4287
Views
2609
Downloads |
Public investment for sustainable growth – managing subnational risks
Ehtisham Ahmad* 
Ehtisham Ahmad
Affiliation: London School of Economics and Political Science, London, UK University of Bonn, Bonn, Germany Zhejiang University, Hangzhou, Zhejiang Province, P. R. China
 0000-0002-6054-3336
Correspondence
s.e.ahmad@lse.ac.uk
Conference keynote | Year: 2017 | Pages: 137 - 157 | Volume: 41 | Issue: 2 Received: May 17, 2017 | Accepted: May 25, 2017 | Published online: June 15, 2017
|
FULL ARTICLE
FIGURES & DATA
REFERENCES
CROSSMARK POLICY
METRICS
LICENCING
PDF
|
Goods/inputs
|
Conversion
factor
|
|
Social
discount rate
|
6%
(8% and 12% in previous years)
|
|
Exchange
rate
|
1.01
|
|
Emissions
(CO2)
|
2.213
pesos per ton of equivalent carbon emission
|
|
Land
|
Market
value (without any correction)
|
|
Domestic
goods and inputs
|
Market
value – VAT
|
|
Importable
materials
|
(Market
value-duties) x currency conversion factor
|
|
Fuels
|
Depends
on type of fuel and vehicle
|
|
High-skill
labor
|
Market
value x factor of conversion for high-skilled labor (0.98)
|
|
Medium-skill
labor
|
Market
value x factor of conversion for mid-skilled labor (0.68)
|
|
Low-skill
labor
|
Market
value x factor of conversion for low-skilled labor (0.62)
|
|
General
expenses and profits
|
Market
value – VAT
|
See Ahmad and Viscarra (2016).
|
|
|
K=0.81
|
K=0.5
|
K=0.25
|
|
Groups
|
Class
|
L=0.37
M=0.40
H=0.70
|
L=0.62
M=0.68
H=0.98
|
L=0.87
M=0.90
H=1.00
|
L=0.37
M=0.4
H=0.7
|
L=0.62
M=0.68
H=0.98
|
L=0.87
M=0.90
H=1.00
|
L=0.37
M=0.40
H=0.70
|
L=0.62
M=0.68
H=0.98
|
L=0.87
M=0.93
H=1.00
|
|
Flour, pasta, cereals
|
IM
|
0.986
|
0.986
|
0.986
|
0.986
|
0.986
|
0.986
|
0.986
|
0.986
|
0.986
|
|
Vegetables
|
EX
|
0.934
|
0.929
|
0.929
|
0.935
|
0.931
|
0.93
|
0.936
|
0.932
|
0.932
|
|
Fruits
|
EX
|
0.541
|
0.538
|
0.537
|
0.542
|
0.539
|
0.539
|
0.543
|
0.54
|
0.539
|
|
Meats, sausages
|
IM
|
0.988
|
0.988
|
0.988
|
0.988
|
0.988
|
0.988
|
0.988
|
0.988
|
0.988
|
|
Dairy products, cheese,
eggs
|
NT
|
0.988
|
1.134
|
1.208
|
0.954
|
1.074
|
1.174
|
0.927
|
1.047
|
1.147
|
|
Edible oils, fats
|
IM
|
0.987
|
0.987
|
0.987
|
0.987
|
0.987
|
0.987
|
0.987
|
0.987
|
0.987
|
|
Fish, crustaceans, mollusks
|
EX
|
0.985
|
0.982
|
0.981
|
0.986
|
0.983
|
0.982
|
0.987
|
0.984
|
0.983
|
|
Animal feed
|
NT
|
0.635
|
0.755
|
0.86
|
0.611
|
0.73
|
0.836
|
0.591
|
0.711
|
0.816
|
|
Fuels
|
IM
|
0.991
|
0.991
|
0.991
|
0.991
|
0.991
|
0.991
|
0.991
|
0.991
|
0.991
|
|
Other food products
|
IM
|
0.977
|
0.977
|
0.977
|
0.977
|
0.977
|
0.977
|
0.977
|
0.977
|
0.977
|
|
Liquor
|
EX
|
0.961
|
0.953
|
0.952
|
0.965
|
0.956
|
0.955
|
0.967
|
0.958
|
0.957
|
|
Non-alcoholic beverages
|
NT
|
0.550
|
0.661
|
0.682
|
0.513
|
0.625
|
0.645
|
0.484
|
0.595
|
0.616
