Mandatory vs. Voluntary Management Earnings Forecasts in China

Mandatory vs. Voluntary Management Earnings Forecasts in China

Xiaobei Huang University of International Business and Economics – Business School

Xi Li Temple University – Fox School of Business and Management

Senyo Y. Tse Texas A&M University – Lowry Mays College & Graduate School of Business

Jenny Wu Tucker University of Florida – Warrington College of Business Administration

May 2, 2013
Mays Business School Research Paper No. 2012-82

Capital-market regulators face the question of whether mandating management earnings forecasts would improve the information environment or be counterproductive. We examine the efficacy of a forecast regulation in the emerging market of China, which mandates management earnings forecasts in certain performance regions such as anticipated losses, turning profit, and large changes in earnings from the previous year and allows voluntary forecasts in other circumstances. We examine the quantity, quality, and usefulness of mandatory forecasts by comparing firms’ forecast behavior under the mandatory vs. voluntary regime in China. Our results suggest that the Chinese mandate substantially increases the quantity of information available to investors, particularly by state-owned enterprises (SOEs) — firms that play a major role in the economy but are reluctant to provide forecasts voluntarily. Firms that issue mandatory forecasts are more likely to issue voluntary forecasts in the subsequent year. Yet mandatory forecasts are less timely and less precise than voluntary forecasts, suggesting that mandatory forecasts are of lower quality than voluntary forecasts. On balance, investors react to mandatory forecasts as if they are useful. One unintended consequence of the mandate is that firms appear to manage their reported earnings to avoid the bright-line threshold for mandatory forecasts of large earnings decreases. Overall, our evidence provides guidance to regulators in emerging markets and feedback to regulators in developed economies.

About bambooinnovator
Kee Koon Boon (“KB”) is the co-founder and director of HERO Investment Management which provides specialized fund management and investment advisory services to the ARCHEA Asia HERO Innovators Fund (, the only Asian SMID-cap tech-focused fund in the industry. KB is an internationally featured investor rooted in the principles of value investing for over a decade as a fund manager and analyst in the Asian capital markets who started his career at a boutique hedge fund in Singapore where he was with the firm since 2002 and was also part of the core investment committee in significantly outperforming the index in the 10-year-plus-old flagship Asian fund. He was also the portfolio manager for Asia-Pacific equities at Korea’s largest mutual fund company. Prior to setting up the H.E.R.O. Innovators Fund, KB was the Chief Investment Officer & CEO of a Singapore Registered Fund Management Company (RFMC) where he is responsible for listed Asian equity investments. KB had taught accounting at the Singapore Management University (SMU) as a faculty member and also pioneered the 15-week course on Accounting Fraud in Asia as an official module at SMU. KB remains grateful and honored to be invited by Singapore’s financial regulator Monetary Authority of Singapore (MAS) to present to their top management team about implementing a world’s first fact-based forward-looking fraud detection framework to bring about benefits for the capital markets in Singapore and for the public and investment community. KB also served the community in sharing his insights in writing articles about value investing and corporate governance in the media that include Business Times, Straits Times, Jakarta Post, Manual of Ideas, Investopedia, TedXWallStreet. He had also presented in top investment, banking and finance conferences in America, Italy, Sydney, Cape Town, HK, China. He has trained CEOs, entrepreneurs, CFOs, management executives in business strategy & business model innovation in Singapore, HK and China.

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