The current paper has applied the MDDF to compute and compare production efficiencies of banks in 17 CEE countries, in which the banking industry of each country is assumed to have potential access to the same technology, but each bank chooses to operate on a different part of technology frontier. The directional distance function appears to be a better choice for estimating banking efficiency, since it allows for gauging a bank’s efficiency from the orientations of inputs, outputs, and undesirables at the same time. As the undesirables - loan loss reserves - are jointly produced with some desirables - various loans - and the disposal of the undesirables requires the use of resources and adversely affects the production of desirables, it is suggested that researchers include the undesirables in their econometric models in order to appropriately characterize a bank’s production process, as well as to correctly measure its technical efficiency. Moreover, the employment of the MDDF enables the technology gap to be evaluated for banks under different technologies relative to the potential technology available to the industry as a whole in the framework of the
19
stochastic frontier approach, as opposed to the programming technique proposed by Battese et al. (2004). One of the advantages of our MDDF is that the technology gap can be further related to a group of environmental variables, which is infeasible in the context of programming techniques.
Evidence is found to verify that the banking industries of the 17 CEE countries do indeed adopt different technologies. This justifies the validity of the MDDF in the comparison of technical efficiencies among groups. Some of the environmental variables are found to have significant impacts on the group frontiers and the metafrontier, confirming the usefulness of the stochastic metafrontier model.
Our empirical study shows that the average TGDs substantially vary across countries and exceed average technical inefficiency scores in most countries, while those mean TGDs present no clear trend during the sample period. Bank managers should promote their production technology by quickly responding to financial innovations in such a way as to shift their group frontiers closer to the metafrontier.
As the average technical inefficiency score is relatively small to the average TGD of the same country, managerial inability appears to be less of an issue.
The production of undesirables is almost inevitable in many industries, such as manufacturing and banking sectors, and it requires the disposing of consuming resources. The exclusion of undesirables from the model is apt to mislead the subsequent results. Therefore, using the directional distance function by the current paper is more preferable. This is confirmed in Subsection 5.4, where the model ignoring the undesirables tends to underestimate the technical inefficiency scores.
For future research studies, our MDDF can be extended to measure and compare productivity change for banks in different countries under the framework of the Luenberger productivity indicator. Since these indicators of different groups are evaluated relative to the same metafrontier, they are comparable and able to provide
20
insightful information, or more specifically, whether productivity change is driven by technical efficiency change or technological change has different implications to managers, business consultants, and regulatory authorities.
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Table 1. Average group-specific technical inefficiency over time
1995 1996 1997 1998 1999 2000 2001 2002
Bosnia (BA) NA 1.50 0.74 1.28 1.10 1.16 1.23 0.90
Bulgaria (BG) 0.95 0.86 2.07 1.30 1.37 1.66 1.52 0.91
Czech (CZ) 1.39 10.04 1.97 6.25 5.77 2.97 1.97 2.88
Estonia (EE) 0.96 1.48 0.82 1.01 0.70 1.01 0.47 0.71
Croatia (HR) 2.44 1.57 1.27 1.27 2.32 2.03 1.98 1.93
Hungary (HU) 3.75 2.71 2.21 1.94 1.53 1.41 1.08 0.70
Lithuania (LT) 0.83 1.60 1.12 1.22 1.40 0.80 1.01 0.80
Latvia (LV) 1.73 1.24 0.89 2.41 2.20 1.27 1.35 1.41
Moldova (MD) 2.71 2.82 2.58 2.83 2.54 2.61 2.49 2.75
Macedonia (MK) 0.58 0.26 0.15 0.34 0.31 0.35 0.44 0.27
Poland (PL) 1.57 1.06 2.79 2.98 3.39 3.83 8.44 18.00
Romania (RO) 29.08 11.37 0.51 0.96 9.48 2.79 5.17 4.38
Serbia (RS) 1.28 1.92 2.21 1.43 3.02 2.54 2.99 2.30
Russia (RU) 19.36 15.01 18.63 10.46 5.49 6.33 5.19 4.61
Slovenia (SI) 5.04 2.46 2.54 1.95 2.38 3.04 9.64 5.04
Slovakia (SK) 1.03 3.98 2.70 3.01 0.83 0.67 2.89 1.18
Ukraine (UA) 0.88 0.90 0.45 0.48 0.48 1.84 1.47 1.27
2003 2004 2005 2006 2007 2008 Mean
Bosnia (BA) 1.31 1.47 1.43 1.48 1.25 1.21 1.24
Bulgaria (BG) 0.61 1.99 1.73 2.03 1.62 1.59 1.53
Czech (CZ) 3.17 1.80 1.70 1.31 1.05 1.68 2.90
Estonia (EE) 1.28 0.37 1.03 0.75 0.12 2.79 0.97
Croatia (HR) 1.52 1.84 2.62 3.08 1.98 2.23 1.98
27
Table 2. Parameter estimates of the MDDF
Variables Parameter
28
likelihood -0.3292E+05 ty1 1.55E-02
(8.68E-04)***
Table 3. Average TGD over time and various inefficiency estimates across countries
Year TGD Country TGD Group-specific
Ineff.
