Productividad del sector de Sociedades de Garantía Recíproca en España

1. Productivity of Mutual Guarantee Societies in Spain Fernando Gascón Universidad de Oviedo Luís Carlos Sánchez Asturgar, SGR ACEDE Tenerife, Septiembre 2005

2. Objective Assess how recent regulatory and organizational changes have affected the productive activity of the Spanish mutual guarantee system Characteristics of Mutual Guarantee activities Banking firms deny credit to many new start-ups and small business because of a lack of a backing guarantee  high risk without collateral It is socially desirable to finance some of these new firms even if the information regarding their expected bankruptcy rate is opaque  screening costs versus externalities Local, regional and national Governments are interested in giving incentives for firms with potential for creating positive externalities  Job creation and higher economic activity Most Spanish MGS do not compete geographically  Two non-competing hypothesis Non-for-profit and conflicting interests  Three alternative views of MGS

3. Table 1a – Description of the mutual guarantee system 2.2% 60,647 Riesgo vivo dudoso no reavalado 0.9% 25,610 Ingresos por avales 4.9% 134,435 Riesgo vivo dudoso 0.3% 8,840 Gastos explotación 11.2% 310,327 Recursos propios 0.5% 14,753 Gastos personal 100.0% 2,759,123 Riesgo vivo Total Year 2004 (‘000 €)

4. Table 1b – Descriptive Statistics Returns to scale of MGS  Soft info processing versus other arguments Input Input 18,220 0 4,640 2,888 Riesgo vivo dudoso no reavalado Input 7,776 148 1,762 1,220 Ingresos por avales Input 38,504 0 10,914 6,402 Riesgo vivo dudoso Input 2,624 73 555 421 Gastos explotación Output 64,394 2,718 17,638 14,777 Recursos propios Output Input 3,146 70 794 703 Gastos personal Output Output Output 767,824 15,426 191,535 131,387 Riesgo vivo Management Model Entrepreneur Model Technical Model Max Min S. Deviation Average Year 2004 (‘000 Euros)

5. M CCD Efficiency change (  E i t.t+1 ) Technological change (  T CCR.i t.t+1 ) Pure Technical Efficiency change (  PE i t.t+1 ) Scale Efficiency change (  SE i t.t+1 ) Technical change (BCC Frontier) (  T BCC.i t.t+1 ) Scale change (  S i t.t+1 )

6. Malmquist Productivity index decompositions Always possible M CCD =  E i t.t+1   T CCR.i t.t+1 Always possible M CCD = =  PE i t.t+1   SE i t.t+1   T CCR.i t.t+1 Not always possible M CCD = =  PE i t.t+1   SE i t.t+1   T BCC.i t.t+1   S i t.t+1

7. Graph - Distance computations over four frontiers

8. Graph b - M CCD Malmquist index We also need to compute

9. Graph c -  PE i t.t+1 Pure efficiency change

10. Graph d -  SE i t.t+1 Scale efficiency change

11. Graph e -  T BCC.i t.t+1 Technical change BCC frontier

12. Graph f -  S i t.t+1 Residual (technology) scale change

13. Table 2 – CRS and VRS efficiency in 1999 and 2004 (Technical Model) 79.9% 76.0% 75.0% 68.1% Arithmetic mean 98.7% 98.3% T2004_21 65.4% 60.8% T99_21 OINARRI 100.0% 100.0% T2004_20 100.0% 95.6% T99_20 EXTRAVAL 96.5% 95.3% T2004_19 100.0% 100.0% T99_19 FIANZAS 61.5% 59.7% T2004_18 20.3% 20.1% T99_18 SOGAPYME 100.0% 100.0% T2004_17 79.0% 79.0% T99_17 ARAVAL 76.0% 74.1% T2004_16 54.2% 52.8% T99_16 SURAVAL 100.0% 100.0% T2004_15 66.9% 65.9% T99_15 AVALUNION 77.9% 77.7% T2004_14 70.5% 69.0% T99_14 AFIGAL 100.0% 79.6% T2004_13 100.0% 68.6% T99_13 ASTURGAR 100.0% 74.1% T2004_12 82.9% 73.6% T99_12 TRANSAVAL 100.0% 100.0% T2004_11 75.9% 68.9% T99_11 UNDEMUR 57.4% 55.9% T2004_10 55.5% 51.7% T99_10 SOGARTE 33.5% 32.8% T2004_09 25.2% 22.2% T99_09 CREDIAVAL 60.8% 60.3% T2004_08 71.5% 63.2% T99_08 SOGARPO 41.0% 34.8% T2004_07 80.0% 67.5% T99_07 AVALMADRID 78.8% 78.1% T2004_06 100.0% 70.5% T99_06 IBERAVAL 50.6% 39.2% T2004_05 33.1% 31.0% T99_05 SOGARCA 100.0% 100.0% T2004_04 100.0% 100.0% T99_04 VALENCIA 100.0% 100.0% T2004_03 100.0% 100.0% T99_03 SONAGAR 90.4% 81.3% T2004_02 94.3% 68.8% T99_02 ELKARGI 55.7% 55.4% T2004_01 100.0% 100.0% T99_01 ISBA VRS CRS DMU VRS CRS DMU SGR

