Spatial Proximity and Firm Performances: Empirical Evidence from Turkey, Tunisia, and Italy

1. FEMISE Annual Conference 2016 13-14 February 2016 Hotel Grande Bretagne, Athens, Greece Theme: “Two Decades after Barcelona: Rethinking the EU-Med Partnership” Spatial proximity and firm performances. Empirical evidence from Turkey, Tunisia and Italy. THEME: TRANSITION OF SOUTH MED ECONOMIES: ECONOMIC TRANSITION 1st Round Femise Internal Competition 2015 Agreement No. FEM41-09. Femise Partners: ESSEC (HIGHER SCHOOL OF ECONOMIC AND COMMERCIAL SCIENCES, ESSEC) University of Tunis

2. Outline of the PRESENTATION • Aims of the project • Theoretical background • Research questions: 1) the relationships between localisation economies and firms’ efficiency and growth;  2)  innovation and productivity spillovers at spatial level (taking into account geographical and sector clustering of firms) 3) spatial spillovers by MNEs • Data description • Descriptive analysis of spatial distribution of activities, role of agglomeration economies in Turkey, Tunisia and Italy • Empirical methodology and econometric specification • Preliminary results for Turkey • Preliminary results for Italy • Preliminary results for Tunisia • Further steps

3. Aims of the analysis • to investigate the interaction between firms’ specific variables and spatial factors in enhancing firm ouput, total factor productivity (TFP), employment growth, innovation. • The proposed methodology entails a multidimensional approach to the investigation of the impact of the localisation economies on co-located firm performances: emphasis on micro and macro level (firm, sector and spatial level), firm heterogeneity, complementarity domestic/foreign firms, small/large firms. • 3 countries located in three different regions of the Mediterranean, the North (Italy) the East (Turkey) and the South (Tunisia). • different size and development but all sharing important regional divides, non-inclusiveness of remote areas, polarization of activities and significant support policies in favour of regional convergence and clusters of firms and innovation • The different economic features of the countries involved help us to obtain robust results and a better understanding of the topic in different Mediterranean contexts.

4. Theoretical framework: 1 • Literature on agglomeration economies effects (Glaeser et al. 1992; Porter, 1998; Jacobs, 1969; Jaffe, Trajtenberg, and Henderson 1993; Audretsch and Feldman 1996): • Technology transfers (intra and inter industry knowledge spillover) • Vertical linkages (along the supply chain)and the creation of specialized suppliers • Horizontal linkages (collaboration among firms, imitation) • Concentration of customers and suppliers • Labour market pooling and workers mobility • Informal contacts • Pro-competitive effects (increased competition) • productivity improvements of incumbent firms • reallocation of resources towards more productive firms But also negative effects in the short term: firms can lose the race

5. Theoretical framework: 2 “geography of innovation” literature, which concentrates on measuring localized knowledge spillovers from R&D (Griliches, 1979; Jaffe, 1986; Breschi and Malerba, 2001; Bottazzi and Peri, 2003; Audretsch and Feldman, 2004). Clustering of economic activities as an important driver of R&D via a broad range of processes like learning-by doing, externalities on inputs, knowledge spillovers, labour market and knowledge and R&D cooperation between firms (Rosenthal and Strange; 2001; Ellison et al., 2010; Baltagi et al., 2012). knowledge spillovers tend to vanish rapidly as spatial or economic distance increases (Audretsch and Feldman, 1996; Keller, 2002).

6. Theoretical framework: 3 • Literature on “new new econ. geography”: • spatial sorting of firms according to their productivity: (Baldwin and Okubu, 2006; Martin et al. 2008; Ottaviano, 2011); • Literature on firm heterogeneity and engagement in FDI: • productivity sorting of firms according to their internationalisation (Helpman et al., 2004; Melitz, 2003).

7. (Main) Research questions • The bilateral relationship between localisation, innovation and firms’ productivity: • what role agglomeration economies measured by geographical and sector firm clustering play on productivity spillovers? • how far concentration of intangible assets, patents and R&D of co-located firms should increase efficiency and innovation of close firms? • How all this impact on employment? • What is the complementarity between domestic and foreign firms, small and large firms. How far localisation of firms nearby multinationals and large firms operating in the same localised cluster contribute to develop their productivity? • What is the role of firm size across sectors in localised clusters. Does a difference exists between SMEs and large firms performance and how far does it depend on the industry?

