Transaction Cost Economics of Port Performance: A Composite Frontier Analysis

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, 2010 1 JJ Liu 10/21/2010

ABSTRACT o o o o Derive transaction cost characteristics of port logistics Verify and test them against the theory of transaction cost economics (Williamson 2002, 2008): Firm as a governance structure: Governance cost is inevitable Governance cost: a nonlinear function of asset specificity (k) within a certain mode of governance Transaction cost Address research questions of: The implication of omitting TCE from port efficiency analysis (e.g., DEA and SFA, both excluding TCE) Implications of TEC for port logistics: TEU-only rankings? Impact of ownership structure, and legal origin?

Outlines o o Port performance: Port production, port governance Transaction cost economics (Williamson 2002, 2008): From choice to contract; cost of governance 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 TEUonly 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

Research Questions: To explain Why TEU-only rankings of ports? What s missing? Why coexist single-operator (e.g., Singapore) and multi-operator (e.g., Hong Kong) ports? Why coexist stevedore and carrier terminal operators? 10/21/2010 LGT/Liu 5

Current Port Logistics Studies Port: The Firm as a Production Function Port logistics: Broadly defined as transport logistics of seaport, airport, and dry port,. Port as a production function: The classical theory of 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 governance structure Port as a governance structure of terminal production 10/21/2010 LGT/Liu 6

Transaction Cost Economics The Firm Theory: Production Function versus Governance Structure From Choice to Contract Cost of Contract Governance 10/21/2010 LGT/Liu 7

Firm as a Governance Structure (1): From Choice to Contract [Williamson, 2002] Science of Choice: Theory of firm as production function Economics throughout the twentieth century has been developed predominantly as a science of choice.... Choice has been developed in two parallel constructions: the theory of consumer behavior, in which consumers maximie utility, and the theory of the firm as production function, in which firms maximie profit. 10/21/2010 LGT/Liu 8

Firm as Governance Structure: From Choice to Contract [Williamson, 2002] Science of Contract: Theory of firm as governance structure. By contrast with mechanism design and agent theory of the firm, contract/governance approach associates a firm with three critical attributes, namely, incentive intensity, administrative control and contract law regime. 10/21/2010 LGT/Liu 9

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; Governance structures differ in costs and competencies 10/21/2010 LGT/Liu 11

Transaction Cost Economics Transaction cost: Asset specificity (which gives rise to bilateral dependency) and uncertainty (which poses adaptive needs) of transaction incur different transaction cost consequences (highly non-linear) under different modes and attributes (heterogeneous) of governance structure. Adaptive regulation: The requisite mix of autonomous adaptations and coordinated adaptations vary among transactions. Specifically, the need for coordinated adaptations builds up as asset specificity deepens. (Williamson, 2002) 10/21/2010 LGT/Liu 12

Governance: Regular v.s. Contingent Contingent risk: Disruption to Equilibrium Classical control: speed, rate, differential dynamics Impulse control: position, injection, stimulus impulse Speed

Heuristic Model of Firm as Governance Structure: Heterogeneous and non-linear Costs [Williamson, 2002] Markets mode Hybrid mode Hierarchies

Review: Efficiency Frontier Models Classical Frontier Model Applications to port performance: DEA and SFA for port level performance; v.s. terminal level 10/21/2010 LGT/Liu 15

