Efficiency in the Mondragon Cooperatives: Evidence from an Econometric case study For Presentation at the CONGRESO INTERNA...
<ul><li>Mondragon Group </li></ul><ul><li>The case: EROSKI </li></ul><ul><li>Data  </li></ul><ul><li>Insider econometric e...
MONDRAGON HUMANITY AT WORK MONDRAGON GROUP
<ul><li>The Mondragon Group: often considered the most successful example of employee-owned enterprise in the world.   </l...
<ul><li>250+ organizations, 92,773 employees   </li></ul><ul><li>3 BUSINESS GROUPS: </li></ul><ul><ul><ul><li>FINANCIAL </...
Group Structure Mondragon Group
Sales, 2008 Industrial Group 6,511 Retail Group 9,073 TOTAL SALES 15,584 M€ Mondragon Group
Work force Geographic Distribution, 2008 Mondragon Group
Work force Industrial Distribution, 2008 Mondragon Group
Mondragon in the world, 2008 Mondragon Group
Cooperative Structure Mondragon Group
EROSKI GROUP The case: EROSKI
Group Structure Mondragon Group
Distribution Area Agro-food Eroski Retail Hypermarkets Supermarkets Dapargel Forum Sport Eroski Travel The case: EROSKI
Retail & Allied Group, Sales History, 1988-2008 Why Eroski?
<ul><li>Eroski Chain </li></ul><ul><li>One of the largest and rapidly growing members of Mondragon Group </li></ul><ul><li...
<ul><li>Eroski Chain </li></ul><ul><li>Total employment  ~  50, 600  </li></ul><ul><li>Eroski the third largest retail cha...
<ul><li>RQ1: Is the legal structure important to explain firm productivity? </li></ul><ul><ul><li>H1: Cooperatives are mor...
The Case:  THREE OWNERSHIP STRUCTURES Regular and temporary contract workers. GESPA non-members (regular workers opting no...
The Case:  THREE OWNERSHIP STRUCTURES Null reduced very high % members among workers No Minimum Yes for members Wage premi...
<ul><li>for teamwork; </li></ul><ul><li>to produce and share valuable local  knowledge; </li></ul><ul><li>to respond to lo...
<ul><li>COOP vs. GESPA </li></ul><ul><li>Much more limited participation in decision making in GESPA than in COOP. </li></...
<ul><li>COOP vs. GESPA </li></ul><ul><li>Membership in GESPA involves a capital stake that is about half as large as in a ...
<ul><li>COOP vs. Capitalist </li></ul><ul><li>Capitalist lacks:  </li></ul><ul><li>Whatever GESPA lacks as compared to COO...
<ul><li>GESPA vs. Capitalist </li></ul><ul><li>As compared to GESPA, Capitalist lacks:  </li></ul><ul><li>Job security; </...
<ul><li>Key performance & financial panel data for: </li></ul><ul><ul><li>435 supermarkets (142 coop, 26 Gespa, 267 conven...
First difference model (2) Insider econometrics evidence
<ul><li>Δ indicates the first difference between month t and t-1;  </li></ul><ul><li>Q it  = output (real sales) in store ...
321 967 8001 703 4747 1420 675 N (0.1024) (0.1390) (0.0874) (0.0615) (0.0974) (0.0669) (0.0434) 0.0022  0.0069  0.0025  0....
<ul><li>In addition to labor (L), store space often considered crucial capital input (K) in retail service production.  </...
<ul><li>Control variables </li></ul><ul><li>A store located in a rapidly growing market with rising population and average...
321 967 8001 703 4747 1420 675 N (0.0999) (0.1156) (0.1048) (0.0967) (0.1129) (0.1071) (0.1152) 0.0012  0.0029  0.0038  0....
<ul><li>Due to the standard lifecycle model of retail stores, younger stores tend to grow faster than older stores. To con...
321 967 8001 703 4747 1420 675 N (1.8423) (2.5270) (4.9424) (2.7747) (4.7485) (4.4902) (5.4675) 2002.05 2000.18 1999.36 20...
