New Structural Transition
Economics—a Doable Project?
By
Michael Keren
Hebrew University of Jerusalem
PAPER PREPARED FOR WORKSHOP ON “Transition Economics Meet
New Structural Economics”, London, 25/26. June 2013.
Fair disclosure
• Biographical detail:
– Spent 6 years, 1956-1962, as government bureaucrat,
Ministry of Commerce and Industry (MCI)
– Period when no significant economic step feasible,
unless unapproved by some ministry.
• Enjoyed much of it,
– Even when I knew that all I was doing was
counterproductive.
• Not every government as inefficient as MCI,
– But characteristics of all similar.
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Life as bureaucrat
• Midfielder but not playmaker:
– Not bottom rank, where you see only paperwork,
– Not top, where you believe you call the shots,
– But connecting link, where you see the soiled
linen, what motivates bureaucrats.
• Learned how economy should not be run
– Because incentives were wrong,
– No relevant information—asymmetrical.
– Slow decision-making, where ‘time is money’.
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New Structural Economics
• Micro-economic decisions to government.
– Governments in general less fit to make such
decisions.
– In particular, governments of
• Low capacity governments—low development
countries,
• Historically burdened—transition countries.
– Burdening any organization with additional tasks
reduces its performance in essential tasks.
– Increases dangers of corruption.
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Simple model of capital market
• 2 sets of actors—investors and lenders.
• Investors have projects, no resources.
– Projects: investment of 1 at  produces if
successful R, unsuccessful—0 at +1.
– When successful pay lender r, otherwise 0.
– Projects differ by probability of success, i , 0    
– i is uniformly distributed (to simplify life).
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Lender n:
• Meets at time  at random a single investor, i.
• Is endowed
– With 𝐾𝑛( = 0 )=1 of loanable capital.
– With an ability, ∝ 𝑛: determines error observing
investor’s success probability:  n     n 
– Observes   n, i   n ,i , n,i 
n ,i  i     n  ; n,i  i     n 
• Lender unaware of error.
• Lends if he believes loan will increase capital.
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Graphically:
r
H
D
  
A
1
E
  
G
C
B
0
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
+
 

-
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Figure explains model
• When  n  0    n   EGH maximum.
• Reduced when  n  0 : = DCGH.
– Because miss expected good project when get
low reading of   i ,  n  .



