The willingness to pay for Renewable Energy Sources (RES): the case of Italy

1. Universityof Perugia DepartmentofEconomics Finance and Statistics The willingness to pay for Renewable Energy Sources (RES): the case of Italy S. Bigerna (Faculty of Economics, UTIU) P. Polinori (Department of Economics, Finance and Statistics, University of Perugia) Washington D.C. October, 9-12 2011 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

2. Universityof Perugia DepartmentofEconomics Finance and Statistics Outline • Introduction • Energy scenario • Method and Data • Empricalfindings • Conclusions 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

3. Universityof Perugia DepartmentofEconomics Finance and Statistics Introduction … today’s economy is mainly based on fossil fuels that are finite and polluting … consequencesregarding the use of fossil energy have become evident In this context RES are essential to reduce harmful emissions and to conserveno renewable resources 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

4. Universityof Perugia DepartmentofEconomics Finance and Statistics Policy Scenario In EU the RES Directive (2009/72/CE) known as “20-20-20”, includes well-known environmental and energy targets for 2020. 20% of emission reduction 20% of total energy satisfied by renewable resources, 20% of energy savings ……….. …….. in reference to EU Directive 2009/72/CE Italian goal is to attain the share of 17% in RES 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

5. Universityof Perugia DepartmentofEconomics Finance and Statistics One important feature of the RES is their high supply-generation cost …. Consequently: ….. high cost prevents the widespread uptake of renewable energy systems ….. But If a positive attitude exists to RES: …... it could affect consumers WTP augmenting the premiums they are potentially apt to pay for such new technology ….. it could potentially reduce the needed amount of public funding. 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

6. Universityof Perugia DepartmentofEconomics Finance and Statistics Coherently with this Energy Scenario the primary purpose of this study is to estimate consumers’ WTP for the development of the RES use in Italy (We made a National Survey) 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

7. Universityof Perugia DepartmentofEconomic, Finance and Statistics Green energy and WTP (State of Art) Several surveys have been performed in the world. These studies are not very comparable because they differ in terms of: • survey periods • countries and institutional context • survey typology • elicitation formats • applied methodology and econometric techniques 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

8. Universityof Perugia DepartmentofEconomic, Finance and Statistics Batley et al. (2001) [U.K.] Nomura and Akay (2004) [Japan] Ivanova (2005) [State of Queensland] Bollino (2009) [Italy] Zografakiset al. (2010) [Crete] Yoo and Kwak (2009) [Korea] …. however by analyzing their empirical results all studies estimated a low WTP if compared with the additional cost due to the respective National Renewable Energy Target. 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

9. Universityof Perugia DepartmentofEconomic, Finance and Statistics Method Let us consider households direct utility function: U = U(Xp, Xg, R) positively related to: the private goods Xp (Xp1, ...., Xpn) the composite public good Xg the public good R (RES use services) 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

10. Universityof Perugia DepartmentofEconomic, Finance and Statistics Xg is a composite commodity of all the others public goods with unit prices and value equal to the tax charged to the households. Households maximise U subject to their budget constraint that is: M = PpXp + Xg where M is the nominal income and Pp is a price vector of private goods 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

11. Universityof Perugia DepartmentofEconomic, Finance and Statistics Each household spends all its disposable income by purchasing private goods: Md = M – Xg Maximization framework provides a set of conditional demand functions: di*(Pp, R, Xg, Md) 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

12. Universityof Perugia DepartmentofEconomic, Finance and Statistics Bysubstituting di* into U we obtain a conditional indirect utility function V(Pp, R, Xg, Md) InvertingV for Md we obtain the conditional expenditure function E* = Md = E*(Pp, R, Xg, U) 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

13. Universityof Perugia DepartmentofEconomic, Finance and Statistics Minimizing both the expenditure relating to private and public goods subject to the utility level we obtain the restricted expenditure function: E = E(Pp, R, Xg, U) Conditionalexpenditurefunction and restrictedexpenditurefunction are relatedasfollows E = E(Pp, R, Xg, U) = E*(Pp, R, Xg, U) + Xg 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

14. Universityof Perugia DepartmentofEconomic, Finance and Statistics By changing the energy scenario we assume that the restricted expenditure function varies accordingto R: R0 = scenario without RES in the energy portfolio R1 = scenario with RES in the energy portfolio 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

