Can land use regulations and taxes help mitigate vehicular CO₂emissions? An empirical study of Japanese cities

Abstract

AcknowledgementsWe truly appreciate the constructive comments and suggestions from the anonymous reviewers. This paper was supported by JSPS KAKENHI Grant Number 23730223, 25705007 and by MEXT KAKENHI Grant Number 26000001. 2 AbstractThis study advocates a multi-dimensional urban planning strategy to help combat climate change under local-and not national-policies. However, the literature does not provide adequate guidance to local governments seeking to enhance urbanization and in turn reduce vehicular carbon dioxide (CO2) emissions. Therefore, this study sheds light on the effects of the following four urban planning instruments on vehicular CO2 emissions: urbanization promoting areas, urbanization control areas, urban planning taxes and property taxes. Using Japanese city-level data from 1990 to 2010, we find that the two urbanization area planning instruments and the urban planning taxes help lower emissions by increasing population density in low-density cities and that property taxes help reduce emissions in high-density cities. However, the increased population density associated with these instruments can lead to other negative outcomes, including increased traffic accidents, increased crime and a decrease in the facility condition index. City governments should consider complementary policies to mitigate such negative outcomes when employing planning instruments aiming to increase population density.

How do urban characteristics affect climate change mitigation policies?

“…Glaeser and Kahn (2010) account for social and economic factors in their analysis and find that CO 2 emissions from vehicles are negatively correlated with population density based on data from 66 large cities in the United States. Using Japanese city data from 1990 to 2010, Iwata and Managi (2016) show the same relationship and conclude that urban policies such as property taxes and land use regulations can be used to increase population densities, thereby reducing CO 2 emissions from vehicles.…”

“…In other words, urban policy makers will not refer to a suggested urban policy if it will decrease the flexibility of land use and the attractiveness of the city. From an economic perspective, it is well known that policy options using market mechanisms are more flexible and efficient than restrictive policies (e.g., command and control) (Iwata and Managi, 2016). Based on this idea, we…”

“…Banzhaf and Lavery (2010) note that an increase in land (split) taxes exerts a more constraining influence on city size (urban sprawl) than an increase in property taxes. Iwata and Managi (2016) clarify that property taxes and land use regulations clearly affect population density. To restrict suburban living by applying these land tax and land use regulations, governments can create urban commuting zones.…”

Untangling Urban Sprawl and Climate Change: A Review of the Literature on Physical Planning and Transportation Drivers

“…Cities are already responsible for approximately 80% of the overall GHG/CO 2 emissions [18], while urbanized populations are expected to double, as rural populations level off or decline [19] (p.3133). The Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change identifies urban form as a significant driver for GHG emissions [17].…”

Ten years after Copenhagen: Reimagining climate change governance in urban areas

“…The new wave of urban pragmatism has also involved an intensification of attempts to evaluate policy instruments available for mitigation and adaptation, including control‐and‐demand approaches (Guan & Delman, 2017 ; Lee & Kim, 2018 ; Li, 2013 ; Li & Song, 2016 ), regulation (Castello, 2011 ; Kocabas, 2013 ; Leibowicz, 2017 ), plans (Millard‐Ball, 2012 ), economic instruments and voluntary programs for innovation (Huang‐Lachmann & Lovett, 2016 ; Iwata & Managi, 2016 ), or new participatory tools, such as collaborative visioning (Bailey et al, 2012 ) and social media‐based methods (Napawan, Simpson, & Snyder, 2017 ). We also find attempts to measure and quantify the impacts of plans, discrete policy tools or political leadership, most often in terms of emission reductions (Krause, 2012 ; Lee & Koski, 2012 ; Leibowicz, 2017 ; Millard‐Ball, 2012 ; Park & Page, 2017 ; Simon Rosenthal et al, 2015 ; Wang, 2012 ).…”