Identifying government spending shocks in the U.K: A novel instrumental approach based on natural disasters.

识别英国政府支出冲击：基于自然灾害的新颖工具方法。

• 批准号: 2864734
• 金额: --
• 依托单位: Lancaster University
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2864734
• 关键词: Identifying; government; spending; shocks; U.K

Identifying government spending shocks in the U.K:A novel instrumental approach based on natural disasters.Following the global financial crisis of 2007, many countries resorted to significant fiscal stimulus packages, consisting of increased government spending and tax cuts, to boost economic activity. Most of these packages were based on the Keynesian view that expansionary fiscal policy can mitigate the economic downfall and prevent the waste of economic resources. In line with this rationale, in 2008, the United Kingdom was one of the major economies to lead calls for fiscal expansion to stimulate aggregate demand and help offset the global economic downturn. Adopting such measures generated a renewed interest among academics and policymakers in whether and to what extent fiscal policies are effective. This interest was recently further stimulated by the massive fiscal response that followed the Covid-19 pandemic.Despite its importance, there is still no consensus over the effectiveness of fiscal policy in stabilising the economy (Cloyne, 2013; Ramey, 2011; Mertens and Ravn, 2012; Leeper et al., 2013). A prime reason for this lack of consensus lies in the difficulty of identifying primitive, unanticipated policy shocks (i.e. changes in fiscal policy not correlated with other macroeconomic fluctuations) which are required for conducting a causal analysis. The existing literature has proposed various methods for identifying fiscal shocks to address this. These involve time and sign restrictions in a VAR system and instruments (Ramey, 2016). Unfortunately, each of these techniques exhibits weaknesses that raise concerns about the findings of empirical studies. For instance, the short-run restriction approach suffers from anticipation issues. Specifically, because government expenditure or tax cuts are usually announced several quarters before they take place, it fails to account for changes in expectations which leads to underestimation of the effect of fiscal policy (see Mertens and Ravn, 2010). Similarly, sign restrictions that compute impulse responses based on a large set of plausible models make the structural analysis less informative (Braun and Bruggemann, 2022).A method which has been gaining popularity in recent years is the identification of shocksusing instruments. As shown by Ramey (2016), exploiting variation from proper instruments deals with the problem of fiscal foresight (anticipation) and provides robust results. The mainchallenge of identification using instruments is the selection of the instrument itself. Theselected instrument must be correlated with the shock of interest and orthogonal to the restof the shocks. These conditions are untestable, and as a consequence, applications of shockidentification using instruments are often criticised either for lack of strict exogeneity1 or forlow relevance. Regarding government spending shocks, most of the existing literature exploitsvariation in military spending to construct instruments for identification. The underlyingassumption is that military expenditures constitute government spending unrelated to thestate of the economy (Ramey and Shapiro, 1998; Ramey, 2011; Ben Zeev and Pappa, 2017).However, Ramey (2016) argues that proxies of government spending shocks constructedfrom historical records on military spending are weak instruments for the post-Korean warsamples.

识别英国政府支出冲击：基于自然灾害的新颖工具方法。2007 年全球金融危机后，许多国家采取了重大财政刺激计划，包括增加政府支出和减税，以促进经济活动。这些一揽子计划大多基于凯恩斯主义观点，即扩张性财政政策可以缓解经济衰退并防止经济资源浪费。与此相一致，2008年，英国是带头呼吁财政扩张以刺激总需求并帮助抵消全球经济衰退的主要经济体之一。采取这些措施引起了学术界和政策制定者对财政政策是否有效以及在多大程度上有效的新兴趣。最近，Covid-19 大流行后采取的大规模财政应对措施进一步刺激了这种兴趣。尽管财政政策很重要，但对于稳定经济的财政政策的有效性仍没有达成共识（Cloyne，2013；Ramey，2011；Mertens 和 Ravn） ，2012；利珀等人，2013）。缺乏共识的主要原因在于难以识别进行因果分析所需的原始的、意外的政策冲击（即与其他宏观经济波动不相关的财政政策的变化）。现有文献提出了各种识别财政冲击的方法来解决这个问题。这些涉及 VAR 系统和工具中的时间和符号限制（Ramey，2016）。不幸的是，这些技术中的每一种都表现出弱点，引起了人们对实证研究结果的担忧。例如，短期限制方法就存在预期问题。具体而言，由于政府支出或减税通常在实施前几个季度宣布，因此未能考虑预期的变化，从而导致低估财政政策的效果（参见 Mertens 和 Ravn，2010）。同样，基于大量合理模型计算脉冲响应的符号限制使得结构分析的信息量较少（Braun 和 Bruggemann，2022）。近年来越来越流行的一种方法是使用仪器识别冲击。正如 Ramey（2016）所示，利用适当工具的变化可以解决财政远见（预期）问题，并提供稳健的结果。使用仪器进行识别的主要挑战是仪器本身的选择。所选工具必须与感兴趣的冲击相关并与其余冲击正交。这些条件是无法测试的，因此，使用仪器进行冲击识别的应用经常因缺乏严格的外生性1或相关性较低而受到批评。关于政府支出冲击，大多数现有文献利用军事支出的变化来构建识别工具。基本假设是，军事支出构成与经济状况无关的政府支出（Ramey 和 Shapiro，1998；Ramey，2011；Ben Zeev 和 Pappa，2017）。然而，Ramey（2016）认为，政府支出冲击的代理是根据历史记录构建的对于后朝鲜战争样本来说，军费支出是一个薄弱的工具。