Jurnal Akuntansi dan Auditing Indonesia (Jun 2009)
The Occurrence of Environmental Disclosures in The Annual Reports
Abstract
This study aims to evaluate whether the occurrence of environmental disclosures in a corporate annual report is associated with a firm environmental visibility. As environmentally visible firms are easier to observe by relevant constituents, they are more vulnerable to public scrutiny. This paper hypothesizes that environmentally visible firms tend to disclose environ-mental information in their annual reports as compared to those of less visible companies. A firm’s environmental visibility is proxied by size, profitability and industry sensitivity to the environment. While firm size is measured by total asset and profitability is measured by return on Asset (ROA), industry sensitivity is measured by the sensitivity of firm activities to the envi-ronment. Industry sectors such as banking, insurance, finance, services are considered as non-sensitive, whereas those of chemical, forestry, mining, automotive, paper and timber, are consid-ered as sensitive sectors. This paper uses the categorization by the Indonesian Accounting Stan-dards (PSAK) No. 32 and 33 which considers forestry and mining firms as the most environmentally sensitive industries by requiring firms in these sectors to report any material information regarding environmental issues. Environmental disclosure in this study is measured by the occurrence of environmental information in the annual reports using a dummy variable (1, if it occurs and 0, otherwise). The sample consists of 205 companies listed on Jakarta Stock Exchange in 2002. It is found that 66 of companies under non-sensitive industries did not mention any environmental information. This study also shows that the occurrence of environmental disclosure in annual reports of Indonesian companies is associated with size and industry sector, but not with profitability. Keywords:   environmental disclosure, environmentally sensitive industry, returns on asset, prof-itability, logistic regression