公共危机中的政府协作治理能力*——中国省级新冠肺炎疫情防控的文本分析

协作治理，是应对公共危机形成的一种新的治理形式。本文使用文本分析法考察了2020年2月末各省区市政府在本次疫情应对政策中协作治理能力的四种关键机制：促进式顶层领导、开放式参与路径、明确的协作职责、透明信息披露的运用情形及运用效果。研究结果显示，30个省区市都在运用协作治理机制抗击疫情、恢复经济。四种机制的运用存在差异，整体上沿海地区运用协作治理机制更充分。进一步的分析显示政府协作治理机制的运用显著促进了各省份疫情中第三产业的经济恢复水平，原因在于其改善了省级层面经济恢复的市场环境。本文的研究结论表明，强大的政府协作治理机制有助于社会快速有效应对公共危机，也是优化市场环境的政府治理新途径。本文为政府协作治理的机制构成与实际效果提供了重要补充，在公共危机应对的背景下发展了政府治理的理论内容，为公共危机情境下政府职能转变思路提供了参考。     

从利益共同体到命运共同体:地方政府隐性债务的合作治理

在地方政府性债务的治理中,隐性债务因其增长迅速、规模不清和风险不确定,成为未来债务治理的重点和难点。隐性债务挟裹主体众多,关联利益甚广,因此,基于共同体视角,明确治理主体,有利于化解风险。在隐性债务生产阶段,因利而合的共同体大肆攫取利益导致隐性债务激增;在债务风险凸显阶段,利益共同体的本能选择不是"安危与共",而是"大难临头各自保"。但债务风险的"飞去来器效应"和群体性焦虑,将促使利益共同体走向命运共同体。命运共同体既是利益共同体,更是治理共同体。在隐性债务治理阶段,共同体应形成"共生"意识、采取"共治"行动、构筑"共担"保障,实现有效共治。     

Dynamic Cost Inefficiency of the European Union Meat Processing Firms

We apply dynamic data envelopment analysis (DEA) to estimate dynamic cost inefficiency for a sample of European Union (EU) large meat processing firms over the period 2005–2012 and decompose this into the contributions of technical and allocative inefficiency. The estimation of dynamic inefficiencies controls for adjustment costs associated with firms’ investments. We further contribute by measuring dynamic cost inefficiencies and their components with regard to own region group (managerial inefficiencies) and the gap between the pooled frontier and the region-specific frontier (programme inefficiencies). Results show that technical inefficiency tends to be the largest component of cost inefficiency when both conducting the analysis for the EU as a whole and estimating a region-specific frontier. Results suggest significant differences in cost, technical, and allocative inefficiencies between meat processing firms in eastern, western and southern EU countries. We also find that the gaps between the pooled and region-specific frontiers tend to be small to negligible, which suggests that the main source of pooled inefficiencies are shortcomings in managerial practices rather than differences in region-specific conditions.     

Effects of financial constraints on export performance of firms during the global financial crisis: microeconomic evidence from Korea

This study uses a manufacturing firm-level panel data set of South Korea for 2006–2013 to investigate the effect of financial constraints on the export performance of firms, with particular emphasis on the corporate ownership structure. The empirical results show that foreign multinational corporation (MNC) subsidiaries are not affected by financial constraint during both crisis and noncrisis periods, implying advantages of foreign ownership. However, domestic firms suffer more from financial constraints on exports during crisis years. In particular, domestic firms without parent firms are financially constrained during both crisis and noncrisis periods. However, those with parent firms do not experience financial constraints during noncrisis periods, although they too suffer from them during crisis periods. Thus, parent–subsidiary linkage among domestic firms plays an important role in alleviating financial constraints on export activity in noncrisis years but not as much during crisis years. Therefore, domestic parent firms exhibit less resilience to the global financial crisis, in comparison to foreign MNC parent firms.     

Are REITs more resilient than non-REITs? Evidence from natural experiments

REITs draw attention from investors around the world, yet our understanding of the various risks associated with such securities is limited. Using the introduction of Arrowhead, a low-latency high-frequency trading platform, to the Tokyo Stock Exchange and the financial crisis of 2008 as natural experiments, we compare the resilience of REITs and equities in terms of liquidity and volatility. The results indicate that the introduction of Arrowhead improved the quality of the Japanese REIT market but also increased the probability of flash crashes. We also find that although the financial crisis significantly deteriorated overall equity market quality, the Japanese REIT market was resilient. Finally, using a difference-in-differences regression model, we show that the higher transparency and better price discovery of REITs, compared to non-REITS, protected them from the negative effects of the financial crisis and the introduction of Arrowhead. Overall, our analysis shows that REITs are more resilient than non-REITs.     

