1. On the effectiveness of the European Central Bank’s conventional and unconventional policies under uncertainty. (2021). Pfarrhofer, Michael ; Hauzenberger, Niko ; Stelzer, Anna.
   In: Journal of Economic Behavior & Organization.
   RePEc:eee:jeborg:v:191:y:2021:i:c:p:822-845.

   Full description at Econpapers || Download paper

1. Andrea Carriero, Todd Clark, and Massimiliano Marcellino. Large vector autoregressions with stochastic volatility and flexible priors. Journal of Econometrics, 212(1):137–154, 2019.

2. Andrea Carriero, Todd E Clark, and Massimiliano Giuseppe Marcellino. Capturing macroeconomic tail risks with Bayesian vector autoregressions. Working Paper 202002R, Federal Reserve Bank of Cleveland, 2020.
   Paper not yet in RePEc: Add citation now
   

3. Carlos M Carvalho, Nicholas G Polson, and James G Scott. The horseshoe estimator for sparse signals. Biometrika, 97(2):465–480, 2010.

4. Chang-Jin Kim and Charles R. Nelson. State-space models with regime switching: Classical and Gibbs-sampling approaches with applications. MIT Press, Cambridge and London, 1999.

5. Chris K Carter and Robert Kohn. On Gibbs sampling for state space models. Biometrika, 81(3): 541–553, 1994.
   Paper not yet in RePEc: Add citation now
   

6. Christopher A Sims and Tao Zha. Were there regime switches in US monetary policy? American Economic Review, 96(1):54–81, 2006. James H Stock and Mark Watson. Dynamic factor models. In Michael P. Clements and David F.

7. Constantino Hevia, Martin Gonzalez-Rozada, Martin Sola, and Fabio Spagnolo. Estimating and forecasting the yield curve using a Markov switching dynamic Nelson and Siegel model. Journal of Applied Econometrics, 30(6):987–1009, 2015.

8. Enes Makalic and Daniel F Schmidt. A simple sampler for the horseshoe estimator. IEEE Signal Processing Letters, 23(1):179–182, 2015.
   Paper not yet in RePEc: Add citation now
   

9. Francis X Diebold and Canlin Li. Forecasting the term structure of government bond yields. Journal of Econometrics, 130(2):337–364, 2006.

10. Francis X Diebold, Canlin Li, and Vivian Z Yue. Global yield curve dynamics and interactions: A dynamic Nelson–Siegel approach. Journal of Econometrics, 146(2):351–363, 2008.

11. Gary Koop, Roberto Leon-Gonzalez, and Rodney W Strachan. On the evolution of the monetary policy transmission mechanism. Journal of Economic Dynamics and Control, 33(4):997–1017, 2009. Dimitris Korobilis. High-dimensional macroeconomic forecasting using message passing algorithms.

12. Giorgio Primiceri. Time varying structural autoregressions and monetary policy. Review of Economic Studies, 72(3):821–852, 2005.

13. Giovanni Caggiano, Efrem Castelnuovo, and Giovanni Pellegrino. Estimating the real effects of uncertainty shocks at the zero lower bound. European Economic Review, 100:257–272, 2017.

14. Gregor Kastner and Sylvia Frühwirth-Schnatter. Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models. Computational Statistics & Data Analysis, 76:408–423, 2014.

15. Hendry, editors, The Oxford Handbook of Economic Forecasting, pages 35–60. Oxford University Press, 2011. Appendices A Technical appendix A.1 Sampling the state innovation variances For sampling the state innovation variances based on Eq. (1), we let ηji,t denote the shock to the ith coefficient in γ̃t with respect to the jth equation. The posterior of the state innovation variances is a generalized inverse Gaussian (GIG) distribution:7 ωji|$ji, ϑj ∼ GIG 1 − T , T X t=1 η2 ji,t, $jiϑj ! . A.2 Posterior for the horseshoe prior Our specification of the horseshoe prior on Λj, γj and the square root of ωj in Section 2.4 for a generic parameter bi for i = 1, . . . , K is: bi|ci, d ∼ N(0, c2 i d2 ), ci ∼ C+ (0, 1), d ∼ C+ (0, 1).

16. John Geweke and Gianni Amisano. Comparing and evaluating Bayesian predictive distributions of asset returns. International Journal of Forecasting, 26(2):216–230, 2010.

17. John Geweke and Guofu Zhou. Measuring the pricing error of the arbitrage pricing theory. Review of Financial Studies, 9(2):557–587, 1996.

