Disaggregated Accounting Data as Explanatory Variables for Returns
Coauthor(s): James Ohlson.
This article explores the differential measurement problems related to the earnings components by invoking the standard errors-in-variables perspective on estimated coefficients. A more traditional way of looking at accounting recognizes the process as one of measurements. That is, the analysis of transactions leads to line items in the financial statements, which in turn aggregate into the bottom line numbers: earnings and book value. The disclosures of the line items clearly suggest that the accountant is aware of the insufficiency of earnings and book values as determinants of values. Earnings derive from line items, and these may have differential valuation implications because investors perceive differential measurement errors. Aggregation is not generally satisfied unless the measurement errors in the line items are relatively insignificant. The coefficients associated with income components that are traditionally considered difficult to measure, depreciation and tax expenses, in particular, do have relatively lower coefficients for the shorter return intervals as compared to other, less problematic, income items. Only as the measurement interval lengthens can expect a reduction in differences of the coefficient magnitudes.
Source: Journal of Accounting, Auditing and Finance
Ohlson, James, and Stephen Penman. "Disaggregated Accounting Data as Explanatory Variables for Returns." Journal of Accounting, Auditing and Finance 7, no. 4 (Fall 1992): 553-573.