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Jel Classification:C22 

Working Paper
Assessing Macroeconomic Tail Risks in a Data-Rich Environment

We use a large set of economic and financial indicators to assess tail risks of the three macroeconomic variables: real GDP, unemployment, and inflation. When applied to U.S. data, we find evidence that a dense model using principal components (PC) as predictors might be misspecified by imposing the “common slope” assumption on the set of predictors across multiple quantiles. The common slope assumption ignores the heterogeneous informativeness of individual predictors on different quantiles. However, the parsimony of the PC-based approach improves the accuracy of out-of-sample forecasts ...
Research Working Paper , Paper RWP 19-12

Working Paper
Regular Variation of Popular GARCH Processes Allowing for Distributional Asymmetry

Linear GARCH(1,1) and threshold GARCH(1,1) processes are established as regularly varying, meaning their heavy tails are Pareto like, under conditions that allow the innovations from the, respective, processes to be skewed. Skewness is considered a stylized fact for many financial returns assumed to follow GARCH-type processes. The result in this note aids in establishing the asymptotic properties of certain GARCH estimators proposed in the literature.
Finance and Economics Discussion Series , Paper 2017-095

Working Paper
How Well Does Economic Uncertainty Forecast Economic Activity?

Despite the enormous reach and influence of the literature on economic and economic policy uncertainty, one surprisingly under-researched topic has been the forecasting performance of economic uncertainty measures. We evaluate the ability of seven popular measures of uncertainty to forecast in-sample and out-of-sample over real and financial outcome variables. We also evaluate predictive content over different quantiles of the GDP growth distribution. Real-time data and estimation considerations are highly consequential, and we devote considerable attention to them. Four main findings ...
Finance and Economics Discussion Series , Paper 2019-085

Working Paper
Weather-adjusting employment data

First version: December 18, 2014. This version: January 12, 2015. This paper proposes and implements a statistical methodology for adjusting employment data for the effects of deviation in weather from seasonal norms. This is distinct from seasonal adjustment, which only controls for the normal variation in weather across the year. Unusual weather can distort both the data and the seasonal factors. We control for both of these effects by integrating a weather adjustment step in the seasonal adjustment process. We use several indicators of weather, including temperature, snowfall and ...
Working Papers , Paper 15-5

Working Paper
Episodes of Exuberance in Housing Markets: In Search of the Smoking Gun

In this paper, we examine changes in the time series properties of standard housing market indicators (real house prices, price-to-income ratios, and price-to-rent ratios) for a large set of countries to detect episodes of explosive dynamics. Dating exuberance in housing markets provides a timeline as well as empirical content to the narrative connecting housing exuberance to the global 2008?09 recession. For our investigation, we employ two recursive univariate unit root tests developed by Phillips et al. (2011) and Phillips et al. (2015). We also propose a novel extension of the Phillips et ...
Globalization Institute Working Papers , Paper 165

Report
Revisiting useful approaches to data-rich macroeconomic forecasting

This paper analyzes the properties of a number of data-rich methods that are widely used in macroeconomic forecasting, in particular principal components (PC) and Bayesian regressions, as well as a lesser-known alternative, partial least squares (PLS) regression. In the latter method, linear, orthogonal combinations of a large number of predictor variables are constructed such that the covariance between a target variable and these common components is maximized. Existing studies have focused on modelling the target variable as a function of a finite set of unobserved common factors that ...
Staff Reports , Paper 327

Report
Flighty liquidity

We study how the risks to future liquidity flow across corporate bond, Treasury, and stock markets. We document distribution ?flight-to-safety? effects: a deterioration in the liquidity of high-yield corporate bonds forecasts an increase in the average liquidity of Treasury securities and a decrease in uncertainty about the liquidity of investment-grade corporate bonds. While the liquidity of Treasury securities both affects and is affected by the liquidity in the other two markets, corporate bond and equity market liquidity appear to be largely divorced from each other. Finally, we show that ...
Staff Reports , Paper 870

Working Paper
exuber: Recursive Right-Tailed Unit Root Testing with R

This paper introduces the R package exuber for testing and date-stamping periods of mildly explosive dynamics (exuberance) in time series. The package computes test statistics for the supremum ADF test (SADF) of Phillips, Wu and Yu (2011), the generalized SADF (GSADF) of Phillips, Shi and Yu (2015a,b), and the panel GSADF proposed by Pavlidis, Yusupova, Paya, Peel, Martínez-García, Mack and Grossman (2016); generates finite-sample critical values based on Monte Carlo and bootstrap methods; and implements the corresponding date-stamping procedures. The recursive least-squares algorithm that ...
Globalization Institute Working Papers , Paper 383

Report
Changing risk-return profiles

We show that realized volatility, especially the realized volatility of financial sector stock returns, has strong predictive content for the future distribution of market returns. This is a robust feature of the last century of U.S. data and, most importantly, can be exploited in real time. Current realized volatility has the most information content on the uncertainty of future returns, whereas it has only limited content about the location of the future return distribution. When volatility is low, the predicted distribution of returns is less dispersed and probabilistic forecasts are ...
Staff Reports , Paper 850

Working Paper
Monitoring the world business cycle

We propose a Markov-switching dynamic factor model to construct an index of global business cycle conditions, to perform short-term forecasts of world GDP quarterly growth in real time and to compute real-time business cycle probabilities. To overcome the real-time forecasting challenges, the model accounts for mixed frequencies, for asynchronous data publication and for leading indicators. Our pseudo real-time results show that this approach provides reliable and timely inferences of the world quarterly growth and of the world state of the business cycle on a monthly basis.
Globalization Institute Working Papers , Paper 228

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