On cross-sectional analysis in accounting research

Christie, Andrew A.

doi:10.1016/0165-4101(87)90007-3

Cited by 483 publications

(255 citation statements)

References 34 publications

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“…All the EPS variables are the basic EPS excluding extraordinary items (Compustat Data58), adjusted for stock splits and stock dividends, and, according to Christie (1987), deflated by the stock price at the beginning of Year t. R t3 is the aggregate stock return in Year t+1 to t+3 with annual compounding.…”

Section: Primary and Supplementary Modelsmentioning

confidence: 99%

Does Income Smoothing Improve Earnings Informativeness?

Tucker

Zarowin

2006

The Accounting Review

700

514

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This paper uses a new approach to examine whether income smoothing garbles earnings information or improves the informativeness of past and current earnings about future earnings and cash flows. We measure income smoothing by the negative correlation of a firm's change in discretionary accruals with its change in pre-managed earnings. Using the approach of Collins, Kothari, Shanken and Sloan (1994), we find that change in the current stock price of higher-smoothing firms contains more information about their future earnings than does change in the stock price of lower-smoothing firms.This result is robust to decomposing earnings into cash flows and accruals and to controlling for firm size, growth, future earnings variability, private information search activities, and cross-sectional correlations.

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Section: Primary and Supplementary Modelsmentioning

confidence: 99%

Does Income Smoothing Improve Earnings Informativeness?

Tucker

Zarowin

2006

The Accounting Review

700

514

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“…In extending the work by CLR I examine the relevant variables in the following specification: This model is estimated using an OLS specification. The OLS estimator is appropriate in this model because concerns over the serial correlation of errors are alleviated in a changes specification (Christie 1987). The tests of my hypotheses are as follows:…”

Section: MVmentioning

confidence: 99%

“…The first, unscaled, levels model used by CLR is unbiased but inefficient (Christie 1987). Their model scaled by common shares outstanding attempts to rectify this inefficiency but may not be the optimal choice of scaling variable (Christie 1987). My changes specification of the model attempts to circumvent these issues by examining changes in relevant variables thereby relieving the scaling issue.…”

Section: Introductionmentioning

confidence: 99%

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Further Examination of the Market Valuation of Environmental Capital Expenditures by Pulp and Paper Companies

Solheim

2012

ijafr

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In this study I use the US pulp and paper industry to explore the equity market's valuation of environmental capital expenditures. I replicate and extend a study by Clarkson, Li, and Richardson that bifurcates the industry into high and low polluting groups. As with their study, I find evidence indicating that the market values environmental capital expenditures by over-compliant firms while attaching no such value to the same expenditures by minimally compliant firms. I do not find that the market assesses unrecorded liabilities to firms that are minimally compliant. My extension also seeks to address two possible specification issues in the Clarkson, et Al. approach. The first, levels model they used is unbiased but inefficient. Their model scaled by common shares outstanding attempts to rectify this inefficiency but may not be the optimal choice of scaling variable. My results suggest that a "Best Available Technology" approach to environmental regulation may carry additional incentives provided by the capital markets.

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“…Lang and Lundholm (1996) shows that increasing informational transparency improves forecast accuracy and decreases forecast dispersion and can be used as a measure of earnings forecast error to calculate information asymmetry. Using the method proposed by Christie (1987), the FE was measured as the ratio of absolute difference between forecast earnings ( ) and actual earnings per share ( ) to calculate information asymmetry as:…”

Section: Earning Forecast Error (Fe)mentioning

confidence: 99%