Transaction Cost Economics of Port Performance: A ... Conference... · Derive transaction cost...

IFSPA 2010 – Chengdu, China

Transaction Cost Economics of Port Performance:A Composite Frontier Analysis

Presentation by:John Liu

Director, C.Y. Tung International Centre for Maritime Studies

Department of Logistics and Maritime Studies

Hong Kong PolyU

October 15 - 18, 201010/21/2010JJ Liu1

Presentation by:John Liu

Director, C.Y. Tung International Centre for Maritime Studies

Department of Logistics and Maritime Studies

Hong Kong PolyU

October 15 - 18, 2010

Derive transaction cost characteristics of port logistics

Verify and test them against the theory of transactioncost economics (Williamson 2002, 2008):o Firm as a governance structure: Governance cost is inevitableo Governance cost: a nonlinear function of asset specificity (k)

within a certain mode of governance Transaction cost

Address research questions of:o The implication of omitting TCE from port efficiency analysis

(e.g., DEA and SFA, both excluding TCE)o Implications of TEC for port logistics: TEU-only rankings?

Impact of ownership structure, and legal origin? …

ABSTRACT

Derive transaction cost characteristics of port logistics

Verify and test them against the theory of transactioncost economics (Williamson 2002, 2008):o Firm as a governance structure: Governance cost is inevitableo Governance cost: a nonlinear function of asset specificity (k)

within a certain mode of governance Transaction cost

Address research questions of:o The implication of omitting TCE from port efficiency analysis

(e.g., DEA and SFA, both excluding TCE)o Implications of TEC for port logistics: TEU-only rankings?

Impact of ownership structure, and legal origin? …

Port performance: Port production, port governanceo Transaction cost economics (Williamson 2002, 2008): From

choice to contract; cost of governanceo Transaction characteristics of port governance: From nonlinear

cost to non-smooth frontier

A Composite Frontier Model of Port Logistics:Production (smooth) + Transaction (non-smooth)

Econometrical measures of port performance: Is TEU-only measure sufficiency? What’s missing?

Example: Container Port Efficiency Assessment

Outlines

Port performance: Port production, port governanceo Transaction cost economics (Williamson 2002, 2008): From

choice to contract; cost of governanceo Transaction characteristics of port governance: From nonlinear

cost to non-smooth frontier

A Composite Frontier Model of Port Logistics:Production (smooth) + Transaction (non-smooth)

Econometrical measures of port performance: Is TEU-only measure sufficiency? What’s missing?

Example: Container Port Efficiency Assessment

Port Performance

Port production performance: DEA, SFA TEU-only rankings? Implications of transaction cost: Cost of

governance

10/21/2010 LGT/Liu 4

Port Performance

Port production performance: DEA, SFA TEU-only rankings? Implications of transaction cost: Cost of

governance

Research Questions: To explain …

Why TEU-only rankings of ports? What’smissing?

Why coexist single-operator (e.g., Singapore)and multi-operator (e.g., Hong Kong) ports?

Why coexist stevedore and carrier terminaloperators?

10/21/2010 LGT/Liu 5

Research Questions: To explain …

Why TEU-only rankings of ports? What’smissing?

Why coexist single-operator (e.g., Singapore)and multi-operator (e.g., Hong Kong) ports?

Why coexist stevedore and carrier terminaloperators?

Current Port Logistics StudiesPort: The Firm as a Production Function

Port logistics: Broadly defined as transportlogistics of seaport, airport, and dry port, ….

Port as a production function: The classical theoryof the firm as a production function (or a DMU) Port level performance: DEA, SFA (not

operator performance; Yan, et al. 2009)

Transaction cost economics: Firm as a governancestructure Port as a governance structure ofterminal production

10/21/2010 LGT/Liu 6

Current Port Logistics StudiesPort: The Firm as a Production Function

Port logistics: Broadly defined as transportlogistics of seaport, airport, and dry port, ….

Port as a production function: The classical theoryof the firm as a production function (or a DMU) Port level performance: DEA, SFA (not

operator performance; Yan, et al. 2009)

Transaction cost economics: Firm as a governancestructure Port as a governance structure ofterminal production

Transaction Cost Economics

The Firm Theory:Production Function versusGovernance Structure

From Choice to Contract Cost of Contract Governance

10/21/2010 LGT/Liu 7

Transaction Cost Economics

The Firm Theory:Production Function versusGovernance Structure

From Choice to Contract Cost of Contract Governance

Firm as a Governance Structure (1):From Choice to Contract [Williamson, 2002]

Science of Choice: Theory of firm asproduction function

“Economics throughout the twentieth century has beendeveloped predominantly as a science of choice. ......Choice has been developed in two parallel constructions:the theory of consumer behavior, in which consumersmaximize utility, and the theory of the firm as productionfunction, in which firms maximize profit.”

