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Unpublished manuscript :: With Fushing, Chen, and Berge :: October 2010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Unpublished manuscript :: With Knuppel and Marcellino :: March 2010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).
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.
Empirical Simultaneous Prediction Regions for Path-Forecasts
2012-05 :: May 2012
This paper investigates the problem of constructing prediction regions for forecast trajectories 1 to H periods into the future a path forecast. We take the more general view that the null model is only approximative and in some cases it may be altogether unavailable. As a consequence, one cannot derive the usual analytic expressions nor resample from the null model as is usually done when bootstrap methods are used. The paper derives methods to construct approximate rectangular regions for simultaneous probability coverage which correct for serial correlation. The techniques appear to work well in simulations and in an application to the Greenbook path-forecasts of growth and inflation.
A Chronology of Turning Points in Economic Activity: Spain, 1850-2011
2011-28 :: With Berge :: November 2011
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: Leverage, Business Cycles, and Crises
2011-27 :: With Schularick and Taylor :: October 2012
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 Carry Trade and Fundamentals: Nothing to Fear but FEER Itself
Forthcoming in Journal of International Economics :: 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.
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.
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.
Discussion of 'Anchoring Countercyclical Capital Buffers: The Role of Credit Aggregates' by Drehmann, Borio, and Tsatsaronis
Forthcoming in International Journal of Central Banking
Forthcoming in Encyclopedia of Financial Globalization. Elsevier
Currency Carry Trades
Forthcoming in International Seminar of Macroeconomics 2010. NBER :: With Taylor
Book Review: 'New Introduction to Multiple Time Series Analysis' by Helmut Lutkepohl
Econometric Reviews 29(2), 2010, 243-246
Open Market Operations
In International Encyclopedia of the Social Sciences, 2nd edition :: MacMillan Reference/Thomson-Gale, 2007
North Coast River Loading Study: Road Crossing on Small Streams
In Report prepared for the Division of Environmental Analysis :: California Department of Transportation, 2002 :: With et al.
The Announcement Effect: Evidence from Open Market Desk Data
Economic Policy Review, FRB New York 8(1), May 2002, 29-48 :: With Demiralp
Measuring Systematic Monetary Policy
FRB St. Louis Review 83(4), July 2001, 113-137 :: With Hoover
Boletín Inflación y Analisis Económico: Predicción y Diagnóstico 68, June 2000
Improved Testing and Specification of Smooth Transition Regression Models
In Dynamic Modeling and Econometrics in Economics and Finance, Vol 1, Nonlinear Time Series Analysis of Economic and Financial Data, ed. by Rothman :: Kluwer Academic Press, 1998. 289-319 :: With Escribano
La Política Monetaria en los Estados Unidos: El Objetivo de los Tipos de Fondos Federales
Situación, March 1998, 89-92