Estimating the Regional Impacts of EFREPrograms in Austria using a Multiregional
Econometric Input-Output Model
methods and first results
Gerhard Streicher (Joanneum Research)
Oliver Fritz, Robert Hierländer, Peter Mayerhofer (WIFO)
Overview of the research project
Aim: collecting first empirical evidence on the quantitative effects of
structural fund programs in Austria
• "Top-Down“-approach
• Focus on growth and employment (Lisbon)
• Pilot study – limited resources
• Selected research questions
• Medium level of aggregation (regional and sectoral)
•
Overview of the research project
Empirical evidence on quantitative effects of EFRE-programs in
Austria missing so far – existing evaluations studies are qualitative
in nature:
• Lack of (regional) data and instruments
• Short intervention period
Overview of the research project
Part 1: Before – after analysis
• Regional development before and after 1995 (Austria’s
accession to the EU)
Part 2: Macro-simulations of selected interventions
– MultiREG
– Supply and demand side effects
– „Predefined“ transformation channels
– Scarce data on subsidized projects
Part 1: Before – after analysis
Data:
• Funds of subsidized projects for 99 districts, 1995-2008
• Employment for 93 districts, 1983-2007
• (Registered) Unemployment for 83 labor market districts,
1971-2007
• Regional valued added for 35 NUTS III-regions, 1995-2005
Part 1: Before – after analysis
Issues:
• Economic performance of subsidized regions compared to
other regions
• Can observed differences in performance be related to
program-periods?
• Do observed differences depend on amount of subsidies and
type of region?
Part 1: Before – after analysis
Methods:
• Stability tests of regional employment development over time
• Difference-in-Difference analysis
Part 1: Before – after analysis
Results:
• Regional disparities decrease in program periods; some
evidence of catching-up, but statistically insignificant
• Based on GDP/capita and unemployment: Subsidies flow
into lagging regions; however, this is not true with respect to
productivity levels
• Superior performance of subsidized regions with respect to
unemployment for both EFRE-periods, with respect to
employment only for the first period; employment gains
increase with intensity of subsidies
Part 1: Before – after analysis
Results:
• After EU-accession (relative) growth of employment in
subsidized regions significantly higher than before; correlates
with amount of subsidies and is true for rural and more
densely populated regions
• Labor market: significantly positive structural break after EU
accession in formerly worst-performing regions
• Impacts more evident with respect to employment but
dampened with respect to unemployment due to supply side
reactions on the labor market
Part 1: Before – after analysis
Results:
• Growth differences in periods with and without EFRE-support
are significantly higher in subsidized regions than in others
• Growth performance positively depends on intensity of
subsidies
 Hypothesis of positive impact of EFRE-programs cannot be
rejected
Caveat:


