PIER ANGELO MARIA TONINELLIPIER ANGELO MARIA TONINELLI

Growth and entrepreneurship in Italy: a Growth and entrepreneurship in Italy: a regional approachregional approach

El empresariado español en el contexto regional

Alcalà, 5-9 July 2010

The outline1. The growth of the Italian economy

2. The regional development1. 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

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)

1891 1911 1938 19195151 19711971 1981 1991 2001

Piedmont

1.08 1.15 1.39

1.47 1.21 1.14 1.15 1.15

Aosta Valley 1.58 1.35 1.30 1.18 1.24

Liguria 1.44 1.54 1.68 1.62 1.16 1.11 1.15 1.09

Lombardy 1.15 1.19 1.39 1.53 1.34 1.28 1.30 1.30

North-West 1.16 1.22 1.43 1.52 1.28 1.22 1.24 1.24

Trentino-Alto A. - - 0.95 1.06 1.01 1.12 1.10 1.29

Veneto 0.80 0.86 0.84 0.98 0.99 1.08 1.12 1.13

Friuli - - 1.19 1.11 1.00 1.09 1.14 1.12

Emilia 1.06 1.08 1.04 1.12 1.14 1.29 1.21 1.23

Tuscany 1.03 0.97 1.01 1.05 1.05 1.11 1.05 1.09

The Marches 0.88 0.81 0.79 0.86 0.91 1.05 0.99 0.99

Umbria 1.02 0.92 0.96 0.90 0.93 0.98 0.97 0.96

Latium 1.57 1.49 1.19 1.08 1.07 1.05 1.13 1.13

Center/north-east 1.01 1.00 0.99 1.04 1.04 1.11 1.11 1.13

Abruzzi 0.66 0.68 0.58 0.58 0.80 0.84 0.89 0.84

Campania 0.97 0.94 0.82 0.69 0.71 0.67 0.68 0.65

Apulia 1.02 0.85 0.72 0.65 0.75 0.72 0.73 0.67

Lucania 0.74 0.73 0.57 0.47 0.75 0.68 0.66 0.73

Calabria 0.67 0.70 0.49 0.47 0.67 0.65 0.59 0.64

Sicily 0.93 0.85 0.72 0.58 0.70 0.71 0.68 0.66

Sardinia 0.94 0.92 0.83 0.63 0.85 0.72 0.74 0.76

South and islands 0.88 0.84 0.70 0.61 0.73 0.70 0.70 0.68

Italy (2001 euros) 1,313 2,064 2,596 2,940 10,027 13,199 16,470 19,928

Yearly growth rate (%) - 2.29 0.85 0.96 6.33 2.79 2.24 1.92

Regional disparities in Italy: per capita value added, Italy =1 Regional disparities in Italy: per capita value added, Italy =1 ((Source:Source: Felice 2010Felice 2010))

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• By 1891 the north-south divide 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.

• 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

• probably referable to the role of conditioning variables, such as low low levels of social capital or institutional failurelevels 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)

Workforce in agriculture (%) Workforce in industry (%)

1911 1951 1971 2001 1911 1951 1971 2001

Piedmont

55.4

34.8 13.8 3.7

27.4

39.139.1 50.450.4 38.2

Aosta Valley 55.0 22.6 5.7 27.2 34.5 22.9

Liguria 35.1 25.8 10.8 3.5 32.3 29.9 32.4 23.1

Lombardy 43.3 23.2 6.4 1.9 37.6 46.346.3 54.754.7 39.9

North-WestNorth-West 47.047.0 27.627.6 9.29.2 2.62.6 33.033.0 41.941.9 50.850.8 37.8

Trentino-Alt. A. (66.5) 49.3 19.7 8.3 (15.5) 21.6 29.1 26.7

Veneto 61.1 48.6 17.1 4.2 21.5 25.5 42.642.6 40.740.7

Friuli (51.9) 39.0 14.5 3.2 (25.2) 28.7 37.7 32.5

Emilia 58.3 47.7 18.7 5.6 24.2 24.1 39.0 35.9

Tuscany 50.9 41.0 13.0 3.9 30.8 30.8 43.0 34.1

The Marches 67.4 55.9 26.8 4.0 19.2 21.9 35.2 40.8

Umbria 69.5 55.6 23.4 4.7 17.5 21.6 36.1 32.8

Latium 44.9 32.8 10.0 3.6 23.0 20.5 26.3 19.7

Central/north-eastCentral/north-east 57.557.5 44.544.5 16.016.0 4.54.5 23.923.9 24.924.9 36.836.8 32.832.8