18. John M Maheu and Yong Song. An efficient Bayesian approach to multiple structural change in multivariate time series. Journal of Applied Econometrics, 33(2):251–270, 2018.

19. Joshua CC Chan, Eric Eisenstat, and Rodney Strachan. Reducing the state space dimension in a large TVP-VAR. Journal of Econometrics, 218(1):105–118, 2020.

20. Martin Kliem, Alexander Kriwoluzky, and Samad Sarferaz. On the low-frequency relationship between public deficits and inflation. Journal of Applied Econometrics, 31(3):566–583, 2016.

21. Niko Hauzenberger, Florian Huber, Gary Koop, and Luca Onorante. Fast and flexible Bayesian inference in time-varying parameter regression models. arXiv preprint, 1910.10779, 2019.

22. Niko Hauzenberger. Flexible mixture priors for time-varying parameter models. arXiv preprint, 2006.10088, 2020.

23. Omar Aguilar and Mike West. Bayesian dynamic factor models and portfolio allocation. Journal of Business & Economic Statistics, 18(3):338–357, 2000.

24. Paolo Giordani and Robert Kohn. Efficient Bayesian inference for multiple change-point and mixture innovation models. Journal of Business & Economic Statistics, 26(1):66–77, 2008.

25. Patrick A Adams, Tobias Adrian, Nina Boyarchenko, and Domenico Giannone. Forecasting macroeconomic risks. International Journal of Forecasting, in press, published online 6 Feb, 2021.

26. Refet S Gürkaynak, Brian Sack, and Jonathan H Wright. The US treasury yield curve: 1961 to the present. Journal of Monetary Economics, 54(8):2291–2304, 2007.
    Paper not yet in RePEc: Add citation now
    
27. Richard Gerlach, Chris Carter, and Robert Kohn. Efficient Bayesian inference for dynamic mixture models. Journal of the American Statistical Association, 95(451):819–828, 2000.
    Paper not yet in RePEc: Add citation now
    

28. Sylvia Frühwirth-Schnatter and Helga Wagner. Stochastic model specification search for Gaussian and partial non-Gaussian state space models. Journal of Econometrics, 154(1):85–100, 2010.

29. Sylvia Frühwirth-Schnatter. Data augmentation and dynamic linear models. Journal of Time Series Analysis, 15(2):183–202, 1994.
    Paper not yet in RePEc: Add citation now
    

30. Thomas Dangl and Michael Halling. Predictive regressions with time-varying coefficients. Journal of Financial Economics, 106:157–181, 2012.

31. Thomas J Sargent and Paolo Surico. Two illustrations of the quantity theory of money: Breakdowns and revivals. American Economic Review, 101(1):109–28, 2011.

32. Timothy Cogley and Thomas J. Sargent. Drifts and volatilities: Monetary policies and outcomes in the post WWII US. Review of Economic Dynamics, 8(2):262 – 302, 2005.

33. Tobias Adrian, Nina Boyarchenko, and Domenico Giannone. Vulnerable growth. American Economic Review, 109(4):1263–89, 2019.

34. Trevor Hastie and Robert Tibshirani. Varying-coefficient models. Journal of the Royal Statistical Society: Series B (Methodological), 55(4):757–779, 1993.
    Paper not yet in RePEc: Add citation now
    

1. Sparse time-varying parameter VECMs with an application to modeling electricity prices. (2023). Rossini, Luca ; Pfarrhofer, Michael ; Hauzenberger, Niko.
   In: Papers.
   RePEc:arx:papers:2011.04577.

   Full description at Econpapers || Download paper

2. Dynamic Shrinkage Priors for Large Time-varying Parameter Regressions using Scalable Markov Chain Monte Carlo Methods. (2023). Koop, Gary ; Huber, Florian ; Hauzenberger, Niko.
   In: Papers.
   RePEc:arx:papers:2005.03906.

   Full description at Econpapers || Download paper

3. General Bayesian time-varying parameter VARs for modeling government bond yields. (2022). Pfarrhofer, Michael ; Huber, Florian ; Hauzenberger, Niko ; Fischer, Manfred.
   In: Working Papers in Regional Science.
   RePEc:wiw:wus046:8006.

   Full description at Econpapers || Download paper

4. Global Stagflation. (2022). Ohnsorge, Franziska ; Kose, Ayhan ; Ha, Jongrim.
   In: MPRA Paper.
   RePEc:pra:mprapa:113306.