<ul><li>constant (to capture an Eroski-wide time trend which is common to all Eroski stores regardless of its ownership ty...
<ul><li>The first-difference model adopted for two reasons.  </li></ul><ul><ul><li>Field research at Eroski    sales grow...
Sales Growth and Ownership Types: Insider Econometric Evidence  Dependent variable=  lnQ it   0.311 0.404 0.852 R-squared...
<ul><li>1.  The extent of “Opportunity” measured by: </li></ul><ul><ul><li>INVOLVE i  = proportion of scheduled work hours...
321 967 8001 703 4747 1420 675 N (0.0003) (0.0084) (0.0001) (0.0034) (0.0057) (0.0007) (0.0048) 0.0000  0.0044  0.0000  0....
<ul><li>The strength of “Incentive” gauged by: </li></ul><ul><ul><li>STAKE i  = average stake of employee owners (monthly ...
321 967 8001 703 4747 1420 675 N 0.0000  (0.1549) 0.0000  (0.1532) (0.1186) (0.1352) (0.0739) 0.0000  0.6443  0.0000  0.51...
<ul><li>3.  The extent of “skill/ability” measured by: </li></ul><ul><ul><li>TRAINING i  = proportion of scheduled hours s...
321 967 8001 703 4747 1420 675 N (0.0129) (0.0415) (0.0534) (0.0215) (0.0386) (0.0152) (0.0130) 0.0059  0.0108  0.0062  0....
New model: (3) Insider econometrics evidence: additional analysis
Sales Growth and HRM for Hypermarket:  Dependent variable=  lnQ it   0.852 0.852 0.847 0.852 R-squared 2070 2070 1889 207...
Sales Growth and HRM for Supermarket (City only) Dependent variable=  lnQ it   0.311 0.311 0.311 0.311 R-squared 1195 119...
<ul><li>We also estimated a fully nested version of Eq. (3) with all four HPWP variables considered simultaneously.  </li>...
<ul><li>RQ1: Is the legal structure important to explain firm productivity? </li></ul><ul><ul><li>H1: Cooperatives are mor...
<ul><li>RQ2: Which legal structure is nearest to the HPWS? </li></ul><ul><ul><li>H2: Cooperatives are more likely to perfo...
<ul><li>Thank you! </li></ul>
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Productividad en las cooperativas de Mondragon: estudio de un caso econométrico

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En el marco del congreso internacional de economía social celebrado en EOI Sevilla y en colaboración con Goldsmiths College, Saioa Arando Lasagabaster y Mónica Gago García, MIK, S.Coop. & Mondragon Unibertsitatea-Enpresagintza, presentan su estudio que prueba que las cooperativas son las formas jurídicas más rentables.
27_05_2010

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Productividad en las cooperativas de Mondragon: estudio de un caso econométrico

  1. 1. Efficiency in the Mondragon Cooperatives: Evidence from an Econometric case study For Presentation at the CONGRESO INTERNACIONAL DE ECONOMIA SOCIAL (EOI) Saioa Arando (MIK, S.Coop. & MU-Enpresagintza) Monica Gago (MIK, S.Coop. & MU-Enpresagintza) Derek C. Jones (Hamilton College) Takao Kato (Colgate University)
  2. 2. <ul><li>Mondragon Group </li></ul><ul><li>The case: EROSKI </li></ul><ul><li>Data </li></ul><ul><li>Insider econometric evidence </li></ul><ul><li>Conclusions </li></ul>INDEX
  3. 3. MONDRAGON HUMANITY AT WORK MONDRAGON GROUP
  4. 4. <ul><li>The Mondragon Group: often considered the most successful example of employee-owned enterprise in the world.  </li></ul>Mondragon Group
