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PIER ANGELO MARIA TONINELLI Growth and entrepreneurship in Italy: a regional approach El empresariado español en el contexto regional Alcalà, 5-9 July.

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Presentation on theme: "PIER ANGELO MARIA TONINELLI Growth and entrepreneurship in Italy: a regional approach El empresariado español en el contexto regional Alcalà, 5-9 July."— Presentation transcript:

1 PIER ANGELO MARIA TONINELLI Growth and entrepreneurship in Italy: a regional approach El empresariado español en el contexto regional Alcalà, 5-9 July 2010

2 The outline 1.The growth of the Italian economy 2.The regional development 1.Regional disparities: per capita value added 2.Regional disparities: distribution of workforce 3.Regional disparities: productivity 3.The regional distribution of enterprises SOES: Number and assets Industrial districts 4.Italian entrepreneurship: determinants and distribution 1.The framework 2.The sample 3.The clusters

3 Per capita GDP: Italy vs Spain (UK=100) Source: our own elaborations on Maddison 2001 First stage of industrialization (1896-1914) Economic miracle (1950s-1960s)


5 189119111938 1951 1971 198119912001 Piedmont 1.471.211.141.15 Aosta Valley 1.581.351.301.181.24 Liguria 1.441.541.681.621. Lombardy North-West Trentino-Alto A. --0.951. Veneto 0.800.860.840.980.991.081.121.13 Friuli -- Emilia Tuscany 1.030.971.011.05 The Marches 0.880.810.790.860.911.050.99 Umbria 1.020.920.960.900.930.980.970.96 Latium 1.571.491. Center/north-east 1.11 1.13 Abruzzi 0.660.680.58 0.800.840.890.84 Campania 0.970.940.820.690.710.670.680.65 Apulia 1.020.850.720.650.750.720.730.67 Lucania 0.740.730.570.470.750.680.660.73 Calabria 0.670.700.490.470.670.650.590.64 Sicily 0.930.850.720.580.700.710.680.66 Sardinia 0.940.920.830.630.850.720.740.76 South and islands 0.880.840.700.610.730.70 0.68 Italy (2001 euros) 1,3132,0642,5962,94010,02713,19916,47019,928 Yearly growth rate (%) -2.290.850.966.332.792.241.92 Regional disparities in Italy: per capita value added, Italy =1 (Source: Felice 2010 )

6 Some basic facts of regional development (1) Around 1860, the Italian economy was made up of different local economic systems. These followed the political map of pre-unification Italy but with some additional fragmentation, like the disparities within the former Southern kingdom, the Papal states or the kingdom of Savoy It was still overwhelmingly agricultural, with an urban life and manufacturing and tertiary poles mostly located on the western coast, from Turin and Genoa southward to Naples and Palermo Contrasting findings about the level of regional disparities north-south divideBy 1891 the north-south divide was relatively modest, but already clear. The rise of the north-west was modest during the Giolitti’s age, much speeder over the following four decades Southern Italy fell back dramatically, whereas the center/north-east (Nec) regions hovered around the Italian average, but with considerable differences Over the first half of the twentieth century, differences within the macro- areas decreased; conversely, they augmented within Italy as a whole.

7 Convergence took place between 1951 and 1971, that is during the very years of most intense national economic growth In the 1970s, the stagflation crisis, southern Italy began to fall back again, while the Nec regions converged towards the north-west at a remarkable speed during the last two decades of the 20th century this trend continued but slower Williamsonian convergence occurred in the Nec regions, whilst southern convergence during the 1950s and 1960s was exceptional and transitory due: – to interregional migration –to the massive regional policies pursued by the state through the agency called ‘Cassa per il Mezzogiorno’ The south’s falling back during the last decades, when on the contrary it was expected to converge towards the rest of the country, was again exceptional low levels of social capital or institutional failure probably referable to the role of conditioning variables, such as low levels of social capital or institutional failure Indeed during the 1973–98 years the south’s rate of growth was approximately on the average of western Europe; but its product per capita was just two-thirds Some basic facts of regional development (2)

