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Hurdles and steps: Estimating demand for solar photovoltaics

Hurdles and steps: Estimating demand for solar photovoltaics. Kenneth Gillingham, Tsvetan Tsvetanov. This paper estimates demand for residential solar photovoltaic (PV) systems using a new approach to address three empirical challenges that often arise with count data: excess zeros, unobserved heterogeneity, and endogeneity of price.

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Hurdles and steps: Estimating demand for solar photovoltaics

While several prominent recent papers on solar PV adoption have used reduced form approaches, rather than dynamic discrete choice models (see, e.g., Rogers and Sexton (2014), Hughes and Podolefsky (2015)), many economists may instinctively consider the purchase of a solar PV system as a "buy-or-wait" decision that is best modeled with a

Hurdles And Steps: Estimating Demand For Solar Photovoltaics

Kenneth Gillingham, Tsvetan Tsvetanov, "Hurdles And Steps: Estimating Demand For Solar Photovoltaics", Quantitative Economics, Volume 10, Issue 1 (January 2019), DOI: 10.3982/QE919

Hurdles and Steps: Estimating Demand for Solar Photovoltaics

Hurdles and Steps:Estimating Demand for Solar Photovoltaics Tsvetan Tsvetanov, Yale UniversityKenneth Gillingham, Yale UniversityNovember 12, 2014JOB MARKET PAPER: AbstractIn light of the steadily Public Policy

Hurdles and steps: Estimating demand for solar photovoltaics

Quantitative Economics 10 (2019) Estimating demand for solar photovoltaics 277 At the basis of our approach is the conditional maximum likelihood (CMLE) estima-tor for ﬁxed effects logit models introduced in a sequence of works by Rasch (1960, 1961), Andersen (1972), and Chamberlain (1980). Majo and van Soest (2011) show that this con-

Hurdles And Steps: Estimating Demand For Solar Photovoltaics

Hurdles And Steps: Estimating Demand For Solar Photovoltaics Loading... Publication. Hurdles And Steps: Estimating Demand For Solar Photovoltaics. Gillingham, Kenneth ; Tsvetanov,

Hurdles and steps: Estimating demand for solar photovoltaics

This paper estimates demand for residential solar photovoltaic (PV) systems using a new approach to address three empirical challenges that often arise with count data: excess zeros,

Hurdles and steps: Estimating demand for solar photovoltaics

This paper estimates demand for residential solar photovoltaic (PV) systems using a new approach to address three empirical challenges that often arise with count data: excess zeros, unobserved heterogeneity, and endogeneity of price.

Hurdles and Steps: Estimating Demand for Solar Photovoltaics

Hurdles and Steps: Estimating Demand for Solar Photovoltaics Kenneth Gillingham Yale University, School of Forestry & Environmental Studies K. Gillingham, T. Tsvetanov Demand for Solar Photovoltaics November 6, 2015 2 / 32. Background Motivation Data Estimation Results Conclusion Addressing Excess Zeros in Data

Hurdles and steps: Estimating demand for solar photovoltaics

This paper estimates demand for residential solar photovoltaic (PV) systems using a new approach to address three empirical challenges that often arise with count data: excess zeros, unobserved heterogeneity, and endogeneity of price.

Hurdles and steps: Estimating demand for solar photovoltaics

We estimate a price elasticity of demand for a PV system of-0.65, a ﬁnding useful to both policymakers and ﬁrms. Policymakers are often interested in how changes in PV system prices—whether due to policy or other factors—inﬂuence the sales of PV systems. Such knowledge is essential for assessing the impacts of solar PV policies.

Supplement to ''Hurdles and steps: Estimating demand for

While several prominent recent papers on solar PV adoption have used reduced form approaches, rather than dynamic discrete choice models (see, e.g., Rogers and Sexton (2014), Hughes and Podolefsky (2015)), many economists may instinctively consider the purchase of a solar PV system as a "buy-or-wait" decision that is best modeled with a

How do we estimate a hurdle model based on data generating processes?

We estimate a hurdle model based on two data generating processes: a standard logit for whether a block group has at least one adoption and a zero-truncated Poisson that models the rate of adoptions conditional on a block group having an adoption.