Abruzzi 77.2 69.3 36.4 6.8 13.0 13.1 26.0 32.6

Campania 53.4 46.6 25.7 6.9 23.3 20.9 29.6 24.4

Apulia 63.0 64.7 39.9 11.7 20.1 13.4 24.1 26.1

Lucania 76.7 75.2 43.7 10.8 12.8 11.0 23.8 34.6

Calabria 67.3 66.4 38.8 12.0 20.6 15.3 25.6 19.4

Sicily 52.7 56.4 30.3 9.6 22.8 16.9 26.1 19.9

Sardinia 59.0 56.5 27.0 8.5 20.9 17.5 26.9 23.0

South and islandsSouth and islands 60.560.5 59.259.2 32.832.8 9.29.2 20.620.6 16.316.3 26.526.5 24.324.3

ITALY (%)ITALY (%) 55.455.4 44.644.6 18.918.9 5.25.2 25.525.5 26.826.8 38.138.1 32.032.0

• Data on sectoral employment confirm that the industrial triangle was already apparent in 1911.

• LombardyLombardy was the most industrialized region and it would keep this primacy through most of the 20th century, while LiguriaLiguria 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

• In Lombardy and Piedmont 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)

Product per worker (Italy=1) Activity rates (Italy=1)

1911 1951 1971 2001 1911 1951 1971 2001

Piedmont

0.99

1.23 1.01 1.02

1.17

1.19 1.20 1.13

Aosta Valley 1.18 1.10 1.02 1.42 1.23 1.22

Liguria 1.50 1.66 1.07 1.11 1.03 0.98 1.09 0.99

Lombardy 1.13 1.37 1.06 1.10 1.06 1.12 1.27 1.18

North-West 1.11 1.35 1.04 1.08 1.10 1.12 1.23 1.15

Trentino-Alt. A. - 1.00 0.97 1.08 - 1.06 1.04 1.20

Veneto 0.87 0.96 1.01 0.96 0.99 1.02 0.98 1.17

Friuli - 1.06 0.92 0.98 - 1.05 1.08 1.14

Emilia 1.05 1.08 1.09 1.03 1.03 1.03 1.05 1.19

Tuscany 0.96 1.00 1.00 1.00 1.01 1.05 1.05 1.09

The Marches 0.78 0.80 0.90 0.88 1.05 1.08 1.01 1.12

Umbria 0.91 0.88 0.88 0.94 1.01 1.02 1.06 1.03

Latium 1.54 1.09 1.02 1.14 0.96 0.99 1.05 0.99

Central/north-east 0.99 1.01 1.01 1.02 1.01 1.03 1.03 1.11

Abruzzi 0.66 0.59 0.90 0.87 1.02 0.98 0.88 0.97

Campania 0.97 0.83 0.93 0.91 0.98 0.84 0.76 0.71

Apulia 0.94 0.71 0.92 0.83 0.91 0.92 0.82 0.81

Lucania 0.69 0.42 0.87 0.82 1.06 1.12 0.86 0.89

Calabria 0.67 0.47 0.84 0.85 1.04 1.01 0.79 0.75

Sicily 1.05 0.74 0.99 0.92 0.81 0.79 0.71 0.72

Sardinia 1.11 0.70 1.12 0.86 0.82 0.89 0.76 0.88

South and isl. 0.91 0.69 0.94 0.88 0.92 0.890.89 0.770.77 0.77

Italy (%)*4,358 6,986

27,043

54,211 47.3 42.1 37.1 36.8

• 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

• another factor favoured the convergence of southern Italy, migrationmigration, 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)

1901 1911 1951 1971 1981 2001

1.429 1.4511.210 1.098 1.128 1.048

Val d’Aosta 1.668 1.763 1.514 1.493Liguria 1.331 1.189 1.040 1.022 1.091 1.050Lombardy 1.370 1.364 1.179 1.087 1.067 1.096North-West

