Financial crisis,Omori's law,and negative entropy flow

The 2008 global financial crisis has revived great interest in early warning system (EWS) models for reducing the risks of future crises. Existing EWS models employ aggregated variables that cannot examine the nonlinear dynamics of participating players on scales smaller than a country in unstable, non-equilibrium economies. To help understand the mechanism of financial crises and identify new robust indicators for financial crises and economic recessions, in this work, we take an “anatomical” approach, i.e., to examine the income structures of different sectors of an economy separately, as well as to analyze the exposure networks associated with Fannie Mae/Freddie Mac, Lehman Brothers, and American International Group. We show that the losses in exposure networks can be modeled by a two-parameter Omori-law-like distribution for earthquake aftershocks. Such a distribution suggests that losses will be widespread around crises or recessions. Indeed, around crises or recessions, the heavy-tailed distributions for the negative income cluster are even heavier than those for the positive income cluster. Consequently, the entropies associated with the distribution of the negative income cluster exceed that of the positive income cluster. Moreover, instability propagates from the crisis initiating sector to other sectors. Therefore, the anatomical approach developed here can indeed shed some light on the detailed dynamics of financial crises and economic recessions, and the distribution and entropy approaches can help predict economic downturns.     

The risk of financial crises: Is there a role for income inequality?

Could macroeconomic factors such as income inequality be the real root cause of financial crises? We explore a broad variety of financial and macroeconomic variables and employ a general-to-specific model selection process to find the most reliable predictors of financial crises in developed countries over a period of more than 100 years. Our in-sample results indicate that income inequality has predictive power beyond loan growth and several other financial variables. Out-of-sample forecasts for individual predictors show that their predictive power tends to vary considerably over time, but income inequality has predictive power in each forecasting period.     

Credit conditions and recoveries from financial crises

Recoveries from recessions associated with a financial crisis tend to be sluggish. In this paper, we present evidence that stressed credit conditions are an important factor constraining the pace of recovery. In particular, using industry-level data, we find that industries relying more on external finance grow more slowly than other industries during recoveries from recessions associated with financial crises. Additional tests, based on establishment size, on alternative definitions of financial crises, and on corporate-government interest rate spreads, support the findings. Moreover, for subsets of industries where financial frictions are more severe, we find much stronger differential growth effects.     

Financial Development and Income Inequality: Long-Run Relationship and Short-Run Heterogeneity

This article examines the dynamic relationship between financial development and income inequality using the PMG. We find that financial development will reduce inequality in the long run, while it can increase inequality in the short run. Using the estimates of country-specific short-run coefficients, we also find that adverse short-run effects of financial development are associated with the vulnerabilities of countries in terms of their greater susceptibility to crises and poor quality of governance. Good governance seems to be important for achieving inclusive growth though financial development.     

Does inequality lead to a financial crisis?

The recent global crisis has sparked interest in the relationship between income inequality, credit booms, and financial crises. Rajan (2010) and Kumhof and Rancière (2011) propose that rising inequality led to a credit boom and eventually to a financial crisis in the US in the first decade of the 21st century as it did in the 1920s. Data from 14 advanced countries between 1920 and 2000 suggest these are not general relationships. Credit booms heighten the probability of a banking crisis, but we find no evidence that a rise in top income shares leads to credit booms. Instead, low interest rates and economic expansions are the only two robust determinants of credit booms in our data set. Anecdotal evidence from US experience in the 1920s and in the years up to 2007 and from other countries does not support the inequality, credit, crisis nexus. Rather, it points back to a familiar boom-bust pattern of declines in interest rates, strong growth, rising credit, asset price booms and crises.     

When Credit Bites Back

Using data on 14 advanced countries between 1870 and 2008 we document two key facts of the modern business cycle: relative to typical recessions, financial crisis recessions are costlier, and more credit‐intensive expansions tend to be followed by deeper recessions (in financial crises or otherwise) and slower recoveries. We use local projection methods to condition on a broad set of macro‐economic controls to study how past credit accumulation impacts key macro‐economic variables such as output, investment, lending, interest rates, and inflation. The facts that we uncover lend support to the idea that financial factors play an important role in the modern business cycle.     

The financial Kuznets curve: Evidence for the euro area

The paper introduces a new specification of the Kuznets curve, where turning point per capita income is conditioned on the level of financial development. We then provide new evidence on income inequality dynamics for the euro area (EA) countries since the mid-1980s. We find evidence in favor of an EA-wide financial Kuznets curve, also resilient to the recent financial and economic crises. From a policy perspective, our findings highlight the importance of financial development in fostering not only economic growth, but also a more even distribution of income.     

