Transcript Medium-Term Expenditure Scenario Analysis

Medium-Term Expenditure
Scenario Analysis
USING BOOSTS
Outline
 Why?
 Objectives of medium-term analysis
 How?
 Setting a macro-framework
 Selecting a unit of analysis
 Designing scenarios and options
 Limitations and constraints
Why?
Medium-Term Analysis Using
BOOSTs
Objectives of Medium-Term Analysis
using BOOSTs
 BOOSTs provide detailed historical
expenditure information
 Can be extrapolated to assess expenditure
allocation options over the medium-term
Objectives of Medium-Term Analysis
using BOOSTs
 Analysis using BOOSTs provides powerful tool
to illustrate:
 How sector or ministry-level expenditure can adjust to
macroeconomic trends and shocks
 Impacts of expenditure decisions on fiscal aggregates
 Trade-offs and conflicts between expenditure in different
priorities and sectors
 Trade-offs and conflicts between expenditure decisions and
macro-fiscal policy objectives
Example 1:
 Country with growing debt repayment obligations
 Policy targets to:
 Increase expenditure in “priority sectors” of health and
education
 Reduce the share of expenditure on the wage bill
 BOOST analysis used to show how policy targets could be
achieved within sustainable aggregate limits and while
meeting repayment obligations
Tax Revenue
Grows by about 3 percent per year in real terms (slightly above GDP growth), as per DSA baseline
Budget Support Remains at the level projected for FY13 (about 23 million TOP), as per DSA baseline
Sector
Priority
Economic
Law & Order
Other
Wage Expenditure
Nominal spending grows by about 4¼ percent per
year; Real spending falls by about 2½ percent per
year
Nominal spending grows by about 3¼ percent per
year; Real spending falls by about 3½ percent per
year
Non-Wage Expenditure
Nominal spending grows by 10 percent per year;
Real spending grows by about 3¼ percent per
year
Nominal spending grows by 3 percent per year;
Real spending falls by about 3¾ percent per
year
Output: share of expenditure by sector
Output: share of expenditure on wage bill
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
60%
50%
40%
30%
20%
10%
FY12
Priority
FY13
FY14
Economic
FY15
FY16
Law & Order
FY17
Other
0%
FY12
FY13
FY14
Actual Wage Ratio
FY15
FY16
FY17
Target Wage Ratio
Example 2:
 Country with deteriorating revenue effort, SOE
subsidies imposing severe fiscal costs
 Policy target of maintaining the real value of
Sovereign Wealth fund
 BOOST analysis used to demonstrate the need for
revenue and SOE reforms if policy objectives were to
be achieved without large cuts in expenditure in
priority ministries
Fiscal Aggregate
Macroeconomic
Outcomes
Based on IMF projections, medium-term real growth GDP of 2% and inflation of around 2.5%.
Revenue
No growth in revenue in nominal terms. No budget support. Project grants remain at trend levels.
Financing
Commercial debt is maintained at current levels.
45
40
35
30
25
20
15
10
5
Priority
Health
Education
Infrastructure
Environment
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
0
2008
Real expenditure (2006 AUD million)
Output: Expenditure and Fund Balance trends
How?
