Details
Efficiency and Productivity Growth
Modelling in the Financial Services IndustryStatistics in Practice 1. Aufl.
84,99 € |
|
Verlag: | Wiley |
Format: | EPUB |
Veröffentl.: | 21.03.2013 |
ISBN/EAN: | 9781118541586 |
Sprache: | englisch |
Anzahl Seiten: | 288 |
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Beschreibungen
<p><b>An authoritative introduction to efficiency and productivity analysis with applications in both the banking and finance industry</b></p> <p>In light of the recent global financial crisis, several studies have examined the efficiency of financial institutions. A number of open questions remain and this book reviews recent issues and state-of-the-art techniques in the assessment of the efficiency and productivity of financial institutions. Written by an international team of experts, the first part of the book links efficiency with a variety of topics like Latin American banking, market discipline and governance, economics of scale, off-balance-sheet activities, productivity of foreign banks, mergers and acquisitions, and mutual fund ratings. The second part of the book compares existing techniques and state-of-the-art techniques in the bank efficiency literature, including among others, network data envelopment analysis and quantile regression.</p> <p>The book is suitable for academics and professionals as well as postgraduate research students working in banking and finance.</p> <p><i>Efficiency and Productivity Growth: </i></p> <ul> <li>Provides an authoritative introduction to efficiency and productivity analysis with applications in both the banking and mutual funds industry such as efficiency of Asian banks, cooperatives and not-for-profit credit associations.</li> <li>Explores contemporary research issues in the area of efficiency and productivity measurement in the financial sector.</li> <li>Evaluates the most suitable approaches to selecting inputs and outputs as well as selecting the most efficient techniques, such as parametric and non-parametric, to estimate the models.</li> </ul>
<p>Preface xiii</p> <p>Contributors xvii</p> <p><b>1 Bank efficiency in Latin America 1</b><br /> <i>Philip Molyneux and Jonathan Williams</i></p> <p>1.1 Introduction 1</p> <p>1.2 Privatization and foreign banks in Latin America 2</p> <p>1.3 Methodology 4</p> <p>1.4 Model specification and data 7</p> <p>1.5 Estimated parameters and cost efficiency 10</p> <p>1.6 Conclusion 15</p> <p>References 15</p> <p><b>2 A primer on market discipline and governance of financial institutions for those in a state of shocked disbelief 19</b><br /> <i>Joseph P. Hughes and Loretta J. Mester</i></p> <p>2.1 Introduction 20</p> <p>2.2 Assessing the performance of financial institutions 21</p> <p>2.3 Market discipline, public regulation, and the federal safety net 24</p> <p>2.4 Sources of market discipline 27</p> <p>2.4.1 Ownership structure 27</p> <p>2.4.2 Capital markets 37</p> <p>2.4.3 Product markets 37</p> <p>2.4.4 Labor markets 39</p> <p>2.4.5 Boards of directors 40</p> <p>2.4.6 Compensation 41</p> <p>2.5 Conclusions 42</p> <p>Appendix 2.A: Measuring performance based on the highest potential market value of assets 43</p> <p>References 44</p> <p><b>3 Modeling economies of scale in banking: Simple versus complex models 49</b><br /> <i>Robert DeYoung</i></p> <p>3.1 Introduction 49</p> <p>3.2 The increasing size of banks 50</p> <p>3.3 What has allowed banks to grow larger? 53</p> <p>3.3.1 New banking technologies 53</p> <p>3.4 Why do banks choose to be large? 