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Regional Inequalities in the EU and the Role of

Institutions

Vinko Muštra and Blanka Škrabić,Faculty of economics, University of Split

DUBROVNIK, JUNE 28th, 2011

WORKING PAPER

Regional convergence has become a heated topic in the last decades in the EU

1/3 of the total budget of EU (FP 2007-2013) goes to Cohesion policy

What is main goal of Cohesion policy?“to promote the “overall harmonious development” of the EU, to reduce disparities between the levels of development of the various regions…”(Art. 158 Treaty on European Union)”

Results?

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Investigating the dynamics of the convergence process has provided mixed and contradictory results (Mohl and Hahen, 2010; Le Pen, 2010)◦ Positive trend in convergence process (Barro and Sala-i-Martin,

1991, Sala-i-Martin, 1996, Martin and Sanz, 2003, Quah, 1996b, Le Pen, 2010)

◦ Weakly positive trend in convergence process (Fingleton, 1999, Hall, Robertson and Wickens, 1992)

◦ Negative trend in convergence process (Magrini, 1999, Pittau and Zelli, 2006)

Three broad sets of approaches to test for convergence:◦ β and σ convergence criteria (e.g. Barro and Sala-i-Martin,1991, Fingleton, 1999;

Lopez-Bazo et al, 2004; Ertur et al, 2006, Le Gallo and Dall’erba, 2006)

◦ intra-distribution dynamics approach (e.g. Quah 1993a, 1993b, 1996, 1997, Pittau and Zelli, 2006, Hierro and Maza, 2009)

◦ time series econometrics (e.g. Bernard, 1991; De Siano and D'Uva, 2006)

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The doubt on the convergence of European regions is also grounded in the economic theory

Arguments in favor of convergence:◦ Theory of neoclassical growth (e.g.: Solow 1957, 1994, Le Pen, 2010)

Arguments in favor of divergence:◦ Theory of endogenous growth (e.g. Romer, 1986, 1990) ◦ “New” theory of international trade (e.g. Krugaman, 1991; and Krugman

and Venables,1995)

Missing piece?

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The possible reasons for absence of the empirical and theoretical confirmation of the convergence process:◦ use of imprecise data (Becker et al., 2010,

Azomahou et al., 2010)◦ different methods for testing the convergence

process (Mohl and Hahen, 2010; Le Pen, 2010) ◦not taking into consideration significant

determinants (Rodriguez – Pose, 2009).

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Under a mainstream growth framework, achieving economic development was mainly a matter of investing in physical capital, innovation and education.

However, the implementation of such policy didn’t provide expected results in the EU (Rodriguez-Pose, 2010)

Obviously, the European regional strategies have overlooked an additional determinant of the growth process.

But, which one? Institutions!?!

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First tackles the importance of institution quality for regional inequalities in EU countries

Second tries to recognize which dimension of the institutional quality is important for pattern of regional imbalances

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Institutions as “the rules of the game in a society” (North, 1990)

(and) more formally, (as) the humanly devised constraints that shape human interaction” (North, 1990: 477).

In the last twenty years researchers have made considerable progress in showing that institutions ‘matter’ more for economic growth than traditional factor-endowments (e.g.Hall and Jones, 1999; Acemoglu, Johnson, and Robinson, 2001; Vijayaraghavan and Ward, 2001; Rodrik, Subramanian, and Trebbi ,2004, Knack and Keefer, 1997; Zak and Knack, 2001; Beugelsdijk and van Schaik, 2004; Knack, 2003; Bengtsson, Berggren, and Jordahl, 2005, Putnam, 1993, 2000; Beugelsdijk and van Schaik, 2005)

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◦ Regarding beliefs of Institutionalists and their idea that markets are “social constructs made and reproduced through frameworks of socially constructed institutions and conventions” (Pike et al. 2006, p 91) local and regional dimension of the institutions should be underlined as important factor of economic activity.

◦ But, how do they impact economic growth patterns on regional level?

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H1: Higher institution quality reduces regional inequalities in EU member countries

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Starting point is the model with the structure: (1)

Yit represents measure for regional inequalities measured by the sum of the absolute differences between regional (NUTS II level) and national GDP per inhabitant, weighted with the share of population and expressed in percent of the national GDP per inhabitant in country i for a period t.

