Transcript Slide 1

Regulation and
Regulatory Reforms in
Developing Countries
Antonio Estache
European School on New Institutional Economics
ESNIE 2009
Cargèse
May 2009
Overview
• Focus on regulation in key
infrastructure industries
– Some background data on the main
reforms of the last 15 years
– A zoom on regulatory reforms
– A further zoom on the institutional
dimensions of regulatory reform in
developing countries
The reforms of the 1990s
• Three main “standard” reforms:
– Relying more on competition
• In the market when possible
• For the market otherwise
– End to old fashion self-regulation when
regulation was still needed
• create “independent” regulatory agencies
• deal more explicitly with the incentives for efficiency
in the design of regulation (i.e. replacing cost + by
price caps)
– Opening up to private sector to get access to
private financing to fasten service coverage
increases
Mixed to poor success of the efforts to
attract the private sector…
% of countries with Private Participation in Infrastructure (2004)
Elec.Gn.
Elec.Dis.
W&S
Rail
Telecms
Tot.
Dvlping
44%
36%
35%
37%
48%
Tot.
Dvloped
70%
43%
80%
65%
83%
Total
48%
36%
42%
43%
55%
Investment commitments to infrastructure
projects with private participation in developing
countries in real and nominal terms, 1990–2007
180
150
Total: US$1,475 billion committed through
+/- 4,100 projects… adds up to less than
20% of the investment in the sector….
158
144
120
111
90
60
30
0
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
US$ billions
Source: World Bank and PPIAF, PPI Project Database.
2007 US$ billions
Telecoms and energy dominate
investments levels
180
2007 US$ billions
150
120
90
60
30
0
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Energy
Telecoms
Source: World Bank and PPIAF, PPI Project Database.
Transport
Water and sewerage
Total
Energy and transport dominate the
number of projects
400
350
300
Projects
250
200
150
100
50
0
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Energy
Telecoms
Source: World Bank and PPIAF, PPI Project Database.
Transport
Water and sewerage
Total
East Asia and Latin America are
the favorite destinations
90
80
2007 US$ billions
70
60
50
40
30
20
10
0
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
East Asia and Pacific
Latin America and the Caribbean
South Asia
Source: World Bank and PPIAF, PPI Project Database.
Europe and Central Asia
Middle East and North Africa
Sub-Saharan Africa
One slide on the crisis and infrastructure
investments…not good news…
Private flows to LDCs forecast
PPI in infrastructure et PIB growth
2007 US$ billions
Percentage
180
9
800
160
8
700
140
7
600
120
6
500
100
5
400
80
4
60
3
40
2
US$ billions
300
200
100
2008
2006
2004
2002
2000
1998
1996
1994
1992
0
1990
0
Commercial banks, net
GDP growth (annual %)
Source: World Bank and PPIAF, Impact of the financial crisis on PPI database, PPI Projects database, and Institute of International Finance.
2009f
2008e
2007
2006
2005
2004
2003
-200
Equity investment, net
PPI
2002
2001
2000
1999
1998
-100
1997
1
1996
20
1995
0
The regulation independence war also
only enjoyed only a mixed success
(% of countries with Independent Regulatory Agency)
Elect. W&S.
Rails
Telecms
Total Developing
50%
26%
7%
61%
Total Developed
92%
20%
21%
55%
Total
57% 25% 9%
60%
In a nutshell….
How did it work out?
• Fiscal cost: ok in short term but not ok
over the longer run
• Efficiency: reasonably ok although
increased shift from price caps to
hybrids dominated by strong costs
pass thru rules
• Equity: key problem and essentially a
regulatory design issue
• Accountability: not good either…and
again a regulatory design issue
The winners and losers in terms of Actors
• The actors in the payoff matrix
– The users (access: (+ but not as much as expected
and distributional issues), affordability(-), quality (+))
– The taxpayers (cash!: + in SR, -/+ in LR)
– The workers (jobs + cash: - in SR, + in LR)
– The operators (cash in the SR and IRR> COC in the
LR for a few! (+ in SR, ? for LR)
– The local owners (cash! + in SR and LR)
– The foreign owners (cash! + in SR, +/- in LR)
– The bankers (cash! + in SR and LR)
– The politicians (cash! + in SR and LR)
– The donors (???)
Emerging Issues
• For users:
– Residential users: Distributional issues
– Non-residential users: could do much better
• For operators:
–
–
–
–
–
Demand uncertainty
Cost levels revisions to address overruns
Projects design revisions
Exchange rate risks and other economic shocks
De facto expropriation risks
• For government:
–
–
–
–
Uncertainty about demand and costs!
Uncertain net fiscal effects
Fiscal space: the illusion of private sector invest
Weak regulatory capacity, commitment and strong
capture
• But counterfactual may be worse!
How can regulation theory
help in the diagnostic
and
…how can it help fix
things?
First: recognize a few basic
principles emerging from theory…
1.
Information asymmetry matters and can matter a lot!
•
•
When a regulated operator has privileged information: it usually
gets a rent from it
Information asymmetry seems to be a much bigger issue in LDCs
