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Inside EU economic space Ex-post convergence vs EMU-OCA challenges

Martino Lo Cascio (University of Rome 2 "Tor Vergata" Massimo Bagarani (University "Guglielmo Marconi", Rome)

Edizione rivista per la riunione del 10 novembre 2016


Summary This paper moves from the Krugman-Euro-OCA European debate and aims to capture additional insights on the Krugman caveats, exploring their spatial side. LB concentration/specialization indices for 98 NUTS1 regions in the 2000-2014 time span are quantified. To test and estimate the convergence/divergence patterns in the context of EU regional policy, a model is developed in the “Complexity-Meso Economics� framework where: a.

The steady state condition, assumed as continuously shifting, represents the result and a new impulse for a platea of adapting decision makers;

b. A chained variable of Total Factor Productivity Transfer (TFPT) is included as a relevant factor in explaining the regional convergence/divergence process. The results on the methodological side are consistent with the hypothesis of the transitional adaptive behavior of the EU regions with shifting steady state condition. The introduction of the TFPT variable, measuring purchasing power transfers among regions, improves the estimates, contributing to a better explanation of the role of economic, political and structural components in the process of searching for transitional steady state conditions. On the operational side, some positive effects of the territorial EU policies, including industrial and capacity building policies, are captured. The unsolved question is whether such effects are counterbalanced by the impacts of EU restrictive fiscal policies (fiscal compact). Finally, some policy insights starting from the political statements of both the Five Presidents Report and the very new "Towards a European Pillar of Social Rights" report are discussed.


Foreword (I) There is some evidence of the existence of the convergence in the EU economic area Convergence in average (current and volume) among EU Regions at NUTS 1 level, period 2004-2012

Grouping the convergence paths on the current productivity values among EU Regions at NUTS 1 level, period 2004-2012


Foreword (II)

This issue partially overlaps with the Krugman-Euro OCA (Mundell II) debate • Endogeneity / Hexogeneity of institutional and economic factors in integrating economic areas in a common currency framework In Krugman, moving towards an OCA could induce vulnerabilities in the participating countries, when external shocks occur, such as: • Demand or supply shocks (when increasing sectoral/regional specializations are enhanced by the common currency) • Macro economic or financial shocks (for instance: financial crisis) • Pro-cyclical effect and/or rigidity in the real rate of exchange adjustment (labor market or public demand)


Objectives The work has the following five objectives: 1. Verify the first type of Krugman caveat with some concentration/specialization indices inside the European space;

ex-post

figures

on

2. Analyze regional economies at NUTS 1 level to capture additional in-sights on the other two Krugman caveats (in our modeling we have adopted a regional dimension, as EU policies - such as industrial policies and the S3 policies - are in fact regionally deployed), as a distinct issue beyond the monetary-fiscal debate at macro-economic level; 3. Improve, theoretically and operationally, the approach for testing and quantifying the convergence hypothesis in the Complexity-Meso Eco-nomics framework: a. The steady state condition, assumed as continuously shifting, is the result and a new impulse for a platea of adapting decision makers; b. The inclusion of the Total Factor Productivity Transfer (TFPT) as a relevant factor in explaining and making endogenous the regional convergence/divergence process; 4. Estimate the magnitude order of the EU regional policies impact in the last ten years on convergence-divergence machine; 5. Provide some policy insights starting from the political statements of both the Five Presidents Report (European Commission, 2015) and the very new "Towards a European Pillar of Social Rights" report (European Commission 2016).


Verifying specializations: the Lo Cascio-Bagarani (LB) specialization index

LBi , j 

qi , j  qi ,.

1  q  q  1  q  q i, j

i ,.

i ,.

i, j

Where:

qi , j 

xij

 xij i

x  x

ij

and

qi ,.

j

ij

ij

Xij is the value added or the number of employees of the region i in the sector j. This index has a range from 1 (highest specialization) to -1 ( lowest specialization). The difference between LBij calculated on value added and LBij calculated on number of employees, can be considered as a measure of productivity of each region relative to the whole EU sample (Lo Cascio, Bagarani 1991) -1

+1


Verifying specializations: is the increasing specialization verified in the time laps?

