the reform of the energy industries, privatisation and consumers' welfare: evidence ... ·...

The reform of the energy industries, privatisation andconsumers’ welfare: evidence from the EU15

Carlo Fiorio & Massimo FlorioUniversity of Milan

http://www.economia.unimi.it

Fiorio & Florio (University of Milan) Reforms of the energy industries 1 / 44

Introduction

In the 1970s several nationalised SGEI in Europe were underbudgetary stress, and widely perceived as inefficient.

The UK, in the mid 1980s, was the front-runner of reform, while,among the EU member states, France was often regarded as acountry adverse to move away from public monopoly.

In fact, in the last 15-20 years virtually all the European countrieshave adopted dramatic regulatory reforms in the network industries.

Wide variations around a common policy trend, however, can be,observed across countries and sectors.

We focus on a simple and straightforward research question: “Doconsumers benefit from the reform of network industries as it hasbeen designed and implemented in the EU?”


The typical EU reform

A typical ’European-style’ reform package has four maindimensions:

divestiture of public ownership;unbundling of the network from service operations;price regulation by an independent office (usually in the form of pricecapping);lifting of restrictions to market entry and eventually full liberalisation.


The typical EU reform

The EU institutions have been in general strongly supportive of thereforms. While neutral on public ownership divestiture, the EChas proposed over the years a number of important directives ontransport and energy sectors that push the Member States towards ahomogenous pattern of regulatory legislation, see e.g. CEC (2007).

A new paradigm (and legislation) has emerged.


Testing the paradigm

We want to test the paradigm on empirical grounds.

We two industries (electricity and gas), each representing differentstages and features of the reform story.

We consider the EU15 (low reliability of data from NMS, shorter timeseries, very different institutions up to 1990s)

Government-owned providers in energy were not loss makers, hencetheir prices covered costs, and comparison with pricing of privatefirms is more sensible.


Our empirical strategy

We focus on consumer prices. After all, we think that the mainjustification of a regulatory reform in SGEI should lie in the potentialbenefits for users.

Under very general assumptions consumer surplus changes areinversely related to price changes, thus focussing on consumer pricesis a sensible shortcut for welfare analysis.


A crucial data set: ETCR

We measure reforms using the OECD Indicators of regulation inenergy, transport and communications (ETCR, formerly known asREGREF), a database very recently (April 2009) released by theOECD, and covering years 1975-2007.

As it wisely provides the sub-indicator variables, as well as 0-6scores, we slightly modified it producing 0-1 dummies replacingcontinuous scores of categorical variables.



Figure 2:

02

46

1975 1980 1985 1990 1995 2000 2005year

Countries Median25th perc. 75th perc.

Whole average indicator. Country indexECTR: Electricity

Figure 3:

12

34

56

1975 1980 1985 1990 1995 2000 2005year

Countries Median25th perc. 75th perc.

Whole average indicator. Country indexECTR: Gas

-1


ELECTRICITYSector indic.

Question weights Weights by theme

Our label Coding Our label

PUBLIC OWNERSHIP:What is the ownership structure of the largest companies in the generation, transmission, distribution, and supply segments of the electricity industry? (ERpo1)

1/3 1/3 1 if ownership is public ERpo_d

ENTRY REGULATION:How are the terms and conditions of third party access (TPA) to the electricity transmission grid determined? (ERen1)

1/3

Is there a liberalised wholesale market for electricity (a wholesale pool)? (ERen2) 1/3

What is the minimum consumption threshold that consumers must exceed in order to be able to choose their electricity supplier ? (ERen3)

1/3

VERTICAL INTEGRATION:What is the degree of vertical separation between the transmission and generation segments of the electricity industry? (ERvi1)

1/2

What is the o erall degree of ertical integration in 1/2

Our coding

Country scores 0-6 Binary variable 0-1

1/3 ERvi_d

ER

Original OECD coding

1 if wholesale market for elect. is not liberlised & consumption threshold is larger than 1MWatts

1 if overall degree of vertical

integration in the industry is

i d

1/3 ERen_d

What is the overall degree of vertical integration in the electricity industry? (ERvi2)

1/2

Source: OECD coding taken from Conway and Nicoletti (2006).

mixed or integrated.


GASSector indic.

Question weights Weights by theme

Our label

Coding (zero otherwise) Our label

PUBLIC OWNERSHIP:What percentage of shares in the largest firm in the gas production/import sector are owned by government?

What percentage of shares in the largest firm in the gas transmission sector are owned by government?

What percentage of shares in the largest firm in the gas distribution sector are owned by government?

