Betting the House
2014-28 | With Schularick and Taylor | December 2014
Is there a link between loose monetary conditions, credit growth, house price booms, and financial instability? This paper analyzes the role of interest rates and credit in driving house price booms and busts with data spanning 140 years of modern economic history in the advanced economies. We exploit the implications of the macroeconomic policy trilemma to identify exogenous variation in monetary conditions: countries with fixed exchange regimes often see fluctuations in short-term interest rates unrelated to home economic conditions. We use novel instrumental variable local projection methods to demonstrate that loose monetary conditions lead to booms in real estate lending and house prices bubbles; these, in turn, materially heighten the risk of financial crises. Both effects have become stronger in the postwar era.
The Great Mortgaging: Housing Finance, Crises, and Business Cycles
2014-23 | With Schularick and Taylor | September 2014
This paper unveils a new resource for macroeconomic research: a long-run dataset covering disaggregated bank credit for 17 advanced economies since 1870. The new data show that the share of mortgages on banks’ balance sheets doubled in the course of the 20th century, driven by a sharp rise of mortgage lending to households. Household debt to asset ratios have risen substantially in many countries. Financial stability risks have been increasingly linked to real estate lending booms which are typically followed by deeper recessions and slower recoveries. Housing finance has come to play a central role in the modern macroeconomy.
Sovereigns versus Banks: Credit, Crises, and Consequences
2013-37 | With Schularick and Taylor | February 2014
Two separate narratives have emerged in the wake of the Global Financial Crisis. One interpretation speaks of private financial excess and the key role of the banking system in leveraging and deleveraging the economy. The other emphasizes the public sector balance sheet over the private and worries about the risks of lax fiscal policies. However, the two may interact in important and understudied ways. This paper examines the co-evolution of public and private sector debt in advanced countries since 1870. We find that in advanced economies significant financial stability risks have mostly come from private sector credit booms rather than from the expansion of public debt. However, we find evidence that high levels of public debt have tended to exacerbate the effects of private sector deleveraging after crises, leading to more prolonged periods of economic depression. We uncover three key facts based on our analysis of around 150 recessions and recoveries since 1870: (i) in a normal recession and recovery real GDP per capita falls by 1.5 percent and takes only 2 years to regain its previous peak, but in a financial crisis recession the drop is typically 5 percent and it takes over 5 years to regain the previous peak; (ii) the output drop is even worse and recovery even slower when the crisis is preceded by a credit boom; and (iii) the path of recovery is worse still when a credit-fueled crisis coincides with elevated public debt levels. Recent experience in the advanced economies provides a useful out-of-sample comparison, and meshes closely with these historical patterns. Fiscal space appears to be a constraint in the aftermath of a crisis, then and now.
Output and Unemployment Dynamics
2013-32 | With Daly, Fernald, and Nechio | November 2014
The evolution of the secular and business-cycle comovement between different components of the production function and unemployment, Okun’s law, provides important stylized facts for macro modelers. We show that total hours worked adjust two-to-one to changes in the unemployment rate. The cyclicality of productivity has changed over time and as a function of the type of shock hitting the economy. Even the responses of different margins to shocks vary over time. We document these and other features of the data using the growth-accounting decomposition in Fernald (2014)
The Time for Austerity: Estimating the Average Treatment Effect of Fiscal Policy
2013-25 | With Taylor | September 2013
Elevated government debt levels in advanced economies have risen rapidly as sovereigns absorbed private sector losses and cyclical deficits blew up in the Global Financial Crisis and subsequent slump. A rush to fiscal austerity followed but its justifications and impacts have been heavily debated. Research on the effects of austerity on macroeconomic aggregates remains unsettled, mired by the difficulty of identifying multipliers from observational data. This paper reconciles seemingly disparate estimates of multipliers within a unified framework. We do this by first evaluating the validity of common identification assumptions used by the literature and find that they are largely violated in the data. Next, we use new propensity score methods for time-series data with local projections to quantify how contractionary austerity really is, especially in economies operating below potential. We find that the adverse effects of austerity may have been understated.
