EconPapers    
Economics at your fingertips  
 

An empirical analysis of county-level residential PV adoption in California

Lado Kurdgelashvili, Cheng-Hao Shih, Fan Yang and Mehul Garg

Technological Forecasting and Social Change, 2019, vol. 139, issue C, 321-333

Abstract: To understand long term PV deployment, it is important to explore the underlying mechanisms that drive PV market diffusion. This paper examines the relationships between several social and economic factors and residential PV market diffusion on a county level. The Bass diffusion model was used to estimate diffusion parameters for 46 counties in California. Regression analysis was then applied to find associations between these parameters and several socio-demographic, economic, and political variables in each county. Finally, a Generalized Bass Model was employed to explore the price effect on PV diffusion. We have found supporting evidence of the inverse relationship between attainment of higher education and the coefficient of imitation. We have clearly shown evidence for heterogeneity between counties in one or more of our observed dimensions, or unobserved and possibly confounding factors. Although not significant at the conventional 5% and 10% levels, our Generalized Bass Model nonetheless supports the presence of price-based fluctuations in adoption rates.

Keywords: PV diffusion; Bass model; Generalized Bass Model; Residential PV; Innovation; Imitation (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162517309307
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:139:y:2019:i:c:p:321-333

DOI: 10.1016/j.techfore.2018.11.021

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:tefoso:v:139:y:2019:i:c:p:321-333