Cheng-Few Lee’s research while affiliated with Rutgers, The State University of New Jersey and other places

Synopsis The research problem Our study explores the association between tax enforcement and tone management in the Management’s Discussion and Analysis (MD&A). Motivation Prior studies have shown that tax enforcement influences financial reporting due to the tax authority’s scrutiny of financial statements to detect tax evasion, which deters financial reporting manipulation. However, the spillover effect of tax enforcement on qualitative disclosures remains unexplored. Motivated by the relevance of MD&A as a comprehensive discussion of a firm’s conditions and a target for manipulation, we investigate the association between tax enforcement and tone management. The test hypotheses We test two competing hypotheses: increased tax enforcement is associated with more tone management, and it is associated with lesser tone management. Target population Our study should be of interest to corporate stakeholders, including managers, investors, regulatory authorities, and policymakers. Adopted methodology Ordinary least squares regressions, staggered difference-in-differences model, and path analysis. Analysis Our study explores a sample of Chinese A-share listed firms from 2008 to 2020. We measure tone management using Huang et al.’s [(2014). Tone management. The Accounting Review, 89(3), 1083–1113. https://doi.org/10.2308/accr-50684 ] model, which regresses the tone level in MD&A on firm fundamentals, and use the discretionary tone portion as a proxy. Tone level is calculated as the difference between the number of positive and negative sentiment words divided by their sum. Findings We find that increased tax enforcement is associated with lesser tone management. Path analysis shows that this effect is driven by constraints on earnings management and enhanced accounting conservatism, suggesting that tax enforcement improves financial reporting quality, which in turn disciplines disclosure tone. Cross-sectional tests further indicate that the effect of increased tax enforcement varies with tax compliance levels, managerial incentives to influence investor perceptions, and external monitoring.

This study investigates how the imputation tax system affects investor valuation of corporate tax avoidance. We find that under the full imputation tax system, investors assign a lower value to corporate tax avoidance, compared to the classical tax system, as tax avoidance reduces imputation credits available to shareholders, effectively transferring cash flows from shareholders to firms. Additionally, under the full imputation tax system, this negative valuation effect on corporate tax avoidance is more pronounced in firms with higher dividend payouts. We also find that stronger investor protection and greater firm growth opportunities mitigate the negative valuation of the cash flow transfer induced by tax avoidance, suggesting that investors are concerned about whether the transferred cash is efficiently utilized by the firm. These results challenge the traditional view that corporate tax avoidance enhances shareholder value and highlight the importance of tax system characteristics when evaluating the financial implications of tax avoidance.

This study provides a comparative analysis of hedging determination for four international equity index futures, namely S&P 500, FTSE 100, Nikkei 225, and TAIEX futures contracts. Three alternative estimations are used to determine the hedge ratio for sizing hedge positions: a conventional OLS model, a conventional OLS model with an AR(2)-GARCH(1,1) error structure and an error correction model. Additionally, we evaluate the hedging effectiveness of these alternative models in different stock markets. First, three alternative methods of conducting optimal hedging in different markets are not identical. Moreover, comparisons of in-sample hedging performance reveal that the conventional OLS model outperforms two alternative models for these four stock markets. However, our out-of-sample hedging performance reveals that all hedge ratios which considering heteroscedastic error or cointegration relationship are superior to that of hedge ratio estimated by conventional OLS model. Overall, it is found that considering the existence of heteroscedastic error structure or cointegration relationship cannot be ignored when sizing hedge positions.

The main purposes of this paper are to show how financial analysis and forecasting can be performed in terms of (i) financial ratio analysis, (ii) policy decision analyses, (iii) beta coefficient, performance measures, and three costs of equity capital, and (iv) simultaneous equation approach to forecast JNJ’s EPS, PPS, and DPS. We first use JNJ’s annual report and price data from Yahoo Finance to calculate financial ratios by using Excel program. Second, we use JNJ, IBM, and S&P 500 monthly returns to calculate beta coefficients, performance measures and cost of equity capital. Third, we use JNJ’s annual report and Yahoo Finance data to forecast EPS, PPS, and DPS in terms of Excel program. In addition, we also use sensitivity analysis to show how growth rate, leverage ratio, and dividend payout ratio can affect the forecast of EPS, PPS, and DPS. There are two potential applications for this paper. First, this paper shows financial analysts how to use accounting data and market rate of return data to determine the fundamental value of individual company and forecast EPS, PPS, and DPS for that company. Second, this paper can also be used by professors of corporate finance and investment analysis to show students how to use real-world financial data to perform financial analysis and forecasting for an individual company.

