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Real-Time Forecasting with a Mixed-Frequency VAR. (2013). Song, Dongho ; Schorfheide, Frank.
In: NBER Working Papers.
RePEc:nbr:nberwo:19712.

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  1. .

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  2. Short-Run Forecasting of Core Inflation in Ukraine: a Combined ARMA Approach. (2019). Krukovets, Dmytro ; Verchenko, Olesia .
    In: Visnyk of the National Bank of Ukraine.
    RePEc:ukb:journl:y:2019:i:248:p:11-20.

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  3. Mixed frequency models with MA components. (2018). Stevanovic, Dalibor ; Marcellino, Massimiliano ; Foroni, Claudia.
    In: Discussion Papers.
    RePEc:zbw:bubdps:022018.

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  4. Fitting and forecasting yield curves with a mixed-frequency affine model: Evidence from China. (2018). Shang, Yuhuang ; Zheng, Tingguo .
    In: Economic Modelling.
    RePEc:eee:ecmode:v:68:y:2018:i:c:p:145-154.

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  5. Structural analysis with mixed-frequency data: A MIDAS-SVAR model of US capital flows. (2018). Rossi, Eduardo ; Missale, Alessandro ; Bastianin, Andrea ; Bacchiocchi, Emanuele.
    In: Papers.
    RePEc:arx:papers:1802.00793.

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  6. Should forecasters use real-time data to evaluate leading indicator models for GDP prediction? German evidence. (2017). Scheufele, Rolf ; Heinisch, Katja.
    In: IWH Discussion Papers.
    RePEc:zbw:iwhdps:52017.

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  7. Mixed-frequency macro-financial spillovers. (2017). Yilmaz, Kamil ; Hallam, Mark ; cotter, john.
    In: Working Papers.
    RePEc:ucd:wpaper:201704.

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  8. Time-varying mixed frequency forecasting: A real-time experiment. (2017). Neuwirth, Stefan.
    In: KOF Working papers.
    RePEc:kof:wpskof:17-430.

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  9. Mixed-Frequency Macro-Financial Spillovers. (2017). Yilmaz, Kamil ; Hallam, Mark ; cotter, john.
    In: Koç University-TUSIAD Economic Research Forum Working Papers.
    RePEc:koc:wpaper:1704.

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  10. A real-time analysis on the importance of hard and soft data for nowcasting German GDP. (2016). Heinisch, Katja.
    In: Annual Conference 2016 (Augsburg): Demographic Change.
    RePEc:zbw:vfsc16:145864.

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  11. Forecasting euro area recessions in real-time. (2016). Pirschel, Inske.
    In: Kiel Working Papers.
    RePEc:zbw:ifwkwp:2020.

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  12. Forecasting Czech GDP Using Mixed-Frequency Data Models. (2016). Rusnák, Marek ; Havrlant, David ; Franta, Michal.
    In: Journal of Business Cycle Research.
    RePEc:spr:jbuscr:v:12:y:2016:i:2:d:10.1007_s41549-016-0008-z.

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  13. The Beveridge–Nelson decomposition of mixed-frequency series. (2016). Murasawa, Yasutomo.
    In: Empirical Economics.
    RePEc:spr:empeco:v:51:y:2016:i:4:d:10.1007_s00181-015-1061-5.

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  14. The Impact of Monetary Policy on Inequality in the UK. An Empirical Analysis. (2016). Theophilopoulou, Angeliki ; mumtaz, haroon.
    In: Working Papers.
    RePEc:qmw:qmwecw:wp783.

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  15. Forecasting US GNP Growth: The Role of Uncertainty. (2016). Wohar, Mark ; GUPTA, RANGAN ; Bekiros, Stelios ; Segnon, Mawuli.
    In: Working Papers.
    RePEc:pre:wpaper:201667.

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  16. Dynamic Analyses Using VAR Model with Mixed Frequency Data through Observable Representation. (2016). Kim, Yun-Yeong.
    In: Korean Economic Review.
    RePEc:kea:keappr:ker-20160630-32-1-03.

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  17. Forecasting U.S. Recessions and Economic Activity. (2016). Stevanovic, Dalibor ; Kotchoni, Rachidi.
    In: Working Papers.
    RePEc:hal:wpaper:hal-04141569.