   Full description at Econpapers || Download paper

5. A Unified Framework to Estimate Macroeconomic Stars. (2022). Zaman, Saeed.
   In: Working Papers.
   RePEc:fip:fedcwq:93166.

   Full description at Econpapers || Download paper

6. Sparse change‐point VAR models. (2021). Dufays, Arnaud ; Li, Zhuo ; Song, Yong.
   In: Journal of Applied Econometrics.
   RePEc:wly:japmet:v:36:y:2021:i:6:p:703-727.

   Full description at Econpapers || Download paper

7. Combining shrinkage and sparsity in conjugate vector autoregressive models. (2021). onorante, luca ; Huber, Florian ; Hauzenberger, Niko.
   In: Journal of Applied Econometrics.
   RePEc:wly:japmet:v:36:y:2021:i:3:p:304-327.

   Full description at Econpapers || Download paper

8. Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them. (2021). Rossi, Barbara.
   In: Economics Working Papers.
   RePEc:upf:upfgen:1711.

   Full description at Econpapers || Download paper

9. Inflation During the Pandemic: What Happened? What is Next?. (2021). Ohnsorge, Franziska ; Kose, Ayhan ; Ha, Jongrim.
   In: MPRA Paper.
   RePEc:pra:mprapa:108677.

   Full description at Econpapers || Download paper

10. Inflation During the Pandemic: What Happened? What is Next?. (2021). Ohnsorge, Franziska ; Kose, Ayhan ; Ha, Jongrim.
    In: Koç University-TUSIAD Economic Research Forum Working Papers.
    RePEc:koc:wpaper:2108.

    Full description at Econpapers || Download paper

11. Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs. (2021). Pfarrhofer, Michael ; onorante, luca ; Koop, Gary ; Huber, Florian ; Schreiner, Josef ; Florian, Huber.
    In: JRC Working Papers in Economics and Finance.
    RePEc:jrs:wpaper:202101.

    Full description at Econpapers || Download paper

12. Structural Panel Bayesian VAR with Multivariate Time-Varying Volatility to Jointly Deal with Structural Changes, Policy Regime Shifts, and Endogeneity Issues. (2021). Pacifico, Antonio.
    In: Econometrics.
    RePEc:gam:jecnmx:v:9:y:2021:i:2:p:20-:d:548164.

    Full description at Econpapers || Download paper

13. Macroeconomic Forecasting and Variable Ordering in Multivariate Stochastic Volatility Models. (2021). Shin, Minchul ; Rubio-Ramirez, Juan F ; Arias, Jonas E.
    In: Working Papers.
    RePEc:fip:fedpwp:92355.

    Full description at Econpapers || Download paper

14. Forecasting with Shadow-Rate VARs. (2021). Mertens, Elmar ; Marcellino, Massimiliano ; Clark, Todd ; Carriero, Andrea.
    In: Working Papers.
    RePEc:fip:fedcwq:91780.

    Full description at Econpapers || Download paper

15. Addressing COVID-19 Outliers in BVARs with Stochastic Volatility. (2021). Mertens, Elmar ; Marcellino, Massimiliano ; Clark, Todd ; Carriero, Andrea.
    In: Working Papers.
    RePEc:fip:fedcwq:89757.

    Full description at Econpapers || Download paper

16. Dividend Momentum and Stock Return Predictability: A Bayesian Approach. (2021). Rubio-Ramirez, Juan F ; Petrella, Ivan ; Antolin-Diaz, Juan.
    In: FRB Atlanta Working Paper.
    RePEc:fip:fedawp:93480.

    Full description at Econpapers || Download paper

17. Dividend Momentum and Stock Return Predictability: A Bayesian Approach. (2021). Rubio-Ramirez, Juan F ; Petrella, Ivan ; Antolin-Diaz, Juan.
    In: Working Papers.
    RePEc:fda:fdaddt:2021-14.

    Full description at Econpapers || Download paper

18. Minnesota-type adaptive hierarchical priors for large Bayesian VARs. (2021). Chan, Joshua.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:37:y:2021:i:3:p:1212-1226.

    Full description at Econpapers || Download paper

19. On the China factor in the world oil market: A regime switching approach11We thank Hilde Bjørnland, Tatsuyoshi Okimoto, Ippei Fujiwara, Knut Aastveit, Leif Anders Thorsrud, Francesco Ravazzolo, Renee Fry-McKibbin, Warwick McKibbin and members of the workshop on Energy Economics hosted by the Free University of Bozen-Bolzano for their comments in the development of this research.. (2021). Cross, Jamie ; Hou, Chenghan ; Nguyen, Bao H.
    In: Energy Economics.
    RePEc:eee:eneeco:v:95:y:2021:i:c:s0140988321000244.

