We study the determinants of PV adoption in the region of Flanders (Belgium), where PV adoption reached high levels during 2006-2012, because of active government intervention. Based on a unique dataset at a very detailed spatial level, we estimate a Poisson model to explain the heterogeneity in adoption rates. We obtain the following findings. First, local policies have a robust and significant impact on PV adoption, providing indirect evidence that the larger regional incentives formed the basis for the strong development of PV adoption in the region. Second, there is a strong unconditional income effect, implying a Matthew effect in the subsidization of PVs. Our third finding is however that this income effect is largely driven by the fact that wealthier households are more likely to adopt because they tend to be larger (and hence higher users), are more frequent house owners (who capture more of the benefits), or own houses that are better suited for PV. We can thus identify the channels through which wealthier households are more likely to benefit from the PV support. Finally, we identify the importance of several housing characteristics: PV adoption tends to be more likely in larger and in more recently built houses. In several extensions, we consider the determinants of the average size of installed PVs, and the differential impact of certain variables over time.
We study a generous program to promote the adoption of solar photovoltaic (PV) systems through subsidies on future electricity production, rather than through upfront investment subsidies. We develop a tractable dynamic model of new technology adoption, also accounting for local market heterogeneity. We identify the discount factor from demand responses to variation that shifts expected future but not current utilities. Despite the massive adoption, we find that households significantly discounted the future benefits from the new technology. This implies that an upfront investment subsidy program would have promoted the technology at a much lower budgetary cost. (JEL C51, D15, Q48, Q58)
We study the determinants of PV adoption in the region of Flanders (Belgium), where PV adoption reached high levels during 2006-2012, because of active government intervention. Based on a unique dataset at a very detailed spatial level, we estimate a Poisson model to explain the heterogeneity in adoption rates. We obtain the following findings. First, local policies have a robust and significant impact on PV adoption, providing indirect evidence that the larger regional incentives formed the basis for the strong development of PV adoption in the region. Second, there is a strong unconditional income effect, implying a Matthew effect in the subsidization of PVs. Our third finding is however that this income effect is largely driven by the fact that wealthier households are more likely to adopt because they tend to be larger (and hence higher users), are more frequent house owners (who capture more of the benefits), or own houses that are better suited for PV. We can thus identify the channels through which wealthier households are more likely to benefit from the PV support. Finally, we identify the importance of several housing characteristics: PV adoption tends to be more likely in larger and in more recently built houses. In several extensions, we consider the determinants of the average size of installed PVs, and the differential impact of certain variables over time.
Many countries have relied on subsidies to promote the adoption of renewable energy technologies. We study a generous program to promote the adoption of solar photovoltaic (PV) systems through subsidies on future electricity production, rather than through upfront investment subsidies. We develop and estimate a tractable dynamic model of technology adoption, also accounting for local market heterogeneity. We exploit rich variation at pre-announced dates in the future production subsidies. Although the program led to a massive adoption, we …nd that households signi…cantly undervalued the future bene…ts from the new technology. This implies that an upfront investment subsidy program would have promoted the technology at a much lower budgetary cost, so that the government essentially shifted the subsidy burden to future generations of electricity consumers. (JEL C51, Q48, Q58)
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