Obligation, Risk, and Opportunity in

the Renaissance Economy

 

 

by

 

 

 

John F. Padgett                                                                                  Paul D. McLean

     Department of Political Science                                                                             Department of Sociology

     University of Chicago                                                                                                Rutgers University

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paper presented at the conference, “The U.S. Economy in Context,” Princeton University, February 22-23, 2002.   Sponsored by the Russell Sage Foundation, Princeton University’s Department of Sociology, and Princeton’s Center for Migration and Development.

 

 

This paper is a draft.  Please do not cite or quote without the authors’ permission.


Obligation, Risk, and Opportunity in

the Renaissance Economy

 

Introduction

            The New Economic Sociology has performed salutary work in uncovering the social integuments underlying interactions and decision-making in contemporary markets.  In so doing, it shatters the one-sided image of homo oeconomicus and the economistic fallacy that the economic sphere has a life of its own and imperatives that determinately shape all action, and has, in key instances, shown the interweaving of economic and social logics (for example, Uzzi 1996).

            While this critique on contemporary economic life has proceeded, it has remained more or less taken for granted by sociologists at the same time that the social embeddedness of the market in past times was more substantial and far-reaching than it is today.  Notwithstanding the discovery of the ‘traditional’ in the ‘modern,’ it has been harder to acknowledge the ‘modern’ in the ‘traditional,’ or more precisely, to document empirically the way different specific forms of sociation we commonly associate with each of these meta-categories, intersect to produce markets of particular sorts, with particular impetuses for development.  Only in economic history has the empirical investigation of the structure of earlier markets been undertaken, and only there has the link between economic strategy and social obligation been considered in its intricacy.

            In much the same way that the literature on early modern European state-building has drifted away from unilinear, quasi-teleological narratives of the emergence of the rationalized, bureaucratized, disciplined state towards acknowledging both the variety of outcomes (Ertman 1997), and the intersection of both ‘modernizing’ and ‘traditionalizing’ tendencies in the same institutions (Molho 1996, Connell and Zorzi 2000) , economic sociology should move towards a consideration of the plethora of possible markets and the intersection of different logics in the same markets for a richer understanding of economic life.  To develop a more nuanced picture of early European commerce and industry is to take seriously both of the goals of economic practice articulated in the famous epigraph that graced the first page of so many Renaissance Florentine merchants’ account books: “To the Glory of God and profit.”  Florentine merchants avidly pursued profit and assiduously shunned loss, but at the same time carefully pursued honor and assiduously avoiding shame (Weissman 1982).  Considerable classic economic historical research has been conducted to unearth how the Italians pioneered vital devices of commercial activity such as double-entry bookkeeping, bills-of-exchange, limited liability partnerships, and holding companies (for example, Sapori 1926, 1932, 1970; de Roover 1944, 1966; Lopez 1976).  Less has been done to figure out the implications for market structure of the intersection of the profit motive with the honor motive so neatly articulated by Weissman.  How did Florentines construct and innovatively adapt markets to pursue economic gain while simultaneously fulfilling social obligations and using shared dimensions of identity to create trust between trading partners, or between lenders and borrowers?  This paper constitutes an effort in the direction of depicting that market structure and strategy in particular at the level of choosing the recipients of credit.

This amounts to thinking about economic behavior in terms of the simultaneously operating constraints of social obligation, risk, and opportunity.  Social obligation was manifested to some extent in the choice of career (as families typically participated in the same industry transgenerationally), but was palpably felt and, we shall see, behaviorally prominent in the choice of partners in business and the choice of trading alters.  Risk was present, not only in the daring Mediterranean commercial ventures ably celebrated by the Florentines themselves and commemorated by nineteenth and twentieth century historians, but also in the way that Florentines’ economic well-being was threatened by means of the demands put upon them by others to whom they were connected, by the extent of their indebtedness relative to their capital, and the vulnerability of the entire interconnected system to the failure of component parts of it.  Opportunity is the ‘profit’ component of the picture.  Florentines, and in particular Florentine bankers, found ways to capitalize on the variety of kinds of social ties linking them to pursue new economic opportunities which, on the face of it, more ‘traditionalist’ actors might have let slip by.  Florentines’ social identities were multiple, and opportunities for achieving new revenues, particularly in the emerging silk industry, appear to have been forged cleverly, through subtle management of these diverse identities.

 

The Character of Economic Life in Renaissance Florence

 

            Notwithstanding the typical appreciation of Renaissance Italy as the birthplace of  modern capitalism, Renaissance historians have correctly pointed out that, in terms of motivation and organization, the Florentine economy lacked certain features integral to contemporary capitalism.  Notwithstanding its decentralization into a multitude of privately owned and operated small firms, hardly any mention is made in contemporary documents of competition as a key element of the market (Goldthwaite 1987).  Whatever allusions are made to competition and the accumulation of wealth, such as by the character of Lionardo Alberti in Leon Battista Alberti’s I Libri della famiglia, are typically counterbalanced by voices articulating the crucial role of a commercial career in the conduct of an honorable life and the importance of being well liked rather than rich

(Alberti 1969).  Alberti’s well-known praise of “ink-stained hands” derives from the esteem held for merchant activity, but specifically from the virtues of diligence, sobriety, and rectitude which careful bookkeeping reputedly symbolized. 

Whereas firms operated more continuously in business than did the short-term joint ventures (commenda) of the medieval period, they still operated for fixed periods, usually two or three years, at which point the books were closed and balanced and shares of profit or loss distributed to the partners and any outside investors.  Sometimes the same partnerships recreated themselves; just as often new combinations of partners would arise.  Although individuals typically worked in the same industry for entire careers, it was not uncommon for them to disappear from active partnership periodically.  Moreover, the participatory nature of the Florentine state required all citizens, regardless of their commercial activities, to serve periodically in administrative offices outside the city or in legislative offices within the city (the occupants of which were sequestered in the Signoria for the duration of their term) that could not help but affect those citizens’ ability to participate in or oversee their commercial activities fully.  Yet political participation was, if anything, a more vital component of a life well-led than was commercial enterprise. 

As to the profit motive, Goro Dati, a silk merchant in our data, famously eschewed profit-making on holy days, while Giovanni di Pagolo Morelli counseled against placing untested trust in friends and business associates, concluding that tested friendship, not impersonal market mechanisms, formed the proper basis for interpersonal trust (see Branca 1986).  Clearly the record shows that considerations of honor and interpersonal obligation were integral to the Florentine commercial psyche, even as business was conducted with extreme diligence and a sharp eye on the bottom line.  The first question lies in figuring out how such obligation played itself out, especially at an aggregate level, in crafting a portfolio of transactions or relationships with other firms.

