Structural Funds: An Effective Redistributive Policy? Some ... · 4) for structural differences across regions and the allocation mechanisms of funds. RSA Workshop: EU Cohesion Policy:

Lisboa, 05 e 06 de Novembro de 2015

RSA WORKSHOP

EU Cohesion Policy: Focus on the Territorial Dimension

Structural Funds: An Effective Redistributive Policy?

Some Evidence From Italian Public Policies)

Gianluigi Coppola, (University of Salerno, Italy)

Sergio Destefanis, (University of Salerno, Italy)

Giorgia Marinuzzi, (IFEL - ANCI Foundation Italy)

Walter Tortorella, (IFEL - ANCI Foundation Italy)

The RSA Network on EU Cohesion Policy

RSA Workshop: EU Cohesion Policy: Focus on the Territorial Dimension

1. Introduction

2. The Stylised Facts

3. A Brief Lit. Sur.

4. The Empirical Approach

5. The Dataset

6. The Estimates

7. Concluding Remarks


Introduction I

• The Italian Mezzogiorno has experienced longstanding gaps vis-à-

vis the rest of the country in terms of income per capita, and

economic performance (Allen and Stevenson, 1974; Putnam 1993;

Paci e Saba, 1998, Iuzzolino, 2011).

• The European Structural Funds are the most important tool used by

the EU to sustain the economic growth of the less developed regions

in Europe

• In the last years an important theoretical and political debate has

grown about the usefulness of the Structural Funds


Introduction II

• In this paper we study the impact of the EU funds on the GDP per

capita and capital accumulation of the 20 Italia administrative

regions for the programming periods 1994-99, 2000-06, 2007-13

•We ask whether the Funds are an effective redistributive policy

or, in other words, whether the financial resources redistributed

by the EU actually contributed to reduce interregional disparities

in Italy.

Introduction III

5

• We aim to identify efficient practices and areas of intervention by:

• Considering various types of nationally-financed funds along with the EU funds;

• Estimating separate equations for GDP per capita and fixed investment;

• Assessing the impact of a measure of the quality of local governments provided by the Quality of Government Survey (Charron et al., 2014);

• Examining various programming cycles, ruled by different governance systems.


The Stylised Facts I

6

• EU funds per inhabitant are much higher in the Italian Southern

regions, especially with respect to the ERDF. However, note that

there is considerable variation even among the Mezzogiorno

regions. Particularly high values are obtained for Molise and

Basilicata.

• Note also that a substantial share of EU funds is not allocated to

any single region, but to multi-regional aggregates. In the

following analysis we shall assume that this funding affects

regions proportionally to the shares of regionally-allocated

funds.


The Stylised Facts II

7

Financial endowment of structural interventions in Italy for the 1994-1999, 2000-2006 and 2007-2013 programming periods, by Fund (million Euros)

Funds

1994-1999 (data to

31/12/2003)

2000-2006 (data to

31/12/2010)

2007-2013 (data to

30/04/2015) a.v. % a.v. % a.v. %

ERDF 32,641 62.2% 40,512 63.0% 33,352 50.6% ESF 9,931 18.9% 16,613 25.8% 14,018 21.3% EAGGF 9,090 17.3% 6,088 9.5% FIFG 790 1.5% 1,080 1.7% EAFRD* 17,695 26.8% EFF* 849 1.3% Total 52,452 100.0% 64,294 100.0% 65,914 100.0%

* MEF data to 31/12/2012.


The Stylised Facts III

8

Financial endowment of structural interventions in Italy for the 1994-1999, 2000-2006 and 2007-2013 programming periods, by Objective (million Euros)

Objective 1994-1999

(data to 31/12/2003)

2000-2006 (data to

31/12/2010)

2007-2013 (data to

30/04/2015) a.v. % a.v. % a.v. %

Objective 1 31,850 60.7% 45,896 71.4%

Objective 2 4,352 8.3% 7,183 11.2% Objective 3 3,047 5.8% 9,098 14.2% … … … Convergence 31,494 47.8% Competitiveness 15,179 23.0% … … …

Rural Devm’nt* 17,695 26.8%

Fishery* 849 1.3%

Total 52,452 100.0% 64,294 100.0% 65,914 100%

* MEF data to 31/12/2012. Source: elaboration by IFEL-Dipartimento Studi Economia Territoriale on MEF data, various years.


A Brief Lit. Sur. I

9

The various papers can be classified on the basis of:

1) the period considered;

2) the level of territorial disaggregation;

3) the estimation method;

4) the variables included in the model (dependent

variables, covariates and their frequency);

5) the results obtained;


A Brief Lit. Sur. II

10

Examination of the previous works reveals that there is

room for a new study:

1) Differentiating productivity change and capital

accumulation; and allowing

2) for the role of other policies besides EU funds;

3) for the role of quality of government;

4) for structural differences across regions and the

allocation mechanisms of funds.


The Empirical Approach I

11

We do this by:

1) Estimating two separate equations for GDP per

capita and investment;

2) Including various policy indicators;

3) Allowing for a measure of quality of government,

and various sample cuts;

4) Coming to terms with the structural divide

between the Mezzogiorno’s and other regions.


