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     

Does local government competition aggravate haze pollution? A new perspective of factor market distortion

Haze pollution has become a new threat to China's sustainable development, but it may be that local government behaviour can play an important role in the prevention and control of pollutants. A dynamic spatial autoregressive (SAR) model is used to study the relationship between local government competition and haze pollution. To further explore the indirect impact of factor market distortion on haze pollution and control potential endogeneity problems, a newly developed intermediary effect model that incorporates the characteristics of the generalized method of moments (GMM) is utilized to explore how factor market distortion indirectly affects haze pollution. The research results show that regional haze pollution in China is characterized by significant spatial correlation, and local government competition has a positive impact on haze pollution; that is, local government competition exacerbates haze pollution. In general, local government competition not only directly leads to an increase in haze pollution but also further intensifies it by distorting the local factor market, and the intermediary role of factor market distortion is approximately 7.04%. The results of the regional inspection found that competition among local governments in the eastern region did not lead to haze pollution, and distortion of the factor market did not exist as an intermediary effect. However, both direct and intermediary effects are significant in the central and western regions. Therefore, an official performance appraisal system that includes ecological constraints should be established to guide the benign transformation of local government competition, and an environmental management mechanism must be developed for joint prevention and control to reduce haze pollution. In addition, the free flow of factors and marketization are equally important.     

高技术企业多元化战略对创新持续性的影响——动态能力的调节作用

基于资源基础理论和持续创新内生机制，利用435家高技术企业2010—2018年面板数据，对多元化战略对高技术企业创新持续性的影响进行探究。结果表明，产品多元化与创新持续性呈正U型关系，技术多元化对创新持续性具有正向促进作用，产品多元化与技术多元化协同效应对创新持续性具有负向影响；动态能力强化了产品多元化与创新持续性之间的正U型关系，并正向调节技术多元化与创新持续性之间的关系。在动态能力调节作用下，高技术企业产品多元化与技术多元化协同效应对创新持续性具有正向影响。     

Factor extraction using Kalman filter and smoothing: This is not just another survey

Dynamic factor models have been the main “big data” tool used by empirical macroeconomists during the last 30 years. In this context, Kalman filter and smoothing (KFS) procedures can cope with missing data, mixed frequency data, time-varying parameters, non-linearities, non-stationarity, and many other characteristics often observed in real systems of economic variables. The main contribution of this paper is to provide a comprehensive updated summary of the literature on latent common factors extracted using KFS procedures in the context of dynamic factor models, pointing out their potential limitations. Signal extraction and parameter estimation issues are separately analyzed. Identification issues are also tackled in both stationary and non-stationary models. Finally, empirical applications are surveyed in both cases. This survey is relevant to researchers and practitioners interested not only in the theory of KFS procedures for factor extraction in dynamic factor models but also in their empirical application in macroeconomics and finance.     

How have the dependence structures between stock markets and economic factors changed during the COVID-19 pandemic?

This study investigates how the dependence structures between stock markets and economic factors have changed during the COVID-19 pandemic using the dynamic model averaging approach. A series of economic factors such as commodity markets, cryptocurrency, monetary policy, international capital flows, and market uncertainty indices are considered. We find that the importance of economic variables and the sign and size of their coefficients are significantly different from those before the COVID-19 pandemic. The stock markets are most influenced by economic factors during the COVID-19 outbreak.     

Is the system reliability profitable for retailing and consumer service of a dynamical system under cross-price elasticity of demand?

Retailing strategy is one of the most crucial factors for industries. A proper retailing strategy can help to enhance consumer service and increase the industry's profit. An improved approach to retailing is suggested in this research to deliver superior customer service while maximizing profits in a dynamic system. The study analyzes a retailing strategy for a demand with cross-price elasticity upon the retail price. A product's cross-price elasticity and the system reliability are critical factors in retailing. Understanding the cross-price elasticity of demand between products helps retailers to make pricing decisions that maximize profits by maintaining demand. Imperfect products are produced due to an imperfect production system. The imperfect ones must be adjusted with some costs to make them perfect for better retailing. The system failure rate is crucial for retailing under cross-price elasticity of demand patterns. Production system reliability, cross-price elasticity of demand, and consumer service are all essential factors that can impact a company's success in the market. The production rate is considered time- and system failure rate-dependent. Contradictory to the literature, a dynamical system is proposed for improved retail management, which is solved using the Euler-Lagrange theory. Finally, one can achieve the expected maximum profit for this retail system with optimum selling prices for different products by reducing the system failure rate. Some numerical illustrations with graphical representations are provided to validate the current study. Numerical examples show that applying cross-price elasticity of demand for more than two identical products provides 35% more profit for the retail industry than a single type of product.     

Are USDA reports still news to changing crop markets?

This study investigates whether major USDA reports still provide important news to changing crop markets. The news component of each report, or market “surprise,” is measured as a difference between the USDA estimate and its private expectation in corn, soybeans, and wheat markets. Changes in the relevance of USDA information are assessed by examining changes in the magnitude of market surprises and shifts in the futures price reaction to these surprises, which isolates the impact of each report. The stable size of market surprises over time suggests that competition from alternative data sources has not reduced the news component of USDA crop reports. Increasing price reaction to most reports, including those facing competition from alternative information sources, suggests that value of public information may be enhanced in uncertain markets affected by structural changes.     

Sensory Aspects of Retailing: Theoretical and Practical Implications

Sensory elements are an important aspect of both offline and online retail stores and can non-consciously influence consumer judgments and purchase behavior. In offline settings, ambient factors like scent, lighting, and music have been shown to influence customers’ shopping experiences and their buying behaviors. For online retail outlets, sensory factors related to color, display patterns, and layouts can have significant effects on consumer behavior. Sensory elements have strong managerial relevance since they can non-consciously influence behaviors and because they are relatively easy to change; for example, it requires minimal effort to change the lighting or the music at a physical retail store or the display pattern for an online store. The eight papers in this special issue address theoretical and practical issues related to how different sensory elements can strongly influence retail practices. These papers focus on underexplored topic areas and also on emerging technologies, which stimulate thoughts for further research in these areas.     

FREE VERSUS SECOND‐BEST ENTRY IN COURNOT OLIGOPOLIES WITH FIRM‐SPECIFIC NETWORKS

This paper endogenizes the number of firms in an industry with positive network effects, complete incompatibility, and firms that compete in quantity. To this end, we compare two possibilities: free entry and second‐best number of firms (the one that maximizes social welfare). We show that with business‐stealing competition, free entry yields, in general, more firms than the socially optimal solution. In addition, we find that by the nature of the industry with firm‐specific networks, total production may be greater or lower under free entry than with a regulator; moreover, some industries attain their maximum social welfare with a monopoly.     

The end of the flat tax experiment in Slovakia: An evaluation using behavioural microsimulation in a dynamic macroeconomic framework

The paper introduces a new way of linking microsimulation models with dynamic general equilibrium frameworks to obtain an evaluation of the impact of detailed tax and benefit measures on the aggregate economy. In the approach presented in this paper, income heterogeneity interacts with the macro-economy via aggregated individual labour supply decisions which influence, and are influenced by, the dynamic evolution of the real wage rate. The method involves a reduced-form representation of the information flow between the macroeconomic and microeconomic blocks. The practical usefulness of the approach is demonstrated by evaluating actual and hypothetical tax reforms that involve abandoning the flat tax system in Slovakia. A hypothetical move to a highly progressive tax structure is shown to generate some employment gains but is associated with a drop in aggregate income and tax revenue.