Semiparametric Estimates of Monetary Policy Effects: String Theory Revisited
2013-24 | With Angrist and Kuersteiner | August 2013
We develop flexible semiparametric time series methods that are then used to assess the causal effect of monetary policy interventions on macroeconomic aggregates. Our estimator captures the average causal response to discrete policy interventions in a macro-dynamic setting, without the need for assumptions about the process generating macroeconomic outcomes. The proposed procedure, based on propensity score weighting, easily accommodates asymmetric and nonlinear responses. Application of this estimator to the effects of monetary restraint shows the Fed to be an effective inflation fighter. Our estimates of the effects of monetary accommodation, however, suggest the Federal Reserve’s ability to stimulate real economic activity is more modest. Estimates for recent financial crisis years are similar to those for the earlier, pre-crisis period.
Performance Evaluation of Zero Net-Investment Strategies
NBER Working Paper 17150 | With Taylor | June 2011
This paper introduces new nonparametric statistical methods to evaluate zero-cost investment strategies. We focus on directional trading strategies, risk-adjusted returns, and the investor’s decisions under uncertainty as the core of our analysis. By relying on classification tools with a long tradition in the sciences and biostatistics, we can provide a tighter connection between model-based risk characteristics and the no-arbitrage conditions for market efficiency. Moreover, we extend the methods to multicategorical settings, such as when the investor can sometimes take a neutral position. A variety of inferential procedures are provided, many of which are illustrated with applications to excess equity returns and to currency carry trades.
A Chronology of International Business Cycles Through Nonparametric Decoding
Unpublished manuscript | With Fushing, Chen, and Berge | October 2010
This paper introduces a new empirical strategy for the characterization of business cycles. It combines nonparametric decoding methods that classify a series into expansions and recessions but does not require specification of the underlying stochastic process generating the data. It then uses network analysis to combine the signals obtained from different economic indicators to generate a unique chronology. These methods generate a record of peak and trough dates comparable, and
in one sense superior, to the NBER’s own chronology. The methods are then applied to 22 OECD countries to obtain a global business cycle chronology.
Empirical Simultaneous Confidence Regions for Path-Forecasts
Unpublished manuscript | With Knuppel and Marcellino | March 2010
Measuring and displaying uncertainty around path-forecasts, i.e. forecasts made in period T about the expected trajectory of a random variable in periods T+1 to T+H is a key ingredient for decisionmaking under uncertainty. The probabilistic assessment about the set of possible trajectories that the variable may follow over time is summarized by the simultaneous confidence region generated from its forecast generating distribution. However, if the null model is only approximative or altogether
unavailable, one cannot derive analytic expressions for this confidence region, and its non-parametric estimation is impractical given commonly available predictive sample sizes. Instead, this paper derives the approximate rectangular confidence regions that control false discovery rate error, which are a function of the predictive sample covariance matrix and the empirical distribution of the Mahalanobis distance of the path-forecast errors. These rectangular regions are simple to construct and appear to work well in a variety of cases explored empirically and by simulation. The proposed techniques are applied to provide confidence bands around the Fed and Bank of England real-time path-forecasts of
growth and inflation.
Fluctuations in the Exchange Rates and the Carry Trade
Bank of Korea WP 405 | With Chung | October 2009
This paper examines the relationship between the carry trade and exchange rate volatility. In a carry trade, investors borrow in low-yield currencies and invest in high-yield currencies while bearing the exchange rate risk of depreciation that could undo this profit opportunity. Prior to the onset of the 2007 global financial crisis, the carry trade provided consistently high returns, later offset by large depreciations of high-yield
currencies since. Thus, low exchange rate volatility prior to 2007 is often blamed for inducing investors to take on excessive carry trade risks. On the other hand, high levels of exchange rate volatility can be harmful because of currency mismatch–the well-known fear of floating. We investigate these issues by examining how volatility and the carry trade are related in the context of recent work by Brunnermeier, Nagel, and Pedersen (2009) and Jorda and Taylor (2009).
