Subsidies for Close Substitutes: Evidence from Residential Solar Systems

Abajian, Alexander and Pretnar, Nick (2023): Subsidies for Close Substitutes: Evidence from Residential Solar Systems.

Abstract

Policies promoting residential solar system adoption are designed assuming the associated generation displaces retail electricity purchases on a one-for-one basis. This assumption is not innocuous; electricity from residential solar systems is unlikely to be perfectly substitutable with grid electricity. We estimate a model of U.S. residential electricity demand allowing for spatial heterogeneity and imperfect substitution between forms of electricity to quantify the implications for green energy subsidization. We find subsidies inducing one kWh of residential solar electricity demand displace only 0.5 kWh of grid consumption. As an emissions reduction policy subsidies had national abatement costs of $332 per MTCO2 in 2018.

• Item Type: MPRA Paper
• Language: English
• Keywords: Residential PV systems, residential electricity demand, rebound effects, energy subsidies
• Subjects: H - Public Economics > H2 - Taxation, Subsidies, and Revenue > H23 - Externalities ; Redistributive Effects ; Environmental Taxes and Subsidies; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q42 - Alternative Energy Sources; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q48 - Government Policy; R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R2 - Household Analysis > R23 - Regional Migration ; Regional Labor Markets ; Population ; Neighborhood Characteristics

References

Barbose, Galen et al. (2019). “Tracking the Sun: Pricing and Design Trends for Dis- tributed Photovoltaic Systems in the United States-2019 Edition” (cit. on pp. 3, 15).

Barbose, Galen L et al. (2020). Income Trends among US Residential Rooftop Solar Adopters. Tech. rep. Lawrence Berkeley National Lab.(LBNL), Berkeley, CA (United States) (cit. on p. 4).

Bollinger, Bryan and Kenneth Gillingham (2012). “Peer effects in the diffusion of solar photovoltaic panels”. Marketing Science 31.6, pp. 900–912 (cit. on p. 4).

Borenstein, Severin (2017). “Private net benefits of residential solar PV: The role of electricity tariffs, tax incentives, and rebates”. Journal of the Association of Environ- mental and Resource Economists 4.S1, S85–S122 (cit. on pp. 4, 18, 35).

Borenstein, Severin and James B Bushnell (2022). “Do two electricity pricing wrongs make a right? Cost recovery, externalities, and efficiency”. American Economic Journal: Economic Policy 14.4, pp. 80–110 (cit. on pp. 11, 32).

Borenstein, Severin and Lucas W Davis (2016). “The distributional effects of US clean energy tax credits”. Tax Policy and the Economy 30.1, pp. 191–234 (cit. on pp. 4, 35).

Buchsbaum, Jesse (2023). “Long-Run Price Elasticities and Mechanisms: Empirical Evidence from Residential Electricity Consumers” (cit. on p. 35).

Callaway, Duncan S, Meredith Fowlie, and Gavin McCormick (2018). “Location, lo- cation, location: The variable value of renewable energy and demand-side effi- ciency resources”. Journal of the Association of Environmental and Resource Economists 5.1, pp. 39–75 (cit. on pp. 5, 27, 32).

Chan, Nathan W and Kenneth Gillingham (2015). “The microeconomic theory of the rebound effect and its welfare implications”. Journal of the Association of Environ- mental and Resource Economists 2.1, pp. 133–159 (cit. on p. 12).

Crago, Christine Lasco and Ilya Chernyakhovskiy (2017). “Are policy incentives for solar power effective? Evidence from residential installations in the Northeast”. Journal of Environmental Economics and Management 81, pp. 132–151 (cit. on p. 32).

Cruz, Jose ́-Luis and Esteban Rossi-Hansberg (2022). Local Carbon Policy. Tech. rep. National Bureau of Economic Research (cit. on p. 33).

Cullen, Joseph (2013). “Measuring the environmental benefits of wind-generated electricity”. American Economic Journal: Economic Policy 5.4, pp. 107–133 (cit. on p. 27).

Dauwalter, Travis E and Robert I Harris (2023). “Distributional Benefits of Rooftop Solar Capacity”. Journal of the Association of Environmental and Resource Economists 10.2, pp. 487–523 (cit. on pp. 4, 5, 27, 32).

De Groote, Olivier and Frank Verboven (2019). “Subsidies and time discounting in new technology adoption: Evidence from solar photovoltaic systems”. American Economic Review 109.6, pp. 2137–72 (cit. on pp. 4, 18).

