Real-time monitoring procedures for early detection of bubbles
提出了新的计量程序，通过改进方差标准化方法，在实时中更快检测资产价格泡沫，且不增加误报概率。蒙特卡洛模拟和OECD住房市场及比特币价格的应用表明，该程序能更早发现泡沫，如美国住房泡沫在1999年第一季度即可被检测到。
Asset price bubbles and crashes can have severe consequences for the stability of financial and economic systems. Policymakers require timely identification of such bubbles in order to respond to their emergence. In this paper we propose new econometric procedures that improve the speed of detection for an emerging asset price bubble in real time. Our new monitoring procedures make use of alternative variance standardisations that are better able to capture the behaviour of the underlying process during a bubble phase. We derive asymptotic results to show that using these alternative variance standardisations does not increase the probability of false detection under the no-bubble (unit root) null hypothesis relative to existing procedures. However, Monte Carlo simulations demonstrate that much earlier detection becomes possible with our new procedures under the bubble (explosive autoregressive) alternative. Empirical applications to OECD housing markets and bitcoin prices show the value in terms of earlier detection of bubbles that our new procedures can achieve. In particular, we show that the United States housing bubble that preceded the global financial crisis could have been detected as early as 1999:Q1 by our new procedures.