Specification of Models that Estimate Response Coefficients in the Market–Accounting Relation
论证了基于幂律关系的对数线性模型能有效估计市场与会计数据间的长期关系，并利用该模型证明财务报表数据足以解释公司市场价值，同时讨论了股息无关性、市账比与增长及不确定性的关系。
We argue that log‐linear models based on a power‐law relation between market and accounting data, which use elasticities to measure response coefficients in regression models of the fundamental market–accounting relation, are well specified and provide precise, readily interpreted and valid estimates of the long‐run relation between market and accounting values. Using this approach, we show that financial statement data is sufficient, with little or no extra data, to explain fundamental firm market value. We illustrate the use of the measures of elasticity response coefficients by discussing the evidence for dividend irrelevancy, the relationship of the market‐to‐book ratio with growth and its uncertainty, and the existence of abandonment options. Our method of estimating parameters in the market–accounting relation facilitates replication. We use all active Compustat firms between 1971–2020, without deletion or special treatment of outliers, demonstrating the virtues of log‐linear models in capital market research.