  5. 5. <ul><li>250+ organizations, 92,773 employees </li></ul><ul><li>3 BUSINESS GROUPS: </li></ul><ul><ul><ul><li>FINANCIAL </li></ul></ul></ul><ul><ul><ul><li>INDUSTRIAL – 12 DIVISIONS </li></ul></ul></ul><ul><ul><ul><li>RETAIL & ALLIED </li></ul></ul></ul><ul><li>KNOWLEGDE AREA </li></ul><ul><ul><ul><ul><li>UNIVERSITY – 3 Faculties / Schools... Engineering – Business – Humanities & Ed </li></ul></ul></ul></ul><ul><ul><ul><ul><li>R&D CENTERS (11) </li></ul></ul></ul></ul><ul><ul><ul><ul><li>MANAGEMENT & COOPERATIVE TRAINING CENTER </li></ul></ul></ul></ul><ul><li>.  </li></ul>Group Structure Mondragon Group
  6. 6. Group Structure Mondragon Group
  7. 7. Sales, 2008 Industrial Group 6,511 Retail Group 9,073 TOTAL SALES 15,584 M€ Mondragon Group
  8. 8. Work force Geographic Distribution, 2008 Mondragon Group
  9. 9. Work force Industrial Distribution, 2008 Mondragon Group
  10. 10. Mondragon in the world, 2008 Mondragon Group
  11. 11. Cooperative Structure Mondragon Group
  12. 12. EROSKI GROUP The case: EROSKI
  13. 13. Group Structure Mondragon Group
  14. 14. Distribution Area Agro-food Eroski Retail Hypermarkets Supermarkets Dapargel Forum Sport Eroski Travel The case: EROSKI
  15. 15. Retail & Allied Group, Sales History, 1988-2008 Why Eroski?
  16. 16. <ul><li>Eroski Chain </li></ul><ul><li>One of the largest and rapidly growing members of Mondragon Group </li></ul><ul><li>Core businesses=supermarkets (705) and hypermarkets (109)=the focus of our investigation. </li></ul>The Case: Core Businesses
  17. 17. <ul><li>Eroski Chain </li></ul><ul><li>Total employment ~ 50, 600 </li></ul><ul><li>Eroski the third largest retail chain in Spain. </li></ul><ul><li>Eroski is among the ten best spanish brands ( Branding Global y Brand Finance ). </li></ul>The Case: Third largest retail chain in Spain
  18. 18. <ul><li>RQ1: Is the legal structure important to explain firm productivity? </li></ul><ul><ul><li>H1: Cooperatives are more productive than others. </li></ul></ul><ul><li>RQ2: Which legal structure is nearest to the HPWS? </li></ul><ul><ul><li>H2: Cooperatives are more likely to perform as a HPWS </li></ul></ul>Research Questions
  19. 19. The Case: THREE OWNERSHIP STRUCTURES Regular and temporary contract workers. GESPA non-members (regular workers opting not to join and temporary contract workers) COOP non-members (prospective members on probation and temporary contract workers) Non-members None. GESPA Members COOP Members Members Capitalist stores GESPA stores COOP stores
  20. 20. The Case: THREE OWNERSHIP STRUCTURES Null reduced very high % members among workers No Minimum Yes for members Wage premia No Yes for members Yes for members Job security Null Moderate High Decision-making Participation Null Moderate High Ownership Participation CONVEN TIONAL GESPA COOP            
  21. 21. <ul><li>for teamwork; </li></ul><ul><li>to produce and share valuable local knowledge; </li></ul><ul><li>to respond to local shocks quickly; </li></ul><ul><li>to accumulate firm-specific human capital; </li></ul>COOP as High Performance Work System Ability/skill Incentive Goal Alignment Job Security Opportunity High Performance Work System