EIA (2020). “Monthly energy review”. DOE/EIA-0035 (2020/9). Office of Energy Statis- tics, US Department of Energy Washington (cit. on p. 3).

Flowers, Mallory E et al. (2016). “Climate impacts on the cost of solar energy”. En- ergy Policy 94, pp. 264–273 (cit. on p. 17).

Gillingham, Kenneth and James H Stock (2018). “The cost of reducing greenhouse gas emissions”. Journal of Economic Perspectives 32.4, pp. 53–72 (cit. on p. 5).

Gillingham, Kenneth and Tsvetan Tsvetanov (2019). “Hurdles and steps: Estimating demand for solar photovoltaics”. Quantitative Economics 10.1, pp. 275–310 (cit. on pp. 4, 18, 29, 32).

Graziano, Marcello and Kenneth Gillingham (2015). “Spatial patterns of solar photo- voltaic system adoption: the influence of neighbors and the built environment”. Journal of Economic Geography 15.4, pp. 815–839 (cit. on p. 5).

Hughes, Jonathan E and Molly Podolefsky (2015). “Getting green with solar sub- sidies: evidence from the California solar initiative”. Journal of the Association of Environmental and Resource Economists 2.2, pp. 235–275 (cit. on p. 4).

IRS, Internal Revenue Service (2019). “Statistics of Income - Individual Income Tax Returns, Line Item Estimates” (cit. on p. 18).

Ito, Koichiro (2014). “Do consumers respond to marginal or average price? Evidence from nonlinear electricity pricing”. American Economic Review 104.2, pp. 537–63 (cit. on p. 11).

Kulmer, Veronika and Sebastian Seebauer (2019). “How robust are estimates of the rebound effect of energy efficiency improvements? A sensitivity analysis of con- sumer heterogeneity and elasticities”. Energy Policy 132, pp. 1–14 (cit. on p. 12).

Lamp, Stefan and Mario Samano (2023). “(Mis) allocation of Renewable Energy Sources”. Journal of the Association of Environmental and Resource Economists 10.1, pp. 195–229 (cit. on pp. 5, 33).

Langer, Ashley and Derek Lemoine (2022). “Designing dynamic subsidies to spur adoption of new technologies”. Journal of the Association of Environmental and Re- source Economists 9.6, pp. 1197–1234 (cit. on p. 4).

Lewbel, Arthur (1989). “Exact aggregation and a representative consumer”. The Quar- terly Journal of Economics 104.3, pp. 621–633 (cit. on p. 11).

— (2001). “Demand Systems with and without Errors”. American Economic Review 91.3, pp. 611–618 (cit. on p. 15).

Lyu, Xueying (Forthcoming). “Are Electric Cars and Solar Panels Complements?” Journal of the Association of Environmental and Resource Economists (cit. on pp. 18, 35).

Mu ̈ller,SvenandJohannesRode(2013).“Theadoptionofphotovoltaicsystemsin Wiesbaden, Germany”. Economics of Innovation and New Technology 22.5, pp. 519– 535 (cit. on p. 4).

O’Shaughnessy, Eric et al. (2021). “The impact of policies and business models on income equity in rooftop solar adoption”. Nature Energy 6.1, pp. 84–91 (cit. on p. 4).

Pless, Jacquelyn and Arthur A van Benthem (2019). “Pass-through as a test for mar- ket power: An application to solar subsidies”. American Economic Journal: Applied Economics 11.4, pp. 367–401 (cit. on pp. 4, 18, 29).

Qiu, Yueming, Matthew E Kahn, and Bo Xing (2019). “Quantifying the rebound ef- fects of residential solar panel adoption”. Journal of Environmental Economics and Management 96, pp. 310–341 (cit. on pp. 12, 26).

Sexton, Steven et al. (2021). “Heterogeneous solar capacity benefits, appropriability, and the costs of suboptimal siting”. Journal of the Association of Environmental and Resource Economists 8.6, pp. 1209–1244 (cit. on pp. 5, 27, 32).

Wiser, Ryan and Dev Millstein (2020). “Evaluating the economic return to public wind energy research and development in the United States”. Applied Energy 261, p. 114449 (cit. on p. 4).

Wolske, Kimberly S, Kenneth T Gillingham, and P Wesley Schultz (2020). “Peer in- fluence on household energy behaviours”. Nature Energy 5.3, pp. 202–212 (cit. on p. 5).

Yu, Jiafan et al. (2018). “DeepSolar: A machine learning framework to efficiently construct a solar deployment database in the United States”. Joule 2.12, pp. 2605– 2617 (cit. on pp. 4, 6, 7).