ABSTRACT
To achieve ambitious energy-climate targets, all EU member states have introduced policies to support the market introduction of renewable energy sources (RES) generation. Motivated to close the gap of the merit order effect (MOE) in less mature Central and South East European electricity markets, we empirically confirm economic theory predictions that in the short run, an increase in RES generation reduces electricity prices. The merit order effect is initially econometrically confirmed and quantified. Different econometric model specifications are estimated to differentiate the MOE caused by wind and solar generation and to differentiate the MOE on high-load and low-load days. In addition, we simulate the adjustment of the realised day-ahead electricity prices to the no-RES generation scenario. Modern statistical methods are applied to bridge the gap in the limited public data availability to solve simulation models used in the power system or agent-based simulations. A family of data mining algorithms is applied for the merit order estimation used in the dynamic adaptation of the generation mix to the omitted RES generation. The estimated energy imbalance caused by the excluded RES generation is therefore compensated by the additional conventional generation dispatch according to the estimated power plant merit order. The estimated supply curves for each generation technology assist the reasoning behind the established MOE in econometric models. Based on our findings, policymakers should prioritise policies that facilitate the integration of RES into their electricity markets, which would in turn accelerate energy transition. With increasingly growing shares of renewables in the system, the governments need to rethink the support scheme, where the emphasis should be placed on efficiently integrating renewables in the power system by taking into account temporal and spatial dimensions.
Subject(s)
Electricity , Renewable Energy , Greece , Hungary , RomaniaABSTRACT
This paper investigates the dynamic short-term and long-term relationships among real GDP per capita, energy consumption, urbanization, and carbon dioxide emissions within the framework of the environmental Kuznets curve (EKC) hypothesis for Southeastern Europe (SEE) from 1997 to 2014. The evidence highlights an inverted U-shaped nexus between real GDP per capita and carbon dioxide emissions (i.e., the EKC hypothesis is verified in the long-run in the sample as a whole). The short-run estimates provide evidence of inverted U-shaped EKC only for Greece and Moldova. Two-way causal relationship between urbanization and pollutant emission was also established in the short-run, as well as one-way causality flowing from real GDP per capita to pollutant emission. The coefficients with the real GDP per capita and energy consumption are negative and statistically significant in the long-term. These findings indicate the existence of an error correction mechanism that drives the observed variables back to their equilibrium. Moreover, the findings show that the consistent increase in energy consumption has not reduced environmental pressures.
Subject(s)
Environmental Pollutants , Urbanization , Carbon Dioxide/analysis , Economic Development , EuropeABSTRACT
In this paper we analyse the effectiveness of demand- and supply-side fiscal policies in the small open economy of Slovenia. Simulating the SLOPOL10 model, an econometric model of the Slovenian economy, we analyse the effectiveness of various categories of public spending and taxes during the period 2020 to 2030, assuming that no crisis occurs. Our simulations show that those public spending measures that entail both demand- and supply-side effects are more effective at stimulating real GDP and increasing employment than pure demand-side measures. This is due to the fact that supply-side measures also increase potential and not only actual GDP. Measures which foster research and development and those which improve the education level of the labour force are particularly effective in this respect. Employment can also be stimulated effectively by cutting the income tax rate and the social security contribution rate, i.e. by reducing the tax wedge on labour income, which positively affects Slovenia's international competitiveness. Successful stabilisation policies should thus contain a supply-side component in addition to a demand-side component. We also provide a first simulation of potential effects of the Covid-19 crisis on the Slovenian economy, which is modelled as a combined demand and supply shock.
ABSTRACT
BACKGROUND: Willingness-to-pay (WTP) studies frequently use a contingent valuation (CV) method to determine the economic value of a good or service. However, a typical CV study is able to estimate the WTP for a good as a whole, but provides no information about the marginal WTP for different attributes of a good. OBJECTIVE: The aim was to estimate marginal WTP for different attributes of a CV scenario. METHODS: By using the data from an additional best-worst choice (BWC) experiment, we disaggregated the holistic WTP values for dental care, estimated using the CV method, into attribute-specific WTP values. The study was conducted at the School of Dental Medicine, University of Zagreb, Croatia. Dental school patients were surveyed from March 2016 to January 2017, and their WTP for dental care was estimated using either a CV survey (n = 242), which also included a BWC task, or a discrete choice experiment (DCE) survey (n = 275). RESULTS: The largest marginal welfare estimate (13.5) was obtained for the improvement in treatment explanation, followed by the improvements in staff behavior (8.1) and waiting time in the office (7.2), and by the changes in dental care provider (3.4). These estimates were generally highly similar to the traditional marginal WTP estimates obtained with a traditional multi-profile DCE, after adjusting DCE estimates for non-attendance to the cost attribute. CONCLUSION: Our BWC-CV framework may serve as a valuable alternative for estimating marginal WTP values for health care attributes when the choice behavior of respondents raises concerns for the validity of DCE estimates.
