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  • 1
    Publication Date: 2017-11-29
    Description: In this paper we propose a general approach for estimating stochastic frontier mod- els, suitable when using long panel data sets. We measure efficiency as a linear combi- nation of a finite number of unobservable common factors, having coefficients that vary across firms, plus a time-invariant component. We adopt recently developed economet- ric techniques for large, cross sectionally correlated, non-stationary panel data models to estimate the frontier function. Given the long time span of the panel, we investigate whether the variables, including the unobservable common factors, are non-stationary, and, if so, whether they are cointegrated. To empirically illustrate our approach, we estimate a stochastic frontier model for energy demand, and compute the level of the “underlying energy efficiency” for 24 OECD countries over the period 1980 to 2008. In our specification, we control for variables such as Gross Domestic Product, energy price, climate and technological progress, that are known to impact on energy consumption. We also allow for hetero- geneity across countries in the impact of these factors on energy demand. Our panel unit root tests suggest that energy demand and its key determinants are integrated and that they exhibit a long-run relation. The estimation of efficiency scores points at European countries as the more efficient in consuming energy.
    Keywords: C10 ; C31 ; C33 ; ddc:330 ; Energy demand ; panels ; common factors ; principal components
    Repository Name: EconStor: OA server of the German National Library of Economics - Leibniz Information Centre for Economics
    Language: English
    Type: doc-type:workingPaper
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  • 2
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    Zurich: ETH Zurich, CER-ETH - Center of Economic Research
    Publication Date: 2017-11-29
    Description: The productive efficiency of a firm can be seen as composed of two parts, one persistent and one transient. The received empirical literature on the measurement of productive efficiency has paid relatively little attention to the difference between these two components. Ahn, Good and Sickles (2000) suggested some approaches that pointed in this direction. The possibility was also raised in Greene (2004), who expressed some pessimism over the possibility of distinguishing the two empirically. Recently, Colombi (2010) and Kumbhakar and Tsionas (2012), in a milestone extension of the stochastic frontier methodology have proposed a tractable model based on panel data the promises to provide separate estimates of the two components of efficiency. The approach developed in the original presentation proved very cumbersome actually to implement in practice. Colombi (2010) notes that FIML estimation of the model is ‘complex and time consuming.’ In the sequence of papers, Colombi (2010), Colombi et al. (2011, 2014), Kumbhakar, Lien and Hardaker (2012) and Kumbhakar and Tsionas (2012) have suggested other strategies, including a four step least squares method. The main point of this paper is that full maximum likelihood estimation of the model is neither complex nor time consuming. The extreme complexity of the log likelihood noted in Colombi (2010), Colombi et al. (2011, 2014) is reduced by using simulation and exploiting the Butler and Moffitt (1982) formulation. In this paper, we develop a practical full information maximum simulated likelihood estimator for the model. The approach is very effective and strikingly simple to apply, and uses all of the sample distributional information to obtain the estimates. We also implement the panel data counterpart of the JLMS (1982) estimator for technical or cost inefficiency. The technique is applied in a study of the cost efficiency of Swiss railways.
    Keywords: C1 ; C23 ; D2 ; D24 ; ddc:330 ; productive efficiency ; stochastic frontier analysis ; panel data ; transient and persistent efficiency
    Repository Name: EconStor: OA server of the German National Library of Economics - Leibniz Information Centre for Economics
    Language: English
    Type: doc-type:workingPaper
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  • 3
    Publication Date: 2017-11-29
    Description: Many countries have adopted policies designed to reduce CO2 emissions from road vehicles. Taxes linked to the CO2 emissions rate or the fuel economy of a vehicle (which is inversely related to its CO2 emissions rate) are examples of such policies. These taxes are usually imposed on new vehicles, and previous evaluations have estimated the increases in the shares or sales of new and fuel-efficient vehicles associated with such taxes. In contrast, we ask whether taxes on new cars that penalize high emitters induce changes in the retirement of used and inefficient vehicles. We exploit natural experiment conditions in Switzerland to analyze the impact of two different “bonus”/“malus” schemes implemented at the cantonal level. In both schemes, the bonus rewards new efficient vehicles. The malus is retroactive in canton Obwalden, in the sense that it is charged on both new and existing high-emitting cars, but it is only applied prospectively to new cars in Geneva. We use a difference-in-difference design within a survival analysis setting. We find that a bonus/malus accelerates the retirement of existing high-emitting vehicles in Obwalden, shortening the expected lifetime of the three most popular make-models by 7 to 11 months. The effect is the opposite in Geneva, where we estimate that the expected lifetime of these three popular models is extended by 5 to 8 months. These findings have important implications about the desirability of bonus/malus schemes and on their design, as well as on old car scrappage programs.
