Downloadable Papers

· “When Credit Bites Back: Leverage, Business Cycles, and Crises” (with Mortiz Schularick and Alan Taylor)

Abstract

This paper studies the role of leverage in the business cycle. Based on a study of nearly 200 recession episodes in 14 advanced countries between 1870 and 2008, we document a new stylized fact of the modern business cycle: more credit-intensive booms tend to be followed by deeper recessions and slower recoveries. We find a close relationship between the rate of credit growth relative to GDP in the expansion phase and the severity of the subsequent recession. We use local projection methods to study how leverage impacts the behavior of key macroeconomic variables such as investment, lending, interest rates, and inflation. The effects of leverage are particularly pronounced in recessions that coincide with financial crises, but are also distinctly present in normal cycles. The stylized facts we uncover lend support to the idea that financial factors play an important role in the modern business cycle.

· “A Chronology of Turning Points in Economic Activity: Spain 1850-2011” (with Travis Berge)

Abstract

This paper 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.

· “Performance Evaluation of Zero Net-Investment Strategies” (with Alan M. Taylor)

Abstract

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.

· Discussion of “Anchoring Countercyclical Capital Buffers: The Role of Credit Aggregates” forthcoming in the International Journal of Central Banking.

· “Carry Trade” Encyclopedia of Financial Globalization, forthcoming.

· “Financial Crises, Credit Booms, and External Imbalances: 140 Years of Lessons” (with Moritz Schularick and Alan Taylor) IMF Economic Review, 59(2): 340-378. June 2011.

Abstract

Do external imbalances increase the risk of financial crises? In this paper, we study the experience of 14 developed countries over 140 years (1870-2008). We exploit our long-run dataset in a number of different ways. First, we apply new statistical tools to describe the temporal and spatial patterns of crises and identify five episodes of global financial instability in the past 140 years. Second, we study the macroeconomic dynamics before crises and show that credit growth tends to be elevated and natural interest rates depressed in the run-up to global financial crises. Third, we show that recessions associated with crises lead to deeper recessions and stronger turnarounds in imbalances than during normal recessions. Finally, we ask if external imbalances help predict financial crises. Our overall result is that credit growth emerges as the single best predictor of financial instability, but the correlation between lending booms and current account imbalances has gwowh much tighter in recent decades.

· “A Chronology of International Business Cycles Through Non-parametric Decoding” (with Travis Berge, Shu-Chun Chen and Fushing Hsieh)

Abstract

This paper introduces a new empirical strategy for the characterization of business cycles. It combines non-parametric 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.

· “Future Recession Risks,” (with Travis Berge), Federal Reserve Bank of San Francisco, Economic Letter, 2010-24.

Abstract

An unstable economic environment has rekindled talk of a double-dip recession. The Conference Board's Leading Economic Index provides data for predicting the probability of a recession but is limited by the weight assigned to its indicators and the varying efficacy of those indicators over different time horizons. Statistical experiments with LEI data can mitigate these limitations and suggest that a recessionary relapse is a significant possibility sometime in the next two years.

· “Currency Carry Trades,” (with Travis Berge and Alan Taylor), International Seminar on Macroeconomics 2010, NBER.

Abstract

A wave of recent research has studied the predictability of foreign currency returns. A wide variety of forecasting structures have been proposed, including signals such as carry, value, momentum, and the forward curve. Some of these have been explored individually, and others have been used in combination. In this paper we use new econometric tools for binary classification problems to evaluate the merits of a general model encompassing all these signals. We find very strong evidence of forecastability using the full set of signals, both in sample and out-of-sample. The holds true for both an unweighted directional forecast and one weighted by returns. Our preferred model generates economically meaningful returns on a portfolio of nine major currencies versus the U.S. dollar, with favorably Sharpe and skewness characteristics. We also find no relationship between our returns and a conventional set of so-called risk factors.

· “The Harrod-Balassa-Samuelson Hypothesis: Real Exchange Rates and their Long-Run Equilibrium,” (with Yanping Chong and Alan Taylor) International Economic Review, forthcoming.

