IDEAS home Printed from https://ideas.repec.org/f/c/pso450.html
   My authors  Follow this author

Dongho Song

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. S. Boragan Aruoba & Francis X. Diebold & Jeremy Nalewaik & Frank Schorfheide & Dongho Song, 2011. "Improving GDP Measurement: A Forecast Combination Perspective," NBER Working Papers 17421, National Bureau of Economic Research, Inc.

    Mentioned in:

    1. Better GDP estimates
      by Economic Logician in Economic Logic on 2011-10-12 19:28:00
  2. Aruoba, S. Borağan & Diebold, Francis X. & Nalewaik, Jeremy & Schorfheide, Frank & Song, Dongho, 2016. "Improving GDP measurement: A measurement-error perspective," Journal of Econometrics, Elsevier, vol. 191(2), pages 384-397.

    Mentioned in:

    1. Is the economy growing? Depends on how you measure it : GDP vs. GDI
      by ? in FRED blog on 2022-09-01 13:00:00

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Frank Schorfheide & Dongho Song, 2020. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," PIER Working Paper Archive 20-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

    Mentioned in:

    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Consequences > Macroeconomic
  2. Bianchi, Francesco & Bianchi, Giada & Song, Dongho, 2020. "The Long-Term Impact of the COVID-19 Unemployment Shock on Life Expectancy and Mortality Rates," CEPR Discussion Papers 15605, C.E.P.R. Discussion Papers.

    Mentioned in:

    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Long-term consequences
  3. Frank Schorfheide & Dongho Song, 2015. "Real-Time Forecasting With a Mixed-Frequency VAR," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 366-380, July.

    Mentioned in:

    1. > Econometrics > Time Series Models > VAR Models > Bayesian Vector autoregressions (BVARs)

Working papers

  1. Schorfheide, Frank & Song, Dongho, 2021. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," CEPR Discussion Papers 16760, C.E.P.R. Discussion Papers.

    Cited by:

    1. Christiane Baumeister & Pierre Guérin, 2020. "A Comparison of Monthly Global Indicators for Forecasting Growth," CESifo Working Paper Series 8656, CESifo.
    2. Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2020. "Nowcasting Tail Risks to Economic Activity with Many Indicators," Working Papers 20-13R2, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
    3. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    4. Evgenidis, Anastasios & Fasianos, Apostolos, 2023. "Modelling monetary policy’s impact on labour markets under Covid-19," Economics Letters, Elsevier, vol. 230(C).
    5. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Reconciled Estimates of Monthly GDP in the US," Working Papers 22-01, Federal Reserve Bank of Cleveland.
    6. Hwee Kwan Chow & Keen Meng Choy, 2023. "Economic forecasting in a pandemic: some evidence from Singapore," Empirical Economics, Springer, vol. 64(5), pages 2105-2124, May.
    7. Frank Schorfheide & Dongho Song, 2020. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," PIER Working Paper Archive 20-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    8. Florian, Huber & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2021. "Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs," Working Papers 2021-01, Joint Research Centre, European Commission.
    9. De Backer, Bruno & Dewachter, Hans & Iania, Leonardo, 2021. "Macrofinancial information on the post- COVID-19 economic recovery: will it be V, U or L-shaped?," LIDAM Discussion Papers LFIN 2021002, Université catholique de Louvain, Louvain Finance (LFIN).
    10. Ramis Khabibullin & Sergei Seleznev, 2022. "Fast Estimation of Bayesian State Space Models Using Amortized Simulation-Based Inference," Papers 2210.07154, arXiv.org.
    11. Bobeica, Elena & Hartwig, Benny, 2023. "The COVID-19 shock and challenges for inflation modelling," International Journal of Forecasting, Elsevier, vol. 39(1), pages 519-539.
    12. Bobeica, Elena & Hartwig, Benny, 2021. "The COVID-19 shock and challenges for time series models," Working Paper Series 2558, European Central Bank.
    13. Paul Ho, 2021. "Forecasting in the Absence of Precedent," Working Paper 21-10, Federal Reserve Bank of Richmond.
    14. Anna Sznajderska & Alfred A. Haug, 2023. "Bayesian VARs of the U.S. economy before and during the pandemic," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 13(2), pages 211-236, June.
    15. Zhang, Wen, 2022. "China’s government spending and global inflation dynamics: The role of the oil price channel," Energy Economics, Elsevier, vol. 110(C).
    16. Karin Klieber, 2023. "Non-linear dimension reduction in factor-augmented vector autoregressions," Papers 2309.04821, arXiv.org.
    17. Serena Ng, 2021. "Modeling Macroeconomic Variations after Covid-19," NBER Working Papers 29060, National Bureau of Economic Research, Inc.
    18. John Cotter & Mark Hallam & Kamil Yilmaz, 2020. "Macro-Financial Spillovers," Working Papers 202005, Geary Institute, University College Dublin.
    19. Roberta Cardani & Olga Croitorov & Massimo Giovannini & Philipp Pfeiffer & Marco Ratto & Lukas Vogel, 2021. "The Euro Area's Pandemic Recession: A DSGE-Based Interpretation," European Economy - Discussion Papers 153, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    20. Tino Berger & James Morley & Benjamin Wong, 2020. "Nowcasting the output gap," CAMA Working Papers 2020-78, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    21. Danilo Cascaldi-Garcia, 2022. "Pandemic Priors," International Finance Discussion Papers 1352, Board of Governors of the Federal Reserve System (U.S.).
    22. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," Working Papers 21-02R, Federal Reserve Bank of Cleveland, revised 09 Aug 2021.
    23. Antonio Musa, 2022. "Nowcasting Bosnia and Herzegovina GDP in Real Time," IHEID Working Papers 08-2022, Economics Section, The Graduate Institute of International Studies.
    24. Thomas B Götz & Klemens Hauzenberger, 2021. "Large mixed-frequency VARs with a parsimonious time-varying parameter structure," The Econometrics Journal, Royal Economic Society, vol. 24(3), pages 442-461.
    25. Valentina Aprigliano & Alessandro Borin & Francesco Paolo Conteduca & Simone Emiliozzi & Marco Flaccadoro & Sabina Marchetti & Stefania Villa, 2021. "Forecasting Italian GDP growth with epidemiological data," Questioni di Economia e Finanza (Occasional Papers) 664, Bank of Italy, Economic Research and International Relations Area.
    26. Marcellino, Massimiliano & Foroni, Claudia & Stevanovic, Dalibor, 2020. "Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis," CEPR Discussion Papers 15114, C.E.P.R. Discussion Papers.
    27. Danilo Cascaldi-Garcia & Matteo Luciani & Michele Modugno, 2023. "Lessons from Nowcasting GDP across the World," International Finance Discussion Papers 1385, Board of Governors of the Federal Reserve System (U.S.).
    28. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Working Papers 22-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    29. Vito Polito & Yunyi Zhang, 2021. "Tackling Large Outliers in Macroeconomic Data with Vector Artificial Neural Network Autoregression," CESifo Working Paper Series 9395, CESifo.
    30. Larson, William D. & Sinclair, Tara M., 2022. "Nowcasting unemployment insurance claims in the time of COVID-19," International Journal of Forecasting, Elsevier, vol. 38(2), pages 635-647.
    31. Bhaghoe, Sailesh & Ooft, Gavin, 2021. "Nowcasting Quarterly GDP Growth in Suriname with Factor-MIDAS and Mixed-Frequency VAR Models," Studies in Applied Economics 176, The Johns Hopkins Institute for Applied Economics, Global Health, and the Study of Business Enterprise.
    32. 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.
    33. Zeynep Kantur & Gülserim Özcan, 2022. "Dissecting Turkish inflation: theory, fact, and illusion," Economic Change and Restructuring, Springer, vol. 55(3), pages 1543-1553, August.
    34. John O’Trakoun, 2022. "Business forecasting during the pandemic," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 57(3), pages 95-110, July.
    35. Eraslan, Sercan & Schröder, Maximilian, 2023. "Nowcasting GDP with a pool of factor models and a fast estimation algorithm," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1460-1476.
    36. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021. "Forecasting with Shadow-Rate VARs," Working Papers 21-09, Federal Reserve Bank of Cleveland.
    37. Boriss Siliverstovs, 2021. "Gauging the Effect of Influential Observations on Measures of Relative Forecast Accuracy in a Post-COVID-19 Era: Application to Nowcasting Euro Area GDP Growth," Working Papers 2021/01, Latvijas Banka.
    38. Metiu, Norbert & Prieto, Esteban, 2023. "The macroeconomic effects of inflation uncertainty," Discussion Papers 32/2023, Deutsche Bundesbank.
    39. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org.

