In this paper we critically evaluate the standard-setting inferences that can be drawn from value relevance research studies that are motivated by standard setting. Our evaluation concentrates on the theories of accounting, standard setting and valuation that underlie those inferences. Unless those underlying theories are descriptive of accounting, standard setting and valuation, the value-relevance literature's reported associations between accounting numbers and common equity valuations have limited implications or inferences for standard setting; they are mere associations. We argue that the underlying theories are not descriptive and hence drawing standard-setting inferences is difficult.

We estimate a firm-year measure of accounting conservatism, examine its empirical properties as a metric, and illustrate applications by testing new hypotheses that shed further light on the nature and effects of conservatism. The results are consistent with the measure, C_Score, capturing variation in conservatism and also predicting asymmetric earnings timeliness at horizons of up to 3 years ahead. Cross-sectional hypothesis tests suggest firms with longer investment cycles, higher idiosyncratic uncertainty and higher information asymmetry have higher accounting conservatism. Event studies suggest increased conservatism is a response to increases in information asymmetry and idiosyncratic uncertainty.

Using an accounting conservatism theory that reflects accounting's role in practice, we investigate the relation between two extensively used measures of conservatism: asymmetric timeliness of earnings and the market-to-book ratio (MTB). We predict and observe that when asymmetric timeliness is measured cumulatively over long periods, its relation with end-of-period MTB is positive. When asymmetric timeliness is measured over short periods, its dependence on beginning-of-period composition of equity value (EV) is responsible for its negative association with MTB. Further, asymmetric timeliness appears to measure conservatism more efficiently when it is estimated cumulatively over multiple periods.

A model of earnings, cash flows and accruals is developed assuming a random walk sales process, variable and fixed costs, and that the only accruals are accounts receivable and payable, and inventory. The model implies earnings better predict future operating cash flows than current operating cash flows and the difference varies with the operating cash cycle. Also, the model is used to predict serial and cross-correlations of each firm's series. The implications and predictions are tested on a 1337 firm sample over 1963–1992. Both earnings and cash flow forecast implications and correlation predictions are generally consistent with the data.