Assessing the Historical Role of Credit: Business Cycles, Financial Crises and the Legacy of Charles S. Peirce
International Journal of Forecasting 30(3), July 2014, 729-740
This paper provides a historical overview of financial crises and their origins. The objective is to discuss a few of the modern statistical methods that can be used to evaluate predictors of these rare events. The problem involves the prediction of binary events, and therefore fits modern statistical learning, signal processing theory, and classification methods. The discussion also emphasizes the need for statistics and computational techniques to be supplemented with economics. The success of a forecast in this environment hinges on the economic consequences of the actions taken as a result of the forecast, rather than on typical statistical metrics of prediction accuracy.
Computing Systemic Risk Using multiple Behavioral and Keystone Networks: The Emergence of a Crisis in Primate Societies and Banks
International Journal of Forecasting 30(3), July 2014, 797-806 | With Fushing, Beisner, and McCowan
What do the behavior of monkeys in captivity and the financial system have in common? The nodes in such social systems relate to each other through multiple and keystone networks, not just one network. Each network in the system has its own topology, and the interactions among the system’s networks change over time. In such systems, the lead into
a crisis appears to be characterized by a decoupling of the networks from the keystone network. This decoupling can also be seen in the crumbling of the keystone’s power structure toward a more horizontal hierarchy. This paper develops nonparametric methods for describing the joint model of the latent architecture of interconnected networks in order to describe this process of decoupling, and hence provide an early warning system of an
Labor Markets in the Global Financial Crisis: The Good, the Bad and the Ugly
National Institute Economic Review 228: R58-R64, May 2014 | With Nechio, Daly, and Fernald
This note examines labor market performance across countries through the lens of Okun’s Law. We find that after the 1970s but prior to the global financial crisis of the 2000s, the Okun’s Law relationship between output and unemployment became more homogenous across countries. These changes presumably reflected institutional and technological changes. But, at least in the short term, the global financial crisis undid much of this convergence, in part because the affected countries adopted different labor market policies in response to the global demand shock.
Empirical Simultaneous Prediction Regions for Path-Forecasts
International Journal of Forecasting 29(3), September 2013, 456-468 | With Marcellino and Knuppel
This paper investigates the problem of constructing prediction regions for forecast trajectories 1 to H periods into the future-a path forecast. When the null model is only approximative, or completely unavailable, one cannot either derive the usual analytic expressions or resample from the null model. In this context, this paper derives a method for constructing approximate rectangular regions for simultaneous probability coverage that correct for serial correlation in the case of elliptical distributions. In both Monte Carlo studies and an empirical application to the Greenbook path-forecasts of growth and inflation, the performance of this method is compared to the performances of the Bonferroni approach and the approach which ignores simultaneity.
A Chronology of Turning Points in Economic Activity
Journal of the Spanish Economic Association – SERIES 4(1), March 2013, 1-34 | With Berge
This paper codifies in a systematic and transparent way a historical chronology of business cycle turning points for Spain reaching back to 1850 at annual frequency, and 1939 at monthly frequency. Such an exercise would be incomplete without assessing the new chronology itself and against others—this we do with modern statistical tools of signal detection theory. We also use these tools to determine which of several existing economic activity indexes provide a better signal on the underlying state of the economy. We conclude by evaluating candidate leading indicators and hence construct recession probability forecasts up to 12 months in the future.
When Credit Bites Back
Journal of Money Credit and Banking 45(s2), 2013, 3-28 | With Schularick and Taylor
This paper studies the role of credit in the business cycle, with a focus on private credit overhang. Based on a study of the universe of over 200 recession episodes in 14 advanced countries between 1870 and 2008, we document two key facts of the modern business cycle: financial-crisis recessions are more costly than normal recessions in terms of lost output; and for both types of recession, more credit-intensive expansions tend to be followed by deeper recessions and slower recoveries. In additional to unconditional analysis, we use local projection methods to condition on a broad set of macroeconomic controls and their lags. Then we study how past credit accumulation impacts the behavior of not only output but also other key macroeconomic variables such as 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 Harrod-Balassa-Samuelson Hypothesis: Real Exchange Rates and their Long-Run Equilibrium
International Economic Review 53(2), May 2012, 609-634 | With Chong and Taylor
Frictions and perturbations may influence currency values in the short run, but it is generally acknowledged that real-exchange rates eventually settle toward equilibrium. The puzzle then is how gradually this parity is reached given the fluidity in foreign exchange markets. Persistent differences in the relative productivity of countries—a broad characterization of the Harrod–Balassa–Samuelson hypothesis—may help explain this puzzle. This article introduces methods to estimate equilibrium adjustment paths semiparametrically, and then sort how each of these components influences the dynamics of exchange rates. This is done in a dynamic panel setting by introducing novel local projections methods for cointegrated systems. Productivity shocks affect dynamics, and after adjusting for these factors, adjustment toward equilibrium is relatively rapid.
