Accounting Comparability and Corporate Innovative Efficiency

Abstract

We predict that a firm's greater accounting comparability with its industry peers facilitates its learning from those peer firms' research and development (R&D) investments, allowing that firm to have greater innovative efficiency. We estimate accounting comparability using pro-forma capitalized R&D earnings that link lagged R&D expenditures to future profitability employing the Almon (1965) distributed lag model. We find that greater accounting comparability leads to enhanced ability to predict future cash flows generated by R&D investments of peer firms. In the cross-section, we observe the relation between accounting comparability and innovative efficiency is stronger if peer firms exhibit higher accounting (accrual) quality and are themselves successful innovators. In sum, this study shows that a shared qualitative characteristic of accounting, namely accounting comparability, is positively associated with innovative efficiency.

The real effect of the initial enforcement of insider trading laws

“…Consistent with this notion, Ozoguz and Rebello (2013) find that a firm's investment is more sensitive to the prices of its peer firms when it is operating in a more competitive product market. Chircop, Collins, and Hass (2016) also provide evidence that the peer learning effect is stronger in more competitive product markets. Thus, to the extent that enforcement improves capital allocation efficiency by enabling stock prices to provide more information to guide managers' decisions, the improvement is expected to be more pronounced for firms that operate in more competitive product markets.…”

Reexaming the Economic Recovery Tax Act of 1981: Evidence From Innovative Efficiency

“…Aghion, Van Reenen and Zingales (2013) find institutional ownership is associated positively with research outputs and efficiency but the effect on efficiency is larger. Chircop, Collins, Hass and Nguyen (2020) show that innovative efficiency increases when a firm's accounting system is more comparable to its industry peers. Both Merz (2021) and Almeida, Hsu, Li and Tseng (2021) find that innovative efficiency is negatively associated with financial constraint.…”

Board diversity and financial statement comparability: evidence from China

“…Greater comparability leads to greater availability of information (to creditors, investors, and regulators), resulting in lower information asymmetry (De Franco et al, 2011 ). Earlier research documented that comparability is negatively associated with the cost of capital (Imhof et al, 2017 ; Kim et al, 2013 ; Majeed & Yan, 2021 ), stock price crash risk (Kim et al, 2016 ), and enhances the flow of information (Choi et al, 2015), facilitates in the efficient deployment of cash, capital and labor and research resources (Chircop et al, 2020 ; Kim et al, 2020 ; Zhang et al, 2020 ), reduces tax avoidance (Majeed & Yan, 2019 ), aids investors in decision making (Chen & Gong, 2019 ; Young & Zeng, 2015 ) and curbs risk-taking by financial institutions (Hasan et al, 2020 ) leading to higher firm value (Neel, 2017 ). Such benefits of comparability motivate to study the governance, institutional, and business factors that nurture this qualitative feature of financial reporting.…”

“…Comparability, according to archival research, improves the accuracy (quality) of accounting information while minimizing the cost of its acquisition and processing (Barth et al, 2012 ; De Franco et al, 2011 ; Zhang, 2018 ). Comparability curtails information asymmetry leading to increased transparency which results in higher innovation efficiency (Chircop et al, 2020 ), efficient allocation of resources (Kim et al, 2020 ), higher stock price informativeness (Choi et al, 2019 ), lower tax avoidance (Majeed & Yan, 2019 ), superior acquisitions (Chen et al, 2018 ), greater relevance of accounting information (Kim et al, 2018 ), decrease the cost of capital (Imhof et al, 2017 ), minimize credit risk (Kim et al, 2013 ), lower stock price crash risk (Kim et al, 2016 ), and forecast accuracy (De Franco et al, 2011 ). However, there are various benefits linked with comparability in the literature (e.g., Chen et al, 2018 ; Chircop et al, 2020 ; Choi et al, 2019 ; Kim et al, 2018 , 2020 ; Zhang et al, 2020 ), only a handful of studies focused on the determinants of comparability (Cao et al, 2016 ; Dhole et al, 2021 ; Francis et al, 2014 ; Imhof et al, 2018 ; Lee et al, 2016 ; Majeed et al, 2018 ).…”