29
Figure 2. The trend of average TGD measures Figure 1. Metafrontier directional distance function
30
Figure 3. Scatter diagram
BA BG
CZ
EE HRHU LT
LV MD
MK
PL
RO RS
RU SI SK UA
0 2 4 6 8 10 12 14 16 18
0 1 2 3 4 5 6 7
TGD
group-specific technical inefficiency
31
國科會補助專題研究計畫成果報告自評表
請就研究內容與原計畫相符程度、達成預期目標情況、研究成果之學術或應用價
值（簡要敘述成果所代表之意義、價值、影響或進一步發展之可能性） 、是否適
合在學術期刊發表或申請專利、主要發現或其他有關價值等，作一綜合評估。
1. 請就研究內容與原計畫相符程度、達成預期目標情況作一綜合評估
□ 5 達成目標
□ 未達成目標（請說明，以 100 字為限）
□ 實驗失敗
□ 因故實驗中斷
□ 其他原因 說明：
本結案報告內容，與原計畫內容完全相符，且達成預期目標。例如，
(i) 為凸顯考慮非意欲產出的重要性，同時估計有無非意欲產出的方向距離函數，進而 衡量和比較效率估計值的差異。
(ii) 使用 Bankscope 資料庫，收集中、東歐各國銀行業縱橫資料，樣本銀行家數高達 1466，
總樣本數為6770 筆。
(iii) 採用兩個階段估計步驟，第一階段運用 SFA 模型個別估計每個國家的群組邊界，得 到迴歸係數與技術效率估計值。第二階段合併所有國家樣本資料以及迴歸係數估計
值，仍然使用SFA 模型得到共同邊界函數的估計值，從而可以計算技術缺口比率，
做為計算和比較各國銀行業生產效率的依據。此時，技術缺口比率可與表為環境變 數的函數，探討兩者間之關係。
32
2. 研究成果在學術期刊發表或申請專利等情形：
論文：□已發表 5 未發表之文稿 □撰寫中 □無 專利：□已獲得 □申請中 □無
技轉：□已技轉 □洽談中 □無 其他：（以 100 字為限）
3. 請依學術成就、技術創新、社會影響等方面，評估研究成果之學術或應用價 值（簡要敘述成果所代表之意義、價值、影響或進一步發展之可能性）（以 500 字為限）
過去探討跨國間銀行業效率與生產力的實證研究，一者假設各國銀行廠商的生產技術相 同，將各國銀行資料合併後進行估計，此做法忽略不同國家間之差異；或者雖假設各國銀行 採用不同生產技術，但未能在相同基礎上進行比較。Battese et al. (2004) 提出的共同生產函數 雖然成功的解決上述問題，但是，在第二階段使用數理規劃法，造成前後兩階段方法不一致。
本研究針對第二階段從事改良，建構共同邊界隨機方向距離函數，使得前後兩階段方法趨於 一致，技術缺口比率也可與環境變數連結，進一步探討影響技術缺口比率的因素有哪些。方 向距離函數另一項優點，可將非意欲產出—不良放款--納入模型中，較能更正確反映銀行業實 況。
針對中、東歐各國商業銀行近十四年的縱橫資料 (panel data)，深入分析和比較這各國銀 行業生產效率。發現距離函數中若忽略環境變數，易造成低估技術效率和技術缺口比率。另 外，迴歸模型中若忽略非意欲產出，也導致效率值的低估。如此，可以深入了解中、東歐各 國商業銀行歷經民主化與自由化的洗禮，它們的生產效率是否有所提升，做為我國政府擬訂 相關政策時的參考。
本研究之成果具有實證應用價值，經改寫後可投稿至國外學術性期刊，具有發表之潛力。
101 8 8
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( ) An Evaluation of Technical Efficiencies for the Top 100 Public
Accounting Firms in China Using Input Distance Functions
APPC2010
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From: APPC 2012 <[email protected]>
To: [email protected]
Date: Sun, 08 Apr 2012 17:41:13 +0100 Subject: Acceptance for oral presentation
Dear colleague,
I am pleased to inform you that your abstract "An Evaluation of Technical Efficiencies for the Top 100 Public Accounting Firms in China Using Input Distance Functions", reference 0144 has been accepted as an oral presentation at APPC 2012.
