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Forecasting national activity using lots of international predictors: An application to New Zealand
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- Robert Lehmann, 2016. "Economic Growth and Business Cycle Forecasting at the Regional Level," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 65.
- Eickmeier, Sandra & Ng, Tim, 2015.
"How do US credit supply shocks propagate internationally? A GVAR approach,"
European Economic Review, Elsevier, vol. 74(C), pages 128-145.
- Eickmeier, Sandra & Ng, Tim, 2011. "How do credit supply shocks propagate internationally? A GVAR approach," Discussion Paper Series 1: Economic Studies 2011,27, Deutsche Bundesbank.
- Eickmeier, Sandra & Ng, Tim, 2011. "How Do Credit Supply Shocks Propagate Internationally? A GVAR approach," CEPR Discussion Papers 8720, C.E.P.R. Discussion Papers.
- Petar Sorić & Blanka Škrabić Perić & Marina Matošec, 2022. "Breaking new grounds: a fresh insight into the leading properties of business and consumer survey indicators," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(6), pages 4511-4535, December.
- 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.
- Marijn A Bolhuis & Judd N L Cramer & Lawrence H Summers, 2022.
"The Coming Rise in Residential Inflation [The repeat rent index],"
Review of Finance, European Finance Association, vol. 26(5), pages 1051-1072.
- Marijn A. Bolhuis & Judd N. L. Cramer & Lawrence H. Summers, 2022. "The Coming Rise in Residential Inflation," NBER Working Papers 29795, National Bureau of Economic Research, Inc.
- Stamer, Vincent, 2022. "Thinking Outside the Container: A Sparse Partial Least Squares Approach to Forecasting Trade Flows," VfS Annual Conference 2022 (Basel): Big Data in Economics 264096, Verein für Socialpolitik / German Economic Association.
- Chenghan Hou & Bao Nguyen & Bo Zhang, 2023. "Real‐time forecasting of the Australian macroeconomy using flexible Bayesian VARs," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 418-451, March.
- Chudik, Alexander & Grossman, Valerie & Pesaran, M. Hashem, 2016.
"A multi-country approach to forecasting output growth using PMIs,"
Journal of Econometrics, Elsevier, vol. 192(2), pages 349-365.
- Alexander Chudik & Valerie Grossman & M. Hashem Pesaran, 2014. "A Multi-Country Approach to Forecasting Output Growth Using PMIs," CESifo Working Paper Series 5100, CESifo.
- Alexander Chudik & Valerie Grossman & M. Hashem Pesaran, 2014. "A multi-country approach to forecasting output growth using PMIs," Globalization Institute Working Papers 213, Federal Reserve Bank of Dallas.
- Halberstadt, Arne & Stapf, Jelena, 2012. "An affine multifactor model with macro factors for the German term structure: Changing results during the recent crises," Discussion Papers 25/2012, Deutsche Bundesbank.
- Schumacher, Christian, 2010.
"Factor forecasting using international targeted predictors: The case of German GDP,"
Economics Letters, Elsevier, vol. 107(2), pages 95-98, May.
- Schumacher, Christian, 2009. "Factor forecasting using international targeted predictors: the case of German GDP," Discussion Paper Series 1: Economic Studies 2009,10, Deutsche Bundesbank.
- Richardson, Adam & van Florenstein Mulder, Thomas & Vehbi, Tuğrul, 2021.
"Nowcasting GDP using machine-learning algorithms: A real-time assessment,"
International Journal of Forecasting, Elsevier, vol. 37(2), pages 941-948.
- Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2019. "Nowcasting New Zealand GDP using machine learning algorithms," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
- Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2018. "Nowcasting New Zealand GDP using machine learning algorithms," CAMA Working Papers 2018-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Bušs, Ginters, 2009. "Comparing forecasts of Latvia's GDP using simple seasonal ARIMA models and direct versus indirect approach," MPRA Paper 16684, University Library of Munich, Germany.
- Sorić, Petar & Lolić, Ivana & Claveria, Oscar & Monte, Enric & Torra, Salvador, 2019. "Unemployment expectations: A socio-demographic analysis of the effect of news," Labour Economics, Elsevier, vol. 60(C), pages 64-74.
- Cubadda, Gianluca & Guardabascio, Barbara, 2012.
"A medium-N approach to macroeconomic forecasting,"
Economic Modelling, Elsevier, vol. 29(4), pages 1099-1105.
- Gianluca Cubadda & Barbara Guardabascio, 2010. "A Medium-N Approach to Macroeconomic Forecasting," CEIS Research Paper 176, Tor Vergata University, CEIS, revised 09 Dec 2010.
- Cepni, Oguzhan & Güney, I. Ethem & Swanson, Norman R., 2019. "Nowcasting and forecasting GDP in emerging markets using global financial and macroeconomic diffusion indexes," International Journal of Forecasting, Elsevier, vol. 35(2), pages 555-572.
- Panagiotelis, Anastasios & Athanasopoulos, George & Hyndman, Rob J. & Jiang, Bin & Vahid, Farshid, 2019.