Declining specialization in sectors - Values of kurtosis in LO-BA specialization indices 2000-2014

Values of skewness in LO-BA specialization indices - 2000-2013 1,5

Skewness values of LO-BA Index

12

Kurtosis values of LO-BA Index

11 10 9 8 7 6 5 4

1

0,5

0

-0,5

3 2

-1 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 VA Industry

VA Constructions

VA Commerce

VA Finance

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 VA Industry

VA Constructions

VA Commerce

VA Finance


Some initial considerations

As for the Krugman type caveat for an Euro-OCA, the specialization/concentration of productivity throughout the EU regions seems not to be conclusive

The inconclusiveness of the introduction of Euro with respect to real exchange rates is also suggested by C. and I. Viera (2012). Their argument “"Is EMU more justifiable ex post than ex ante?" as in (Frankel and Rose, 1997) ex ante analysis. Our ex post examination of the euro's first decade”, is consistent, since ex post estimates of declining standard deviation of real exchange rates mostly holds, “however suggests that the hypothesis does not hold for some countries”.


Literature review I The convergence hypothesis starts from the Swan-Solow model in the mid-1950s (Solow 1956) under the following assumptions: one product, two primary factors and close economy with the convergence achieved at steady state zero growth. Einstein would comment: a model must be simple but not so much. Nonetheless, three Swan-Solow suggestions are still useful: • The decreasing marginal productivity of each primary factor, other things being equal (including the positive effect that endogenous growth factors may have on productivity growth paths in given sectors areas); • The algebraic trick between average rate of growth and the corresponding different levels in the values; • The way the specification of the production function interacts with the convergence problem, where technology is considered as strictly exogenous. A good steady state definition can be retrieved in the thought of J.B. Clark, the father of U.S. economic theory between classic and neoclassic economics (Clark 1886; Clark 1889; Clark 1907). Going through The Philosophy of Wealth, The Distribution of Wealth: A Theory of Wages, Interest and Profits, and Essential of Economic Theory, Clark argues that the spontaneous evolution of free market does not necessarily imply the condition that relative marginal productivity equalizes the relative prices of factors coupled with relative marginal utilities equalizing relative goods and services prices. In this case, a well-oriented public strategy directed to realize this condition is required to enhance the national welfare. The “ethical” commitment of public intervention is to limit the rental position of every operator in the market.


Literature review I Theoretical developments in the following fifty years highlight that conver-gence mechanisms seem to be weaker than expected, particularly as they show longer and more unstable patterns of realization than those suggested in the Solow-Swan model. Following theoretical works have addressed the problem of economic growth by identifying increasing returns and technical change as main factors of de-velopment (Romer 1986; Lucas 1988; Mankiw et al. 1992; Barro and Sala i Mar-tín 1997). Literature on regional economic growth and convergence provided some evi-dence on several relevant factors affecting economic processes (De la Fuente 2001), mainly assuming various extensions of the neoclassical production function in cross-section and panel regressions with Barro’s approach of convergence clusters and the transfers of countries between and within clusters (Barro and Sala i Martín 2004). Theoretical conclusions and policy implications had not enjoyed consensus, although it is widely recognized the relevance of human capital, structural change, reallocation of productive factors across sectors and heterogeneity of narrow defined steady state regional conditions. A mixed approach based on the existence of coexistence of increasing and de-creasing scale economies was introduced by Brian Arthur in complex adaptive systems (Arthur, 1989, 2013). In Brian Arthur, cumulative effects are self-reinforcing, up to a certain thresh-old value beyond which they change direction. The economic system walks ran-domly up to that threshold value beyond which changes drift. Furthermore, the Baumol-Fontela approach that puts in relation the transfers of total factor productivity generated by the difference among factors requirement, the factor prices and the final goods prices, due to the effects of technology, has to be taken into account (Hieronymi, Lo Cascio 2016).


Literature review III

More recently, convergence theory shows a new life thanks to the European theoretical and operational debate, mainly on Euro-OCA interactions (Mongelli 2008 and subsequent contributions and different conclusions based on time series cointegration). In this work, a quantitative analysis is proposed, starting from “Economic space trajectory through different regional growth models” (Lo Cascio et al., 2012), with three main areas of application: 1. specification of the expected productivity with a generic quadratic function including as special cases Cobb-Douglas functions, C.E.S. functions, cumulative increasing returns functions; 2. considering the usual beta-convergence parameter as representative of an adaptive behavior; 3. assuming that all market operators have a rational myopic behavior, since the overall decisions are based on ex-post interaction. Public intervention based on this Clark type “ethical” commitment are justified.


