmax(A)]*50 Upper bound on score B = 30 Bi = [bidi(B)/bidmax(B)]*30 Upper bound on score C = 20 Ci = [bidi(C)/bidmax(C)]*20

Total Scorei = Ai + Bi + Ci

5

 Upper bounds on the scores  Formulas to compute each score

Background

• Monopoly franchising
• Seminal idea: Demsetz (1968)
• Critics on competitive franchising arrangement
• Transaction costs: Williamson (1976), Goldberg (1976)
• Taxation by regulation: Posner (1771-1972), Prager (1989), Beutel

(1990), Otsuka & Braun (2002)

• Scoring Auctions
• Theoretical analyses: Asker & Cantillon (2008-2010)

6

Data and variables (1/2)

7

• Sample
• 174 calls for tenders spanning from 2001 to 2008

Region 2001 2002 2003 2004 2005 2006 2007 2008 Tot

Abruzzi 3 6 1 1 11 Aosta V. 1 1 Apulia 2 2 Basilicata 3 2 1 2 8 Calabria 1 1 1 3 Campani a 1 5 2 3 1 1 2 15 Emilia R. 1 1 Friuli V.G. 1 1 Lazio 1 4 2 1 1 1 10 Liguria 2 2 Lombardy 4 6 6 15 7 7 11 56 Marche 1 1 2 Molise 2 1 1 4 Piedmont 1 3 1 1 1 1 8 Sardinia 1 2 13 16 Sicily 2 2 2 1 7 Tuscany 1 1 2 Veneto 1 4 4 5 6 5 25

Total

1 6 26 26 37 20 22 36 174

Data and variables (2/2)

• Score variables
• Fee (upper bound on franchise fee score)
• Trans (upper bound on terms for infrastructure transfer score)
• Prices (upper bound on prices score)
• Infra (upper bound on new infrastructure asset score)
• Serv (upper bound on service quality and organization score)
• City characteristics variables
• FinAut (Financial Autonomy)
• Debt (Level of obligations)
• Liq (Liquidity indicator)
• qProceeds (Quality of proceeds)
• Turnover (Political turnover indicator)
• Exp (Experience of bureaucrats)
• Size (size of the city)
• S (Localization dummy)
• Poverty (Poverty indicator)
• PubNet (Public network)
• Constr (Construction dummy)

8

The model

9

• Linear simultaneous equations model:

5 57 56 55 5 5 1 5 50 5 4 47 46 45 42 41 5 4 1 4 40 4 3 37 36 35 31 5 3 1 3 30 3 2 27 26 25 24 23 22 21 5 2 1 2 20 2 1 17 16 15 14 13 12 11 5 1 1 1 10 1

ln ln ln ln ln ln ln ln Pr ln ln u Size Exp Turnover Sc Sc u Size Exp Turnover S Constr Sc Sc u Size Exp Turnover Poverty Sc Sc u Size Exp Turnover PubNet Liq Debt Constr Sc Sc u Size Exp Turnover

• ceeds

q Liq Debt FinAut Sc Sc

i i i i i i i i i i i i i i i i i i i i

                                        

    

         

                                   

10 (eq by eq IV) (3SLS) Debt

• 77.6800

1654.10** (-0.06) (2.00) Liq

• 4.70100

100.400** (-0.06) (2.00) FinAut

• 0.64200

13.630** (-0.06) (1.98) qProceeds 0.00130

• 0.03140*

(0.03) (-1.87) Exp 0.84200

• 17.2500*

(0.06) (-1.95) Turnover

• 1.49600

31.1200** (-0.06) (2.08) Size

• 0.00024

0.00495** (-0.06) (2.04)

Results – First equation only (Franchise fee)

Note: standard errors in parentheses. ***, ** and * indicate, respectively, significance levels of <1%, <5% and <10%.

Conclusions

• Weak evidence for taxation by regulation effect
• No

evidence about some

• ther

aspects influencing competitive procedure designing

• Difficulties in capturing other relevant aspects because of

no availability of data

11

Thank you for your attention!

12