 

The Data

 

            The details of the collection of the data used in this paper are provided elsewhere (see McLean and Padgett 1997), although we have gathered some additional data since then.   For present purposes, a much shorter account can be offered.  The data for this project are drawn from the Florentine Catasto of 1427, a remarkable document in the history of public fiscal administration (see Herlihy and Klapisch-Zuber 1985).  All Florentine households, as well as those in the surrounding contado, were required to submit a statement in a standardized format to city officials of their total assets in land, holdings in the public debt, investments in and revenues from commercial enterprise, and interpersonal loans, so that officials could assess more reliably how to distribute the tax burden in the city.  As part of this massive data collection project, officials required owners of firms to submit a copy of the balance sheets from their firms, offering summary information on the outstanding flows of business between all firms in the market, Florentine and foreign as of a particular, fixed point in time: July 12, 1427.  These bilanci survive in the portate version of the tax records in the Archivio di Stato di Firenze in Florence.    We focused chiefly on gathering transactional (credit/debt) information on all firms in the most prestigious industries in the economy, namely banking (including international merchant-banking, import/export firms, and domestic banking engaged in both commercial credit and personal lending operations), silk manufacture, wool manufacture, and cloth retailing.   We coded the presence/absence and value of ties for all dyadic pairs of firms within and between these industries.   The estimated percentage of total credit coded at present, and the distribution of firms across industries canvassed, are reported in Tables 1 and 2 respectively.  Also purely for descriptive purposes, we offer Table 3 here, a summary of the volume and total value of ties flowing between different industries in the Florentine economy.

Based on our collection of the ‘credits’ data through the reading of the bilanci, we were able furthermore to develop a census of firms in these industries, to characterize firms in terms of their industry, geographic location (Florence chiefly, but also in a variety of other Italian cities such as Pisa, Venice, Rome, and Ancona, and a variety of other European mercantile centers such as London, Bruges, Barcelona, Avignon, and Montpelier), size of their capital investment (corpo),  and the number of ties and aggregate value of the ties which they maintained.  Naturally we also identified the partners active in each firm.  It was rare in the early 1400s for firms to have more than three partners (by which is typically meant individuals with a stake in the start-up capital of the firm), and consequently it is not implausible, nor is it particularly arduous, to characterize firms in terms of the attributes of their partners—here meaning wealth, patrilineage, social status, kinship relations, neighborhood of residence, and so on. 

            More specifically, for each partner we coded the following information: 1) the name of his family (that is, his patrilineage); 2) his family’s social status, based on when any member of that family first entered the Florentine priorate (here discrete status classifications are based on discrete waves of new entry into the priorate: see Padgett

Table 1: Ties of High Certainty, Active Firms in Key Industries to all Persons and Companies

 

 

             in the Economy:

Estimated Percent Coverage of the Market

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Seen Bilanci

 

 

Unseen Bilanci

 

Overall

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Estimated

 

 

 

 

%

%

 

 

est. %

est.%

 

%

est. %

est. %

Total

 

Debts

 

N of

trans.

value

 

N of

trans.

value

 

bilanci

trans.

value

 

Market

 

Coded

 

firms

coded

coded

firms

coded

coded

 

seen

coded

coded

Size

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

International

1364

 

16

25.4

44.3

 

29

19.4

70.2

 

35.6

23.8

45.4

 

1418387

Merchant-Banks

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Florence/Pisa

1172

 

16

31

58

 

4

4.3

9.4

 

80

28.7

56.2

 

535761

Banks

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Domestic

4194

 

39

46.9

71.2

 

14

25

66.8

 

73.6

44.7

70.7

 

2150706

Banks

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

All Banks

6730

 

71

39.1

60.1

 

47

19.7

64

 

60.2

37.3

60.4

 

4104854

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Cloth Retail

2705

 

26

22.3

50.4

 

9

12

23.1

 

74.3

21.1

47.5

 

592033

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Silk

1765

 

37

33.4

81.2

 

9

20

 

 

80.4

33.4

81.2

 

281424

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Wool:

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

San Martino

1726

 

31

48.5

79.4

 

10

8.9

18.8

 

75.6

47.6

78.8

 

359732

Via Maggio

434

 

17

35.7

84.1

 

10

14.2

35.9

 

63

31.1

75.5

 

39058

San Pancrazio

200

 

6

44

59.7

 

2

 

 

 

75

44

59.7

 

23291

S Pier Sch.

108

 

4

32.9

98.1

 

5

17.6

31.9

 

44.4

25.4

66.2

 

8127

All Garbo

 

 

27

37.2

77.3

 

17

15.6

34.4

 

61.4

32.3

70

 

70476

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Unknown

795

 

21

42.3

64.3

 

18

29.7

98.3

 

53.8

39.8

67.2

 

173080

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Total Wool

3263

 

79

44.3

75.8

 

45

23.2

68.2

 

63.7

41.4

75

 

603288

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Tintori

619

 

10

27.4

47.5

 

8

32.9

51.6

 

55.6

28.7

50

 

67364

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Totals

 

 

223

34.9

64.2

 

118

20.3

44.3

 

65.4

33.4

62.3

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

note: for mb/intl, mb/Pisa, and dom bank with unseen bilanci, est. of total # and value of ties

 

 

is based on pooled values across all types of unseen bilanci banks

 

 

 

 

 

 

note: for all wool firms, est. of total value and # of ties is based on pooled values across all unseen

 

bilanci wool firms regardless of convento

 

 

 

 

 

 

 

 

 

 


 

 

 

A Census of 1427 Companies/Partnerships in Major Industries

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

High Certainty Companies

 

Low Certainty Companies

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Florence

Overseas

Old

 

Florence

Overseas

Old

 

 

 

 

 

 

 

 

 

 

 

 

 

International

0

 

45

 

7

 

0

 

10

 

2

 

Merchant-Banks

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Florence/Pisa

0

 

20

 

1

 

0

 

1

 

0

 

Banks

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Domestic

53

 

0

 

10

 

12

 

0

 

4

 

Banks

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Cloth Retail

32

 

3

 

5

 

4

 

1

 

2

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Silk

38

 

8

 

4

 

11

 

1

 

1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Wool

 

 

 

 

 

 

 

 

 

 

 

 

San Martino

36

 

5

 

10

 

2

 

0

 

0

 

Via Maggio

27

 

0

 

2

 

1

 

0

 

0

 

San Pancrazio

8

 

0

 

0

 

0

 

0

 

0

 

S Pier Scheraggio

9

 

0

 

1

 

0

 

0

 

0

 