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  18. Forecasting Economic Activity with Mixed Frequency Bayesian VARs. (2016). Brave, Scott ; Justiniano, Alejandro ; Butters, Andrew R.
    In: Working Paper Series.
    RePEc:fip:fedhwp:wp-2016-05.

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  19. Macroeconomics and the reality of mixed frequency data. (2016). Ghysels, Eric.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:193:y:2016:i:2:p:294-314.

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  20. The BEAR toolbox. (2016). van Roye, Björn ; Legrand, Romain ; Dieppe, Alistair.
    In: Working Paper Series.
    RePEc:ecb:ecbwps:20161934.

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  21. Forecasting U.S. Recessions and Economic Activity. (2016). Stevanovic, Dalibor ; Kotchoni, Rachidi.
    In: EconomiX Working Papers.
    RePEc:drm:wpaper:2016-40.

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  22. Forecasting U.S. Recessions and Economic Activity. (2016). Stevanovic, Dalibor ; Kotchoni, Rachidi.
    In: CIRANO Working Papers.
    RePEc:cir:cirwor:2016s-36.

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  23. Comparing several methods to compute joint prediction regions for path forecasts generated by vector autoregressions. (2015). Bruder, Stefan.
    In: ECON - Working Papers.
    RePEc:zur:econwp:181.

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  24. Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts. (2015). Ravazzolo, Francesco ; Clark, Todd ; Kruger, Fabian.
    In: Annual Conference 2015 (Muenster): Economic Development - Theory and Policy.
    RePEc:zbw:vfsc15:113077.

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  25. Forecasting Euro Area Recessions in real-time with a mixed-frequency Bayesian VAR. (2015). Pirschel, Inske.
    In: Annual Conference 2015 (Muenster): Economic Development - Theory and Policy.
    RePEc:zbw:vfsc15:113031.

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  26. Testing for Granger causality in large mixed-frequency VARs. (2015). Smeekes, Stephan ; Hecq, Alain ; Götz, Thomas ; Gotz, Thomas B.
    In: Discussion Papers.
    RePEc:zbw:bubdps:452015.

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  27. Testing for Granger Causality in Large Mixed-Frequency VARs. (2015). Smeekes, Stephan ; Hecq, Alain ; Götz, Thomas.
    In: Research Memorandum.
    RePEc:unm:umagsb:2015036.

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  28. Effects of Monetary Policy Shocks on UK Regional Activity: A Constrained MFVAR Approach. (2015). Mandalinci, Zeyyad.
    In: Working Papers.
    RePEc:qmw:qmwecw:wp758.

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  29. Monetary Policy and Inequality in the UK. (2015). Theophilopoulou, Angeliki ; mumtaz, haroon.
    In: Working Papers.
    RePEc:qmw:qmwecw:wp738.

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  30. Point and Density Forecasts Using an Unrestricted Mixed-Frequency VAR Model. (2015). Barsoum, Fady.
    In: Working Paper Series of the Department of Economics, University of Konstanz.
    RePEc:knz:dpteco:1519.

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  31. Euro area financial shocks and economic activity in The Netherlands. (2015). Broer, Peter ; Antony, Jürgen.
    In: Empirica.
    RePEc:kap:empiri:v:42:y:2015:i:3:p:571-595.

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  32. Real-Time Forecasting with a Large, Mixed Frequency, Bayesian VAR. (2015). Sekhposyan, Tatevik ; Owyang, Michael ; McCracken, Michael.
    In: Working Papers.
    RePEc:fip:fedlwp:2015-030.

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  33. Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts. (2015). Ravazzolo, Francesco ; Clark, Todd ; Krueger, Fabian .
    In: Working Papers (Old Series).
    RePEc:fip:fedcwp:1439.

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  34. Do high-frequency financial data help forecast oil prices? The MIDAS touch at work. (2015). Kilian, Lutz ; Guérin, Pierre ; Baumeister, Christiane.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:31:y:2015:i:2:p:238-252.

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  35. Not Just Another Mixed Frequency Paper. (2015). Fasolo, Angelo ; Alves, Sergio ; Lago, Sergio Afonso .
    In: Working Papers Series.
    RePEc:bcb:wpaper:400.

