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。     

Threshold effects of terms of trade on Latin American growth

This paper investigates nonlinear relationships between terms of trade volatility (totvol) and economic growth in 14 Latin American economies from 1997 to 2014. In the 2000s, Latin American countries experienced accelerated economic growth often attributed to commodity price booms. We split the sample into two regimes based on totvol thresholds determined by bootstrap techniques. Fixed effects, instrumental variable and dynamic panel regressions address endogeneity in trade growth, subject to traditional economic channels such as domestic investment, population growth, exchange rate, government size, and institutions. We find statistically significant thresholds and stronger trade-growth links during the 2000s commodity boom and in larger economies.     

全国煤炭交易中心运营模式研究

全国煤炭交易中心的设立对规范我国煤炭交易市场规则、实施能源宏观调控、提升我国煤炭国际定价话语权具有重要意义。在分析全国煤炭交易中心功能定位和业务的基础上,设计中长期合同邀约、现货挂牌、现货竞价、现货招投标4种交易模式及业务流程,提出依托国家重大战略争取政策支持、加强各方沟通完善综合物流体系、建立银企合作机制与信用体系、完善煤炭交易中心协调机制、增强信息服务与风险防控能力等对策建议。研究成果对优化煤炭供给结构、规范煤炭交易市场和保障国家煤炭能源安全提供了支撑。     

干旱区内陆河流域未利用地开发生态风险评价及预测*——以开都河流域为例

[目的]探析开都河流域在未利用地开发过程中生态风险指数的变化特征,为西北干旱区内陆河流域土地利用结构调整与生态保护修复协调发展提供建议。[方法]文章采用PSR模型构建基于14个指标框架的流域未利用地开发生态风险评价指标体系;通过测度综合生态风险指数法进行时空视角的特征变化与格局划分评价;并运用灰色预测模型前瞻性模糊预测该区域未来4年的生态风险变化态势。[结果]2009—2016年开都河流域未利用地开发生态风险整体呈波动上升趋势,生态风险程度由较低下降至低生态风险水平,随后上升至一般程度。这是因为土地开发利用对生态环境造成压力,但在政府相应生态保护政策的出台落实下又逐步缓解,生态系统结构和功能好转明显,抵御风险能力得以提升。预测结果显示2017—2020年开都河流域生态风险将由一般生态风险程度上升至较高程度,因此需要采取适当的管理措施来消减生态风险发生的可能性。[结论]开都河流域作为沙漠中典型的绿洲生态系统,生态环境较为脆弱,通过未利用地的差别化开发、鼓励零星分散的开发模式以及细分不同地类开发的生态补偿设置等方式路径,以期缓解降低干旱区内陆河流域未利用地开发带来的生态风险。     

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.