Please use this identifier to cite or link to this item: https://ah.nccu.edu.tw/handle/140.119/139547


Title: 利用網絡DEA與網絡SFA探討企業社會責任對於銀行效率之影響
The effect of corporate social responsibility on bank performances: an application of network data envelopment analysis and network stochastic frontier analysis
Authors: 胡聚男
Hu, Chu-Nan
Contributors: 黃台心
Huang, Tai-Hsin
胡聚男
Hu, Chu-Nan
Keywords: 企業社會責任
共用生產要素
網絡DEA
網絡SFA
環境變數
截斷迴歸模型
關聯結構
成本吝嗇假說
Corporate social responsibility
Shared inputs
Network DEA
Network SFA
Environmental variables
Truncated regression model
Copula
Cost skimping hypothesis
Date: 2020
Issue Date: 2022-04-01 15:01:47 (UTC+8)
Abstract: 本文將銀行生產過程分成兩個階段,此架構更能反映在存款與企業社會責任
扮演中間產出的角色。第一階段利用部分勞工與資本設備生產存款與企業社會責任;第二階段是銀行獲利階段,利用剩餘的勞工與資本設備,搭配上階段的中間產出--存款與企業社會責任,製造放款、投資與非利息收入等三種最終產出。由於勞工與資本拆成兩個階段使用,故須利用共用生產要素之網絡 DEA 與網絡SFA 兩種模型評估銀行效率,並在控制銀行體質與各國文化等環境變數下,探討企業社會責任對於銀行效率的影響。

值得一提者,在網絡 DEA 模型下,本文使用兩步驟法 (two-step approach),在第二步驟採用截斷迴歸模型 (truncated regression model) 估計環境變數對效率之影響,而非文獻上常用之 Tobit 模型,並使用 Simar and Wilson (2007) 提出的兩種演算法調整截斷迴歸模型估計標準誤存在偏誤的問題;另在在網絡 SFA 下,本文則延伸 Huang et al. (2017) 的架構,將環境變數納入成本函數中,加入產出面距離函數以及兩條成本份額方程式,共計四條聯立估計。由於納入環境變數,使得本文網絡 SFA 運用關聯結構法推導的概似函數型態相當複雜,實證估計時
面臨極大挑戰。

有關樣本銀行投入和產出資料,主要綜整自 BankScope 與 Orbis Bank Focus資料庫,蒐集 2003-2014 年間跨國 187 家銀行的相關數據以及 CAMEL 指標。至於企業社會責任資料則取自於 EIRIS 資料庫,並細分為員工、社區、環境、公司治理、利益攸關人、賄賂與 ESG 傳遞等七個面向。此外,本文研究主題為跨國的銀行效率比較,故採用 Hofstede et al. (1991, 2010) 建構的文化指標以控制國家異質性,包含個人主義、長期關係傾向、對不確定性趨避程度以及權力距離等四個面向。

網絡 DEA 與網絡 SFA 模型的實證結果,在多個面向上相當類似,與環境相關企業社會責任對於銀行效率有正面影響,可能因為銀行越重視「環境」議題,有助於銀行推出綠色產品,例如綠色放款、綠色債券,或藉由綠色存款取得較成本的資金來源,因此環境是銀行從事策略性企業社會責任的關鍵。然而,當銀行從事與「員工」或「社區」相關的企業社會責任議題時,可能降低銀行效率,顯示這類活動可能比較偏向利他行為。值得注意者,當銀行管理階層傳達 ESG 風險與機會越全面時,其「ESG 傳遞」面向分數越高,但在網絡 SFA 與網絡 DEA會得到相反的結果。本研究認為網絡 SFA 將要素價格納入第二階段的成本函數中,網絡 DEA 僅從生產函數角度使用投入和產出變數進行效率評估,忽略要素價格,故網絡 SFA 的估計結果應較網絡 DEA 合宜。本研究結果支持「成本吝嗇」假說,該假說認為當銀行審核放款、投資等營運活動不謹慎時,雖然會花費較少成本而提高經營效率,但也會造成銀行穩定度不佳,因此「ESG 傳遞度」越高的銀行,其營運流程相對較為謹慎致成本相對較高,故效率表現應當較差。最後,「公司治理」、「利益攸關人」與「賄賂」在網絡 DEA 多半無法得到顯著的結果,但在網絡 SFA 實證結果則依序得到對效率的影響為顯著負向、正向與正向。
This dissertation divides the production process of commercial banking into two stages for describing the dual roles of deposits and corporate social responsibility (CSR) activities and for linking CSR with cost efficiency. In the first stage, banks expend a portion of their labor and physical capital inputs to collect deposits and engage in CSR; in the second stage, they employ their remaining labor and physical capital and two intermediate goods (i.e., deposits and CSR) to produce loans, investments, and noninterest income. Because the labor and capital inputs are utilized in both stages, we adopt the network data envelopment analysis (DEA) and network stochastic frontier analysis (SFA) models to evaluate bank efficiency, and we investigate the relationship between efficiency and various CSR activities after controlling for bank structures and their country-specific cultural factors.

Under the network DEA framework, we use a truncated regression model, as suggested by Simar and Wilson (2007), to estimate the effects of chosen environmental variables on efficiency. This approach contrasts with the widely applied Tobit model that has been utilized in numerous previous relevant studies. In addition, we adjust the biases of the standard errors from the truncated regression model using two algorithms proposed by Simar and Wilson (2007). We also extend the findings of Huang et al. (2017) by incorporating environmental variables into the inefficiency term of the cost frontier, and we simultaneously estimate the parameter coefficients of the output distance function, cost frontier, and two cost share equations. We derive the joint probability density function of these four equations by applying the copula method. The incorporation of environmental variables substantially complicates the function, which is thus very difficult to estimate.

We combine the Bankscope and Orbis Bank Focus databases to compile input–output data and CAMEL indices for 187 banks in 27 countries during 2003–2014. We collect a set of CSR measures from the Ethical Investment Research and Information Service (EIRIS) database and divide them into seven dimensions: employee, community, environment, governance, stakeholder, bribery, and ESG delivery. We then rescale the scores. In addition, we include the four cultural indices developed by Hofstede et al. (1991, 2010) (i.e., individualism, long-term orientation, uncertainty avoidance, and power distance) in the regression model to partially control for country heterogeneity.

The empirical results of the network DEA and network SFA are similar in several aspects. For example, banks that engage in frequent environment-related CSR activities may pay higher attention to environmental issues and produce more green financial products, such as green loans and green bonds, than banks that rarely engage in environment-related CSR activities. The former banks may acquire green deposits and thereby reduce their funding costs. This implies that banks engage in environmental CSR due to strategic motivation. Conversely, the employee and community dimensions reduce bank efficiency, indicating that these dimensions are consistent with an altruistic motive. The results of analysis of the ESG delivery dimension using the network SFA model support the cost skimping hypothesis, which suggests that superior efficiency may partially be due to a bank’s relatively less careful monitoring of lending or other operations. However, the network DEA provides the opposite result from network SFA. Because the network SFA considers input prices when estimating the cost frontier and efficiency and the network DEA does not, our findings validate the results of the network SFA. Finally, the governance, stakeholder, and bribery dimensions have no significant effect on efficiency in the network DEA, but they exert negative, positive, and positive effects, respectively, on efficiency in the network SFA.
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Description: 博士
國立政治大學
金融學系
102352507
Source URI: http://thesis.lib.nccu.edu.tw/record/#G0102352507
Data Type: thesis
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