10/21/2010 LGT/Liu 8

Firm as a Governance Structure (1):From Choice to Contract [Williamson, 2002]

Science of Choice: Theory of firm asproduction function

“Economics throughout the twentieth century has beendeveloped predominantly as a science of choice. ......Choice has been developed in two parallel constructions:the theory of consumer behavior, in which consumersmaximize utility, and the theory of the firm as productionfunction, in which firms maximize profit.”

Firm as Governance Structure:From Choice to Contract [Williamson, 2002]

Science of Contract: Theory of firm asgovernance structure

……. By contrast with mechanism design and agenttheory of the firm, contract/governance approachassociates a firm with three critical attributes, namely,incentive intensity, administrative control and contractlaw regime.

10/21/2010 LGT/Liu 9

Firm as Governance Structure:From Choice to Contract [Williamson, 2002]

Science of Contract: Theory of firm asgovernance structure

……. By contrast with mechanism design and agenttheory of the firm, contract/governance approachassociates a firm with three critical attributes, namely,incentive intensity, administrative control and contractlaw regime.

Distinctions: Choice and Contract[Williamson, 2002]

Attributes: Transaction and Governance

Transaction = Ultimate unit of activity: “…must contain three principles of conflict,mutuality, and order. This unit is a transaction”

Attributes of Transaction: Asset specificity,disturbance (to transaction), and frequency

Attributes of Governance: Incentive intensity,administrative control and contract law regime

Transactions differ in attributes; Governancestructures differ in costs and competencies

10/21/2010 LGT/Liu 11

Attributes: Transaction and Governance

Transaction = Ultimate unit of activity: “…must contain three principles of conflict,mutuality, and order. This unit is a transaction”

Attributes of Transaction: Asset specificity,disturbance (to transaction), and frequency

Attributes of Governance: Incentive intensity,administrative control and contract law regime

Transactions differ in attributes; Governancestructures differ in costs and competencies

Transaction Cost Economics

Transaction cost: Asset specificity (which gives riseto bilateral dependency) and uncertainty (which posesadaptive needs) of transaction incur differenttransaction cost consequences (highly non-linear)under different modes and attributes (heterogeneous)of governance structure.

Adaptive regulation: “The requisite mix ofautonomous adaptations and coordinated adaptationsvary among transactions. Specifically, the need forcoordinated adaptations builds up as asset specificitydeepens.” (Williamson, 2002)

10/21/2010 LGT/Liu 12

Transaction Cost Economics

Transaction cost: Asset specificity (which gives riseto bilateral dependency) and uncertainty (which posesadaptive needs) of transaction incur differenttransaction cost consequences (highly non-linear)under different modes and attributes (heterogeneous)of governance structure.

Adaptive regulation: “The requisite mix ofautonomous adaptations and coordinated adaptationsvary among transactions. Specifically, the need forcoordinated adaptations builds up as asset specificitydeepens.” (Williamson, 2002)

Governance:Regular v.s. Contingent

Contingent risk: Disruption to Equilibrium

Classical control: speed, rate, differential dynamics

Impulse control: position, injection, stimulus

Contingent risk: Disruption to Equilibrium

Classical control: speed, rate, differential dynamics

Impulse control: position, injection, stimulus

Speed

impulse

Heuristic Model of Firm as Governance Structure:Heterogeneous and non-linear Costs

[Williamson, 2002]

Markets mode

Hybrid mode

Hierarchies

Hybrid mode

Review: Efficiency FrontierModels

Classical Frontier Model Applications to port performance:

DEA and SFA for port levelperformance; v.s. terminal level

10/21/2010 LGT/Liu 15

Review: Efficiency FrontierModels

Classical Frontier Model Applications to port performance:

DEA and SFA for port levelperformance; v.s. terminal level

A . O u tp u t C o n ta in e r T h ro u g h p u t in T E U s (m il l io n )B . In p u ts1 . C a r g o H a n d l in g E q u ip m e n ts :

C H Q : C a rg o h a n d lin g c a p a c i ty a t q u a y in to n n a g e (0 0 0 ’ s ) a

C H Y : C a rg o h a n d lin g c a p a c i ty a t y a rd in to n n a g e ( 0 0 0 ’ s ) b

2 . T e r m in a l I n fr a s tr u c tu r e s :B e r th : N u m b e r o f b e r thQ le n g th : L e n g th o f q u a y l in e in m e te r ( 0 0 0 ’ s )T a r e a : T e rm in a l a r e a in s q u a re d m e te r s ( 0 0 0 ’s )

3 . S to r a g e F a c i l i t ie s :S to r a g e : S to r a g e c a p a c i ty in n u m b e r o f T E U s ( 0 0 0 ’ s )R e e fe r : N u m b e r o f e le c t r ic r e e fe r p o in ts

C . In d iv id u a l C h a r a c te r is t ic s1 . T e r m in a l a n d p o r t le v e l :

D e p th : D e p th o f w a te r in m e te rC a ll : N u m b e r o f l in e r s c a l l in g th e te rm in a lO p e r a to r : N u m b e r o f o p e ra to r s in p o r tT e r m in a l : N u m b e r o f te rm in a ls in p o r t