The Carry Trade and Fundamentals: Nothing to Fear but FEER Itself
Journal of International Economics 88(1), 2012, 74-90 | With Taylor
The carry trade is the investment strategy of going long in high-yield target currencies and short in low-yield funding currencies. Recently, this naive trade has seen very high returns for long periods, followed by large crash losses after large depreciations of the target currencies. Based on low Sharpe ratios and negative skew, these trades could appear unattractive, even when diversified across many currencies. But more sophisticated conditional trading strategies exhibit more favorable payoffs. We apply novel (within economics) binary-outcome classification tests to show that our directional trading forecasts are informative, and out-of-sample loss-function analysis to examine trading performance.
The critical conditioning variable, we argue, is the fundamental equilibrium exchange rate (FEER). Expected returns are lower, all else equal, when the target currency is overvalued. Like traders, researchers should incorporate this information when evaluating trading strategies. When we do so, some questions are resolved: negative skewness is purged, and market volatility (VIX) is uncorrelated with returns; other puzzles remain: the more sophisticated strategy has a very high Sharpe ratio, suggesting market inefficiency.
Financial Crises, Credit Booms, and External Imbalances: 140 Years of Lessons
IMF Economic Review 59(2), June 2011, 340-378 | With Schularick and Taylor
Do external imbalances increase the risk of financial crises? This paper studies the experience of 14 developed countries over 140 years (1870-2008). It exploits the long-run data set in a number of different ways. First, the paper applies new statistical tools to describe the temporal and spatial patterns of crises and identifies five episodes of global financial instability in the past 140 years. Second, it studies the macroeconomic dynamics before crises and shows that credit growth tends to be elevated and short-term interest rates depressed relative to the “natural rate” in the run-up to global financial crises. Third, the paper shows that recessions associated with crises lead to deeper slumps and stronger turnarounds in imbalances than during normal recessions. Finally, the paper asks to what extent external imbalances help predict financial crises. The overall result is that credit growth emerges as the single best predictor of financial instability. External imbalances have played an additional role, but more so in the pre-WWII era of low financialization than today.
Estimation and Inference by the Method of Projection Minimum Distance: An Application to the New Keynesian Hybrid Phillips Curve
International Economic Review 52(2), May 2011, 461-487 | With Kozicki
The stability of the solution path in a macroeconomic model implies that it admits a Wold representation. This Wold representation can be estimated semiparametrically by local projections and used to estimate the model’s parameters by minimum distance techniques even when the stochastic process for the solution path is unknown or unconventional. We name this two-step estimation procedure “projection minimum distance” and investigate its statistical properties for the broad class of models where the mapping between Wold coefficients and parameters is linear. This includes many situations with likelihood score functions nonlinear in the parameters that would otherwise require numerical optimization routines.
