| Year |
Citation |
Score |
| 2020 |
Yu B, Mizrach B, Swanson NR. New Evidence of the Marginal Predictive Content of Small and Large Jumps in the Cross-Section Econometrics. 8: 19. DOI: 10.3390/Econometrics8020019 |
0.403 |
|
| 2020 |
Swanson NR, Xiong W, Yang X. Predicting Interest Rates Using Shrinkage Methods, Real‐Time Diffusion Indexes, and Model Combinations* Journal of Applied Econometrics. 35: 587-613. DOI: 10.1002/Jae.2768 |
0.441 |
|
| 2020 |
Cepni O, Guney IE, Swanson NR. Forecasting and nowcasting emerging market GDP growth rates: The role of latent global economic policy uncertainty and macroeconomic data surprise factors Journal of Forecasting. 39: 18-36. DOI: 10.1002/For.2602 |
0.315 |
|
| 2019 |
Cheng M, Swanson NR. Fixed and Long Time Span Jump Tests: New Monte Carlo and Empirical Evidence Econometrics. 7: 13. DOI: 10.3390/Econometrics7010013 |
0.376 |
|
| 2019 |
Cepni O, Güney IE, Swanson NR. Nowcasting and forecasting GDP in emerging markets using global financial and macroeconomic diffusion indexes International Journal of Forecasting. 35: 555-572. DOI: 10.1016/J.Ijforecast.2018.10.008 |
0.401 |
|
| 2019 |
Mukherjee A, Peng W, Swanson NR, Yang X. Financial econometrics and big data: A survey of volatility estimators and tests for the presence of jumps and co-jumps ☆ Handbook of Statistics. 42: 3-59. DOI: 10.1016/Bs.Host.2018.11.006 |
0.479 |
|
| 2018 |
Swanson NR, Xiong W. Big Data Analytics in Economics: What Have We Learned So Far, and Where Should We Go from Here? Canadian Journal of Economics. 51: 695-746. DOI: 10.1111/Caje.12336 |
0.418 |
|
| 2018 |
Corradi V, Silvapulle MJ, Swanson NR. Testing for Jumps and Jump Intensity Path Dependence Journal of Econometrics. 204: 248-267. DOI: 10.1016/J.Jeconom.2018.02.004 |
0.403 |
|
| 2018 |
Kim HH, Swanson NR. Methods for backcasting, nowcasting and forecasting using factor‐MIDAS: With an application to Korean GDP Journal of Forecasting. 37: 281-302. DOI: 10.1002/For.2499 |
0.485 |
|
| 2017 |
Jin S, Corradi V, Swanson NR. Robust Forecast Comparison Econometric Theory. 33: 1306-1351. DOI: 10.2139/Ssrn.2605927 |
0.485 |
|
| 2016 |
Kim HH, Swanson NR. Mining Big Data Using Parsimonious Factor, Machine Learning, Variable Selection and Shrinkage Methods International Journal of Forecasting. 34: 339-354. DOI: 10.1016/J.Ijforecast.2016.02.012 |
0.46 |
|
| 2015 |
Duong D, Swanson NR. Empirical evidence on the importance of aggregation, asymmetry, and jumps for volatility prediction Journal of Econometrics. 187: 606-621. DOI: 10.1016/J.Jeconom.2015.02.042 |
0.752 |
|
| 2015 |
Swanson NR, Urbach R. Prediction and Simulation Using Simple Models Characterized by Nonstationarity and Seasonality International Review of Economics & Finance. 40: 312-323. DOI: 10.1016/J.Iref.2015.02.027 |
0.513 |
|
| 2014 |
Corradi V, Swanson NR. Testing for Structural Stability of Factor Augmented Forecasting Models Journal of Econometrics. 182: 100-118. DOI: 10.1016/J.Jeconom.2014.04.011 |
0.421 |
|
| 2014 |
Chen X, Swanson NR. Causality, prediction, and specification analysis: Recent advances and future directions Journal of Econometrics. 182: 1-4. DOI: 10.1016/J.Jeconom.2014.04.003 |
0.352 |
