Disbursement profile for Large-Scale Infrastructure Projects

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Transcript Disbursement profile for Large-Scale Infrastructure Projects

An Empirical Assessment
of Vietnam’s
Public Investment Program
1996-2000
Theo Ib Larsen and Martin Rama
The World Bank
Workshop on Development of Large-Scale Infrastructure for
Growth and Poverty Reduction
Hanoi, September 25, 2003
The Issue

The PIP amounts to roughly 18 % of GDP

It consists of hundreds of projects in a
variety of sectors

The impact of those projects is seldom
assessed
The Project Approach

A rate of return is computed
 It compares an upfront cost (I)
 To a long-term flow of additional income
(ΔY)
 But only direct income (YD) is taken into
account
The Statistical Approach

The impact on an outcome is computed
 It evaluates the immediate change in
income (ΔY)
 Associated with public spending (I)
 But only local income (YL) is taken into
account
The Shortcomings of these
Approaches

The project approach ignores indirect effects
(such as job creation or congestion)
Which are common in developing countries

The statistical approach ignores network effects
(such as connecting distant places to a grid)
Which are typical of large-scale infrastructure
The Nature of Large-Scale
Infrastructure Impacts
Elsewhere
Total
Examples:
E: Increased power supply
T: Long-haul traffic
S: Probably none
ΔYD
Direct
Examples:
E: Electric connections
T: Local traffic
S: Water and sanitation
Indirect
Mechanisms:
Job creation
Lower congestion
Increased formality
Total
E: Electricity consumption
T: Total traffic
S: Water connections
Externalities
?

ΔYL
ΔY
Increased local output,
from all sources
Increased output,
from all sources
Network Effects
Externalities
Local

The project approach and the
statistical approach need
to be combined

This presentation is a first step in that
direction
 It uses the 1996-2000 PIP as an illustration
Quantifying Growth Impacts
a. From Rates of Return
Y
g
Y
Growth rate
of GDP
(in %)

Y D  Y D  I


Y
 I  Y



r

Rate of return
of the project
( in %)
I
Y
Investment
volume (in %
of total GDP)
x
b. From Estimated Elasticities
Y
g
Y
Growth rate
of GDP
(in %)


Y L  Y L

Y
 YL

I  I
  Y
L
Y
Provincial
elasticity of GDP
to investment

x


I
Y
Investment
volume (in %
of total GDP)
Quantifying Poverty Reduction
Impacts
a. From Rates of Return

p  P   P

Y  Y
 
Y  Y
Poverty
Elasticity of
reduction
 poverty reduction
(in % points)
to growth
   g   r 
I
Y
Rate of return
Investment
X of the project X volume (in %
( in %)
of total GDP)
b. From Estimated Elasticities
p  P
Poverty
reduction (in
% points)



 P L   P L

I  I

 L
L
Y  Y
Provincial elasticity
of poverty reduction
to investment
X
 
I
YL
Investment
volume (in % of
provincial GDP)
The Empirical Strategy


To generate a database of large-scale
infrastructure projects from the 1996-2000 PIP
Based on actual (not planned) spending
 By main sector
 By province
 By year of spending
 By funding

And to match it with provincial growth and
poverty indicators
First difficulty:
Assessing actual spending per
year

Delays in implementation in most projects
 Scattered information on disbursement
 Inconsistencies between donors and PMUs
Second
difficulty:
allocating
spending
by province
Projects in the Database
Projects (number)
Investment Volume (billion VND)
Sector
PIP 1996 2000
Database
Share
PIP 1996 2000
Database
Share
Energy
14
9
64 %
46,301
44,624
96 %
Transport
Urban Water
/Sanitation
42
27
64 %
64,622
60,832
94 %
35
14
40 %
19,316
14,500
75 %
Irrigation
Large-Scale
infrastructure
16
5
31 %
12,014
9,293
77 %
107
55
50 %
142,253
129,249
91 %
Other sectors
124
0
0%
183,263
0
0%
Total
231
55
32 %
325,516
129,249
40%
Funding for Large-Scale
Infrastructure
Planned (in billion VND)
Sector
Actual (in billion VND)
Total
Government
ODA
Total
Government
ODA
46,301
13,435
33,003
25,743
4,799
20,680
64,622
16,324
49,098
49,534
16,033
33,558
19,316
4,529
14,876
6,061
1,356
4,705
12,014
6,379
5,644
2,863
488
2,375
142,253
40,667
102,621
84,202
22,676
61,318
Energy
Transport
Urban Water
/Sanitation
Irrigation
Large-Scale
infrastructure
Donors and the PIP
VND billion
Share of total
ODA
Share of total
Investment
40,707
40 %
29 %
13,623
13 %
11 %
Asian Development
Bank
10,136
10 %
8%
Others and nonidentified
38,488
37 %
25 %
102,621
100 %
73 %
Japan
World Bank
Large-scale
infrastructure
Delays in implementation are
considerable
160,000
140,000
120,000
100,000
80,000
60,000
40,000
20,000
0
Original PIP
1996 -2000
1996 Actual
1997 Actual
1998 Actual
1999 Actual
2000 Actual
But they vary across donors
%
140
%
120
120
100
100
80
80
60
60
40
40
20
20
0
0
1996 - 2000 1996 Actual 1997 Actual 1998 Actual 1999 Actual 2000 Actual
PIP
Donor A
1996 2000 PIP
1996
Actual
1997
Actual
Donor B
1998
Actual
1999
Actual
2000
Actual
Few empirical results to report

The database still needs to be adjusted
 In the meantime, findings are not reliable
Communes with road
in % points)
(addition
Still, some preliminary
evidence of externalities
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
1
2
3
4
Investment (% of provincial GDP)
Energy
Transport
Despite controlling for unobservable province
characteristics
Conclusion

Assessing growth and poverty impacts of
the PIP is not impossible
 It requires combining the project approach
 And the statistical approach
 It also requires a good information system
 To monitor project implementation