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Activism through Information: Political Behavior and its Relationship to Environmental Disclosure Programs
Unformatted Document Text:  2 Understanding Information Disclosure Programs: Raising Questions about Available Data and Appropriate Methodologies Abstract: The 1990s and early 2000s have seen a broad expansion of the environmental performance measures in use here in the United States. One measure that has led the way has been the Environmental Protection Agency’s best known information disclosure program – the Toxics Release Inventory (TRI). Though information disclosure programs have been analyzed as to whether they work, less attention has been given to why they work. This study extends our understanding of why the TRI program works through a discussion of the potentially relevant variables, data availability, and potential methodologies to be used. Illustrative examples are included of quantitative and qualitative data from facilities in three northwestern states that are required to submit TRI data. The conclusion is made that defining the dependent variable is not necessarily a straightforward process. Furthermore, qualitative analyses will be critical because quantitative analysis will not be capable of full answering key questions about why environmental information disclosure programs seem to succeed in changing environmental behavior. As we move further into the new millennium, the use of environmental performance measures as tools of environmental policy are moving into new terrain. Though conversations about being “in compliance” still dominate many discussions between the private and public sector, there is a growing understanding that our capacity to measure progress in the areas of environmental conservation, preservation, and restoration has dramatically improved. For example, with some of the new geographical information system (GIS) data that is now becoming available, conservationists more readily understand where ecosystems are being hardest hit, where new regulations are having positive effects, and where work still needs to be done. Mathematical models of global warming trends are becoming more sophisticated and reliable. Data gathering and data collection have also grown more extensive (at least in the

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Understanding Information Disclosure Programs: Raising Questions about
Available Data and Appropriate Methodologies
Abstract: The 1990s and early 2000s have seen a broad expansion of the environmental
performance measures in use here in the United States. One measure that has led the way has
been the Environmental Protection Agency’s best known information disclosure program – the
Toxics Release Inventory (TRI). Though information disclosure programs have been analyzed
as to whether they work, less attention has been given to why they work. This study extends our
understanding of why the TRI program works through a discussion of the potentially relevant
variables, data availability, and potential methodologies to be used. Illustrative examples are
included of quantitative and qualitative data from facilities in three northwestern states that are
required to submit TRI data. The conclusion is made that defining the dependent variable is not
necessarily a straightforward process. Furthermore, qualitative analyses will be critical because
quantitative analysis will not be capable of full answering key questions about why
environmental information disclosure programs seem to succeed in changing environmental
behavior.
As we move further into the new millennium, the use of environmental performance
measures as tools of environmental policy are moving into new terrain. Though conversations
about being “in compliance” still dominate many discussions between the private and public
sector, there is a growing understanding that our capacity to measure progress in the areas of
environmental conservation, preservation, and restoration has dramatically improved. For
example, with some of the new geographical information system (GIS) data that is now
becoming available, conservationists more readily understand where ecosystems are being
hardest hit, where new regulations are having positive effects, and where work still needs to be
done. Mathematical models of global warming trends are becoming more sophisticated and
reliable. Data gathering and data collection have also grown more extensive (at least in the


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