Would a $1/W decrease in PV installation price increase demand?

At the average system price and number of installations in our sample, this elasticity estimate suggests that a $1/W decrease in the installation price (well within the variation in our data) would lead to an increase in demand of approximately 0.083 additional PV systems in each block group during the respective year.

Hurdles and Steps: Estimating Demand for Solar Photovoltaics

Our results imply a price elasticity of demand for solar PV systems of -0.65. Counterfactual policy simulations indicate that reducing state financial incentives in half would have led to 9 percent fewer new installations in Connecticut in 2014. Hurdles and Steps: Estimating Demand for Solar Photovoltaics (January 30, 2018). USAEE Working

Hurdles and Steps: Estimating Demand for Solar Photovoltaics

This paper estimates demand for residential solar photovoltaic (PV) systems using a new approach to address three empirical challenges that often arise with count data: excess zeros, unobserved heterogeneity, and endogeneity of price. Our results imply a price elasticity of demand for solar PV systems of −0.65. Counterfactual policy simulations indicate that

Hurdles and Steps: Estimating Demand for Solar Photovoltaics

Large-scale integration of invisible solar photovoltaic generation into power systems could significantly affect the system net load and pose new challenges in the operation of

Hurdles and steps: Estimating demand for solar photovoltaics

A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.The file type is

Hurdles and steps: Estimating demand for solar photovoltaics

Abstract: This paper estimates demand for residential solar photovoltaic (PV) systems using a new approach to address three empirical challenges that often arise with count data: excess

Hurdles and Steps: Estimating Demand for Solar Photovoltaics

The California Solar Initiative (CSI) rebate program disbursed more than two billion dollars in incentives to install solar photovoltaics (PV) over roughly a decade (2007-2016); a large proportion

What is the price elasticity of demand for solar PV systems in CT?

We estimate the price elasticity of demand for solar PV systems in CT over 2008–2014 to be −0.65. This estimate is valuable to both policymakers and firms. As module prices continue to drop, it provides useful guidance for forecasting the number of new installations, absent policy changes.

Hurdles and steps: Estimating demand for solar photovoltaics

This paper estimates demand for residential solar photovoltaic (PV) systems using a new approach to address three empirical challenges that often arise with count data: excess zeros, unobserved heter...

Hurdles and Steps: Estimating Demand for Solar Photovoltaics

Key takeaway: ''The Poisson hurdle approach effectively estimates demand for residential solar photovoltaic systems, with a price elasticity of 0.65 and a potential 9% fewer new installations in Connecticut if state financial incentives were reduced.'' Hurdles and Steps: Estimating Demand for Solar Photovoltaics. K. Gillingham, Tsvetan G

Can a hurdle model predict solar demand?

This suggests that the hurdle model, as a mix of components that can exploit both binary and zero-truncated count data variation, offers a flexible approach for estimating solar demand in various settings: from emerging markets with few installations to booming higher-demand markets.

Is solar PV demand a "buy-or-wait" decision in CT?

However, we provide survey and descriptive evidence in Online Appendix A of the Supplemental Material (Gillingham and Tsvetanov ( 2019 )) suggesting that solar PV demand in CT is more similar to the many other contexts where consumers do not appear to treat adoption as a dynamic "buy-or-wait" decision.

Hurdles and Steps: Estimating Demand for Solar Photovoltaics

This paper estimates demand for residential solar photovoltaic (PV) systems using a new approach to address three empirical challenges that often arise with count data: excess

Hurdles and steps: Estimating demand for solar photovoltaics

1 Introduction. The market for rooftop solar photovoltaic (PV) systems has been growing rapidly around the world in the past decade. In the United States, there has been an increase in new installed capacity from under 500 MW in 2008 to over 4500 MW in 2013, along with a decrease in average (preincentive) PV system prices from over $8/W in 2008 to just above $4/W in 2013

Hurdles and steps: Estimating demand for solar

This paper estimates demand for residential solar photovoltaic (PV) systems using a new approach to address three empirical challenges that often arise with count data: excess zeros, unobserved

About Hurdles and steps estimating demand for solar photovoltaics

About Hurdles and steps estimating demand for solar photovoltaics

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