  22. 22. <ul><li>COOP vs. GESPA </li></ul><ul><li>Much more limited participation in decision making in GESPA than in COOP. </li></ul><ul><li>GESPA membership widely regarded as a “second class” form of membership. </li></ul><ul><li>More limited opportunities in GESPA than in COOP. </li></ul>COOP as High Performance Work System
  23. 23. <ul><li>COOP vs. GESPA </li></ul><ul><li>Membership in GESPA involves a capital stake that is about half as large as in a COOP (3,000 vs. 6,000 euros). </li></ul><ul><li>Average stake of GESPA members: less than one tenth of that of COOP members </li></ul><ul><li>%members: 61% in GESPA vs. 76% in COOP </li></ul><ul><li>Weaker incentives in GESPA than in COOP. </li></ul><ul><li>In sum, COOP more likely to be HPWS than GESPA. </li></ul>COOP as High Performance Work System
  24. 24. <ul><li>COOP vs. Capitalist </li></ul><ul><li>Capitalist lacks: </li></ul><ul><li>Whatever GESPA lacks as compared to COOP; </li></ul><ul><li>Job security; </li></ul><ul><li>Efficiency wage enjoyed by COOP members (about 20%); </li></ul><ul><li>COOP more likely to be HPWS than Capitalist. </li></ul>COOP as High Performance Work System
  25. 25. <ul><li>GESPA vs. Capitalist </li></ul><ul><li>As compared to GESPA, Capitalist lacks: </li></ul><ul><li>Job security; </li></ul><ul><li>Efficiency wage enjoyed by GESPA members (about 20%); </li></ul><ul><li>GESPA’s advantages in opportunities and incentives over Capitalist are much more modest. </li></ul><ul><li>Neither GESPA nor Capitalist is close to HPWS. </li></ul>COOP as High Performance Work System
  26. 26. <ul><li>Key performance & financial panel data for: </li></ul><ul><ul><li>435 supermarkets (142 coop, 26 Gespa, 267 conventional) and 80 hypermarkets (25 Coop, 55 Gespa). </li></ul></ul><ul><ul><li>Monthly data (feb-06/may-08) </li></ul></ul><ul><ul><li>10.000 observations for supermarkets and 2.150 observations for hypermarkets. </li></ul></ul>Data
  27. 27. First difference model (2) Insider econometrics evidence
  28. 28. <ul><li>Δ indicates the first difference between month t and t-1; </li></ul><ul><li>Q it = output (real sales) in store i in month t; </li></ul><ul><li>L it = employment (measured by the number of full-time equivalent workers) in store i in month t; </li></ul><ul><li>COOP i = 1 if store i is a coop store, 0 otherwise; </li></ul><ul><li>GESPA i = 1 if store i is a GESPA store, 0 otherwise. </li></ul>Insider econometrics evidence
  29. 29. 321 967 8001 703 4747 1420 675 N (0.1024) (0.1390) (0.0874) (0.0615) (0.0974) (0.0669) (0.0434) 0.0022 0.0069 0.0025 0.0039 0.0024 0.0016 0.0004  lnL it (0.1162) (0.1826) (0.1749) (0.1692) (0.1590) (0.2345) (0.1663) 0.0020 0.0105 0.0053 0.0061 0.0042 0.0004 0.0021  lnQ it Conventional COOP Conventional GESPA COOP GESPA COOP City All stores Supermarket Hypermarket
  30. 30. <ul><li>In addition to labor (L), store space often considered crucial capital input (K) in retail service production. </li></ul><ul><li>For all Eroski stores during the time period under study, however, month to month variations of store space are zero and hence in our first-difference model, </li></ul><ul><li> lnK it = 0. </li></ul>Insider econometrics evidence
