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on Regulation |
By: | Bisceglia, Michele; Cellini, Roberto; Grilli, Luca |
Abstract: | In several countries, healthcare services are provided by public and/or private subjects, and they are reimbursed by the Government, on the basis of regulated prices. Thus, providers take prices as given and compete on quality to attract patients. In some countries, regulated prices differ across regions. This paper focuses on the interdependence between regional regulators within a country: it proposes a model of spatial competition to study how price-setters of different regions interact, in a simple but realistic framework. We show that the decentralisation of price regulation implies higher expenditure, but higher patients' welfare. |
Keywords: | Healthcare Services; Diagnosis Related Group; 2-Stage Non Cooperative Game; Quality Competition. |
JEL: | H42 I11 L13 R12 R38 |
Date: | 2017–07–10 |
URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:80507&r=reg |
By: | Don Fullerton; Erich Muehlegger |
Abstract: | Public economics has a well-developed literature on tax incidence – the ultimate burdens from tax policy. This literature is used here to describe not only the distributional effects of environmental taxes or subsidies but also the likely incidence of non-tax regulations, energy efficiency standards, or other environmental mandates. Recent papers find that mandates can be more regressive than carbon taxes. We also describe how the distributional effects of such policies can be altered by various market conditions such as limited factor mobility, trade exposure, evasion, corruption, or imperfect competition. Finally, we review data on carbon-intensity of production and exports around the world in order to describe implications for effects of possible carbon taxation on countries with different levels of income per capita. |
JEL: | H22 H23 Q48 Q52 |
Date: | 2017–08 |
URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:23677&r=reg |
By: | Garth Heutel |
Abstract: | Investments in energy efficiency entail uncertainty, and when faced with uncertainty consumers have been shown to behave according to prospect theory: preferences are reference-dependent and exhibit loss aversion, and probabilities are subjectively weighted. Using data from a choice experiment eliciting prospect theory parameters, I provide evidence that loss-averse people are less likely to invest in energy efficiency. Then, I consider policy design under prospect theory when there are also externalities from energy use. A higher degree of loss aversion implies a higher subsidy to energy efficiency. Numerical simulations suggest that the impact of prospect theory on policy may be substantial. |
JEL: | D81 H23 Q41 Q58 |
Date: | 2017–08 |
URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:23692&r=reg |
By: | Daniel de Abreu Pereira Uhr; Júlia Gallego Ziero Uhr, André Luis Squarize Chagas |
Abstract: | This paper fills a gap in the literature on residential energy consumption in Brazil. We estimate price and income elasticities for residential electricity consumption using disaggregated data at household level for the São Paulo metropolitan area. Data were obtained from Fundação Instituto de Pesquisas Econômicas (Fipe), which has complete access to Pesquisa de Orçamento Familiar (POF). Information about residential electricity consumption and household characteristics was available at two different periods, 1998 and 2008, which enabled us to adopt panel data estimation procedures. This study is the first to use Brazilian household level data on electricity consumption and a panel approach to estimate price and income elasticities. The results show that the price elasticity ranges from -0.26 to -0.64 and the income elasticity between 0.11 and 0.32. Controlling for a variety of fixed effects, household and family characteristics, price and income elasticities for the short-run are, approximately, -0.50, and 0.21. |
Keywords: | Electricity; Price elasticity; Income elasticity; Brazil; household data. |
JEL: | C23 D12 Q41 |
Date: | 2017–08–11 |
URL: | http://d.repec.org/n?u=RePEc:spa:wpaper:2017wpecon12&r=reg |
By: | Grzegorz Marcjasz; Bartosz Uniejewski; Rafal Weron |
Abstract: | In day-ahead electricity price forecasting the daily and weekly seasonalities are always taken into account, but the long-term seasonal component was believed to add unnecessary complexity and in most studies ignored. The recent introduction of the Seasonal Component AutoRegressive (SCAR) modeling framework has changed this viewpoint. However, the latter is based on linear models estimated using Ordinary Least Squares. Here we show that considering non-linear neural network-type models with the same inputs as the corresponding SCAR model can lead to a yet better performance. While individual Seasonal Component Artificial Neural Network (SCANN) models are generally worse than the corresponding SCAR-type structures, we provide empirical evidence that committee machines of SCANN networks can significantly outperform the latter. |