Abstract

Frictionless, perfectly competitive traded-goods markets justify thinking of purchasing power parity (PPP) as the main driver of exchange rates in the long-run. But differences in the traded/non-traded sectors of economies tend to be persistent and affect movements in local price levels in ways that upset the PPP balance (the underpinning of the Harrod-Balassa-Samuelson hypothesis, HBS). This paper uses panel-data techniques on a broad collection of countries to investigate the long-run properties of the PPP/HBS equilibrium using novel local projection methods for cointegrated systems. These semi-parametric methods isolate the long-run behavior of the data from contaminating factors such as frictions not explicitly modelled and thought to have effects only in the short-run. Absent the short-run effects, we find that the estimated speed of reversion to long-run equilibrium is much higher. In addition, the HBS effects means that the real exchange rate is converging not to a steady mean, but to a slowly to a moving target. The common failure to properly model this effect also biases the estimated speed of reversion downwards. Thus, the so-called ``PPP puzzle'' is not as bad as we thought.

· “Empirical Simultaneous Confidence Regions for Path-Forecasts” (with Malte Knüppel and Massimiliano Marcellino)

Abstract

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 decision making 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.

· “Diagnosing Recessions” Federal Reserve Bank of San Francisco Economic Letter 2010-05

Abstract

The beginnings and ends of recessions are officially dated about 12 months after the fact. A common rule of thumb declares recessions as two quarters of consecutive negative GDP growth, but this is very inaccurate. A better option is to apply medical diagnostic evaluation methods to the business conditions indexes of the Chicago and Philadelphia Federal Reserve Banks, which suggests the recent recession ended in July or August 2009.

· “The Classification of Economic Activity into Expansions and Recessions” (with Travis Berge) American Economic Journal: Macroeconomics, 2011, 3(2): 246–77.

Abstract

The Business Cycle Dating Committee (BCDC) of the National Bureau of Economic Research provides a historical chronology of business cycle turning points. This paper investigates three central aspects about this chronology: (1) How skillful is the BCDC in classifying economic activity into expansions and recessions? (2) Which indices of business conditions best capture the current but unobservable state of the business cycle? And (3) Which indicators predict future turning points best and at what horizons? We answer each of these questions in detail with methods novel to economics designed to assess classification ability. In the process we clarify several important features of business cycle phenomena.

Classification since December 2007 (last release from BCDC) until October 2009

	ADS	CFNAI	PMI
Threshold	-0.80	-0.72	44.5

December-07	-0.20	-0.44	49.1
January-08	-0.56	-0.40	50.8
February-08	-1.06	-0.82	48.8
March-08	-1.03	-0.99	49.0
April-08	-0.90	-1.12	48.6
May-08	-0.93	-1.12	49.3
June-08	-0.92	-1.07	49.5
July-08	-1.05	-1.16	49.5
August-08	-1.92	-1.41	49.3
September-08	-3.36	-2.24	43.4
October-08	-1.78	-2.31	38.7
November-08	-1.94	-2.63	36.6
December-08	-2.95	-2.74	32.9
January-09	-3.54	-3.63	35.6
February-09	-2.91	-3.46	35.8
March-09	-2.52	-3.32	36.3
April-09	-1.90	-2.66	40.1
May-09	-1.64	-2.64	42.8
June-09	-1.26	-2.13	44.8
July-09	-0.21	-1.53	48.9
August-09	0.33	-0.94	52.9
September-09	0.06	-0.67	52.6
October-09	-0.33	-0.91	55.7

This table summarizes what Business Conditions Indices say about the current state of the business cycle since the NBER declared the beginning of the current recession as December 2007. Yellow shading indicates a recession-month. According to the Aruoba, Diebold and Scotti business conditions index maintained by the Federal Reserve Bank of Philadelphia we came out of the recession July 2009. According to the Chicago Fed National Activity Index we came out September 2009, and according to the Purchasing Managers Index it would be June 2009.

These dates match up reasonably well with recent reports in the press. For example, The Economist on October 29, 2009 reports that "Robert Gordon, a member of this group [the Business Cycle Dating Committee], is confident that the recession, which began in December 2007, ended in June." Robert Hall, who chairs the Business Cycle Dating Committee, declared for Bloomberg December 4, 2009 that "The trough in output was probably some time in the summer." Meanwhile, Alan Greenspan declared in Meet the Press on December 13, 2009 that the recession probably ended in July 2009 and possibly as early as June 2009. Marcelle Chauvet at U.C. Riverside and Jeremy Piger at U. of Oregon and James Hamilton at UCSD in his blog at www.econbrowser.com also seem to coincide in choosing July 2009 as the end of the current recession.

Below are time series plots for each of the indices I just described along with a horizontal line, which is the threshold calculated by us that would most naturally separate recessions and expansions to coincide with the NBER dating. The vertical line indicates the beginning of the current recession. Shaded areas represent NBER recessions.