Rents exist…but are not necessarily bad!
2.
•
3.
Regulation can be designed to get operator to use the rent (within
limits…) in a Pareto improving way
Limited commitment ability of a regulator is an
essential driver of the effectiveness of regulation in
terms of efficiency, equity and fiscal costs
•
It may be a good idea to limit a regulator’s powers to avoid undue
use of information through capture associated with a limited
ability to commit
15
How can these issues be modeled?
• Ideally, we need a general model to see how a
monopolist will behave to maximize rent from
weak institutional capacity
• But we need to make sure that the main
institutional capacity issues generally
recognized by experts on LDCs can be
addressed explicitly within the model
• This also means we need to explicitly separate
the regulator from the government to check for
regulator specific problems
• In addition, we want try to reconcile the policy
recommendations emerging from research
focusing on narrow issues using issues specific
models
16
So what are the institutional
weaknesses we need to track down?
• A survey of policy and theoretical
literature identifies:
– Limited capacity/skills to regulate
– Limited accountability
– Limited ability to commit
– Limited enforcement capacity
– Limited fiscal efficiency
Each of these dimensions needs to hit on a
specific variable in the general model
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Some basic stylized facts on these
institutional weaknesses? (1)
• Limited capacity to regulate or to enforce
– Regulators are severely under-resourced …
– … which can lead to increased firm rents.
• Limited commitment
– Many contracts have been renegotiated…
– … tends to increase the cost of capital…
– … but could this effect have been decreased by
independent regulation…
– … and better checks and balances???
18
Some basic stylized facts on these
institutional weaknesses? (2)
• Limited accountability
– Regulators (and governments) are often not
accountable…
– … which decreases efficiency and inequality
• Limited fiscal space
– High cost of public funds…
– … partly explains why SOEs have not expanded
network enough…
– … but increasing access is not profitable for
privatized firms…
– … partly because of conflicts between affordability
and access…
– … independent regulation appears to help
19
A Basic Model of Monopoly Regulation:
(1)The Monopolist
• Monopolist produces a quantity q of a good with a
fixed costs of F and a marginal cost of C(q)
• Monopolist cost-function is also driven by:
– e = firm effort (i.e. moral hazard variable)
• Exerting effort e causes firm disutility of ψ(e) (ψ’>0 , ψ’’>0 , ψ’’’ ≥ 0 )
=> this is the controlable part of costs
– β = underlying cost outside of firm’s control (i.e.
adverse selection variable such as technology or factor
prices=> this is the uncontrolable part of costs
• β= β (low cost) with probability v, or high cost with probability 1-v.
C(q) = (β-e)q + F
• Monopoly utility is U = qp - (β-e)q – F – Ψ (e) + t
With p=price and t=transfer
• Participation constraint: U>0 (once β is revealed)
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A Basic Model of Monopoly Regulation:
(2) Consumers
• Consumer welfare: V = S (q)  qp  (1   )t
q
• S(q) = gross surplus = 0 P(q)dq
•
P (q) = inverse demand function
• λ >0 is the opportunity cost of public funds
• Consumers maximize welfare  p=P(q)=S’(q)
(3) Government
• Benevolent government welfare function:
W = U  V = S (q)  (   e)q  (e)  F  t
• Government always observes F & c = (β - e)
• !!!but government does not observe not β or e (i.e.
composition of cost)
• In order to learn β and e, the government employs a
regulator…
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A Basic Model of Monopoly Regulation:
(4) The Regulator
• Intuitively, the idea is that the main focus of the regulator is
the cost function and the variables it can control β and e
• The firm’s cost β is revealed to the regulator with
probability ξ
• If the regulator learns β, it chooses whether or not to reveal
it to the government
– Signal is `hard information’ – i.e. regulator cannot report a costlevel that it has not observed
• Government can incentivise regulator to reveal signal by
paying s if β is revealed
– Social cost is λs due to cost of public funds
• Firm can incentivise regulator to hide signal by paying
bribe
– Such side-transfers are illegal and hence costly=> regulator
receives only a fraction 0 < k < 1 of bribe
• We assume the gvt decides on the set of contracts offered
to the firm BEFORE the regulator makes its report on costs
=> gvt can influence regulator’s choice on info revelation
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Complete Institutions Benchmark:
Symmetric information
• In this version, the country does not suffer from any of the
4 institutional weaknesses
• If regulator reveals β, there is symmetric information
 Government maximizes welfare W, s.t. binding
participation constraints (PC)
dW/dq=0 leads to usual markup price over mrgnal costs
p  (   e)
 1