  31. 31. <ul><li>Control variables </li></ul><ul><li>A store located in a rapidly growing market with rising population and average household income will naturally grow its sales faster. </li></ul><ul><li>To control for such differences in each store’s market condition, </li></ul><ul><ul><li> MARKET it where MARKET it = monthly market index in month t for the area which store i serves. </li></ul></ul>Insider econometrics evidence
  32. 32. 321 967 8001 703 4747 1420 675 N (0.0999) (0.1156) (0.1048) (0.0967) (0.1129) (0.1071) (0.1152) 0.0012 0.0029 0.0038 0.0036 0.0029 0.0035 0.0034  MARKET it (0.1024) (0.1390) (0.0874) (0.0615) (0.0974) (0.0669) (0.0434) 0.0022 0.0069 0.0025 0.0039 0.0024 0.0016 0.0004  lnL it (0.1162) (0.1826) (0.1749) (0.1692) (0.1590) (0.2345) (0.1663) 0.0020 0.0105 0.0053 0.0061 0.0042 0.0004 0.0021  lnQ it Conventional COOP Conventional GESPA COOP GESPA COOP City All stores Supermarket Hypermarket
  33. 33. <ul><li>Due to the standard lifecycle model of retail stores, younger stores tend to grow faster than older stores. To control for such a lifecycle effect, we also include </li></ul><ul><ul><li>YEAROPENED i = the year store i was opened. </li></ul></ul>Insider econometrics evidence
  34. 34. 321 967 8001 703 4747 1420 675 N (1.8423) (2.5270) (4.9424) (2.7747) (4.7485) (4.4902) (5.4675) 2002.05 2000.18 1999.36 2000.63 1998.41 1999.90 1995.48 YEAROPENED i (0.0999) (0.1156) (0.1048) (0.0967) (0.1129) (0.1071) (0.1152) 0.0012 0.0029 0.0038 0.0036 0.0029 0.0035 0.0034  MARKET it (0.1024) (0.1390) (0.0874) (0.0615) (0.0974) (0.0669) (0.0434) 0.0022 0.0069 0.0025 0.0039 0.0024 0.0016 0.0004  lnL it (0.1162) (0.1826) (0.1749) (0.1692) (0.1590) (0.2345) (0.1663) 0.0020 0.0105 0.0053 0.0061 0.0042 0.0004 0.0021  lnQ it Conventional COOP Conventional GESPA COOP GESPA COOP City All stores Supermarket Hypermarket
  35. 35. <ul><li>constant (to capture an Eroski-wide time trend which is common to all Eroski stores regardless of its ownership types), </li></ul><ul><li>monthly dummy variables (to capture seasonality of retail sales), and </li></ul><ul><li>year dummy variables (to control for year time effects) </li></ul>Insider econometrics evidence
  36. 36. <ul><li>The first-difference model adopted for two reasons. </li></ul><ul><ul><li>Field research at Eroski  sales growth a primary business goal, </li></ul></ul><ul><ul><li>First-difference models control for all time-invariant unobserved heterogeneity of stores that affects the level of sales. </li></ul></ul>Insider econometrics evidence
  37. 37. Sales Growth and Ownership Types: Insider Econometric Evidence Dependent variable=  lnQ it 0.311 0.404 0.852 R-squared 1195 10994 2070 N -0.0001 [-0.10] GESPA i 0.0074** [2.63] -0.0003 [-0.32] 0.0022** [2.94] COOP i 0.0002 [0.29] 0.0004** [2.36] 0.00016* [1.87] YEAROPENED i 1.165*** [5.90] 0.815*** [19.39] 0.645*** [9.92]  MARKET it 0.292** [2.03] 0.265*** [4.96] 0.552*** [6.57]  lnL it Supermarket City only Supermarket Hypermarket
  38. 38. <ul><li>1. The extent of “Opportunity” measured by: </li></ul><ul><ul><li>INVOLVE i = proportion of scheduled work hours spent on joint labor-management meetings (monthly average of store i during the time period under study). </li></ul></ul>Insider econometrics evidence: additional analysis
