Time-varying pricing may increase total electricity consumption: Evidence from Costa Rica

We study the implementation of a time-varying pricing (TVP) program by a major electricity utility in Costa Rica. Because of particular features of the data, we use recently developed understanding of the two-way fixed effects differences-in-differences estimator along with event-study specifications to interpret our results. Similar to previous research, we find that the program reduces consumption during peak-hours. However, in contrast with previous research, we find that the program increases total consumption. With a stylized economic model, we show how these seemingly conflicted results may not be at odds. The key element of the model is that previous research used data from rich countries, in which the use of heating and cooling devices drives electricity consumption, but we use data from a tropical middle-income country, where very few households have heating or cooling devices. Since there is not much room for technological changes (which might reduce consumption at all times), behavioral changes to reduce consumption during peak hours are not enough to offset the increased consumption during off-peak hours (when electricity is cheaper). Our results serve as a cautionary piece of evidence for policy makers interested in reducing consumption during peak hours—the goal can potentially be achieved with TVP, but the cost is increased total consumption     

The market-based dissemination of energy-access technologies as a business model for rural entrepreneurs: Evidence from Kenya

Improving access to more modern forms of energy requires supply chains that reach further into rural areas. This paper studies a supply-side intervention intended to foster last-mile distribution of energy-access technologies through local small-scale entrepreneurship. We use a staggered-implementation evaluation design to assess the impact on employment and income outcomes of the intervention, which is a large-scale program in Kenya that supports the diffusion of improved cookstoves and small solar products. The results demonstrate how trained entrepreneurs intensify and diversify their income-generating activities, often by shifting away from subsistence farming as a main source of income. For cookstove entrepreneurs, this goes along with improvements in individual and household incomes as well as perceived economic well-being. Our estimates suggest that impacts do not only differ between the two technologies but also across subgroups including gender, age, and baseline occupation. Our findings substantiate that market-based interventions can foster energy access in rural areas by supporting the establishment of local businesses. We highlight several contextual factors that are of relevance when considering the adoption of this approach.     

Financing energy efficiency retrofits in Chilean households: The role of financial instruments,savings and uncertainty in energy transition

High firewood consumption for heating produces high levels of pollution in cities in central and southern Chile, with serious consequences for health and quality of life. Energy efficiency measures (EEMs) have been identified as the best strategy to reduce air pollution and maximize social benefits. However, their adoption has been slow. The objective of this article is to investigate household preferences for financial incentives needed to promote private investments in EEMs in Central-Southern Chilean households and study the role of energy savings and the uncertainty about potential savings in the investment decision, with the aim of finding solutions to increase the adoption of these technologies. We use a choice experiment to explore the trade-off between the investment costs, financial instruments, energy savings, and the uncertainty about achieving the theoretical savings provided by engineering and architectural models. The results show that financial instruments play the most important role in this decision, followed by the savings achieved by the retrofit. Householders prefer to finance their investments with a mix of their personal resources and medium-term credits, trying to avoid long-term commitments. Although uncertainty was found to be a significant variable, it seems to play a small role in the investment decision.     

Volatility spillovers between WTI and Brent spot crude oil prices: an analysis of granger causality in variance patterns over time

There has been an increase in price volatility in oil prices during and since the global financial crisis (GFC). This study investigates the Granger causality patterns in volatility spillovers between West Texas International (WTI) and Brent crude oil spot prices using daily data. We use Hafner and Herwartz’s (2006) test and employ a rolling sample approach to investigate the changes in the dynamics of volatility spillovers between WTI and Brent oil prices over time. Volatility spillovers from Brent to WTI prices are found to be more pronounced at the beginning of the analysis period, around the GFC, and more recently in 2020. Between 2015 and 2019, the direction of volatility spillovers runs unidirectionally from WTI to Brent oil prices. In 2020, however, a Granger-causal feedback relation between the volatility of WTI and Brent crude oil prices is again detected. This is due to the uncertainty surrounding how the COVID-19 pandemic will evolve and how long the economies and financial markets will be affected. In this uncertain environment, commodities markets participants could be reacting to prices and volatility signals on both WTI and Brent, leading to the detection of a feedback relation.     

Existence of long memory in crude oil and petroleum products: Generalised Hurst exponent approach

This study examines the presence of long-run dependence in a variety of crude and refined energy spot markets during the 1986–2018 period using the time-varying generalised Hurst exponent. Our results indicate that the weak-form efficiency in energy spot markets is clearly time-varying, with USGC(U.S. Gulf Coast Conventional Gasoline) Diesel Fuel the most efficient and Propane the least. An important finding is that after the subprime crisis, the persistence of energy spot market products has increased. Overall, our finding highlights that the time-varying model is preferable to the time-constant one since the former can capture time-varying efficiency, which heavily depends on a country’s predominant economic and political conditions.     