p
1  
( = elasticity of demand)
=>since for a given β, the only variable the regulator can
focus on is effort (e) => dW/de=0 to get the optimal effort
the gvt aims which leads to
- ψ’(e)=q (i.e. efficient effort)
- U=0 (i.e. no rent)
=> Price is set above MC to cover for cost of transfers which
is itself set to avoid any rent and H or L firms efforts are
both optimal
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Complete Institutions Benchmark:
Now…Asymmetric information (1)
• If regulator does not reveal β:
 Asymmetric information
 For a firm to be interested in any offer by the gvt, the offer
has to satisfy the incentive compatibility constraints (ICC)
U  U   (e )
U  U  (e   )
• Here     
and (e)   (e)  (e   )
• i.e. firm is incentivized to reveal β truthfully
 Std result: the binding PC is for high cost firm and ICC is
for low cost firm
•  Low cost firm is given positive rent: U  (e ) ;
• an information rent which does not apply to high cost firm
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Complete Institutions Benchmark:
Asymmetric information (2)
 Now…if regulator reveals information, low cost firm gets no rent
 Low cost firm has incentive to bribe the regulator to keep β
hidden
 Willing to bribe regulator up to  (e )
 Government is willing to pay conditional transfer to regulator to
prevent the regulator accepting bribe, i.e. s  k (e )
• Regulator only get k  (e ) with 0<k<1 due to transaction costs
• Paying the regulator allows the gvt to avoid a cost to society of
λk  (e ) ; rent given to firm is costly to society since there is
opportunity cost of public funds
 Now we can calculate the optimal gvt choice of q and e
 Do so by computing the expected welfare E(W) given ξ and v
 dE(W)/dq=0 and get usual markup formula for price
 And…dE(W)/de=0 and get a complex formula
 (e )  q 

v 

1

1   1  v  1  

k  (e )

(2)
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Complete Institutions Benchmark:
Asymmetric information (3)
 What does this equation mean????,
 (e )  q 


v 

1
k  (e )