|
| 2014 |
Kim HH, Swanson NR. Forecasting Financial and Macroeconomic Variables Using Data Reduction Methods: New Empirical Evidence Journal of Econometrics. 178: 352-367. DOI: 10.1016/J.Jeconom.2013.08.033 |
0.523 |
|
| 2014 |
Chao JC, Hausman JA, Newey WK, Swanson NR, Woutersen T. Testing overidentifying restrictions with many instruments and heteroskedasticity Journal of Econometrics. 178: 15-21. DOI: 10.1016/J.Jeconom.2013.08.003 |
0.604 |
|
| 2012 |
Hausman JA, Newey WK, Woutersen T, Chao JC, Swanson NR. Instrumental Variable Estimation with Heteroskedasticity and Many Instruments Quantitative Economics. 3: 211-255. DOI: 10.3982/Qe89 |
0.618 |
|
| 2012 |
Chao JC, Swanson NR, Hausman JA, Newey WK, Woutersen T. Asymptotic Distribution Of Jive In A Heteroskedastic Iv Regression With Many Instruments Econometric Theory. 28: 42-86. DOI: 10.1017/S0266466611000120 |
0.575 |
|
| 2011 |
Swanson NR, Cai L. In- and Out-of-Sample Specification Analysis of Spot Rate Models: Further Evidence for the Period 1982-2008 Journal of Empirical Finance. 18: 743-764. DOI: 10.2139/Ssrn.1856053 |
0.477 |
|
| 2011 |
Corradi V, Distaso W, Swanson NR. Predictive Inference for Integrated Volatility Journal of the American Statistical Association. 106: 1496-1512. DOI: 10.1198/Jasa.2011.Tm10012 |
0.445 |
|
| 2011 |
Armah NAC, Swanson NR. Some Variables are More Worthy than Others: New Diffusion Index Evidence on the Monitoring of Key Economic Indicators Applied Financial Economics. 21: 43-60. DOI: 10.1080/09603107.2011.523188 |
0.419 |
|
| 2010 |
Korenok O, Radchenko S, Swanson NR. International evidence on the efficacy of new-keynesian models of inflation persistence Journal of Applied Econometrics. 25: 31-54. DOI: 10.2139/Ssrn.966410 |
0.402 |
|
| 2010 |
Swanson NR. Further Developments in the Study of Cointegrated Variables Journal of Financial Econometrics. 8: 187-190. DOI: 10.1093/Jjfinec/Nbq004 |
0.309 |
|
| 2009 |
Corradi V, Swanson NR. Predictive density construction and accuracy testing with multiple possibly misspecified diffusion models Journal of Econometrics. 161: 304-324. DOI: 10.1016/J.Jeconom.2010.12.009 |
0.479 |
|
| 2009 |
Corradi V, Distaso W, Swanson NR. Predictive density estimators for daily volatility based on the use of realized measures Journal of Econometrics. 150: 119-138. DOI: 10.1016/J.Jeconom.2008.12.015 |
0.45 |
|
| 2009 |
Swanson NR. Comments on “Forecasting economic and financial variables with global VARs” International Journal of Forecasting. 25: 697-702. DOI: 10.1016/J.Ijforecast.2009.05.020 |
0.314 |
|
| 2008 |
Corradi V, Fernandez A, Swanson NR. Information in the Revision Process of Real-Time Datasets Journal of Business & Economic Statistics. 27: 455-467. DOI: 10.1198/Jbes.2009.07209 |
0.412 |
|
| 2008 |
Bhardwaj G, Corradi V, Swanson NR. A simulation-based specification test for diffusion processes Journal of Business and Economic Statistics. 26: 176-193. DOI: 10.1198/073500107000000412 |
0.742 |
|
| 2007 |
Korenok O, Swanson NR. How Sticky Is Sticky Enough? A Distributional and Impulse Response Analysis of New Keynesian DSGE Models Journal of Money, Credit and Banking. 39: 1481-1508. DOI: 10.2139/Ssrn.812089 |