8 Workforce in agriculture (%)Workforce in industry (%) 19111951197120011911195119712001 Piedmont 55.4 34.813.83.7 27.4 39.150.438.2 Aosta Valley Liguria 35.125.810.83.532.329.932.423.1 Lombardy 43.323.26.41.937.646.354.739.9 North-West Trentino-Alt. A. (66.5)49.319.78.3(15.5)21.629.126.7 Veneto 61.148.617.14.221.525.542.640.7 Friuli (51.9) Emilia 58.347.718.75.624. Tuscany 50.941.013.03.930.8 43.034.1 The Marches 67.455.926. Umbria 69.555.623.44.717.521.636.132.8 Latium 44.932.810.03.623.020.526.319.7 Central/north-east 57.544.516.04.523.924.936.832.8 Abruzzi 77.269.336.46.813. Campania 53.446.625.76.923.320.929.624.4 Apulia 63.064.739.911.720.113.424.126.1 Lucania 76.775.243.710.812.811.023.834.6 Calabria 67.366.438.812.020.615.325.619.4 Sicily 52.756.430.39.622.816.926.119.9 Sardinia 59.056.527.08.520.917.526.923.0 South and islands 60.559. ITALY (%) 55.444.618.95.225.526.838.132.0

9 Data on sectoral employment confirm that the industrial triangle was already apparent in 1911. Lombardy Liguria Lombardy was the most industrialized region and it would keep this primacy through most of the 20th century, while Liguria ranked second. In NW industrial workforce had reached one third of the total; less than half the labor force was engaged in agriculture. The NW reached remarkable shares of the industrial production: in textiles, 50 per cent of the Italian total production was in Lombardy Lombardy and PiedmontIn Lombardy and Piedmont the three main industrial sectors – textiles, food and engineering – absorbed 50% of total industrial production. These three regions could boast a wide range of manufacturing activities above the national average: it meant that the north-west benefited of general systemic advantages, rather than of specific sectoral ones At the origins of their success lied the exploitation of local (regional) comparative advantages: hydraulic power (later hydroelectricity) and local raw materials (silk), as well as the possible complementarity between agricultural and industrial activities Some basic facts of regional development (3)

10 Product per worker (Italy=1)Activity rates (Italy=1) 19111951197120011911195119712001 Piedmont 0.99 1.17 Aosta Valley Liguria 1.501.661. Lombardy 1.131.371. North-West 1.111.351. Trentino-Alt. A. -1.000.971.08- Veneto 0.870.961.010.960.991.020.981.17 Friuli -1.060.920.98- Emilia 1.051.19 Tuscany 0.961.00 1.011.05 1.09 The Marches 0.780.800.900.881. Umbria 0.910.88 0.941. Latium 1.541. Central/north-east 0.991.01 1.11 Abruzzi 0.660.590.900.871.020.980.880.97 Campania 0.970.830.930.910.980.840.760.71 Apulia 0.940.710.920.830.910.920.820.81 Lucania 0.690.420.870.821.061.120.860.89 Calabria 0.670.470.840.851.041.010.790.75 Sicily 1.050.740.990.920.810.790.710.72 Sardinia 1.110.701.120.860.820.890.760.88 South and isl. 0.910.690.940.880.920.890.770.77 Italy (%)* 4,3586,98627,04354,21147.342.137.136.8

11 South-North convergence in productivity (1951-1971) –Product per capita can be decomposed in two components: product per worker and workers per capita (activity rates). Product per worker, in turn, depends on productivity within each economic sector, and on the allocation of the workforce across sectors with lower productivity (usually agriculture) and those with higher one (industry and services), activity rates from gender. In 1950, a complex regional program called ‘Extraordinary intervention for the South’ was set-up, to be implemented by the state agency ‘Cassa per il Mezzogiorno During the 1960s regional subsidies were aimed mostly to heavy industries, with high capital/labor ratios. As a consequence, in the south product per worker rose rapidly (while the share of workforce did not) the extraordinary intervention therefore was an attempt to change southern economy without changing its society migrationanother factor favoured the convergence of southern Italy, migration, but – as long as those who emigrate are from the less productive jobs, as was the case, the average productivity of those who remain increases. At the same time, however, migration is preponderantly of (male) workers, so that the rise in product per worker is partly offset by the decline in workers per capita Some basic facts of regional development (4)