1  1 v  1  
Marginal disutility to effort of the firm (ψ’) can be
impacted by a set of variables of relevance to the
government
This includes the fact that the rent that the low cost
firm receives is costly to society (comes from
distortive taxation)
The gvt wants to minimize it
To reduce the rent, the gvt can make the high cost firm
production (q) level less appealing to the low cost firm
(work on e and hence Ø(e))
26
Complete Institutions Benchmark:
Asymmetric information (4)
We end up with an actual level of effort is lower than
the efficient one
The 2nd term is increasing in v since the more likely
the firm is to be low cost, the less likely the distortion
in effort will occur and hence the gvt can allow the
distortion to be greater
Note: gvt can act directly on cost looking at effort BUT
it can also introduce an incentive scheme to get the
firm to do the right thing on its own
Rather than setting p, cost or transfers, the gvt can set
the price and come up with a reimbursement rule
which makes the firm decide on the optimal effort level
to max the rent (from low powered to high powered)
Note: in this particular model, the level of incentive is
equivalent to the level of effort
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Now we have a model…so what?
Let’s use the model to review the impact of
each institutional weakness and the optimal
policy response to each weakness
Let’s see how consistent these various
optimal policies
Let’s see how these optimal policies match
the standard policies recommended and
often adopted by regulators in developing
countries
What if limited regulatory capacity?
• Limited regulatory capacity implies
– (a) lower ξ , the proba that the regulator observes the firms’
type or
– (b) no observation of C = (β - e)
• So what?
– (a) From equation (2), lower ξ implies higher powered
incentives needed since collusion btw firm and
regulator occurs less often and hence anti-collusion
payments less of a concern
– (b) Non-observation of c implies high-powered
incentives by definition – price caps are the only option
• => less capacity makes a stronger case for
high powered incentive regulatory regimes
29
What if limited accountability? (1)
• Less accountability of the regulator can imply greater value
of k (the cost to the government to cut the ease of making
bribes)
 Less likely to be optimal to prevent capture because so
expensive to do so
 Lower social welfare and greater frequency of capture
• Assume that with probability ζ regulator is `dishonest’ and
will take bribes and with probability 1- ζ is `honest’ and
will not …but the gvt does not know the regulator type
 Strange result…with less accountability…may
no longer necessarily be optimal to prevent
regulator’s capture through payments to this
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regulator!
What if limited accountability (2)
• Now what if the problem of limited accountability is not
about the regulator but about government nonbenevolence?
• Less accountability of government can thus be modelled
as greater value of
γ => can be modelled as misaligned
objective function and favouring of firm over consumers:
W=V+γU
• Government favoring of firm implies cares less about rent,
hence lower distortion of effort:
• Now E(W) also includes γ and dE(W)/de=0 leads to drivers
of marginal disutility to effort of the firm (ψ’) as follows:

1
v 

 (e )  q 

 k  1    (e )

1  1 v  1 

 greater γ results in higher powered incentives to cut costs =>but
associated with higher risks of regulatory capture…
31
What if limited accountability (3)
• So do we have any solutions???
• 1. recognize that limited accountability is mainly
due to lack of information flows between actors!
• 2. this means that we need to reduce the
importance of information that any agents holds
• 3. this can be achieved for instance by
– Lowering the power of incentives (cost plus looks
good!)
– But also by the creation of new information sources (get
multiple regulatory agencies to generate competition for
the generation of information)
• …but not easy if you have limited capacity…
32
What if limited commitment (1)
• 3 forms: (i) too much renegotiation, (ii) non respect of promises to firm
and (iii) limited enforcement willingness
• => inefficiency ex-post and all firms will pretend to be high costs and
hence gvt needs of give up more rent to get the right ones on board
• => high risk when need to make long term investments
• If firm invests I to influence β, it increases the probability that it will
be a low cost firm i.e. ν= ν(I) (ν’>0, v’’<0)
• If government can commit to rents at time of investment, will set firm’s
payoffs to account for all surpluses as follows: v '( I )  1/ U  U  V  V 