0.405 |
|
| 2007 |
Corradi V, Swanson NR. Nonparametric Bootstrap Procedures for Predictive Inference Based on Recursive Estimation Schemes International Economic Review. 48: 67-109. DOI: 10.1111/J.1468-2354.2007.00418.X |
0.5 |
|
| 2007 |
Bhardwaj G, Swanson NR. A Predictive Comparison of Some Simple Long Memory and Short Memory Models of Daily U.S. Stock Returns, With Emphasis on Business Cycle Effects Contributions to Economic Analysis. 276: 379-405. DOI: 10.1016/S0573-8555(05)76014-4 |
0.769 |
|
| 2007 |
Corradi V, Swanson NR. Evaluation of Dynamic Stochastic General Equilibrium Models Based on Distributional Comparison of Simulated and Historical Data Journal of Econometrics. 136: 699-723. DOI: 10.1016/J.Jeconom.2005.11.010 |
0.449 |
|
| 2007 |
Chao JC, Swanson NR. Alternative approximations of the bias and MSE of the IV estimator under weak identification with an application to bias correction Journal of Econometrics. 137: 515-555. DOI: 10.1016/J.Jeconom.2005.09.002 |
0.386 |
|
| 2006 |
Corradi V, Swanson NR. Bootstrap Conditional Distribution Tests In the Presence of Dynamic Misspecification Journal of Econometrics. 133: 779-806. DOI: 10.2139/Ssrn.433002 |
0.421 |
|
| 2006 |
Swanson NR, Dijk DJCv. Are Statistical Reporting Agencies Getting it Right? Data Rationality and Business Cycle Asymmetry Journal of Business & Economic Statistics. 24: 24-42. DOI: 10.1198/073500105000000036 |
0.339 |
|
| 2006 |
Chao JC, Swanson NR. Asymptotic normality of single-equation estimators for the case with a large number of weak instruments Econometric Theory and Practice: Frontiers of Analysis and Applied Research. 82-124. DOI: 10.1017/CBO9781139164863.006 |
0.333 |
|
| 2006 |
Corradi V, Swanson NR. Predictive density and conditional confidence interval accuracy tests Journal of Econometrics. 135: 187-228. DOI: 10.1016/J.Jeconom.2005.07.026 |
0.459 |
|
| 2006 |
Swanson NR, Elliott G, Ghysels E, Gonzalo J. Predictive methodology and application in economics and finance: Volume in honor of the accomplishments of Clive W.J. Granger Journal of Econometrics. 135: 1-9. DOI: 10.1016/J.Jeconom.2005.07.011 |
0.36 |
|
| 2006 |
Corradi V, Swanson NR. The effect of data transformation on common cycle, cointegration, and unit root tests: Monte Carlo results and a simple test Journal of Econometrics. 132: 195-229. DOI: 10.1016/J.Jeconom.2005.01.028 |
0.346 |
|
| 2006 |
Bhardwaj G, Swanson NR. An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series Journal of Econometrics. 131: 539-578. DOI: 10.1016/J.Jeconom.2005.01.016 |
0.792 |
|
| 2005 |
Chao JC, Swanson NR. Consistent Estimation with a Large Number of Weak Instruments Econometrica. 73: 1673-1692. DOI: 10.1111/J.1468-0262.2005.00632.X |
0.316 |
|
| 2005 |
Korenok O, Swanson NR. The Incremental Predictive Information Associated with Using Theoretical New Keynesian DSGE Models vs. Simple Linear Econometric Models Oxford Bulletin of Economics and Statistics. 67: 905-930. DOI: 10.1111/J.1468-0084.2005.00145.X |
0.524 |
|
| 2005 |
Bachmeier LJ, Swanson NR. Predicting inflation: Does the quantity theory help? Economic Inquiry. 43: 570-585. DOI: 10.1093/Ei/Cbi039 |
0.768 |
|
| 2005 |