1/3

ENTRY REGULATION:How are the terms and conditions of third party access (TPA) to the gas transmission grid determined?

1/3

What percentage of the retail market is open to consumer choice? 1/3

Do national, state or provincial laws or other regulations restrict the number of competitors allowed to operate a business in at least some markets in the sector: gas production/import

1/3

VERTICAL INTEGRATION:What is the degree of vertical separation between gas production/import and the other segments of the industry?

1/3

What is the degree of vertical separation between gas supply and the other segments of the industry? 1/3

Is gas distribution vertically separate from gas supply? 1/3

GRvi_d

GR

Source: ECTM coding taken from Conway and Nicoletti (2006).

1 if 100% of ownership of shares in all

segments of the industry is

public

1/4

1 if the industry is

integrated in all segments

GRen_d

Country scores 0-6 Binary variable 0-1

1/4

Original ECTM coding Our coding

1/3 1/4

GRpo_d

1 if no third party access,

no consumers' choice in the retail market,

and restrictions operate in all

markets.

Do consumers gain? Let’s ask consumers!

Perceived price fairness by (individual) users was recorded byEurobarometro, for which four biannual waves (2000-2006) andaround 60,000 data points are available.

The question asked to individual consumers is: “The price paid forelectricity (gas) services is excessive, unfair or fair.”

We classified respondents into “dissatisfied” and “satisfied”.

The dichotomous (0/1) consumer price dissatisfaction variable isrecorded equal to 1 if the respondent states that the price he pays forelectricity services is unfair/excessive, and is recorded equal to 0 iffair.

As shown in EB reports the average dissatisfaction with SGEI hasdecreased across time.



Dep. variable Probit Probit Probit ProbitCons. price dissatisfaction marg.effects marg.effects marg.effects marg.effects

ER -0.009(0.157)

ERpo_d -0.105*** -0.088*** -0.102***(0.000) (0.000) (0.000)

ERvi_d 0.039*** 0.039*** 0.037***(0.002) (0.002) (0.004)

ERen_d 0.024(0.205)

ERen1_d -0.066***(0.010)

ERen2_d 0.000(0.986)

ERen3_d 0.030** 0.031**(0.013) (0.014)

Average price per Kw/h 2.963*** 3.538*** 3.451*** 3.624***(0.000) (0.000) (0.000) (0.000)

Per capita GDP 13.736*** 14.848*** 16.702*** 17.456***(0.000) (0.000) (0.000) (0.000)

Year: 2002 -0.036*** -0.028*** -0.031*** -0.032***(0.000) (0.007) (0.003) (0.001)

Year: 2004 -0.154*** -0.137*** -0.143*** -0.145***(0.000) (0.000) (0.000) (0.000)

Year: 2006 -0.224*** -0.230*** -0.234*** -0.241***(0.000) (0.000) (0.000) (0.000)

Individual characteristics yes yes yes yesCountry fixed-effects yes yes yes yes

Observations 49619 49619 49619 49619chi2 3369 3432 3499 3459Log-likelihood -30513 -30450 -30445 -30448Pseudo-R2 0.0637 0.0656 0.0658 0.0657Robust p-value in parentheses*** p<0.01, ** p<0.05, * p<0.1

ELECTRICITY



ER -0.009(0.157)

ERpo_d -0.105*** -0.088*** -0.102***(0.000) (0.000) (0.000)

ERvi_d 0.039*** 0.039*** 0.037***(0.002) (0.002) (0.004)

ERen_d 0.024(0.205)

ERen1_d -0.066***(0.010)

ERen2_d 0.000(0.986)

ERen3_d 0.030** 0.031**(0.013) (0.014)


Per capita GDP 13.736*** 14.848*** 16.702*** 17.456***(0.000) (0.000) (0.000) (0.000)

Year: 2002 -0.036*** -0.028*** -0.031*** -0.032***(0.000) (0.007) (0.003) (0.001)

Year: 2004 -0.154*** -0.137*** -0.143*** -0.145***(0.000) (0.000) (0.000) (0.000)

Year: 2006 -0.224*** -0.230*** -0.234*** -0.241***(0.000) (0.000) (0.000) (0.000)



ELECTRICITY



GR -0.083***(0.000)

GRpo_d -0.134*** -0.131*** -0.132***(0.000) (0.000) (0.000)

GRvi_d -0.050** -0.004 -0.009(0.035) (0.901) (0.768)

GRen_d -0.015(0.547)

GRen1_d -0.011(0.554)

GRen2_d -0.066* -0.058*(0.075) (0.081)

