Search Results

(refine search)

SORT BY: PREVIOUS / NEXT

All:
Title:
Author:
Abstract:
Keywords:

+ Add Search Parameter

Working Paper
Predictive Modeling of Surveyed Property Conditions and Vacancy
Richter, Francisca; Urban, Apirl Hirsh; Oduro, Isaac; Whitaker, Stephan; Martin, Hal (2016-12-23)
Using the results of a comprehensive in-person survey of properties in Cleveland, Ohio, we fit predictive models of vacancy and property conditions. We draw predictor variables from administrative data that is available in most jurisdictions such as deed recordings, tax assessor?s property characteristics, and foreclosure filings. Using logistic regression and machine learning methods, we are able to make reasonably accurate out-of-sample predictions. Our findings indicate that housing professionals could use administrative data and predictive models to identify distressed properties between ...
Working Papers (Old Series) , Paper 1637

Working Paper
How Biased Are U.S. Government Forecasts of the Federal Debt?
Ericsson, Neil R. (2017-01-06)
Government debt and forecasts thereof attracted considerable attention during the recent financial crisis. The current paper analyzes potential biases in different U.S. government agencies? one-year-ahead forecasts of U.S. gross federal debt over 1984-2012. Standard tests typically fail to detect biases in these forecasts. However, impulse indicator saturation (IIS) detects economically large and highly significant time-varying biases, particularly at turning points in the business cycle. These biases do not appear to be politically related. IIS defines a generic procedure for examining ...
International Finance Discussion Papers , Paper 1189

Working Paper
Nowcasting Tail Risks to Economic Activity with Many Indicators
Clark, Todd E.; Carriero, Andrea; Massimiliano, Marcellino (2020-05-11)
This paper focuses on tail risk nowcasts of economic activity, measured by GDP growth, with a potentially wide array of monthly and weekly information. We consider different models (Bayesian mixed frequency regressions with stochastic volatility, classical and Bayesian quantile regressions, quantile MIDAS regressions) and also different methods for data reduction (either the combination of forecasts from smaller models or forecasts from models that incorporate data reduction). The results show that classical and MIDAS quantile regressions perform very well in-sample but not out-of-sample, ...
Working Papers , Paper 20-13

Working Paper
Indeterminacy and forecastability
Hirose, Yasuo; Fujiwara, Ippei (2011)
Recent studies document the deteriorating performance of forecasting models during the Great Moderation. This conversely implies that forecastability is higher in the preceding era, when the economy was unexpectedly volatile. We offer an explanation for this phenomenon in the context of equilibrium indeterminacy in dynamic stochastic general equilibrium models. First, we analytically show that a model under indeterminacy exhibits richer dynamics that can improve forecastability. Then, using a prototypical New Keynesian model, we numerically demonstrate that indeterminacy due to passive ...
Globalization Institute Working Papers , Paper 91

Working Paper
Macroeconomic and Financial Risks: A Tale of Mean and Volatility
Caldara, Dario; Scotti, Chiara; Zhong, Molin (2021-08-19)
We study the joint conditional distribution of GDP growth and corporate credit spreads using a stochastic volatility VAR. Our estimates display significant cyclical co-movement in uncertainty (the volatility implied by the conditional distributions), and risk (the probability of tail events) between the two variables. We also find that the interaction between two shocks--a main business cycle shock as in Angeletos et al. (2020) and a main financial shock--is crucial to account for the variation in uncertainty and risk, especially around crises. Our results highlight the importance of using ...
International Finance Discussion Papers , Paper 1326

Working Paper
Tracking U.S. Consumers in Real Time with a New Weekly Index of Retail Trade
Aaronson, Daniel; Brave, Scott A.; Karger, Ezra; Fogarty, Michael; Krane, Spencer D. (2021-06-18)
We create a new weekly index of retail trade that accurately predicts the U.S. Census Bureau's Monthly Retail Trade Survey (MRTS). The index's weekly frequency provides an early snapshot of the MRTS and allows for a more granular analysis of the aggregate consumer response to fast-moving events such as the Covid-19 pandemic. To construct the index, we extract the co-movement in weekly data series capturing credit and debit card transactions, foot traffic, gasoline sales, and consumer sentiment. To ensure that the index is representative of aggregate retail spending, we implementa novel ...
Working Paper Series , Paper WP-2021-05

Working Paper
Forecasting with Sufficient Dimension Reductions
Barbarino, Alessandro; Bura, Efstathia (2015-09-14)
Factor models have been successfully employed in summarizing large datasets with few underlying latent factors and in building time series forecasting models for economic variables. When the objective is to forecast a target variable y with a large set of predictors x, the construction of the summary of the xs should be driven by how informative on y it is. Most existing methods first reduce the predictors and then forecast y in independent phases of the modeling process. In this paper we present an alternative and potentially more attractive alternative: summarizing x as it relates to y, so ...
Finance and Economics Discussion Series , Paper 2015-74

Working Paper
Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions
Clark, Todd E.; Carriero, Andrea; Marcellino, Massimiliano (2020-09-22)
A rapidly growing body of research has examined tail risks in macroeconomic outcomes. Most of this work has focused on the risks of significant declines in GDP, and it has relied on quantile regression methods to estimate tail risks. Although much of this work discusses asymmetries in conditional predictive distributions, the analysis often focuses on evidence of downside risk varying more than upside risk. We note that this pattern in risk estimates over time could obtain with conditional distributions that are symmetric but subject to simultaneous shifts in conditional means (down) and ...
Working Papers , Paper 20-02R

Working Paper
Is China fudging its figures? Evidence from trading partner data
Spiegel, Mark M.; Fernald, John G.; Hsu, Eric (2015-09-21)
How reliable are China?s GDP and other data? We address this question by using trading-partner exports to China as an independent measure of its economic activity from 2000-2014. We find that the information content of Chinese GDP improves markedly after 2008. We also consider a number of plausible, non-GDP indicators of economic activity that have been identified as alternative Chinese output measures. We find that activity factors based on the first principal component of sets of indicators are substantially more informative than GDP alone. The index that best matches activity in-sample ...
Working Paper Series , Paper 2015-12

Working Paper
Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data
Cajner, Tomaz; Crane, Leland D.; Decker, Ryan A.; Hamins-Puertolas, Adrian; Kurz, Christopher J. (2019-09-05)
This paper combines information from two sources of U.S. private payroll employment to increase the accuracy of real-time measurement of the labor market. The sources are the Current Employment Statistics (CES) from BLS and microdata from the payroll processing firm ADP. We briefly describe the ADP-derived data series, compare it to the BLS data, and describe an exercise that benchmarks the data series to an employment census. The CES and the ADP employment data are each derived from roughly equal-sized samples. We argue that combining CES and ADP data series reduces the measurement error ...
Finance and Economics Discussion Series , Paper 2019-065

show more (106)

PREVIOUS / NEXT

Fed in Print

Search Results

FILTER BY year

FILTER BY Bank

FILTER BY Series

FILTER BY Content Type

FILTER BY Author

FILTER BY Jel Classification

FILTER BY Keywords