  39. 39. 321 967 8001 703 4747 1420 675 N (0.0003) (0.0084) (0.0001) (0.0034) (0.0057) (0.0007) (0.0048) 0.0000 0.0044 0.0000 0.0012 0.0033 0.0002 0.0024 INVOLVE i (1.8423) (2.5270) (4.9424) (2.7747) (4.7485) (4.4902) (5.4675) 2002.05 2000.18 1999.36 2000.63 1998.41 1999.90 1995.48 YEAROPENED i (0.0999) (0.1156) (0.1048) (0.0967) (0.1129) (0.1071) (0.1152) 0.0012 0.0029 0.0038 0.0036 0.0029 0.0035 0.0034  MARKET it (0.1024) (0.1390) (0.0874) (0.0615) (0.0974) (0.0669) (0.0434) 0.0022 0.0069 0.0025 0.0039 0.0024 0.0016 0.0004  lnL it (0.1162) (0.1826) (0.1749) (0.1692) (0.1590) (0.2345) (0.1663) 0.0020 0.0105 0.0053 0.0061 0.0042 0.0004 0.0021  lnQ it Conventional COOP Conventional GESPA COOP GESPA COOP City All stores Supermarket Hypermarket
  40. 40. <ul><li>The strength of “Incentive” gauged by: </li></ul><ul><ul><li>STAKE i = average stake of employee owners (monthly average of store i during the time period under study). </li></ul></ul><ul><ul><li>MEMBER i = proportion of workers who are COOP or GESPA members (monthly average of store i during the time period under study). </li></ul></ul>Insider econometrics evidence: additional analysis
  41. 41. 321 967 8001 703 4747 1420 675 N 0.0000 (0.1549) 0.0000 (0.1532) (0.1186) (0.1352) (0.0739) 0.0000 0.6443 0.0000 0.5181 0.7289 0.6076 0.7590 MEMBER i 0.00 (10545.04) (23.56) (201.35) (8175.98) (1010.40) (8847.05) 0.00 23030.07 1.40 865.63 26270.68 2511.33 33295.79 STAKE i (0.0003) (0.0084) (0.0001) (0.0034) (0.0057) (0.0007) (0.0048) 0.0000 0.0044 0.0000 0.0012 0.0033 0.0002 0.0024 INVOLVE i (1.8423) (2.5270) (4.9424) (2.7747) (4.7485) (4.4902) (5.4675) 2002.05 2000.18 1999.36 2000.63 1998.41 1999.90 1995.48 YEAROPENED i (0.0999) (0.1156) (0.1048) (0.0967) (0.1129) (0.1071) (0.1152) 0.0012 0.0029 0.0038 0.0036 0.0029 0.0035 0.0034  MARKET it (0.1024) (0.1390) (0.0874) (0.0615) (0.0974) (0.0669) (0.0434) 0.0022 0.0069 0.0025 0.0039 0.0024 0.0016 0.0004  lnL it (0.1162) (0.1826) (0.1749) (0.1692) (0.1590) (0.2345) (0.1663) 0.0020 0.0105 0.0053 0.0061 0.0042 0.0004 0.0021  lnQ it Conventional COOP Conventional GESPA COOP GESPA COOP City All stores Supermarket Hypermarket
  42. 42. <ul><li>3. The extent of “skill/ability” measured by: </li></ul><ul><ul><li>TRAINING i = proportion of scheduled hours spent on training in general (crude). </li></ul></ul>Insider econometrics evidence: additional analysis
  43. 43. 321 967 8001 703 4747 1420 675 N (0.0129) (0.0415) (0.0534) (0.0215) (0.0386) (0.0152) (0.0130) 0.0059 0.0108 0.0062 0.0103 0.0139 0.0081 0.0074 TRAINING i 0.0000 (0.1549) 0.0000 (0.1532) (0.1186) (0.1352) (0.0739) 0.0000 0.6443 0.0000 0.5181 0.7289 0.6076 0.7590 MEMBER i 0.00 (10545.04) (23.56) (201.35) (8175.98) (1010.40) (8847.05) 0.00 23030.07 1.40 865.63 26270.68 2511.33 33295.79 STAKE i (0.0003) (0.0084) (0.0001) (0.0034) (0.0057) (0.0007) (0.0048) 0.0000 0.0044 0.0000 0.0012 0.0033 0.0002 0.0024 INVOLVE i (1.8423) (2.5270) (4.9424) (2.7747) (4.7485) (4.4902) (5.4675) 2002.05 2000.18 1999.36 2000.63 1998.41 1999.90 1995.48 YEAROPENED i (0.0999) (0.1156) (0.1048) (0.0967) (0.1129) (0.1071) (0.1152) 0.0012 0.0029 0.0038 0.0036 0.0029 0.0035 0.0034  MARKET it (0.1024) (0.1390) (0.0874) (0.0615) (0.0974) (0.0669) (0.0434) 0.0022 0.0069 0.0025 0.0039 0.0024 0.0016 0.0004  lnL it (0.1162) (0.1826) (0.1749) (0.1692) (0.1590) (0.2345) (0.1663) 0.0020 0.0105 0.0053 0.0061 0.0042 0.0004 0.0021  lnQ it Conventional COOP Conventional GESPA COOP GESPA COOP City All stores Supermarket Hypermarket