8. Novelty of the analysis • the specific additional insights are: 1) the focus on agglomeration economies and innovation spilloversat spatial and firm level: underinvestigated issues expecially for Turkey and Tunisia 2) the effort to catch firm heterogeneity 3) the application of appropriate quantitative methodologies to better detect spatial spillovers

9. Methodology & data • Three case studies: Italy, Turkey and Tunisia • sameestimation strategies: • panel estimates for output and TFP (by Levinshon and Petrin methodology and by stochastic frontier analysis), and employment controlling for industry, region and time fixed effects • simultaneity and endogeneity addressed using system Generalized Method of Moments (GMM) dynamic panel estimation techniques • butdifferentspatialunit of analysis and differentproxies for innovation • data coverage: • Italy: unbalanced panel of Italian manufacturing firms for 2005-2010 merging AIDA with Capitalia survey Xth wave (manufacturing only). Spatial unit of analysis: LLS; provinces; regions. • Turkey: unbalanced panel data including all private establishments employing 25 or more people for 2006-2013 because 2003-2005 data are not reliable. Spatial unit of analyses: regions. • Tunisia: Balanced panel 1997-2001 extension undergoing to an unbalanced sample 1997-2008 (the only long time series of micro data available in Tunisia at this moment! provided by the Tunisian National Institute of Statistics). Spatial unit of analyses: governorates.

10. STYLISED FACTS ON SPATIAL PRODUCTIVITY, INNOVATION AND FIRM CLUSTERING IN TURKEY maps 1-4 represent respectively geographical concentration of: value added, employment growth, relative productivity, foreign share Figures 1-3 shows the correlations between respectively: regional agglomeration (log regional share of value added) and regional relative productivity: more concentrated regions are more productive regional agglomeration (log regional share of value added) and employment growth: more concentrated regions achieved lower employment growth from 2006-7 to 2011-12(mainly because the less developed regions have higher population growth? Or because concentration enhance productivity but not employment?). regional agglomeration & share of foreign firms in regional output: more concentrated regions attract more foreign firms

11. Maps 1-4: geographical concentration of: value added, employment growth, foreign firm share,relative productivity

12. STYLISED FACTS ON SPATIAL PRODUCTIVITY, INNOVATION AND FIRM CLUSTERING IN ITALY Figures below are 6 maps representing respectively geographical concentration of: firms distribution, output share of the province in the sectoral output (sectoral refers to 2-digit NACE sector), TFP, employment growth, intangible assets and patent distribution at province level Figures 1-6 show the correlations between respectively: province agglomeration (log province share of value added) and TFP: more concentrated provinces are more productive Innovation and agglomerationat province level: positivelycorrelated Innovation and TFP at province level:positivelycorrelated province agglomeration (log regional share of value added) and province employment growth: more agglomerated provinces achieved lower employment growth from 2005 to 2010(mainly because less developed provinces have higher population growth? Or concentration enhance productivity but not employment?). Innovationnotcorrelated with employmentgrowthat province levelnetiher Province agglomeration & share of foreign firms in province output: more concentrated provinces attract less foreign firms

13. Geo-referenced Italian manufacturing firms in our sample

14. Fig. 1 Correlation between TFP and geographical concentration of output in Italy (average 2005-2010) Fig. 2 Geographical concentration and share of foreign firms in Italy Fig. 3 Geographical concentration and employment growth 2005-2010 in Italy Fig. 4 Correlation of intangible assets with measures of geographical concentration of activities Fig. 6 Correlation between intangible asset and employment growth Fig. 5 Correlation between TFP and intangible asset

15. STYLISED FACTS ON SPATIAL PRODUCTIVITY, INNOVATION AND FIRM CLUSTERING IN TUNISIA • Regional disparity in Tunisia is a serious concern. • High levels of inequality and regional disparities led to the Tunisian Revolution in 2011. • The Tunisia‘s interior and coastal regions don’t have the same access to basic public services such as water services (99% in Tunis sand 54.6%in Sidi Bouzid), sanitation (96%in Tunis, and 26.4% in Mednine), proximity to school. • Inequalities between the regions is accentuated by the concentration of economic activities in the coastal region: • coastal area receiving almost 90% of enterprises and 95% of foreign investment (and 65% of public investment) with nearly 40% located in either the Tunis or the Sfax governorate where there are superior infrastructure and transportation networks • deprived regions host only 30% of the Tunisian population and less than 8% of enterprises. • tendency of firms to cluster in Central Business Districts (CBDs) in coastal areas • differences between the more developed coastal region and interior regions have become more pronounced not only due to geographic distance but also unequal infrastructure, transportation and information networks. • Tab. 1 the regional agglomeration (% of firms) • Tab. 2 the share of foreign firms in regional output • Tab. 3 relative size and relative labour productivity of regions • Maps 1-4 visualise the geographical concentration of them and of employment growth.