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  36. Real-Time Nowcasting Nominal GDP Under Structural Break. (2014). Leiva-Leon, Danilo ; Chauvet, Marcelle ; Barnett, William.
    In: MPRA Paper.
    RePEc:pra:mprapa:53699.

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  37. Identifying Long-Run Risks: A Bayesian Mixed-Frequency Approach. (2014). Yaron, Amir ; Song, Dongho ; Schorfheide, Frank.
    In: NBER Working Papers.
    RePEc:nbr:nberwo:20303.

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  38. Forecasting Chinese GDP Growth with Mixed Frequency Data. (2014). Mikosch, Heiner ; Zhang, Ying.
    In: KOF Working papers.
    RePEc:kof:wpskof:14-359.

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  39. Nowcasting U.S. Headline and Core Inflation. (2014). Zaman, Saeed ; Knotek, Edward.
    In: Working Papers (Old Series).
    RePEc:fip:fedcwp:1403.

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  40. Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections. (2014). Lenza, Michele ; Giannone, Domenico ; Banbura, Marta ; Babura, Marta.
    In: Working Paper Series.
    RePEc:ecb:ecbwps:20141733.

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  41. Markov-Switching Mixed-Frequency VAR Models. (2014). Marcellino, Massimiliano ; Guérin, Pierre ; Foroni, Claudia.
    In: CEPR Discussion Papers.
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  42. Forecasting Czech GDP Using Mixed-Frequency Data Models. (2014). Rusnák, Marek ; Havrlant, David ; Franta, Michal.
    In: Working Papers.
    RePEc:cnb:wpaper:2014/08.

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  43. Estimating Dynamic Equilibrium Models Using Mixed Frequency Macro and Financial Data. (2014). van der Wel, Michel ; Posch, Olaf ; Christensen, Bent Jesper.
    In: CESifo Working Paper Series.
    RePEc:ces:ceswps:_5030.

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  44. Mixed frequency structural VARs. (2014). Marcellino, Massimiliano ; Foroni, Claudia.
    In: Working Paper.
    RePEc:bno:worpap:2014_01.

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  45. Do High-Frequency Financial Data Help Forecast Oil Prices? The MIDAS Touch at Work. (2014). Kilian, Lutz ; Guérin, Pierre ; Baumeister, Christiane ; Guerin, Pierre .
    In: Staff Working Papers.
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  46. Real-Time Nowcasting Nominal GDP Under Structural Break. (2013). Leiva-Leon, Danilo ; Barnett, William ; Leiva-Leonx, Danilo ; Chauvetz, Marcelle .
    In: WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS.
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  47. Identifying long-run risks: a bayesian mixed-frequency approach. (2013). Song, Dongho ; Schorfheide, Frank ; Yaron, Amir.
    In: Working Papers.
    RePEc:fip:fedpwp:13-39.

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  48. A 14-Variable Mixed-Frequency VAR Model. (2013). Beauchemin, Kenneth.
    In: Staff Report.
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  49. A survey of econometric methods for mixed-frequency data. (2013). Marcellino, Massimiliano ; Foroni, Claudia.
    In: Economics Working Papers.
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  50. Do High-Frequency Financial Data Help Forecast Oil Prices? The MIDAS Touch at Work. (2013). Kilian, Lutz ; Guérin, Pierre ; Baumeister, Christiane.
    In: CEPR Discussion Papers.
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  51. Real-Time Nowcasting with a Bayesian Mixed Frequency Model with Stochastic Volatility. (2013). Marcellino, Massimiliano ; Clark, Todd ; Carriero, Andrea.
    In: CEPR Discussion Papers.
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  52. Nowcasting Czech GDP in Real Time. (2013). Rusnák, Marek.
    In: Working Papers.
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  53. Modeling Multivariate Data Revisions. (2013). van Norden, Simon ; Sturm, Jan-Egbert ; Sarferaz, Samad ; Jacobs, Jan ; Jan P. A. M. Jacobs, .
    In: CIRANO Working Papers.
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  54. A survey of econometric methods for mixed-frequency data. (2013). Marcellino, Massimiliano ; Foroni, Claudia.
    In: Working Paper.
    RePEc:bno:worpap:2013_06.

