1. Introduction and Overview. 2. Detecting Influential Observations and Outliers. 3. Detecting and Assessing Collinearity. 4. Applications and Remedies. 5. Research Issues and Directions for Extensions. Bibliography. Author Index. Subject Index.

Regression Diagnostics: Identifying Influential Data and Sources of Collinearity

We develop a new index of economic policy uncertainty (EPU) based on newspaper coverage frequency Several types of evidence – including human readings of 12,000 newspaper articles – indicate that our index proxies for movements in policy-related economic uncertainty Our US index spikes near tight presidential elections, Gulf Wars I and II, the 9/11 attacks, the failure of Lehman Brothers, the 2011 debt-ceiling dispute and other major battles over fiscal policy Using firm-level data, we find that policy uncertainty raises stock price volatility and reduces investment and employment in policy-sensitive sectors like defense, healthcare, and infrastructure construction At the macro level, policy uncertainty innovations foreshadow declines in investment, output, and employment in the United States and, in a panel VAR setting, for 12 major economies Extending our US index back to 1900, EPU rose dramatically in the 1930s (from late 1931) and has drifted upwards since the 1960s

/pdf/measuring-economic-policy-uncertainty-4nrg3ei76f.pdf

Measuring Economic Policy Uncertainty

The 'credit channel' theory of monetary policy transmission holds that informational frictions in credit markets worsen during tight- money periods. The resulting increase in the external finance premium--the difference in cost between internal and external funds-- enhances the effects of monetary policy on the real economy. We document the responses of GDP and its components to monetary policy shocks and describe how the credit channel helps explain the facts. We discuss two main components of this mechanism, the balance-sheet channel and the bank lending channel. We argue that forecasting exercises using credit aggregates are not valid tests of this theory.

Inside the Black Box: The Credit Channel of Monetary Policy Transmission

https://pubs.aeaweb.org/doi/pdfplus/10.1257/jep.9.4.27

The financial market turmoil in 2007 and 2008 has led to the most severe financial crisis since the Great Depression and threatens to have large repercussions on the real economy The bursting of the housing bubble forced banks to write down several hundred billion dollars in bad loans caused by mortgage delinquencies At the same time, the stock market capitalization of the major banks declined by more than twice as much While the overall mortgage losses are large on an absolute scale, they are still relatively modest compared to the $8 trillion of US stock market wealth lost between October 2007, when the stock market reached an all-time high, and October 2008 This paper attempts to explain the economic mechanisms that caused losses in the mortgage market to amplify into such large dislocations and turmoil in the financial markets, and describes common economic threads that explain the plethora of market declines, liquidity dry-ups, defaults, and bailouts that occurred after the crisis broke in summer 2007 To understand these threads, it is useful to recall some key factors leading up to the housing bubble The US economy was experiencing a low interest rate environment, both because of large capital inflows from abroad, especially from Asian countries, and because the Federal Reserve had adopted a lax interest rate policy Asian countries bought US securities both to peg the exchange rates at an export-friendly level and to hedge against a depreciation of their own currencies against the dollar, a lesson learned from the Southeast Asian crisis of the late 1990s The Federal Reserve Bank feared a deflationary period after the bursting of the Internet bubble and thus did not counteract the buildup of the housing bubble At the same time, the banking system underwent an important transformation The

/pdf/deciphering-the-liquidity-and-credit-crunch-2007-2008-3612pahtil.pdf

Deciphering the Liquidity and Credit Crunch 2007-2008

We re-examine the evidence on the relationship between credit spreads and economic activity, by constructing a credit spread index based on an extensive data set of prices of outstanding corporate bonds trading in the secondary market. Compared with the standard default-risk indicators, our credit spread index is a robust predictor of economic activity at both the short- and longer-term horizons. Using an empirical framework, we decompose the index into a predictable component that captures the available firm-specific information on expected defaults and a residual component—the excess bond premium—which we argue likely reflects variation in the price of default risk rather than variation in the risk of default. Our results indicate that the predictive content of credit spreads for economic activity is due primarily to movements in the excess bond premium. Innovations in the excess bond premium that are orthogonal to the current state of the economy are shown to lead to significant declines in economic activity and equity prices. We also show that a deterioration in the creditworthiness of broker-dealers—key financial intermediaries in the corporate cash market—causes an increase in the excess bond premium. These findings support the notion that a rise in the excess bond premium represents a reduction in the e!ective risk-bearing capacity of the financial sector and, as a result, a contraction in the supply of credit with significant adverse consequences for the macroeconomy.

/pdf/credit-spreads-and-business-cycle-fluctuations-2hg0cfvcs2.pdf

Credit Spreads and Business Cycle Fluctuations

Micro- and macro-level evidence indicates that fluctuations in idiosyncratic uncertainty have a large effect on investment; the impact of uncertainty on investment occurs primarily through changes in credit spreads; and innovations in credit spreads have a strong effect on investment, irrespective of the level of uncertainty. These findings raise a question regarding the economic significance of the traditional "wait-and-see" effect of uncertainty shocks and point to financial distortions as the main mechanism through which fluctuations in uncertainty affect macroeconomic outcomes. The relative importance of these two mechanisms is analyzed within a quantitative general equilibrium model, featuring heterogeneous firms that face time-varying idiosyncratic uncertainty, irreversibility, nonconvex capital adjustment costs, and financial frictions. The model successfully replicates the stylized facts concerning the macroeconomic implications of uncertainty and financial shocks. By influencing the effective supply of credit, both types of shocks exert a powerful effect on investment and generate countercyclical credit spreads and procyclical leverage, dynamics consistent with the data and counter to those implied by the technology-driven real business cycle models.

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Uncertainty, Financial Frictions, and Investment Dynamics

https://www.nber.org/system/files/working_papers/w14863/w14863.pdf

Credit Market Shocks and Economic Fluctuations: Evidence from Corporate Bond and Stock Markets

https://www.federalreserve.gov/econresdata/ifdp/2016/files/ifdp1166.pdf

The Macroeconomic Impact of Financial and Uncertainty Shocks

Using confidential product-level price data underlying the U.S. Producer Price Index (PPI), this paper analyzes the effect of changes in firms’ financial conditions on their price-setting behavior during the ”Great Recession” that surrounds the financial crisis. The evidence indicates that during the height of the crisis in late 2008, firms with “weak” balance sheets increased prices significantly relative to industry averages, whereas firms with “strong” balance sheets lowered prices, a response consistent with an adverse demand shock. These stark differences in price-setting behavior are consistent with the notion that financial frictions may significantly influence the response of aggregate inflation to macroeconomic shocks. We explore the implications of these empirical findings within a general equilibrium framework that allows for customer markets and departures from the frictionless financial markets. In the model, firms have an incentive to set a low price to invest in market share, though when financial distortions are severe, firms forgo these investment opportunities and maintain high prices in an effort to preserve their balance-sheet capacity. Consistent with our empirical findings, the model with financial distortions—relative to the baseline model without such distortions—implies a substantial attenuation of price dynamics in response to contractionary demand shocks.

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Egon Zakrajsek

Papers

Credit Spreads and Business Cycle Fluctuations

Uncertainty, Financial Frictions, and Investment Dynamics

Credit Market Shocks and Economic Fluctuations: Evidence from Corporate Bond and Stock Markets

The Macroeconomic Impact of Financial and Uncertainty Shocks

Inflation Dynamics During the Financial Crisis