1.388 1.373 1.174 1.087 1.091 1.088Trentino-Alto Ad. - - 3.979 3.626 3.134 2.057Veneto 1.110 1.113 1.055 1.128 1.257 1.255Emilia 1.293 1.231 1.206 1.093 1.297 1.272Tuscany 1.342 1.359 1.334 1.169 1.303 1.247The Marches 0.750 0.834 1.125 1.051 1.205 1.239Umbria 1.201 1.198 1.112 1.125 1.331 1.366Latium 1.041 0.919 0.812 0.867 0.796 0.804Center/north-ea. 1.167 1.152 1.231 1.181 1.260 1.193Abruzzi 0.614 0.629 0.661 0.726 0.887 1.131Campania 0.491 0.505 0.542 0.659 0.374 0.430Apulia 0.687 0.586 0.682 0.711 0.548 0.748Lucania 0.637 0.697 0.557 0.789 0.785 0.830Calabria 0.438 0.483 0.541 0.738 0.817 0.654Sicily 0.709 0.722 0.669 0.806 0.733 0.823Sardinia 0.430 0.510 0.799 0.914 1.045 1.095South and islands 0.592 0.596 0.630 0.743 0.646 0.641

Pearson correlation with income disparitiesCorrelationCorrelation 0.5590.559 0.5460.546 0.7980.798 0.7550.755 0.7560.756 0.7040.704

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)

• 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)

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

The regional distribution of State-owned enterprises (2)

• Caveat: SOEs regional distribution data involve some unavoidable bias, that is an abnormal concentration in the Lazio 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.

• Such disproportion does not concern so much the absolute numbers as the size of assets. 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.

NUMBER 1936 1952-54 1960 1972 1983 % 1936 1952-54 1960 1972 1983

VDA 1 1 VDA - - - 0,3 0,3

PIE 7 8 10 12 19 PIE 7,9 6,0 6,1 4,1 6,1

LIG 8 14 21 29 23 LIG 9,0 10,5 12,7 10,0 7,4

LOM 23 34 39 58 70 LOM 25,8 25,6 23,6 20,0 22,4

Nord Ovest 38 56 70 100 113

Nord Ovest 42,7 42,1 42,4 34,5 36,2

TAA 1 1 TAA - - - 0,3 0,3

VEN 5 2 4 8 14 VEN 5,6 1,5 2,4 2,8 4,5

FVG 7 5 5 10 11 FVG 7,9 3,8 3,0 3,4 3,5

EMR 4 1 4 3 8 EMR 4,5 0,8 2,4 1,0 2,6

Nord Est 16 8 13 22 34 Nord Est 18,0 6,0 7,9 7,6 10,9

MAR 2 2 MAR - - - 0,7 0,6

TOS 2 3 6 9 18 TOS 2,2 2,3 3,6 3,1 5,8

UMB 2 5 UMB - - - 0,7 1,6

LAZ 24 47 42 78 68 LAZ 27,0 35,335,3 25,5 26,9 21,8

Centro 26 50 48 91 93 Centro 29,2 37,6 29,1 31,4 29,8

CAM 7 13 25 34 33 CAM 7,9 9,8 15,2 11,7 10,6

ABR-MOL 1 3 ABR-MOL - - - 0,3 1,0

PUG 16 10 PUG - - - 5,5 3,2

BAS 6 3 BAS - - - 2,1 1,0

CAL 3 2 CAL - - - 1,0 0,6

SAR 1 1 7 8 SAR - 0,8 0,6 2,4 2,6

SIC 2 5 8 10 13 SIC 2,2 3,8 4,8 3,4 4,2

Sud 9 19 34 77 72 Sud 10,110,1 14,314,3 20,620,6 26,626,6 23,123,1

Total 89 133 165 290 312 Total 100,0 100,0 100,0 100,0 100,0

Regional distribution of SOEs (number and %) source: Toninelli-Vasta 2010

• 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.

• LombardyLombardy 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)

1936 1952/4 1960 1972 1983

VDA - - - 0,0 0,0

PIE 5,8 5,6 5,0 3,9 7,7

LIG 23,0 20,0 18,0 17,9 20,9

LOMLOM 27,327,3 22,822,8 25,625,6 25,325,3 24,724,7

North-West 56,1 48,4 48,6 47,2 53,2

TAA - - - - 0,0

VEN 0,5 1,3 1,5 0,3 0,7

FVG 0,1 4,5 2,6 1,6 1,3

EMR 0,6 0,6 0,8 0,0 0,2

North-East 1,2 6,4 4,8 2,0 2,2

MAR - - - 0,0 0,0

TOS 0,2 0,2 1,8 0,7 1,7

UMB - - - 0,1 0,1

LAZLAZ 41,641,6 41,041,0 40,540,5 45,145,1 37,837,8

Central 41,8 41,2 42,2 45,9 39,6

CAM 0,7 3,9 4,2 2,2 3,1

ABR-MOL - - - 0,1 0,1

PUG - - - 0,3 0,2

BAS - - - 0,0 0,0

CAL - - - 0,0 0,0

SAR - 0,0 0,0 0,3 0,3

SIC 0,2 0,0 0,1 1,9 1,3

South 0,9 4,0 4,3 4,9 5,0

Total 100,0 100,0 100,0 100,0 100,0

Regional Regional distribution distribution of SOEs of SOEs (assets %)(assets %)