Unclear Location

34

 

4

 

9

 

21

 

4

 

4

 

All Wool Firms

114

 

9

 

22

 

24

 

4

 

4

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Tintori

18

 

0

 

3

 

7

 

0

 

2

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Other Industries

 

 

 

 

 

 

 

 

 

 

 

 

  Fur

6

 

0

 

0

 

4

 

0

 

0

 

  Gold

3

 

0

 

0

 

5

 

0

 

0

 

  Linaioli

6

 

0

 

0

 

10

 

1

 

0

 

  Merciai

6

 

1

 

0

 

5

 

1

 

1

 

  Rigattieri

7

 

1

 

0

 

4

 

0

 

1

 

  Speziali

11

 

0

 

2

 

1

 

0

 

0

 

  Miscellaneous

6

 

1

 

5

 

6

 

0

 

1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Unknown

9

 

9

 

10

 

110

 

20

 

15

 

Industry

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Totals

312

 

94

 

69

 

203

 

39

 

33

 

 


Table 3: Input/Output Flows of Credits/Debts Among Firms in Key Florentine Industries

Table 3: Input/Output Flows of Credits/Debts Among Firms in Major Florentine Industries

 

 

     Debtor:

mb/intl

mb/Pisa

Banks

Ritagl.

Silk

Wool, SM

Wool, Oth.

Tintori

 

Row totals

 

 

 

 

 

 

 

 

 

 

 

Creditor:

119

96

157

22

40

51

15

1

 

501

mb/intl

69427

32851

150849

3992

11338

24620

4161

801

 

298842

 

1980

900

2385

1575

2070

1845

3735

810

 

15300

 

0.0429

0.0644

0.0356

0.0127

0.0179

0.0233

0.004

0.0012

 

 

 

 

 

 

 

 

 

 

 

 

 

 

56

23

78

39

48

23

38

2

 

307

mb/Pisa

29143

7918

39938

7288

9384

7252

5929

293

 

109465

 

900

380

1060

700

920

820

1660

360

 

6800

 

0.0467

0.0421

0.0472

0.0443

0.0489

0.0256

0.0211

0.0056

 

 

 

 

 

 

 

 

 

 

 

 

 

 

104

60

260

101

159

100

83

27

 

894

Banks

67823

26111

124858

13393

33662

27080

15682

2919

 

323875

 

2385

1060

2756

1855

2438

2173

4399

954

 

18020

 

0.0319

0.0415

0.0675

0.048

0.0541

0.0396

0.0164

0.0273

 

 

 

 

 

 

 

 

 

 

 

 

 

 

12

18

54

66

79

39

52

36

 

356

Ritagliatori

5776

1847

6751

11657

9328

5110

6439

2229

 

52856

 

1575

700

1855

1190

1610

1435

2905

630

 

11900

 

0.0076

0.0257

0.0275

0.0521

0.0435

0.0244

0.0176

0.0492

 

 

 

 

 

 

 

 

 

 

 

 

 

 

45

33

99

62

153

14

11

28

 

445

Silk

12931

5170

15872

4072

12970

1671

514

2482

 

56645

 

2070

920

2438

1610

2070

1886

3818

828

 

15640

 

0.0179

0.0293

0.0357

0.0348

0.0705

0.0069

0.0029

0.0302

 

 

 

 

 

 

 

 

 

 

 

 

 

 

38

115

102

425

26

49

60

27

 

842

Wool, SM

10818

15583

14191

58392

1885

12722

6723

1748

 

124415

(high

1845

820

2173

1435

1886

1640

3403

738

 

13940

quality)

0.0152

0.1061

0.0405

0.223

0.0133

0.0274

0.0162

0.0366

 

 

 

 

 

 

 

 

 

 

 

 

 

 

10

69

51

364

8

43

64

29

 

638

Wool, Oth.

3927

7106

7214

32260

1089

7953

4367

941

 

69444

(lower

3735

1660

4399

2905

3818

3403

6806

1494

 

28220

quality)

0.0021

0.038

0.0109

0.1053

0.0018

0.012

0.0093

0.0187

 

 

 

 

 

 

 

 

 

 

 

 

 

 

3

2

11

40

47

93

142

2

 

340

Tintori

88

127

805

1487

2034

4617

5672

26

 

14917

(dyeing)

810

360

954

630

828

738

1494

306

 

6120

 

0.0037

0.0028

0.0094

0.0603

0.0568

0.1192

0.0917

0.0065

 

 

 

 

 

 

 

 

 

 

 

 

 

Column

387

416

812

1119

560

412

465

152

 

 

Totals

206

314

604

932

509

372

439

142

 

 

 

15300

6800

18020

11900

15640

13940

28220

6120

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

size of market (# of possible dyadic pairs)

 

 

 

 

 

 

density = # of dyadic pairs with ties / size of market

 

 

 

N.b.: Each cell provides: 1) # of ties; 2) florin value of ties; 3) # of possible dyadic pairs; 4) density of market = (# of pairs with ties / # of possible pairs)


2001 for details); 3) the year in which the partner himself first entered the priorate; 4) whether the partner’s father served on the priorate during the Albizzi regime (1382-1427); 5) the actual two-month periods during which the partner served on the priorate;

6) the year the partner first sat on the Sei della Mercanzia, an administrative body charged chiefly with resolving disputes between actors (between firms, or between firms and private individuals) in the market; 7) whether the partner’s father served on the Mercanzia during the Albizzi regime; 8) the partner’s year of birth, used for calculating his age cohort; 9) the partner’s household wealth in 1427; 10) the partner’s parish of residence in 1427; 11) the partner’s neighborhood of residence in 1427; 12) the partner’s quarter of residence in 1427; 13) the name of the partner’s wife’s family, whenever available; 14) the factional affiliation of the partner himself when antagonism between Medici supporters and defenders of the oligarchic Albizzi regime broke out in the early 1430s; 15) the factional affiliation of the partner’s family.  Data for variables 2 through 5 are drawn from the Tratte holdings in the archives listing the names of participants in all major offices in the city from 1282 on.  This data is also available in less comprehensive form in various published source.  Data on variables 6 and 7 come from archival rosters of Mercanzia participation (Fondo della Mercanzia, ASF).  Data on partner age comes predominantly from (need actual manuscript source info here), but also is available I many instances from the 1427 catasto.  Data for variables 9 through 12 are drawn exclusively from the 1427 catasto.  Data on marriages come from the Carte dell’Ancisa, as well as various published sources (Passerini 18xx, Litta 17xx, etc.).  Data on factional affiliation was taken from Kent (1978), who collected it from primary documentary sources such as the confession offered by Ser Niccolo Tinucci and contemporary patronage letters.