12 190119111951197119812001 1.4291.451 1.2101.0981.1281.048 Val d’Aosta 1.6681.7631.5141.493 Liguria 1.3311.1891.0401.0221.0911.050 Lombardy 1.3701.3641.1791.0871.0671.096 North-West 1.3881.3731.1741.0871.0911.088 Trentino-Alto Ad. --3.9793.6263.1342.057 Veneto 1.1101.1131.0551.1281.2571.255 Emilia 1.2931.2311.2061.0931.2971.272 Tuscany 1.3421.3591.3341.1691.3031.247 The Marches 0.7500.8341.1251.0511.2051.239 Umbria 1.2011.1981.1121.1251.3311.366 Latium 1.0410.9190.8120.8670.7960.804 Center/north-ea. 1.1671.1521.2311.1811.2601.193 Abruzzi 0.6140.6290.6610.7260.8871.131 Campania 0.4910.5050.5420.6590.3740.430 Apulia 0.6870.5860.6820.7110.5480.748 Lucania 0.6370.6970.5570.7890.7850.830 Calabria 0.4380.4830.5410.7380.8170.654 Sicily 0.7090.7220.6690.8060.7330.823 Sardinia 0.4300.5100.7990.9141.0451.095 South and islands 0.5920.5960.6300.7430.6460.641 Pearson correlation with income disparities Correlation 0.5590.5460.7980.7550.7560.704 Regional disparities in social capital (Italy=1 ) source: Felice 2009 N.B. the index is a simple mean of social participation, political participation and trust (Nuzzo 2006)

13 A comprehensive interpretation of the path of regional inequality in Italy has yet to be proposed. the idea that north-western industrialization took place at the expense of the south supported among the others by liberal scholars (Romeo 1959) or Gramscian historians (Villari 1966) According to Cafagna instead the northern regions had pre-existing conditions which ‘naturally’ favoured public and private investments in these areas: as a consequence of market rules rather than of public intervention. Such as a more favourable natural endowment, rich especially in water and thus hydraulic power; higher levels of human capital; better institutions and higher social capital However these three factors had different weights, according to the changes in technological regimes: natural resources were important in the first industrial revolution ( 1830–80), human capital in the second one (1880–970), social capital in the post-fordist age. Some basic facts of regional development (5)

14 The regional distribution of State-owned enterprises (1) But did just the South benefit from State intervention ? A look to the dynamics of distribution of public enterprise in Italy This represents also a step towards the comprehension of Italian regional distribution of all enterprises: –the SOEs dynamics and contribution to the country’s economy – source: Toninelli-Vasta, Size, Boundaries And Distribution Of Italian State- Owned Enterprise (1939-1983 ) in Amatori, Toninelli, Millward, Re- Appraising State Owned Enterprise: a Comparison of the UK and Italy, Routledge (forthcoming) The national series have bee broken down into disaggregate categories, representing four regional macro-areas (North-West, North-East, Central, South and Islands). Each of them has been in turn further subdivided according to the country’s administrative regional structure (that is 19 regions). Such analysis has been performed with regard to number of firms and assets

15 The regional distribution of State-owned enterprises (2) LazioCaveat: SOEs regional distribution data involve some unavoidable bias, that is an abnormal concentration in the Lazio region, where the capital city is located in fact in Rome not only the headquarters of the main state-holdings (IRI, ENI, EFIM) were located, but also a fair number of operating companies. size of assets.Such disproportion does not concern so much the absolute numbers as the size of assets. In fact with respect to the first only in the 1952-54 benchmark-years Lazio shows an abnormal value: 35,3% of the country’s total.

16 NUMBER 19361952-54196019721983 % 19361952-54196019721983 VDA11 ---0,3 PIE78101219PIE7,96,06,14,16,1 LIG814212923LIG9,010,512,710,07,4 LOM2334395870LOM25,825,623,620,022,4 Nord Ovest 385670100113 Nord Ovest 42,742,142,434,536,2 TAA11 ---0,3 VEN524814VEN5,61,52,42,84,5 FVG7551011FVG7,93,83,03,43,5 EMR41438 4,50,82,41,02,6 Nord Est 168132234 Nord Est 18,06,07,97,610,9 MAR22 ---0,70,6 TOS236918TOS2,22,33,63,15,8 UMB25 ---0,71,6 LAZ2447427868LAZ27,035,325,526,921,8 Centro 2650489193 Centro 29,237,629,131,429,8 CAM713253433CAM7,99,815,211,710,6 ABR-MOL13 ---0,31,0 PUG1610PUG---5,53,2 BAS63 ---2,11,0 CAL32 ---1,00,6 SAR1178 -0,80,62,42,6 SIC2581013SIC2,23,84,83,44,2 Sud 919347772 Sud10,114,320,626,623,1 Total89133165290312Total100,0 Regional distribution of SOEs (number and %) source: Toninelli-Vasta 2010

