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Kang, Jian
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Kang, Jian
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- PublicationAccès libreFinancial development, intangible investments, and the evolution of earnings quality(2021)
; We contribute to the ongoing debate on the reason for the decline in earnings qual- ity (EQ) documented by prior literature. We argue that Srivastava (2014)’s explanation that “each new cohort of listed firms exhibits lower earnings quality than its predecessors, mainly because of higher intangible intensity” may not be satisfactory. Instead, we assert that the downward trend in the EQ measures of successive cohorts reflects a progressive decrease in newer firms’ business effectiveness, as measured by profitability, operational efficiency, and economic risk. This is a direct result of easier access to public funding brought about by the 1970s trend change in the state of development of the U.S. finan- cial sector (Rajan and Zingales, 2003). Our explanation strictly encompasses Srivastava (2014)’s. While for newcomers in specific industries lower business effectiveness is as- sociated with higher intangible intensity, the lack of fit of most of the new listings is not explained by their investments in intangibles. They are simply weaker, riskier firms and have lower EQ as a result. - PublicationAccès libreWhy have measures of earnings quality changed over time? A competing narrative(2019)
; We contribute to the debate on the reason for the decline in earnings quality (EQ) documented by prior literature. We dissent from Srivastava (2014)’s conclusion that “each new cohort of listed firms exhibits lower earnings quality than its predecessors, mainly because of higher intangible intensity”. Instead, we argue that the downward trend in EQ measures is explained by changes in firms’ economic risk and operational efficiency associated with “broadening of the kinds of firms publicly traded” (Fama and French (2004)). The association of intangible intensity to EQ measures is spurious and disappears when controlling for the mentioned firm’s characteristics. - PublicationAccès libreAccounting information vs. analysts forecasts in market’s expectations formation(2018)
; We find that the expectations about future earnings incorporated in prices are mainly informed by the analysts earnings forecasts. Neither the stock nor the flow accounting items considered do not contribute significantly to shaping investors price setting expectations. - PublicationAccès libreWhat kind of earnings shape more market expectations?(2018)
; We study how earnings attributes affect investors expectations about future earnings reflected in market prices. We separate the contribution of current earnings to price setting through a valuation incorporating expectations informed only by the current value of earnings. Its pricing error measures the extent to which expectations are shaped by information other than current earnings. We estimate the association between this pricing error and eleven earnings quality constructs commonly used in the empirical literature using a large sample of US non-financial firms over the period 1971-2016. We find that, above all, quality earnings vary little (are sustainable) and are predictive of future earnings. Moreover, their low volatility is shared by their accrual component and is not due to aggressive smoothing. We document that time-series accrual quality proxies subsume measures based on popular residual accruals models in shaping expectations. How often firms report special items has a significant impact on current earnings relevance to expectation formation: the less often, the better. - PublicationAccès libreAccounting information vs. analysts forecasts in market’s expectations formation(2018)
; We find that the expectations about future earnings incorporated in prices are mainly informed by the analysts earnings forecasts. Neither the stock nor the flow accounting items considered do not contribute significantly to shaping investors price setting expectations. - PublicationAccès libreA consistent research design for value relevance studies(2017)
; We argue that Ohlson’s linear solution to the residual earnings (RE) equation, a crucial component of a widely used value relevance research design, is generally not a linear regression. Moreover, its coefficients are firm-dependent. As such, its empirical specifications, the price-levels regression and the returns-earnings regressions are structurally ill-suited for consistent inference in cross-sections. To address this issue we, first, prove the existence of a regression solution to the RE equation and, second, introduce a valuation-based research design that builds on such a solution and warrants a consistent estimation of the empirical specification (which takes the form of a non-linear regression). Its estimation turns out to be an optimal implementation of the price-to-book (P/B ) multiple valuation, a technique that is easy to implement and familiar to the accounting community. The regression view on multiple valuation identifies P/B value with a price that incorporates earnings expectations formed only on the basis of the current levels of the RE drivers. Using a large sample of US non-financial firms over an almost 40 year-period, we document the usefulness of the alternative research design through a comparative testing of four economically-motivated and intuitively-appealing predictions: size, earnings predictability and volatility, and the quality of accruals are value-relevant. While the current research design does not validate them, the approach based on the regression solution shows a significant association between prices and the four attributes for most of the years in the sample.