Medium-Term Analysis Using
BOOSTs
Setting a macro framework
 “Anchor” can be chosen according to objective of
analysis
 Fix aggregate expenditure
 Used to demonstrate tradeoffs within sustainable
expenditure limits
 Flexible aggregate expenditure
 Used to demonstrate short-term impacts of expenditure
decisions on cash reserves/debt levels
Setting a macro framework
 Fixed aggregate expenditure
 Copy aggregate expenditure limits from appropriate
scenario of IMF/World Bank Debt Sustainability Analysis
over projection period
 Divide expenditure types (ministries, sectors, inputs)
into:
 Those determined by input assumptions that you control
 Residual expenditures that will be forced to adjust to
accommodate change in manually-determined expenditure
types
Expenditure can be presented in the most useful
disaggregation for the policy purpose using BOOST
data for current year baseline
Input expenditure
trajectories in dropdown menus
Nominal
Total Expenditure (DSA)
GDP (DSA)
Ministry of Health
Ministry of Education
Ministry of Infrastructure
Ministry of Foreign Affairs
Ministry of Internal Affairs
Ministry of Environment
Ministry of Commerce
Ministry of Justice
1,954
8,011
2,003
8,212
2,053
8,417
2,104
8,865
2,157
8,905
2,211
9,064
2,266
9,291
2,323
9,523
Wages
Other
Wages
Other
Wages
Other
Input
5% real growth
5% real growth
5% real growth
5% real growth
5% real growth
5% real growth
211.03
316.55
180.55
229.79
93.79
218.85
221.58
332.38
189.58
241.28
98.48
229.79
232.66
348.99
199.06
253.34
103.41
241.28
244.30
366.44
209.01
266.01
108.58
253.34
256.51
384.77
219.46
279.31
114.00
266.01
269.34
404.00
230.43
293.28
119.71
279.31
282.80
424.20
241.95
307.94
125.69
293.28
296.94
445.41
254.05
323.34
131.97
307.94
Wages
Other
Wages
Other
Wages
Other
Wages
Other
Wages
Other
Zero real growth
Adjust
Zero real growth
Adjust
Zero real growth
Adjust
Zero real growth
Adjust
Zero real growth
Adjust
54.71
82.07
82.65
93.21
54.71
23.45
64.48
52.76
111.38
84.02
55.81
76.92
84.31
87.36
55.81
21.98
65.77
49.45
113.61
78.75
56.92
71.27
85.99
80.95
56.92
20.36
67.09
45.82
115.88
72.97
58.06
65.09
87.71
73.93
58.06
18.60
68.43
41.85
118.20
66.64
59.22
58.34
89.47
66.26
59.22
16.67
69.80
37.51
120.56
59.73
60.41
50.99
91.26
57.92
60.41
14.57
71.19
32.78
122.97
52.21
61.61
43.01
93.08
48.84
61.61
12.29
72.62
27.65
125.43
44.03
62.85
34.34
94.94
39.00
62.85
9.81
74.07
22.08
127.94
35.16
Taken from DSA
Calculated based on
input assumption
Set to adjust
automatically to
keep deficit equal to
DSA level –share of
non-priority
expenditure
maintained
Setting a macro framework
 Flexible aggregate expenditure
 All expenditure lines are manually determined
 Adjustments reflected in change in the deficit/surplus
Expenditure can be presented in the most useful
disaggregation for the policy purpose using BOOST
data for current year baseline
All expenditure
dynamics input from
drop-down menu
Taken from DSA
Manually input
based on policy
assumptions
Adjusts to reflect
aggregate impact of
sector/ministry
expenditure
decisions
Selecting unit of analysis
 BOOSTs allow high level of disaggregation when analyzing
expenditure
 Appropriate level at which to model expenditure choices
will depend on policy issues




Sectors – implications of achieving sector expenditure targets
Ministries – implications of ministry expenditure targets
Inputs – implications of public sector wage settlements
Sub-national governments – implications of decentralization
initiatives
 Etc.
Expenditure categories
taken from BOOST
Level of disaggregation
appropriate to
complexity of analysis
Sector, Ministry,
Division, Input, subnational government
unit, etc.