|
|
Tobacco
|
NT
|
0.464
|
0.556
|
0.585
|
0.437
|
0.529
|
0.558
|
0.415
|
0.507
|
0.536
|
|
Textiles, clothing,
footwear
|
IM
|
0.982
|
0.982
|
0.982
|
0.982
|
0.982
|
0.982
|
0.982
|
0.982
|
0.982
|
|
Material for conservation,
repair of dwelling
|
IM
|
0.949
|
0.949
|
0.949
|
0.949
|
0.949
|
0.949
|
0.949
|
0.949
|
0.949
|
|
Stationery, office supplies
|
EX
|
0.975
|
0.969
|
0.968
|
0.977
|
0.971
|
0.97
|
0.978
|
0.973
|
0.972
|
|
Printing, publishing
|
NT
|
0.653
|
0.846
|
1.014
|
0.63
|
0.823
|
0.991
|
0.611
|
0.805
|
0.973
|
|
Pharmaceutical products
|
NT
|
0.678
|
0.856
|
0.888
|
0.652
|
0.829
|
0.861
|
0.631
|
0.808
|
0.84
|
|
Toiletries, cosmetics
|
NT
|
0.847
|
1.064
|
1.098
|
0.827
|
1.044
|
1.078
|
0.811
|
1.028
|
1.062
|
|
Glassware, crystal,
tableware, household utensils
|
NT
|
0.535
|
0.639
|
0.65
|
0.498
|
0.602
|
0.613
|
0.468
|
0.572
|
0.583
|
|
Electronic artifacts, large
size tools, equipment for the household
|
NT
|
0.664
|
0.83
|
0.853
|
0.644
|
0.81
|
0.833
|
0.627
|
0.794
|
0.817
|
|
Electronic artifacts, small
size tools, equipment for the household
|
NT
|
0.692
|
0.853
|
0.87
|
0.675
|
0.837
|
0.853
|
0.662
|
0.824
|
0.84
|
|
Furniture
|
NT
|
0.655
|
0.847
|
1.012
|
0.592
|
0.785
|
0.95
|
0.542
|
0.735
|
0.899
|
|
Other electronic artifacts,
tools, equipment for the household
|
NT
|
0.563
|
0.686
|
0.793
|
0.54
|
0.662
|
0.77
|
0.521
|
0.644
|
0.751
|
|
Electricity
|
NT
|
1.051
|
1.111
|
1.121
|
0.784
|
0.845
|
0.855
|
0.569
|
0.63
|
0.64
|
|
Gas supply
|
IM
|
0.995
|
0.995
|
0.995
|
0.995
|
0.995
|
0.995
|
0.995
|
0.995
|
0.995
|
|
Basic public services
|
NT
|
1.043
|
1.248
|
1.27
|
0.896
|
1.100
|
1.122
|
0.776
|
0.981
|
1.003
|
|
Repair of household goods
|
NT
|
0.732
|
0.936
|
0.969
|
0.71
|
0.913
|
0.946
|
0.691
|
0.894
|
0.927
|
|
Hotels, restaurants
|
NT
|
1.036
|
1.232
|
1.389
|
0.999
|
1.193
|
1.352
|
0.968
|
1.163
|
1.321
|
|
Transportation
|
NT
|
0.645
|
0.79
|
0.811
|
0.593
|
0.738
|
0.759
|
0.55
|
0.696
|
0.717
|
|
Mail, courier services
|
NT
|
0.541
|
0.758
|
0.938
|
0.509
|
0.725
|
0.905
|
0.482
|
0.699
|
0.879
|
|
Telephone services
|
NT
|
0.877
|
1.026
|
1.059
|
0.72
|
0.868
|
0.902
|
0.593
|
0.741
|
0.775
|
|
Financial services
|
NT
|
0.41
|
0.525
|
0.539
|
0.386
|
0.501
|
0.516
|
0.367
|
0.482
|
0.497
|
|
Assurance, reinsurance
services
|
NT
|
0.706
|
0.893
|
0.918
|
0.651
|
0.838
|
0.863
|
0.607
|
0.794
|
0.819
|
|
Services to companies
|
NT
|
0.570
|
0.709
|
0.728
|
0.518
|
0.656
|
0.675
|
0.475
|
0.614
|
0.633
|
|
Rents (apartments, houses)
|
NT
|
1.026
|
1.031
|
1.032
|
0.702
|
0.708
|
0.708
|
0.441
|
0.446
|
0.447
|
|
Education
|
NT
|
0.820
|
1.066
|
1.091
|
0.793
|
1.039
|
1.064
|
0.772
|
1.018
|
1.043
|
|
Medical, health services
|
NT
|
0.768
|
0.985
|
1.011
|
0.735
|
0.952
|
0.978
|
