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Proceedings of the 3rd European Conference on Intellectual Capital

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Stelian Stancu and Anca Domnica Lupu<br />

Fur<str<strong>on</strong>g>the</str<strong>on</strong>g>r <strong>on</strong>,an envelopment model also informs about <str<strong>on</strong>g>the</str<strong>on</strong>g> reference counties for each analysed<br />

county.In table 3 it is shown , for each individual county, <str<strong>on</strong>g>the</str<strong>on</strong>g> county <str<strong>on</strong>g>the</str<strong>on</strong>g>y should be compared to,<br />

according to <str<strong>on</strong>g>the</str<strong>on</strong>g> size <str<strong>on</strong>g>of</str<strong>on</strong>g> <str<strong>on</strong>g>the</str<strong>on</strong>g> used inputs .<br />

Table 3. CRS and VRS input efficiency scores for 2009<br />

County Efficiency in CRS Efficiency in VRS Scale Type<br />

1 0.312 0.331 0.941 Irs<br />

2 1.000 1.000 1.000 -<br />

3 0.364 0.371 0.980 Irs<br />

4 0.605 0.605 0.999 -<br />

5 1.000 1.000 1.000 -<br />

6 0.936 1.000 0.936 Drs<br />

7 1.000 1.000 1.000 -<br />

8 0.138 1.000 0.136 Drs<br />

9 0.664 0.678 0.979 Irs<br />

10 1.000 1.000 1.000 -<br />

11 0.372 0.494 0.753 Drs<br />

12 0.090 0.094 0.954 Drs<br />

13 1.000 1.000 1.000 -<br />

14 1.000 1.000 1.000 -<br />

15 0.372 0.534 0.695 Drs<br />

16 0.502 0.695 0.722 Irs<br />

17 1.000 1.000 1.000 -<br />

18 0.870 1.000 0.870 Drs<br />

19 0.124 0.228 0.545 Irs<br />

20 1.000 1.000 1.000 -<br />

21 0.447 0.565 0.792 Drs<br />

22 0.244 0.244 0.999 -<br />

23 0.233 0.244 0.957 Drs<br />

24 0.331 0.436 0.759 Irs<br />

25 0.071 0.075 0.949 Drs<br />

26 0.142 0.153 0.926 Drs<br />

27 0.500 1.000 0.500 Drs<br />

Average 0.567 0.657 0.866<br />

B) DEA output oriented VRS model<br />

The same results have been obtained here also, but <str<strong>on</strong>g>the</str<strong>on</strong>g>re is no rule however regarding <str<strong>on</strong>g>the</str<strong>on</strong>g> dimensi<strong>on</strong><br />

<str<strong>on</strong>g>of</str<strong>on</strong>g> <str<strong>on</strong>g>the</str<strong>on</strong>g> scores, that is, <str<strong>on</strong>g>the</str<strong>on</strong>g>y should be higher/lower than in input oriented models.<br />

A close analysis reveals that no county has increasing outputs to scale.<br />

References<br />

Anders<strong>on</strong>, L.J., Boget<str<strong>on</strong>g>of</str<strong>on</strong>g>t, P., Frost, H., 2003, “The Applicati<strong>on</strong> Of Producti<strong>on</strong> Functi<strong>on</strong>s In Bioec<strong>on</strong>omic models”,<br />

Danish Research Institute <str<strong>on</strong>g>of</str<strong>on</strong>g> Food Ec<strong>on</strong>omics<br />

Brunnermeier, Markus K, Andrew Crockett, Charles A Goodhart, Avinash Persaud, and Hyun S<strong>on</strong>g Shin. 2009.<br />

“The Fundamental Principles <str<strong>on</strong>g>of</str<strong>on</strong>g> Financial Regulati<strong>on</strong>.” Geneva Reports <strong>on</strong> <str<strong>on</strong>g>the</str<strong>on</strong>g> World Ec<strong>on</strong>omy. Geneva:<br />

Internati<strong>on</strong>al Center for M<strong>on</strong>etary and Banking Studies.<br />

Calvo, Guillermo A. 2009. “Financial Crises and Liquidity Shocks: A Bank-run Perspective.” NBER Working<br />

Papers, Nati<strong>on</strong>al Bureau <str<strong>on</strong>g>of</str<strong>on</strong>g> Ec<strong>on</strong>omic Research, Cambridge, MA.<br />

Cambell, R., Rogers, K., Rezek, J., “Efficiency Fr<strong>on</strong>tier Estimati<strong>on</strong>: A Maximum Entropy Approach”, Department<br />

<str<strong>on</strong>g>of</str<strong>on</strong>g> Finance and Ec<strong>on</strong>omics Mississippi State University<br />

Casu, B., Girard<strong>on</strong>e, C., Molyneux , P., “Productivity Change In <str<strong>on</strong>g>European</str<strong>on</strong>g> Banking: A Comparis<strong>on</strong> Of Parametric<br />

a N<strong>on</strong>-Parametric Approaches”, Essex Finance Centre, University <str<strong>on</strong>g>of</str<strong>on</strong>g> Essex, 6-8<br />

607

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