17 But if we turn to the assets data, the share of the Rome region jumps to much higher values, with a record in 1972 (45.1% of the total assets of Italian SOEs) towering over a set of values around 40%. Such region alone attracted Central Italy’s almost entire investment in public firms. Lombardy Lombardy was still the second more concentrated region, even though at much lower level (between 22,8% and 27,3% of total assets). Lombardy’s position in the ranking explained by the area’s high level of industrialization. Such a position in the public sector quite contradicts the conventional wisdom tending to contrast Milan, and the core of the private capitalism, with very few public undertakings, with the political capital Rome, the core of state capitalism in Italy The regional distribution of State-owned enterprises (3)

18 19361952/4196019721983 VDA---0,0 PIE5,85,65,03,97,7 LIG23,020,018,017,920,9 LOM27,322,825,625,324,7 North-West 56,148,448,647,253,2 TAA----0,0 VEN0,51,31,50,30,7 FVG0,14,52,61,61,3 EMR0,6 0,80,00,2 North-East 1,26,44,82,02,2 MAR---0,0 TOS0,2 1,80,71,7 UMB---0,1 LAZ41,641,040,545,137,8 Central 41,841,242,245,939,6 CAM0,73,94,22,23,1 ABR-MOL---0,1 PUG---0,30,2 BAS---0,0 CAL---0,0 SAR-0,0 0,3 SIC0,20,00,11,91,3 South 0,94,04,34,95,0 Total100,0 Regionaldistribution of SOEs (assets %)

19 Looking then at the internal dynamics of the numbers, we can note that three of the four macro-areas do not show a clear trend. Only the South grew both in number and assets: between 1936 and 1972 the number of public undertakings increases from 9 to 72, then a small decline in the next decade: this corresponds to an increase of 12 percentage points (from 10,1 to 23,1). As for assets this meant a growth from an almost non-existent 0,9% in 1936 to 5,0% in 1981, thus marking quite clearly the change of economic policy towards the South since the post-war period. ENI IRI ENI and IRI were among the main instruments through which the government tried to pursue the convergence of the southern regions, especially Campania and Sicily (which received the greatest help), towards the North The regional distribution of State-owned enterprises (4)

20 The regional distribution of the main districts

21 The districts’ share on total firms: number of firms, employment, turnover

22 The Historical determinants of entrepreneurship project (Tortella et al.) aimed to provide an empirical comparative approach to the role of entrepreneurship in economic growth What historians need is thus empirical support, starting at a national level, from which to induce possible generalizations: –datasets, large qualitative samples Most of the new studies converge in this direction Tortella-Quiroga-Moral-Arce 2008 Garcia Ruiz-Toninelli, The determinats of entrepreneurship. Leadership, culture and institutions (Pickering and Chatto, 2010): the proceedings of a special session at the 2009 Utrecht International Conference in Economic History Ch. 3, Toninelli & Vasta; Italian Entrepreneurship. Conjecture and evidence from a historical perspective. This is the first step of an ongoing project, to which we will come back soon. The entrepreneurship (1): the historical determinants

23 The entrepreneurship (2): research questions for the Italian case Is Italy’s prolonged backwardness to be explained mostly by her structural absence of those Schumpeterian virtues - innovative capacity and risk-taking – which were at the basis of the Anglo- American success? Did such a frailty ask for substitutive factors such as State intervention and banks support? Or, au contraire, has that supposed prolonged process of entrepreneurial accumulation been hampered by the State’s political and economic interference and banks’ excessive power? Finally and more generally, is on the whole the Italian institutional setting ill-suited to offer opportunities to the most valid entrepreneurial projects?