0.708
|
0.926
|
0.952
|
|
Entertainment
|
NT
|
0.673
|
0.911
|
1.121
|
0.621
|
0.859
|
1.069
|
0.579
|
0.817
|
1.027
|
|
Other services
|
NT
|
0.217
|
0.282
|
0.336
|
0.191
|
0.256
|
0.31
|
0.17
|
0.235
|
0.288
|
|
Mining
|
EX
|
0.981
|
0.976
|
0.976
|
0.982
|
0.978
|
0.977
|
0.983
|
0.979
|
0.978
|
|
Construction
|
NT
|
0.563
|
0.713
|
0.845
|
0.543
|
0.693
|
0.824
|
0.526
|
0.676
|
0.807
|
|
Commerce
|
NT
|
0.553
|
0.734
|
0.87
|
0.518
|
0.699
|
0.834
|
0.489
|
0.67
|
0.806
|
|
Chemical industry
|
IM
|
0.989
|
0.989
|
0.989
|
0.989
|
0.989
|
0.989
|
0.989
|
0.989
|
0.989
|
|
Basic industry metals
|
EX
|
0.974
|
0.97
|
0.969
|
0.976
|
0.972
|
0.971
|
0.977
|
0.973
|
0.972
|
L = low-skilled labor; M = medium-skilled labor; H = high-skilled labor, K = capital, IM = importable sectors; EX = exportable sectors; NT = non-tradable sectors. Source: Ahmad and Viscarra (2016). Calculations based on the input-output matrix 2008, Central Bank of Chile.
|
|
K=0.81
(A1)
|
K=0.5
(A2)
|
K=0.25
(A3)
|
|
Groups
|
L=0.37
M=0.43
H=0.73
|
L=0.62
M=0.68
H=0.98
|
L=0.87
M=0.93
H=1
|
L=0.37
M=0.43
H=0.73
|
L=0.62
M=0.68
H=0.98
|
L=0.87
M=0.93
H=1
|
L=0.37
M=0.43
H=0.73
|
L=0.62
M=0.68
H=0.98
|
L=0.87
M=0.93
H=1
|
|
Flour, pasta, cereals
|
0.404
|
0.409
|
0.321
|
0.435
|
0.445
|
0.351
|
0.459
|
0.470
|
0.376
|
|
Vegetables
|
0.395
|
0.380
|
0.316
|
0.430
|
0.426
|
0.351
|
0.458
|
0.454
|
0.379
|
|
Fruits
|
-0.030
|
-0.089
|
-0.317
|
0.046
|
0.006
|
-0.240
|
0.108
|
0.067
|
-0.178
|
|
Meats, sausages
|
0.255
|
0.260
|
0.182
|
0.280
|
0.299
|
0.207
|
0.301
|
0.320
|
0.227
|
|
Oils, fats
|
0.354
|
0.355
|
0.311
|
0.368
|
0.369
|
0.325
|
0.379
|
0.380
|
0.336
|
|
Fish, crustaceans, mollusks
|
0.228
|
0.242
|
0.154
|
0.244
|
0.257
|
0.170
|
0.257
|
0.270
|
0.183
|
|
Fuels
|
0.847
|
0.852
|
0.837
|
0.864
|
0.869
|
0.854
|
0.877
|
0.882
|
0.868
|
|
Other food products
|
0.523
|
0.535
|
0.461
|
0.546
|
0.557
|
0.482
|
0.563
|
0.574
|
0.499
|
|
Liquor
|
0.474
|
0.505
|
0.416
|
0.503
|
0.533
|
0.445
|
0.526
|
0.556
|
0.468
|
|
Textiles, clothing,
footwear
|
0.494
|
0.497
|
0.385
|
0.523
|
0.527
|
0.414
|
0.547
|
0.550
|
0.438
|
|
Material for conservation,
repair of dwelling
|
0.451
|
0.460
|
0.383
|
0.479
|
0.488
|
0.411
|
0.502
|
0.510
|
0.433
|
|
Stationery, office supplies
|
0.478
|
0.502
|
0.398
|
0.514
|
0.538
|
0.435
|
0.544
|
0.567
|
0.465
|
|
Mining
|
0.538
|
0.545
|
0.512
|
0.596
|
0.603
|
0.569
|
0.643
|
0.649
|
0.616
|
|
Chemical industry
|
0.527
|
0.539
|
0.505
|
0.568
|
0.580
|
0.547
|
0.601
|
0.613
|
0.586
|
|
Basic industry metals
|
0.491
|
0.496
|
0.455
|
0.509
|
0.513
|
0.472
|
0.523
|
0.527
|
0.493
|
Source: Ahmad and Viscarra (2016). A number of simulations were carried out with alternative assumptions concerning the tradable and non-tradable sectors.