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 illio n ) B. In p u ts 1. C a r g o H a n d lin 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 ity a t q u a y in to n n a g e (0 0 0 s) a b C H Y : C a rg o h a n d lin g c a p a c ity a t y a rd in to n n a g e (0 0 0 s) 2. T e r m in a l In fr a s tr u c tu r e s : B e r th : N u m b e r o f b e rth Q le n g th : L e n g th o f q u a y lin e in m e te r (0 0 0 s) T a r e a : T e rm in a l a re a in s q u a re d m e te rs (0 0 0 s) 3. S to r a g e F a c ilitie s : S to r a g e : S to ra g e c a p a c ity 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 tric re e fe r p o in ts C. In d iv id u a l C h a r a c te r is tic s 1. 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 r C a ll: N u m b e r o f lin e rs c a llin g th e te rm in a l O p e r a to r : N u m b e r o f o p e ra to rs in p o rt T e r m in a l: N u m b e r o f te rm in a ls in p o rt 2. P o r t g r o u p d u m m ie s (in fr a c tio n o f to ta l s a m p le ): H P H : H u tc h is o n P o rt H o ld in g s P S A : P o rt o f S in g a p o re A u th o rity C o rp o ra tio n P N O : P & O S S A : S S A M a rin e M S K : M a e rs k O 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 rre n t U S $ (b illio n) c E X P : G o o d s e x p o rts in c u rre n t U S $ (b illio n) c I M P : G o o d s im p o rts in c u rre n t U S $ (b illio n) c 4. C o n tin e n ta l D is tr ib u tio n (in fr a c tio n o f to ta l s a m p le ): A S : A s ia E U : E u ro p e N A : N o rth A m e ric a L A : L a tin A m e ric a O C : O c e a n ia A F : A fric a M E : M id d le E a s t 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 4 0.0 3 0.0 6 0.0 5 0.0 2 0.8 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 1 0.2 6 0.2 0 0.0 6 0.0 8 0.0 4 0.0 5 N u m b e r o f C o u n trie s N u m b e r o f P o rts N u m b e r o f T e rm in a l O p e ra to rs N u m b e r o f O b s e rv a tio n s a T h e a g g re g a te d c a p a c ity o f : (1) q u a y c ra n e s ; (2) s h ip s h o re c o n ta in e r c ra n e s. T h e a g g re g a te d c a p a c ity o f : (1) g a n try c ra n e s ; (2) y a rd c ra n e s ; (3) y a rd g a n trie s ; (4) re a c h s ta c k e rs ; (5) y a rd tra c k to rs ; (6) y a rd c h a s is tra ile rs ; (7) fo rk lifts ; (8) s tra d d le c a rrie rs ; (9) c o n ta in e r lifte rs ; (1 0) m o b ile c ra 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 rld B a n k w e b s ite : h ttp ://d e v d a ta.w o rld b a n k.o rg /d a ta o n lin e /o ld -d e fa u lt.h tm 3 9 7 8 1 4 1 5 9 7

Production Frontier: Defined The frontier model in economic efficiency theory, as pioneered by Arrow, Cheney, Minhas and Solow (1961) and McFadden (1963)), is constructed via an input costminimiation problem subject to functional technology constraint in term of production function, y = g(x); that is: Find an input vector that solves the following problem: (PF) m t C( y; w) = min w x = w x L ( y) j= 1 s.t. y = A g( x) L( y) = { x : A g( x) y} j x, j for any given y 0

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

Transaction Cost in Port Logistics Port-Operator Logistics System Measures of Port Transaction Asset Factors o Asset Specificity (operational attributes) o Contingent Adaptive-ness (infrastructural attributes) 10/21/2010 LGT/Liu 19

x Port-Operator Logistics System Operator(s) Terminal 1.. Port y g(x) A() f(x,) g( x) : outputof A( ) : Terminal l x : technicalinput(regular;capitaland capacity,e.g.,cargohandling) : transaction inputcharacteristics(irregular) 1 2 3 operational attributes(transactionalcapacity,e.g.,# of infrastructuralattributes(adaptivedensity,e.g.,admincontrol) legal/policticalattibutes(legalregime,e.g.,legalorigin) collectiveport production operators) transaction function(transaction output;e.g.,asset specificity)

Port Logistics: Production + Transaction - - Terminal Production Function, g( x) : Regular input x e.g., x = TEU capacity - - Port Transaction Function, A( ) : Irregular input e.g., = admin control and governance - - Port logistics: Production g( x) + Transaction A( ) : f ( x, ) = A( ) g( x) - - Port logistics cost : Productio n cost + Transactio n cost w x t + ( x, )