Economic Growth and Inequality: Why It Matters and What's Coming Next

This article makes the case that the recent rise in income inequality in OECD countries reflects profound changes in the economic model that previously resulted in growth, prosperity, and social progress during the second half of the last century. The author begins by citing French economist Thomas Piketty's identification of the key driver of rising income inequality as the recent sharp increase in the share of national income going to capital (defined as interest, dividends and other investment returns) and the accompanying decline in the share going to labor (in the form of wages, salaries, pension, and other work‐related benefits). For most of the last 100 years, a successful balance was struck in a majority of OECD countries between the returns to capital and labor. Within the framework of nationally defined economies, labor could effectively advocate for its share of the productivity gains by capital, and governments had the ability to constrain the free movement of capital, set labor compensation standards, and redistribute income through progressive taxation. The author explores how two developments—globalization and the rise of machine intelligence—are disrupting this social contract and reshaping our economy and society. The combination of these two developments, by accelerating the flow of income to capital and away from labor, is eroding the historical relationship between capital, labor, and governments that has long prevailed in most OECD countries. As this happens, we are seeing rising income inequality and the erosion of the middle class, which had been the driver of economic growth for most of the past century. Indeed, the thesis of Piketty's book, Capital in the Twenty‐First Century, is that such an effect may well be taking us back to the pre‐20th century norm of high income inequality and low economic growth. In his closing arguments, the author suggests that avoiding this scenario will be more complicated than simply raising taxes on capital, as proposed by Piketty. It may well require a fundamental rethinking of the role of employment as the primary mechanism for income distribution in society and how we prepare our workforce for an economy and society in which the concept of work will be radically redefined.     

Banking system control,capital allocation,and economy performance

We observe less efficient capital allocation in countries whose banking systems are more thoroughly controlled by tycoons or families. The magnitude of this effect is similar to that of state control over banking. Unlike state control, tycoon or family control also correlates with slower economic and productivity growth, greater financial instability, and worse income inequality. These findings are consistent with theories that elite-capture of a country’s financial system can embed “crony capitalism.”     

A Study on the Effect of Financial Inclusion on the Relationship Between Income Inequality and Economic Growth

In this article, we attempt to estimate whether financial inclusion, expressed as financial accessibility, has a positive effect on reducing income inequality. Furthermore, we estimate the effect of such financial inclusion on economic growth by reducing income inequality. From the results of our empirical analysis, we can draw the following three conclusions. First, income inequality has a very negative effect on GDP growth. The negative relationship between income inequality and GDP growth is strong in low-income countries. In addition, income inequality has a stronger effect on reducing economic growth in high-fragility countries. Second, progressivity is not a major factor in reducing income inequality in low-income countries or in high-fragility countries. Finally, financial inclusion improves the relationship between income inequality and economic growth. The reduction in income inequality through financial inclusion changes the negative relationship between income inequality and economic growth into a positive relationship. This trend is stronger in high-fragility countries than in low-fragility countries.     

金融摩擦、收入风险与财富不平等

本文通过构建带有职业选择的两部门异质模型,探讨了个体面临的金融摩擦和收入风险对财富分配的作用机制。结果发现,经济中存在的金融摩擦会通过职业选择、自我保险和自融资来影响个人的财富积累,从而导致财富的集中和不平等。对模型模拟的结果表明:降低金融摩擦在总体上会降低财富不平等程度,但对不同财富阶层的影响不同,其在大幅减少前1%和前10%阶层财富份额的同时,虽然也会在一定程度上提升后50%阶层的财富份额,但提升幅度并不大,过高或过低的企业家收入风险,都会加大财富不平等程度,因而存在一个使经济中财富不平等程度最低的适度企业家收入风险水平;虽然金融摩擦和收入风险都会影响经济中的财富不平等,但收入风险本身对财富不平等程度的影响较小,其主要是通过金融摩擦放大了经济中财富不平等的程度。     

Financial Structure and Income Inequality: Evidence from China

This study investigates the relationship between financial structure and income inequality in China and explores a channel for changes of financial structure to influence income inequality. Our results suggest that, relative to total bank credit, an increase in the raised capital from the stock market reduces income inequality, whereas a rise of turnover in the stock market augments income inequality. Financial structure affects income inequality by influencing the development of medium-sized enterprises. Our evidence supports the financial structure relevancy view. To reduce income inequality, the Chinese government should help to promote equity financing and decrease excessive speculation on the stock market.     

Bank recapitalization and economic recovery after financial crises

Does support to distressed banks early on during financial crises mitigate the macroeconomic consequences of financial distress, and if so does it matter what form the intervention takes? We analyze the effects of government and central bank interventions in 69 systemic banking crises since 1980, of which 29 are part of the recent global financial crisis. Our estimation approach controls for the correlation between intervention measures and the time-invariant component of unobservable crisis severity. We find that timely bank recapitalizations substantially reduce the duration of recessions, underscoring the distortions caused by zombie banks and the costs of regulatory forbearance.     

Sovereign debt and reserves with liquidity and productivity crises

During the recent financial crisis, emerging economies have kept accumulating both sovereign reserves and debt. To account for this empirical fact, we model the optimal portfolio choice of a sovereign that is subject to liquidity and productivity shocks. We determine the equilibrium level of debt and its cost by solving a contracting game between sovereign and international lenders. Although raising debt increases the sovereign exposure to liquidity and productivity crises, the simultaneous accumulation of reserves can mitigate the negative effects of such crises. This mechanism rationalizes the complementarity between debt and reserves.     