The 32nd Annual Conference on Pacific Basin Finance, Economics, Accounting, and Management was held at Rutgers University, USA on August 29 and 30, 2024. The first conference was held at Rutgers University in 1993. Since then, the conference has been held in Hong Kong (1994, 1998), Taiwan (1995, 1999, 2003, 2006, 2011, 2016, 2019, 2020, 2022, 2023), Rutgers (1996, 2001, 2005, 2012, 2018, 2021), Singapore (1997, 2002, 2017), Bangkok (2000, 2004, 2009), Vietnam (2007, 2015), Australia (2008, 2013), China (2010), Japan (2014). The program directors of the conference were Cheng-Few Lee and Bharat Sarath, Rutgers University, USA.

In this study, we argue that Research and Development (R&D) (Selling, General, and Administrative expenses, SG&A) expenses are in response to various earning-related stimuli rather than intangible or tangible capital accumulation that classic investment-[Formula: see text] theory advocates, and there is a specification error in [Gunny, KA (2010). The relation between earnings management using real activities manipulation and future performance: Evidence from meeting earnings benchmarks. Contemporary Accounting Research, 27(3), 855-888] suspected R&D (SG&A) real activity manipulation. Our finding indicates that among three Tobin’s [Formula: see text] measures, either standard Tobin’s [Formula: see text] used in finance (a firm’s market value over the physical capital) or total Tobin’s [Formula: see text] incorporated intangible capital into standard Tobin’s [Formula: see text] [Peters, RH and LA Taylor (2017). Intangible capital and the investment-[Formula: see text] relation. Journal of Financial Economics, 123(2), 251–272] cannot better explain R&D (SG&A) expense than classic Tobin’s [Formula: see text] regarding slope coefficient level and [Formula: see text]-squared value. Moreover, the specification of R&D- or SG&A-based real activity manipulation, i.e., deep cuts in R&D or SG&A, is significantly related to firms just meeting zero and last year’s earnings. These findings suggest managers may deeply cut R&D or SG&A expenses to avoid an earnings shortfall. Our results further indicate that deep SG&A cuts or deep R&D cuts are negatively associated with future operating performance, which is more pronounced in the post-Sarbanes–Oxley (SOX) period. The net effects of deep SG&D cuts (R&D cuts) on future operating performance are negative (positive) when the firms meet the earnings benchmarks and have deep SG&D cuts (R&D cuts), implying that deeper cuts in SG&A expenses in response to earning-related stimuli could reflect firm-level opportunistic behaviors but deeper cuts in SG&A expenses in response to earning-related stimuli do not. Finally, deep SG&A cuts or deep R&D cuts increase the persistent predictability of cash flows on future earnings. However, the net effects of deep SG&A cuts (R&D cuts) on persistent predictability of cash flows for future earnings are negative (positive) when the firms meet earnings benchmarks and have deep SG&D cuts (R&D cuts). Overall, our estimated results imply that deep SG&A cuts are an expected outcome of opportunistic real earnings management, but deep low R&D cuts are not.

The main purposes of this paper are to (i) Report my experiences teaching Ph.D. students, MBA students, Masters students, and undergraduate students; (ii) Report my achievements and experience in research from 1973 to 2023; (iii) Report my experience of serving as the Ph.D. director of UIUC from 1978 to 1988 and chairperson of Rutgers Business School from 1988 to 1996; (iv) Report my achievements in textbook writing, editing, work on the Encyclopedia of Finance, and handbook writing; and (v) Report my experience of journal editing and conference organizing. From these experiences, I will provide some suggestions in regard to teaching, research, and service in the area of finance.