Using the newly developed formulae, this paper aims to gain further insights on the productivity growth of West European banking industries during the period 1993-2006 and to broaden our capacity in identifying various components of
productivity growth. Most importantly, these components can provide useful information to managers, industry consultants, and regulators to assess performance and to adjust business strategy and enforce new regulation policy. The empirical application reveals that a representative bank in West Europe sustains a positive productivity growth during the sample period when the financial markets become more competitive and integrated after the creation of a single market for financial services in 1993. The productivity gains are chiefly stimulated by scale efficiency change, justifying the significance of the scale effect in the evaluation of a bank’s productivity change. Overlooking the role played by the scale effect is likely to result in an underestimation for the measure of productivity change.
Banks in nine out of the fifteen countries are confronted with productivity growth and scale efficiency gains and technical progress prevail in the vast majority of the sample states. However, the data failed to identify the prevalence of positive technical efficiency change in most of the countries under consideration. Larger banks seemed to grow faster than smaller ones, due to technological advance and the enhancement of production scale, rather than efficiency change. Finally, a bank with a higher value of ETA is inclined to grow faster than a bank with a lower value of ETA.
This may be ascribable to the fact that risk-averse bank managers are frequently engaging in monitoring and supervising activities that help reduce the exposure of risks.
22
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Figure 1. Trends in gMMPI and MTRC components
Figure 2. Trends in gMMPI
Figure 3. Trends in gMMPI and MTRC components by ETA class
28
Trends in gMMPI and MTRC components
Trends in gMMPI and MTRC components by asset size class
Trends in gMMPI and MTRC components by ETA class Trends in gMMPI and MTRC components
and MTRC components by asset size class
Trends in gMMPI and MTRC components by ETA class
Table 1. Descriptive statistics
AUS BEL DNK FIN FRA DEU ITA LUX NLD NOR PRT ESP SWE CHE GBR
Number of banks 146 77 97 11 280 876 106 138 22 113 17 49 101 498 42
Number of observations 1235 632 1132 81 2496 9640 690 1279 121 557 109 342 609 3435 269
Labor (total assets net 2613 14068 2652 12975 13494 4934 7689 5576 1629 3588 8406 7294 6845 3868 1783 fixed assets) (8788 (48850 (16737 (16059 (64075 (39664 (17619 (9682 (2076 (12398 (12102 (18369 (22281 (45107 (2580)
Physical capital 21 69 22 91 51 31 124 18 4 26 135 131 32 31 13
(43) (195) (97) (150) (243) (97) (272) (45) (9) (82) (189) (356) (175) (259) (34) Borrowed funds 2430 12707 2216 11556 11070 4504 6620 4772 1460 3223 7643 6550 5655 3188 1366 (8192 (43001 (13600 (14398 (48257 (33413 (15209 (8227 (1859 (11066 (10890 (16553 (18257 (36506 (1884) Loans 2080 8706 1234 8763 8880 3459 5605 3927 1038 2987 6244 5245 4635 2526 1238 (7022 (30089 (6944) (11540 (37557 (24202 (13200 (7002 (1063 (10162 (8919) (12680 (14783 (26426 (1675) Investments 441 4429 1182 3109 3112 1175 1503 1442 481 408 1377 1582 1589 896 328 Notes: All inputs and outputs are expressed in millions of real US dollars with base year 2000. Standard deviations are in parentheses.
