Environmental regulation and the productivity of Japanese manufacturing industries

Hamamoto, Mitsutsugu

doi:10.1016/j.reseneeco.2005.11.001

Cited by 483 publications

(290 citation statements)

References 16 publications

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“…They do not, however, find evidence of an effect of pollution-control expenditure on overall patenting. Hamamoto (2006) finds similar effects on R&D spending in Japan. Brunneimer and Cohen (2003) estimate the relationship between PACE and environmental patents across various US industries.…”

Section: Empirical Evidence On Induced Innovation In Pollution Abatemmentioning

confidence: 78%

Energy, the Environment, and Technological Change

Popp

Newell

Jaffe

2010

Handbook of the Economics of Innovation

340

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Section: Empirical Evidence On Induced Innovation In Pollution Abatemmentioning

confidence: 78%

Energy, the Environment, and Technological Change

Popp

Newell

Jaffe

2010

Handbook of the Economics of Innovation

340

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“…Such data inform on the level of financial effort a given firm/sector has to face to comply with given standards (Lanjouw and Mody, 1996;Jaffe and Palmer, 1997;Berman and Bui, 2001;Hamamoto, 2006;Rubashkina et al, 2014). The use of this indicator is based on the assumption that profit maximizing firms typically face marginal abatement costs that are increasing in pollution abatement.…”

Section: Literature Reviewmentioning

confidence: 99%

Environmental policy performance and its determinants: Application of a three-level random intercept model

et al. 2018

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We propose the use of a three-level random intercept model to measure the degree of environmental policy performance of different countries and to study its determinants. Inspired by the literature on multilevel latent models and Item Response Theory (IRT), this framework treats policy commitment as a latent variable which is estimated conditional on the difficulty of the policy portfolio implemented by each country. We contribute to the study and scoring of environmental and energy policies in three main ways. First, the model results in a ranking of countries which is conditional on the complexity of their chosen policy portfolio. Second, we provide a unified framework in which to construct a policy indicator and to study its determinants through a latent regression approach. The resulting country ranking can thus be cleaned from the effect of economic and institutional observables which affect policy design and implementation. Third, the model estimates parameters which can be used to describe and compare policy portfolios across countries. We apply this methodology to the case of energy efficiency policies in the industrial sectors of 29 EU countries between 2004 and 2011. We conclude by highlighting the future possible applications of this approach, which are not confined to the realm of environmental and energy policy.

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“…However, he does not find a significant impact of pollution abatement costs on TFP growth in his cross-sectional analysis for U.S. industries. In contrast, a recent study undertaken by Hamamoto (2006) suggests that pollution control expenditures measured at the industry level for Japan positively affect TFP growth via a stimulation of R&D investment. Our study is most closely related to Shadbegian and Gray (2005) that introduce PACE data into a production function approach at the U.S. plant level for pulp and paper mills, oil refineries, and steel mills.…”

Section: Introductionmentioning

confidence: 76%

Clean and Productive? Evidence from the German Manufacturing Industry

et al. 2008

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Abstract:In this paper, we analyze the productivity effects of environment-and energyrelated expenditure and investment activities. For this purpose, we follow a production function approach accounting for environmental investment as well as environmental and energy expenditures as capital inputs, and making use a panel dataset of the German manufacturing industry between 1996 and 2002. Our estimations show only week evidence for a significant contribution of both environmental and energy expenditures for production growth. In contrast, environmental investment positively impacts on productivity. Our results therefore suggest that environmental performance, measured with environmental investment, may be a productivity driver. Given this, environmental regulation does not necessarily slow down production growth. In order to be compatible with economic goals such as productivity, however, it should stimulate investment.

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Environmental regulation and the productivity of Japanese manufacturing industries

Cited by 483 publications

References 16 publications

Energy, the Environment, and Technological Change

Energy, the Environment, and Technological Change

Environmental policy performance and its determinants: Application of a three-level random intercept model

Clean and Productive? Evidence from the German Manufacturing Industry

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