Why this measure for regional inequalities? It fulfills the standards introduced by Portnov and Felsenstein

(2010) which are used to test sensitivity of commonly used inequality measures to changes in the ranking, size and number of regions into which a country is divided

Data has been used from Eurostat and World bank database for period 2000 – 2007 for 18 member countries ( 6 new member states)

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1T

it it it it itY Y X I

Vector presents control variable vector with dimensions 1 x k in county i for a period t (based on paper written by Barrios and Strobl, 2009):◦ trade openness is measured by real trade index

(Realopeness), ◦ regional industrial specialization is measured by adjusted

Krugman index (AK), ◦ fiscal decentralization is measured by sum of shares of

local and state revenues in GDP (Fiscal decen),◦ EU regional policy is measured by amount of Structural

funds per capita (Sfpercapita)

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TitX

Institution quality (I) is measured by WGI indicator which includes six dimension of indicator quality:

Voice and Accountability (VA), Political Stability and Absence of Violence/Terrorism

(PV), Government Effectiveness (GE), Regulatory Quality (RQ), Rule of Law (RL), and Control of Corruption (CC))

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The main reasons are: 1. Resemblance between their definition of

governance and institutions, 2. Broad aspect of the WGI 3. The process dimension of the WGI

Ad 1. The definition offered by the Kaufmann et al (2010) defines governance as "rules, enforcement mechanisms, and organizations"

Ad 2. The WGI include 31 different data sources and they are measured by 25 different organizations

Ad 3. WGI includes six different indicators representing three different processes: first represent the process by which governments are selected,

monitored, and replaced, second process which boots the capacity of the government to

effectively formulate and implement sound policies third process which elevates the respect of citizens and the state

for the institutions that govern economic and social interactions among them (Kaufmann et al, 2010)

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1. Voice and Accountability (VA) – captures perceptions of the extent to which a country's citizens are able to participate in selecting their government, as well as freedom of expression, freedom of association, and a free media.

2. Political Stability and Absence of Violence/Terrorism (PV) – captures perceptions of the likelihood that the government will be destabilized or overthrown by unconstitutional or violent means, including politically‐motivated violence and terrorism.

3. Government Effectiveness (GE) – captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies.

4. Regulatory Quality (RQ) – captures perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development.

5. Rule of Law (RL) – captures perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence.

6. Control of Corruption (CC) – captures perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as "capture" of the state by elites and private interests.

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Country Regional inequalities Belgium 25.3Bulgaria 25.5Czech Republic 24.7Denmark* 15Germany 17.5Greece 24.6Spain 19.2France 20.4Hungary 35.1Netherlands 11.2Austria 17.4Poland 18.7Portugal 22.7Romania 25.1Slovakia 28.8Finland 16.2Sweden 15.2United Kingdom 22.3* Available data for year 2000 and period 2005-2007.

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Table 1. Dispersion of regional (NUTS II level) GDP per capita (ppp) for period 2000-2007

Descriptive statistics

Mean

Overall Standard Deviation

Between Standard Deviation

Within Standard Deviation Minimum Maximum Obs

disp 21.575 5.8548 5.7744 1.6787 10.6 37.8 140

AK 0.0766 0.0486 0.4647 0.0143 0.0094 0.3023 175

Sfpercapita 59.6678 75.5752 65.0856 40.2146 0 392.5347 270

Fiscal decen 11.9851 7.4732 7.4937 1.2538 0.6 36.6 270

Realopeness 1043.21 4084.473 4095.599 642.8103 23.6989 26547.55 269

I 1.1174 0.4661 0.4672 0.0787 -0.0759 1.900 243

CC 1.1154 0.7490 0.7506 0.1274 -0.3430 2.4665 243

PV 0.8537 0.3651 0.3358 0.1559 -0.1798 1.5768 243

VA 1.1751 0.3139 0.3091 0.0781 0.3440 1.8266 243

GE 1.2036 0.6028 0.5933 0.1515 -0.1266 2.124 243

RL 1.1316 0.5690 0.5705 0.0949 -0.1555 1.9640 243

RQ 1.225 0.4008 0.3921 0.1094 -0.1045 2.0120 243

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Table 2. Summary statistics for explanotory variables

Variable Model

Const. 10.7997***Lagged disp2 0.6918***AK -4.0518SFpercapita 0.0071***

Fiscal decen -0.1565***Realopeness -0.0001**I -1.6761**Number of observation 84Sargan test (p-value) 0.4512m1-test (p-value) 0.1081m2-test (p-value) 0.7611

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Table 3. The results of two step Arellano-Bond dynamic panel estimator

Variable AK Sfpercapita Fiscal decen Realopeness IAK 1        

Sfpercapita 0.1478 1      Fiscal decen -0.33 -0.169 1    Realopeness -0.0999 -0.0434 0.0306 1  

I -0.5393 -0.0175 0.513 -0.07 1

Source: Calculation by authors

Correlation coefficients

Relevance of the institution quality should not be an enormous surprise. (e.g. Farole et al, 2009).