• 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 ENI and IRI 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 The regional distribution of State-owned enterprises (4)enterprises (4)

The regional distribution of the main The regional distribution of the main districtsdistricts

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

turnoverturnover

• 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 entrepreneurship (1):the historical determinantsthe historical determinants

The entrepreneurship (2):The entrepreneurship (2):research questions for the Italian caseresearch 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?

The entrepreneurship (3):The entrepreneurship (3):some theorethical suggestionssome 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)

• 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):The entrepreneurship (4):a taxonomya taxonomy

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.

Italian entrepreneurship (2): Italian entrepreneurship (2): The main features of the sample

  Frequency

%

Who isEntrepreneur/owner 67 11,0Entepreneur/manager 92 15,1Entrepreneur/owner & manager

449 73,9

 GenderMale 598 98,4Female 10 1,6Year of birth before 1830 63 10,4between 1831 and 1850 81 13,3between 1851 and 1870 128 21,1between 1871 and 1890 126 20,7between 1891 and 1910 150 24,7after 1910 60 9,9Involvement in politicsyes 188 30,9No 420 69,1Level of involvement in politics local level 102 54,3national level 55 29,3international level 5 2,7Local &national level 26 13,8

  Frequency

%

Area of birthCenter 126 20.7abroad 38 5,7North-East 140 23,0North-West 211 34,7South 93 15,3Father main activity (459 cases)farmer 15 3,3labourer 23 5,0manager 18 3,9technician 8 1,7craftsman 51 11,1entrepreneur 215 46,8freelance 31 6,8employee 22 4,8merchant 76 16,6Social background Low classes 78 12.8middle 342 56.3High 188 30,9

Italian entrepreneurship (3): Italian entrepreneurship (3): education and training

Frequency

%

 Education levelilliterate 1 0,2primary education 93 15,3middle school 113 18,6high school 210 34,5laurea degree 185 30,4post-laurea degree 6 1,0 Field of laurealaws 45 241,economics 23 12,3other Arts 10 5,4engineering 73 39,0chemistry/Pharmacology

15 8,0

other Sciences 21 11,2

  Frequency

%

Education abroadyes 91 15.0no 517 85,0 Experience abroadyes 216 35,5no 392 64,5 Experiences abroad (area, 216 cases)developed countries 185 85,7developing countries 31 14,4

Italian entrepreneurship (4) Italian entrepreneurship (4) The sample: “innovative features”

 Level of innovation Frequency

%

no innovation 122 20,1low innovation level 150 24,7medium innovation level

266 43,843,8

high innovation level 70 11,511,5

Level of innovation Freq %

0 122 20,1

1 150 24,7

2 130 21,4

3 136 22,4

4 48 7,9

5 17 2,8

6 5 0,8

Italian Italian entrepreneurshientrepreneurshi

p p (5) (5) Indicators of Indicators of entrepreneurientrepreneuri

al successal success

Skill for innovation Freq %

zero 340 55,9

low 112 18,4

medium 103 16,9

high 53 8,7

Growth in size Freq %

no growth 33 5,4

local level growth 132 21,7

national level growth 294 48,4

international level growth 149 24,5

Survival after death Freq %

<30 years 163 26,8

30-50 years 36 5,9

>50 years 45 7,4

still existant 349 57,4

ceased 15 2,5

Successful brand/product Freq %

yes 254 41,8

no 354 58,2

The sample: the company 1The sample: the company 1

 Ways of acquisition Frequency %

founder 277 45,6

inheritance 205 33,7

purchasing 34 5,6

No owner 92 15,1

Relations with banks

yes 213 35,0

no 395 65,0

The sample: the The sample: the company 2company 2

Starting sector

Agriculture, hunting and sylviculture 31 5,1

Fhising and related activities 1 0,16

Extraction 8 1,32

Manufacture 392 64,47

Energy-using products, Gas Appliances 14 2,3

Construction 24 3,95

Trade, servicing for cars, goods 62 10,2

Hotels and restaurants 1 0,16

Transport, storage and communications 16 2,63

Financial services 49 8,06

Property, renting, IT, services 2 0,33

Other public, social and personal services

8 1,32

The variables used for the MCA - I(first exercise, 390 entrepreneurs)

