Information disclosure policy: Do state data processing efforts help more than the information disclosure itself?

Hyunhoe Bae, Peter Wilcoxen, David Popp

Research output: Contribution to journalArticle

32 Citations (Scopus)

Abstract

The Toxics Release Inventory (TRI) was expected to reduce health risks stemming from emissions of hazardous chemicals by increasing public pressure on polluters. However, raw TRI data fails to transmit accurate information fitted to the public's interest. TRI is a massive and complex data set that, in its raw form, provides information on the pounds of toxics released, rather than the risks these releases pose to human health, which is the true quantity of interest. Consequently, raw TRI data needs to be refined and interpreted in terms of health risks by its users, which requires analytical sophistication and substantial data processing. State governments have attempted to increase of the usefulness of the TRI to the general public via two types of policies: (1) selection and dissemination of raw TRI data for plants within the state, and (2) data processing activities producing more refined reports and further data analysis. This study assesses the effectiveness of those two policies, asking how much each contributes to the intended policy outcome of reducing health risks. Our results show that state-level data dissemination efforts lowered the total number of pounds of chemicals released, but had little effect on health risks. State-level data processing efforts, in contrast, did lead to significant reductions in health risks. We conclude that simple dissemination of the data was ineffective (and even counterproductive in some instances), and that the states' data processing efforts have played a critical role in achieving the TRI's intended policy goal by providing better information to end users.

Original languageEnglish
Pages (from-to)163-182
Number of pages20
JournalJournal of Policy Analysis and Management
Volume29
Issue number1
DOIs
Publication statusPublished - 2010 Dec 1

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All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting(all)
  • Sociology and Political Science
  • Public Administration

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