Evaluating the Classification of Economic Activity into Recessions and Expansions
American Economic Journal: Macroeconomics 3(2), April 2011, 246-277 | With Berge
The Business Cycle Dating Committee of the National Bureau of
Economic Research provides a historical chronology of business
cycle turning points. We investigate three central aspects of this
chronology. How skillful is the Dating Committee when classifying
economic activity into expansions and recessions? Which indices of
economic conditions best capture the current but unobservable state
of the business cycle? And which indicators best predict future turning
points, and at what horizons? We answer each of these questions
in detail using methods specifically designed to assess classification
ability. In the process, we clarify several important features of the
Path Forecast Evaluation
Journal of Applied Econometrics 25(4), May 2010, 635-662 | With Marcellino
A path forecast refers to the sequence of forecasts 1 to H periods into the future. A summary of the range of possible paths the predicted variable may follow for a given confidence level requires construction of simultaneous confidence regions that adjust for any covariance between the elementsof the path forecast. This paper shows how to construct such regions with the joint predictive density and Scheffe’s (1953) S-method. In addition, the joint predictive density can be used to construct simple statistics to evaluate the local internal consistency of a forecasting exercise of a system of variables. Monte Carlo simulations demonstrate that these simultaneous confidence regions provide
approximately correct coverage in situations where traditional error bands, based on the collection of marginal predictive densities for each horizon, are vastly off mark. The paper showcases these methods with an application to the most recent monetary episode of interest rate hikes in the U.S. macroeconomy.
Simultaneous Confidence Regions for Impulse Responses
Review of Economics and Statistics 91(3), August 2009, 629-647
Inference about an impulse response is a multiple testing problem with serially correlated coefficient estimates. This paper provides a method to construct simultaneous confidence regions for impulse responses and conditional bands to examine significance levels of individual impulse response coefficients given propagation trajectories. The paper also shows how to constrain a subset of impulse response paths to anchor
structural identification and how to formally test the validity of such identifying constraints. Simulation and empirical evidence illustrate the new techniques. A broad summary of asymptotic analytic formulas is provided to make the methods easy to implement with commonly available
Estimation and Inference of Impulse Responses by Local Projections
American Economic Review 95(1), March 2005, 161-182
This paper introduces methods to compute impulse responses without specification and estimation of the underlying multivariate dynamic system. The central idea consists in estimating local projections at each period of interest rather than extrapolating into increasingly distant horizons from a given model, as it is done with vector autoregressions (VAR). The advantages of local projections are numerous: (1) they can be estimated by simple regression techniques with standard regression packages; (2) they are more robust to misspecification; (3) joint or point-wise analytic inference is simple; and (4) they easily accommodate experimentation with highly nonlinear and flexible specifications that may be impractical in a multivariate context. Therefore, these methods are a natural alternative to estimating impulse responses from VARs. Monte Carlo evidence and an application to a simple, closed-economy, new-Keynesian model clarify these numerous advantages.
Time Scale Transformations of Discrete Time Processes
Journal of Time Series Analysis 25(6), November 2004, 873-894 | With Marcellino
This paper investigates the effects of temporal aggregation when the aggregation frequency is variable and possibly stochastic. The results that we report include, as a particular case, the well-known results on fixed-interval aggregation, such as when monthly data are aggregated into quarters. A variable aggregation frequency implies that the aggregated process will exhibit time-varying parameters and non-spherical disturbances, even when these characteristics are absent from the original model. Consequently, we develop methods for specification and estimation of the aggregate models and show with an example how these methods perform in practice.
Measuring Monetary Policy Interdependence
Journal of International Money and Finance 23(5), September 2004, 761-783 | With Bergin
This paper measures the degree of monetary policy interdependence between major industrialized countries from a new perspective. The analysis uses a special data set on central bank issued policy rate targets for 14 OECD countries. Methodologically, our approach is novel in that we separately examine monetary interdependence due to (1) the coincidence in time of when policy actions are executed from (2) the nature and magnitude of the policy adjustments made. The first of these elements requires that the timing of events be modeled with a dynamic discrete duration design. The discrete nature of the policy rate adjustment process that characterizes the second element is captured with an ordered response model. The results indicate there is significant policy interdependence among these 14 countries during the 1980-1998 sample period. This is especially true for a number of European countries which appeared to respond to German policy during our sample period. A number of other countries appeared to respond to U.S. policy, though this number is smaller than that suggested in preceding studies. Moreover, the policy harmonization we find appears to work through channels other than formal coordination agreements.