2 . P o r t g r o u p d u m m ie s ( in f r a c t io n o f to ta l s a m p le ) :H P H : H u tc h is o n P o r t H o ld in g sP S A : P o r t o f S in g a p o re A u th o r i ty C o rp o ra t io nP N O : P & OS S A : S S A M a r in eM S K : M a e r s kO th e r : n o t b e lo n g to a n y o f a b o v e g ro u p s

3 . C o u n tr y le v e l:G D P : G D P in c u r r e n t U S $ (b i l l io n ) c

E X P : G o o d s e x p o r ts in c u r r e n t U S $ (b i l l io n ) c

I M P : G o o d s im p o r ts in c u r re n t U S $ (b i l l io n ) c

4 . C o n t in e n ta l D is tr ib u t io n ( in f r a c t io n o f to ta l s a m p le ) :A S : A s iaE U : E u ro p eN A : N o r th A m e r ic aL A : L a t in A m e r ic aO C : O c e a n iaA F : A f r ic aM E : M id d le E a s t

N u m b e r o f C o u n tr ie sN u m b e r o f P o r tsN u m b e r o f T e rm in a l O p e ra to r sN u m b e r o f O b s e rv a t io n s

0 .7 9 3 4 (1 .4 7 5 4 )

0 .3 3 4 6 (0 .3 4 6 1 )5 .0 6 6 7 (6 .8 3 6 2 )

4 .6 5 1 6 (4 .8 1 7 4 )1 .2 5 8 2 (1 .0 9 6 0 )5 7 1 .2 9 (8 4 1 .5 1 )

2 2 .8 3 5 (8 7 .6 9 2 )4 2 0 .2 1 (4 4 4 .8 7 )

1 2 .5 0 6 (1 .9 5 4 1 )1 5 .0 6 0 (1 3 .2 4 5 )3 .5 8 2 9 (2 .6 0 4 6 )6 .9 0 4 5 (6 .3 4 0 9 )

0 .0 40 .0 30 .0 60 .0 50 .0 20 .8 0

2 3 8 2 .8 (3 4 1 3 .7 )2 6 5 .3 2 (2 4 4 .8 9 )3 1 1 .2 6 (3 7 3 .3 9 )

0 .3 10 .2 60 .2 00 .0 60 .0 80 .0 40 .0 5

3 97 8

1 4 15 9 7

a T h e a g g re g a te d c a p a c i ty o f : ( 1 ) q u a y c r a n e s ; ( 2 ) s h ip s h o re c o n ta in e r c r a n e s .b T h e a g g re g a te d c a p a c i ty o f : ( 1 ) g a n try c r a n e s ; ( 2 ) y a rd c r a n e s ; (3 ) y a rd g a n tr ie s ; (4 ) r e a c h s ta c k e r s ; (5 ) y a rd t r a c k to r s ; ( 6 ) y a rd c h a s is t r a i le r s ;(7 ) f o rk l if ts ; ( 8 ) s t r a d d le c a r r ie r s ; (9 ) c o n ta in e r l i f te r s ; (1 0 ) m o b ile c r a n e s .c T h e c o u n try d a ta c a n b e fo u n d a t th e W o r ld B a n k w e b s i te : h t tp : / /d e v d a ta .w o r ld b a n k .o rg /d a ta o n lin e /o ld -d e fa u l t .h tm

A . O u tp u t C o n ta in e r T h ro u g h p u t in T E U s (m il l io n )B . In p u ts1 . C a r g o H a n d l in g E q u ip m e n ts :

C H Q : C a rg o h a n d lin g c a p a c i ty a t q u a y in to n n a g e (0 0 0 ’ s ) a

C H Y : C a rg o h a n d lin g c a p a c i ty a t y a rd in to n n a g e ( 0 0 0 ’ s ) b

2 . T e r m in a l I n fr a s tr u c tu r e s :B e r th : N u m b e r o f b e r thQ le n g th : L e n g th o f q u a y l in e in m e te r ( 0 0 0 ’ s )T a r e a : T e rm in a l a r e a in s q u a re d m e te r s ( 0 0 0 ’s )

3 . S to r a g e F a c i l i t ie s :S to r a g e : S to r a g e c a p a c i ty in n u m b e r o f T E U s ( 0 0 0 ’ s )R e e fe r : N u m b e r o f e le c t r ic r e e fe r p o in ts

C . In d iv id u a l C h a r a c te r is t ic s1 . T e r m in a l a n d p o r t le v e l :

D e p th : D e p th o f w a te r in m e te rC a ll : N u m b e r o f l in e r s c a l l in g th e te rm in a lO p e r a to r : N u m b e r o f o p e ra to r s in p o r tT e r m in a l : N u m b e r o f te rm in a ls in p o r t