Data allow only for indirect tests
Evidence of causal link between regional
development and programs only through modelbased impact analysis
Part 2: Model simulations
Issues:
• How do programs influence regional growth with respect to
GDP?
• In which regions can impacts be measured; how large are
regional spill-overs?
Types of impacts:
• Short run: Increase of demand through investment, etc.
• Long run: Improvement in regional competitiveness (supply
side effect) – key program goal
Part 2: Model simulations
• Model analysis based on theory-driven transformation channels no statistical analysis of correlations
• Model applied: MultiREG – a multiregional multisectoral
economectric input-output model for Austria
• Results restricted to state-level (9 Bundesländer)
Facts about MultiREG
 9 regions (NUTS II: “Bundesländer”)
 32 sectors and commodities (groups of 2-digit NACE / CPA codes),
 4 categories of final demand (CP, CG, I, X)
 3 modules:
 regional make-use-matrices (year 2000);
 econometrically estimated equations:
 private consumption (YD, AIDS)
 cost functions (Translog) -> demand for labor & intermediates
 investment (stock adjustment model)
 trade matrix: for each commodity flows between the 9 regions (and abroad)
 Implemented in GAMS (previous version: EViews)
MultiREG
Interregional Trade Matrix
Regional Final Demand
Foreign Exports
Regional Exports
Regional Total Demand
Regional
Imports
Foreign
Imports
Private Consumption
Regional Production
Intermediate Demand
Value Added
Factor Demand
Regional Production
Public Consumption
(Output) Prices
Investment
Wage Rate
Capital
Employment
Regional Income
Types of Income
Taxes and Social Sec.
DIRECT EFFECTS
Transformation channels
Production, income and
employment after demand
impulse through subsidies
Backward
linkages
Analysis of
subsidized projects
INDIRECT EFFECTS
Production, income and
employment through demand
for inputs
INDUCED EFFECTS
Model simulations
Production, income and employment
through consumption of employees in
• institutions receiving subsidies
• institutions delivering inputs
TOTAL EFFECTS
Forward
linkages
KATALYTIC EFFECTS
• Supply side: Increase of
level of competitiveness
Supply-side analysis
and model simulations
Simulation challenges
• Imperfect suitability of EFRE data base for model simulations:
 Types of projects
 New investment vs. incremental investment
• Difficult modeling of supply side effects:
 Price vs. quality effects
 Regional reallocation vs. net effects at national level
 Time lag between project implementation and economic effect
• Difficult modeling of “soft” measures
 Human capital improvements
 R&D subsidies
 (extremely) long reaction time
Demand-side Simulation
Simulation base
• Only EFRE-funds are taken into account
• inflow of foreign funds, therefore:
• no opportunity costs assumed!
• Information on projects by type of intervention
• However: for model simulations, funds must be broken down into CPAcommodities; regional effects significantly influenced by:
– Different import quota and
– different technologies
• Most funds flow into “hard” investment (construction, machinery)
Increase of demand by commodities and
regions
Total value added effects
200
180
160
[Mio €]
140
120
100
80
60
EFRE-funds
EFRE-Mittel
40
VA –- induced
effects
BWS
induzierte
Effekte
20
VA – indirect effects
BWS
- indirekte Effekte
Multiplier: 1.5
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
0
100%
90%
80%
70%
60%
50%
40%
30%
VA – indirect effects
20%
W, 24%
V, 3%
T, 6%
St, 16%
S, 5%
O, 15%
N, 17%
BWS-indirekte Effekte
K, 7%
VA – induced effects
W, 20%
V, 3%
T, 5%
St, 18%
S, 4%
O, 15%
N, 19%
K, 8%
B, 8%
V, 3%
W, 3%
T, 5%
St, 21%
S, 3%
O, 14%
N, 22%
K, 10%
B, 19%
EFRE-Mittel
10%
BWS-induzierte Effekte
B, 6%
EFRE-funds
0%
Effects on regional value added
100%
90%
80%
70%
60%
7071, 8%
50%
60, 3%
3033, 3%
2728, 3%
29, 4%
6567, 6%
5052, 12%
40%
7374, 13%
BWS-indirekte Effekte
30%
VA – induced effects
2728, 4%
60, 2%
3033, 4%
29, 7%
6567, 5%
7071, 8%
5052, 6%
7374, 19%
45, 31%
2728, 5%
3033, 10%
60, 1%
29, 18%
5052,
0%
7071,
6567, 1%
1%
7374, 17%
45, 36%
EFRE-Mittel
20%
VA – indirect effects
45, 22%
BWS-induzierte Effekte
10%
EFRE-funds
0%
Effects on sectoral value added
Rest, 12%
Rest, 14%
Rest, 26%
Supply-side simulation
Analysis of investment programs
• Analysis restricted to investment programs and their impacts
• Periods 1995-1999, 2000-2007
• Objective 1 and 2, INTERREG, URBAN
• Total project funds ~ 11 Bil. €
• Subsidies:
– ~ 1.25 Bil. € EFRE-funds
– ~ 1.8 Bil. national funds
Investitionsvolumen
Effects of part of theses funds are simulated:
– Investment in capital stock of manufacturing industry
– Funds ~6 Bil. €, share of subsidies 7 % (EFRE), 8 % (national funds)
8%
6%
100
4%
50
Wien
Vorarlberg
0%
Tirol
0
Steiermark
2%
relativ zu K und I 2000
150
Salzburg
„Relative winner“ : B
10%
Oberoesterreich

„Absolute winner“: St
12%
200
Niederoesterreich

14%
250
Kaernten
Regional distribution:
16%
Burgenland

Fördersumme 1995-2007 [Mio. €]
300
Fördersumme
Total public funds
bezogen
Relatedauf
toK-Stock
K 20002000
Relatedauf
toInvestitionen
I 2000
bezogen
2000
Impacts of investment
Projects lead to increase in capital stock
– Demand side impacts:
Multiplier effect through additional investment
– Supply-side impacts:
Capacity effect -> Output-effect
Efficiency effect -> Price-effect
Additionality issue:
– Which share of the project would have been carried out without
public funds (crowding out)?
– Additionality probably low – empirical evidence: only public funds
are additional
Opportunity cost
„Alternative use“ of private / public funds – impacts?
Assumptions:
– Private funds are not influenced by public funds, no alternative use
– EFRE-funds: completely additional (foreign funds – „manna from
heaven“)
– National funds: alternative use – funds could have been used for
- ... similar projects
- ... government activities in general (assumption here)
- ... certain government activities (health, defense, etc.)
- ... deficit reduction
- ….
MultiREG-Simulations
Simulations using MultiREG:
– PLUS:
State level
Sectoral disaggregation (32 activities/ commodities, 6 final use
categories)
Detailed modeling of inter-regional und inter-sectoral linkages
(„Spillovers“)
MultiREG-Simulations
Simulations using MultiREG:
– MINUS:
MultiREG demand-side oriented model
Modeling of pure supply side effects (expansion capital stock!)
incomplete
Solution: Analysis of price and output effects outside MultiREG
and transformation into demand-side effects as inputs for
MultiREG
Output- vs. price effects
Estimation of price and output effects:
– Price effects: Expansion of K -> demand impulse through lower domestic
prices -> increase of exports and reduction of imports
– Output effects: Reduction of capacity constraints -> excess demand can
be satisfied (additional demand through price effects)
– Conceptional issue: new and incremental investment
– No additional information about type of investment
– Assumptions:
 „small“ investment used to renew capital stock (pure price effect);
 „larger“ investment used to expand capacity (output effect through
additional exports / reduced imports)
Output- vs. price effects
small regions