The Response of Term Rates to Fed Announcements
Journal of Money, Credit, and Banking 36(3), June 2004, 387-406 | With Demiralp
In February 4, 1994 the Federal Reserve began the practice of announcing changes in the targeted level for the federal funds rate immediately after such decisions were made. This paper investigates to what extent the policy of “the announcement” affected a key ingredient in the monetary transmission mechanism: the term structure of nominally risk-free, Treasury securities. We find that term rates react much more in unison during announcement days than at any other time. Moreover, the practice of circumscribing almost all changes in the federal funds rate target to Federal Open Market Committee (FOMC) meeting dates regiments the formation of market expectations in the overnight rate and the price discovery process of term rates, thus facilitating the Fed’s goal of controlling long-term rates.
The Response of Term Rates to Monetary Policy Uncertainty
Review of Economic Dynamics 6(4), October 2003, 941-962 | With Salyer
This paper shows that greater uncertainty about monetary policy can lead to a decline in nominal interest rates. In the context of a limited participation model, monetary policy uncertainty is modeled as a mean preserving spread in the distribution for the money growth process. This increase in uncertainty lowers the yield on short-term maturity bonds because the household sector responds by increasing liquidity in the banking sector. Long-term maturity bonds also have lower yields but this decrease is a result of the effect that greater uncertainty has on the nominal intertemporal rate of substitution–which is a convex function of money growth. We examine the nature of these relations empirically by introducing the GARCH-SVAR model–a multivariate generalization of the GARCH-M model. The predictions of the model are broadly supported by the data: higher uncertainty in the federal funds rate can lower the yields of the three- and six-month treasury bill rates.
Modeling High-Frequency FX Data Dynamics
Macroeconomic Dynamics 7(4), August 2003, 618-635 | With Marcellino
This paper shows that high-frequency, irregularly spaced, foreign exchange (FX) data can generate nonnormality, conditional heteroskedasticity, and leptokurtosis when aggregated into fixed-interval calendar time, even when these features are absent in the original DGP. Furthermore, we introduce a new approach to modeling these high-frequency irregularly spaced data based on the Poisson regression model. The new model is called the autoregressive conditional intensity model and it has the advantage of being simple and of maintaining the calendar timescale. To illustrate the virtues of this approach, we examine a classical issue in FX microstructure: the variation in information content as a function of fluctuations in the intensity of activity levels.
A Model for the Federal Funds Rate Target
Journal of Political Economy 110(5), July 2002, 1135-1167 | With Hamilton
This paper is a statistical analysis of the manner in which the Federal Reserve determines the level of the federal funds rate target, one of the most publicized and anticipated economic indicators in the financial world. The paper introduces new statistical tools for forecasting a discrete-valued time series such as the target, and suggests that these methods, in conjunction with a focus on the institutional details of how the target is determined, can significantly improve on standard VAR forecasts of the effective federal funds rate. We further show that the news that the Fed has changed the target has substantially different statistical content from the news that the Fed failed to make an anticipated target change, causing us to challenge some of the conclusions drawn from standard linear VAR impulse-response functions.
Testing Nonlinearity: Decision Rules for Choosing between Logistic and Exponential STAR Models
Spanish Economic Review 3, 2001, 193-209 | With Escribano
A new LM specification procedure to choose between Logistic and Exponential Smooth Transition Autoregressive (STAR) models is introduced. The new decision rule has better properties than those previously available in the literature when the model is ESTAR and similar properties when the model is LSTAR. A simple natural extension of the usual LM-test for linearity is introduced and evaluated in terms of power. Monte-Carlo simulations and empirical evidence are provided in support of our claims.
Random Time Aggregation in Partial Adjustment Models
Journal of Business and Economic Statistics 7(3), July 1999, 382-396
How is econometric analysis (of partial adjustment models) affected by the fact that, while data collection is done at regular, fixed intervals of time, economic decisions are made at random intervals of time? This paper addresses this question by modelling the economic decision making process as a general point process. Under randomtime aggregation: (1) inference on the speed of adjustment is biased–adjustments are a function of the intensity of the point procEss and the proportion of adjustment; (2) inference on the correlation with exogenous variables is generally downward biased; and (3) a non-constant intensity of the point process gives rise to a general class of regime dependent time series models. An empirical application to test the production smoothing-buffer stock model of inventory behavior illustrates, in practice, the effects
of random-time aggregation.