Armed with these attributes of the partners, and with the attributes of firms both as units of commercial enterprise and cum assemblages of partners, we were able to examine both patterns in partnership formation and patterns in the offering of credits, and their possible relationship to each other.

On the partnership formation front, we took a census of all persons active in any of our sectors (wool manufacture, dyeing, and cloth retail; silk manufacture, dyeing, and retail; commercial banking and international merchant-banking) and coded all possible dyadic pairs for whether or not they engaged in a business partnership with each other.  This dependent variable was then parallel in form to the data construction we had done previously (McLean and Padgett 1997) coding the number of credits passed in each direction between all possible dyadic pairs of firms in the market. 

In order to try to explain patterns of partnership and patterns of credits between firms, we assembled a battery of variables indicating whether or not various kinds of social ties existed between pairs of partners in creditor and debtor firms, and testing for the similarity between firms in terms of the similarity of the social, political and economic attributes of the partners who comprised them.  To repeat, the idea was to probe for connections between kinship networks and social, geographic, and political affiliations (and the social identities they confer) on the one hand, and patterns of ties in economic networks on the other. 

Naturally we also generated a number of statistical control variables associated with expected number of ties in the market given the amount of firm activity, firm size, and whether or not we have a complete record of a given firm’s debts as of July 12, 1427.  Expected number of ties is calculated by multiplying the creditor firm’s number of credits in a given industry-by-industry market interface by the debtor’s number of debts in the same market, divided by the total number of debts in that market.  This is precisely the independence model in a Chi-square test, the expected number of ties between firms if creditors and debtors distributed their ties uniformly within that market.  The summary reports of company balances in the portate were viewed and coded for many, but not all, firms.[1]  We assume that the data for these ‘seen’ firms is more comprehensive, and therefore has higher density, than for ‘unseen’ firms, simply as an artifact of our data collection efforts.  Furthermore, since markets differ markedly in the number of ties we observe, we calculated a dummy variable for each industry-by-industry market interface to discern whether the volume (or density) of debt in different markets, independent of the qualities of the firms participating in them, affects the likelihood of debts between firms occurring in the first place.  These also help us to discern whether some ‘industry logic’ is at work pushing firms to pursue credits in certain markets, over and above any social determinants of these choices.

On the partnership side, looking for similarities between partners—whether in terms of concrete interactions between them such as through marriage ties or co-participation in the priorate, or in terms of patterns of co-membership (i.e., common affiliations) in various ascriptive categories like status groups, political and economic elites, age cohorts, and political factions—was relatively straightforward, in that each partner had precisely one set of attributes to compare to each other’s.  Consequently, measures of whether or not partner A and partner B lived in the same gonfalone (neighborhood, for administrative purposes; there were sixteen of them in the city in 1427), or were from the same social class, or were linked through patrilineage or through marriage ties, for example, are essentially all binary variables.  We report on logit regressions on the dependent variable of whether or not we observe a partnership between any given pair of potential partners in Table 5 (printed at the end of the paper).

            On the firm credits side, calculating similarities is slightly dicier, in that each firm may have multiple partners; consequently we needed to create measures of the number of times any partner’s attributes in firm A matched the attributes of any partner in firm B.   That is to say, we calculated degrees of similarity between firms by a pairwise[2] count of the number of partners in creditor and debtor firms respectively who shared ties or common group affiliations.[3]

More specifically, we calculated the following measures of concrete ties between pairs of partners: 1) number of partners shared by the creditor and debtor firms, or in other words, a measure of the number of ‘board interlocks’ between firms; 2) number of partners in the creditor and debtor firms respectively tied to each other through intimate marriage ties;[4] 3) number of partners in creditor and debtor firm sharing marriage ties (parentado) at the level of the patrilineage; 4) number of creditor and debtor firm partners who served simultaneously on the priorate during the 1382-1427 period.  Only nine priors served at a time, and for periods of only two months duration, suggesting that co-participants would have directly interacted with each other during their service.

We also calculated the following measures of shared group affiliation between pairs of partners: 1) number of partners from the creditor and debtor firms who came from the same patrilineage; 2) number of creditor and debtor firm partners who resided in the same parish;[5] 3) number of creditor and debtor firm partners who resided in the same gonfalone, or administrative neighborhood of the city; 4) number of creditor and debtor firm partners who resided in the same quarter of the city; 5) number of creditor and debtor firm partners with shared political/social status;[6] 6) number of creditor and debtor firm partners who were from the same age cohort;[7] 7) number of creditor and debtor firm partners who likewise served on the priorate during the Albizzi period (1382-1427), a period of elite consolidation and the emergence of a civic humanism-based consensual government of the city; 8) number of creditor and debtor firm partners who likewise would come to serve on the priorate during the Medici period that began in 1434; 9) number of creditor and debtor firm partners who likewise served on the court of the Mercanzia during the Albizzi period (1382-1427); 10) number of creditor and debtor firm partners who likewise would come to serve on the court of the Mercanzia during the Medici period that began in 1434; 11) similarity of future factional affiliation across pairs of partners in creditor and debtor firms.[8]  The importance of each of these factors for giving credits was determined, as for the issue of choice of partner, by means of logit regressions, the output from which is reported in Table 6 (printed at the end of the paper).

            Before proceeding with the analysis of the findings concerning the social underpinnings of partnerships and commercial credit, however, it may be instructive first to give some indication of the importance of credit relationships for the solvency of firms.  This we can do by measuring the average size of capital invested in firms within different industries, and by comparing this invested capital to the volume of debt the average firm was carrying.  This is basically a measure of the leverage under which firms were operating, and hence an indication of the extent to which firms were dependent on each other for dependable repayment of credits offered, thus in turn indicating the degree to which the trustworthiness of one’s alters must have been integral to all decisions to offer credit.  These figures are reported in Table 4.