ACTIVE VARIABLES (18) ILLUSTRATIVE VARIABLESEntrepreneurial typology Place of birth (area)Social class AgeEducational level ReligionFather’s educational level Direct involvement in politicsFather’s main activity Honour of Cavaliere del lavoroFamily job relationships University teachingTypology of the first activity NobleIndirect involvement in

politicsMember of aristocracy

Affiliation to employers’ associations

Affiliation to Masonry

Form of enterprise Financial public supportWays of company acquisition Job relations with the partner’s

familySector of activity Experiences abroadRelations with banks Age of first entrepreneurial

activityInnovative entrepreneur Main sector of activity (not

aggregated)Product innovation Business strategies Process innovation Innovation levelNew sale markets New markets of production

The variables used for the MCA, II(608 entrepreneurs)

Active variables (11)

Entrepreneurial typology

Indirect political involvement

Employers association

Family job relationship

GrowthGrowth

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

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

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

I dimension: Entrepreneurial Spirit (55%)

Left quadrantCategories of active variables

Contribution Squared cosin

Owner and manager 2.2 0.39Family job relationships 2.7 0.27Manufacture 2.0 0.28No relation with banks 2.3 0.29Innovator 2.1 0.36Product innovation 3.5 0.19New sale markets 5.1 0.38

Right quadrantCategories of active variables

Contribution Squared cosin

Manager 14.6 0.62No family job relationships 4.5 0.29Financial activities 11.9 0.46State-owned enterprise 9.0 0.34Relation with banks 5.2 0.30No innovator 6.5 0.33No product innovation 2.0 0.28No process innovation 1.6 0.19No new sale markets 5.2 0.44

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

II dimension: Entrepreneurial stability (28%)

Left quadrantCategories of active

variablesContribution

Squared cosin

High class 6.8 0.29Father self-employed 5.5 0.39Family job relationships 3.5 0.28High education level 0.9 0.04First job self-employment 5.4 0.30Inheriting 9.6 0.44

Right quadrantCategories of active variables

ContributionSquared

cosinLow class 7.8 0.24Father low educated 7.2 0.22Father employee 6.1 0.23No family job relationships 5.1 0.27Low education level 8.1 0.27First job employee 5.1 0.34Founding 3.6 0.20

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

III dimension: Innovation (10%)

Left quadrantCategories of active variables

Contribution

Squared cosin

High education level 5.0 0.16Innovator 3.2 0.33Product innovation 8.6 0.27Process innovation 4.3 0.15

Right quadrantCategories of active variables

Contribution

Squared cosin

Owner 10.2 0.25No innovator 8.1 0.24No product innovation 3.8 0.32No process innovation 2.4 0.16No new sale markets 2.4 0.12No new market production

1.1 0.19

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

IV dimension: Political and Lobby Commitment (4%)

Left quadrant

Categories of active variables Contribution Squared cosin

Indirect involvement in politics 11.8 0.29

Employers association 11.9 0.33

Right quadrant

Categories of active variables Contribution Squared cosin

No indirect involvement in politics

6.2 0.43

No employers association 8.2 0.44

Medium class 6.4 0.25

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

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

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%

CLUSTER 1 ‘Schumpeterian Entrepreneurs’ (29%)

Modalities Test 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 innovation 9.83 63.64 68.14 31.03Innovator 7.61 38.93 96.46 71.79No politic involv. 6.78 38.60 92.92 69.74New sale markets 6.10 44.20 70.80 46.41Founding 5.95 44.51 68.14 44.36No relation banks 5.82 38.43 86.73 65.38Manufacture 5.72 37.93 87.61 66.92Medium innovation 5.39 45.27 59.29 37.95Owner &manager 5.19 36.04 90.27 72.56First job employee 4.55 39.02 70.80 52.56Medium class 4.51 39.11 69.91 51.79Process innovation 4.44 42.96 53.98 36.41Purchasing 4.40 73.91 15.04 5.90Private enterprise 4.26 31.56 100.00 91.79Machinery 3.82 49.28 30.09 17.69Other Manufacture 3.67 62.07 15.93 7.44No employers assoc 3.53 35.22 76.99 63.33No dir political inv 3.09 33.57 82.30 71.03High innovation 2.99 52.78 16.81 9.23Medium education 2.47 37.40 43.36 33.59Father employee 2.35 40.51 28.32 20.26

CLUSTER 2 ‘First Generation Entrepreneurs’ (7.7%)