· “The Carry Trade and Fundamentals: Nothing to Fear but FEER Itself” (with Alan Taylor) NBER working paper 15518

Abstract

The carry trade is the investment strategy of going long in high-yield target currencies and short in low-yield funding currencies. Recently, this naïve 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.

· “Fluctuations in the Exchange Rate and the Carry Trade” (with Kyuil Chung) Bank of Korea working paper 405

Abstract

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 a 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 harmuful 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 Jordà and Taylor (2009).

· “Estimation and Inference by the Method of Projection Minimum Distance: An Application to the New Keynesian Phillips Curve,” (with Sharon Kozicki) International Economic Review, 2011, 52(2): 461-487.

Abstract

In most macroeconomic models, the stability of the solution path implies that the system is covariance-stationary and hence admits a Wold representation. The ability to estimate this Wold representation semi-parametrically by local projections (Jordà, 2005), even when the process for the solution path is unknown or unconventional, can be exploited to estimate the model's parameters by minimum distance techniques. We label this two-step estimation procedure "projection minimum distance" (PMD) and formally investigate its statistical properties in models where the mapping between Wold coefficients and parameters is linear even though the likelihood score function is nonlinear in the parameters, which traditionally requires numerical routines to maximize the likelihood. As an illustration of the practicalities of PMD estimation, we reexamine estimates of the New Keynesian Hybrid Phillips curve by providing ample Monte Carlo evidence and an empirical reassessment of Fuhrer and Olivei (2005).

Gauss Code:

· All replication files for the paper contained in the following zip file [PMD_2008.zip]

· “Path Forecast Evaluation” (with Massimiliano Marcellino) Journal of Applied Econometrics, 2010, 25(4): 635-662.

Abstract

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 elements of the path forecast. This paper shows how to construct such regions with the joint predictive density and Scheffé'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.

GAUSS Code:

o VAR/Direct Forecast Marginal, Bonferroni and Scheffe Bands based on Stock and Watson’s (2001) VAR. These files should be easy to adapt for different applications. [JAE_SW.zip]

o Stock and Watson (2001) VAR Monte Carlos (Tables 1 and 2 in the paper). [JAE_MC_SW.zip]

o AR(1) Monte Carlo files (Table 3). [JAE_MC_AR.zip]

o Files that generate figures 4 and 5 (direct forecast empirical application and counterfactual simulation). [JAE_FIGS.zip]

“Simultaneous Confidence Regions for Impulse Responses” Review of Economics and Statistics, 2009, 91(3): 629-647.

Abstract

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 to evaluate uncertainty about the shape of the impulse response; and conditional bands to examine individual significance levels of impulse response coefficients given propagation trajectories. The paper also shows how to constrain a subset of impulse response paths to anchor structural identification of the system; and how to formally test for the validity of such identifying constraints. Simulation and empirical evidence illustrate the new techniques. A broad summary of asymptotic results and simple formulas for a impulse response estimators based on VARs and local projections are provided to make the methods easily implementable with commonly available statistical software.

Gauss Code

The code contained in the folder replicates the figures in the paper. However, I have modified the code slightly from what is prescribed in the paper to incorporate a refinement due to Holm (1979) that I used in my “Path Forecast Evaluation” paper with Massimiliano Marcellino. The figures will look slightly different than in the paper but the benefit is that if you adapt the code to your own application; you will have a more up-to-date procedure. [irs_se.zip]

"Estimation and Inference of Impulse Responses by Local Projections" American Economic Review, 2005, 95(1), 161-182.

Formerly "Model-Free Impulse Responses"

Basic GAUSS code for impulse response calculation

Check my paper “Simultaneous Confidence Regions for Impulse Responses” for more up to date code and better error bands

E-mail me if you would like the Monte-Carlo code

The GAUSS code to estimate time-varying parameter/volatility Bayesian VAR is available directly from Massimiliano de Santis at: mdesantis@ucdavis.edu

Abstract

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 non-linear 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," with Massimiliano Marcellino. Journal of Time Series Analysis, 2004, 25(6), 873-894.

Abstract

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 is 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.