Keywords: | Electricity spot price; Forecasting; Day-ahead market; Long-term seasonal component; Neural network; Committee machine |
JEL: | C14 C22 C45 C51 C53 Q47 |
Date: | 2017–07–29 |
URL: | http://d.repec.org/n?u=RePEc:wuu:wpaper:hsc1703&r=reg |
By: | Rogge, Karoline S.; Pfluger, Benjamin; Geels, Frank |
Abstract: | Global climate change represents one of the grand societal challenges which policy makers around the world have agreed to jointly tackle it under the Paris Agreement. Henceforth, much research and policy advice has focused on de-veloping model-based scenarios to identify pathways towards achieving corre-sponding decarbonisation targets. In this paper, we complement such model-based analysis (based on IMAGE and Enertile) with insights from socio-technical transition analysis (MLP) to develop socio-technical storylines that plausibly show how low-carbon transitions can be implemented. We take the example of the transition of the German electricity system towards renewable energies, and elaborate two transition pathways which are assumed to achieve an 80% reduction in GHG emissions by 2050, but differ in terms of lead actors, depth of change and scope of change: the first pathway captures the substitu-tion of technological components (pathway A) and assumes incumbents as lead actors and focuses on radical technological change while leaving other system elements intact; in contrast, pathway B (broader system transformation) postu-lates new entrants as lead actors, which rests on the assumption that trans-formative change occurs in the whole system, i.e. affecting the architecture of the system, technologies but also practises. For both pathways, we focus on how policy makers could govern such transition processes through transforma-tive policy mixes, and compare the requirements of such policy mixes depend-ing on the pathway pursued. We find that multi-dimensional socio-technical change going beyond technological substitution (pathway B) requires much greater emphasis on societal experimentation and a more proactive role for an-ticipatory deliberation processes from the outset. In contrast, shifting gear from a new entrant friendly past trajectory to an incumbent dominated pathway (pathway A) requires active agency from incumbents and is associated with what we have called regime stabilizing instruments which defend core principles of the old regime while simultaneously fulfilling decarbonisation as additional success criteria. |
Keywords: | socio-technical scenarios,transformative policy mix,German Ener-giewende,MLP,energy system modelling,transition pathways |
Date: | 2017 |
URL: | http://d.repec.org/n?u=RePEc:zbw:fisisi:s112017&r=reg |
By: | Donald S. Kenkel; Sida Peng; Michael F. Pesko; Hua Wang |
Abstract: | Electronic cigarettes are a less harmful alternative to combustible cigarettes. We analyze data on e-cigarette choices in an online experimental market. Our data and mixed logit model capture two sources of consumer optimization errors: over-estimates of the relative risks of e-cigarettes; and present bias. Our novel data and policy analysis make three contributions. First, our predictions about e-cigarette use under counter-factual policy scenarios provide new information about current regulatory tradeoffs. Second, we provide empirical evidence about the role consumer optimization errors play in tobacco product choices. Third, we contribute to behavioral welfare analysis of policies that address individual optimization errors. |
JEL: | I12 |
Date: | 2017–08 |
URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:23710&r=reg |
By: | Jesus Lago; Fjo De Ridder; Peter Vrancx; Bart De Schutter |
Abstract: | Motivated by the increasing integration among electricity markets, in this paper we propose three different methods to incorporate market integration in electricity price forecasting and to improve the predictive performance. First, we propose a deep neural network that considers features from connected markets to improve the predictive accuracy in a local market. To measure the importance of these features, we propose a novel feature selection algorithm that, by using Bayesian optimization and functional analysis of variance, analyzes the effect of the features on the algorithm performance. In addition, using market integration, we propose a second model that, by simultaneously predicting prices from two markets, improves even further the forecasting accuracy. Finally, we present a third model to predict the probability of price spikes; then, we use it as an input in the other two forecasters to detect spikes. As a case study, we consider the electricity market in Belgium and the improvements in forecasting accuracy when using various French electricity features. In detail, we show that the three proposed models lead to improvements that are statistically significant. Particularly, due to market integration, predictive accuracy is improved from 15.7% to 12.5% sMAPE (symmetric mean absolute percentage error). In addition, we also show that the proposed feature selection algorithm is able to perform a correct assessment, i.e. to discard the irrelevant features. |