24 The entrepreneurship (3): some theorethical suggestions The new entrepreneurial economy induced by the ICT revolution puts forward again the question about the relationship between the expansion and the renewal of the entrepreneurial class and economic growth (Audretsch-Thurik 2001; Audretsch et al. 2003; Baumol et al. 2007; GEM 1997-2008; Monitor Group 2009) Why and how the two relate? Is it possible to figure out some generalizations about the reciprocal behaviour? By now we all know that even though the entrepreneur constitutes “one of the most intriguing” characters acting in the economic game, economics has failed to offer a convincing analysis of its basic features: –most elusive character and analytical vagueness (Baumol 1968; Leff 1979)

25 The broad partition of entrepreneurship proposed by Baumol et al.(2007) in two main categories - innovative vs. replicative entrepreneurs If economic growth is the object of interest, it is the innovative entrepreneur who matters Baumol et al.(2007) also suggest the existence of four different categories of capitalism (different rate of innovation and entrepreneurship) and provide a taxonomy: 1.State guided capitalism Supports particular industries “national champions” 2.Oligarchic capitalism Entangled network of groups and families 3.Big firm capitalism Giant enterprises drive economic system 4.Entrepreneurial capitalism Significant role played by small and medium enterprises The entrepreneurship (4): a taxonomy

26 Italian entrepreneurship (1): Italian entrepreneurship (1): Sources The source of our research is a collection of entrepreneurial biographies prepared for an ongoing Dizionario biografico degli imprenditori italiani (Dictionary of Italian Entrepreneurs), a large project directed by Franco Amatori. This has so far processed about 600 “gross” entries these biographies have been classified on the basis of a scheme (see table 1 in the paper) organized according to the following main categories, which evoke the ones suggested by the Madrid group: –demographic variables –family relations: inheritance, number of generations, marriage –networks and affiliations –human capital formation –Versatility, diversification, geographical mobility –innovation The data collected concern 610 entrepreneurs (volumes 1 and 2 of the Dictionary: letters A to N) Yet it has to be considered that this distribution is not representative of the real geographical allocation of entrepreneurs, as the initial choice of the names to be inserted in the list was purposely biased in order to cover all the national territory.

27 Italian entrepreneurship (2): Italian entrepreneurship (2): The main features of the sample Frequency% Who is Entrepreneur/owner 67 11,0 Entepreneur/manager9215,1 Entrepreneur/owner & manager 449 73,9 Gender Male 598 98,4 Female 10 1,6 Year of birth before 183063 10,4 between 1831 and 1850 8113,3 between 1851 and 187012821,1 between 1871 and 1890126 20,7 between 1891 and 1910150 24,7 after 191060 9,9 Involvement in politics yes188 30,9 No 42069,1 Level of involvement in politics local level 10254,3 national level 5529,3 international level 52,7 Local &national level 2613,8 Frequency% Area of birth Center12620.7 abroad385,7 North-East14023,0 North-West21134,7 South9315,3 Father main activity (459 cases) farmer 153,3 labourer 235,0 manager 183,9 technician 81,7 craftsman 5111,1 entrepreneur 21546,8 freelance 316,8 employee 224,8 merchant 7616,6 Social background Low classes7812.8 middle34256.3 High18830,9

28 Italian entrepreneurship (3): Italian entrepreneurship (3): education and training Frequency% Education level illiterate 10,2 primary education 9315,3 middle school 11318,6 high school 21034,5 laurea degree 18530,4 post-laurea degree 61,0 Field of laurea laws 45241, economics 2312,3 other Arts 105,4 engineering 7339,0 chemistry/Pharmacology 158,0 other Sciences 2111,2 Frequency% Education abroad yes 9115.0 no 51785,0 Experience abroad yes 21635,5 no 39264,5 Experiences abroad (area, 216 cases) developed countries 18585,7 developing countries 3114,4

29 Italian entrepreneurship (4) Italian entrepreneurship (4) The sample: “innovative features” Level of innovationFrequency% no innovation 12220,1 low innovation level 15024,7 medium innovation level 26643,8 high innovation level 7011,5 Level of innovationFreq% 012220,1 115024,7 213021,4 313622,4 4487,9 5172,8 650,8

30 Italian entrepreneurship (5) Indicators of entrepreneurial success Skill for innovationFreq% zero34055,9 low11218,4 medium10316,9 high538,7 Growth in sizeFreq% no growth335,4 local level growth13221,7 national level growth29448,4 international level growth14924,5 Survival after deathFreq% <30 years16326,8 30-50 years365,9 >50 years457,4 still existant34957,4 ceased152,5 Successful brand/productFreq% yes25441,8 no35458,2