 

Table 4:

Average Capital of Florentine Firms in Key Industries and Degree of Indebtedness with Respect to Invested Capital

 

I.  Average Capital (Corpo) in florins:

                                    N         corpo       corpo+              all previous                        all previous

only     sopraccorpo+       +inventory              +personal

                                                               profits                                               wealth

 

Merchant Banks           23        5080        5751                       6973                8910

 

Domestic Banks          24        6375         9941                     10119              12574

 

Cloth Retail                 21        4305         5348                       7102                7141

 

Silk                              25        3568         3928                       4851                5227

 

Wool, San Martino      30        3239         3654                       4373                4658

(high quality)

 

Wool, Other                24        2030         2233                       2517                2681

(lower quality)

 

Cloth Dyeing                 8        1095         1195                       1595                1636

 

 

II.  Average Leverage (total debt / capital):

                                    N         corpo       corpo+              all previous                        all previous

only     sopraccorpo+       +inventory              +personal

                                                               profits                                               wealth

 

Merchant Banks           12        5.42          4.98                        3.62                 2.77

 

Domestic Banks          14        4.93          3.29                        3.20                 2.36

 

Cloth Retail                 14        2.20          1.66                        1.15                 1.14

 

Silk                              19        0.94          0.86                        0.66                 0.60

 

Wool, San Martino      23        1.17          1.04                        0.84                 0.79

 

Wool, Other                16        0.54          0.48                        0.41                 0.37

 

Cloth Dyeing                 7        2.27          2.03                        1.44                 1.40

            The most noteworthy feature of this table is that Florentine firms, and in particular banks, were leveraged to a considerably greater extent than many firms are today—meaning precisely that they were exposing themselves considerably more to risks in the market than we today consider advisable.  This was particularly true of banks—both banks overseas and those with a Florentine tavola: notwithstanding the greater capital invested in these firms by the partners (as the top half of the table indicates), the debt:capital ratio of these firms was markedly higher than for manufacturing or strictly retailing firms, and was so regardless of how expansively we define the capital the partners could have available to them in the event of a run on the bank.  This is the first indication of the primary importance banks played in the overall economy, as carriers of debt for manufacturing firms.  It appears quite likely that banks accepted credits from manufacturing firms and each other (not to mention individual depositors, for whom we have considerable information not yet analyzed), in the form of both merchandise (for example, finished cloth offered on consignment) and cash deposits, which they used to sell Florentine goods abroad on the one hand, and to pursue promising investment opportunities on the other.  It is, moreover, essential to note how this function of banks—essentially as brokers in a complexly structured economy—differed markedly from the heyday of Florentine banks a century earlier in the early 1300s.  At that time, the main role of the great Bardi, Peruzzi and Gianfigliazzi banks was as creditors to foreign monarchs (although admittedly banks played a substantial merchant/importer function at that time too), and little in the way of a banking system had yet emerged.  Lending was the key to profit.  By 1427, banks had clearly discovered that debt could just as viably be the path to profit as could credit.  The chief risk accordingly shifted from the risk of default (which is what killed those banks in the first place), to the risks associated with constipated cash flow and requests for repayment.

 

Economic Exchange as Social Exchange

 

            Upon examining Tables 5 and 6 two facts should be immediately evident.  First, contrary to any initial suspicions we might have had that social obligations completely enveloped and determined economic relations in pre-modern markets, the statistical controls (Table 6) clearly indicate that the most important ‘predictor’ of the giving of credit in this economy is the joint volume of credits offered and received by creditor and debtor firms.  Credit was actually widely dispersed, rather than concentrated on a handful of alter firms, and thus the market overall had the characteristic of deconcentration often taken to be integral to ‘pure’ markets (see McLean and Padgett 1997 for a more extensive discussion).  Moreover, the next most powerful predictor of giving credit (looking at Table 6 again) is the extent to which firms are connected through interlocking directorates—an organizational innovation fairly new to the time and most famously associated with the Medici and their system of interconnected banks in Florence, Rome, and Venice, in addition to their woolshop in Florence (de Roover 1966).[9] 

The second immediately evident fact, however, is that within this broadly deconcentrated market, certain social relationships were of critical importance for forging both partnerships and credit relationships.  This is especially evident in the large and strongly significant coefficients for shared nuclear family, in-law ties, and shared patrilineage in the complete model of partnership (Table 5) and in the model of all credit relations (Table 6).  Not surprisingly perhaps, family was a critical strong tie upon which economic relationships were based.  The nuclear in-law coefficients in both tables in particular document the importance of marriage as a basis upon which to erect economic ventures.  Yet two important cautions are in order here.  First, on the partnership side, it was by no means always the case that family ties were the modal foundation.  Certainly they had been at the root of banking in the early fourteenth century, but by the middle decades of the 1300s smaller firms with fewer partners typically organized on a master-and-apprentice style of organization came to dominant the field (Padgett 2001), in the spirit of the guild corporatism that characterized the mid-Trecento political regime of the city (Najemy 1982).  The later fifteenth century also had a greater share of cross-family, perhaps patron-client style partnerships, again perhaps imitating the dominant (though informal) political organization of that era.  In short, this finding must be put in proper historical context, and not taken as a given.  Second, it may be of some interest that the effects of shared patrilineage on the giving of credits in key industries is the inverse of its effect on partnership.  It was extremely important for the formation of silk manufacturing partnerships, to such an extent that un-partnered family members were hardly left in the field to do firm-to-firm business with each other.  By contrast, the banking industry was characterized not so much by firms erected on the basis of extended patrilineage, but independent firms operated by scions of separate branches of the family who happened to form a kind of loose consortium of businesses maintaining active current accounts with each other at the core of the market.  This hints at the different styles or forms of organization characterizing these different industries—a topic we will pick up below.

At this point, however, the results presented in Tables 5 and 6 diverge; the kinds of social ties that mattered for each type of relation differed from each other, and differed across industries and markets, and so it begins to be more enlightening to handle the tables separately.  To put it most simply, whereas social class identity is invoked to construct partnerships, neighborhood identity is used to construct credit ties to alter firms.  More precisely, economic partnerships tend to be formed, by all three major class groupings, and in most industries, according to a principle of class endogamy, whereas credits are offered much more commonly according to a logic of neighborhood endogamy without regard to class.  This warrants some explanation.

It is true that in the complete model of partnership, social class endogamy has a less pronounced effect than in the baseline model (prior to the introduction of the kin and neighborhood variables).  Yet the tendency towards class endogamy is not entirely swept away by the family variables, especially not in the banking industry, which evidently was remarkably class-stratified: popolani joined with fellow popolani, new men with fellow new men.  Moreover, these banking partnerships are formed between members of the same class evidently without regard to neighborhood.  This structure also parallels the developments in the polity at large, moving away (forcibly) from a guild corporatist regime to a more consensualist, civic humanism-based regime comprised of a consolidated elite.[10]  The popolani could not keep new men out of the market, but they could well decide to shun them as partners.  The numbers also nicely depict the class endogamy of the most recently arrived industry on the scene, silk, except that here it is the new men and non-admitted who account for the trend.  Silk was, by and large, a new man’s industry.  Wool, by contrast, is the most ‘traditional’ in form: not significant patterns, but patterns nonetheless, indicating a tendency for new men and men never admitted to the priorate to team up with partners from other social classes, which suggests a kind of master-apprentice model which, again, was dominant in the mid-1300s.