30
Table 2. Summary statistics of the various gMMPI components over time
Period gMMPI TEC* TC* SEC* MMPI TEC TC SEC RSEC MTRC CUT PTC
1994 1.0076 1.0051 1.0010 1.0015 1.0061 1.0093 0.9965 1.0003 1.0012 1.0009 0.9964 1.0047 1995 1.0044 1.0017 1.0013 1.0014 1.0031 1.0054 0.9973 1.0003 1.0011 1.0008 0.9967 1.0042 1996 1.0022 1.0014 1.0015 0.9993 1.0029 1.0036 0.9978 0.9997 0.9996 1.0020 0.9983 1.0037 1997 1.0045 1.0042 1.0014 0.9989 1.0056 1.0057 0.9982 0.9994 0.9998 1.0025 0.9992 1.0033 1998 1.0001 0.9974 1.0011 1.0017 0.9985 1.0030 0.9988 1.0006 1.0012 0.9990 0.9967 1.0024 1999 1.0032 1.0028 1.0012 0.9992 1.0040 0.9992 0.9993 1.0003 0.9991 1.0062 1.0043 1.0020 2000 1.0039 1.0033 1.0010 0.9997 1.0042 1.0032 0.9993 0.9998 0.9999 1.0025 1.0008 1.0018 2001 0.9950 0.9945 1.0006 0.9999 0.9951 0.9983 0.9995 1.0001 0.9998 0.9999 0.9988 1.0012 2002 1.0019 0.9983 1.0002 1.0035 0.9984 1.0011 0.9988 1.0006 1.0030 1.0000 0.9987 1.0014 2003 1.0001 0.9967 0.9997 1.0038 0.9964 1.0049 0.9985 1.0004 1.0036 0.9938 0.9926 1.0013 2004 1.0032 1.0010 0.9996 1.0026 1.0006 1.0037 0.9985 1.0000 1.0026 0.9995 0.9983 1.0013 2005 0.9993 1.0021 0.9993 0.9980 1.0013 1.0062 0.9977 0.9999 0.9981 0.9991 0.9975 1.0017 2006 1.0024 0.9997 0.9992 1.0036 0.9988 1.0049 0.9977 1.0006 1.0032 0.9989 0.9973 1.0016 93-98 1.0038 1.0020 1.0013 1.0006 1.0032 1.0054 0.9977 1.0001 1.0006 1.0010 0.9975 1.0036 98-03 1.0008 0.9991 1.0005 1.0012 0.9996 1.0013 0.9991 1.0003 1.0011 1.0005 0.9990 1.0015 03-06 1.0016 1.0009 0.9994 1.0014 1.0002 1.0049 0.9980 1.0002 1.0013 0.9992 0.9977 1.0015 Average 1.0021 1.0006 1.0005 1.0010 1.0011 1.0037 0.9983 1.0002 1.0009 1.0004 0.9981 1.0023
Table 3. Summary statistics of the various gMMPI components across country
Rank Country gMMPI TEC* TC* SEC* MMPI TEC TC SEC RSEC MTRC CUT PTC
1 Belgium 1.0105 1.0056 1.0046 1.0003 1.0103 1.0239 0.9836 1.0009 0.9998 1.0067 0.9853 1.0219 2 Sweden 1.0099 1.0106 0.9978 1.0016 1.0083 1.0235 0.9779 1.0001 1.0016 1.0086 0.9881 1.0208 3 United Kingdom 1.0099 1.0083 1.0007 1.0009 1.0090 1.0002 1.0055 1.0006 1.0009 1.0048 1.0096 0.9953 4 Demark 1.0080 1.0047 1.0032 0.9999 1.0079 0.9993 1.0031 1.0004 0.9995 1.0082 1.0081 1.0001 5 France 1.0043 1.0032 0.9999 1.0012 1.0031 1.0173 0.9883 1.0004 1.0009 1.0000 0.9885 1.0117 6 Germany 1.0021 0.9995 1.0020 1.0006 1.0015 1.0019 0.9999 1.0001 1.0005 0.9999 0.9979 1.0020 7 Austria 1.0011 1.0002 1.0000 1.0008 1.0003 0.9994 1.0030 0.9996 1.0012 1.0036 1.0066 0.9971 8 Luxembourg 1.0010 0.9993 1.0005 1.0013 0.9998 0.9968 1.0024 1.0004 1.0009 1.0010 1.0029 0.9982 9 Finland 1.0007 0.9950 1.0036 1.0021 0.9986 1.0013 0.9942 0.9991 1.0030 1.0031 0.9936 1.0097 10 Netherlands 0.9987 0.9942 1.0024 1.0020 0.9966 1.0102 1.0006 0.9924 1.0130 0.9954 0.9934 1.0022 11 Italy 0.9984 0.9966 1.0016 1.0002 0.9982 0.9786 1.0169 1.0006 1.0010 1.0066 1.0214 