But, how the institutional factors contribute to the regional inequalities or how institutions shape the ability of an economy to use and develop its resources in particular ways?

Therefore, goal of the second hypothesis is to recognize which dimension of the institutional quality is important for pattern of regional imbalances

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The complexity of institutions is confirmed by the existence of multiple types of institutions.

Three different processes important for institution quality (Kaufmann et al, 2010)

Emphasizing the processes dimension of the institution in recent literature (Glaeser et al., 2004) puts on top the third approach

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For the testing H2 we use model structure:

(2)

Variable represents n dimensions of institution quality measured by different indicators (n = 1 to 6, where:

1 stands for Voice and Accountability (VA), 2 for Political Stability and Absence of Violence/Terrorism

(PA), 3 for Government Effectiveness(GE), 4 for Regulatory Quality(RQ), 5 for Rule of Law (RL) and 6 for Control of Corruption (CC)).

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Tit it it itY X In

itIn

Variable CC PV VA GE RL RQ

CC 1          

PV 0.5838 1        

VA 0.9096 0.64 1      

GE 0.949 0.6063 0.9142 1    

RL 0.948 0.6476 0.9282 0.9422 1  

RQ 0.8794 0.5823 0.8664 0.9023 0.8967 1

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Table 4. Correlation coefficients of institutional quality indicators

The Table 4: expect high risk of multicolinearity problem Therefore, we will test six models, each including control variable vector and different indicator for institutional quality.

Variable Model 1 Model 2 Model 3 Model 4 Model 5  Model 6

Const. 9.6130*** 9.0647*** 9.9428*** 13.26931*** 12.3103*** 12.5813***Lagged disp2 0.6877*** 0.6520*** 0.7329*** 0.5383*** 0.6479*** 0.5929***AK -7.33425 -18.72206** 2.379746 -38.40294*** -2.9778 -11.71705SFpercapita 0.0817*** 0.0077*** 0.00871*** 0.011351*** 0.0085*** 0.00689***

Fiscal decen -0.0981* -0.0683 -0.2045*** -0.1112 -0.1248** -0.1237**Realopeness -0.00007* -5.0000 -0.00017*** -0.00014*** -0.00008 -0.00004Voice and Accountability (VA) -1.0111***Political Stability and Absence of Violence/Terrorism (PV) 0.377292*Government Effectiveness (GE) -1.142454*Regulatory Quality (RQ) 0.2635324Rule of Law (RL) -2.721868***Control of Corruption (CC) -1.364107***Number of observations 84 84 84 84 84 84

Sargan test (p-value) 0.5373 0.5721 0.3584 0.1796 0.3304 0.4064

m1-test (p-value) 0.0895 0.0974 0.1236 0.1977 0.0925 0.1141

m2-test (p-value) 0.8835 0.9344 0.8104 0.6936 0.8092 0.5929*, **, ***- indicate significance at 10%, 5% and 1% levelSource: Calculation by authors

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Variable CC PV VA GE RL RQAK -0.4594 -0.3888 -0.55 -0.532 -0.4975 -0.6299

Sfpercapita -0.0647 -0.0544 0.0434 -0.0127 0.0205 0.0043Fiscal decen 0.5715 0.2088 0.5141 0.5419 0.4628 0.4463Realopeness -0.1237 0.0263 -0.0334 -0.0914 -0.0711 -0.0169

Table 5. The results of two step Arellano-Bond dynamic panel estimator for six indicators of WGI

Correlation coefficients

The confirmation Voice and accountability indicator, Rule of Law indicator and Control of Corruption indicator show that for regional growth inequalities are the most important:

processes that elevate the respect of citizens and the state for the institutions that govern economic and social interactions among them

and, to some extent,process by which governments are selected, monitored and replaced.

Process which boots the capacity of the government to effectively formulate and implement sound policies has showed not significant for regional growth pattern.

CONCLUSION?

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The results show that for regional growth inequalities in EU the most important processes are those that elevate the respect of citizens and the state for the institutions that govern economic and social interactions among them.

These could be because processes reduce transactions costs by lowering uncertainty and facilitating the mutual trustworthiness of individual economic agents.