15. Universityof Perugia DepartmentofEconomic, Finance and Statistics By holding M as a constant the WTP for the use of RES is given by the compensated surplus (CS): CS = E(Pp, R0, Xg0, U0) - E(Pp, R1, Xg0, U0) CS = [E*(Pp, R0, Xg0, U0) + Xg0] – [E*(Pp, R1, Xg0, U0) + Xg0] CS = E*(Pp, R0, Xg0, U0) – E*(Pp, R1, Xg0, U0) where U0 is the utility level of the household without RES program. This estimate of compensating surplus is a measure of the WTP for “RES use” service 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

16. Universityof Perugia DepartmentofEconomic, Finance and Statistics Cont’ d Method Elicitation format We try to deal with two questions: 1) Consumershavea range of economic values, or a valuation distribution in their mind instead of a single point economicvalueestimation 2) Overestimation of WTP typically occurs in contingent valuation studies 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

17. Universityof Perugia DepartmentofEconomic, Finance and Statistics To dale with the first question we adopt a variant of the payment card approach….. • payment card method is consistent with important guidelines (e.g. U.K. Government guidelines) • many scholars assert that this method could be more intensively employed in CV studies (Champ et al. 2003; O'Garra and Mourato 2007; Atkinson et al. 2005). Payment Card allows us to consider that consumers have a range of economic values in their mind 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

18. Universityof Perugia DepartmentofEconomic, Finance and Statistics To mitigate hypothetical bias Cheap Talk is often used … participants are explicitly warned about hypothetical bias and are asked to respond to the valuation question as if the payment were real However Cheap Talk might have little or no effect on some people 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

19. Universityof Perugia DepartmentofEconomic, Finance and Statistics In order to reduce the overestimation risk …. We adopted a “certainty correction method” proposing five types of acceptance intensity: • “definitely yes” and “definitely no” (DY, DN), • “probably yes” and “probably no” (PY, PN) • “not sure or don’t know” (DK) Consequently we adopt a SPC approach 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

20. Universityof Perugia DepartmentofEconomic, Finance and Statistics 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

21. Universityof Perugia DepartmentofEconomic, Finance and Statistics Cont’ d Method Payment card data may be analyzed in several ways. The choice of which model to use in regression analysis is mainly affected by the data. Three aspects are relevant (Cameron and Huppert 1989; Whitehead et al. 1995; O’Garra and Mourato 2006): 1) the number of zero responses; 2) the size of the intervals; 3) the percentage of data that is point estimates. 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

22. Universityof Perugia DepartmentofEconomic, Finance and Statistics • In our case the limited number of zeros and of point estimated WTP jointly to small size of the intervals suggests we use interval regression method • So …… respondents maximum WTP may lie between the value recorded on the card and the higher value of the next card. 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

23. Universityof Perugia DepartmentofEconomic, Finance and Statistics Cont’ d Method WTP probability associated with the choice of the respondents is: P(ti) = P(tli < WTPi≤ tui) WTP is non-negative and its distribution is skewed we use a lognormal conditional distribution: log WTPi= xi'* β + εi[εi ~ N(0, σ)] 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

24. Universityof Perugia DepartmentofEconomic, Finance and Statistics The probability of choosing ti can be written: P(ti) = Φ [(log tui − xi'*β)/σ]− Φ[(log tli − xi'*β)/σ] where Φ is the standard normal cumulative density function. 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

25. Universityof Perugia DepartmentofEconomic, Finance and Statistics The corresponding log likelihood function can be written: T log L =∑log[Φ[(log tui− xi'*β)/σ]−Φ[(log tli− xi'*β)/σ]] i= 1 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

26. Universityof Perugia DepartmentofEconomic, Finance and Statistics We estimate the optimal values of β and σ, and the mean and median WTP (Cameron and Huppert, 1989; Hanemann and Kanninen, 1999): Median WTP= exp(xi’β) Mean WTP= exp(xi'β) exp (σ2/2 ) and we have computed the confidence interval according to Krinsky and Robb’s simulation model. 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

27. Universityof Perugia DepartmentofEconomic, Finance and Statistics Data In a typical CV study a policy scenario is proposed to interviewees and their WTP to attain it is subsequently elicited. Respondents were asked to consider the benefits to themselves of developing the RES use in Italy. 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

28. Universityof Perugia DepartmentofEconomic, Finance and Statistics Each respondent was confronted with a range of: • general questions concerning RES and their potential development; • questions on knowledge about Italian energy system; • bids in order to support RES development in Italy 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

29. Universityof Perugia DepartmentofEconomic, Finance and Statistics In order to derive WTP a national survey with 1.019 interviews was admnisteredat the end of November 2007 This is a very good period because before 2008-2009…… financial crisis alters the long run consumers perception 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

30. Universityof Perugia DepartmentofEconomic, Finance and Statistics The stratified sample is representative of 46.8 million individuals, residents of Italy, and the survey was conducted by IstitutoPiepoli. The sample is highly representative of Italian populationin terms of: male-female ratio geographical and urban location demographic characteristics education and income distribution 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

31. Universityof Perugia DepartmentofEconomic, Finance and Statistics The profile of the typical interviewee is: men aged 47 highly educated married family with one child income is around 35 000 € home owner About the topic of survey the interviewee believes that the Italian energy scenario will lot worse in the next ten years, he knows the RES, his knowledge is really accurate and he consider RES a strategic opportunity for Italy. 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

32. Universityof Perugia DepartmentofEconomic, Finance and Statistics Empirical findings 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

33. Universityof Perugia DepartmentofEconomic, Finance and Statistics As expected, the results show that: • the proportion of respondents who are willing to pay decreases with the amount submitted • the proportion is larger when “yes category” includes also PY and DK responses • this is especially evident at the right most end of the tail, for amounts greater than € 5 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

35. Universityof Perugia DepartmentofEconomic, Finance and Statistics Main findings: • knowledge of RES and conviction that RES could play an important role in Italian energy scenario positively affects the WTP • higher level of education and a better employment (which proxies higher income) are associated, coeteris paribus, with higher WTP • men are willing to pay less ifcomparedwith women • olderrespondents are willing to pay less ifcomparedtoyoungerones…… 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

36. Universityof Perugia DepartmentofEconomic, Finance and Statistics • residents in North and Center Italy exhibit a higher WTP • people who live in municipalities greater than 100,000 inhabitants are willing to pay less • household size influences negatively the WTP • “actingconsistently” has a negative influence on the WTP 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

37. Universityof Perugia DepartmentofEconomic, Finance and Statistics Finally • Based on the estimated parameters it is possible to compute the mean and median WTP of the sample, and then to compute the total WTP for Italy Tot WTP = WTP(monthly) x 2 x 6(Bimonthly bill) x Nr. households • The total WTP may be compared with the total annual subsidy needed in Italy to comply with the EUclimate change package goals by 2020 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

38. Universityof Perugia DepartmentofEconomic, Finance and Statistics 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

39. Universityof Perugia DepartmentofEconomic, Finance and Statistics Conclusions We can see that a measure of the market sustainability of RES , i.e. the cover capacity range, lies between 19% and 37%, according to different estimation models….. however: • wefind a substantial willingness of consumers to partially cover the cost of RES • uncertainty plays a crucial role counting for 8% -19% of the annual goal (Choice of the SPC OK) 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

40. Universityof Perugia DepartmentofEconomic, Finance and Statistics • in table 6 we consider the full incremental cost that we arbitrarily ascribe entirely to the “small consumers” (eglow voltageclients). Maybeifweconsiderall the clients, market sustainabilitycouldnoticeablyincrease • ifweconsider the currentburdenpaiedbyitalianhouseholdswenoticethatthe actual additional cost due actually to renewables is less than all the elicitedvalues in ourmodels 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

41. Universityof Perugia DepartmentofEconomic, Finance and Statistics Thismeansthat: --a further margin could exist in the Italian context; -- Italians (Are? Were? -2007-) ready to pay more for RES according to the European target PerhapsItaliancitizensneedappropriate information and education campaigns finalized to: a) better explaining all the advantages linked to the renewable energy use b) reducing erroneous evaluations on the costs of renewable energies 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research

42. Universityof Perugia DepartmentofEconomic, Finance and Statistics Thanksforattention ... suggestions and questions are welcome polpa@unipg.it 30thUSAEE/IAEE Conference: Changing Roles of Industry, Government and Research