Online adaptive lasso estimation in vector autoregressive models for high dimensional wind power forecasting

Wind power forecasts with lead times of up to a few hours are essential to the optimal and economical operation of power systems and markets. Vector autoregression (VAR) is a framework that has been shown to be well suited to predicting for several wind farms simultaneously by considering the spatio-temporal dependencies in their time series. Lasso penalisation yields sparse models and can avoid overfitting the large numbers of coefficients in higher dimensional settings. However, estimation in VAR models usually does not account for changes in the spatio-temporal wind power dynamics that are related to factors such as seasons or wind farm setup changes, for example. This paper tackles this problem by proposing a time-adaptive lasso estimator and an efficient coordinate descent algorithm for updating the VAR model parameters recursively online. The approach shows good abilities to track changes in the multivariate time series dynamics on simulated data. Furthermore, in two case studies it shows clearly better predictive performances than the non-adaptive lasso VAR and univariate autoregression.     

A hybrid machine learning model for forecasting a billing period’s peak electric load days

Many models have been studied for forecasting the peak electric load, but studies focusing on forecasting peak electric load days for a billing period are scarce. This focus is highly relevant to consumers, as their electricity costs are determined based not only on total consumption, but also on the peak load required during a period. Forecasting these peak days accurately allows demand response actions to be planned and executed efficiently in order to mitigate these peaks and their associated costs. We propose a hybrid model based on ARIMA, logistic regression and artificial neural networks models. This hybrid model evaluates the individual results of these statistical and machine learning models in order to forecast whether a given day will be a peak load day for the billing period. The proposed model predicted 70% (40/57) of actual peak load days accurately and revealed potential savings of approximately USD $80,000 for an American university during a one-year testing period.     

Beyond symbolic and substantive: Strategic disclosure of corporate environmental information in China

Under increasing regulatory pressure to disclose environmental impacts, corporate environmental information disclosure (EID) is becoming more prevalent. However, the motives for EID and disclosure approaches (i.e., symbolic or substantive) remain controversial. Using a sample of data for 742 listed manufacturing firms in China across 3 years, we provide evidence to show that the level of EID is significantly positively associated with a firm's advertising intensity and that firms in moderately competitive industries have a higher propensity for adopting an EID‐based differentiated strategy than firms in stronger or weaker competitive industries. We also find that firms that are more sensitive to environmental issues strategically understate their environmental impact when directly facing consumers. Our results suggest that the implementation of corporate EID is strategic and that firms have strong market motives, even under regulatory pressure to demonstrate legitimacy. We discuss this study's contributions to research on EID theory and implications for strategic EID management.     

能效改善与能源节约：助力还是阻力

研究目标：测算中国分行业的能源回弹效应与综合能耗系数。研究方法：通过编制含能源实物流量的价值型能源投入产出可比价序列表，测算出能源回弹效应与综合能耗系数，结合行业综合能耗情况分析了能源回弹效应的行业异质性。研究发现：各行业在能耗方面表现迥异，能源回弹效应也存在典型的行业异质性；中国整体经济能源回弹程度并不高，能效改善可以有效节约能源，但整体经济低能源回弹的表象也掩盖了部分行业能源效率无改善和高能耗行业高能源回弹的事实。研究创新：从系统与结构的视角审视了行业的综合能耗情况，并给出了一种基于能源投入产出表的能源回弹效应计算方法。研究价值：有助于提出整体经济结构优化与节能减排的行业政策。     

The aesthetic fidelity effect

Product aesthetics is a powerful means for achieving competitive advantage. Yet most studies to date have focused on the role of aesthetics in shaping pre-purchase preferences and have failed to consider how product aesthetics affects post-purchase processes and consumers' usage behavior. This research focuses on the relationship between aesthetics and usage behavior in the context of durable products. Studies 1A to 1C provide evidence of a positive effect of product aesthetics on usage intensity using market data from the car and the fashion industries. Study 2 corroborates these findings and shows that the more intensive use of highly aesthetic products may lead to the acquisition of product-specific usage skills that form the basis for a cognitive lock-in. Hence, consumers are less likely to switch away from products with appealing designs, an effect that is labeled as the ‘aesthetic fidelity’ effect. Study 3 addresses an alternative explanation for the ‘aesthetic fidelity effect’ based on mood and motivation but finds that the ‘aesthetic fidelity’ effect is indeed determined by usage intensity. Finally, Study 4 identifies a boundary condition of the positive effect of product aesthetics on product usage, showing that it is limited to durable products. In sum, this research demonstrates that the effects of product aesthetics extend beyond the pre-consumption stage and have an enduring impact on people's consumption experiences.