A truly global crisis? Evidence from contagion dependence across international REIT markets

This study examines the global nature of the recent crisis under bivariate Markov-switching models for pre- and post-crisis periods using the breakpoint of August 9, 2007. It quantifies international synchronization of boom-bust regime switches to investigate contagion-type dynamic comovements of Real Estate Investment Trusts (REITs). Global REIT markets display persistent bust regimes from September 2008 to May 2009, whereas the regime-switching patterns are not significant in the pre-crisis period. The results provide new evidence for global REIT contagion phenomena and suggest greater difficulties in diversifying risks across global REIT markets during the post-crisis period.     

Deep learning for modeling the collection rate for third-party buyers

This study evaluates a wide range of machine learning techniques such as deep learning, boosting, and support vector regression to predict the collection rate of more than 65,000 defaulted consumer credits from the telecommunications sector that were bought by a German third-party company. Weighted performance measures were defined based on the value of exposure at default for comparing collection rate models. The approach proposed in this paper is useful for a third-party company in managing the risk of a portfolio of defaulted credit that it purchases. The main finding is that one of the machine learning models we investigate, the deep learning model, performs significantly better out-of-sample than all other methods that can be used by an acquirer of defaulted credits based on weighted-performance measures. By using unweighted performance measures, deep learning and boosting perform similarly. Moreover, we find that using a training set with a larger proportion of the dataset does not improve prediction accuracy significantly when deep learning is used. The general conclusion is that deep learning is a potentially performance-enhancing tool for credit risk management.     

地方财政政策逆周期调节：财政分权还是债务增发*

财政政策工具实际操作偏离最初设计将会降低政策工具的调控效果，导致宏观经济波动加剧。针对地方政府财政政策的逆周期性调控目标，本文关注财政分权深化和政府债务增发的逆周期性效应。研究发现：地方政府财政政策总体呈现顺周期特征。财政分权程度的提高放大了地方财政政策的顺周期性。地方政府债务增发使地方财政政策呈现逆周期特征。地方政府财政政策及其收入面、支出面均呈现顺周期性，由“顺”转“逆”的债务平衡点分别为0137，0113，0209。当前绝大部分地区的债务规模都在债务平衡点之下。驱动地方政府债务逆周期调控的内在因素是官员晋升激励。晋升激励的程度越高，地方债务逆周期调控的力度就越大。但外部市场融资环境的波动削弱了地方政府债务逆周期调控的力度。本文的政策主张是，不宜过度财政分权，应该扩大地方债发行规模，促使地方财政政策逆周期调节。     

Error analysis of finite difference and Markov chain approximations for option pricing

Mijatovi? and Pistorius proposed an efficient Markov chain approximation method for pricing European and barrier options in general one‐dimensional Markovian models. However, sharp convergence rates of this method for realistic financial payoffs, which are nonsmooth, are rarely available. In this paper, we solve this problem for general one‐dimensional diffusion models, which play a fundamental role in financial applications. For such models, the Markov chain approximation method is equivalent to the method of lines using the central difference. Our analysis is based on the spectral representation of the exact solution and the approximate solution. By establishing the convergence rate for the eigenvalues and the eigenfunctions, we obtain sharp convergence rates for the transition density and the price of options with nonsmooth payoffs. In particular, we show that for call‐/put‐type payoffs, convergence is second order, while for digital‐type payoffs, convergence is generally only first order. Furthermore, we provide theoretical justification for two well‐known smoothing techniques that can restore second‐order convergence for digital‐type payoffs and explain oscillations observed in the convergence for options with nonsmooth payoffs. As an extension, we also establish sharp convergence rates for European options for a rich class of Markovian jump models constructed from diffusions via subordination. The theoretical estimates are confirmed using numerical examples.     

Debt Overhang and Deleveraging in the US Household Sector: Gauging the Impact on Consumption

Using a novel data set for the U.S. states, this paper examines whether household debt and the protracted debt deleveraging help explain the dismal performance of U.S. consumption since 2007 in the aftermath of the housing bubble. By separating the concepts of deleveraging and debt overhang—a flow and a stock effect—we find that excessive indebtedness exerted a meaningful drag on consumption over and beyond wealth and income effects. The overall effect, however, is modest—‐around one sixth of the slowdown in consumption between 2000–06 and 2007–12—and mostly driven by states with particularly large imbalances in their household sector. This might be indicative of non‐linearities, whereby indebtedness begins to bite only when misalignments from sustainable debt dynamics become excessive.