The Residential Solar PV in the Mid-Atlantic: A Spatial Panel Approach

Abstract

This study examines residential solar photovoltaic (PV) adoption in mid-Atlantic counties over the 2005–2016 period. Using a spatial Durbin panel model, we find significant spatial dependence in residential solar PV adoption at the county level. In the presence of spatial dependence, major determinants of the solar adoptions are electricity rates and solar-related policy regulation. The combined direct and indirect effect of electricity rates on solar PV capacity is 5.37 percent increase for a 1 percent increase in electricity price. This spatial coefficient estimate is about twice as large as corresponding panel estimates. We also find that the regulation and incentives significantly boost solar PV demand, which explains about 38 percent variation in residential solar capacity.

Keywords

residential solar PV capacity electricity rates spatial panel

Get full access to this article

View all access options for this article.

References

Anselin

Le Gallo

Hubert

. 2008. “Spatial Panel Econometrics.” In The Econometrics of Panel Data: Fundamentals and Recent Developments in Theory and Practice, edited by Lászlo

Sevestre

, 625–60. Boston, MA: Springer-Verlag.

Balta-Ozkan

Yildirim

Connor

P. M.

. 2015. “Regional Distribution of Photovoltaic Deployment in the UK and Its Determinants: A Spatial Econometric Approach.” Energy Economics 51:417–29.

Bollinger

Gillingham

. 2012. “Peer Effects in the Diffusion of Solar Photovoltaic Panels.” Marketing Science 31:900–12.

Borenstein

2008. “The Market Value and Cost of Solar Photovoltaic Electricity Production.” Center for the Study of Energy Markets Working Paper 176. Accessed November 28, 2019. https://ei.haas.berkeley.edu/research/papers/CSEM/csemwp176.pdf.

Borenstein

2017. “Private Net Benefits of Residential Solar PV: The Role of Electricity Tariffs, Tax Incentives and Rebates.” Journal of the Association of Environmental and Resource Economists 4:S85–122.

Capello

2009. “Spatial Spillovers and Regional Growth: A Cognitive Approach.” European Planning Studies 17:639–58.

Crago

C. L.

Chernyakhovskiy

. 2017. “Are Policy Incentives for Solar Power Effective? Evidence from Residential Installations in the Northeast.” Journal of Environmental Economics and Management 81:132–51.

Dharshing

2017. “Household Dynamics of Technology Adoption: A Spatial Econometric Analysis of Residential Solar Photovoltaic (PV) Systems in Germany.” Energy Research and Social Science 23:113–24.

DSIRE (Database of State Incentives for Renewables and Efficiency). 2019. Accessed November 28, 2019. http://www.dsireusa.org.

10.

Elhorst

2010. “Spatial Panel Data Models.” In Handbook of Applied Spatial Analysis: Software Tools, Methods and Applications, edited by Fischer

Getis

, 377–407. New York: Springler-Verlag.

11.

Elhorst

2014. “Matlab Software for Spatial Panels.” International Regional Science Review 37:389–405.

12.

GATS (Generation Attribute Tracking System). 2019. “Solar Weighted Average Price.” Accessed November 28, 2019. http://www.pjm-eis.com.

13.

Graziano

Gillingham

. 2015. “Spatial Patterns of Solar Photovoltaic System Adoption: The Influence of Neighbors and the Built Environment.” Journal of Economic Geography 15:815–39.

14.

Hughes

J. E.

Podolefsky

. 2015. “Getting Green with Solar Subsidies: Evidence from the California Solar Initiative.” Journal of the Association of Environmental and Resource Economists 2:235–75.

15.

Kosugi

Shimoda

Tashiro

. 2019. “Neighborhood Influences on the Diffusion of Residential Photovoltaic Systems in Kyoto City, Japan.” Environmental Economics and Policy Studies 21:477–505.

16.

Kwan

C. L.

2012. “Influence of Local Environmental, Social, Economic and Political Variables on the Spatial Distribution of Residential Solar PV Arrays across the United States.” Energy Policy 47:332–44.

17.

LeSage

Kelley

P. R.

. 2009. Introduction to Spatial Econometrics. Boca Raton, FL: Chapman & Hall/CRC.

18.

NREL (National Renewable Energy Laboratory). 2014. The Effectiveness of State-level Policies on Solar Market Development in Different State Contexts. Accessed November 28, 2019. https://www.nrel.gov/docs/fy14osti/61029.pdf.

19.

O’Shaughnessy

Nemet

Darghouth

. 2018. “The Geography of Solar Energy in the United States: Market Definition, Industry Structure, and Choice in Solar PV Adoption.” Energy Research and Social Science 38:1–8.

20.

Rogers

2003. Diffusion of Innovations. 5th ed. New York: Free Press.

21.

Schaffer

A. J.

Brun

. 2015. “Beyond the Sun—Socioeconomic Drivers of the Adoption of Small-scale Photovoltaic Installations in Germany.” Energy Research and Social Science 10:220–27.

22.

Solar Energy Industries Association. 2019. “Map Solar State by State.” Accessed November 28, 2019. https://www.seia.org/states-map.

23.

US Census Bureau. 2019. “American Factfinder: A Service of the American Community Survey.” Accessed November 28, 2019. https://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml.

24.

US EIA (US Energy Information Administration). 2018a. “Electric Power Monthly with Data for December 2017.” Accessed November 28, 2019. https://www.eia.gov/electricity/monthly/archive/february2018.pdf.

25.

US EIA (US Energy Information Administration). 2018b. “Monthly Electric Power Industry Report (Form EIA-861 M).” Accessed November 28, 2019. https://www.eia.gov/electricity/data/eia861m//.