We can link these observations and the evident significance of kinship to the findings concerning the importance of neighborhood.  Not surprisingly, neighborhood operates in a compensatory manner with respect to class and family: silk manufacturers who lack large and prestigious families from which to draw potential partners (and who therefore lack social capital) pick neighbors they can trust (and monitor: there is no doubt the neighborhoods of the city were hotbeds of gossip).  The same goes for wool manufacturers (to a lesser extent).  This dovetails nicely with the advice Giovanni di Pagolo Morelli offered in his ricordi to latch onto people in your neighborhood you could trust, as a device for surviving in the cutthroat world of Florentine politics and society.  Thus, in terms of partnership organization, silk is an assemblage of highly ‘locally’ organized firms formed by economically affluent political outsiders, wool maintains the old guild-style organization, and banking is a dense, almost incestuous social network organized without regard to neighborhood locale and stratified by class, in particularly being dominated by elite popolani. 

Given these findings, and given our awareness of how class-conscious early Quattrocento Florence was, in observing the commercial credit part of the picture we have been struck by how little social class seems to have mattered.  There are no significant class effects at the aggregate level of the economy as a whole, and only in a few scattered markets are there significant class endogamy effects, and these effects disappear when kinship and neighborhood are factored in as well.  This is particularly true in business among banks (international, Pisa-based, and domestic), where ‘social class’ is just far too broad a category to capture how ‘incestuous’ the giving and receiving of credit really is.  At a gross level, examination of the production chains in this market (that is, leaving aside the banking system and its interconnections) suggests that the fairly youthful and new man-populated silk industry successfully sought outlets for its production with some of the most entrenched merchant-banker popolani.  Meanwhile, the master-apprentice-style wool firms, regardless of quality, sold their product on consignment to a very sizable extent (see Table 3 above) to Florentine ritagliatori who marketed it domestically; a majority of ritagliatori were new men or individuals not yet admitted to the priorate—that is, men beneath the typical wool merchants in social station.  In other words, on the basis of a crude classification of the class character of each major ‘occupational group,’ the step from production to distribution was flowing across class lines to a considerable extent.  How can this be explained?

Before proceeding to answer that question, let us consider the effect of neighborhood on the giving of credit, since here we do see some significant effects, and the issue of whether or not we observe symmetry or asymmetry in the giving and receiving of credit.  Most notably banks appear to be significantly invested in neighborhood as a frame or an identity facilitating economic relations.  This operates over and above the effect of family ties, which do commonly operate within neighborhoods (as the households of Florentine patrilineages had the pronounced and durable habit of clustering together around particular squares or in particular buildings).  This is evident when we consider all ties in the data, but also for both symmetrical and asymmetrical ties,[11] and when we consider not only ties among banks, but also ties between banks and the wool and silk production industries respectively.  This gonfalone effect, taken in conjunction with the forging of symmetrical ties, is especially noteworthy, since both wool and silk production are, taken by themselves: 1) asymmetrically organized industries—that is, on the wool side, we find a consignment system where the majority of credits flow from wool manufacturers to ritagliatori (a different occupational group in the same ‘industry’),[12] and in silk we find a significant tendency towards asymmetrical ties between what are ostensibly identically oriented firms[13] (see the significant coefficient for asymmetrical silkàsilk ties in the list of market dummies in Table 6); and 2) not significantly attentive to neighborhood identity as a device for forging economic ties.  Consequently, the use of neighborhood as an identity frame is used most pronouncedly by precisely those actors ostensibly most cosmopolitan, including a subset of actors not even living presently in their home neighborhoods (namely, Florentine bankers abroad and merchant-banking firms in Pisa)!  And these actors apparently were able to ‘infiltrate’ contiguous industries in the economy and alter the organizing principles otherwise at work there in the direction of invoking neighborhood identities, and in the direction of symmetrical relations.  For manufacturing firms dependent on the input of raw materials, and dependent on successfully securing profitable outlets for their goods, finding one alter firm capable of supplying both needs (as Florentine merchant bankers could) would be highly beneficial—although at the same time it would carry the cost of a more deeply embedded relationship with that alter firm.  Hence the shift from asymmetrical to symmetrical ties has profound consequences for the structure of the market, understood as a network of firms.

It is time to bring the parts of our puzzle together: the relevance of class for partnership formation, the relevance of neighborhood for commercial credit relations, and the adoption of bank-style symmetry in the relations asymmetrically organized manufacturing sectors have with banks.  Banks were unquestionably the engine of the Florentine economy, in terms of capital resources, number of credits, and the importance of the functions they served as suppliers of cash, raw materials, and distribution networks for cloth producers.  Purely from the standpoint of economic imperatives, banks would need to develop stable, institutionalized relationships with each other; for example, banks depended on constantly fluctuating foreign exchange rates and the regular reportage of such rates to each other for writing the bills of exchange that were one of their main sources of profit (de Roover 1966).  Although we do not know precisely when it happened, the character of banking changed in the course of the 1300s, some time after the bankruptcy of the major family-based firms in the 1320s, 1330s, and 1340s.  As noted above, banks moved away from serving primarily (or at least most saliently) as the creditors of nobles, and towards serving as depositories for the riches of nobles, clerics,[14] and affluent Florentines; they became brokers looking for profit-making opportunities at the interstices of a great variety of economic operations in Florence and abroad.  As brokers in the market, it appears likely they acted as agents for other kinds of actors in the market, and interacted with each other certainly, not only on their own behalf, but also on behalf of their non-bank correspondents.  Consequently the banking system at the core of the economy required a system of current accounts (actually, a system of ‘accounts payable’ and ‘accounts receivable,’ or ‘per loro’ and ‘per noi’ accounts: see de Roover 1944) to keep the economy working smoothly.