0.9854 12 Norway 0.9982 0.9968 0.9986 1.0029 0.9954 1.0019 0.9990 1.0001 1.0028 0.9947 0.9950 0.9997 13 Switzerland 0.9981 1.0005 0.9956 1.0020 0.9961 1.0050 0.9952 1.0002 1.0018 0.9963 0.9959 1.0004 14 Portugal 0.9944 0.9891 1.0013 1.0046 0.9903 1.0144 1.0033 0.9978 1.0071 0.9756 0.9767 0.9987 15 Spain 0.9944 0.9930 1.0002 1.0011 0.9933 0.9789 1.0239 0.9995 1.0017 0.9926 1.0161 0.9775 Average 1.0021 1.0006 1.0005 1.0010 1.0011 1.0037 0.9983 1.0002 1.0009 1.0004 0.9981 1.0023
32
Table 4. Summary statistics of the various gMMPI components by asset sizes and the ratio of equity to total assets
Class Obs. gMMPI TEC* TC* SEC* MMPI TEC TC SEC RSEC MTRC CUT PTC
Panel A. Total Assets
size1 below 100 1,479 1.0049 1.0066 0.9985 0.9999 1.0050 1.0076 0.9976 1.0002 0.9998 1.0043 1.0034 1.0009 size2 100-200 2,081 1.0025 1.0044 0.9973 1.0009 1.0017 1.0061 0.9972 1.0000 1.0009 0.9992 0.9991 1.0002 size3 200-400 2,775 1.0019 1.0028 0.9983 1.0007 1.0012 1.0026 0.9983 1.0003 1.0006 1.0009 1.0009 1.0001 size4 400-1000 4,600 1.0015 1.0005 1.0005 1.0005 1.0010 1.0031 0.9987 1.0001 1.0005 1.0007 0.9988 1.0019 size5 1,000-3,000 4,879 1.0014 0.9989 1.0016 1.0010 1.0004 1.0014 0.9989 1.0003 1.0008 1.0011 0.9984 1.0027 size6 3,000-5,000 1,302 1.0009 0.9974 1.0021 1.0015 0.9995 1.0053 0.9984 0.9999 1.0015 0.9963 0.9926 1.0038 size7 5,000-10,000 1,255 1.0034 0.9986 1.0028 1.0021 1.0013 1.0061 0.9973 1.0002 1.0019 0.9997 0.9942 1.0057 size8 above 10,000 1,399 1.0036 0.9953 1.0050 1.0034 1.0003 1.0043 0.9981 0.9999 1.0034 0.9980 0.9912 1.0071
Panel B. ETA (%)
ETA1 below 3 2,004 1.0011 1.0000 0.9984 1.0028 0.9984 1.0044 0.9963 1.0002 1.0026 0.9984 0.9964 1.0022 ETA2 3-4 3,046 1.0025 1.0001 1.0013 1.0011 1.0014 1.0047 0.9988 1.0001 1.0010 0.9984 0.9959 1.0026 ETA3 4-5 3,952 1.0009 0.9985 1.0016 1.0009 1.0000 1.0020 0.9987 1.0001 1.0009 0.9999 0.9971 1.0029 ETA4 5-7 4,097 1.0012 0.9995 1.0006 1.0011 1.0001 1.0028 0.9983 1.0003 1.0009 1.0000 0.9977 1.0024 ETA5 7-12 3,357 1.0012 1.0008 0.9994 1.0010 1.0002 1.0028 0.9981 1.0002 1.0008 1.0007 0.9994 1.0015 ETA6 12-15 1,050 1.0038 1.0037 0.9997 1.0004 1.0034 1.0048 0.9977 1.0001 1.0003 1.0029 1.0009 1.0022 ETA7 15-20 1,031 1.0041 1.0039 1.0005 0.9998 1.0044 1.0046 0.9970 1.0001 0.9997 1.0034 0.9998 1.0038 ETA8 above 20 1,233 1.0085 1.0070 1.0020 0.9996 1.0089 1.0093 1.0012 1.0002 1.0005 1.0053 1.0042 1.0011 Notes: The values of total assets are measured in millions of US dollars to save space.
1.
100
(i)
(ii) Bankscope 2573
22627
(iii) SFA
34
2.
□ □ □
□ □ □
□ □ □ 100
3.
500
(panel data)
SFA Battese and Coelli (1995)
Orea (2002)
國科會補助計畫衍生研發成果推廣資料表
日期:2011/08/27
國科會補助計畫
計畫名稱: 應用一般化共同邊界麥氏生產力指數探討銀行業生產力變動 計畫主持人: 黃台心
計畫編號: 99-2410-H-004-054- 學門領域: 財務與金融
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99 年度專題研究計畫研究成果彙整表
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