"Non-Institutional Market Making Behavior: The Dalian Futures Exchange," with Holly Liu and Jeffrey Williams

Abstract

This paper contains three useful contributions: (1) it collects a new data-set of electronic transaction data on soybean futures from the Dalian Futures Exchange in China that records, not only the usual elements of each transaction (such as price and size) but also identifies broker and customer identities, variables not usually obtainable; (2) it presents new econometric methods for the analysis of dynamic multivariate count data based on the autoregressive conditional intensity model of Jordà and Marcellino (2000); and (3) together, the new data and econometric methods allow us to investigate, in a manner not available before, the determinants and effects of non-institutional market making (or scalping).

"The Response of Term Rates to Monetary Policy Uncertainty," with Kevin D. Salyer. Review of Economic Dynamics, October 2003; 6(4): 941-62.

Abstract

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.

“The Announcement Effect: Evidence from Open Market Desk Data,” with Selva Demiralp. Prepared for the Conference: Financial Innovation and Monetary Transmission, Federal Reserve Bank of New York, April 5-6, 2001. Available in Policy Review, FRBNY, May 2002; 8(1): 29-48.

Abstract

This paper investigates the ability of the Federal Reserve to manipulate the overnight rate without open market operations (which Demiralp and Jorda (2000) term the announcement effect), using high-frequency, open-market-desk data. Using similar data, Hamilton (1997) takes advantage of forecast errors in the Treasury balance to compute the elasticity of the federal funds rate to these errors and thus to obtain a measure of the liquidity effect. Similarly, one can view daily deviations of the federal funds rate from target as forecast errors in the reserve need (see Taylor, 2000). By analyzing the manner and the type of operation the Fed uses to maintain the federal funds rate close to its targeted value and by observing the pattern of operations on the days surrounding a change in this target, we provide evidence of the announcement effect. An integral part of the analysis requires that we provide forecasts of market expectations on future target changes. We do this in two ways, using federal funds futures data as in Kuttner (2000) and with the autoregressive conditional hazard model proposed by Hamilton and Jordá (2000).

“Monetary Policy Coordination: A New Empirical Approach,” with Paul R. Bergin. Journal of International Money and Finance, 2004, 23(5), 761-783.

e-mail me if you would like a copy of an alternative set of GAUSS code to estimate ACH models with the specification in this paper.

Abstract

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.

"Measuring Systematic Monetary Policy" with Kevin Hoover. Prepared for the Conference: "Monetary Policy in Theory and Practice: Essays in Honor of Darryl R. Francis" – 2000, 25th Annual Economic Policy Conference. Federal Reserve Bank of St. Louis, October 20-21, 2000.

Abstract

The 1970s and early 1980s witnessed two main approaches to the analysis of monetary policy. The first is the early new classical approach of Lucas, based on the assumptions of rational expectations and market clearing. The second is the atheoretical econometrics of Sims's VAR program. Both have developed: the new classical approach has been enriched through various accounts of price stickiness, cost of adjustment or alternative expectational schemes; the original VAR program has developed into the structural VAR program. This paper clarifies the relationship between these two programs. Based on work of Cochrane (1998), it shows that the typical method of evaluating unanticipated, unsystematic monetary policy is correct only if the conditions necessary for Lucas's policy-ineffectiveness proposition hold, while recent methods for evaluating systematic monetary policy violate Lucas's policy-noninvariance proposition ("the Lucas critique"). The paper shows how to construct and estimate (using regime changes) a model in which some agents form rational-expectations and others follow rules of thumb. In such a model, monetary policy actions can be validly decomposed into systematic and unsystematic components and valid counterfactual experiments on alternative systematic monetary-policy rules can be evaluated.

"The Pavlovian Response of Term Rates to Fed Announcements" with Selva Demiralp
July, 2001 Revision "The Pavlovian Response to Fed Announcements" (although there is overlap between the two versions, there are differences that warrant having both linked simultaneously). Journal of Money, Credit, and Banking, 36(3, Part I), 387-405.

Abstract

The traditional view of the monetary transmission mechanism rests on the premise that the Federal Reserve (Fed) controls the level of the Federal funds rate via open market operations and the liquidity effect. By contrast, this paper argues that the Fed also manipulates the Federal funds rate via public disclosures of the new level of the Federal funds rate target and the "announcement effect.'' We define the announcement effect as the portion of interest rate movements associated with public statements on interest rate targets that do not require conventional open market operations for their support. This paper provides evidence on how the Fed uses the liquidity effect in conjunction with the announcement effect to execute monetary policy. In addition, it investigates the implications of the announcement effect on term structure behavior and the rational expectations hypothesis.