Hai Yen Pham, Richard Chung, Eduardo Roca, and Ben-Hsien Bao Do Investors Value Firm Efficiency Improvement? Evidence from the Australian Context? Authors: Hai Yen Pham, Richard Chung, Eduardo Roca, and Ben-Hsien Bao Discussion Searat Ali Griffith University

Subsequent stock returns What this paper does Do investors value improvement in efficiency? Stochastic Frontier Analysis (SFA) to evaluate a firm’s efficiency Sample firms: non-financial companies Sample country: Australia Sample period: January 1990 to October 2012 Efficiency change Subsequent stock returns

What this paper does How efficient Australian firms are? Portfolio performance analysis Preliminary analysis: High vs low CH sorted portfolios The Carhart 4-factor Model Effect of efficiency change on subsequent stock returns Panel Data Analysis The Fama-MacBeth (1973) Typed Regressions The Issue of Endogeneity Robustness on ARCH/GARCH effects Robustness on Seasonality

Results and interpretation Average efficiency score is 61.5% The paper shows that over the sample period, the estimated mean improvement in firm’s efficiency is 3% per year. Equally-weighted (value-weighted) portfolio of stocks with the top tertile level change in efficiency outperforms an equally-weighted (value-weighted) portfolio of stocks with the bottom tertile level change in efficiency, by an average of 11% (7%) per annum during the sample period. There is a significant efficiency change effect on a cross-section of stock returns after controlling for other risk factors such as size, book- to-market, market liquidity, industry concentration, and seasonality effect. These findings are not sensitive to different estimation methods, endogeneity bias etc.

Some of the paper’s strengths Methodology is well explained: Portfolio construction, return models Large dataset: Cross-section (14,857 firm-year observations or 137,174 firm-month observations) time series (22 years). Strong results robust to a large number of control tests (e.g., fixed effect, Fama-MacBeth, GMM) Top ranked journal references Grade Frequency Most cited A* 30 JFE, JF A 10 AJM B 3 AE C --

Comments/suggestions 1-Major contributions 2-Interpretation of results 3-Instrumental variable 4-Referencing and proofreading

Comments/suggestions 1-Major contributions

Comments/suggestions Gap in literature There are number of studies examining the relationship between efficiency and stock returns. Gap: The results are mixed. Either positive or negative. Most of the studies find……..? How your study is resolving the issue of mixed findings? Suggestion: Try to figure out why there are mixed results in the literature? Because of country? Because of industries? Because of sample period? Data after GFC? Sample size? Methodology? DEA or SFA; RE, FE, GMM.

Comments/suggestions Contributions of the study Data is the driver whereas idea and tool are passengers First study in Australia considering non-financial firms. Suggestion: Why it is important to study efficiency return nexus in Australia? What are the expected results? Large sample. Suggestion: Argue that the prior literature suffers from small sample bias. Examines EC effect over time and across industries. Suggestion: Emphasize on the value it will bring to the literature.

Comments/suggestions 2-Interpretation of results

Comments/suggestions Results of the study Low portfolios: High systematic risk, small stocks, value stocks, mom is insignificant Risk premium Size premium? yes Value premium? Liquidity premium? yes Efficiency premium? No Adjusted Rsq=0.0004?

Comments/suggestions What is the implication of the industry based regressions? Industries Panel data Fama-MacBeth CH %CH Energy No Materials Yes Industrials Consumer D Consumer S Health care IT Telecommunication Utilities

Comments/suggestions 3-Instrumental variable

Comments/suggestions Instrument Corporate governance mechanisms such as board size, Proportion of non-executive directors, CEO duality, top20 shareholding percentage. Relevance: fine Prior studies suggest that an improvement in corporate governance could lead to a better monitoring mechanism, better operation, and thus, an improvement in firm efficiency. Suggestion: 1) use CGQ index 2) Display first-stage result to show relevance. Exclusion: critical However, the empirical evidence suggests the existence of other factors not captured by beta, such as size and book-to-market (Fama and French, 1992), momentums (Jegadeesh and Titman, 1997), excess cash holding (Dittmar and Marhrt-Smith, 2007), liquidity (Chan and Faff, 2003; Mahipala, Chan and Faff, 2009), default risk (Garlappi, Shu and Yan, 2008), industry concentration (Hou and Robinson, 2006) and corporate governance (Gompers, Ishii and Metrick, 2003).

Comments/suggestions 4-Referencing and proofreading

Comments/suggestions Update the references Minor issues: Some proof reading required… Target AJM Altogether, it was a joy to read this paper and potential to make an important contribution to the literature. Year Frequency 2015 2014 2013 5 2012 6 2011 1 2010