Search Results - subject:"factor augmented models"

On the applicability of dynamic factor models for forecasting real GDP growth in Armenia

Poghosyan, Karen; Poghosyan, Ruben - In: Finance a úvěr 71 (2021) 1, pp. 52-79

Persistent link: https://www.econbiz.de/10012601903

Exchange rate predictability, common factors, and applications in carry trade

Ogruk-Maz, Gokcen; Wu, Shengxiong; Yildirim, Sinan - In: International journal of monetary economics and finance … 13 (2020) 6, pp. 513-530

Persistent link: https://www.econbiz.de/10012515315

Forecasting US real private residential fixed investment using a large number of predictors

Aye, Goodness C.; Miller, Stephen M.; Gupta, Rangan; … - In: Empirical economics : a journal of the Institute for … 51 (2016) 4, pp. 1557-1580

Persistent link: https://www.econbiz.de/10011661835

Forecasting US Real Private Residential Fixed Investment Using a Large Number of Predictors

GUPTA, RANGAN; Miller, Stephen M.; Balcilar, Mehmet; … - Department of Economics, University of Connecticut - 2014

This paper employs classical bivariate, factor augmented (FA), slab-and-spike variable selection (SSVS)-based, and Bayesian semi-parametric shrinkage (BSS)-based predictive regression models to forecast US real private residential fixed investment over an out-of-sample period from 1983:Q1 to...

Persistent link: https://www.econbiz.de/10010888383

Using large data sets to forecast sectoral employment

Gupta, Rangan; Kabundi, Alain; Miller, Stephen; … - In: Statistical Methods and Applications 23 (2014) 2, pp. 229-264

augmented models, especially error-correction versions, generally prove the best in out-of-sample forecast performance, implying …-of-sample forecasts from January 1990 through March 2009 and from April 2009 through March 2010, respectively. We find that factor …

Persistent link: https://www.econbiz.de/10010998669

Forecasting the US Real Private Residential Fixed Investment Using Large Number of Predictors

Aye, Goodness C.; Miller, Stephen M.; Gupta, Rangan; … - Department of Economics, Faculty of Economic and … - 2013

This paper employs classical bivariate, factor augmented (FA), slab and spike variable selection (SSVS)-based, and Bayesian semiparametric shrinkage (BSS)-based predictive regression models to forecast the US real private residential fixed investment series over an out of sample period of 1983Q1...

Persistent link: https://www.econbiz.de/10011149763

Forecasting house prices for the four census regions and the aggregate US economy in a data-rich environment

Gupta, Rangan - In: Applied economics 45 (2013) 31/33, pp. 4677-4697

Persistent link: https://www.econbiz.de/10010225005

Forecasting House Prices for the Four Census Regions and the Aggregate US Economy: The Role of a Data-Rich Environment

Gupta, Rangan - Department of Economics, Faculty of Economic and … - 2012

This paper considers the ability of large-scale (involving 145 fundamental variables) time-series models, estimated based on dynamic factor analysis and Bayesian shrinkage, to forecast real house price growth rates of the four US census regions and the aggregate US economy. Besides, the standard...

Persistent link: https://www.econbiz.de/10010603880

Using Large Data Sets to Forecast Sectoral Employment

GUPTA, RANGAN; Kabundi, Alain; Miller, Stephen M.; … - Department of Economics, University of Connecticut - 2011

the best forecasting model for each employment series as well as combined forecasts. We find that factor augmented models …

Persistent link: https://www.econbiz.de/10008796107

Using Large Data Sets to Forecast Sectoral Employment

Gupta, Rangan; Kabundi, Alain; Miller, Stephen M.; … - Department of Economics, Faculty of Economic and … - 2011

model for each employment series. We find that factor augmented models, especially error-correction versions, generally …

Persistent link: https://www.econbiz.de/10008784600