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PurposeThe objective of this study is to examine how the heterogeneity of the institutional environments within a single country influences International Financial Reporting Standards (IFRS) convergence and earnings quality based on a meso- and multi-level approach.Design/methodology/approachUsing hierarchical linear modeling (HLM) to capture the between-group heteroskedasticity and within-cluster interdependence, this study investigates the simultaneous effect by incorporating institutional factors residing at different hierarchical levels and the interaction effects of factors within the same level on IFRS convergence and earnings quality in the largest IFRS adopter, China.FindingsThe results show that after IFRS convergence (i.e. 2007–2015), earnings quality decreases in terms of conservatism. However, the further analysis indicates that the strong institutional environment could mitigate the negative impact of IFRS on conservatism.Originality/valueConsistent with the emphasis of heterogeneity within a country by Terracciano et al. (Science, 2005, 310 (5745)), this study indicates that the heterogeneity in the institutional environments and the simultaneous effect of the multilevel institutional environments within a single country cannot be ignored. This study also indicates that, equally important, research methodology plays a substantial role in investigating the outcomes of IFRS convergence. Finally, this study, based on an integrated theory, adopts a meso-paradigm linking macro- and micro-level institutions to provide comprehensive insights into IFRS convergence and conservatism.

The question of whether environmental regulation stimulates innovation activities has long been important and controversial. This study explores an ideal setting, the low-carbon city pilot program conducted by the Chinese government as a quasi-natural experiment to address this question. We conduct a difference-in-differences approach to analyze the impact of environment regulation on R&D investment. We find that the program’s adoption has led to an increase in R&D investment of 0.145% as a percentage of total assets and 0.273% as a percentage of sales, indicating a positive effect of environmental regulation on R&D expenditures. The increase in R&D expenditures is greater for firms experiencing a larger increase in government subsidies, a greater decline in corporate tax or a greater improvement in financial condition following the low-carbon pilot program. A series of robustness tests support a causal interpretation of our findings and indicate that the observed effect of the low-carbon pilot program on corporate R&D investment is unlikely driven by chance. Our results provide in-depth insights into the economic consequences of low-carbon regulation policies which could be of interest to academic researchers and policymakers.

There has been a significant worldwide movement to adopt International Financial Reporting Standards (IFRS), which are more principles‐based compared to many of the more rules‐based national accounting standards that they replaced. The majority of previous studies focus on how this financial reporting environment change influences earnings quality, while there has been limited research on how auditors respond to IFRS. We perform an experiment using Chinese professional auditors to test the joint effects of the type of accounting standards and the strength of the financial regulatory regime on both the quantity and quality of auditors' evidence demands. We find that auditors are likely to have more evidence demands and, particularly, more diagnostic evidence demands under principles‐based accounting standards. This influence is more pronounced under the stronger financial regulatory regime. The effect of the institutional environment on IFRS standards is an important international reporting topic particularly for emerging markets like China where there is strong economic growth with an increased focus on reporting standards and regulation. China is an ideal environment to examine this topic because it is the largest country in the world to adopt IFRS, and many Chinese auditors have experienced both rules‐ and principles‐based accounting standards.

This study uses an ideal setting to capture the influence of the national institutional environment on outcomes (i.e., earnings quality) of IFRS convergence using a within‐country approach. We show that earnings quality in terms of discretionary accruals and persistence has increased, while conservatism has decreased after IFRS convergence. The results are more pronounced in companies with a strong institutional environment. Our results are robust after considering incentives and other confounding factors. Our findings show differences in earnings quality in firms within a country adopting the same standards, let alone in firms worldwide. This indicates the context embeddedness of accounting standards.

This study contributes to the low-carbon city (LCC) related literature by providing causal evidence on the impact of carbon reduction regulation on firm risk. Using staggered adoption of LCC program shocks in China as a quasi-natural experiment, we implement a difference-in-differences (DiD) analysis to investigate the impact of the low-carbon city initiatives on firm risk. We find that low-carbon city initiatives are significantly correlated with firm total risk, systematic risk, and idiosyncratic risk. The results are more pronounced for firms with greater changes of investment in fixed assets and R&D and for firms in provinces with stronger legal enforcement. Our study provides in-depth insights into the low-carbon city initiatives and the firm-level impact of its implementation.

This study describes a novel rat whole embryo culture (rWEC) teratogenicity assay that applies a simplified experimental design and statistical prediction model, resulting in reduced animal requirements and increased throughput with low prediction error rate for classifying teratogenic potential of compounds. A total of 70 compounds (38 teratogens and 32 nonteratogens) were evaluated, and the prediction model was generated from a dataset of 59 compounds. The rWEC assay requires only one test concentration (1μM) and three structural endpoints (group average morphological scores of spinal cord, heart, and number of somite pairs), which are used in a recursive partition model for classifying teratogenic liability. The model fitting concordance between the WEC assay and in vivo outcome was 83% with a standard deviation (SD) of 4.9%. The predictivity for future compounds was evaluated by using two statistical methods. Fivefold cross-validation estimated the predictivity of this model at 73% (SD 5.8%). A second estimation of predictivity was obtained from an independent test set of 11 compounds that were not used to build the prediction model and reached 82% (SD 11.6%). The overall estimate for prediction concordance is 74% (SD 5.2%). There is no statistically significant difference (p value > 0.50) in the predictivity between this model and the model supporting European Center for the Validation of Alternative Methods WEC assay with predictivity of 80% (SD 10.6%). Overall, the streamlined WEC assay is estimated to reduce animal use and operational costs by more than 50%. It substantially improves results turnaround with no loss of predictivity.