Guidelines for presentations will shortly be posted on the conference website. Please register for the conference to confirm your participation. Registration must be done online through the link on the conference website. May we remind you that early registration deadline is on May 31, 2012 while regular registration deadline is on June 22, 2012. Payment information will shortly be posted on the conference website. In addition, please book your accommodation immediately to reserve the room and special price. Booking form and instruction are available on the conference website.
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An Evaluation of Technical Efficiencies for the Top 100 Public Accounting Firms in China Using Input Distance Functions
Tai-Hsin Huang
*Bao-Guang Chang
**Hsiu-Mei Wang
***Abstract: This paper investigates the effect from a policy that expands a public accounting firm’s
size, enforced by China’s government, on firms’ technical efficiency and economies of scale. We apply and estimate a standard input distance frontier using data on the top 100 Chinese accounting firms covering 2008-2009. We find that the larger the firm size is, the more technically efficient it is, thus justifying policy enforcement. Economies of scale prevail in the top 100 accounting firms and are not exhausted, supporting that these firms keep extending their production scale to reduce their long-run average costs. Those sample firms experiencing a merger and acquisition (M&A) do not outperform firms without any merger and acquisition in terms of technical efficiency scores, possibly resulting from the short sample period, such that the beneficial effects from M&A have not been taken into account yet.
Key words: Chinese public accounting firms; input distance function; technical
efficiency; returns to scale;
* Professor, Department of Money and Banking, National Chengchi University
**
無研發成果推廣資料
100 年度專題研究計畫研究成果彙整表
其他成果
(
無法以量化表達之成果如辦理學術活動、獲 得獎項、重要國際合 作、研究成果國際影響 力及其他協助產業技 術發展之具體效益事 項等，請以文字敘述填 列。)
無
成果項目 量化 名稱或內容性質簡述
測驗工具(含質性與量性) 0
課程/模組 0
電腦及網路系統或工具 0
教材 0
舉辦之活動/競賽 0
研討會/工作坊 0
電子報、網站 0
科 教 處 計 畫 加 填 項
目 計畫成果推廣之參與（閱聽）人數 0
國科會補助專題研究計畫成果報告自評表
請就研究內容與原計畫相符程度、達成預期目標情況、研究成果之學術或應用價
值（簡要敘述成果所代表之意義、價值、影響或進一步發展之可能性） 、是否適
合在學術期刊發表或申請專利、主要發現或其他有關價值等，作一綜合評估。
1. 請就研究內容與原計畫相符程度、達成預期目標情況作一綜合評估
■達成目標
□未達成目標（請說明，以 100 字為限）
□實驗失敗
□因故實驗中斷
□其他原因 說明：
2. 研究成果在學術期刊發表或申請專利等情形：
論文：□已發表 ■未發表之文稿 □撰寫中 □無 專利：□已獲得 □申請中 ■無
技轉：□已技轉 □洽談中 ■無 其他：（以 100 字為限）
3. 請依學術成就、技術創新、社會影響等方面，評估研究成果之學術或應用價 值（簡要敘述成果所代表之意義、價值、影響或進一步發展之可能性）（以 500 字為限）
過去探討跨國間銀行業效率與生產力的實證研究，一者假設各國銀行廠商的生產技術相 同，將各國銀行資料合併後進行估計，此做法忽略不同國家間之差異；或者雖假設各國銀 行採用不同生產技術，但未能在相同基礎上進行比較。Battese et al. (2004) 提出的共 同生產函數雖然成功的解決上述問題，但是，在第二階段使用數理規劃法，造成前後兩階 段方法不一致。本研究針對第二階段從事改良，建構共同邊界隨機方向距離函數，使得前 後兩階段方法趨於一致，技術缺口比率也可與環境變數連結，進一步探討影響技術缺口比 率的因素有哪些。方向距離函數另一項優點，可將非意欲產出—不良放款--納入模型中，
較能更正確反映銀行業實況。
針對中、東歐各國商業銀行近十四年的縱橫資料 (panel data)，深入分析和比較這各國 銀行業生產效率。發現距離函數中若忽略環境變數，易造成低估技術效率和技術缺口比 率。另外，迴歸模型中若忽略非意欲產出，也導致效率值的低估。如此，可以深入了解中、
東歐各國商業銀行歷經民主化與自由化的洗禮，它們的生產效率是否有所提升，做為我國 政府擬訂相關政策時的參考。
本研究之成果具有實證應用價值，經改寫後可投稿至國外學術性期刊，具有發表之潛力。