Non-smooth Cost of Port Governance 5 operators 3 mixed operators 1 stevedore

Composite Port Frontier (CPF) Composite non-smooth frontier: both x (regular input) and (transaction input) as decision variables Composite: production + transaction Non-smooth: non-smooth cost and production output 10/21/2010 LGT/Liu 23

Composite Frontier (CF) Model for Port Logistics { } = + = ) ( ) ( ), ( s.t. ), ( min ) ;, ( : (CF) - ) ( ), ( x g A x f x x w w y C t y L x { } = = given demand function : ) ( 0 any given for, ) ( ) ( : ), ( ) ( : (CF) - p d y y y x g A x y L

Non-smooth Transaction Function, of function stepwise a is ) ( where i i i A k i A A A i i k i, 1, ), ( ) ( : ) ( smooth - non and, input Irregular - 1 = = =,, 1, ),, [ for, ) ( such that 0, nondecreasing numbers of series a with, of function stepwise a is ) ( where 1 i i j i j i i j i i i j i i N j c c A A c A = = +

Application to Port Efficiency: Econometrical Calibration of Composite Port Frontier 10/21/2010 LGT/Liu 26

Econometrical Calibration of Composite Frontier CF Model : y = f ( x) e = A( Z ) g( X ) e + + LHMY Empirical CF Model(2010) : y ˆ t = + X ˆ B + t = ˆ + t + ZtΘ t t t where yˆ = ln y, = lna( Z ), Xˆ = ln X Zˆ t = lnz : transactio n attribute inputs t ~ N (0, 2 ) t

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 (Our current work, and ongoing): time-invariant

Features should be incorporated in an empirical model 1. Controlling for Individual heterogeneity: Clustering effects (by port, country, region, and port groups); 2. Controlling for the technical change; 3. Time varying efficiency and time persistence in efficiency 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: Containeriation International Yearbooks, World Bank, and a subscribed data base Containeriation International Intelligence

Mean Efficiency Levels Base model Model ignoring technical change Model ignoring unobs. heter. Mean Efficiency 1997 1998 Median Estimate [5%-ile, 95%-ile] 0.8072 [0.7009, 0.8293] Median Estimate [5%-ile, 95%-ile] 0.7015 [0.6221, 0.7832] Median Estimate [5%-ile, 95%-ile] 0.4138 [0.3376, 0.4880] 1999 2001 0.8393 [0.7406, 0.9153] 0.7816 [0.7202, 0.8675] 0.4267 [0.3652, 0.4825] 2002 2004 0.8423 [0.7415, 0.8986] 0.8602 [0.7867, 0.9267] 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.

Sensitivity Analysis Mean Efficiency 1997 1998 Base model Median Estimate [5%-ile, 95%-ile] 0.8072 [0.7009, 0.8293] Model with translog frontier a Median Estimate [5%-ile, 95%-ile] 0.7748 [0.6751, 0.8628] Model with multivariate half normal distributed inefficiency b Median Estimate [5%-ile, 95%-ile] 0.7134 [0.6416, 0.7748] 1999 2001 0.8393 [0.7406, 0.9153] 0.7923 [0.7056, 0.8824] 0.7335 [0.6680, 0.7823] 2002 2004 0.8423 [0.7415, 0.8986] 0.8164 [0.7233, 0.8953] 0.7032 [0.6362, 0.7541] a This model is the variation from the base model by replacing the Cobb-Douglas production frontier with the translog production frontier. b This model is the variation from the base model by changing the inefficiency specification as it = i1 d9798+ i2 d9901+ i3 d0204, ( i1, i2, i3 ) ~ N( 0, ).

Explanatory Conclusion TEU-only rankings without TCE tend to over estimate port performance: 1) Cost of governance ignored; 2) Cost of adaptation (e.g., optimal ) ignored Coexist of single-operator (e.g., Singapore) and multioperator (e.g., Hong Kong) ports: can be explained by TCE, especially by legal origin theory. Coexist stevedore and carrier terminal operators: can be explained by infrastructural transaction costs, especially the mode of governance 10/21/2010 LGT/Liu 36

Thank You!