Corradi V, Swanson NR. A Test For Comparing Multiple Misspecified Conditional Interval Models Econometric Theory. 21: 991-1016. DOI: 10.1017/S0266466605050498 |
0.489 |
|
| 2005 |
Corradi V, Swanson NR. Bootstrap specification tests for diffusion processes Journal of Econometrics. 124: 117-148. DOI: 10.1016/J.Jeconom.2004.02.013 |
0.437 |
|
| 2004 |
Bachmeier L, Gaughan P, Swanson NR. The Volume of Federal Litigation and the Macroeconomy International Review of Law and Economics. 24: 191-207. DOI: 10.1016/J.Irle.2004.08.004 |
0.738 |
|
| 2004 |
Clements MP, Franses PH, Swanson NR. Forecasting economic and financial time-series with non-linear models International Journal of Forecasting. 20: 169-183. DOI: 10.1016/J.Ijforecast.2003.10.004 |
0.463 |
|
| 2004 |
Corradi V, Swanson NR. Some recent developments in predictive accuracy testing with nested models and (generic) nonlinear alternatives International Journal of Forecasting. 20: 185-199. DOI: 10.1016/J.Ijforecast.2003.09.008 |
0.429 |
|
| 2004 |
Corradi V, Swanson NR. A test for the distributional comparison of simulated and historical data Economics Letters. 85: 185-193. DOI: 10.1016/J.Econlet.2004.04.005 |
0.436 |
|
| 2003 |
Krishna K, Ozyildirim A, Swanson NR. Trade, investment and growth: nexus, analysis and prognosis Journal of Development Economics. 70: 479-499. DOI: 10.1016/S0304-3878(02)00106-2 |
0.4 |
|
| 2002 |
Ghysels E, Swanson NR, Callan M. Monetary policy rules with model and data uncertainty Southern Economic Journal. 69: 239-265. DOI: 10.2307/1061671 |
0.305 |
|
| 2002 |
Breitung J, Swanson NR. Temporal aggregation and spurious instantaneous causality in multiple time series models Journal of Time Series Analysis. 23: 651-665. DOI: 10.1111/1467-9892.00284 |
0.369 |
|
| 2002 |
Christoffersen P, Ghysels E, Swanson NR. Let's get "real" about using economic data Journal of Empirical Finance. 9: 343-360. DOI: 10.1016/S0927-5398(01)00059-7 |
0.336 |
|
| 2002 |
Corradi V, Swanson NR. A Consistent Test for Nonlinear Out of Sample Predictive Accuracy Journal of Econometrics. 110: 353-381. DOI: 10.1016/S0304-4076(02)00099-4 |
0.529 |
|
| 2002 |
Swanson NR. Comments on 'A vector error-correction forecasting model of the US economy' Journal of Macroeconomics. 24: 599-606. DOI: 10.1016/S0164-0704(02)00068-X |
0.372 |
|
| 2001 |
Chen X, Racine J, Swanson NR. Semiparametric ARX neural-network models with an application to forecasting inflation. Ieee Transactions On Neural Networks / a Publication of the Ieee Neural Networks Council. 12: 674-83. PMID 18249903 DOI: 10.1109/72.935081 |
0.457 |
|
| 2001 |
Granger CWJ, Swanson N. Further developments in the study of cointegrated variables Oxford Bulletin of Economics and Statistics. 58: 302-318. DOI: 10.1111/J.1468-0084.1996.Mp58003007.X |
0.309 |
|
| 2001 |
Chao J, Corradi V, Swanson NR. Out-Of-Sample Tests For Granger Causality Macroeconomic Dynamics. 5: 598-620. DOI: 10.1017/S1365100501023070 |
0.406 |
|
| 2001 |
Corradi V, Swanson NR, Olivetti C. Predictive ability with cointegrated variables Journal of Econometrics. 104: 315-358. DOI: 10.1016/S0304-4076(01)00086-0 |
0.513 |
|
| 2001 |