Selecting Input Assumptions
 Based on policy options under consideration
 Based on policy decisions already made to
understand implications
 Examples:
 Fixed rates of expenditure growth by sector
 Sector or ministry expenditure levels established in
plans or policy commitments
 Changes in spending to achieve target expenditure
ratios
5% Growth
Ministry of Health
Ministry of Education
Ministry of Infrastructure
Drop-down menus linked
to scenario sheets are an
easy way to update
assumptions and
examine the implications
of different policy targets
Ministry of Foreign Affairs
Ministry of Internal Affairs
Ministry of Environment
Ministry of Commerce
Ministry of Justice
Wages
Other
Wages
Other
Wages
Other
Wages
Other
Wages
Other
Wages
Other
Wages
Other
Wages
Other
2013
211.032
316.548
180.5496
229.7904
93.792
218.848
54.712
82.068
82.6542
93.2058
54.712
23.448
64.482
52.758
111.378
84.022
2014
221.5836
332.3754
189.5771
241.2799
98.4816
229.7904
57.4476
86.1714
86.78691
97.86609
57.4476
24.6204
67.7061
55.3959
116.9469
88.2231
2015
232.6628
348.9942
199.0559
253.3439
103.4057
241.2799
60.31998
90.47997
91.12626
102.7594
60.31998
25.85142
71.09141
58.1657
122.7942
92.63426
2016
244.2959
366.4439
209.0087
266.0111
108.576
253.3439
63.33598
95.00397
95.68257
107.8974
63.33598
27.14399
74.64598
61.07398
128.934
97.26597
2017
256.5107
384.7661
219.4592
279.3117
114.0048
266.0111
66.50278
99.75417
100.4667
113.2922
66.50278
28.50119
78.37827
64.12768
135.3807
102.1293
2018
269.3363
404.0044
230.4321
293.2773
119.705
279.3117
69.82792
104.7419
105.49
118.9568
69.82792
29.92625
82.29719
67.33406
142.1497
107.2357
2019
282.8031
424.2046
241.9537
307.9411
125.6903
293.2773
73.31931
109.979
110.7645
124.9047
73.31931
31.42256
86.41205
70.70077
149.2572
112.5975
2020
296.9432
445.4148
254.0514
323.3382
131.9748
307.9411
76.98528
115.4779
116.3028
131.1499
76.98528
32.99369
90.73265
74.2358
156.72
118.2274
Running scenarios
 BOOST analysis can:
 Help communicate incompatibilities and required tradeoffs between competing commitments and priorities
 Identify the need for trade-offs within an overall
resource constraint
 Show macro-fiscal impacts of expenditure policy
decisions
 Illustrate required sector expenditure adjustments
within a given macro framework
Running scenarios
 Government considering ambitious program of
expenditure in priority sectors identified in the national
plan
 Real expenditure growth of 5% per annum for health,
education and infrastructure
 Government has implemented a hiring freeze, but agreed
with the public sector union to inflation indexing of wages
and no layoffs
 Under the terms of an IMF program, there is no scope for
additional borrowing
Input appropriate
spending trends
Ministry of Health
Ministry of Education
Ministry of Infrastructure
Ministry of Foreign Affairs
Ministry of Internal Affairs
Ministry of Environment
Ministry of Commerce
Ministry of Justice
Wages
Other
Wages
Other
Wages
Other
Input
5% real growth
5% real growth
5% real growth
5% real growth
5% real growth
5% real growth
211.03
316.55
180.55
229.79
93.79
218.85
221.58
332.38
189.58
241.28
98.48
229.79
232.66
348.99
199.06
253.34
103.41
241.28
244.30
366.44
209.01
266.01
108.58
253.34
256.51
384.77
219.46
279.31
114.00
266.01
269.34
404.00
230.43
293.28
119.71
279.31
282.80
424.20
241.95
307.94
125.69
293.28
296.94
445.41
254.05
323.34
131.97
307.94
Wages
Other
Wages
Other
Wages
Other
Wages
Other
Wages
Other
Zero real growth
Adjust
Zero real growth
Adjust
Zero real growth
Adjust
Zero real growth
Adjust
Zero real growth
Adjust
54.71
82.07
82.65
93.21
54.71
23.45
64.48
52.76
111.38
84.02
55.81
76.92
84.31
87.36
55.81
21.98
65.77
49.45
113.61
78.75
56.92
71.27
85.99