54</p> <p>3.4.1 Objectives of bank management 55</p> <p>3.4.2 Government subsidies 56</p> <p>3.4.3 Scale economies 56</p> <p>3.5 Econometric modeling of bank scale economies 57</p> <p>3.5.1 Findings from 50 years of studies 58</p> <p>3.6 Weaknesses in econometric modeling of bank scale economies 60</p> <p>3.6.1 Few and far between 61</p> <p>3.6.2 Strategic groups 62</p> <p>3.6.3 External costs 68</p> <p>3.7 Other evidence on bank scale economies 68</p> <p>3.7.1 Survivor analysis 68</p> <p>3.7.2 The market price of banks 70</p> <p>3.7.3 Bank size and bank risk-return trade-offs 71</p> <p>3.8 Conclusions 73</p> <p>References 74</p> <p><b>4 Optimal size in banking: The role of off-balance sheet operations 77</b><br /> <i>Jaap W.B. Bos and James W. Kolari</i></p> <p>4.1 Literature review 78</p> <p>4.2 Off-balance sheet activities of European banks 79</p> <p>4.3 Methodology 83</p> <p>4.3.1 Stochastic frontier analysis 83</p> <p>4.3.2 Functional form 84</p> <p>4.3.3 Scale economies 85</p> <p>4.4 Data 86</p> <p>4.5 Results 86</p> <p>4.5.1 Increasing OBS operations 86</p> <p>4.5.2 Nonseparability effects of OBS operations 89</p> <p>4.6 Conclusion 91</p> <p>References 91</p> <p><b>5 Productivity of foreign banks: Evidence from a financial center 95</b><br /> <i>Claudia Curi and Ana Lozano-Vivas</i></p> <p>5.1 Introduction 95</p> <p>5.2 Literature overview 98</p> <p>5.3 Methodology 100</p> <p>5.3.1 TFP growth measures 100</p> <p>5.3.2 Estimation of the TFP growth measures 102</p> <p>5.4 Data and sources 103</p> <p>5.5 Empirical results 109</p> <p>5.5.1 Productivity growth over time 109</p> <p>5.5.2 Breaking down productivity growth 111</p> <p>5.6 Conclusions 116</p> <p>Acknowledgments 118</p> <p>References 118</p> <p><b>6 The impact of merger and acquisition on efficiency and market power 123</b><br /> <i>Franco Fiordelisi and Francesco Saverio Stentella Lopes</i></p> <p>6.1 Introduction 123</p> <p>6.2 Literature review 125</p> <p>6.3 Empirical design 125</p> <p>6.3.1 Data 125</p> <p>6.3.2 Variables 127</p> <p>6.3.3 The econometric approach 129</p> <p>6.4 Results 129</p> <p>6.5 Conclusions 131</p> <p>References 132</p> <p><b>7 Backtesting superfund portfolio strategies based on frontier-based mutual fund ratings 135</b><br /> <i>Olivier Brandouy, Kristiaan Kerstens, and Ignace Van de Woestyne</i></p> <p>7.1 Introduction 135</p> <p>7.2 Frontier-based mutual funds rating models 137</p> <p>7.2.1 A taxonomy 137</p> <p>7.2.2 MF frontier rating models retained 142</p> <p>7.3 Backtesting setup, data description, and frontier-based portfolio models 144</p> <p>7.3.1 Backtesting setup 144</p> <p>7.3.2 Frontier-based portfolio models 146</p> <p>7.3.3 Data description 146</p> <p>7.4 Empirical analysis 148</p> <p>7.4.1 Descriptive statistics 148</p> <p>7.4.2 Analysis of both hedonic rating models 148</p> <p>7.4.3 Backtesting results for 48 different strategies 153</p> <p>7.4.4 Backtesting results for MF rating models: Some plausible explanations 159</p> <p>7.5 Conclusions 166</p> <p>Acknowledgments 168</p> <p>References 168</p> <p><b>8 Bank efficiency measurement and network DEA: A discussion of key issues and illustration of recent developments in the field 171</b><br /> <i>Necmi K. Avkiran</i></p> <p>8.1 Introduction 171</p> <p>8.2 Global financial crisis and the importance of DEA in bank performance analysis 172</p> <p>8.3 The wider contribution of DEA to bank efficiency analysis and potential improvements 173</p> <p>8.4 Principal advantages and disadvantages of DEA 174</p> <p>8.5 DEA versus stochastic frontier analysis 176</p> <p>8.6 Drilling deeper with network DEA in search of inefficiencies 177</p> <p>8.6.1 Definition of ‘Network’ in banking applications of NDEA 177</p> <p>8.6.2 Conceptualizing bank branch production 179</p> <p>8.6.3 Network slacks-based measure of efficiency 181</p> <p>8.6.4 A brief numerical example 183</p> <p>8.6.5 Jackknifing versus bootstrapping 185</p> <p>8.7 Moving forward with DEA 186</p> <p>8.8 Conclusions 187</p> <p>Appendix 8.A: Jackknifing 188</p> <p>References 189</p> <p><b>9 A dynamic network DEA model with an application to Japanese Shinkin banks 193</b><br /> <i>Hirofumi Fukuyama and William L. Weber</i></p> <p>9.1 Introduction 193</p> <p>9.2 Literature review of productivity analysis in credit banks in Japan 194</p> <p>9.3 Dynamic network production 196</p> <p>9.3.1 The two-stage technology 196</p> <p>9.3.2 Three-year dynamic DEA 199</p> <p>9.4 