  44. 44. New model: (3) Insider econometrics evidence: additional analysis
  45. 45. Sales Growth and HRM for Hypermarket: Dependent variable=  lnQ it 0.852 0.852 0.847 0.852 R-squared 2070 2070 1889 2070 N 0.255 [1.15] TRAINING i 0.0037 [1.01] MEMBER i 6.2x10 -8 *** [2.74] STAKE i 0.558*** [2.84] INVOLVE i 0.00007 [0.87] 0.0001 [1.16] 0.0002*** [2.71] 0.00014 [1.61] YEAROPENED i 0.645*** [9.92] 0.645*** [9.92] 0.653*** [9.51] 0.645*** [9.92]  MARKET it 0.552*** [6.57] 0.552*** [6.57] 0.576*** [6.53] 0.552*** [6.57]  lnL it (ii) (v) (iii) (i)
  46. 46. Sales Growth and HRM for Supermarket (City only) Dependent variable=  lnQ it 0.311 0.311 0.311 0.311 R-squared 1195 1195 1195 1195 N -0.047 [-0.67] TRAINING i 0.0069 [1.51] MEMBER i 2.26x10 -8 [0.29] STAKE i 0.151 [0.48] INVOLVE i -0.0002 [-0.29] 0.00003 [0.004] -0.0002 [-0.27] -0.0002 [-0.36] YEAROPENED i 1.165*** [5.90] 1.165*** [5.90] 1.165*** [5.90] 1.165*** [5.90]  MARKET it 0.292** [2.03] 0.292** [2.03] 0.292** [2.03] 0.292** [2.03]  lnL it (ii) (v) (iii) (i)
  47. 47. <ul><li>We also estimated a fully nested version of Eq. (3) with all four HPWP variables considered simultaneously. </li></ul><ul><li>The results turned out to be quite robust to the use of such a fully nested specification although the estimates are slightly less precise due to multicollinearily as expected. </li></ul>Insider econometrics evidence: additional analysis
  48. 48. <ul><li>RQ1: Is the legal structure important to explain firm productivity? </li></ul><ul><ul><li>H1: Cooperatives are more productive than others. </li></ul></ul><ul><li>Hypermarket stores with cooperative ownership grow sales significantly faster than do Gespa stores. </li></ul><ul><li>City supermarket: coop ownership stores are more productive than conventionally owned stores. </li></ul><ul><li>However for Center supermarkets we find that conventional owned stores grow faster than both coops and Gespa. </li></ul>Conclusions
  49. 49. <ul><li>RQ2: Which legal structure is nearest to the HPWS? </li></ul><ul><ul><li>H2: Cooperatives are more likely to perform as a HPWS </li></ul></ul><ul><li>Consistence with those who argue for the existence of powerful incentive mechanisms for coop members who work under institutional arrangements that differ from those facing workers in other firms: </li></ul><ul><ul><li>a large financial stake in the firm; </li></ul></ul><ul><ul><li>substantial employee involvement ; </li></ul></ul><ul><ul><li>unusual job security; </li></ul></ul><ul><ul><li>and working in firms with earnings differences that are substantially more compressed. </li></ul></ul>Conclusions
  50. 50. <ul><li>Thank you! </li></ul>

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