GRen3_d 0.018(0.355)

Average price per Gj 0.062*** 0.044*** 0.043*** 0.044***(0.000) (0.000) (0.000) (0.000)

Per capita GDP 10.889** 13.836*** 16.175*** 15.147***(0.011) (0.010) (0.001) (0.003)

Year: 2002 -0.084*** -0.059*** -0.065*** -0.061***(0.000) (0.000) (0.000) (0.000)

Year: 2004 -0.233*** -0.151*** -0.155*** -0.155***(0.000) (0.000) (0.000) (0.000)

Year: 2006 -0.344*** -0.270*** -0.274*** -0.275***(0.000) (0.000) (0.000) (0.000)



GAS



GR -0.083***(0.000)

GRpo_d -0.134*** -0.131*** -0.132***(0.000) (0.000) (0.000)

GRvi_d -0.050** -0.004 -0.009(0.035) (0.901) (0.768)

GRen_d -0.015(0.547)

GRen1_d -0.011(0.554)

GRen2_d -0.066* -0.058*(0.075) (0.081)

GRen3_d 0.018(0.355)


Per capita GDP 10.889** 13.836*** 16.175*** 15.147***(0.011) (0.010) (0.001) (0.003)

Year: 2002 -0.084*** -0.059*** -0.065*** -0.061***(0.000) (0.000) (0.000) (0.000)

Year: 2004 -0.233*** -0.151*** -0.155*** -0.155***(0.000) (0.000) (0.000) (0.000)

Year: 2006 -0.344*** -0.270*** -0.274*** -0.275***(0.000) (0.000) (0.000) (0.000)



GAS

A thought experiment

Can we predict how prices may respond to privatisation andregulatory reforms of utilities?

Two strands of theoretical literature are relevant to discuss the issue:the theory of privatisation and the literature on regulation ofnetworks industries.

The case for privatisation is reviewed, inter alia, by Bos (1993),Vickersand Yarrow (1993,Ch 2), Parker (1998), Newbery (2000), Florio (2004,Ch.2), Megginson (2005), Roland (2008, Ch 1), Sappington andStiglitz (1987).As for regulatory issues, important new insights are given (selectivelyciting from a very wide literature) by Newbery (2000), Laffont (2005),Rey and Verge (2008), Rey and Tirole (2008).



39

Figure 6. Prices and consumer's surpluses under different regimes.

Need for empirical investigation

The prediction of prices under different regulatory regimes dependsfrom a set of (possibly country/industry specific) parameters.

We cannot take for granted that price-unregulated (or uneffectivelyregulated) oligopoly welfare dominates either regulated privatemonopoly or vertically integrated public monopoly.

Even ’full’ market opening can deliver higher prices than aregulated monopoly, if entrants are few, elasticity of demand low,unbundling and related costs high.

Our view is that evaluation of the reform outcomes of networkindustries is essentially an empirical matter: it depends upon a setof parameters that easily lead to non-linear outcomes along thereform ’line’.


Aim of the empirical analysis

We want to test whether consumers actually pay less when weobserve a reform, looking at average consumer prices and takinginto consideration demand and supply conditions and other potentialexplanatory variables and exploiting across-country variation, aswell as across-time.


The main data sets used

The primary sources for the average (log) price variables are theInternational Energy Agency (IEA).

The IEA data start in 1978.

The IEA net-of-tax electricity and gas prices for households areconverted into e/unit and present a correlation with householdnet-of-tax electricity prices from Eurostat equal to 0.814 and 0.847,respectively.

These are country-average data.

Data are an unbalanced panel of EU15 countries (for gas GR & PTare dropped, SW is missing).


Our estimation strategy

We follow Blundell and Bond (2000) and:1 Test the AR(1) specification for the series of prices by sector2 If AR(1) is not rejected, we test whether any OVB would arise for the

ETCR variables.3 If OVB is significant, we develop dynamic panel models4 Estimated dynamic panel models using inconsistent methods:

OLS are biased upwardsFixed-effects are biased downwards (especially for short time-series)Hence, they provide a useful benchmark (Bond, 2002).

5 Estimate with GMM the selected models.


The dynamic panel model specification

Reduced form model for prices:

Pi ,t = αPi ,t−1 + R ′itβ + X ′ijγ + δt + εit

εit = (ηi + νit)

Common feature of the model for the two sectors but separatelyestimated as they have industry-specific ingredients (as the structuraland evolutionary differences across the two industries are distinctive).