Also, it has been shown, to some extent that process by which governments are selected, monitored, and replaced are important for regional growth pattern indicating that on regional level institutions also shape economic outcomes indirectly through political channels, in terms of both policy and the performance of the government bureaucracy.

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The end

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◦ “WGI provide very broad country coverage, greater than that provided by any individual data base”

◦ “WGI by averaging information from many different data sources are able to conveniently summarize the wealth of existing information “

◦ “WGI by averaging also able to smooth out some of the inevitable idiosyncracies of individual measures and so be more informative about the broad notions they are intended to measure than any individual data source”

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MUSTRA & SKRABEC“Regional Inequalities in the EU and

the Role of Institutions

COMMENTS by Oleh Havrylyshyn

A BOLD ATTEMPT TO TEST HYP.: BETTER INSTITUTIONS WILL CLOSE REGIONAL GAPS,HELP ACHIEVE EU COHESION GOAL

NOVEL: USES WB GOVERNANCE DATA EMPIRICAL RESULTS : INDIRECT TEST OF

HYP.- FINDING THAT COUNTRIES WITH BETTER GOVERNANCE HAVE LESS REGIONAL INEQUALITY

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ACTUAL TEST IS NECESSARILY INDIRECT GIVEN NO REG.INST.DATA : OK , BUT THEN MORE CAUTIOUS INTERPRETATION OF RESULTS

PERIOD COVERAGE MAY BE TOO SHORT FOR PHENOMENA THAT ARE LONG-TERM INST. IMPROVEMENT; INC.CATCH-UP

GIVEN ABOVE PROBLEMS, NEED TO DO MUCH MORE ROBUSTNESS TESTS

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I ASSUME REG. DATA AVAIL. For INC, SF- BUT NOT FOR INSTITUTIONAL INDICATORS?

THEN,OBVIUOSLY TEST CANNOT BE DIRECT, AND SEEMS SENSIBLE TO SPECIFY SPECIFICATION THAT REGIONAL INEQUALITY IN COUNTRY X LESS WITH BETTER INSTITUTIONS PLUS OTHER CONTROL VARIABLES? OR IS IT THE SAME ?

THIS IS OK BUT NEEDS JUSTIFICATION, POSSIBLE DIFF.SPECIFICATIONS.

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UNDER WHAT CONDITIONS DOES INCOME NARROWING IN A COUNTRY NECESSARILY MEAN COHESION? i.e. if mezzogiorno catches up 10 pts. to lombardia, but Italy grows far more slowly than Netherlands …then what??

ARE THERE POSSIBLE PROXIES BY REGION OF INST.? DATA, OR ECONOMETRIC ESTIMATE?

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INST.LIT CLEAR THAT EFFECTS TAKE MANY YEARS, DECADES ( North suggests centuries)

INCOME CATCH-UP ARITHMETIC ALSO POINTS TO LONG PERIODS FOR CATCH-UP: e.g: Port.1896 inc.= 45% EUAV 2006=65 (not easy to know how much was due to INST. catch-up, or new markets, or regional funds.)

VERY REMINISCENT OF PROBLEM WITH EMPIRICS OF INST SUCH AS Rodrik Subramanian,Trebbi:-their finding that institutions rule uses effectively very long-run sample (today’s GDP is cumulated effect of decades, centuries- and the institutions maybe effect as much as cause.

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ADVANTAGE OF EXERCISE: DATA SAMPLE IS QUITE LARGE (at least 84, Tab. 2 suggests much more depending on specification)

YOU DO LIMITED ROBUSTNESS , FOR INDIVIDUAL WGI VAR’S—SURELY CAN DO MUCH MORE”

QUESTIONS THAT COULD BE ASKED:1. Diff. between old , new members?2. Can more effort get data for other members? 3. Why VA, ROL,CC signif. but not GE? Last may be

best measure of using SF efficiently4. Do other INST indicators give similar results: Doing

Business, Heritage oundation , Fraser Inst, TI

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ONLY OLD MEMBERS;ONLY NEW MEMBERS;

CROSS-SECTION FOR FIRST AND LAST YEAR - THIS WOULD MEAN USE ONLY THE “I” , AND NOT ALL CONTROL VARS.

DIFFERENT MEASURES OF INST LEAVE OUT OPENNES MEASURE :

[X+M] RATIOS, EVEN ADJUSTED MAY BE IRRELEVANT HERE—TRADE RESTRICTIVENESS EQUAL FOR ALL EU

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