Data The work is mainly based on statistics provided by Eurostat at regional level and focuses on 28 countries and 98 NUTS1 regions in the period 2000-2014 (with the exclusion of Spanish regions starting from 2008)

Different sub-sets of data are used: • • • • • • • • • • •

EUROSTAT Regional economic accounts (ESA 2010) EUROSTAT Regional education statistics EUROSTAT Regional employment European Commission Belgium – stat.nbb.be Germany – destatis.de Italy – dati.istat.it Netherlands – cbs.nl OECD – stats.oecd.org Spain – ine.es The World Bank – data.worldbank.org


b and s convergence in the light of data Unconditional beta convergence on constant values of productivity

s-convergence as standard deviation trend in the period 20022014 Variable: productivity a.a.r. at current and constant prices


The model: general specification (I)

1  j ,h ln X j ,t  ln X h,t   j h 2

[1]

ln Yi*,t   i   j  j ln X j ,i ,t  

[2]

ln Yi ,t  ln Yi ,t   b (ln Yi *,t  ln Yi ,t  )

[3]

ln Yi ,t  b i  b  j  j ln X j ,i ,t  

1 b  j  h  j , h ln X j ,t  ln X h,t   (1  b ) ln Yi ,t  2

where: Yi *,t = expected transitional steady state productivity in region i relative to EU regions average conditioned to  i and X j , i , t 

Yi ,t = gross productivity in 2001 purchasing power in region ith relative to EU regions average X j ,i ,t  = physical and human capital structural indexes, relative to EU average and total factor productivity transfers (XP,i), defined below b = adaptive coefficient to the above defined steady state, with 0  b  1

 i = social/institutional factors specific for region  j ,  j ,h = across regions constant parameters for observed factors Xj,i = 0,1 depending on factor inputs j,h = [1,…,H], i = [1,…,N] and t = [1,…,T]


The model: general specification (II) From [1], [2], [3]

[4]

d ln Yi ,t   i   j  j ln X j ,i ,t  

1   h j ,h ln X j ,t  ln X h,t   b ln Yi,t    i,t 2 j

Where i  bi ; and  j ,h  b j ,h ; and  j  b  j if  j  0 we expect  j  0 if b  1 and  j ,h  0 then the productivity function degenerates into a Cobb-Douglas function if  j ,h  h, j   1  2j , j   1 h2,h then the productivity function degenerates into a CES function 2 2 For d ln Yi ,t  0 then ln Yi ,t  ln Yi ,t  so [5]

j i 1 ln Y    j ln X j ,i ,t    ln X j ,t  ln X h,t    j  h j ,h b b 2b 1   i   j  j ln X j ,i ,t    j  h  j ,h ln X j ,t  ln X h,t  2 * i ,t


The estimated model (I)

[6]

d ln Yi ,t   i  b ln Yi ,t   1 ln Invi ,t    2 ln TFPTi ,t  1 ln Invi2,t   2 ln TFPTi ,2t  3 (ln Invi ,t   ln TFPTi ,t )   i ,t with: i  v0  vi  vt and i,t ~ (0,s2)

Invi ,t  where:

 i ,t 

INVi ,t K i ,t  (1   ) K i ,t 1 K i ,t    (1   i ) * i GDPi ,t Li ,t i ,t Li ,t i ,t

GDPi ,t Li ,t

K i ,t = capital per employee adjusted with internal technical progress Li ,t i ,t

= capital depreciation and

= capital output ratio approximately constant over time but different across regions

L = Labor Invi,t = capital/labor ratio adjusted for capital/output ratio and related depreciation rate


The estimated model (II)

n   p Q  i , t i , t   pi ,t Qi ,t  pi ,t Qi ,t 1 * ni   p Q  i , t i , t  1 i TFPTi ,t  1   mt    pi ,t Qi ,t      

With: mt = median of Laspeyres chained indices for each year (t) in the EU regions