14. Table 3 – Malmquist Productivity changes (Technical model) 0.9828 1.1041 1.0091 1.0424 1.1414 Geometric mean 2003-2004 1.0450 1.1875 1.0389 1.1038 1.4230 Means multiplied 1999-2004 1.0080 1.1332 0.9863 1.0121 1.1402 Geometric mean 2002-2003 0.9543 0.9802 1.0305 0.9797 0.9443 Geometric mean 2001-2002 1.0048 1.0630 1.0253 1.0027 1.0981 Geometric mean 2000-2001 1.1001 0.9109 0.9879 1.0650 1.0544 Geometric mean 1999-2000  S t.t+1  T BCC t.t+1  S E t.t+1  PE t.t+1 M CCD Measure type Technical Model

15. Table 4 – Malmquist Productivity changes (Manager model) 3.9916 1.0945 0.2494 0.9499 1.0350 Geometric mean 2003-2004 10.5125 1.0765 0.1058 1.0943 1.3106 Means multiplied 1999-2004 1.0774 1.0864 0.9316 0.9550 1.0414 Geometric mean 2002-2003 0.9051 0.9750 1.1268 1.0564 1.0504 Geometric mean 2001-2002 0.7404 0.9773 1.3995 1.0445 1.0576 Geometric mean 2000-2001 3.6480 0.9501 0.2888 1.0932 1.0945 Geometric mean 1999-2000  S t.t+1  T BCC t.t+1  S E t.t+1  PE t.t+1 M CCD Measure type Technical Model

16. Table 5 – Malmquist Productivity changes (Entrepreneur model) 0.9200 0.9763 1.0889 1.0412 1.0183 Geometric mean 2003-2004 1.0410 1.0745 0.9907 0.9020 0.9995 Means multiplied 1999-2004 1.1343 1.1345 0.8427 0.9332 1.0120 Geometric mean 2002-2003 0.8872 0.9220 1.1277 1.0215 0.9423 Geometric mean 2001-2002 1.0489 1.0551 0.9653 0.9610 1.0266 Geometric mean 2000-2001 1.0720 0.9973 0.9917 0.9456 1.0026 Geometric mean 1999-2000  S t.t+1  T BCC t.t+1  S E t.t+1  PE t.t+1 M CCD Measure type Technical Model

17. Conclusions This paper has estimated the sources of productivity change in the Spanish Mutual Guarantee System between 1999 and 2004. Three alternative models were considered that reflect the technical side of MGS, managers own interests and the entrepreneur side of MGS. Results show a notable improvement of 42.30% productivity growth in the technical side indicating that MGS are now better managed Results show an improvement of 31.06% in the managerial side indicating that managers are successful in pursuing their own objectives Results show an apparent lack of productivity change in the entrepreneur side indicating that there are, on average, similar conditions for firms demanding guarantees over the 1999-2004 period. Although total factor productivity results are interesting by themselves, the Malmquist decomposition of the productivity change that we have computed for each of the three models that we have considered in this paper allows for further insights .

18. Productivity of Mutual Guarantee Societies in Spain Fernando Gascón Universidad de Oviedo Luís Carlos Sánchez Asturgar, SGR ACEDE Tenerife, Septiembre 2005