Dep. variable (1) (2) (3) (4) (5) (6) (7) (8)

Av. cons. price OLS Within OLS Within OLS Within OLS WithinLagged dep.var. 0.955*** 0.746*** 0.956*** 0.736*** 0.955*** 0.731*** 0.957*** 0.733***

(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)ER 0.000 -0.004

(0.946) (0.309)ERpo_d 0.004 -0.027* 0.004 -0.031* 0.005 -0.032**

(0.565) (0.079) (0.610) (0.055) (0.529) (0.044)ERen_d 0.001 -0.030*

(0.944) (0.086)ERvi_d -0.009 0.019 -0.010 0.020 -0.008 0.019

(0.525) (0.277) (0.470) (0.249) (0.577) (0.268)ERen1_d -0.001 -0.007

(0.959) (0.598)ERen2_d 0.009 -0.002

(0.544) (0.895)ERen3_d -0.007 -0.029* -0.004 -0.029**

(0.596) (0.058) (0.730) (0.044)Hydroele. source 0.001 -0.003 0.001 -0.003 0.001 -0.003 0.001 -0.003

(0.411) (0.141) (0.336) (0.129) (0.373) (0.136) (0.328) (0.125)Comb. fuel source 0.012** -0.003 0.013** -0.008 0.013** -0.007 0.013** -0.007

(0.029) (0.815) (0.026) (0.519) (0.027) (0.533) (0.026) (0.563)Imports -0.000 -0.003** 0.000 -0.003* 0.000 -0.003* 0.000 -0.003*

(0.891) (0.045) (0.989) (0.061) (0.996) (0.054) (0.979) (0.062)Residential cons. -0.013** -0.109*** -0.014** -0.111*** -0.014** -0.110*** -0.014** -0.111***

(0.041) (0.000) (0.033) (0.000) (0.036) (0.000) (0.031) (0.000)Per capita GDP -0.001 0.150*** 0.000 0.153*** -0.000 0.150*** 0.000 0.145***

(0.944) (0.000) (0.985) (0.000) (0.988) (0.000) (0.982) (0.000)Year fixed-effects yes yes yes yes yes yes yes yesConstant -0.059 1.216*** -0.049 1.258*** -0.050 1.234*** -0.045 1.223***

(0.281) (0.000) (0.392) (0.000) (0.376) (0.000) (0.420) (0.000)Observations 402 402 402 402 402 402 402 402ar1p 0.174 0.0190 0.171 0.034 0.165 0.034 0.177 0.033ar2p 0.786 0.505 0.750 0.581 0.738 0.594 0.734 0.596

ELECTRICITY


Dep. variable (1) (2) (3) (4) (5) (6) (7) (8)


(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)ER 0.000 -0.004

(0.946) (0.309)ERpo_d 0.004 -0.027* 0.004 -0.031* 0.005 -0.032**

(0.565) (0.079) (0.610) (0.055) (0.529) (0.044)ERen_d 0.001 -0.030*

(0.944) (0.086)ERvi_d -0.009 0.019 -0.010 0.020 -0.008 0.019

(0.525) (0.277) (0.470) (0.249) (0.577) (0.268)ERen1_d -0.001 -0.007

(0.959) (0.598)ERen2_d 0.009 -0.002

(0.544) (0.895)ERen3_d -0.007 -0.029* -0.004 -0.029**

(0.596) (0.058) (0.730) (0.044)Hydroele. source 0.001 -0.003 0.001 -0.003 0.001 -0.003 0.001 -0.003

(0.411) (0.141) (0.336) (0.129) (0.373) (0.136) (0.328) (0.125)Comb. fuel source 0.012** -0.003 0.013** -0.008 0.013** -0.007 0.013** -0.007

(0.029) (0.815) (0.026) (0.519) (0.027) (0.533) (0.026) (0.563)Imports -0.000 -0.003** 0.000 -0.003* 0.000 -0.003* 0.000 -0.003*


(0.041) (0.000) (0.033) (0.000) (0.036) (0.000) (0.031) (0.000)Per capita GDP -0.001 0.150*** 0.000 0.153*** -0.000 0.150*** 0.000 0.145***



ELECTRICITY


Dep. variable (1) (2) (3) (4) (5) (6) (7) (8)Av. cons. price OLS Within OLS Within OLS Within OLS Within

Lagged dep.var. 0.957*** 0.814*** 0.952*** 0.809*** 0.943*** 0.824*** 0.944*** 0.823***(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

GR 0.002 0.008(0.723) (0.429)

GRpo_d -0.010 -0.062* -0.017 -0.067* -0.018 -0.060*(0.515) (0.064) (0.276) (0.054) (0.250) (0.080)