31 The sample: the company 1 Ways of acquisitionFrequency% founder27745,6 inheritance20533,7 purchasing345,6 No owner9215,1 Relations with banks yes21335,0 no39565,0

32 The sample: the company 2 Starting sector Agriculture, hunting and sylviculture315,1 Fhising and related activities10,16 Extraction81,32 Manufacture39264,47 Energy-using products, Gas Appliances142,3 Construction243,95 Trade, servicing for cars, goods6210,2 Hotels and restaurants10,16 Transport, storage and communications162,63 Financial services498,06 Property, renting, IT, services20,33 Other public, social and personal services 81,32

33 The variables used for the MCA - I (first exercise, 390 entrepreneurs) ACTIVE VARIABLES (18)ILLUSTRATIVE VARIABLES Entrepreneurial typologyPlace of birth (area) Social classAge Educational levelReligion Father’s educational levelDirect involvement in politics Father’s main activityHonour of Cavaliere del lavoro Family job relationshipsUniversity teaching Typology of the first activityNoble Indirect involvement in politicsMember of aristocracy Affiliation to employers’ associationsAffiliation to Masonry Form of enterpriseFinancial public support Ways of company acquisitionJob relations with the partner’s family Sector of activityExperiences abroad Relations with banksAge of first entrepreneurial activity Innovative entrepreneurMain sector of activity (not aggregated) Product innovationBusiness strategies Process innovationInnovation level New sale markets New markets of production

34 The variables used for the MCA, II (608 entrepreneurs) Active variables (11) Entrepreneurial typology Indirect political involvement Employers association Family job relationship Growth Social class Education level Ways of company acquisition Product and process innovation Main sector of activity New sale market Illustrative variables Religion Direct involvement in politics Level involvement politics Cavaliere del lavoro Noble Masonry Financial public support Family job relationship Apprenticeship Public or private company Relations with banks Successful brand/product Participation in other companies board of directors Merging with other companies Mainly commissioned by PA

35 The four dimensions 1/2 I.Entrepreneurial spirit (55%) Most of the variables which characterize the dimension are relative: to the capacity to develop entrepreneurial activities through new ideas activity in manufacturing the propensity to innovate, especially product innovation and the ability to open new sale markets. being scarcely connected to the banking system II. Entrepreneurial stability (28%) The active variables which mainly characterized the dimension are relative to social status: belonging to the upper class having job relationship with the members of the family inheritance of the firm, high level of formal education

36 The four dimensions 2/2 III. Innovation (10%) three active variables concerning innovation also the high educational level appears to be significant IV.Political and lobby commitment (4%) The active variables are related to lobbying activity one with politicians one through participation to various kinds of association

37 I dimension: Entrepreneurial Spirit (55%) Left quadrant Categories of active variablesContributionSquared cosin Owner and manager2.20.39 Family job relationships2.70.27 Manufacture2.00.28 No relation with banks2.30.29 Innovator2.10.36 Product innovation3.50.19 New sale markets5.10.38 Right quadrant Categories of active variablesContributionSquared cosin Manager14.60.62 No family job relationships4.50.29 Financial activities11.90.46 State-owned enterprise9.00.34 Relation with banks5.20.30 No innovator6.50.33 No product innovation2.00.28 No process innovation1.60.19 No new sale markets5.20.44  most of the variables which characterize the dimension are relative:  to the capacity/incapacity to develop entrepreneurial activities through new ideas  activity in manufacturing  the propensity to innovate, especially product innovation and the ability to open new sale markets.  having job relationship with the own family,  being scarcely connected to the banking system

38 II dimension: Entrepreneurial stability (28%) Left quadrant Categories of active variables ContributionSquared cosin High class6.80.29 Father self-employed5.50.39 Family job relationships3.50.28 High education level0.90.04 First job self-employment5.40.30 Inheriting9.60.44 Right quadrant Categories of active variables ContributionSquared cosin Low class7.80.24 Father low educated7.20.22 Father employee6.10.23 No family job relationships5.10.27 Low education level8.10.27 First job employee5.10.34 Founding3.60.20  the active variables which characterized the dimension are relative to social status. Among the active variables (in the left quadrant) we have: belonging to the upper class, having job relationship with the members of the family, inheritance of the firm, being an independent worker since the first job high level of formal education  Among the active variables (in the right quadrant) we have belonging to the lower classes low education level, not having family job relationship low level of education of the father

