Alternative Pollution Control Policies in Developing Countries

By Allen Blackman. Review of Environmental Economics and Policy, 2010

191 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/ec5b8e733b4e67de4057c098e1c91da11192f27c

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Citations in the corpus

LivestockPlus - The sustainable intensification of forage-based agricultural systems to improve livelihoods and ecosystem services in the tropics * (2015, unknown): “Although these measures have long been a popular tool of the public sector to control environmental damage in developed countries, they have proven to be inefficient and ineffective in developing countries (Blackman 2010).”
How do investors respond to Green Company Awards in China (2013, background): “The business benefits of proactive sustainability strategy are less clear in emerging and transition economies, where environmental and social regulationsmay be lacking or poorly enforced, and demand for greener products may be virtually non-existent (Blackman, 2010; Earnhart et al., 2013).”
Show Me the Money: Do Payments Supply Environmental Services in Developing Countries? (2010, background): “Vincent (2010) offers an introduction to the symposium and an overview of key issues; Blackman (2010) focuses on alternative pollution control policies in developing countries; and Somanathan (2010) examines how information affects environmental quality in developing countries. 3There is almost no o”
Does Environmental Information Disclosure Benefit Waste Discharge Reduction? Evidence from China (2014, background): “Blackman (2010) found that expectations of pollution control effects by environmental information disclosure in developing countries cannot be highly appraised because of the weak non-regulatory factors of pollutant discharge reduction, as well as the limited flow of environmental information.”
Economic Perspectives on Corporate Social Responsibility (2012, background): “The disadvantage of observational work in developing country contexts is data quality, and results are therefore often subject to concerns about measurement error, omitted variable bias, and reverse causality (Blackman 2010).”