Subject(s)
Choice Behavior , Dental Health Services/economics , Dental Health Services/statistics & numerical data , Health Expenditures/statistics & numerical data , Insurance, Health/economics , Insurance, Health/statistics & numerical data , Adult , Aged , Aged, 80 and over , Croatia , Female , Humans , Male , Middle Aged , Surveys and QuestionnairesABSTRACT
In this article, we use the macroeconometric model SLOPOL10 to calculate simulations of the development of the Slovenian economy until 2030. Starting from the present favourable prospects of the European economies, the forecast is very optimistic but it can nevertheless be improved by optimal fiscal policies as calculated using the OPTCON2 algorithm. If a negative shock to world trade of a size comparable to the Great Recession occurs, it will entail a decline in GDP and a slow recovery. In this case, optimal fiscal policies should not act in an expansionary way as the effectiveness of fiscal policy with respect to output and employment is rather limited in a small open economy like Slovenia. Instead, the goal of budget consolidation will call for a more restrictive fiscal policy, at least if the shock is temporary.
ABSTRACT
RATIONALE, AIMS, AND OBJECTIVES: The literature suggests that discrete choice experiments (DCEs) are a preferable method for estimating willingness-to-pay (WTP) values, as they may avoid some biases often observed in contingent valuation surveys, such as protest and strategic behaviour. However, the choice studies have demonstrated that attribute non-attendance may be a serious issue that leads to biased WTP estimates. METHOD: A DCE was used to estimate patients' WTP for dental care at the dental school clinic. The endogenous attribute attendance (EAA) model was used to estimate WTP for dental care attributes, while accounting for non-attendance to the cost attribute. RESULTS: The EAA model revealed that almost every second respondent had ignored the cost attribute when making choices, indicating that patients were very sensitive to other characteristics of dental care. Dental care providers should pay particular attention to providing a detailed explanation of treatment to their patients, as this was the most valued attribute of dental care. The welfare estimates from the EAA model, which accounted for non-attendance to the cost attribute, were more than two times lower than welfare estimates from a traditional multinomial logit model and mixed logit model estimated in WTP space. CONCLUSIONS: The findings raise concerns for derived WTP estimates in DCE studies that did not consider non-attendance to the cost attribute during the estimation process. Non-attendance to the cost attribute overestimates WTP values, even if being motivated by the true preferences of respondents.
Subject(s)
Choice Behavior , Cost of Illness , Delivery of Health Care/economics , Dental Care , No-Show Patients , Patient Satisfaction , Dental Care/economics , Dental Care/organization & administration , Health Care Costs , Humans , No-Show Patients/economics , No-Show Patients/psychologyABSTRACT
OBJECTIVES: To examine the amount of heterogeneity in patients' preferences for dental care, what factors affect their preferences, and how much they would be willing to pay for improvement in specific dental care attributes. METHODS: A discrete choice experiment (DCE) was used to elicit patients' preferences. Three alternative dental care services that differed in the type of care provider, treatment explanation, dental staff behavior, waiting time and treatment cost were described to patients. Patients (n=265) were asked to choose their preferred alternative. The study was conducted at a public dental clinic of the School of Dental Medicine, University of Zagreb. Mixed logit and latent class models were used for analysis. RESULTS: On average, the patients would be willing to pay 45 for getting a detailed explanation of treatment over no explanation. This was the most valued attribute of dental care, followed by dental staff behavior with marginal willingness-to-pay (WTP) of 28. Dental care provided by the faculty members and private dental care were valued similarly, while student-provided care was valued 23 less. Patients also disliked longer waiting time in the office, but this was the least important attribute. Four classes of patients with distinct preferences for dental care were identified. Older and/or more educated patients tended to give relatively less importance to treatment explanation. Higher education was also associated with a higher propensity to substitute faculty dental care with the private care providers. CONCLUSIONS: Large heterogeneity in patients' preferences was detected. Understanding their preferences may improve the delivery of dental care. CLINICAL SIGNIFICANCE: Dental care providers should pay particular attention to providing a detailed treatment explanation to their patients. Dental care for older and/or more educated patients should be more attentive to interpersonal characteristics. Faculty dental care provided by faculty members could be price competitive to private care, and student-provided care more affordable.