2 . P o r t g r o u p d u m m ie s ( in f r a c t io n o f to ta l s a m p le ) :H P H : H u tc h is o n P o r t H o ld in g sP S A : P o r t o f S in g a p o re A u th o r i ty C o rp o ra t io nP N O : P & OS S A : S S A M a r in eM S K : M a e r s kO th e r : n o t b e lo n g to a n y o f a b o v e g ro u p s

3 . C o u n tr y le v e l:G D P : G D P in c u r r e n t U S $ (b i l l io n ) c

E X P : G o o d s e x p o r ts in c u r r e n t U S $ (b i l l io n ) c

I M P : G o o d s im p o r ts in c u r re n t U S $ (b i l l io n ) c

4 . C o n t in e n ta l D is tr ib u t io n ( in f r a c t io n o f to ta l s a m p le ) :A S : A s iaE U : E u ro p eN A : N o r th A m e r ic aL A : L a t in A m e r ic aO C : O c e a n iaA F : A f r ic aM E : M id d le E a s t

N u m b e r o f C o u n tr ie sN u m b e r o f P o r tsN u m b e r o f T e rm in a l O p e ra to r sN u m b e r o f O b s e rv a t io n s

0 .7 9 3 4 (1 .4 7 5 4 )

0 .3 3 4 6 (0 .3 4 6 1 )5 .0 6 6 7 (6 .8 3 6 2 )

4 .6 5 1 6 (4 .8 1 7 4 )1 .2 5 8 2 (1 .0 9 6 0 )5 7 1 .2 9 (8 4 1 .5 1 )

2 2 .8 3 5 (8 7 .6 9 2 )4 2 0 .2 1 (4 4 4 .8 7 )

1 2 .5 0 6 (1 .9 5 4 1 )1 5 .0 6 0 (1 3 .2 4 5 )3 .5 8 2 9 (2 .6 0 4 6 )6 .9 0 4 5 (6 .3 4 0 9 )

0 .0 40 .0 30 .0 60 .0 50 .0 20 .8 0

2 3 8 2 .8 (3 4 1 3 .7 )2 6 5 .3 2 (2 4 4 .8 9 )3 1 1 .2 6 (3 7 3 .3 9 )

0 .3 10 .2 60 .2 00 .0 60 .0 80 .0 40 .0 5

3 97 8

1 4 15 9 7

a T h e a g g re g a te d c a p a c i ty o f : ( 1 ) q u a y c r a n e s ; ( 2 ) s h ip s h o re c o n ta in e r c r a n e s .b T h e a g g re g a te d c a p a c i ty o f : ( 1 ) g a n try c r a n e s ; ( 2 ) y a rd c r a n e s ; (3 ) y a rd g a n tr ie s ; (4 ) r e a c h s ta c k e r s ; (5 ) y a rd t r a c k to r s ; ( 6 ) y a rd c h a s is t r a i le r s ;(7 ) f o rk l if ts ; ( 8 ) s t r a d d le c a r r ie r s ; (9 ) c o n ta in e r l i f te r s ; (1 0 ) m o b ile c r a n e s .c T h e c o u n try d a ta c a n b e fo u n d a t th e W o r ld B a n k w e b s i te : h t tp : / /d e v d a ta .w o r ld b a n k .o rg /d a ta o n lin e /o ld -d e fa u l t .h tm

The frontier model in economic efficiency theory, aspioneered by Arrow, Cheney, Minhas and Solow (1961) andMcFadden (1963)), is constructed via an input cost-minimization problem subject to functional technologyconstraint in term of production function, y = g(x); that is:Find an input vector that solves the following problem:

Production Frontier: Defined

The frontier model in economic efficiency theory, aspioneered by Arrow, Cheney, Minhas and Solow (1961) andMcFadden (1963)), is constructed via an input cost-minimization problem subject to functional technologyconstraint in term of production function, y = g(x); that is:Find an input vector that solves the following problem:

{ }

≥≥⋅=⋅=

=⋅= ∑=∈

0givenanyfor,)(:)(

)(s.t.

min);((PF) 1

)(

yyxgAxyL

xgAy

xwxwwyCm

jjj

t

yLx

Efficiency Measure: Stochastic Production Frontier(Aigner, Lovell and Schmidt 1977; Meeusen and Broeck 1977)

StochasticInefficiency

frontier

Actual output

Transaction Cost in Port Logistics

Port-Operator Logistics System Measures of Port Transaction Asset

Factorso Asset Specificity (operational

attributes)o Contingent Adaptive-ness

(infrastructural attributes)10/21/2010 LGT/Liu 19

Transaction Cost in Port Logistics

Port-Operator Logistics System Measures of Port Transaction Asset

Factorso Asset Specificity (operational

attributes)o Contingent Adaptive-ness

(infrastructural attributes)

Port-Operator Logistics System

y)specificitassete.g.,output;on(transactifunctionntransactio:)(

productionportcollectiveofoutput:)(

origin)legale.g.,regime,(legalattibutescticallegal/poli

control)admine.g.,density,(adaptiveattributesturalinfrastruc

operators)of#e.g.,capacity,onal(transactiattributesloperationa

)(irregularsticscharacteriinputon transacti:

handling)cargoe.g.,capacity,andcapital(regular;input technical:

3

2

1

zA

xg

z

z

z

z

x

−−−

Port

f(x,z)

Operator(s)

…..