|
Groups
|
e = 0
|
e = 0.5
|
e = 1
|
e = 2
|
e = 5
|
|
Rents
(houses, apartments)
|
1
|
1
|
1
|
1
|
1
|
|
Transportation
|
2
|
3
|
15
|
21
|
19
|
|
Other
services
|
3
|
17
|
24
|
24
|
24
|
|
Education
|
4
|
23
|
25
|
25
|
25
|
|
Telephone
services
|
5
|
16
|
22
|
23
|
23
|
|
Hotels,
restaurants
|
6
|
11
|
16
|
18
|
18
|
|
Textiles,
clothing, footwear
|
7
|
7
|
12
|
14
|
8
|
|
Health
|
8
|
13
|
18
|
16
|
10
|
|
Meats,
sausages
|
9
|
5
|
4
|
6
|
9
|
|
Public
basic services
|
10
|
2
|
2
|
2
|
2
|
|
Financial
services
|
11
|
14
|
17
|
15
|
14
|
|
Flour,
pasta, cereals
|
12
|
6
|
5
|
17
|
17
|
|
Entertainment
|
13
|
26
|
26
|
26
|
27
|
|
Electricity
|
14
|
4
|
3
|
5
|
7
|
|
Vegetables
|
15
|
9
|
11
|
12
|
15
|
|
Non-alcoholic
beverages
|
16
|
8
|
7
|
7
|
6
|
|
Pharmaceutical
products
|
17
|
21
|
21
|
20
|
20
|
|
Dairy
products, cheese, eggs
|
18
|
10
|
10
|
11
|
13
|
|
Other
food products
|
19
|
19
|
20
|
19
|
22
|
|
Gas
|
20
|
12
|
8
|
10
|
12
|
|
Liquor
|
21
|
15
|
6
|
3
|
3
|
|
Fruits
|
22
|
18
|
13
|
8
|
5
|
|
Tobacco
|
23
|
25
|
23
|
22
|
21
|
|
Toiletries,
cosmetics
|
24
|
27
|
27
|
27
|
26
|
|
Fish,
crustaceans, mollusks
|
25
|
20
|
9
|
4
|
4
|
|
Oils,
fats
|
26
|
22
|
14
|
9
|
16
|
|
Fuels
|
27
|
24
|
19
|
13
|
11
|
Source: Ahmad and Viscarra (2106). Note 1 is the highest rank social cost, and least attractive to tax and 27 the lowest rank and most attractive to raise an additional dollar in revenue.
Table 1SNI project selection parameters DISPLAY Table
Table 2Accounting ratios, sensitivity analysis DISPLAY Table
Table 3Chile: social profitability of different sectors DISPLAY Table
Table 4Chile social marginal cost ranking for different inequality parameters DISPLAY Table
Chart 1Investment and multilevel taxation linkages DISPLAY Chart
* This paper is based on a keynote delivered at the conference Public Sector Economics organized by the Institute of Public Finance and Friedrich-Ebert-Stiftung in Zagreb on October 14-15, 2016 and the Annual Development Lecture at Peking University, in December 2016. I thank participants for helpful comments. All errors are mine.
1 See Drèze and Stern (  1987).
4 Simulations carried out at the request of SNI and available on request.
|
|
June, 2017
II/2017
|