39 III dimension: Innovation (10%) Left quadrant Categories of active variablesContributionSquared cosin High education level5.00.16 Innovator3.20.33 Product innovation8.60.27 Process innovation4.30.15 Right quadrant Categories of active variablesContributionSquared cosin Owner10.20.25 No innovator8.10.24 No product innovation3.80.32 No process innovation2.40.16 No new sale markets2.40.12 No new market production1.10.19 There are three active variables in the left quadrant concerning innovation. The active variables in the right quadrant are the negative counterparts of most of the innovation variables. Also the high educational level appears to be significant

40 IV dimension: Political and Lobby Commitment (4%) Left quadrant Categories of active variablesContributionSquared cosin Indirect involvement in politics11.80.29 Employers association11.90.33 Right quadrant Categories of active variablesContributionSquared cosin No indirect involvement in politics6.20.43 No employers association8.20.44 Medium class6.40.25 The only two active variables in the left quadrant are related to lobbying activity: the first one with politicians, the second through participation to various kinds of association. At the same time we have symmetrical active variables in the right quadrant

41 The five clusters Schumpeterian entrepreneurs (29%) –prevailing peculiar modalities roughly refer to the characteristics attributed by Schumpeter to his innovative entrepreneur First generation entrepreneurs (7.7%) –wants to symbolize at best the features of the founders of new enterprises in a backward local environment Well Established entrepreneurs (24.4%) –here converges the elite of the entrepreneurs Defensive entrepreneurs (21%) –prevailing modalities are almost the opposite of the ones characterizing the first cluster. They do not innovate or innovate very little Entrepreneurial Managers (16.7%) –they were mainly talented administrators

42 Dendogram – Five main clusters from the classification of profiles DEFENSIVE 21.0% MANAGERS 16.7% WELL- ESTABLISHED 24.4% FIRST GENERATION 7.7% SCHUMPETERIAN 29.0%

43 CLUSTER 1 ‘Schumpeterian Entrepreneurs’ (29%) ModalitiesTest value % of the cluster within the modality (CLA/MOD) % of the modality within the cluster (MOD/CLA) % of the modality within the sample (GLOBAL) Product innovation9.8363.6468.1431.03 Innovator7.6138.9396.4671.79 No politic involv.6.7838.6092.9269.74 New sale markets6.1044.2070.8046.41 Founding5.9544.5168.1444.36 No relation banks5.8238.4386.7365.38 Manufacture5.7237.9387.6166.92 Medium innovation5.3945.2759.2937.95 Owner &manager5.1936.0490.2772.56 First job employee4.5539.0270.8052.56 Medium class4.5139.1169.9151.79 Process innovation4.4442.9653.9836.41 Purchasing4.4073.9115.045.90 Private enterprise4.2631.56100.0091.79 Machinery3.8249.2830.0917.69 Other Manufacture3.6762.0715.937.44 No employers assoc3.5335.2276.9963.33 No dir political inv3.0933.5782.3071.03 High innovation2.9952.7816.819.23 Medium education2.4737.4043.3633.59 Father employee2.3540.5128.3220.26

44 CLUSTER 2 ‘First Generation Entrepreneurs’ (7.7%) ModalitiesTest value % of the cluster within the modality (CLA/MOD) % of the modality within the cluster (MOD/CLA) % of the modality within the sample (GLOBAL) Low education8.9348.9880.0012.56 Father low educated8.8873.0863.336.67 Low class8.0062.0760.007.44 Owner6.8639.5863.3312.31 Founding6.2116.7696.6744.36 First job employee3.4512.2083.3352.56 Construction3.1435.2920.004.36 No relation banks2.9610.5990.0065.38 Father employee2.8316.4643.3320.26 No Cavaliere lavoro2.439.6293.3374.62