80.95
56.92
20.36
67.09
45.82
115.88
72.97
58.06
65.09
87.71
73.93
58.06
18.60
68.43
41.85
118.20
66.64
59.22
58.34
89.47
66.26
59.22
16.67
69.80
37.51
120.56
59.73
60.41
50.99
91.26
57.92
60.41
14.57
71.19
32.78
122.97
52.21
61.61
43.01
93.08
48.84
61.61
12.29
72.62
27.65
125.43
44.03
62.85
34.34
94.94
39.00
62.85
9.81
74.07
22.08
127.94
35.16
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Change in Surplus/Deficit from DSA
Because no additional borrowing, use
“fixed aggregate expenditure, setting
deficit as DSA levels
Running Scenarios
Expenditure growth can be absorbed
by reductions in other sectors
2500.00
But, because of fixed real wages, required
unfeasible compression of non-wage expenditure
80%
70%
2000.00
60%
1500.00
50%
40%
1000.00
30%
500.00
20%
10%
0.00
2013
2014
2015
2016
2017
2018
Total Health
Total Education
Total Infrastructure
Total Others
2019
2020
0%
2013
Health
2014
2015
2016
Education
2017
2018
Infrastructure
2019
2020
Others
Running scenarios
 Government facing economic shock, with expected
decline in real revenue
 Committed to maintaining real expenditure on core
public services, but has established nominal
expenditure freeze in other areas
 Wishes to assess debt implications
Input appropriate
spending trends
2013
Nominal
Total Expenditure
GDP (DSA)
Ministry of Health
Ministry of Education
Ministry of Infrastructure
Ministry of Foreign Affairs
Ministry of Internal Affairs
Ministry of Environment
Ministry of Commerce
Ministry of Justice
Wages
Other
Wages
Other
Wages
Other
Wages
Other
Wages
Other
Wages
Other
Wages
Other
Wages
Other
Input
Zero real growth
Zero real growth
Zero real growth
Zero real growth
Zero real growth
Zero real growth
Zero nominal growth
Zero nominal growth
Zero nominal growth
Zero nominal growth
Zero nominal growth
Zero nominal growth
Zero nominal growth
Zero nominal growth
Zero nominal growth
Zero nominal growth
2014
2015
2016
1,954
1,856
1,745
8011.4 8211.685 8416.977
211.03
215.25
219.56
316.55
322.88
329.34
180.55
184.16
187.84
229.79
234.39
239.07
93.79
95.67
97.58
218.85
223.22
227.69
54.71
54.71
54.71
82.07
82.07
82.07
82.65
82.65
82.65
93.21
93.21
93.21
54.71
54.71
54.71
23.45
23.45
23.45
64.48
64.48
64.48
52.76
52.76
52.76
111.38
111.38
111.38
84.02
84.02
84.02
1,815
8865
223.95
335.92
191.60
243.86
99.53
232.24
54.71
82.07
82.65
93.21
54.71
23.45
64.48
52.76
111.38
84.02
2017
2018
2019
2020
1,869
1,925
1,983
2,042
8905 9064.164 9290.768 9523.037
228.43
233.00
237.66
242.41
342.64
349.49
356.48
363.61
195.43
199.34
203.33
207.39
248.73
253.71
258.78
263.96
101.52
103.55
105.63
107.74
236.89
241.63
246.46
251.39
54.71
54.71
54.71
54.71
82.07
82.07
82.07
82.07
82.65
82.65
82.65
82.65
93.21
93.21
93.21
93.21
54.71
54.71
54.71
54.71
23.45
23.45
23.45
23.45
64.48
64.48
64.48
64.48
52.76
52.76
52.76
52.76
111.38
111.38
111.38
111.38
84.02
84.02
84.02
84.02
Running scenarios
Growth in budget share for
priority sectors
Short-term growth in deficit
0.0%
100%
0
Surples/Deficit (% GDP - Line)
80%
70%
60%
50%
40%
30%
20%
10%
-0.5%
-50
-1.0%
-100
-1.5%
-150
-2.0%
-200
-2.5%
-3.0%
-250
-3.5%
-300
0%
2013
2014
Health
2015
2016
Education
2017
2018
Infrastructure
2019
2020
Others
Deficit
Percent GDP
Surplus/Deficit (millions - Bar)
2013 2014 2015 2016 2017 2018 2019 2020
90%
Limitations and constraints
Limitations and constraints
 Complement to, rather than substitute for, DSA
 BOOST analysis relies on a macro framework taken from
a DSA
 BOOST does not provide data on economic growth,
revenue, inflation, which needs to underpin all analysis
 BOOST data not sufficient for modeling debt dynamics
 Static analysis - No mechanism for tracing interactions
between expenditure decisions and growth or revenue