Thinking Outside the Container: A Sparse Partial Least Squares Approach to Forecasting Trade Flows
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- Giulia Brancaccio & Myrto Kalouptsidi & Theodore Papageorgiou, 2017.
"Geography, Search Frictions and Endogenous Trade Costs,"
NBER Working Papers
23581, National Bureau of Economic Research, Inc.
- Kalouptsidi, Myrto & Papageorgiou, Theodore & Brancaccio, Giulia, 2017. "Geography, Search Frictions and Endogenous Trade Costs," CEPR Discussion Papers 12141, C.E.P.R. Discussion Papers.
- Jushan Bai & Serena Ng, 2002.
"Determining the Number of Factors in Approximate Factor Models,"
Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
- Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Econometric Society World Congress 2000 Contributed Papers 1504, Econometric Society.
- Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Boston College Working Papers in Economics 440, Boston College Department of Economics.
- Eickmeier, Sandra & Ng, Tim, 2011.
"Forecasting national activity using lots of international predictors: An application to New Zealand,"
International Journal of Forecasting, Elsevier, vol. 27(2), pages 496-511, April.
- Eickmeier, Sandra & Ng, Tim, 2011. "Forecasting national activity using lots of international predictors: An application to New Zealand," International Journal of Forecasting, Elsevier, vol. 27(2), pages 496-511.
- Eickmeier, Sandra & Ng, Tim, 2009. "Forecasting national activity using lots of international predictors: an application to New Zealand," Discussion Paper Series 1: Economic Studies 2009,11, Deutsche Bundesbank.
- Sandra Eickmeier & Tim Ng, 2009. "Forecasting national activity using lots of international predictors: an application to New Zealand," Reserve Bank of New Zealand Discussion Paper Series DP2009/04, Reserve Bank of New Zealand.
- Sharat Ganapati & Woan Foong Wong & Oren Ziv, 2024.
"Entrepôt: Hubs, Scale, and Trade Costs,"
American Economic Journal: Macroeconomics, American Economic Association, vol. 16(4), pages 239-278, October.
- Sharat Ganapati & Woan Foong Wong & Oren Ziv, 2020. "Entrepôt: Hubs, Scale, and Trade Costs," CESifo Working Paper Series 8199, CESifo.
- Sharat Ganapati & Woan Foong Wong & Oren Ziv, 2021. "Entrepôt: Hubs, Scale, and Trade Costs," NBER Working Papers 29015, National Bureau of Economic Research, Inc.
- Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015.
"Measuring Uncertainty,"
American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
- Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2013. "Measuring Uncertainty," NBER Working Papers 19456, National Bureau of Economic Research, Inc.
- Boivin, Jean & Ng, Serena, 2006.
"Are more data always better for factor analysis?,"
Journal of Econometrics, Elsevier, vol. 132(1), pages 169-194, May.
- Jean Boivin & Serena Ng, 2003. "Are More Data Always Better for Factor Analysis?," NBER Working Papers 9829, National Bureau of Economic Research, Inc.
- Diebold, Francis X & Mariano, Roberto S, 2002.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
- Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-263, July.
- Francis X. Diebold & Roberto S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Jörg Breitung & Malte Knüppel, 2021.
"How far can we forecast? Statistical tests of the predictive content,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(4), pages 369-392, June.
- Breitung, Jörg & Knüppel, Malte, 2018. "How far can we forecast? Statistical tests of the predictive content," Discussion Papers 07/2018, Deutsche Bundesbank.
- Mr. Serkan Arslanalp & Mr. Marco Marini & Ms. Patrizia Tumbarello, 2019. "Big Data on Vessel Traffic: Nowcasting Trade Flows in Real Time," IMF Working Papers 2019/275, International Monetary Fund.
- Jushan Bai & Serena Ng, 2004.
"A PANIC Attack on Unit Roots and Cointegration,"
Econometrica, Econometric Society, vol. 72(4), pages 1127-1177, July.
- Jushan Bai & Serena Ng, 2001. "A Panic Attack on Unit Roots and Cointegration," Economics Working Paper Archive 469, The Johns Hopkins University,Department of Economics.
- Jushan Bai & Serena Ng, 2001. "A PANIC Attack on Unit Roots and Cointegration," Boston College Working Papers in Economics 519, Boston College Department of Economics.
- Ulltveit-Moe, Karen Helene & Heiland, Inga & Moxnes, Andreas & Zi, Yuan, 2019. "Trade From Space: Shipping Networks and The Global Implications of Local Shocks," CEPR Discussion Papers 14193, C.E.P.R. Discussion Papers.
- Grimme, Christian & Lehmann, Robert & Noeller, Marvin, 2021.
"Forecasting imports with information from abroad,"
Economic Modelling, Elsevier, vol. 98(C), pages 109-117.
- Christian Grimme & Robert Lehmann & Marvin Noeller, 2018. "Forecasting Imports with Information from Abroad," CESifo Working Paper Series 7079, CESifo.
- Christian Grimme & Robert Lehmann & Marvin Noeller, 2019. "Forecasting Imports with Information from Abroad," ifo Working Paper Series 294, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
- Julieta Fuentes & Pilar Poncela & Julio Rodríguez, 2015.
"Sparse Partial Least Squares in Time Series for Macroeconomic Forecasting,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 576-595, June.
- Fuentes, Julieta & Poncela, Pilar & Rodríguez, Julio, 2012. "Sparse partial least squares in time series for macroeconomic forecasting," DES - Working Papers. Statistics and Econometrics. WS ws122216, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Oya Celasun & Mr. Niels-Jakob H Hansen & Ms. Aiko Mineshima & Mariano Spector & Jing Zhou, 2022. "Supply Bottlenecks: Where, Why, How Much, and What Next?," IMF Working Papers 2022/031, International Monetary Fund.
- Maximo Camacho & Gabriel Perez-Quiros, 2010.
"Introducing the euro-sting: Short-term indicator of euro area growth,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 663-694.
- Maximo Camacho & Gabriel Perez-Quiros, 2008. "Introducing the EURO-STING: Short Term INdicator of Euro Area Growth," Working Papers 0807, Banco de España.
- Pérez-Quirós, Gabriel & Camacho, Máximo, 2009. "Introducing the Euro-STING: Short-Term Indicator of Euro Area Growth," CEPR Discussion Papers 7343, C.E.P.R. Discussion Papers.
- Mr. Diego A. Cerdeiro & Andras Komaromi & Yang Liu & Mamoon Saeed, 2020. "World Seaborne Trade in Real Time: A Proof of Concept for Building AIS-based Nowcasts from Scratch," IMF Working Papers 2020/057, International Monetary Fund.
- Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
- Hyonho Chun & Sündüz Keleş, 2010. "Sparse partial least squares regression for simultaneous dimension reduction and variable selection," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(1), pages 3-25, January.
- Christian Grimme & Klaus Wohlrabe, 2014. "Die ifo Exporterwartungen – ein neuer Indikator zur Lage der Exportindustrie in Deutschland," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 67(23), pages 64-65, December.
- Theodore Papageorgiou & Myrto Kalouptsidi & Giulia Brancaccio, 2017. "Geography, Search Frictions and Trade Costs," 2017 Meeting Papers 1105, Society for Economic Dynamics.
- Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
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JEL classification:
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
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This paper has been announced in the following NEP Reports:- NEP-FOR-2022-11-28 (Forecasting)
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