Terminal 1

Terminal l

xg(x) A(z)

z

y

y)specificitassete.g.,output;on(transactifunctionntransactio:)(

productionportcollectiveofoutput:)(

origin)legale.g.,regime,(legalattibutescticallegal/poli

control)admine.g.,density,(adaptiveattributesturalinfrastruc

operators)of#e.g.,capacity,onal(transactiattributesloperationa

)(irregularsticscharacteriinputon transacti:

handling)cargoe.g.,capacity,andcapital(regular;input technical:

3

2

1

zA

xg

z

z

z

z

x

−−−

Port Logistics: Production + Transaction

capacityTEUe.g.,

input Regular:)( Function,n ProductioTerminal--

=x

xxg

governanceandcontroladmine.g.,

inputIrregular:)( Function,nTransactio Port--

=z

zzA

)()(),(

:)(nTransactio)(n Productio:logistics Port--

xgzAzxf

zAxg

⋅=+

),(

costnTransactiocostn Productio:costlogistics Port--

zxxw t +⋅+

Non-smooth Cost of Port Governance

5 operators

3 mixed operators

1 stevedore

Composite Port Frontier (CPF)

Composite non-smooth frontier: bothx (regular input) and z (transactioninput) as decision variables

Composite: production + transaction Non-smooth: non-smooth cost and

production output

10/21/2010 LGT/Liu 23

Composite Port Frontier (CPF)

Composite non-smooth frontier: bothx (regular input) and z (transactioninput) as decision variables

Composite: production + transaction Non-smooth: non-smooth cost and

production output

Composite Frontier (CF) Model forPort Logistics

{ }

=≥≥=

=+⋅=

∈

functiondemandgiven:)(

0givenanyfor,)()(:),()(

)()(),(s.t.

),(min);,(

:(CF)-

)(),(

pdy

yyxgzAzxyL

xgzAzxf

zxxwwzyC t

yLzx

{ }

=≥≥=

=+⋅=

∈

functiondemandgiven:)(

0givenanyfor,)()(:),()(

)()(),(s.t.

),(min);,(

:(CF)-

)(),(

pdy

yyxgzAzxyL

xgzAzxf

zxxwwzyC t

yLzx

Non-smooth Transaction Function

,,,1),,[for,)(

such that,0numbersingnondecreasofseriesa with

,offunctionstepwiseais)(where

1 iij

iji

iji

i

ij

iii

NjcczAzA

c

zzA

=∈=

≥

+

kizAzA

zAz

ii

k

i,,1),()(

:)(smooth-nonand,inputIrregular-

1=∏=

=

,,,1),,[for,)(

such that,0numbersingnondecreasofseriesa with

,offunctionstepwiseais)(where

1 iij

iji

iji

i

ij

iii

NjcczAzA

c

zzA

=∈=

≥

+

Application to Port Efficiency:

Econometrical Calibration ofComposite Port Frontier

10/21/2010 LGT/Liu 26

Application to Port Efficiency:

Econometrical Calibration ofComposite Port Frontier

Econometrical Calibration of Composite Frontier

: ModelCF− +∆−+∆− ⋅⋅=⋅= eXgZAexfy )()()(

:0) Model(201CF EmpiricalLHMY−

ttttt BXy +∆−+= ˆˆ ttttt BXy +∆−+= ˆˆ

ttt Z +Θ+= ˆ

XXZAyy lnˆ),(ln,lnˆwhere ===

inputsattributentransactio:lnˆ ZZ t =

),0(~ 2 Nt

Numerical Validation: Non-smooth Cost of Governance

Container Ports Datasets:SFA of Heterogeneous Frontier

(From TR-B by J.Yan, X.Sun, and J. Liu; 2009)

-- Single output (TEU’s): from 1997 to 2009

-- Homogeneous vs Heterogeneous (in TR-B, YSL 2009,and continuing) in production: time-variant x

-- Non-smooth Frontiers under transaction input (Ourcurrent work, and ongoing): time-invariant z

Container Ports Datasets:SFA of Heterogeneous Frontier

(From TR-B by J.Yan, X.Sun, and J. Liu; 2009)

-- Single output (TEU’s): from 1997 to 2009

-- Homogeneous vs Heterogeneous (in TR-B, YSL 2009,and continuing) in production: time-variant x

-- Non-smooth Frontiers under transaction input (Ourcurrent work, and ongoing): time-invariant z

Features should be incorporated in an empirical model1. Controlling for Individual heterogeneity:

Clustering effects (by port, country, region, andport groups);

2. Controlling for the technical change;

3. Time varying efficiency and time persistence inefficiency change;

1. Controlling for Individual heterogeneity:Clustering effects (by port, country, region, andport groups);

2. Controlling for the technical change;

3. Time varying efficiency and time persistence inefficiency change;

Overview of Current Data on Global Container Ports

The basic unit is operator.