    Full description at Econpapers || Download paper

20. Flexible Mixture Priors for Large Time-varying Parameter Models. (2021). Hauzenberger, Niko.
    In: Econometrics and Statistics.
    RePEc:eee:ecosta:v:20:y:2021:i:c:p:87-108.

    Full description at Econpapers || Download paper

21. Simulation smoothing for nowcasting with large mixed-frequency VARs. (2021). Ankargren, Sebastian ; Joneus, Paulina.
    In: Econometrics and Statistics.
    RePEc:eee:ecosta:v:19:y:2021:i:c:p:97-113.

    Full description at Econpapers || Download paper

22. Using time-varying volatility for identification in Vector Autoregressions: An application to endogenous uncertainty. (2021). Marcellino, Massimiliano ; Clark, Todd ; Carriero, Andrea.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:225:y:2021:i:1:p:47-73.

    Full description at Econpapers || Download paper

23. Boosting high dimensional predictive regressions with time varying parameters. (2021). Ng, Serena ; Yousuf, Kashif.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:224:y:2021:i:1:p:60-87.

    Full description at Econpapers || Download paper

24. Fan charts 2.0: flexible forecast distributions with expert judgement. (2021). Sokol, Andrej.
    In: Working Paper Series.
    RePEc:ecb:ecbwps:20212624.

    Full description at Econpapers || Download paper

25. Combining Bayesian VARs with survey density forecasts: does it pay off?. (2021). Ravazzolo, Francesco ; Paredes, Joan ; Brenna, Federica ; Banbura, Marta ; Babura, Marta.
    In: Working Paper Series.
    RePEc:ecb:ecbwps:20212543.

    Full description at Econpapers || Download paper

26. Do inflation expectations improve model-based inflation Forecasts?. (2021). Menz, Jan-Oliver ; Leiva-Leon, Danilo ; Banbura, Marta ; Babura, Marta.
    In: Working Papers.
    RePEc:bde:wpaper:2138.

    Full description at Econpapers || Download paper

27. General Bayesian time-varying parameter VARs for predicting government bond yields. (2021). Pfarrhofer, Michael ; Huber, Florian ; Fischer, Manfred ; Hauzenberger, Niko.
    In: Papers.
    RePEc:arx:papers:2102.13393.

    Full description at Econpapers || Download paper

28. Deep Distributional Time Series Models and the Probabilistic Forecasting of Intraday Electricity Prices. (2021). Klein, Nadja ; Smith, Michael Stanley ; Nott, David J.
    In: Papers.
    RePEc:arx:papers:2010.01844.

    Full description at Econpapers || Download paper

29. Inference in Bayesian Additive Vector Autoregressive Tree Models. (2021). Rossini, Luca ; Huber, Florian.
    In: Papers.
    RePEc:arx:papers:2006.16333.

    Full description at Econpapers || Download paper

30. Sparse Bayesian vector autoregressions in huge dimensions. (2020). Kastner, Gregor ; Huber, Florian.
    In: Journal of Forecasting.
    RePEc:wly:jforec:v:39:y:2020:i:7:p:1142-1165.

    Full description at Econpapers || Download paper

31. Composite likelihood methods for large Bayesian VARs with stochastic volatility. (2020). Koop, Gary ; Eisenstat, Eric ; Chan, Joshua ; Hou, Chenghan.
    In: Journal of Applied Econometrics.
    RePEc:wly:japmet:v:35:y:2020:i:6:p:692-711.

    Full description at Econpapers || Download paper

32. Reconciled Estimates of Monthly GDP in the US. (2020). Poon, Aubrey ; Mitchell, James ; McIntyre, Stuart ; Koop, Gary.
    In: Economic Statistics Centre of Excellence (ESCoE) Discussion Papers.
    RePEc:nsr:escoed:escoe-dp-2020-16.

    Full description at Econpapers || Download paper

33. Energy Markets and Global Economic Conditions. (2020). Korobilis, Dimitris ; Baumeister, Christiane ; Lee, Thomas K.
    In: NBER Working Papers.
    RePEc:nbr:nberwo:27001.

    Full description at Econpapers || Download paper

34. Energy Markets and Global Economic Conditions. (2020). Korobilis, Dimitris ; Baumeister, Christiane ; Lee, Thomas K.
    In: Working Papers.
    RePEc:gla:glaewp:2020_08.

