Wikil Kwak

Income Smoothing and Discretionary R&D Expenditures of Japanese Firms*

During the recent recession (1991 to present), Japanese firms decreased their spending on R&D for the first time since World War II. The decreases have raised concerns that Japanese managers may be making suboptimal allocations to R&D. We test whether Japanese managers adjust R&D based on short-term performance. Our results show that Japanese firms in several industries adjust their R&D budgets to smooth profits. Interestingly, adjustments to R&D are larger in expansion years. These results, similar to those documented with U.S. managers, point to myopic decision making by Japanese managers.

Bankruptcy prediction for Japanese firms: using Multiple Criteria Linear Programming data mining approach

Data mining applications have been getting more attention in general business areas, but there is a need to use more of these applications in accounting areas where accounting deals with large amounts of both financial and non-financial data. The purpose of this research is to test the effectiveness of a Multiple Criteria Linear Programming (MCLP) approach to data mining for bankruptcy prediction using Japanese bankruptcy data. Our empirical results show that Ohlsons (1980) predictor variables perform better than Altmans (1968) predictor variables using 1990s Japanese financial data. Our Type I (misclassification of bankrupt as non-bankrupt firms) prediction rate using the MCLP approach, Ohlsons (1980) variables and 1990s Japanese financial data is much higher than that reported by Kwak et al. (2005) using the MCLP approach, Ohlsons (1980) variables and 1990s US data.

Human Resource Allocation in a CPA Firm: A Fuzzy Set Approach

The review of existing human resource allocation models for a CPA firm shows that there are major shortcomings in the previous mathematical models. First, linear programming models cannot handle multiple objective human resource allocation problems for a CPA firm. Second, goal programming or multiple objective linear programming (MOLP) cannot deal with the organizational differentiation problems. To reduce the complexity in computing the trade-offs among multiple objectives, this paper adopts a fuzzy set approach to solve human resource allocation problems. A solution procedure is proposed to systematically identify a satisfying selection of possible staffing solutions that can reach the best compromise value for the multiple objectives and multiple constraint levels. The fuzzy solution can help the CPA firm make a realistic decision regarding its human resource allocation problems as well as the firms overall strategic resource management when environmental factors are uncertain.

Institutional Ownership and Income Smoothing by Japanese Banks Through Loan Loss Provisions

This paper examines the association between institutional ownership and income smoothing through bank loan loss provisions for a sample of Japanese banks during the period 1991–1999. We find that as the percentage of institutional ownership of banks increases, income smoothing via loan loss provisions increases. Additional tests show that there is a significant positive relationship between the extent of income smoothing and the percentage ownership of banks by domestic financial institutions and affiliated (keiretsu) institutions. Consistent with the idea that foreign institutional holders do not play an important role in the corporate governance of Japanese banks, we do not find a significant association between foreign institutional ownership and the extent of income smoothing. Our results imply that institutional owners may play a different role in monitoring income smoothing during the recessionary period in Japan from the normal economic periods studied in most prior studies.

The Determinants of Bankruptcy for Chinese Firms

The global financial crisis in 2008 increased the number of business failures in the U.S. as well as in China. The Chinese economy has also been affected by the recent global financial crisis given the fact that the Chinese economy depends heavily on international trade. Our study tries to find the determinants of bankruptcy in Chinese firms. Both logit and survival model analyses provide consistent results on the determinants in predicting distressed firms in China. Our results suggest that firms with liquidity problems and firms experiencing a decline in profits are more likely to file for bankruptcy. In addition, we find that, compared to state-owned enterprises (SOEs), collectively-owned enterprises, private-owned enterprises, and foreign-owned businesses are more likely to file for bankruptcy. This conclusion is robust after controlling for regional differences. The findings of this study show that the financial variables developed by Altman [Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. Journal of Finance, 23(3), 589–609] and Ohlson [Financial ratios and probabilistic prediction of bankruptcy. Journal of Accounting Research, 18(1), 109–131] perform reasonably well in determining business failures of Chinese firms even though SOEs and shadow financing exist in China.

Multiple criteria linear programming data mining approach: an application for bankruptcy prediction

Data mining is widely used in today’s dynamic business environment as a manager’s decision making tool, however, not many applications have been used in accounting areas where accountants deal with large amounts of operational as well as financial data. The purpose of this research is to propose a multiple criteria linear programming (MCLP) approach to data mining for bankruptcy prediction. A multiple criteria linear programming data mining approach has recently been applied to credit card portfolio management. This approach has proven to be robust and powerful even for a large sample size using a huge financial database. The results of the MCLP approach in a bankruptcy prediction study are promising as this approach performs better than traditional multiple discriminant analysis or logit analysis using financial data. Similar approaches can be applied to other accounting areas such as fraud detection, detection of tax evasion, and an audit-planning tool for financially distressed firms.

The Fuzzy Set and Data Mining Applications in Accounting and Finance

To reduce the complexity in computing trade-offs among multiple objectives, our series of papers adopts a fuzzy set approach to solve various accounting or finance problems such as international transfer pricing, human resource allocation, accounting information system selection, and capital budgeting problems. A solution procedure is proposed to systematically identify a satisfying selection of possible solutions that can reach the best compromise value for the multiple objectives and multiple constraint levels. The fuzzy solution can help top management make a realistic decision regarding its various resource allocation problems as well as the firm’s overall strategic management when environmental factors are uncertain. In addition, we provide asn update on the effectiveness of a multiple criteria linear programming (MCLP) approach to data mining for bankruptcy prediction using financial data. Data mining applications have been receiving more attention in general business areas, but there is a need to use more of these applications in accounting and finance areas when dealing with large amounts of financial and non-financial data. The results of the MCLP data mining approach in our bankruptcy prediction studies are promising and may extend to other countries.