Free-Riding in Tax Credits for Home Insulation in France: An Econometric Assessment Using Panel Data

Abstract

This econometric study assesses the efficiency of the income tax credit system implemented in France in 2005 on households' retrofitting investment decisions, focusing on insulation measures. A logit model with random individual effects is estimated using an unbalanced panel of 23,879 households surveyed over the period [2002][2003][2004][2005][2006][2007][2008][2009][2010][2011]. An estimation in difference is performed to identify the impact of the policy. The tax credit had no significant effect during the first two years, suggesting a latency period related to inertia in households' investment decisions, possibly due to the complexity of the tax credit scheme. The tax credit had an increasing, significant positive effect from 2007 to 2010, before slightly decreasing in 2011. This is in line with changes in the tax credit rates, suggesting a correlation with the level of subsidy. Defined as the situation in which the subsidized household would have invested even in the absence of the subsidy, free-riding progressively decreased over the period and was lower for insulation of opaque surfaces (roofs, walls, etc.) than for insulation of windows. The estimated average proportion of free-riders varies between 40% and 85% after 2006. Finally, we assess the potential bias caused by time-varying unobservable variables and conclude that our estimates of the impacts of the policy are conservative. JEL: Q48, R22, D12

Evaluation of financial incentives for green buildings in Canadian landscape

“…Ex-post analysis can be conducted through five major methods [ 11 ]: a top-down approach, bottom-up approach, an amalgamation of top-down and bottom-up approaches, econometric modelling and policy theory. Among these methods, econometric modelling has been most extensively applied and used to study the diffusion of energy conservation technologies, free-riding effect and comparing FIs [ [143] , [144] , [145] , [146] , [147] , [148] ]. However, econometric modelling methods are expensive to implement and need specific data.…”

“…It is quite possible that an incentive has high effectiveness from an end-user's point of view but has a low effectiveness from the society's or program administrator's perspective. Researchers have evaluated effectiveness from the end-users, society and government perspectives [ 10 , 11 , 144 , 145 , 148 , [165] , [166] , [167] , [168] , [169] ]; technical, program administrator and multiple stakeholders perspectives [ 8 , 45 , [170] , [171] , [172] , [173] , [174] , [175] ]; and micro-economic (end-users) and macro-economic (societal) perspectives [ 176 , 177 ].…”

“… Split incentives Particularly important in rental housings where interests of two parties conflict and neither the landlord (due to low ROI) nor the tenant (high initial costs) wants to invest in energy efficiency upgrade [ 119 , [196] , [197] , [198] ] Weak incentives Lack of attractive amount of incentive and connection between the government budget and the energy target needed to be achieved by FIs [ 9 , 11 , 197 , 199 ] Time of implementation Application of FIs at wrong time [ 200 ] Negative impacts of FIs interaction Mitigating impacts are negative interaction between two policy instruments that result in reduced savings [ [201] , [202] , [203] , [204] ] Behavioral impacts Low priority towards energy efficiency (Low resource consumption culture present in most developed countries makes it difficult for FIs to be successful) Free riders (Free-riders are consumers who would have performed energy upgrade regardless of introduction of FIs.) Non-takers (Non-takers are consumers who do not perform energy upgrade even with the introduction of FIs) Rebound effect (Rebound effect results in less energy savings compared to expected due to introduction of FIs and is a source of energy efficiency gap) [ 11 , 21 , 145 , 148 , 163 , 169 , 175 , 191 , 199 ] Other Barriers Tax exemptions High initial investment Long payback periods Transaction costs Limited...…”

“…Behavioral impacts are often complex and constrained by type of adopter (free riders, switchers and non-takers) along with social, economic, and physical parameters [ 212 ]. Free riders and rebound effect are most common behavioral impacts [ 145 , 148 , 169 , 175 , 181 , 191 , 213 , 214 ]. Researchers have also shown that free-ridership problem is more for energy measures that are replaced more frequently; hence, boiler incentive will have higher number of free riders compared to FIs for insulation [ 21 ].…”

Energy efficiency policies for space heating in EU countries: A panel data analysis for the period 1990–2010

“…With regard to financial policies, Nauleau [65] used a panel of over 23,000 French households to analyze the impact of the introduction of a tax credit in 2005; no significant impact was noted for the first 2 years of the scheme, although this changed after 2007. Boonekamp et al [57] reported that across the EU a substantial number of new measures for funding (40%) were introduced after the Energy Services Directive [7] came into force (post-2006).…”