Qi ,t = chained Laspeyres volume GDP index at time t

GDPi ,curr t pi ,t  Qi ,t


The TFPT

The TFPTi is a measure of the difference between current GDP and a benchmark hypothetical GDP, being the last one representative of the perfect malleability of production factors, i.e. the quantity are equal to their purchasing power and the Euro area average for each year

p Q  * p Q n

pi ,t Qi ,t  pi ,t Qi ,t 1

i n

i

pi ,t Qi ,t

i ,t

i ,t

i ,t

i ,t 1

A

If A = 0 → TFPT = 1 If A > 0 → TFPT > 1 that is: increase in productivity of factor inputs in region ith is not completely reflected in distributed value of net product. The opposite happens if A < 0 → TFPT < 1 .

The TFPTs shift the productivity functions in the light of i) hysteresis factors ii) market conditions iii) macroeconomic and regional policies or, from another point of view, the equation [1] identifies an envelope of transfer functions from inputs to outputs


The estimates Variables Productivity t-1 t

model 1

model 2

model 3

-0.19949

-0.10971

-0.10512

-0.093503

-11.35

-7.31

-7

-6.06

-0.009525

-0.3199

-0.24352

-1.68

-3.09

-2.29

0.58022

0.54867

-1.9004

20.81

18.49

-2.3

Investments t-1 t TPPT t TPPT 2 t

1.2442 2.97

Interaction t Constant t N df_r df_m r2_w r2_b r2_o F

model 4

0.31217

0.23428

3.00

2.2

-0.052212

-0.60851

-0.57601

0.63108

-11.24

-22.58

-19.92

1.55

910

910

910

910

818 91 0.13612 0.35414 0.085301 128.89

816 93 0.43703 0.41729 0.16179 211.16

815 94 0.4432 0.41994 0.16702 162.18

814 95 0.44918 0.43379 0.18173 132.76

Model 4 does not include the quadratic term of investment/output ratio since the specific parameter is not significantly different from zero at 95%.


Relative position Model 4 vs Model 1


Overall period Clusters East EU NO euro Core EU LOW Core EU Medium ITALIA - SUD

3.21 0.18 1.52 1.18

3.81 1.51 0.80 -0.18

1.37 -1.66 -0.19 0.17

6.99 1.70 2.32 1.01

23.92 21.85 20.71 20.85

Fixed effects -8.65 -0.54 3.27 0.0452

ITALIA - ISOLE

1.40

-0.21

0.15

1.19

20.37

0.0459

Core EU euro HIGH

1.78

0.48

0.01

2.25

20.79

5.24

ITALIA - CENTRO ITALIA - NORD OVEST ITALIA - NORD EST

1.68 1.62 1.89

-0.18 -0.16 -0.17

-0.09 -0.09 -0.02

1.51 1.46 1.72

18.11 20.18 21.50

0.0545 0.0610 0.0548

High revenue regions

2.67

0.55

0.89 3.22 Period: 2004-2008

18.79

8.52

East EU NO euro

5.48

7.70

24.94

-8.62

p

tppt

2.52

val

13.16

inv

Core EU LOW

2.07

2.33

-0.77

4.40

23.54

-0.53

Core EU Medium

2.44

0.67

-0.43

3.11

21.08

3.27

ITALIA - SUD

2.76

-0.12

-0.43

2.65

22.07

ITALIA - ISOLE

3.16

-0.10

-0.31

3.06

22.67

Core EU euro HIGH

3.17

0.44

-0.13

3.60

21.50

ITALIA - CENTRO

3.41

-0.12

-0.67

3.29

18.92

ITALIA - NORD OVEST

3.38

-0.11

-0.67

3.27

20.93

ITALIA - NORD EST

3.55

-0.13

-0.69

3.42

22.93

High revenue regions

4.00

0.36

1.11 4.38 Period: 2008-2013

18.92

8.49

East EU NO euro

0.95

-0.08

0.21

0.82

23.56

-8.67

-1.71

0.70

-2.54

-1.00

20.53

-0.56 3.27

Core EU LOW

q = rates of growth of volumes tfpt = rates of growth of productivity transfers p = rates of growth of prices val = rates of growth by values

q

Core EU Medium

0.61

0.93

0.04

1.53

20.49

ITALIA - SUD

-0.395

-0.237

0.764

-0.632

19.62

ITALIA - ISOLE

-0.367

-0.317

0.614

-0.684

18.07

Core EU euro HIGH

0.39

0.52

0.15

0.90

20.31

ITALIA - CENTRO

-0.046

-0.230

0.480

-0.276

17.30

ITALIA - NORD OVEST

-0.132

-0.218

0.492

-0.350

19.44

ITALIA - NORD EST

0.231

-0.215

0.651

0.016

20.06

High revenue regions

1.34

0.73

0.67

2.07

19.00

5.24

5.24

8.56

The comparison among clusters of the aggregate rates, shares on GDP (INV) and values (FE)