The Empirical Approach II.a

12

(5.1) xit = a1 xit-1 + a2j FUNDSjit + a3 Zit + a4 gfiit +

+ a5 Dnit + a6 PERIOD_2*SOUTH + a6 PERIOD_3*SOUTH + ai + at

• where:

• xit = log of real GDP per capita • FUNDSit = various EU funds (ERDF, ESF, EAGGF)

• Zit = various national funds

• gfiit = log of gross fixed investment per capita • Dnit = log variation of population


The Empirical Approach II.b

13

(5.2) gfiit = a1 gfiit-1 + a2j FUNDSjit + a3 Zit + a4 Dyit + a5 Dnit +

+ a6 PERIOD_2*SOUTH + a7 PERIOD_3*SOUTH + ai + at

• where:

• gfiit = …

• FUNDSit = …

• Zit = …

• Dyit = log variation of real GDP

• Dnit = …


The Empirical Approach III.a

14

• where: • …

• q is the time-invariant quality of government

A SIMILAR EQUATION (5.2’) IS ESTIMATED FOR FIXED INVESTMENT

(5.1’) xit = a1 xit-1 + a2j FUNDSjit + a2’j qi FUNDS jit + a3 Zit +

+ a3’ qi Zit + a4 gfiit + a5 Dnit + a6 PERIOD_2*SOUTH +

+ a7 PERIOD_3*SOUTH + ai + at


The Dataset I

15

• Regional Dataset (1994 – 2012)

• Annual Variables

• GDP per Capita, Employment, Investment (from regional accounting, Istat)

(In order to obtain a measure of private investment, we subtracted I from health, educ., PA from total I)

• EU Funds (disbursed funds from Spesa Statale Regionalizzata, RGS)

• National Funds (from Spesa Statale Regionalizzata, RGS)


The Dataset II

16

• EU Funds:

• The European Regional Development Fund (ERDF)

• The European Social Fund (ESF)

• The various Funds oriented toward agriculture and fishery

• National Funds:

• National Cohesion Funds (Fondo innovazione tecnologica, Fondo contributo imprese, Fondo solidarietà nazionale),

• Capital Account Expenditure (Spese in conto capitale)

• Current-account subsidies to firms (trasferimenti in conto corrente alle imprese)


q – The (time-invariant) quality of government

17


Legend of the following tables

18

• lifl_pc = gross fixed investment per capita

• fesr = ERDF

• dua = ERDF+agr._oriented funds

• tre = ERDF+ESF+agr._oriented funds

• fdr = ERDF+ESF+agr._oriented funds+

+national co-financing

• z = current-account subsidies to firms

• q = time-invariant quality of government

An f termination stands for a (1-year) forwarded variable.

ALL EQUATIONS ARE ESTIMATED THROUGH Sys-GMM


The Estimates I - Table A.2.a

19

(5.1) FUNDS and Z

(8) (9) (10)

lifl_pc 0.0245*** 0.0248*** 0.0233***

duaf 0.0027**

tref 0.0032

fdrf 0.0043***

z 0.0044*** 0.0045*** 0.0044***


The Estimates II - Table A2.b

(5.2) FUNDS and Z

(1) (2) (3) (4) (5) (6)

fesr 0.0121*** 0.0123** 0.0114* 0.0116*

z -0.0124* -0.0116* -0.0110* -0.0124* -0.0118* -0.0119*

20


The Estimates III - Table A3

(5.1’) FUNDS and Z with quality of government indicator 7 8 9 10

lifl_pc 0.0271*** 0.0260*** 0.0259*** 0.0250***

duaf 0.0036** tref 0.0046***

fdrf 0.0048*** duaf*q 0.0019 tref*q 0.0022 fdrf*q 0.0010

z 0.0043*** 0.0041*** 0.0041*** 0.0041***

z*q 0.0020* 0.0020** 0.0021** 0.0021**

21


The Estimates II - Table A3

The Estimates IV - Table A4

(5.1) FUNDS and Z, only Mezzogiorno regions

8 9 10

lifl_pc 0.0223 0.0225 0.0225

duaf 0.0014

tref 0.0038**

fdrf 0.0038*

z 0.0045* 0.0043* 0.0043*

22


The Estimates V - Table A5

(5.1) FUNDS and Z, ONLY 2000-2012

8 9 10

lifl_pc 0.0110 0.0103 0.0095

duaf 0.0032*

tref 0.0048**

fdrf 0.0059**

z 0.0023* 0.0025* 0.0023*

23


The Estimates VI - Table A6

(5.1) FUNDS and Z, only 1994-2006

8 9 10

lifl_pc 0.0211*** 0.0209*** 0.0213***

duaf -0.0002

tref -0.0016

fdrf -0.0004

z 0.0044*** 0.0045*** 0.0044***

24


Concluding Remarks I

25

EU Funds have a significant impact on GDP per capita but

fairly little effect on capital accumulation.

Different types of Structural Funds have substantially

different influences, with the ERDF, arguably, having the

strongest impact.

Among national policies, current-account subsidies to

firms only have a positive impact on GDP per capita.

Quality of government has relatively little impact on

Structural Funds, but decisively enhances the impact of

subsidies to firms.


Concluding Remarks II

26

The impact of EU funds is not weaker in the Mezzogiorno,

whose regions are more generously endowed.

Hence, it seems that EU funds, more than national funds,

achieve their redistributive aim (reduce interregional

disparities).

EU funds increase their impact in recent years, unlike

current-account subsidies and private investment.


Concluding Remarks III

27

Future work will entail:

A deeper understanding of the allocation rules of the

EU funds;

Utilisation of data also for accredited funds, allowing

an evaluation of the time-varying organisational

efficiency of the various regions and its relationship

with the effectiveness of the EU funds;

Allowance for measures of regional technological

capability.


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Structural Funds: An Effective Redistributive Policy? Some ... · 4) for structural differences across regions and the allocation mechanisms of funds. RSA Workshop: EU Cohesion Policy: