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  1. Distributional and welfare impacts of renewable subsidies in Italy
    Autor*in: Distante, Roberta; Verdolini, Elena; Tavoni, Massimo
    Erschienen: 2016
    Verlag:  Fondazione Eni Enrico Mattei, Milano

    We empirically assess the distributional impacts and welfare effects of policies to incentivize renewable electricity production for the case of Italy. We use data from the Household Budget Survey between 2000 and 2010 to estimate a demand system in... mehr

    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    DS 125 (36)
    Fernleihe:
    keine Fernleihe

     

    We empirically assess the distributional impacts and welfare effects of policies to incentivize renewable electricity production for the case of Italy. We use data from the Household Budget Survey between 2000 and 2010 to estimate a demand system in which energy goods' shares of expenditure are modelled using different empirical approaches. We show that the general Exact Affine Stone Index (EASI) demand system provides more robust estimates of price elasticities of each composite good than the commonly used Almost Ideal Demand System (AIDS). The estimated coefficients are used to perform a welfare analysis of the Italian renewable electricity production incentive policy. We show that different empirical approaches give rise to significantly different estimates of price elasticities and that methodological choices are the reasons for the very high elasticities of substitutions estimated using similar data by previous contributions. We find no evidence of regressivity of the incidence of the Italian renewable incentive scheme in the period under consideration. The renewable subsidies act as a middle-class tax, with the higher welfare losses experienced by households in the second to fourth quintiles of the expenditure distribution.

     
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Hinweise zum Inhalt
    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    hdl: 10419/142310
    Schriftenreihe: Array ; 2016, 36
    Umfang: 1 Online-Ressource (circa 54 Seiten), Illustrationen
  2. Bending the learning curve
    Autor*in: Witajewski-Baltvilks, Jan; Verdolini, Elena; Tavoni, Massimo
    Erschienen: 2015
    Verlag:  Fondazione Eni Enrico Mattei, Milano

    This paper aims at improving the application of the learning curve, a popular tool used for forecasting future costs of renewable technologies in integrated assessment models (IAMs). First, we formally discuss under what assumptions the traditional... mehr

    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    DS 125 (2015,65)
    Fernleihe:
    keine Fernleihe

     

    This paper aims at improving the application of the learning curve, a popular tool used for forecasting future costs of renewable technologies in integrated assessment models (IAMs). First, we formally discuss under what assumptions the traditional (OLS) estimates of the learning curve can deliver meaningful predictions in IAMs. We argue that the most problematic of them is the absence of any effect of technology cost on its demand (reverse causality). Next, we show that this assumption can be relaxed by modifying the traditional econometric method used to estimate the learning curve. The new estimation approach presented in this paper is robust to the reverse causality problem but preserves the reduced form character of the learning curve. Finally, we provide new estimates of learning curves for wind turbines and PV technologies which are tailored for use in IAMs. Our results suggest that the learning rate should be revised downward for wind power, but possibly upward for solar PV.

     
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Hinweise zum Inhalt
    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    hdl: 10419/113970
    Schriftenreihe: Array ; 65.2015
    Umfang: Online-Ressource (31 S.), graph. Darst.
  3. Directed technological change and energy efficiency improvements
    Autor*in: Witajewski-Baltvilks, Jan; Verdolini, Elena; Tavoni, Massimo
    Erschienen: 2015
    Verlag:  Fondazione Eni Enrico Mattei, Milano

    This paper applies the Directed Technical Change (DTC) framework to study improvements in the efficiency of energy use. We present a theoretical model which (1) shows that the demand for energy is shifted down by innovations in energy intensive... mehr

    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    DS 125 (2015,78)
    Fernleihe:
    keine Fernleihe

     

    This paper applies the Directed Technical Change (DTC) framework to study improvements in the efficiency of energy use. We present a theoretical model which (1) shows that the demand for energy is shifted down by innovations in energy intensive sectors and (2) highlights the drivers of innovative activity in these sectors. We then estimate the model through an empirical analysis of patent and energy data. Our contribution is fivefold. First, our model shows that under very general assumptions information about energy expenditures, knowledge spillovers and the parameters governing the R&D process are sufficient to predict the R&D effort in efficiency improving technologies. Second, we pin down the conditions for a log-linear relation between energy expenditure and the R&D effort. Third, the calibration of the model provides clear evidence that the value of the energy market as well as international and inter-temporal spillovers play a significant role in determining the level of innovative activity. Fourth, we show that innovative activity in energy intensive sectors shifts down the (Marshallian) demand for energy. Finally, we show that due to the streamlined modelling framework we adopt, the point estimates from our regression can potentially be used to calibrate any model of DTC in the context of energy consumption.

     
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Hinweise zum Inhalt
    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    hdl: 10419/130257
    Schriftenreihe: Array ; 78.2015
    Umfang: Online-Ressource (43 S.), graph. Darst.