Time period is between 1997 and 2009.

We focus on the top 100 container ports in the world(ranked in 2005)

Data was collected from different sources:Containerization International Yearbooks, World Bank,and a subscribed data base – ContainerizationInternational Intelligence

The basic unit is operator.

Time period is between 1997 and 2009.

We focus on the top 100 container ports in the world(ranked in 2005)

Data was collected from different sources:Containerization International Yearbooks, World Bank,and a subscribed data base – ContainerizationInternational Intelligence

A . O u tp u t C o n ta in e r T h ro u g h p u t in T E U s (m il l io n )B . In p u ts1 . C a r g o H a n d l in g E q u ip m e n ts :

C H Q : C a rg o h a n d lin g c a p a c i ty a t q u a y in to n n a g e (0 0 0 ’ s ) a

C H Y : C a rg o h a n d lin g c a p a c i ty a t y a rd in to n n a g e ( 0 0 0 ’ s ) b

2 . T e r m in a l I n fr a s tr u c tu r e s :B e r th : N u m b e r o f b e r thQ le n g th : L e n g th o f q u a y l in e in m e te r ( 0 0 0 ’ s )T a r e a : T e rm in a l a r e a in s q u a re d m e te r s ( 0 0 0 ’s )

3 . S to r a g e F a c i l i t ie s :S to r a g e : S to r a g e c a p a c i ty in n u m b e r o f T E U s ( 0 0 0 ’ s )R e e fe r : N u m b e r o f e le c t r ic r e e fe r p o in ts

C . In d iv id u a l C h a r a c te r is t ic s1 . T e r m in a l a n d p o r t le v e l :

D e p th : D e p th o f w a te r in m e te rC a ll : N u m b e r o f l in e r s c a l l in g th e te rm in a lO p e r a to r : N u m b e r o f o p e ra to r s in p o r tT e r m in a l : N u m b e r o f te rm in a ls in p o r t

2 . P o r t g r o u p d u m m ie s ( in f r a c t io n o f to ta l s a m p le ) :H P H : H u tc h is o n P o r t H o ld in g sP S A : P o r t o f S in g a p o re A u th o r i ty C o rp o ra t io nP N O : P & OS S A : S S A M a r in eM S K : M a e r s kO th e r : n o t b e lo n g to a n y o f a b o v e g ro u p s

3 . C o u n tr y le v e l:G D P : G D P in c u r r e n t U S $ (b i l l io n ) c

E X P : G o o d s e x p o r ts in c u r r e n t U S $ (b i l l io n ) c

I M P : G o o d s im p o r ts in c u r re n t U S $ (b i l l io n ) c

4 . C o n t in e n ta l D is tr ib u t io n ( in f r a c t io n o f to ta l s a m p le ) :A S : A s iaE U : E u ro p eN A : N o r th A m e r ic aL A : L a t in A m e r ic aO C : O c e a n iaA F : A f r ic aM E : M id d le E a s t

N u m b e r o f C o u n tr ie sN u m b e r o f P o r tsN u m b e r o f T e rm in a l O p e ra to r sN u m b e r o f O b s e rv a t io n s

0 .7 9 3 4 (1 .4 7 5 4 )

0 .3 3 4 6 (0 .3 4 6 1 )5 .0 6 6 7 (6 .8 3 6 2 )

4 .6 5 1 6 (4 .8 1 7 4 )1 .2 5 8 2 (1 .0 9 6 0 )5 7 1 .2 9 (8 4 1 .5 1 )

2 2 .8 3 5 (8 7 .6 9 2 )4 2 0 .2 1 (4 4 4 .8 7 )

1 2 .5 0 6 (1 .9 5 4 1 )1 5 .0 6 0 (1 3 .2 4 5 )3 .5 8 2 9 (2 .6 0 4 6 )6 .9 0 4 5 (6 .3 4 0 9 )

0 .0 40 .0 30 .0 60 .0 50 .0 20 .8 0

2 3 8 2 .8 (3 4 1 3 .7 )2 6 5 .3 2 (2 4 4 .8 9 )3 1 1 .2 6 (3 7 3 .3 9 )

0 .3 10 .2 60 .2 00 .0 60 .0 80 .0 40 .0 5

3 97 8

1 4 15 9 7

a T h e a g g re g a te d c a p a c i ty o f : ( 1 ) q u a y c r a n e s ; ( 2 ) s h ip s h o re c o n ta in e r c r a n e s .b T h e a g g re g a te d c a p a c i ty o f : ( 1 ) g a n try c r a n e s ; ( 2 ) y a rd c r a n e s ; (3 ) y a rd g a n tr ie s ; (4 ) r e a c h s ta c k e r s ; (5 ) y a rd t r a c k to r s ; ( 6 ) y a rd c h a s is t r a i le r s ;(7 ) f o rk l if ts ; ( 8 ) s t r a d d le c a r r ie r s ; (9 ) c o n ta in e r l i f te r s ; (1 0 ) m o b ile c r a n e s .c T h e c o u n try d a ta c a n b e fo u n d a t th e W o r ld B a n k w e b s i te : h t tp : / /d e v d a ta .w o r ld b a n k .o rg /d a ta o n lin e /o ld -d e fa u l t .h tm