Modalities Test 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 education 8.93 48.98 80.00 12.56Father low educated 8.88 73.08 63.33 6.67Low class 8.00 62.07 60.00 7.44Owner 6.86 39.58 63.33 12.31Founding 6.21 16.76 96.67 44.36First job employee 3.45 12.20 83.33 52.56Construction 3.14 35.29 20.00 4.36No relation banks 2.96 10.59 90.00 65.38Father employee 2.83 16.46 43.33 20.26No Cavaliere lavoro 2.43 9.62 93.33 74.62

CLUSTER 3 ‘Well Established Entrepreneurs’ (24.4%)

Modalities Test 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 associate 7.42 46.15 69.47 36.67Inheritance 6.93 46.21 64.21 33.85Family job relation 6.76 36.61 86.32 57.44Innovator 6.55 32.50 95.79 71.79New sale markets 6.32 39.23 74.74 46.41High class 6.26 47.27 54.74 28.21New market product 6.18 53.95 43.16 19.49Father self-employed 5.39 35.44 76.84 52.82Owner &manager 5.34 31.10 92.63 72.56political invol. 5.19 42.37 52.63 30.26First job self-empl. 4.54 35.88 64.21 43.59Medium innovation 4.44 37.16 57.89 37.95Private enterprise 3.76 26.54 100.00 91.79Cavaliere lavoro 3.53 38.38 40.00 25.38Process innovation 3.37 34.51 51.58 36.41Manufacture 3.34 29.50 81.05 66.92Integration &divers 3.04 43.14 23.16 13.08Experience abroad 2.69 31.85 52.63 40.26Integration 2.65 36.71 30.53 20.26Father med educated 2.56 56.25 9.47 4.10Father high educated 2.33 44.83 13.68 7.44Start working 21-25 2.33 34.04 33.68 24.10Food 2.33 40.00 18.95 11.54

CLUSTER 4 ‘Defensive Entrepreneurs’ (21%)

Modalities Test 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 innovation 10.44 60.38 73.56 27.18No innovator 10.40 59.09 74.71 28.21No new sale markets 8.29 37.80 90.80 53.59No product innovation 7.39 31.60 97.70 68.97No process innovation 6.64 32.26 91.95 63.59Inheriting 6.55 42.42 64.37 33.85First job self-empl 6.05 37.06 72.41 43.59Family job relation 5.24 31.70 81.61 57.44Father self-employed 5.12 32.52 77.01 52.82No new market prod 4.30 26.52 95.40 80.26Commercial services 3.58 53.57 17.24 7.18Farming/extraction 3.58 53.57 17.24 7.18Agriculture 2.59 50.00 11.49 5.13Diversification 2.58 32.97 34.48 23.33Commercial services 2.36 39.47 17.24 9.74Owner &manager 2.34 25.44 82.76 72.56

Born NorthBorn North -2.98 16.74 43.68 58.21

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)Manager 14.27 89.83 81.54 15.13No family relation 10.20 37.95 96.92 42.56Financial activities 8.18 80.65 38.46 7.95State-owned entrepreneur

7.83 95.00 29.23 5.13

Relation with banks 7.27 36.30 75.38 34.62No new sale markets 6.23 27.27 87.69 53.59High education 5.82 33.60 64.62 32.05Priv/pub enterprise 4.91 83.33 15.38 3.08Energy 4.88 90.00 13.85 2.56First job employee 4.56 24.88 78.46 52.56No product innov. 4.35 21.93 90.77 68.97No innovation 4.34 31.13 50.77 27.18Other strategies 3.97 25.60 66.15 43.08Start working > 45 3.87 52.17 18.46 5.90No innovator 3.83 29.09 49.23 28.21Father employee 3.63 31.65 38.46 20.26Dir political invol 3.10 26.55 46.15 28.97No new market prod 3.10 19.49 93.85 80.26University teacher 3.10 53.33 12.31 3.85Jewish 2.40 55.56 7.69 2.31No process innov. 2.36 20.16 76.92 63.59

ConclusionsThe 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 4the strong relations both with the own family and the partner’s onethe 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

Next stepsNext steps

Searching for the determinants of entrepreneurial success

◊ ◊ Main Hypothesis (H1Main Hypothesis (H1) • Entrepreneurial success depends on talent, human

capital and social capital

◊ ◊ Two levels of analysisTwo 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

The structural model

RQ: EntS=f(HC,RC,TA)

HC,RC,TA = latent variables

HC

RC

SI

TA

PROXIES

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PROXIES

…..

…..

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