GRen_d 0.038** 0.054**(0.010) (0.014)

GRvi_d -0.000 0.011 0.006 0.021 0.005 0.018(0.983) (0.508) (0.613) (0.324) (0.673) (0.410)

GRen1_d 0.022 0.036(0.380) (0.210)

GRen2_d -0.043 -0.032 -0.028 -0.010(0.132) (0.365) (0.219) (0.737)

GRen3_d 0.043*** 0.047* 0.045*** 0.054**(0.005) (0.070) (0.003) (0.033)

Change Brent price 0.730** 0.602* 0.731** 0.632** 0.721** 0.624** 0.725** 0.617*(0.024) (0.057) (0.023) (0.044) (0.024) (0.047) (0.024) (0.050)

Per capita GDP -0.016 0.025 0.006 0.067 0.013 0.031 0.015 0.027(0.446) (0.567) (0.795) (0.146) (0.560) (0.505) (0.501) (0.563)

Year fixed-effects yes yes yes yes yes yes yes yesConstant 0.090 0.556*** 0.175** 0.733*** 0.221*** 0.591*** 0.221*** 0.583***

(0.230) (0.001) (0.028) (0.000) (0.008) (0.000) (0.008) (0.000)

Observations 316 316 316 316 316 316 316 316ar1p 0.406 0.069 0.528 0.115 0.445 0.134 0.527 0.170ar2p 0.222 0.260 0.154 0.282 0.174 0.220 0.149 0.201Robust p-value in parentheses*** p<0.01, ** p<0.05, * p<0.1

GAS



Lagged dep.var. 0.957*** 0.814*** 0.952*** 0.809*** 0.943*** 0.824*** 0.944*** 0.823***(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

GR 0.002 0.008(0.723) (0.429)

GRpo_d -0.010 -0.062* -0.017 -0.067* -0.018 -0.060*(0.515) (0.064) (0.276) (0.054) (0.250) (0.080)

GRen_d 0.038** 0.054**(0.010) (0.014)

GRvi_d -0.000 0.011 0.006 0.021 0.005 0.018(0.983) (0.508) (0.613) (0.324) (0.673) (0.410)

GRen1_d 0.022 0.036(0.380) (0.210)

GRen2_d -0.043 -0.032 -0.028 -0.010(0.132) (0.365) (0.219) (0.737)

GRen3_d 0.043*** 0.047* 0.045*** 0.054**(0.005) (0.070) (0.003) (0.033)


Per capita GDP -0.016 0.025 0.006 0.067 0.013 0.031 0.015 0.027(0.446) (0.567) (0.795) (0.146) (0.560) (0.505) (0.501) (0.563)


(0.230) (0.001) (0.028) (0.000) (0.008) (0.000) (0.008) (0.000)


GAS

Conclusions

Our empirical findings for EU15 in the two industries we considered,are mixed.

Privatisation per se does not seem to lead to lower consumerprices.

We find no significant evidence of the benefits of unbundling.

There are beneficial effects of liberalisation only in the gas industry

In the electricity industry, allowing consumers to choose theirproviders is correlated with higher prices.


Conclusions

Our results cast some doubts on the validity of a rigid reformdesign and legislation framework for all the EU Member States.

We suggest that a more flexible and country-specific approach isneeded to protect the consumer from the still importantuncompetitive features of network industries.

More (regulatory and price) cross-country comparable data would bevery welcome, especially at the micro level for assessing distributionaleffects of reforms.

We do not dismiss the importance of liberalisation policy in thenetwork industries, but it seems that until now consumers have hadless than a fair dividend from the reforms (while the profitabilityof these industries is still usually quite high and risk relatively low).


Conclusions

Public ownership is not necessarily the enemy of liberalisation.

Examples are the national electricity transmission system operators inthe Nordic power system, perhaps one of the most advanced in theworld in terms of regional integration and market opening involvingDK, SW, FI and NO.

In this context, public ownership of the networks has probably beenan advantage for the promotion of cross-border market integration.


Still far from the competitive paradigm?

Dieter Helm (2003) after two decades of reforms:

[...] in 1980s ad 1990s the pendulum swung too far the otherway (from public monopoly). The market enthusiasts failed tothe recognize how far the electricity market deviated from thenormal commodity model. [...] It is hard to think of any otheractivity in modern developed economies with quite suchcoincidence of major market failures. If the issue of fuel povertyand the distributional implications of electricity and gas pricingand supply are also included, it is extraordinary that anyone couldhave regarded these as anything other than political industries”.


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