19. Map. 1: Production share 2001

20. Map 2: Foreign Firms Share 2001

21. Map. 3: Average annual growth of employment over 1997-2001

22. Map. 4: Relative Labor Productivity (2001)

23. Specification of the econometric model The analysis for each economy aims to provide a measure of spatial spillovers on output/productivity/employment fromgeographical and sectorial clustering of firms and from their innovation In addition to considering innovation measures at firm level we build specific indexes of innovation activity at territorial level (regions for Turkey and Tunisia, province or Local Labour System for Italy). we also use indicatorsof innovation performed by domestic and by foreign multinationals at the spatial level of analysis adopted Hence, we try to capture regional and sectoral spillovers from agglomeration of activities, from foreign firms and from innovation performers (both domestic and foreign) in the sector and in the spatial unit under analysis

24. Description of the variables used in the estimates : Lagged output - Labor- Capital - Materials - Energy - Foreign: Foreign firm dummy, 1 if foreign share is >=10%, 0 otherwise. R&D performer: 1 if R&D performer, 0 otherwise - Regional share: Output share of the region in the sectoral output (sectoral refers to 4-digit NACE sector)- Foreign share in the sector: Output share of foreign firms in sectoral output - Foreign share in the region : Output share of foreign firms in total (manufacturing) output - Regional share of domestic R&D performers: Output share of domestic R&D performers in the regional (manufacturing) output - Regional share of foreign R&D performers: Output share of foreign R&D performers in the regional (manufacturing) output- Sectoral share of domestic R&D performers: Output share of domestic R&D performers in the sectoral output - Sectoral share of foreign R&D performers: Output share of foreign  R&D performers in the sectoral output- Market share: Market share of the firm in sectoral output - In all these variables, "sector" refers to 4-digit NACE (Rev. 2) industry, and "region" refers to NUTS 2.

25. Preliminary econometric results for Turkey with the exception of the regional shares of domestic and foreign R&D performers, all variables have positive and significant coefficients. agglomeration has positive externalities there are spillovers from foreign firms regional shares of domestic and foreign R&D performers do not have positive and statistically significant coefficients spillovers from R&D performers seem rather to be sector-specific Validation of these results by using more refined estimations techniques and better proxies for innovation, agglomeration and spatial clusters

27. Preliminary econometric results for Italy significant impact of innovation indicators on firm productivity at local level firms located in LLS get local productivity premiums in presence of higher innovation in the LLS in the same sector, confirming the crucial role played by innovation spillovers due to closeness in enhancing productivity. no evidence of inter-sectoral innovation spillovers from upstream linkages while negative impact on productivity from innovation from downstream suppliers positive spillovers from spatial concentration of foreign firms in the LLSbut negative spilloversdue foreign firms concentration in the sector negative spillovers from foreign firms innovation in the LLS no evidence of spillovers from foreign firms innovation in the sector

28. Preliminary econometric results for Tunisia

29. Preliminary econometric results for Tunisia • These regressions displayed are OLS, we include time dummies • Sign of variables "Labor", "Capital" and "Foreign" are expected • The variable Rd_performer is not significant • Here the spatial variables not always show positive and significant coefficients and some puzzling results come out: • agglomeration do not show significant externalities • no spillovers from foreign firms in the region • negative spillovers from foreign firms in the sector • regional shares of foreign R&D performers do not have positive and statistically significant coefficients • however, strong positive sector-specific spillovers from foreign R&D performers to firms in the same sector • Validation of these results by using more recent data, more refined estimations techniques and better proxies for innovation, agglomeration and spatial clusters

30. Second step of the analysis • extend the time span and perform TFP estimations on each country • study the impact of agglomeration and innovation on employment growth • deepen the analysis of agglomeration and innovation spillovers, using better proxies for innovation, agglomeration and technology clusters • use interactive variables of our indicators of clustering of activities and of innovation with dummies forfirm size in localised clusters • check whether the impact of size also depends on the industry comparing the productivity spillover of larger and small firms in more and less advanced sectors

31. Third step: expected answers to policy relevant issues How far intense competition and polarisation in clusterised areas is able to promote higher productivity and innovation spillovers? How far is it able to promote higher employment growth as well? Is there evidence that firms in the same industry are more technologically similar and this facilitates flow and absorption of knowledge among them? Is the FDI impact relevant at spatial level? What the role of SMEs as drivers or destinators of local R&D spillovers and firm growth? How different is the role of SMEs in low versus high technology sectors?

32. What implications for the economic transition in South Mediterranean countries? a benchmark to analyse: the issue of efficiency of clusters of SMEs in South Mediterranean countries the Euro-Med cluster co-operation on industry and innovation framework the emerging innovation clusters based in Tunisia (Centre Business Districts), in Morocco and Lebanon the effect of “enclaves” where transparent “rules of the game” are credibly enforced with the help of an external policy anchor (see establishment of a “special zone/regime” SEZs such as Tunisia’s “offshore” regime). the role of MNCs