But the population of banks was cleaved along class lines.  Were class consciousness to dominate, there would remain debilitating holes in the banking network.  The solution was to use the ‘old’ criterion of neighborhood to reach out across class lines and forge trust.  Unwillingness to form partnerships with new men could not and did not carry over into a willingness to forego the economic opportunities that could accrue from such ties.  In some sense, therefore, we could argue the banking system had a kind of supplementary, or “addendum”-like, clientage structure to it (Eisenstadt and Roniger 1984, ch. 5), in this sense: banking elites reached down across class lines a class-stratified population to locals they knew to extend their networks further.   In other words, the logic of neighborhood as a socially sanctioned identity was then adapted and applied in an incrementally learned way to forge ties with other industries.  Here the desiderata of profit-maximization and seizing upon opportunities for growth are consonant with and pursued through cognitively legitimate channels.  Furthermore, bank relations must have dramatically stimulated the growth of the silk industry, which we know was only just taking off in Florence in the early 1400s, to some extent supplanting the increasingly moribund wool industry which had been the bread and butter of Florentine prosperity over the previous century or more.  Merchant bankers, we argue, saw and capitalized on an opportunity to make money off a new set of producers by both bringing them the raw materials they needed and providing outlets to foreign markets, pulling silk merchants into their accounting practices and principles of organizing economic relations.  Table 5 suggests that the popolani involved in the silk industry did not cohere in particular firms: silk was more or less ‘unorganized’ in terms of class.[15]  Consequently, here we might argue that between banks and silk we are witnessing the emergence of a clientage system that does not cross-cut the central organizing principle of the system as a whole and make it function more smoothly, but rather (to put it provocatively) clientage as the constitutive principle of the market.  This interpretation is bolstered by the coefficients for past and future priorate provided in Table 6.  Since worthiness for the priorate was both formally and informally assessed by worthies in one's own neighborhood who conduct the scrutinies,  economic ties forged through neighborhood but across class ought to have resulted in positive judgments of new men and their fitness for office; the simple corollary of this is that a considerable number of cross-class economic ties would involve, by definition, people previously not chosen to be among the elite of the city.  Given the fact that a number of silk merchants operating in the 1420s later became staunch supporters of the Medici regime (reflected in part in the significant positive coefficient for “Medici party (future)” in Table 6), the clientage depiction of this market becomes even more tantalizing.[16]

Undoubtedly the impact of banks is on the margins of the silk (and wool) industries: silk firms tend to choose each other rather than banks as alters, but when silk firms choose domestic banks as alters, the banks lock them in to symmetrical relations.  Here neighborhood, we have argued, is the device for crafting new ties of a particular sort.  The situation is somewhat different with wool.  Between banking and wool neighborhood is significant for forging ties, yet there is a general absence of bank-wool ties, in a fairly predictable rank order: 1) higher quality wool producers were sending goods to ritagliatori to a significant extent (although not receiving goods in return), and to Pisa banks (who specialized in importing and exporting functions, as Pisa was Florence’s Mediterranean port) to a lesser extent, without any significant tie to domestic banks or international banks; 2) for lower quality woolen cloth producers, ties to international and domestic banks are significantly absent.  As a whole, it appears the wool industry was retreating in prominence and retreating from the European market (even though we know there were a number of very successful firms exporting wool cloth abroad in the later fifteenth century (see, for example, Richards 1932).  Gonfalone is thus important in linking banks with wool firms, but only in a situation where the number of such ties appears to be shrinking, and where the character of such ties is asymmetrical.  It is tempting to suggest, although perhaps not entirely defensible, that neighborhood is the last bastion of social obligation between the banking industry and a wool industry on the decline—a constraining tie rather than an opportunity.  Why this should be is not entirely clear: the literature suggests the quality of the finest Florentine wools was high and perhaps even improving (Hoshino 1980).  Did banks have only so many resources to go around, and saw silk as the superior investment opportunity?  Or were socially up-and-coming ritagliatori the main actors here, persuading wool manufacturers to market their wares increasingly through them in the less prestigious but also less volatile domestic market?[17]  There may also have been international reasons for the shift to ritagliatori, for example along the lines of restrictions on imports of Florentine woolen cloth abroad; but we do not know of such restrictions having been put in place.  In short, we can easily enough interpret the results of our detailed snapshot of commercial credit relations in 1427 in terms of the long-term trends we know were operative in the economy, and in the polity.  However, we cannot yet consistently specify a mechanism accounting for these dynamic trends.

 

Conclusion: For a Nuanced Understanding of Embeddedness

            It has been often repeated by now that economic sociologists cannot simply state that social relations undergird economic relations, or that the economy is embedded in social life.  We must move on to concrete specification of which kinds of social relations matter and how to which kinds of economic relations.  The central broad findings of our research include the following: 1) that different types of social ties matter for different types of economic relations; 2) that different types of social relations (and the identities they represent) intersect, softening or reinforcing each other in different ways in different situations, to effect economic ties; 3) that in certain instances we should think of economic ties (as did Adam Smith) as the basis for emergent “bonds of union and friendship” (Smith 1976, I:519), rather than as being only the result of underlying social ties; 4) that social ties can be understood to provide both opportunities and constraints for economic action; 5) that social ties reflect actor identities, which act as frames (Goffman 1974) for organizing conduct in the world and adapting old experiences to new situations.  In particular, concerning the Renaissance Florentine economy, we have shown, among other things, that highly class-conscious Florentines found a way around class in their effort to build and participate in a vibrant economy.


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Richards, Gertrude. 1932.  Florentine Merchants in the Age of the Medici.  Cambridge: Harvard University Press.

 

Sapori, Armando.  1926.  La crisi delle compagnie mercantili del Bardi e dei Peruzzi.  Firenze: Leo S. Olschki.

 

Sapori, Armando.  1932.  Una compagnia di Calimala ai primi del Trecento.  Firenze: Leo S. Olschki.

 

Sapori, Armando.  1970.  The Italian Merchant in the Middle Ages.  New York: Norton.

 

Smith, Adam. 1976.  An Inquiry Into the Nature and Causes of the Wealth of Nations.  Edited by Edwin Cannan.  Chicago: University of Chicago Press.

 

Uzzi, Brian.  1996.  The Sources and Consequences of Embeddedness for the Economic Performance of Organizations: The Network Effect,” American Sociological Review 61,4 (1996):674-698.

 

Weissman, Ronald F. E.  1982.  Ritual Brotherhood in Renaissance Florence.  New York: Academic Press.