    Keywords: L62 ; Q4 ; Q5 ; ddc:330 ; Vehicle retirement ; Emissions-based taxes ; bonus/malus ; difference-in-difference ; survival analysis ; Switzerland ; Kraftfahrzeug ; Technische Effizienz ; Nachfrage ; Ökosteuer ; Anreiz ; Steuerwirkung ; Konsumentenverhalten ; Statistische Bestandsanalyse ; Obwalden ; Genf ; Schweiz
    Repository Name: EconStor: OA server of the German National Library of Economics - Leibniz Information Centre for Economics
    Language: English
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  • 4
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    Zurich: ETH Zurich, CER-ETH - Center of Economic Research
    Publication Date: 2017-11-29
    Description: Ambient air pollution is the environmental factor with the greatest impact on human health. Several epidemiological studies provide evidence for an association between ambient air pollution and human health. However, the recent economic literature has challenged the identification strategy used in these studies. This paper contributes to the ongoing discussion by investigating the association between ambient air pollution and morbidity using hospital admission data from Switzerland. Our identification strategy rests on the construction of geographically explicit pollution measures derived from a dispersion model that replicates atmospheric conditions and accounts for several emission sources. The reduced form estimates account for location and time fixed effects and show that ambient air pollution is strongly correlated with hospital admissions. In particular, we find that SO2 and NO2 are positively associated with admission rates for coronary artery and cerebrovascular diseases. As a robustness check, we adopt instrumental variable methods to account for the possible endogeneity of pollution measures. These results may contribute to a more accurate evaluation of future environmental policies aiming at a reduction of ambient air pollution exposure.
    Keywords: I10 ; Q51 ; Q53 ; ddc:330 ; Ambient air pollution ; dispersion model ; hospital admissions ; count panel data
    Repository Name: EconStor: OA server of the German National Library of Economics - Leibniz Information Centre for Economics
    Language: English
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  • 5
    Publication Date: 2017-11-29
    Description: There is evidence that many individuals make sub-optimal investment decisions when the benefits and costs associated with that decision are distributed over time. One example is the decision to adopt new electrical appliances, with the benefits of choosing a more energy efficient device materializing only in the future. This paper analyses the impact of the level of an individual’s energy-related investment literacy on the adoption of energy-efficient appliances. Moreover, the empirical analysis explores the impact of decision support tools such as educational slides on the probability that individuals identify the appliance with the lowest lifetime cost, which is ideally also the most energy-efficient appliance. To test the influence of these decision support tools, we developed an online randomized controlled trial and implemented it on two independently chosen samples of the Swiss population. One treatment offers a short education program on how to calculate the lifetime cost of an appliance – via a set of information slides. The second intervention provides access to an online calculator that supports the investment decision-making of the individual. Results across the two samples are encouraging. We find that i) pre-treatment energy and investment literacy positively impact on the probability of identifying the appliance with the lowest lifetime cost; ii) the reinforcement of energy-related investment literacy increases the rate at which individuals identify the appliance with the lowest lifetime cost; and iii) while both interventions are effective in increasing the chances that an appliance with the lower lifetime cost is chosen, the online calculator turned out to be more effective than the educational program. Public policy implications are discussed.