Cooperative Shinkin banks: An empirical illustration 202</p> <p>9.4.1 Defining bank inputs and outputs 202</p> <p>9.4.2 NPLs in the efficiency/productivity measurement 203</p> <p>9.4.3 Data 204</p> <p>9.5 Estimates 205</p> <p>9.6 Summary and conclusions 209</p> <p>References 211</p> <p><b>10 Effects of specification choices on efficiency in DEA and SFA 215</b><br /> <i>Michael Koetter and Aljar Meesters</i></p> <p>10.1 Introduction 215</p> <p>10.2 Bank benchmarking background 216</p> <p>10.2.1 Theoretical foundations 216</p> <p>10.2.2 Benchmarking techniques 217</p> <p>10.2.3 Specification options 218</p> <p>10.3 Methodologies 220</p> <p>10.3.1 Stochastic frontier analysis 220</p> <p>10.3.2 Data envelopment analysis 221</p> <p>10.4 Data 221</p> <p>10.5 Results 225</p> <p>10.5.1 Efficiency distributions 225</p> <p>10.5.2 Rank correlations 230</p> <p>10.5.3 Extreme performers 231</p> <p>10.5.4 Accounting-based indicators 232</p> <p>10.6 Conclusion 233</p> <p>References 234</p> <p><b>11 Efficiency and performance evaluation of European cooperative banks 237</b><br /> <i>Michael Doumpos and Constantin Zopounidis</i></p> <p>11.1 Introduction 237</p> <p>11.2 Methodology 239</p> <p>11.2.1 Data envelopment analysis models 239</p> <p>11.2.2 Multicriteria evaluation 240</p> <p>11.3 Empirical results 241</p> <p>11.3.1 Data and variables 241</p> <p>11.3.2 Efficiency analysis results 244</p> <p>11.3.3 Multicriteria evaluation results 247</p> <p>11.4 Conclusions 251</p> <p>References 251</p> <p><b>12 A quantile regression approach to bank efficiency measurement 253</b><br /> <i>Anastasia Koutsomanoli-Filippaki, Emmanuel Mamatzakis, and Fotios Pasiouras</i></p> <p>12.1 Introduction 253</p> <p>12.2 Methodology and data 254</p> <p>12.2.1 Methodology 254</p> <p>12.2.2 Data and specification of the frontier 256</p> <p>12.3 Empirical results 257</p> <p>12.3.1 Cost efficiency estimates 257</p> <p>12.3.2 Determinants of cost efficiency 259</p> <p>12.4 Conclusions 262</p> <p>Appendix 12.A: Information on variables 262</p> <p>References 265</p> <p>Index 267</p>
<p><strong>Fotios Pasiouras</strong>, Department of Production Engineering and Management, Technical University of Crete, Greece.
<p><b>An authoritative introduction to efficiency and productivity analysis with applications in both the banking and finance industry</b></p> <p>In light of the recent global financial crisis, several studies have examined the efficiency of financial institutions. A number of open questions remain and this book reviews recent issues and state-of-the-art techniques in the assessment of the efficiency and productivity of financial institutions. Written by an international team of experts, the first part of the book links efficiency with a variety of topics like Latin American banking, market discipline and governance, economics of scale, off-balance-sheet activities, productivity of foreign banks, mergers and acquisitions, and mutual fund ratings. The second part of the book compares existing techniques and state-of-the-art techniques in the bank efficiency literature, including among others, network data envelopment analysis and quantile regression.</p> <p>The book is suitable for academics and professionals as well as postgraduate research students working in banking and finance.</p> <p><i>Efficiency and Productivity Growth: </i></p> <ul> <li>Provides an authoritative introduction to efficiency and productivity analysis with applications in both the banking and mutual funds industry such as efficiency of Asian banks, cooperatives and not-for-profit credit associations.</li> <li>Explores contemporary research issues in the area of efficiency and productivity measurement in the financial sector.</li> </ul> Evaluates the most suitable approaches to selecting inputs and outputs as well as selecting the most efficient techniques, such as parametric and non-parametric, to estimate the models.
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