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Estimating the Regional Impacts of EFRE- Programs in Austria using a Multiregional Econometric Input-Output Model methods and first results Gerhard Streicher.

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Presentation on theme: "Estimating the Regional Impacts of EFRE- Programs in Austria using a Multiregional Econometric Input-Output Model methods and first results Gerhard Streicher."— Presentation transcript:

1 Estimating the Regional Impacts of EFRE- Programs in Austria using a Multiregional Econometric Input-Output Model methods and first results Gerhard Streicher (Joanneum Research) Oliver Fritz, Robert Hierländer, Peter Mayerhofer (WIFO)

2 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)

3 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

4 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

5 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

6 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?

7 Part 1: Before – after analysis Methods: Stability tests of regional employment development over time Difference-in-Difference analysis

8 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

9 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

10 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 model- based impact analysis

11 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

12 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 )

13 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)

14 MultiREG

15 Model simulations INDIRECT EFFECTS Production, income and employment through demand for inputs DIRECT EFFECTS Production, income and employment after demand impulse through subsidies INDUCED EFFECTS Production, income and employment through consumption of employees in institutions receiving subsidies institutions delivering inputs TOTAL EFFECTS Backward linkages KATALYTIC EFFECTS Supply side: Increase of level of competitiveness Forward linkages Analysis of subsidized project s Supply-side analysis and model simulations Transformation channels

16 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

17 Demand-side Simulation

18 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 CPA- commodities; regional effects significantly influenced by: –Different import quota and –different technologies Most funds flow into “hard” investment (construction, machinery)

19 Increase of demand by commodities and regions

20 Total value added effects Multiplier: 1.5 EFRE-funds VA – induced effects VA – indirect effects

21 Effects on regional value added EFRE-funds VA – induced effects VA – indirect effects

22 Effects on sectoral value added EFRE-funds VA – induced effects VA – indirect effects

23 Supply-side simulation

24 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

25 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) Regional distribution: „Absolute winner“: St „Relative winner“ : B Total public funds Related to K 2000 Related to I 2000

26 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

27 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 -….

28 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“)

29 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

30 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)

31 Output- vs. price effects Criterion for separating price and output effects:  investment 50% of K(2000) -> smaller sectors in small regions Very „ad hoc“....

32 Simulations assumptions Subsidies paid and invested in year T 0 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  PQ = f(  K,....) as exogeneous input for MultiREG Output effect estimated from „typical“ relation Q/K:  Q s =  K s *(Q s /K s ), implementied als exogeneous increase of exports Alternative use of national public funds: negative shock of regional CG

33 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) –In the medium run K-effects become relevant (increase of X due to price and output effects) –Simulations result in small, permanent increase of GDP

34 Results – regional level Regional distribution of cumulated (T0-T20) effects – change of GRP –Largest absolute impact in W (receiving almost no subsidies)  Induced by inter-regional trade, especially in services. Role as capital city (federal government), headquarters –Distribution of relative effects more „intuitive“: B, K profit most

35 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) –Differences in scenarios largest in the public sector (public administration, health, education – assumptions!)

36 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

37 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/inter- regional/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

38 Thank you for your attention!

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