    Keywords: D12 ; D80 ; Q41 ; Q48 ; ddc:330 ; energy-efficient appliances ; energy-related investment literacy ; appliance choice ; bounded rationality ; educational programs ; online tool
    Repository Name: EconStor: OA server of the German National Library of Economics - Leibniz Information Centre for Economics
    Language: English
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  • 6
    Publication Date: 2017-11-29
    Description: This paper presents an empirical analysis of residential electricity demand considering the existence of spatial effects. This analysis has been performed using aggregate panel data at the province level for 46 Spanish provinces for the period from 2001 to 2009. For this purpose, we estimated a log-log demand equation using a spatial autoregressive model with autoregressive disturbances (SARAR). The purpose of this empirical analysis is to determine the influence of price, income, and spatial spillovers on residential electricity demand in Spain. We are particularly interested in analyzing the impact of household disposable income variation across provinces observed during the economic crisis period from 2008-2009. The estimation results show relatively high income elasticity and relatively low price elasticity. Furthermore, the results show the presence of spatial effects in Spanish residential electricity consumption.
    Keywords: D ; D2 ; Q ; Q4 ; R2 ; ddc:330 ; residential electricity demand ; aggregate panel data ; spatial economic effects ; economic crisis ; spatial econometrics ; Energiekonsum ; Räumliche Verteilung ; Wirtschaftskrise ; Panel ; Spanien
    Repository Name: EconStor: OA server of the German National Library of Economics - Leibniz Information Centre for Economics
    Language: English
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  • 7
    Publication Date: 2017-11-29
    Description: The purpose of this study is to analyze the cost efficiency of electricity distribution systems in order to enable regulatory authorities to establish price- or revenue cap regulation regimes. The increasing use of efficiency analysis in the last decades has raised serious concerns among regulators and companies regarding the reliability of efficiency estimates. One important dimension affecting the reliability is the presence of unobserved factors. Since these factors are treated differently in various models, the resulting estimates can vary across methods. Therefore, we decompose the benchmarking process into two steps. In the first step, we identify classes of similar companies with comparable network and structural characteristics using a latent class cost model. We obtain cost best practice within each class in the second step, based on deterministic and stochastic cost frontier models. The results of this analysis show that the decomposition of the benchmarking process into two steps has reduced unobserved heterogeneity within classes and, hence, reduced the unexplained variance previously claimed as inefficiency.
    Keywords: L92 ; L50 ; L25 ; ddc:330 ; Efficiency analysis ; cost function ; electricity sector ; incentive regulation ; Elektrizitätswirtschaft ; Regulierung ; Kosten-Nutzen-Analyse ; Kostenfunktion ; Effizienzmarkthypothese
    Repository Name: EconStor: OA server of the German National Library of Economics - Leibniz Information Centre for Economics
    Language: English
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  • 8
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    Zurich: ETH Zurich, CER-ETH - Center of Economic Research
    Publication Date: 2017-11-29
    Description: The promotion of US energy efficiency policy is seen as a very important activity by the Energy Information Agency (EIA). Generally, the level of energy efficiency of a state is approximated by energy intensity, commonly calculated as the ratio of energy use to GDP. However, energy intensity is not an accurate proxy for energy efficiency, because changes in energy intensity are a function of changes in several factors including the structure of the economy, climate, efficiency in the use of resources and technical change. The aim of this paper is to measure the ‘underlying energy efficiency’ for the whole economy of 49 ‘states’ in the US using a stochastic frontier energy demand approach. A total US energy demand frontier function is estimated using panel data for 49 ‘states’ over the period 1995 to 2009 using several panel data models: the pooled model; the random effects model; true fixed effects model; the true random effects model; and the Mundlak versions of the pooled and random effects models. The analysis confirms that energy intensity is not a good indicator of energy efficiency; whereas, by controlling for a range of economic and other factors, the measure of ‘underlying energy efficiency’ obtained via the approach adopted here (based on the microeconomic theory of production) is.
