Start Date

12-13-2015

Description

Data standardization is a widely recommended solution to improving data quality. Despite the potential benefits, we examine if it has any unintended, especially undesirable, side effects on data quality. The eXtensible Business Reporting Language (XBRL) is an XML-based open standard that aims to facilitate the preparation, exchange and comparison of financial reports. Leveraging the unique opportunity created by the exogenous mandatory XBRL adoption enforced by the U.S. SEC, we use a difference-in-differences (DID) research design to establish the causal relationship between XBRL adoption and quality of HTML-formatted financial reports, an important source for investors and analysts to obtain firms’ financial information. Surprisingly, we find the mandatory XBRL adoption has degraded the quality of the adopting firms’ HTML-formatted financial reports, as measured by a number of data quality metrics, including spelling errors and readability. The U.S. SEC and adopting firms need design appropriate policies to minimize the undesirable side effects.

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Dec 13th, 12:00 AM

Data Standardization and Quality Degradation of Human-readable Data

Data standardization is a widely recommended solution to improving data quality. Despite the potential benefits, we examine if it has any unintended, especially undesirable, side effects on data quality. The eXtensible Business Reporting Language (XBRL) is an XML-based open standard that aims to facilitate the preparation, exchange and comparison of financial reports. Leveraging the unique opportunity created by the exogenous mandatory XBRL adoption enforced by the U.S. SEC, we use a difference-in-differences (DID) research design to establish the causal relationship between XBRL adoption and quality of HTML-formatted financial reports, an important source for investors and analysts to obtain firms’ financial information. Surprisingly, we find the mandatory XBRL adoption has degraded the quality of the adopting firms’ HTML-formatted financial reports, as measured by a number of data quality metrics, including spelling errors and readability. The U.S. SEC and adopting firms need design appropriate policies to minimize the undesirable side effects.