• However, if no commitment, firm only considers private payoffs, hence
v '( I )  1 U  U 
• =>Limited commitment therefore implies under-investment
• NOTE: it will also lead to “ratchet effect” (if the firm reveals
its type to be low cost, it knows the gvt will be more
demanding => added incentive NOT to reveal information
=> gvt could increase welfare by promising not to use info!
33
What if limited commitment? (2)
• So…solutions?
• Note again: gvt led renegotiations are common (unhappy with high
firm profits) => odds are driven by size of rent
• => government can only commit to give a maximum expected rent
(let’s call it c)
• If not satisfied, gvt needs to reduce e
• => To satisfy this ICC, the gvt may have to favor lower incentives!
• This is because the threat of renegotiation constrains its ability to
offer the firm the possibility of making large profits!
 (e )  c
• =>in practice, this means that limited commitment may
require also a reduction in power of incentives since
need to give more rent than it otherwise would have to
get the firms to participate in the business
• NOTE: empirical evidence suggests that price cap are
more associated with renegotiation than cost-plus
34
What if limited commitment? (3)
• More solutions?
– Nationalization…since gvt end up happy with
the rent they now control…=> tolerate higher
profits!
– Increase debt financing since gvt has to
tolerate more interest payment than it tends to
tolerate dividends
– Increase independence of regulator
• The fact is that each form of lack of
commitment tends to lead to its own
solution!
35
What if limited fiscal efficiency? (1)
• If no money for direct subsidies…a natural solution are
cross subsidies (across people or across regions)
• Consider two regions – rich (1) and poor (2)
• In region 2, only a share θ of the population are connected.
• Let Fi , ci , qi , pi be the fixed cost, marginal cost, quantity
per capita and price in region i, and let F2= F2(θ) (F2’>0,
F2’’>0) => F2 a fct of share of people connected
• Write welfare function F
W=S(q1) +λ q1 .p1 - (1+λ)(c1.q1 – F1) +θS(q2) +θλ q2 .p2 - (1+λ)(θc2.q2 – F2 (θ))
• dW/dθ=0 => (3) (1   ) F '( )  S (q2 )   p2 q2  (1   )c2q2
d
0
• Differentiate this to get
d
• This tells us that the optimal size of network shrinks as
fiscal efficiency shrinks!
36
What if limited fiscal efficiency? (2)
• Solutions??? Look at a typical problem
• Imagine rural area more costly, i.e. c2 > c1 , =>ideally: p2>p1
• BUT uniform price restriction to “help” the poor rural area
c1  c2
i.e. implies p2  (1   ) 1  
rather than p2 = (1+λ)c2
• However, (from (3)) this reduces network size
• With no government-firm transfers, instead of (3) we have
 F '( )  S (q2 )  ( 1) p2q2  c2q2
• => there is a trade-off between affordability and access
• Hence when 1+λ >μ, need cross-subsidies targeted to
network expansion to increase network expansion
37
Summary of consequences of
our institutional problems
Quantity
Quality
Cost
Prices
Limited
Capacity
0/-
-
?
+
Limited
Commitment
0/-
-
+
+
Limited
Accountability
-
?
+
?
Limited
Fiscal Space
?
-
+
?
Welfare
-
38
What solutions does theory offer?
Limited
Capacity
Limited
Commitment
Industry Structure
Regulatory Structure
Contract Structure
Vertical disintegration
More competition (?)
Centralisation
Less independence (?)
Fewer regulators
Contracting out
Lower powered
incentives Simpler
contracts
Vertical integration
Less privatisation (?)
More independence
Multiple regulators
Pro-industry bias (?)
Lower powered
incentives ?
Less discretion
Decentralisation
Less independence (?)
Multiple regulators
Anti-industry bias
Lower powered
incentives ?
Less discretion
Fewer crosssubsidies
Independent subsidy
body
More crosssubsidies ?
Vertical disintegration
Limited
More competition (?)
Accountability
More privatisation (?)
Limited
Fiscal Space
More competition (?)
Alternative suppliers
39
CONCLUSIONS
• We know from experience that the real impacts of
the various institutional limitations discussed can
be large
• Main real problem is that the solutions available
are imperfect and OFTEN contradictory
• Moreover, we still have huge gaps in our
understanding of issues
– No real serious link between finance and regulation in
this field
• Moreover, good solutions for LDCs often need to
follow a different path from that taken in
developed countries
– Thus insufficient and possibly damaging to
advocate simply for a regulatory framework that is
closer to some universal ideal.
– …and a lot more work to do on this topic!
40