 

 

 


Table 5: Predicting Partnerships: Logit Regressions on Partnership Dyads

 

                                                            Percentage          Dependent variable = (in partnership

Of                                                                    or not)

                                                            Partners                      

Independent variables:                                                            baseline           complete

                                                                                                model              model 

Social Class:

Popolani + Magnates:

            within m-banking sector          66.4                               .943***             .334**           

            within wool sector                  46.5                               .857***             .124  

            within silk industry                  35.4                             1.120***           -.003  

New Men + New-new Men:

            within m-banking sector          13.5                             1.235***             .634* 

            within wool sector                  32.7                               .313               -.248  

            within silk industry                  36.6                             1.289***             .606*

No Admit:

            within m-banking sector          20.1                             1.246***             .737**           

            within wool sector                  20.8                               .085               -.331  

            within silk industry                  28.0                               .731*                .780* 

 

Kinship Relations:

Nuclear Family                                                                                               4.311***

In-law Nuclear Family                                                                                    2.541***

Patrilineage Family (excl nuclear)

            within m-banking sector                                                                      1.891***

            within wool sector                                                                              2.832***

            within silk industry                                                                              3.509***

In-law Patrilineage Family                                                                              1.406***

 

Neighborhood Relations:

Same Gonfalone

            within m-banking sector                                                                        .303

            within wool sector                                                                                .614**

            within silk industry                                                                                .988**

Same Quarter (excl. gonfalone)                                                                         .399**

 

Political Relations:

Medici party (future)                                                                                       -.656*

Albizzi party (future)                                                                                       -1.443

 

 

*** = (p < .001); ** = (p < .01); * = (p < .05)

 

Number of observations                                                          56,284             56,284

Number of non-zero observations                                                732                  732

Table 5 (cont’d)

 

Log likelihood                                                                         -3824.46          -3266.99

Likelihood ratio                                                                      162.78             1277.70

Number of parameters                                                                 9                    21

Probability > chi-squared                                                       .0000               .0000

Pseudo R-squared                                                                   .021                 .164

 

 


Table 6: Predicting Commercial Credit: Logit Regressions on Credit Relations

 

Dependent variable =  dichotomized credit

(i.e., credit received or not)

Independent                             baseline           all credit    =   symmetric  +    asymmetric

variables:                                model              relations          relations          relations

                       

Statistical Controls:

Firms’ credit volumes             7.046***           6.162***            2.115***            5.138***      

Creditori bilancio seen             .616***             .385***              .716***               .345***        

Debitori bilancio seen               .572***             .329***              .589***              .309***  

Creditori partners’ wealth       1.41e-06         -0.66e-06        -2.80e-06        0.37e-06

Debitori partners’ wealth        -2.07e-06*       -4.09e-06***     -0.91e-06         -5.27e-06***

 

Social Class:

Popolani + Magnates:

   within m-banking sector         .451***             .137                 .207                 .062

   between banking and wool   -.019               -.146               -.405               -.108

   between banking and silk       .050                 .046                 .520                -.091

   within wool sector                 .044                 .005                 .639               -.073

   within silk industry               -.646               -.664                 .000               -.378

 

New Men + New-new Men:

   within m-banking sector         .600*                .230               -.215                 .168

   between banking and wool     .023               -.110               -.457               -.041

   between banking and silk       .529*                .389               -.699                 .524*

   within wool sector                 .142                 .020               -.461                 .133

   within silk industry               -.115               -.461                 .216               -.499

 

No Admit:

   within m-banking sector         .152               -.440               -.247               -.589

   between banking and wool     .444*                .415(*)            1.194**                          .229

   between banking and silk       .525                 .557                 .154                 .461

   within wool sector                 .191                 .354                 .844                 .255

   within silk industry               -.625               -.582               -.931               -.548

 

 

 

 

 

 

 

 

 

Table 6 (cont’d)

 

Dependent variable =  dichotomized credit

(i.e., credit received or not)

 

Independent                             baseline           all credit          symmetric        asymmetric

variables (cont.):                     model              relations          relations          relations

 

Economic Relations:

Org. system (same partner)                             6.306***           6.301***           1.979*

Brokerage (ln # same third comps.)                  .614***           1.121***             .583***

 

Kinship Relations:

Nuclear Family (excl. self)                             3.176***           3.669***           2.190***

In-law Nuclear Family                                    2.154*              3.291*              1.187

Patrilineage Family (excl. nuclear)                                        

   within m-banking sector                               1.788***           1.932***             .849

   between banking and wool                             .548               2.409(*)            -.138

   between banking and silk                               .561               -.847                  .974

   within wool sector                                       1.518*              2.632(*)            1.278

   within silk industry                                         .000                 .000                 .000

In-law  Patrilineage Family                               .084               -.280                  .227

 

Neighborhood Relations:

Same Gonfalone:

   within m-banking sector                               1.289***           1.477***             .693*

   between banking and wool                             .517*              1.159**                          .431*

   between banking and silk                               .724*              1.642***             .125

   within wool sector                                         .031               -.024                 .098

   within silk industry                                       -.109               1.146               -.182

Same Quarter (excl. gonfalone)                         .132*                .048                 .127(*)

 

Political Relations:

Medici party (future)                                         .408               1.103*             -.178

Albizzi party (future)                                         .857                 .585                 .538

 

Priorate (past): Creditori                                 .115                 .094                .134

Priorate (future): Creditori                                .250*                .682**                          .172

Priorate (past): Debitori                                   .179(*)              .197                 .168

Priorate (future): Debitori                                 .153                 .683**                          .039

 

Mercanzia (past): Creditori                            -.084                 .309               -.204

Mercanzia (future): Creditori                          -.062               -.438                 .034

Mercanzia (past): Debitori                              -.247               -.227               -.218

Mercanzia (future): Debitori                           -.335**                        -.613**                        -.254*

 

 

 

Table 6 (cont’d)

 

Dependent variable =  dichotomized credit

(i.e., credit received or not)

 

Independent                             baseline           all credit          symmetric        asymmetric

variables (cont.):                     model              relations          relations          relations

 

Markets:

Merchant-Banking sector:

M.B., Int’l. → M.B., Int’l.         .169                 .060                 1.375***           -.060

M.B., Int’l. → M.B., F/Pisa      .079                 .073               1.420***           -.018

M.B., F/Pisa → M.B., Int’l.      .307                 .169                1.584***           -.130

M.B., F/Pisa → M.B., F/Pisa  -.206               -.450               -.232                -.394

M.B., F/Pisa → Dom. Banks   -.070               -.217                 .587               -.373

Dom. Banks → M.B., F/Pisa   -.036               -.250                 .660*              -.516*

M.B., Int’l. → Dom. Banks     -.279               -.291                 .559               -.403*

Dom. Banks → M.B., Int’l.     -.009               -.123                 .817**                        -.230

Dom. Banks → Dom. Banks      .209                 .028                1.112***           -.138

 

Between banking and wool sectors:

M.B., Int’l. → Wool, S.M.      -.227               -.228                -.776                -.141

Wool, S.M. → M.B., Int’l.      -.356               -.359                -.279                -.311   

M.B., Int’l. → Wool, Other     -1.136***         -.947***             -.796                -1.047***

Wool, Other → M.B., Int’l.     -1.658***         -1.465***          -.763                -1.666***

M.B., F/Pisa → Wool, S.M.     .040               -.071                .196                -.151

Wool, S.M. → M.B., F/Pisa     .180               .090                -1.633**           .337

M.B., F/Pisa → Wool, Other  -.276               -.141                -.200                -.083