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  55. What Central Bankers Need to Know about Forecasting Oil Prices. (2013). Kilian, Lutz ; Baumeister, Christiane.
    In: Staff Working Papers.
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  56. Should macroeconomic forecasters use daily financial data and how?. (2012). Kourtellos, Andros ; Ghysels, Eric ; Andreou, Elena.
    In: 2012 Meeting Papers.
    RePEc:red:sed012:1196.

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  57. Real-time nowcasting with a Bayesian mixed frequency model with stochastic volatility. (2012). Marcellino, Massimiliano ; Clark, Todd ; Carriero, Andrea.
    In: Working Papers (Old Series).
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  58. What Central Bankers Need to Know about Forecasting Oil Prices. (2012). Kilian, Lutz ; Baumeister, Christiane.
    In: CEPR Discussion Papers.
    RePEc:cpr:ceprdp:9118.

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  7. Conditional on Z0:T the MF-VAR reduces to a standard linear Gaussian VAR with a conjugate prior. The reader is referred to Section 2 of the handbook chapter by Del Negro and Schorfheide (2011) for a detailed discussion of posterior inference for such a VAR.
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  29. Some of the vintages of PCE and INVFIX extracted from ALFRED were incomplete. The recent vintages of PCE and INVFIX from ALFRED do not include data prior to 1990 or 1995 (depending on the vintages). However, the most recent data for PCE and INVFIX can be obtained from BEA or NIPA, say, from 1/1/1967 to 1/1/2012. Let us consider PCE for We augment the state vector zt in (2) and (7) by an additional lag of xt to ensure that st is a subvector of the resulting ˜ zt. This augmentation requires a straightforward modification of the state-transition equation (2) and the measurement equations (7). Online Appendix A-7
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  31. Waggoner, D. F., and T. Zha (1999): “Conditional Forecasts in Dynamic Multivariate Models,” Review of Economics and Statistics, 81(4), 639–651. Online Appendix A-1 Online Appendix for Real-Time Forecasting with a Mixed-Frequency VAR Frank Schorfheide and Dongho Song Section A of this appendix provides details of the implementation of the Bayesian computations for the MF-VAR presented in the main text. Section B discusses the construction of the real-time data set. Finally, Section C of this appendix provides tables and figures with additional empirical results. References to equations, tables, and figures without an A, B, or C prefix refer to equations, tables, and figures in the main text. A Implementation Details Recall from the exposition in the main text (see equation (9)) that the Bayesian computations are implemented with a Gibbs sampler that iterates over the conditional distributions p(Φ, Σ|Z0:T , Y−p+1:T ) and p(Z0:T |Φ, Σ, Y−p+1:T ).