A . O u tp u t C o n ta in e r T h ro u g h p u t in T E U s (m il l io n )B . In p u ts1 . C a r g o H a n d l in g E q u ip m e n ts :

C H Q : C a rg o h a n d lin g c a p a c i ty a t q u a y in to n n a g e (0 0 0 ’ s ) a

C H Y : C a rg o h a n d lin g c a p a c i ty a t y a rd in to n n a g e ( 0 0 0 ’ s ) b

2 . T e r m in a l I n fr a s tr u c tu r e s :B e r th : N u m b e r o f b e r thQ le n g th : L e n g th o f q u a y l in e in m e te r ( 0 0 0 ’ s )T a r e a : T e rm in a l a r e a in s q u a re d m e te r s ( 0 0 0 ’s )

3 . S to r a g e F a c i l i t ie s :S to r a g e : S to r a g e c a p a c i ty in n u m b e r o f T E U s ( 0 0 0 ’ s )R e e fe r : N u m b e r o f e le c t r ic r e e fe r p o in ts

C . In d iv id u a l C h a r a c te r is t ic s1 . T e r m in a l a n d p o r t le v e l :

D e p th : D e p th o f w a te r in m e te rC a ll : N u m b e r o f l in e r s c a l l in g th e te rm in a lO p e r a to r : N u m b e r o f o p e ra to r s in p o r tT e r m in a l : N u m b e r o f te rm in a ls in p o r t

2 . P o r t g r o u p d u m m ie s ( in f r a c t io n o f to ta l s a m p le ) :H P H : H u tc h is o n P o r t H o ld in g sP S A : P o r t o f S in g a p o re A u th o r i ty C o rp o ra t io nP N O : P & OS S A : S S A M a r in eM S K : M a e r s kO th e r : n o t b e lo n g to a n y o f a b o v e g ro u p s

3 . C o u n tr y le v e l:G D P : G D P in c u r r e n t U S $ (b i l l io n ) c

E X P : G o o d s e x p o r ts in c u r r e n t U S $ (b i l l io n ) c

I M P : G o o d s im p o r ts in c u r re n t U S $ (b i l l io n ) c

4 . C o n t in e n ta l D is tr ib u t io n ( in f r a c t io n o f to ta l s a m p le ) :A S : A s iaE U : E u ro p eN A : N o r th A m e r ic aL A : L a t in A m e r ic aO C : O c e a n iaA F : A f r ic aM E : M id d le E a s t

N u m b e r o f C o u n tr ie sN u m b e r o f P o r tsN u m b e r o f T e rm in a l O p e ra to r sN u m b e r o f O b s e rv a t io n s

0 .7 9 3 4 (1 .4 7 5 4 )

0 .3 3 4 6 (0 .3 4 6 1 )5 .0 6 6 7 (6 .8 3 6 2 )

4 .6 5 1 6 (4 .8 1 7 4 )1 .2 5 8 2 (1 .0 9 6 0 )5 7 1 .2 9 (8 4 1 .5 1 )

2 2 .8 3 5 (8 7 .6 9 2 )4 2 0 .2 1 (4 4 4 .8 7 )

1 2 .5 0 6 (1 .9 5 4 1 )1 5 .0 6 0 (1 3 .2 4 5 )3 .5 8 2 9 (2 .6 0 4 6 )6 .9 0 4 5 (6 .3 4 0 9 )

0 .0 40 .0 30 .0 60 .0 50 .0 20 .8 0

2 3 8 2 .8 (3 4 1 3 .7 )2 6 5 .3 2 (2 4 4 .8 9 )3 1 1 .2 6 (3 7 3 .3 9 )

0 .3 10 .2 60 .2 00 .0 60 .0 80 .0 40 .0 5

3 97 8

1 4 15 9 7

a T h e a g g re g a te d c a p a c i ty o f : ( 1 ) q u a y c r a n e s ; ( 2 ) s h ip s h o re c o n ta in e r c r a n e s .b T h e a g g re g a te d c a p a c i ty o f : ( 1 ) g a n try c r a n e s ; ( 2 ) y a rd c r a n e s ; (3 ) y a rd g a n tr ie s ; (4 ) r e a c h s ta c k e r s ; (5 ) y a rd t r a c k to r s ; ( 6 ) y a rd c h a s is t r a i le r s ;(7 ) f o rk l if ts ; ( 8 ) s t r a d d le c a r r ie r s ; (9 ) c o n ta in e r l i f te r s ; (1 0 ) m o b ile c r a n e s .c T h e c o u n try d a ta c a n b e fo u n d a t th e W o r ld B a n k w e b s i te : h t tp : / /d e v d a ta .w o r ld b a n k .o rg /d a ta o n lin e /o ld -d e fa u l t .h tm

Base model Model ignoringtechnical change

Model ignoring unobs.heter.