    Full description at Econpapers || Download paper

35. Triple the Gamma—A Unifying Shrinkage Prior for Variance and Variable Selection in Sparse State Space and TVP Models. (2020). Fruhwirth-Schnatter, Sylvia ; Knaus, Peter ; Cadonna, Annalisa.
    In: Econometrics.
    RePEc:gam:jecnmx:v:8:y:2020:i:2:p:20-:d:360596.

    Full description at Econpapers || Download paper

36. Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach. (2020). Zaman, Saeed ; Knotek, Edward.
    In: Working Papers.
    RePEc:fip:fedcwq:88961.

    Full description at Econpapers || Download paper

37. Macroeconomic forecasting with large Bayesian VARs: Global-local priors and the illusion of sparsity. (2020). Poon, Aubrey ; Cross, Jamie ; Hou, Chenghan.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:36:y:2020:i:3:p:899-915.

    Full description at Econpapers || Download paper

38. The heterogeneous impact of monetary policy on the US labor market. (2020). Zoerner, Thomas ; Zens, Gregor ; Boeck, Maximilian ; Zorner, Thomas O ; Bock, Maximilian.
    In: Journal of Economic Dynamics and Control.
    RePEc:eee:dyncon:v:119:y:2020:i:c:s0165188920301573.

    Full description at Econpapers || Download paper

39. Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them. (2020). Rossi, Barbara.
    In: CEPR Discussion Papers.
    RePEc:cpr:ceprdp:14472.

    Full description at Econpapers || Download paper

40. Energy Markets and Global Economic Conditions. (2020). Korobilis, Dimitris ; Baumeister, Christiane ; Lee, Thomas K.
    In: CESifo Working Paper Series.
    RePEc:ces:ceswps:_8282.

    Full description at Econpapers || Download paper

41. Large Time-Varying Volatility Models for Electricity Prices. (2020). Rossini, Luca ; Ravazzolo, Francesco ; Gianfreda, Angelica.
    In: Working Papers.
    RePEc:bny:wpaper:0088.

    Full description at Econpapers || Download paper

42. Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them. (2020). Rossi, Barbara.
    In: Working Papers.
    RePEc:bge:wpaper:1162.

    Full description at Econpapers || Download paper

43. The economic drivers of volatility and uncertainty. (2020). Marcellino, Massimiliano ; Corsello, Francesco ; Carriero, Andrea.
    In: Temi di discussione (Economic working papers).
    RePEc:bdi:wptemi:td_1285_20.

    Full description at Econpapers || Download paper

44. Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs. (2020). Pfarrhofer, Michael ; onorante, luca ; Koop, Gary ; Huber, Florian ; Schreiner, Josef.
    In: Papers.
    RePEc:arx:papers:2008.12706.

    Full description at Econpapers || Download paper

45. Flexible Mixture Priors for Large Time-varying Parameter Models. (2020). Hauzenberger, Niko.
    In: Papers.
    RePEc:arx:papers:2006.10088.

    Full description at Econpapers || Download paper

46. Minnesota-type adaptive hierarchical priors for large Bayesian VARs. (2019). Chan, Joshua.
    In: CAMA Working Papers.
    RePEc:een:camaaa:2019-61.

    Full description at Econpapers || Download paper

47. Bayesian estimation of large dimensional time varying VARs using copulas. (2019). Tsionas, Mike ; Trapani, Lorenzo ; Izzeldin, Marwan.
    In: Papers.
    RePEc:arx:papers:1912.12527.

    Full description at Econpapers || Download paper

48. Triple the gamma -- A unifying shrinkage prior for variance and variable selection in sparse state space and TVP models. (2019). Fruhwirth-Schnatter, Sylvia ; Knaus, Peter ; Cadonna, Annalisa.
    In: Papers.
    RePEc:arx:papers:1912.03100.

    Full description at Econpapers || Download paper

49. Boosting High Dimensional Predictive Regressions with Time Varying Parameters. (2019). Ng, Serena ; Yousuf, Kashif.
    In: Papers.
    RePEc:arx:papers:1910.03109.

    Full description at Econpapers || Download paper

50. Simulation smoothing for nowcasting with large mixed-frequency VARs. (2019). Ankargren, Sebastian ; Jon, Paulina.
    In: Papers.
    RePEc:arx:papers:1907.01075.

    Full description at Econpapers || Download paper

Report date: 2025-09-20 20:16:57 || Missing content? Let us know