    Keywords: D ; D2 ; Q ; Q4 ; Q5 ; ddc:330 ; US total energy demand ; efficiency and frontier analysis ; state energy efficiency
    Repository Name: EconStor: OA server of the German National Library of Economics - Leibniz Information Centre for Economics
    Language: English
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  • 9
    Publication Date: 2017-11-29
    Description: To correct market failures due to the presence of negative externalities associated with energy consumption, governments have adopted a variety of policies, including taxes, subsidies, regulations and standards, and information-based policies. For example, labels that clearly convey energy consumption rates, associated costs, and emissions of conventional pollutants and CO2, have been devised and used in the last two decades to promote rational decisions, but it is unclear whether labeling schemes have realigned consumer and producer behaviors. In 2003, Switzerland introduced a system of fuel economy labels, based on grades ranging from A to G, where is A best and G is worst, to assist consumers in making decisions that improve the fleet’s fuel economy and lower emissions. We use a dataset documenting all passenger cars approved for sale in Switzerland each year from 2000 to 2011 to answer three key research questions. First, what is the willingness to pay for fuel economy? Second, do Swiss drivers—or Swiss auto importers—appear to do a one-to-one tradeoff between car purchase price and savings on fuel costs over the lifetime of the car? Third, does the label have an additional effect on price, all else the same, above and beyond that of fuel efficiency alone? Hedonic pricing regressions that exploit the variation in fuel economy across make-models, and over time within make-models, suggest that there is a (modest) capitalization of fuel economy into car prices. The Diesel premium, however, exceeds the future fuel cost savings made possible by Diesel cars, even at zero discount rates. An alternate calculation suggests that the fuel economy premium is consistent with a very low discount rate (2.5%). We use matching estimators and a sharp regression discontinuity design (RDD) based on the mechanism used by the Swiss Federal Office of Energy to assign cars to the fuel economy label to see if the label has an independent effect on price, above and beyond that of the fuel economy. The matching estimator indicates that the A-label effect on car price is approximately 5%. The RDD approach estimates the effect to be 6-11%.
    Keywords: Q48 ; Q53 ; Q54 ; ddc:330 ; Fuel economy ; CO2 emissions ; Passenger vehicles ; Hedonic pricing model ; Matching Estimator ; Regression Discontinuity Design ; Fuel efficiency premium ; Discounted future fuel costs
    Repository Name: EconStor: OA server of the German National Library of Economics - Leibniz Information Centre for Economics
    Language: English
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  • 10
    Publication Date: 2017-11-29
    Description: This paper estimates the level of transient and persistent efficiency in the use of electricity in Swiss households using the generalized true random effects model (GTREM). A panel dataset of 1, 994 Swiss households from 2010 to 2014 collected via a household survey is used to estimate an electricity demand frontier function. We further investigate whether energy and investment literacy have an influence on the household electricity consumption. The results show significant inefficiencies in the use of electricity among Swiss households, both transient (11%) and persistent (22%). We note that the high persistent inefficiency is indicative of structural problems faced by households and systematic behavioral shortcomings in residential electricity consumption. These results indicate a considerable potential for electricity savings and thus reaching the reduction targets defined by the Swiss federal council as part of the Energy Strategy 2050, wherein end-use efficiency improvement is one of the main pillars. The results support a positive role of energy and, in particular, investment literacy in reducing household electricity consumption. Policies targeting an improvement of these attributes could help to improve efficiency in the use of energy within households.
    Keywords: D12 ; D13 ; D80 ; Q41 ; Q48 ; ddc:330 ; Stochastic frontier analysis ; Transient and persistent efficiency ; Energy literacy ; Investment literacy ; Energy saving behaviour ; Residential electricity demand ; Household data
    Repository Name: EconStor: OA server of the German National Library of Economics - Leibniz Information Centre for Economics
    Language: English
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