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Working Paper
Shrinkage estimation of high-dimensional factor models with structural instabilities
Schorfheide, Frank; Cheng, Xu; Liao, Zhipeng (2013-12-01)
In high-dimensional factor models, both the factor loadings and the number of factors may change over time. This paper proposes a shrinkage estimator that detects and disentangles these instabilities. The new method simultaneously and consistently estimates the number of pre- and post-break factors, which liberates researchers from sequential testing and achieves uniform control of the family-wise model selection errors over an increasing number of variables. The shrinkage estimator only requires the calculation of principal components and the solution of a convex optimization problem, which ...
Working Papers , Paper 14-4

Working Paper
A Nowcasting Model for Canada: Do U.S. Variables Matter?
Bragoli, Daniela; Modugno, Michele (2016-04)
We propose a dynamic factor model for nowcasting the growth rate of quarterly real{{p}}Canadian gross domestic product. We show that the proposed model produces more accurate nowcasts than those produced by institutional forecasters, like the Bank of Canada, the The Organisation for Economic Co-operation and Development (OECD), and the survey collected by Bloomberg, which reflects the median forecast of market participants. We show that including U.S. data in a nowcasting model for Canada dramatically improves its predictive accuracy, mainly because of the absence of timely production data ...
Finance and Economics Discussion Series , Paper 2016-036

Working Paper
Measuring Uncertainty and Its Impact on the Economy
Clark, Todd E.; Carriero, Andrea; Massimiliano, Marcellino (2016-10-14)
We propose a new framework for measuring uncertainty and its effects on the economy, based on a large VAR model with errors whose stochastic volatility is driven by two common unobservable factors, representing aggregate macroeconomic and financial uncertainty. The uncertainty measures can also influence the levels of the variables so that, contrary to most existing measures, ours reflect changes in both the conditional mean and volatility of the variables, and their impact on the economy can be assessed within the same framework. Moreover, identification of the uncertainty shocks is ...
Working Papers (Old Series) , Paper 1622

Working Paper
Back to the Present: Learning about the Euro Area through a Now-casting Model
Modugno, Michele; Cascaldi-Garcia, Danilo; Ferreira, Thiago Revil T.; Giannone, Domenico (2021-03-30)
We build a model for simultaneously now-casting economic conditions in the euro area and its three largest member countries--Germany, France, and Italy. The model formalizes how market participants and policymakers monitor the euro area by incorporating all market moving indicators in real time. We find that area wide and country-specific data provide informative signals to now-cast the economic conditions in the euro area and member countries. The model provides accurate predictions of economic conditions in real time over a period that covers the past three recessions.
International Finance Discussion Papers , Paper 1313

Working Paper
FRED-SD: A Real-Time Database for State-Level Data with Forecasting Applications
Kliesen, Kevin L.; Owyang, Michael T.; Jackson, Laura E.; Bokun, Kathryn (2020-08-14)
We construct a real-time dataset (FRED-SD) with vintage data for the U.S. states that can be used to forecast both state-level and national-level variables. Our dataset includes approximately 28 variables per state, including labor market, production, and housing variables. We conduct two sets of real-time forecasting exercises. The first forecasts state-level labor-market variables using five different models and different levels of industrially-disaggregated data. The second forecasts a national-level variable exploiting the cross-section of state data. The state-forecasting experiments ...
Working Papers , Paper 2020-031

Working Paper
Revealing Cluster Structures Based on Mixed Sampling Frequencies
Ahn, Hie Joo; Rho, Yeonwoo; Liu, Yun (2020-09-23)
This paper proposes a new nonparametric mixed data sampling (MIDAS) model and develops a framework to infer clusters in a panel regression with mixed frequency data. The nonparametric MIDAS estimation method is more flexible and substantially simpler to implement than competing approaches. We show that the proposed clustering algorithm successfully recovers true membership in the cross-section, both in theory and in simulations, without requiring prior knowledge of the number of clusters. This methodology is applied to a mixed-frequency Okun's law model for state-level data in the U.S. and ...
Finance and Economics Discussion Series , Paper 2020-082

Working Paper
Simultaneous Spatial Panel Data Models with Common Shocks
Lu, Lina (2017-08-09)
I consider a simultaneous spatial panel data model, jointly modeling three effects: simultaneous effects, spatial effects and common shock effects. This joint modeling and consideration of cross-sectional heteroskedasticity result in a large number of incidental parameters. I propose two estimation approaches, a quasi-maximum likelihood (QML) method and an iterative generalized principal components (IGPC) method. I develop full inferential theories for the estimation approaches and study the trade-off between the model specifications and their respective asymptotic properties. I further ...
Supervisory Research and Analysis Working Papers , Paper RPA 17-3

Working Paper
The Factor Structure of Disagreement
Herbst, Edward P.; Winkler, Fabian (2021-07-30)
We estimate a Bayesian three-dimensional dynamic factor model on the individual forecasts in the Survey of Professional Forecasters. The factors extract the most important dimensions along which disagreement comoves across variables. We interpret our results through a general semi-structural dispersed information model. The two most important factors in the data describe disagreement about aggregate supply and demand, respectively. Up until the Great Moderation, supply disagreement was dominant, while in recent decades and particularly during the Great Recession, demand disagreement was most ...
Finance and Economics Discussion Series , Paper 2021-046

Working Paper
Global Spillover Effects of US Uncertainty
Chatterjee, Arpita; Bhattarai, Saroj; Park, Woong Yong (2017-11-01)
We study spillover effects of US uncertainty fluctuations using panel data from fifteen emerging market economies (EMEs). A US uncertainty shock negatively affects EME stock prices and exchange rates, raises EME country spreads, and leads to capital outflows from them. Moreover, it decreases EME output, while increasing their consumer prices and net exports. The negative effects on output, exchange rates, and stock prices are weaker, but the effects on capital and trade flows stronger, for South American countries compared to other EMEs. We present a model of a small open economy that faces ...
Globalization Institute Working Papers , Paper 331

Working Paper
Drilling Down: The Impact of Oil Price Shocks on Housing Prices
Sun, Yongzhi; Martinez-Garcia, Enrique; Grossman, Valerie; Torres, Luis Bernardo (2019-10-04)
This paper investigates the impact of oil price shocks on house prices in the largest urban centers in Texas. We model their dynamic relationship taking into account demand- and supply-side housing fundamentals (personal disposable income per capita, long-term interest rates and rural land prices) as well as their varying dependence on oil activity. We show the following: 1) Oil price shocks have limited pass-through to house prices?the highest pass-through is found among the most oil-dependent cities where, after 20 quarters, the cumulative response of house prices is 21 percent of the ...
Globalization Institute Working Papers , Paper 369

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