45 CLUSTER 3 ‘Well Established Entrepreneurs’ (24.4%) ModalitiesTest value % of the cluster within the modality (CLA/MOD) % of the modality within the cluster (MOD/CLA) % of the modality within the sample (GLOBAL) Employers associate7.4246.1569.4736.67 Inheritance6.9346.2164.2133.85 Family job relation6.7636.6186.3257.44 Innovator6.5532.5095.7971.79 New sale markets6.3239.2374.7446.41 High class6.2647.2754.7428.21 New market product6.1853.9543.1619.49 Father self-employed5.3935.4476.8452.82 Owner &manager5.3431.1092.6372.56 political invol.5.1942.3752.6330.26 First job self-empl.4.5435.8864.2143.59 Medium innovation4.4437.1657.8937.95 Private enterprise3.7626.54100.0091.79 Cavaliere lavoro3.5338.3840.0025.38 Process innovation3.3734.5151.5836.41 Manufacture3.3429.5081.0566.92 Integration &divers3.0443.1423.1613.08 Experience abroad2.6931.8552.6340.26 Integration2.6536.7130.5320.26 Father med educated2.5656.259.474.10 Father high educated2.3344.8313.687.44 Start working 21-252.3334.0433.6824.10 Food2.3340.0018.9511.54

46 CLUSTER 4 ‘Defensive Entrepreneurs’ (21%) ModalitiesTest value % of the cluster within the modality (CLA/MOD) % of the modality within the cluster (MOD/CLA) % of the modality within the sample (GLOBAL) No innovation10.4460.3873.5627.18 No innovator10.4059.0974.7128.21 No new sale markets8.2937.8090.8053.59 No product innovation7.3931.6097.7068.97 No process innovation6.6432.2691.9563.59 Inheriting6.5542.4264.3733.85 First job self-empl6.0537.0672.4143.59 Family job relation5.2431.7081.6157.44 Father self-employed5.1232.5277.0152.82 No new market prod4.3026.5295.4080.26 Commercial services3.5853.5717.247.18 Farming/extraction3.5853.5717.247.18 Agriculture2.5950.0011.495.13 Diversification2.5832.9734.4823.33 Commercial services2.3639.4717.249.74 Owner &manager2.3425.4482.7672.56 Born North -2.9816.7443.6858.21

47 CLUSTER 5 ‘Entrepreneurial Managers’ (16.7%) ModalitiesTest value % of the cluster within the modality (CLA/MOD) % of the modality within the cluster (MOD/CLA) % of the modality within the sample (GLOBAL) Manager14.2789.8381.5415.13 No family relation10.2037.9596.9242.56 Financial activities8.1880.6538.467.95 State-owned entrepreneur7.8395.0029.235.13 Relation with banks7.2736.3075.3834.62 No new sale markets6.2327.2787.6953.59 High education5.8233.6064.6232.05 Priv/pub enterprise4.9183.3315.383.08 Energy4.8890.0013.852.56 First job employee4.5624.8878.4652.56 No product innov.4.3521.9390.7768.97 No innovation4.3431.1350.7727.18 Other strategies3.9725.6066.1543.08 Start working > 453.8752.1718.465.90 No innovator3.8329.0949.2328.21 Father employee3.6331.6538.4620.26 Dir political invol3.1026.5546.1528.97 No new market prod3.1019.4993.8580.26 University teacher3.1053.3312.313.85 Jewish2.4055.567.692.31 No process innov.2.3620.1676.9263.59

48 Conclusions The first aim of the project was to describe the main features of Italian entrepreneurship in order to evaluate which have been the crucial socio-economic determinants that can explain its historical evolution A few basic typologies of Italian entrepreneurship over the long run have been identified:  Schumpeterian  First generation  Well-established  Defensive  Entrepreneurial-managers These only partly match either with the picture so far proposed by the historiography on Italy or with the general typologies suggested by the literature A part from the new taxonomy we have reached some other not negligible results  the Northern prominence of “modern” entrepreneurs as indirectly confirmed by the minor value of the modality born-North with respect to the average in cluster 4  the strong relations both with the own family and the partner’s one  the almost total absence of female entrepreneurs  the good level of formal education (70% have a medium/high degree): this for sure is one of the most surprising result

49 Next steps Searching for the determinants of entrepreneurial success ◊ Main Hypothesis (H1 ◊ Main Hypothesis (H1 ) Entrepreneurial success depends on talent, human capital and social capital ◊ Two levels of analysis ◊ Two levels of analysis : – H1a. Relations among proxies variables  linear or non-linear functions?  Several proxies to identify success – H1b. Searching for latent dimensions of success.  Is success a continuous or a discrete variable?  PLS – Path Modeling

50 The structural model RQ: EntS=f(HC,RC,TA) HC,RC,TA = latent variables HC RC SI TA PROXIESPROXIES ….. PROXIESPROXIES

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