Very „ad hoc“....
gesamt
4%
0%
2%
3%
Gesamtergebnis
1%
0%
1%
0%
0%
0%
3%
0%
1%
0%
4%
VORARLBERG
1%
1%
1%
3%
WIEN
2%
1%
0%
9%
18%
46%
21%
10%
26%
17%
20%
13%
25%
0%
2%
1%
0%
0%
TIROL
2%
4%
0%
10%
6%
7%
7%
6%
8%
3%
0%
1%
0%
0%
0%
3%
20%
9%
71%
12%
25%
16%
2%
125%
40%
STEIERMARK
0%
4%
14%
2%
5%
11%
18%
9%
24%
13%
7%
0%
1%
2%
0%
0%
15%
43%
905%
237%
37%
17%
4%
32%
23%
33%
SALZBURG
OBERÖSTERREICH
-> smaller sectors in
S4
S5
S6
S7
S8
S9
S10
S11
S12
S13
S14
S15
S16
S17
S18
S19
....
NIEDERÖSTERREICH
50% of K(2000)
KÄRNTEN
S investment </>
BURGENLAND

.... Sector
Criterion for separating price and output effects:
7%
5%
32%
6%
0%
3%
1%
34%
16%
4%
2%
1%
2%
11%
1%
4%
2%
1%
1%
0%
0%
1%
1%
0%
0%
5%
9%
4%
15%
7%
13%
8%
9%
8%
8%
0%
1%
1%
0%
0%
1%
1%
0%
0%
Simulations assumptions
• Subsidies paid and invested in year T0
• Effects depreciated linearly over life span of sectoral K
• Cumulated effects more evident; assumption does not influence size of
effects
• Price effect estimated based on cost function approach:
– translog-specification for VC, L/VC, PQ = f(Q, K, ....)
– Derivation of DPQ = f(DK,....) as exogeneous input for MultiREG
• Output effect estimated from „typical“ relation Q/K: DQs = DKs*(Qs/Ks),
implementied als exogeneous increase of exports
• Alternative use of national public funds: negative shock of regional CG
Results - national level
Impact on national GDP:
– Substantial immediate impact due to demand side effects (direct, indirect and
induced effects of additional investment)
– Immediate dampening effect of alternative use (CG reduction)
1200
400
200
CG-Reduktion
T20
keine CG-Reduktion
0
T15
permanent increase of GDP
600
T10
– Simulations result in small,
800
T5
due to price and output effects)
1000
T0
become relevant (increase of X
Veränderung ggü Basislösung [Mio. €]
– In the medium run K-effects
Results – regional level
Regional distribution of cumulated (T0-T20) effects – change of GRP
1400
16%
1200
14%
12%
1000
10%
800
8%
600
6%
bezogen auf BWS 2002
18%
Wien
Vorarlberg
CG-Reduktion
Tirol
0%
Steiermark
keine CG-Reduktion
0
Salzburg
2%
Oberoesterreich
4%
200
Niederoesterreich
400
Kaernten
– Distribution of relative
effects more „intuitive“:
B, K profit most
1600
Burgenland
Induced by inter-regional
trade, especially in services.
Role as capital city
(federal government),
headquarters
Veränderung ggü Basislösung [Mio. €]
– Largest absolute impact in W (receiving almost no subsidies)
relativ zu BWS
Results – sectoral level
Sectoral distribution of cumulated (T0-T20) effects :
– Largest effects in trade (induced effects, mostly through CP)
– Significant impact on sectors
receiving subsidies
(metals, machinery)
S505152
S2728
S30313233
S75
S7071
S45
S80
– Differences in scenarios largest
in the public sector
(public administration, health,
education – assumptions!)
S7374
S85
S656667
S25
S26
S2324
CG-Reduktion
S55
keine CG-Reduktion
Rest
0
200
400
600
800
Veränderung ggü Basislösung [Mio. €]
1000
Discussion and further research
Discussion of results:
– Assumptions about additionality
– Assumptions about alternative use
– Shock implemented in a single year
– Separation of price and output effects -> criteria?
– Price effect rather small: alternative specification, estimation
method
Discussion and further research
Further research…..
– Information about type of investment projects:
New vs. incremental K (-> price / output effect!)
Incremental K: markets for additional Q (regional/interregional/international)
– Regional distribution of projects: „regional additionality“ (regional
crowding out)
– Sensitivity tests
– Survey among companies receiving subsidies is required!
– Monitoring system determines scope and quality of evaluation
Thank you for your attention!