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  18. Exploring the core factors and its dynamic effects on oil price: An application on path analysis and BVAR-TVP model. (2011). Guo, Ju-E., ; Wang, Shou-Yang ; Meng, Lei ; Chai, Jian.
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  20. Forecasting economic growth in the euro area during the Great Moderation and the Great Recession. (2011). Maier, Philipp ; Lombardi, Marco.
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  21. Understanding and forecasting aggregate and disaggregate price dynamics. (2011). D'Agostino, Antonello ; Bermingham, Colin ; Dagostino, Antonello .
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  22. Bayesian VARs: Specification Choices and Forecast Accuracy. (2011). Marcellino, Massimiliano ; Clark, Todd ; Carriero, Andrea.
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  24. The Irish Macroeconomic Response to an External Shock with an Application to Stress Testing. (2011). Conefrey, Thomas ; Birmingham, Colin .
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  25. Analysing shock transmission in a data-rich environment: a large BVAR for New Zealand. (2010). Matheson, Troy ; Bloor, Chris.
    In: Empirical Economics.
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  26. Forecasting with Medium and Large Bayesian VARs. (2010). Koop, Gary.
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  27. Business Cycles in the Euro Area. (2010). Giannone, Domenico ; Lenza, Michele ; Reichlin, Lucrezia.
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  28. A comparison of forecast performance between Federal Reserve staff forecasts, simple reduced-form models, and a DSGE model. (2010). Laforte, Jean-Philippe ; Kiley, Michael ; Edge, Rochelle M..
    In: Journal of Applied Econometrics.
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  29. Monetary policy in exceptional times. (2010). Reichlin, Lucrezia ; Pill, Huw ; Lenza, Michele.
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  30. Global commodity cycles and linkages a FAVAR approach. (2010). Schnatz, Bernd ; Osbat, Chiara ; Lombardi, Marco.
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  31. Short-term inflation projections: a Bayesian vector autoregressive approach. (2010). onorante, luca ; Momferatou, Daphne ; Lenza, Michele ; Giannone, Domenico ; Momferatu, Daphne .
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  32. Non-standard Monetary Policy Measures and Monetary Developments. (2010). Reichlin, Lucrezia ; Pill, Huw ; Lenza, Michele ; Giannone, Domenico.
    In: CEPR Discussion Papers.
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  33. Learning the Wealth of Nations. (2010). Primiceri, Giorgio ; Monge-Naranjo, Alexander ; Buera, Francisco.
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  34. Nowcasting. (2010). Reichlin, Lucrezia ; Giannone, Domenico ; Banbura, Marta.
    In: CEPR Discussion Papers.
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  35. Short-Term Inflation Projections: a Bayesian Vector Autoregressive approach. (2010). onorante, luca ; Momferatou, Daphne ; Lenza, Michele ; Giannone, Domenico.
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  36. Monetary policy in exceptional times. (2010). Reichlin, Lucrezia ; Pill, Huw ; Lenza, Michele.
    In: CEPR Discussion Papers.
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  37. Bayesian Multivariate Time Series Methods for Empirical Macroeconomics. (2009). Koop, Gary ; Korobilis, Dimitris.
    In: MPRA Paper.
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  38. Comment on How Has the Euro Changed the Monetary Transmission Mechanism?. (2009). Reichlin, Lucrezia.
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  39. Estimating US Monetary Policy Shocks Using a Factor-Augmented Vector Autoregression: An EM Algorithm Approach. (2009). Bork, Lasse.
    In: Finance Research Group Working Papers.
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  40. The local effects of monetary policy. (2009). Sekhposyan, Tatevik ; Owyang, Michael ; Francis, Neville.
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  41. A comparison of forecast performance between Federal Reserve staff forecasts, simple reduced-form models, and a DSGE model. (2009). Laforte, Jean-Philippe ; Kiley, Michael ; Edge, Rochelle M..
    In: Finance and Economics Discussion Series.
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  42. A COMPARISON OF FORECAST PERFORMANCE BETWEEN FEDERAL RESERVE STAFF FORECASTS, SIMPLE REDUCED-FORM MODELS, AND A DSGE MODEL. (2009). Kiley, Michael ; Laforte, Jean-Philippe ; Edge, Rochelle M..
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  43. Business cycles in the euro area. (2009). Giannone, Domenico ; Lenza, Michele ; Reichlin, Lucrezia.
    In: Working Paper Series.
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  44. Does the Fed Respond to Oil Price Shocks?. (2009). Lewis, Logan ; Kilian, Lutz.
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  45. Do Local Projections Solve the Bias Problem in Impulse Response Inference?. (2009). Kim, Yun Jung ; Kilian, Lutz.
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  46. Business Cycles in the Euro Area. (2009). Reichlin, Lucrezia ; Lenza, Michele ; Giannone, Domenico.
    In: CEPR Discussion Papers.
    RePEc:cpr:ceprdp:7124.

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  47. Estimating US Monetary Policy Shocks Using a Factor-Augmented Vector Autoregression: An EM Algorithm Approach. (2009). Bork, Lasse.
    In: CREATES Research Papers.
    RePEc:aah:create:2009-11.

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  48. Business Cycles in the Euro Area. (2008). Reichlin, Lucrezia ; Lenza, Michele ; Giannone, Domenico.
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  49. Phillips Curve Inflation Forecasts. (2008). Watson, Mark ; Stock, James.
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  50. Business Cycles in the euro Area. (2008). Reichlin, Lucrezia ; Lenza, Michele ; Giannone, Domenico.
    In: Working Papers ECARES.
    RePEc:eca:wpaper:2008_040.

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