The scarring effect of recessions

According to the conventional view, recessions improve resource allocation by driving out less productive firms. This paper posits an additional scarring effect: recessions impede the developments of potentially superior firms by destroying them during their infancy. A model is developed to capture both the cleansing and the scarring effects. A key ingredient of the model is that idiosyncratic productivity is not directly observable, but can be learned over time. When calibrated with statistics on entry, exit and productivity differentials, the model suggests that the scarring effect dominates the cleansing effect, and gives rise to lower average productivity during recessions.     

Household Debt and Income Inequality, 1963–2003

I construct an economy with heterogeneous agents that mimics the time-series behavior of the earnings distribution in the United States from 1963 to 2003. Agents face aggregate and idiosyncratic shocks and accumulate real and financial assets. I estimate the shocks that drive the model using data on income inequality, aggregate income, and measures of financial liberalization. I show how the model economy can replicate two empirical facts: the trend and cyclical behavior of household debt and the diverging patterns in consumption and wealth inequality over time. While business cycle fluctuations can account for the short-run changes in household debt, its prolonged rise of the 1980s and the 1990s can be quantitatively explained only by the concurrent increase in income inequality.     

收入不平等、政府支出与实际汇率——基于跨国面板数据的研究

已有较多研究讨论了实际汇率的决定因素,而从收入不平等角度出发的研究并不多。本文搜集和整理了172个国家和地区1970年到2016年的跨国面板数据,分析了收入不平等对一国实际汇率的影响,并引入政府支出探究了收入分配对非贸易品部门和实际汇率的影响机制。实证检验结果表明,对于非OECD国家,收入不平等和实际汇率显著负相关,即收入越不平等,实际汇率高估越严重,而在OECD国家中这一现象并不存在。进一步的影响机制分析发现,对于非OECD国家,一国收入不平等加剧会导致该国政府支出增多,从而扩大了非贸易品部门规模,导致非贸易品的相对价格上升,使得实际汇率高估。     

Is There a Better Way to Examine Income Inequality?

Dividing U.S. tax returns into half‐millionaires (those reporting adjusted gross income (AGI) of $500,000 or more in a given year) and their complement allows greater use of IRS data on income sources than is possible with an analysis that examines a fixed percentage of returns, such as the top one percent. Contrary to popular perception and media rhetoric, the inflation‐adjusted difference between the reported AGI of half‐millionaires and the rest actually declined by 25 percent from 1993 to 2011. The income gap between half‐millionaires and other filers reflects differences in kinds of income, with half‐millionaires deriving a much larger fraction of their income from capital investments whose varying returns make that component of income—and thus the income of half‐millionaires—more volatile. The percentage of total tax returns filed by half‐millionaires in a given year and the percentage of their income derived from taxable gains reported on Schedule D account for virtually all of the variation in the half‐millionaire percentage of aggregate AGI. As this finding suggests, the expanding income share for half‐millionaires does not signify that some collection of privileged rich have become richer. The significant net growth in the percentage of filers who are half‐millionaires has been uneven because a significant proportion of their income derives from volatile Schedule D gains, which are higher during economic expansions and lower during recessions. The incomes of half‐millionaires—and especially millionaires—are anything but recession proof. But even with that volatile component of income included, when their percentage of returns doubles, their percentage of income less than doubles, consistent with declining income inequality.     

Monetary policy under financial uncertainty

Monetary policy may play a substantial role in mitigating the effects of financial crises. In this paper, I suppose that the economy occasionally but infrequently experiences crises, where financial variables affect the broader economy. I analyze optimal monetary policy under such financial uncertainty, where policymakers recognize the possibility of crises. Optimal monetary policy is affected during the crisis and in normal times, as policymakers guard against the possibility of crises. In the estimated model this effect is quite small. Optimal policy does change substantially during a crisis, but uncertainty about crises has relatively little effect.     

What is the systemic risk exposure of financial institutions?

I compare the performance of three measures of institution-level systemic risk exposure — Exposure CoVaR (Adrian and Brunnermeier, 2016), systemic expected shortfall (Acharya et al., 2016), and Granger causality (Billio et al., 2012). I modify Exposure CoVaR to allow for forecasting, and estimate the ability of each measure to forecast the performance of financial institutions during systemic crisis periods in 1998 (LTCM) and 2008 (Lehman Brothers). I find that Exposure CoVaR forecasts the within-crisis performance of financial institutions, and provides useful forecasts of future systemic risk exposures. Systemic expected shortfall and Granger causality do not forecast the performance of financial institutions reliably during crises. I also find, using cross-sectional regressions, that foreign equity exposure and securitization income determine systemic risk exposure during the 1998 and 2008 crises, respectively; financial institution size determines systemic risk exposure during both crisis periods; and executive compensation does not determine systemic risk exposure.