Mean Efficiency Median Estimate[5%-ile, 95%-ile]

Median Estimate[5%-ile, 95%-ile]

Median Estimate[5%-ile, 95%-ile]

1997 – 1998

1999 – 2001

2002 – 2004

0.8072[0.7009, 0.8293]

0.8393[0.7406, 0.9153]

0.8423[0.7415, 0.8986]

0.7015[0.6221, 0.7832]

0.7816[0.7202, 0.8675]

0.8602[0.7867, 0.9267]

0.4138[0.3376, 0.4880]

0.4267[0.3652, 0.4825]

0.4344[0.3676, 0.4925]

Mean Efficiency Levels

Base model Model ignoringtechnical change

Model ignoring unobs.heter.

Mean Efficiency Median Estimate[5%-ile, 95%-ile]

Median Estimate[5%-ile, 95%-ile]

Median Estimate[5%-ile, 95%-ile]

1997 – 1998

1999 – 2001

2002 – 2004

0.8072[0.7009, 0.8293]

0.8393[0.7406, 0.9153]

0.8423[0.7415, 0.8986]

0.7015[0.6221, 0.7832]

0.7816[0.7202, 0.8675]

0.8602[0.7867, 0.9267]

0.4138[0.3376, 0.4880]

0.4267[0.3652, 0.4825]

0.4344[0.3676, 0.4925]

Figure 2: The estimated distribution of individual efficiency level. The plotted density functions

are estimated by kernel densities using Epanechnikov kernel and Silverman's (1985) rule-of-thumb

bandwidth selector.

Figure 2: The estimated distribution of individual efficiency level. The plotted density functions

are estimated by kernel densities using Epanechnikov kernel and Silverman's (1985) rule-of-thumb

bandwidth selector.

Base model Model with translogfrontier a

Model with multivariatehalf normal distributed

inefficiency b

Mean Efficiency Median Estimate[5%-ile, 95%-ile]

Median Estimate[5%-ile, 95%-ile]

Median Estimate[5%-ile, 95%-ile]

1997 – 1998

1999 – 2001

2002 – 2004

0.8072[0.7009, 0.8293]

0.8393[0.7406, 0.9153]

0.8423[0.7415, 0.8986]

0.7748[0.6751, 0.8628]

0.7923[0.7056, 0.8824]

0.8164[0.7233, 0.8953]

0.7134[0.6416, 0.7748]

0.7335[0.6680, 0.7823]

0.7032[0.6362, 0.7541]

a This model is the variation from the base model by replacing the Cobb-Douglas productionfrontier with the translog production frontier.

b This model is the variation from the base model by changing the inefficiency specification

as

Sensitivity AnalysisBase model Model with translog

frontier aModel with multivariatehalf normal distributed

inefficiency b

Mean Efficiency Median Estimate[5%-ile, 95%-ile]

Median Estimate[5%-ile, 95%-ile]

Median Estimate[5%-ile, 95%-ile]

1997 – 1998

1999 – 2001

2002 – 2004

0.8072[0.7009, 0.8293]

0.8393[0.7406, 0.9153]

0.8423[0.7415, 0.8986]

0.7748[0.6751, 0.8628]

0.7923[0.7056, 0.8824]

0.8164[0.7233, 0.8953]

0.7134[0.6416, 0.7748]

0.7335[0.6680, 0.7823]

0.7032[0.6362, 0.7541]

a This model is the variation from the base model by replacing the Cobb-Douglas productionfrontier with the translog production frontier.

b This model is the variation from the base model by changing the inefficiency specification

as ( ) ( ).,0~,,,020499019798 321321 Nddd iiiiiiit′⋅+⋅+⋅=

Explanatory Conclusion

TEU-only rankings without TCE tend to over estimateport performance: 1) Cost of governance ignored; 2)Cost of adaptation (e.g., optimal z) ignored

Coexist of single-operator (e.g., Singapore) and multi-operator (e.g., Hong Kong) ports: can be explained byTCE, especially by legal origin theory.

Coexist stevedore and carrier terminal operators: canbe explained by infrastructural transaction costs,especially the mode of governance

10/21/2010 LGT/Liu 36

Explanatory Conclusion

TEU-only rankings without TCE tend to over estimateport performance: 1) Cost of governance ignored; 2)Cost of adaptation (e.g., optimal z) ignored

Coexist of single-operator (e.g., Singapore) and multi-operator (e.g., Hong Kong) ports: can be explained byTCE, especially by legal origin theory.

Coexist stevedore and carrier terminal operators: canbe explained by infrastructural transaction costs,especially the mode of governance

Thank You！Thank You！