Market power, survival and accuracy of predictions in financial markets

In a standard General Equilibrium framework, we consider an agent strategically using her large volume of trade to influence asset prices to increase her consumption. We show that, as in Sandroni (Econometrica 68:1303–1341, 2000) for the competitive case, if markets are dynamically complete and some general conditions on market preferences are met then this agent’ long-run consumption will vanish if she makes less accurate predictions than the market, and will maintain her market power otherwise. We thus argue that the Market Selection Hypothesis extends to this situation of market power, in contrast to Alchian (J Pol Econ 58:211–221, 1950) and Friedman (Essays in Positive Economics, University of Chicago Press, Chicago, 1953) who claimed that this selection was solely driven by the competitiveness of markets. I would like to thank T. Hens, A. Kirman and A. Sandroni for many stimulating conversations and encouragements. Two anonymous referees also provided very valuable comments.     

Competition and waiting times in hospital markets

This paper studies the impact of hospital competition on waiting times. We use a Salop-type model, with hospitals that differ in (geographical) location and, potentially, waiting time, and two types of patients: high-benefit patients who choose between neighbouring hospitals (competitive segment), and low-benefit patients who decide whether or not to demand treatment from the closest hospital (monopoly segment). Compared with a benchmark case of monopoly, we find that hospital competition leads to longer waiting times in equilibrium if the competitive segment is sufficiently large. Given a policy regime of hospital competition, the effect of increased competition depends on the parameter of measurement: Lower travelling costs increase waiting times, higher hospital density reduces waiting times, while the effect of a larger competitive segment is ambiguous. We also show that, if the competitive segment is large, hospital competition is socially preferable to monopoly only if the (regulated) treatment price is sufficiently high.     

工业智能化对中国工业碳排放效率的影响及空间效应研究

“30·60”的双碳目标提出后,工业智能化作为新一轮技术革命和产业变革的关键驱动力,对我国实现“碳达峰、碳中和”目标发挥重要作用。基于2006—2019年中国30个省份（因数据缺失,不包括西藏和港澳台地区）的面板数据,运用固定效应模型、中介效应模型、空间杜宾模型,多维度实证分析了工业智能化对中国工业碳排放效率的影响及空间效应。研究发现：(1)工业智能化发展能够提升工业碳排放效率;(2)工业智能化能够依靠技术进步和抑制能源强度提升工业碳排放效率;(3)空间效应上,工业智能化的发展能够提升本地区工业碳排放效率,但对周边地区工业碳排放效率的溢出、扩散效应还未显现;(4)工业智能化对工业碳排放效率的影响存在空间异质性,其发展能够带动东部地区工业碳排放效率的提升,而对中西部地区工业碳排放影响较小。研究结果有效补充了有关工业碳排放效率的影响因素及有关工业智能化的研究,为工业智能化驱动工业碳排放效率提升提供了可靠的实证依据,同时为工业的绿色发展提供了政策参考。