Amato JD, Swanson NR. The real-time predictive content of money for output Journal of Monetary Economics. 48: 3-24. DOI: 10.1016/S0304-3932(01)00070-8 |
0.388 |
|
| 2001 |
Kocagil AE, Swanson NR, Zeng T. A new definition for time-dependent price mean reversion in commodity markets Economics Letters. 71: 9-16. DOI: 10.1016/S0165-1765(00)00397-9 |
0.321 |
|
| 2001 |
Swanson NR, Zeng T. Choosing among competing econometric forecasts: Regression‐based forecast combination using model selection Journal of Forecasting. 20: 425-440. DOI: 10.1002/For.784 |
0.442 |
|
| 2000 |
Swanson NR, Clements MP, Hendry DF. Forecasting Economic Time Series Journal of the American Statistical Association. 95: 687. DOI: 10.2307/2669429 |
0.332 |
|
| 2000 |
Chao JC, Swanson NR. Tests Of Nonnested Hypotheses In Nonstationary Regressions With An Application To Modeling Industrial Production Macroeconomic Dynamics. 4: 42-72. DOI: 10.1017/S1365100500014036 |
0.408 |
|
| 2000 |
Corradi V, Swanson NR, White H. Testing for stationarity-ergodicity and for comovements between nonlinear discrete time Markov processes Journal of Econometrics. 96: 39-73. DOI: 10.1016/S0304-4076(99)00050-0 |
0.526 |
|
| 2000 |
Bierens HJ, Swanson NR. The econometric consequences of the ceteris paribus condition in economic theory Journal of Econometrics. 95: 223-253. DOI: 10.1016/S0304-4076(99)00038-X |
0.307 |
|
| 2000 |
Bierens HJ, Swanson NR. The econometric consequences of the ceteris paribus condition in economic theory Journal of Econometrics. 95: 223-253. |
0.319 |
|
| 1999 |
Swanson NR. Finite sample properties of a simple LM test for neglected nonlinearity in error‐correcting regression equations Statistica Neerlandica. 53: 76-95. DOI: 10.1111/1467-9574.00099 |
0.394 |
|
| 1998 |
Zeng T, Swanson NR. Predictive Evaluation of Econometric Forecasting Models in Commodity Futures Markets Studies in Nonlinear Dynamics and Econometrics. 2: 1-21. DOI: 10.2202/1558-3708.1037 |
0.433 |
|
| 1998 |
Swanson NR. Money and output viewed through a rolling window Journal of Monetary Economics. 41: 455-474. DOI: 10.1016/S0304-3932(98)00005-1 |
0.396 |
|
| 1997 |
Swanson NR, White HL. A Model Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks The Review of Economics and Statistics. 79: 540-550. DOI: 10.1162/003465397557123 |
0.478 |
|
| 1997 |
Swanson NR, Granger CWJ. Impulse Response Functions Based on a Causal Approach to Residual Orthogonalization in Vector Autoregressions Journal of the American Statistical Association. 92: 357-367. DOI: 10.1080/01621459.1997.10473634 |
0.413 |
|
| 1997 |
Swanson NR, White H. Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models International Journal of Forecasting. 13: 439-461. DOI: 10.1016/S0169-2070(97)00030-7 |
0.64 |
|
| 1996 |
Swanson N. Forecasting Using First-Available Versus Fully Revised Economic Time-Series Data Studies in Nonlinear Dynamics and Econometrics. 1: 1-20. DOI: 10.2202/1558-3708.1012 |
0.347 |
|
| 1995 |
Swanson NR, White H. A Model-Selection Approach to Assessing the Information in the Term Structure Using Linear Models and Artificial Neural Networks Journal of Business & Economic Statistics. 13: 265-275. DOI: 10.1080/07350015.1995.10524600 |
0.632 |
|
| Show low-probability matches. |