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Working Paper
Variable Selection and Forecasting in High Dimensional Linear Regressions with Structural Breaks
Chudik, Alexander; Sharifvaghefi, Mahrad; Pesaran, M. Hashem (2021-04-17)
This paper is concerned with the problem of variable selection and forecasting in the presence of parameter instability. There are a number of approaches proposed for forecasting in the presence of breaks, including the use of rolling windows and exponential down-weighting. However, these studies start with a given model specification and do not consider the problem of variable selection, which is complicated by time variations in the effects of signal variables. In this study we investigate whether or not we should use weighted observations at the variable selection stage in the presence of ...
Globalization Institute Working Papers , Paper 394

Working Paper
Binary Conditional Forecasts
Owyang, Michael T.; McGillicuddy, Joseph; McCracken, Michael W. (2019-10-01)
While conditional forecasting has become prevalent both in the academic literature and in practice (e.g., bank stress testing, scenario forecasting), its applications typically focus on continuous variables. In this paper, we merge elements from the literature on the construction and implementation of conditional forecasts with the literature on forecasting binary variables. We use the Qual-VAR [Dueker (2005)], whose joint VAR-probit structure allows us to form conditional forecasts of the latent variable which can then be used to form probabilistic forecasts of the binary variable. We apply ...
Working Papers , Paper 2019-29

Journal Article
A Macroeconomic News Index for Constructing Nowcasts of U.S. Real Gross Domestic Product Growth
Grover, Sean P.; McCracken, Michael W.; Kliesen, Kevin L. (2016)
Analyzing the performance of the economy in real time is a challenge for those who must forecast macroeconomic variables such as inflation or employment. A key aspect of this challenge is evaluating the incoming flow of information contained in economic announcements. In this article, the authors develop a simple-to-read index of these announcements that they then use to construct nowcasts. The index tracks whether key economic data have come in stronger, weaker, or as expected during the current quarter relative to a baseline consensus forecast. Specifically, the data releases are weighted ...
Review , Volume 98 , Issue 4 , Pages 277-296

Working Paper
Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections
Diebold, Francis X.; Rudebusch, Glenn D. (2020-01-11)
The downward trend in the amount of Arctic sea ice has a wide range of environmental and economic consequences including important effects on the pace and intensity of global climate change. Based on several decades of satellite data, we provide statistical forecasts of Arctic sea ice extent during the rest of this century. The best fitting statistical model indicates that overall sea ice coverage is declining at an increasing rate. By contrast, average projections from the CMIP5 global climate models foresee a gradual slowing of Arctic sea ice loss even in scenarios with high carbon ...
Working Paper Series , Paper 2020-02

Working Paper
Weather-adjusting employment data
Wright, Jonathan H.; Boldin, Michael D. (2015-01-12)
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
Estimation of Impulse Response Functions When Shocks are Observed at a Higher Frequency than Outcome Variables
Georgiadis, Georgios; Chudik, Alexander (2019-03-15)
This paper proposes mixed-frequency distributed-lag (MFDL) estimators of impulse response functions (IRFs) in a setup where (i) the shock of interest is observed, (ii) the impact variable of interest is observed at a lower frequency (as a temporally aggregated or sequentially sampled variable), (iii) the data-generating process (DGP) is given by a VAR model at the frequency of the shock, and (iv) the full set of relevant endogenous variables entering the DGP is unknown or unobserved. Consistency and asymptotic normality of the proposed MFDL estimators is established, and their small-sample ...
Globalization Institute Working Papers , Paper 356

Working Paper
Variable Selection and Forecasting in High Dimensional Linear Regressions with Structural Breaks
Chudik, Alexander; Sharifvaghefi, Mahrad; Pesaran, M. Hashem (2020-08-19)
This paper is concerned with the problem of variable selection and forecasting in the presence of parameter instability. There are a number of approaches proposed for forecasting in the presence of breaks, including the use of rolling windows or exponential down-weighting. However, these studies start with a given model specification and do not consider the problem of variable selection. It is clear that, in the absence of breaks, researchers should weigh the observations equally at both the variable selection and forecasting stages. In this study, we investigate whether or not we should use ...
Globalization Institute Working Papers , Paper 394

Working Paper
Binary Conditional Forecasts
Owyang, Michael T.; McGillicuddy, Joseph; McCracken, Michael W. (2021-04)
While conditional forecasting has become prevalent both in the academic literature and in practice (e.g., bank stress testing, scenario forecasting), its applications typically focus on continuous variables. In this paper, we merge elements from the literature on the construction and implementation of conditional forecasts with the literature on forecasting binary variables. We use the Qual-VAR [Dueker (2005)], whose joint VAR-probit structure allows us to form conditional forecasts of the latent variable which can then be used to form probabilistic forecasts of the binary variable. We apply ...
Working Papers , Paper 2019-029

Working Paper
The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility
Murphy, Anthony; Hizmeri, Rodrigo; Tsionas, Mike G.; Izzeldin, Marwan (2019-03-28)
We document the forecasting gains achieved by incorporating measures of signed, finite and infinite jumps in forecasting the volatility of equity prices, using high-frequency data from 2000 to 2016. We consider the SPY and 20 stocks that vary by sector, volume and degree of jump activity. We use extended HAR-RV models, and consider different frequencies (5, 60 and 300 seconds), forecast horizons (1, 5, 22 and 66 days) and the use of standard and robust-to-noise volatility and threshold bipower variation measures. Incorporating signed finite and infinite jumps generates significantly better ...
Working Papers , Paper 1902

Working Paper
Estimation of the discontinuous leverage effect: Evidence from the NASDAQ order book
Winkelmann, Lars; Neely, Christopher J.; Bibinger, Markus (2017-04-26)
An extensive empirical literature documents a generally negative correlation, named the ?leverage effect,? between asset returns and changes of volatility. It is more challenging to establish such a return-volatility relationship for jumps in high-frequency data. We propose new nonparametric methods to assess and test for a discontinuous leverage effect ? i.e. a relation between contemporaneous jumps in prices and volatility ? in high-frequency data with market microstructure noise. We present local tests and estimators for price jumps and volatility jumps. Five years of transaction data from ...
Working Papers , Paper 2017-12

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