• Loss when high reading   i ,  n   and lend to
expected losing projects,    n   ABE .
•  the higher  n , the lower profits and the
smaller K n 1 , K n  2  ,...
• Able lenders control loanable capital.
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Evolution of loanable capital
K n     1     n      n   K n    1
• If ability high, grows quickly over time.
• If low grows slowly or even shrinks.
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The real capital market
• Banks missing: why banks?
– Lumpy projects,
– Transactions costs of consolidating large loans;
– Advantages of information transfer internally.
• Lenders become loan officers, evaluators of
investors, in banks.
• Will go over incentives when deal with
government.
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Government ministry
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Minister’s incentives
• Make political capital, to advance in govt, by
– Succeeding in job
– Influencing policy in general
– Getting on with leaders
– Advancing friends & supporters.
• How is success seen?
• When is it seen?
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Hierarchy
• Incentives of those who evaluate projects not
organization’s profitability, but own career, i.e.,
reputation.
• Superiors evaluate evaluators,
– Take into account characteristics market disregards—
’bad or good luck’, personal regard or even services,
– Many not relevant to the organization’s performance.
• Less effective than market in motivating and
selecting operatives.
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Government bureau as project
selector
• Not subject to creative destruction.
• → Not naturally concerned with cash-flow.
• Objectives less clear:
– Not profitability, because then use private sector;
– Public weal—hazy, open to idiosyncratic interpretation.
– Open to corruption.
• Hence thicket of rules and regulations, red tape.
• Further reduce ability of superiors to sanction
evaluators.
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Compare government bureaucracy• Less knowledgeable, because poorer
incentives.
• Less effective in evaluating future prospects
than banks, private lenders. Bribable.
• Extreme asymmetry of information vis a vis
investor, who possesses information.
• Hence governments very poor selectors of
projects.
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Need for government
• Developing countries have gained from
globalization.
– Reduced trading costs.
– Can perform only part of production process, part
of product.
– Need for coordination reduced.
– No need for big push—smaller steps possible.
• Government freed to do what nobody else can
do effectively
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Essential role of government
• Need effective state, strong government.
– Failed states don’t develop.
– Public goods:
• Hard infrastructure—roads, rails, harbors, etc.
• Soft infrastructure—legal framework to protect investors’
bodies & assets, conveyance of property.
– Not an easy task (Pack, in Lin).
• Industrial policy:
– Whatever is generic—part of soft infrastructure;
– Microeconomic selection, branch and investor—
dangerous.
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Increasing scope of government?
• The bigger government—in terms of tasks—the
weaker supervision,
– The less efficacious its performance in remainder of
tasks,
– Adding tasks in which government ineffective harms
its contribution to essential duties.
• Analogy: firms’ concentration on core
competencies,
– Even downsizing by shedding non-core functions.
– Extreme case: firms leaving production to fabs,
specializing in R&D.
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Governments aren’t all alike
• Government capacity depends on
– Human capital,
– Social capital (cohesion), trust,
– History.
• Governments of poor countries mostly weak,
of low capacity.
• Transition countries’ governments—strong, but
history against dabbling with industrial policy.
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Developing countries and microstructure
• Howard Pack (Lin, 2009) provides a detailed
reasoning why DC should not be burdened /
entrusted with micro selection.
• Add: problems of corruption in weak countries.
– Ruler’s loyal to family, clan, tribe—not country,
– Rulers often rapacious raiders of resources.
• Ex: Chad & pipeline to Cameroon.
• Nigerian story of Shell & ENI vs. shell companies.
– ‘Picking champions’—licence to extract bribes.
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Indian example
• Legacy of British Raj: a relatively efficient civil
service.
– Hard working and effective sub-district-officer in A
Suitable Boy.
– Nehru-Mahalanobis imposition of Soviet-like
industrial policy and the Licence Raj,
– Infested poorly paid bureaucracy with corruption
and ineffectiveness.
– Slow growth until start of partial liberalization in
1991 (or mid-1980s—Singh).
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Transition countries
• From party-state amalgam, highly centralized,
strong government,
– Corruption endemic (because disparity between
demand & supply led to blat, needed protection,
krysha),
– Gorbachev’s glasnost removed party, the
supporting column of state,
– Privatization of ‘law’ and order.
• Putin tried to reverse and recentralize.
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Return to Soviet state?
• Industrial policy
– DNA of communism.
– Led to etatization of all resources, monofirm,
– Abolition of market, ‘planning’=bureaucratic
allocation,
– Disparities between demand and supply.
• Return of industrial policy
– Another step back to old cul de sac.
– Will be implemented by siloviki,
– Will increase corruption
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Eastern Europe?
• Advance, until halted by present recession,
satisfactory.
• Western EU members—do they need it?
• Eastern, Balkan countries, governments too
weak to benefit?
• Corruption never far from surface, and
supplying government excuse for meddling—
dangerous.
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Can ‘abroad’ help?
• FDI:
– Capital—physical + organizational + human + technology:
– Beneficial if,
• Forward & backward linkages.
• Provided not in primary industries (no linkages; corruption).
– Eastern Europe has benefitted.
• Reverse-brain drain:
– Direct: technology, human capital.
– Indirect: Conduit for FDI.
• World Bank & other international agencies.
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Concluding remarks
• Structural economic policies, new or old, a
dangerous prescription:
– Government investments in growth promotion
• Generic—helpful.
– Development banks—provide finance too risky for banks
– Applied research institutes—lacuna left by universities.
• Picking promising industries, selecting specific investors
– May breed corruption, invites corruption.
– Can doom counties to long life in poverty for the masses,
riches for the rapacious rulers—if government weak;
– Return to ills of ancien Régime for transition economies.
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Thank you for your patience!
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Tomorrow’s expected capital
• Define: r*  1 I.e., lender should lend iff    *
• Lender lends if   n, i    * because unaware of
error.
r

K n 1   2
 1



  *, n 
d    
  *, n 
d 

if    *
otherwise
E  K n 1   1     n      n 
•
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K n    ,   1,...
•
•
K n 1
declines in error,  , increases in  .
Kn   ,   1
– Rises fast for high ability,  ;
– Rises slowly for middling  ;
– Declines for low , when        n   .
• NB: Capital market as selection device.
• Over time capital gets concentrated in hands
of those who are skilled in reading market.
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Profits and losses
•

   n   r   r  1 d 
*
= profits from the share lent
   n 
1  *
   n       r  1 d   
1  r  d    0

*
2    n 

• Mean of loss of lending when observing:
– n,i and some expectedly losing loans accepted,


– n,i some expectedly successful loans declined.
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Competitive banks
• Assume advantages to scale:
– Lumpy projects,
– Transactions costs of consolidating large loans;
– Advantages of information transfer internally.
• Lenders become loan officers, evaluators of
investors, in banks.
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Bank m
Boss
CEO
Supervisor
Supervisor
Supervisor
1
2
3
Evaluator
11
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Evaluator
12
Evaluator
21
Evaluator
22
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Evaluator
31
Evaluator
32
32
Loan officers’ incentives
• Evaluators’ incentives:
– Possibly bonus  ar or a  r  1 , a 1
– Then effort less than independent lender, invest
less in seeking information.
• losses when loans fail
– Borne by bank, not evaluator,
– More risk-ready than bank.
– Bribable by investor.
• Need supervisors to oversee evaluators.
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Bank compared to baseline
• Each evaluator less effective than individual
lender, hence
   m      m 
• And bank will be slower in organic growth
than, e.g., successful venture capitalist.
• NB—returns to scale, and dynamically—
learning-by-doing.
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Supervisors
• Supervised by Boss.
• Part of incentive system—evaluators can hope to
advance.
• Each supervisor has to evaluate subordinates:
– Takes into account characteristics market disregards—
’bad or good luck’, personal regard or even services,
– Many not relevant to the bank’s performance.
• Less effective than market in motivating and
selecting operatives.
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