"Macroeconomic forecasting for Australia using a large number of predictors,"
International Journal of Forecasting, Elsevier, vol. 35(2), pages 616-633.
- Bin Jiang & George Athanasopoulos & Rob J Hyndman & Anastasios Panagiotelis & Farshid Vahid, 2017. "Macroeconomic forecasting for Australia using a large number of predictors," Monash Econometrics and Business Statistics Working Papers 2/17, Monash University, Department of Econometrics and Business Statistics.
- Lehmann Robert & Wohlrabe Klaus, 2015.
"Forecasting GDP at the Regional Level with Many Predictors,"
German Economic Review, De Gruyter, vol. 16(2), pages 226-254, May.
- Robert Lehmann & Klaus Wohlrabe, 2015. "Forecasting GDP at the Regional Level with Many Predictors," German Economic Review, Verein für Socialpolitik, vol. 16(2), pages 226-254, May.
- Robert Lehmann & Klaus Wohlrabe, 2012. "Forecasting GDP at the Regional Level with Many Predictors," CESifo Working Paper Series 3956, CESifo.
- Robert Lehmann & Klaus Wohlrabe, 2013. "Forecasting GDP at the regional level with many predictors," ERSA conference papers ersa13p15, European Regional Science Association.
- Lehmann, Robert & Wohlrabe, Klaus, 2013. "Forecasting GDP at the regional level with many predictors," Discussion Papers in Economics 17104, University of Munich, Department of Economics.
- Petar Sorić, 2020. "“Normal†growth of the Chinese economy: new metrics based on consumer confidence data," Economics Bulletin, AccessEcon, vol. 40(2), pages 1740-1746.
- Jack Fosten & Shaoni Nandi, 2023. "Nowcasting from cross‐sectionally dependent panels," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 898-919, September.
- Kevin Moran & Simplice Aimé Nono & Imad Rherrad, 2018. "Forecasting with Many Predictors: How Useful are National and International Confidence Data?," Cahiers de recherche 1814, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
- Kopoin, Alexandre & Moran, Kevin & Paré, Jean-Pierre, 2013. "Forecasting regional GDP with factor models: How useful are national and international data?," Economics Letters, Elsevier, vol. 121(2), pages 267-270.
- Richardson, Adam & van Florenstein Mulder, Thomas & Vehbi, Tuğrul, 2021.
"Nowcasting GDP using machine-learning algorithms: A real-time assessment,"
International Journal of Forecasting, Elsevier, vol. 37(2), pages 941-948.
- Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2019. "Nowcasting GDP using machine learning algorithms: A real-time assessment," Reserve Bank of New Zealand Discussion Paper Series DP2019/03, Reserve Bank of New Zealand.
- 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.
- Michael Callaghan & Enzo Cassino & Tugrul Vehbi & Benjamin Wong, 2019. "Opening the toolbox: how does the Reserve Bank analyse the world?," Reserve Bank of New Zealand Bulletin, Reserve Bank of New Zealand, vol. 82, pages 1-14, April.
- Zhang, Bo & Nguyen, Bao H., 2020. "Real-time forecasting of the Australian macroeconomy using Bayesian VARs," Working Papers 2020-12, University of Tasmania, Tasmanian School of Business and Economics.
- Wang, Shixuan & Syntetos, Aris A. & Liu, Ying & Di Cairano-Gilfedder, Carla & Naim, Mohamed M., 2023. "Improving automotive garage operations by categorical forecasts using a large number of variables," European Journal of Operational Research, Elsevier, vol. 306(2), pages 893-908.
- Jack Fosten, 2017.
"Model selection with estimated factors and idiosyncratic components,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(6), pages 1087-1106, September.
- Jack Fosten, 2016. "Model selection with factors and variables," University of East Anglia School of Economics Working Paper Series 2016-07, School of Economics, University of East Anglia, Norwich, UK..
- Duo Qin & Sophie van Huellen & Qing Chao Wang & Thanos Moraitis, 2022. "Algorithmic Modelling of Financial Conditions for Macro Predictive Purposes: Pilot Application to USA Data," Econometrics, MDPI, vol. 10(2), pages 1-22, April.
- Čižmešija Mirjana & Lukač Zrinka & Novoselec Tomislav, 2019. "Nonlinear optimisation approach to proposing novel Croatian Industrial Confidence Indicator," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 5(2), pages 17-26, December.
- Jiahan Li & Ilias Tsiakas & Wei Wang, 2015.
"Predicting Exchange Rates Out of Sample: Can Economic Fundamentals Beat the Random Walk?,"
Journal of Financial Econometrics, Oxford University Press, vol. 13(2), pages 293-341.
- Jiahan Li & Ilias Tsiakas & Wei Wang, 2014. "Predicting Exchange Rates Out of Sample: Can Economic Fundamentals Beat the Random Walk?," Working Paper series 05_14, Rimini Centre for Economic Analysis.
- Duo Qin & Qingchao Wang, 2016. "Predictive Macro-Impacts of PLS-based Financial Conditions Indices: An Application to the USA," Working Papers 201, Department of Economics, SOAS University of London, UK.