This paper investigates Japanese bank managers' use of the discretionary component of loan loss provisions to manage earnings during the recession of the late 1990s. Although studies of US banks document that bank managers use loan loss provisions to smooth earnings, manage regulatory capital, and signal undervaluation, factors that may affect discretionary loan loss provisions in Japanese banks have not been empirically examined. We find that discretionary loan loss provisions for our sample of Japanese banks are positively related to the demand for external financing, realized securities gains, and prior year taxes and are negatively related to capital and pre-managed earnings.

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<span style="font-family: Times New Roman; font-size: small;"> </span><h1 style="margin: 0in 0.5in 0pt; text-align: justify; page-break-after: auto; mso-pagination: none;"><span style="font-family: Times New Roman;"><span style="color: black; font-size: 10pt; mso-themecolor: text1;">Our study evaluates a multiple criteria linear programming (MCLP) </span><span style="color: black; font-size: 10pt; mso-themecolor: text1; mso-fareast-language: KO;">and other </span><span style="color: black; font-size: 10pt; mso-themecolor: text1;">data mining approach</span><span style="color: black; font-size: 10pt; mso-themecolor: text1; mso-fareast-language: KO;">es</span><span style="color: black; font-size: 10pt; mso-themecolor: text1;"> </span><span style="color: black; font-size: 10pt; mso-themecolor: text1; mso-fareast-language: KO;">to predict auditor changes using a portfolio of financial statement measures to capture financial distress</span><span style="color: black; font-size: 10pt; mso-themecolor: text1;">.<span style="mso-spacerun: yes;"> </span>The results of the MCLP approach and the other data mining approaches show that these methods perform</span><span style="color: black; font-size: 10pt; mso-themecolor: text1; mso-fareast-language: KO;"> reasonably well to predict auditor changes </span><span style="color: black; font-size: 10pt; mso-themecolor: text1;">using financial distress variables.</span><span style="color: black; font-size: 10pt; mso-themecolor: text1; mso-fareast-language: KO;"><span style="mso-spacerun: yes;"> </span>Overall accuracy rates are more than 60 percent, and true positive rates exceed 80 percent.<span style="mso-spacerun: yes;"> </span>Our study is designed to establish a starting point for auditor-change prediction using financial distress variables.<span style="mso-spacerun: yes;"> </span>Further research should incorporate additional explanatory variables and a longer study period to improve prediction rates.</span></span></h1><span style="font-family: Times New Roman; font-size: small;"> </span>

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