Date: | 2017–08 |
URL: | http://d.repec.org/n?u=RePEc:arx:papers:1708.07061&r=reg |
By: | Bontems, Philippe |
Abstract: | This paper examines theoretically whether by combining both output based refunding and abatement expenditures based refunding it is possible to limit the negative consequences that a pollution tax imply for a polluting industry. We actually show that this is indeed the case by using such a three-part policy where emissions are subject to a fee and where output and abatement expenditures are subsidized. In particular, when the industry is homogenous, it is possible to replicate the standard emission tax outcome by inducing a polluting firm to choose the production and emission levels obtained under any emission tax, without departing from budget balance. By construction, any polluter earns strictly more than under the standard tax alone without rebate, making this proposal highly acceptable to the industry. When firms are heterogenous, the refunding policy needed to replicate the standard emission tax outcome is personalized in the sense that at least the output subsidy should be type dependent. Another result is that this three-part policy is strictly prefered only from the industry's point of view to a standard environmental tax. We also explore the implications of uniform three-part refunding policies for a heterogenous industry. |
Keywords: | refunded emission taxes; regulation design; pollution. |
JEL: | H23 Q52 Q58 |
Date: | 2017–07 |
URL: | http://d.repec.org/n?u=RePEc:tse:wpaper:31916&r=reg |
By: | Crossley, T.F.; Zilio, F.; |
Abstract: | Each year the UK records 25,000 or more excess winter deaths, primarily among the elderly. A key policy response is the “Winter Fuel Payment†(WFP), a labelled but unconditional cash transfer to older households. The WFP has been shown to raise fuel spending among eligible households. We examine the causal effect of the WFP on health outcomes, including self-reports of chest infection, measured hypertension and biomarkers of infection and inflammation. We find a robust and statistically significant six percentage point reduction in the incidence of high levels of serum fibrinogen. Reductions in other disease markers point to health benefits, but the estimated effects are not robustly statistically significant. |
Keywords: | benefits; health; biomarkers; heating; regression discontinuity; |
JEL: | H51 I12 |
Date: | 2017–08 |
URL: | http://d.repec.org/n?u=RePEc:yor:hectdg:17/23&r=reg |
By: | Christopher Dixon-O’Mara; L. (Lisa B.) Ryan |
Abstract: | The objective of this research is to empirically examine the drivers and barriers to energy efficiency measures in an important energy-using sector, namely the food retail sector, and support more effective energy efficiency policies for this sector. Although food retailers consume a significant amount of energy due to the refrigeration, air conditioning and specialised lighting needs of stores, there has been little research in this sector on the barriers and drivers for implementing energy efficiency measures. A survey of small food retailers was carried out to understand the barriers and drivers to greater uptake of energy efficiency measures and to examine the acceptability of different energy efficiency policy options for food retailers. In addition, external stakeholders were consulted in order to validate and contextualise the results of the survey. We find there is a complementary relationship between energy efficiency barriers and drivers for food retailers that is remarkably coherent. We identify policies, such as subsidies and support for ESCOs, that both exploit the complementarities between barriers and drivers and are acceptable to food retailers also. This methodology should help identify and design more effective policies to deliver energy efficiency improvements in the food retail sector. |
Keywords: | Energy efficiency policy; Food retail sector; Policy acceptance; Energy economics; Energy efficiency barriers and drivers |
JEL: | Q40 Q41 Q48 |
Date: | 2017–07 |
URL: | http://d.repec.org/n?u=RePEc:ucn:wpaper:201716&r=reg |