| Impulse response functions based on a causal approach to residual orthogonalization in vector autoregressions NR Swanson, CWJ Granger Journal of the American Statistical Association 92 (437), 357-367, 1997 | 658 | 1997 |
| A model selection approach to real-time macroeconomic forecasting using linear models and artificial neural networks NR Swanson, H White Review of Economics and Statistics 79 (4), 540-550, 1997 | 527 | 1997 |
| Consistent estimation with a large number of weak instruments JC Chao, NR Swanson Econometrica 73 (5), 1673-1692, 2005 | 437 | 2005 |
| Money and output viewed through a rolling window NR Swanson Journal of monetary Economics 41 (3), 455-474, 1998 | 392 | 1998 |
| A model-selection approach to assessing the information in the term structure using linear models and artificial neural networks NR Swanson, H White Journal of Business & Economic Statistics 13 (3), 265-275, 1995 | 381 | 1995 |
| Forecasting economic and financial time-series with non-linear models MP Clements, PH Franses, NR Swanson International journal of forecasting 20 (2), 169-183, 2004 | 375 | 2004 |
| Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models NR Swanson, H White International journal of Forecasting 13 (4), 439-461, 1997 | 369 | 1997 |
| Predictive Density Evaluation, in Handbook of Economic Forecasting, CWJ Granger, G. Elliott and A. Timmermann, eds V Corradi, NR Swanson Elsevier: Amsterdam, 197&284, 2006 | 304* | 2006 |
| An introduction to stochastic unit-root processes CWJ Granger, NR Swanson Journal of Econometrics 80 (1), 35-62, 1997 | 294 | 1997 |
| Weak instrument robust tests in GMM and the new Keynesian Phillips curve F Kleibergen, S Mavroeidis Journal of Business & Economic Statistics 27 (3), 293-311, 2009 | 257 | 2009 |
| An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series G Bhardwaj, NR Swanson Journal of econometrics 131 (1-2), 539-578, 2006 | 217 | 2006 |
| Instrumental variable estimation with heteroskedasticity and many instruments JA Hausman, WK Newey, T Woutersen, JC Chao, NR Swanson Quantitative Economics 3 (2), 211-255, 2012 | 214 | 2012 |
| Forecasting financial and macroeconomic variables using data reduction methods: New empirical evidence HH Kim, NR Swanson Journal of Econometrics 178, 352-367, 2014 | 191 | 2014 |
| Predictive density and conditional confidence interval accuracy tests V Corradi, NR Swanson Journal of Econometrics 135 (1-2), 187-228, 2006 | 158* | 2006 |
| Semiparametric ARX neural-network models with an application to forecasting inflation X Chen, J Racine, NR Swanson IEEE Transactions on neural networks 12 (4), 674-683, 2001 | 158 | 2001 |
| Mining big data using parsimonious factor, machine learning, variable selection and shrinkage methods HH Kim, NR Swanson International Journal of Forecasting 34 (2), 339-354, 2018 | 157* | 2018 |
| Asymptotic distribution of JIVE in a heteroskedastic IV regression with many instruments JC Chao, NR Swanson, JA Hausman, WK Newey, T Woutersen Econometric Theory 28 (1), 42-86, 2012 | 155* | 2012 |
| Out-of-sample tests for Granger causality J Chao, V Corradi, NR Swanson Macroeconomic Dynamics 5 (4), 598-620, 2001 | 145 | 2001 |
| Bootstrap conditional distribution tests in the presence of dynamic misspecification V Corradi, NR Swanson Journal of Econometrics 133 (2), 779-806, 2006 | 142* | 2006 |
| FUTURE DEVELOPMENTS IN THE STUDY OF COINTEGRATED VARIABLES* CWJ Granger, N Swanson Oxford Bulletin of Economics and Statistics 58 (3), 537-553, 1996 | 142 | 1996 |
Valentina CorradiUniversity of Surreysurrey.ac.uk의 이메일 확인됨