The share of the investments on the GDP The loss of momentum before and after crisis Cluster

2004-2008

Loss of momentum

2008-2013

East EU NO euro

24.94

-1.37

23.56

Core EU LOW

23.54

-3.00

20.53

Core EU Medium

21.08

-0.60

20.49

ITALIA - SUD

22.07

-2.45

19.62

ITALIA - ISOLE

22.67

-4.60

18.07

Core EU euro HIGH

21.50

-1.18

20.31

ITALIA - CENTRO

18.92

-1.62

17.30

ITALIA - NORD OVEST

20.93

-1.48

19.44

ITALIA - NORD EST

22.93

-2.87

20.06

High revenue regions

18.92

0.07

19.00


Fixed effects in the development path of the EU Regions - 2004-2013 (panel)


Fixed effects theoretical projection - 2004 vs 2013


Comparison between total increase in GDP and total amount of structural funds committed

Clusters East EU NO euro Core EU LOW Core EU Medium Sud Isole Core EU euro HIGH Centro Nord-Ovest Nord-Est High revenue regions

Total increase of Total amount of current GDP in structural funds the period 2004- (ERDF+ESF) in the 2013 period 2004-2013 458,529 126,315 77,635 77,110

% on GDP increases

TFPT - % on GDP increases

27.5% 99.3%

23.8% -153.6%

945,269

63,718

6.7%

-10.6%

17,049 9,763

4,346 3,547

25.5% 36.3%

27.4% 21.2%

573,296

45,150

7.9%

0.2%

32,988 54,342 43,136

10,354 6,096 16,101

31.4% 11.2% 37.3%

-7.3% -6.6% 0.3%

299,642

2,892

1.0%

36.5%


Difference between productivity gross of implicit re-distributional effects of regional EU policies vs net effects of regional EU policies (%)

by cluster

by Italian regions


Conclusions (I)

On methodological side

The results are consistent with the hypothesis of the transitional adaptive behavior of the EU regions with shifting steady state condition (the extended Lo Cascio Bagarani Zampino 2012 approach). The introduction of the new variable- the Chain TFPT Index - improved the estimation, contributing to a better explanation of the role of economic, political and structural components in the process of transitional steady state conditions research attainment.

On operational side The positive effects of the territorial EU policies, including the industrial policies but also the capacity building policies oriented to improve the local administration efficiency, are captured. The question is: have these effects been counterbalanced by the negative effects of a restrictive fiscal macroeconomic policy?


Conclusions (II)

The fixed effects seem to have a negative impact on the convergence path and this would call for a policy action aimed at supporting the improvement of social and structural (context) conditions in less developed EU regions.

Lo Cascio and Aliano (2016) put the subject under question: “Is the Eurozone at a turning point? The descriptive diagnostic and the statistical model carried out do not prevent us to reply: yes”. The EU faces three alternative scenarios: i) Myopic Currently Policy (M.C.P.), ii) High Risk scenario and iii) Opportunity of Recovery (O.R.). “Starting from the turning point, it is more than an opinion that small institutional changes and a limited set of operators can shift the overall trajectories of the EU system from one to another options.” (see also Hieronimi and Lo Cascio 2016). Here is the room for the political statements of both the Five Presidents Report and for the very new "Towards a European Pillar of Social Rights" report. Pushing knowledge improvement in a “labor market” (where the labor is considered as a product and not anymore as a production factor) with an active role of public policies, instead of leaving the task to the market, may induce a rental position for unemployed persons, à la Schumpeter, even with opportunistic behavior, but it can also play a decisive role in supporting the growing path of the regions and in achieving better conditions of convergence.


pp-seminario-g20_2-10-11-2016