  2. Patrick Augustin & Mikhail Chernov & Lukas Schmid & Dongho Song, 2020. "The Term Structure of Covered Interest Rate Parity Violations," NBER Working Papers 27231, National Bureau of Economic Research, Inc.

    Cited by:

    1. Wenxin Du & Benjamin Hébert & Wenhao Li, 2022. "Intermediary Balance Sheets and the Treasury Yield Curve," Staff Reports 1023, Federal Reserve Bank of New York.

  3. Bianchi, Francesco & Bianchi, Giada & Song, Dongho, 2020. "The Long-Term Impact of the COVID-19 Unemployment Shock on Life Expectancy and Mortality Rates," CEPR Discussion Papers 15605, C.E.P.R. Discussion Papers.

    Cited by:

    1. Fischer, Kai & Reade, J. James & Schmal, W. Benedikt, 2022. "What cannot be cured must be endured: The long-lasting effect of a COVID-19 infection on workplace productivity," Labour Economics, Elsevier, vol. 79(C).
    2. Harran Al-Rahamneh & Lubna Arafa & Anas Al Orani & Rahaf Baqleh, 2021. "Long-Term Psychological Effects of COVID-19 Pandemic on Children in Jordan," IJERPH, MDPI, vol. 18(15), pages 1-10, July.
    3. Celine Saul & Shannon Lange & Charlotte Probst, 2022. "Employment Status and Alcohol-Attributable Mortality Risk—A Systematic Review and Meta-Analysis," IJERPH, MDPI, vol. 19(12), pages 1-10, June.
    4. Francesco Bogliacino & Cristiano Codagnone & Frans Folkvord & Francisco Lupiáñez-Villanueva, 2023. "The impact of labour market shocks on mental health: evidence from the Covid-19 first wave," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 40(3), pages 899-930, October.
    5. Víctor Giménez & Diego Prior & Claudio Thieme & Emili Tortosa-Ausina, 2021. "International comparisons of the COVID-19 pandemic management: What can be learned from activity analysis techniques?," Working Papers 2021/12, Economics Department, Universitat Jaume I, Castellón (Spain).
    6. Baira Faulks & Song Yinghua, 2021. "The COVID-19 Crisis: Implications for the Development and Growth of Agricultural Sector in EU countries and Russia," International Journal of Innovation and Economic Development, Inovatus Services Ltd., vol. 7(1), pages 37-46, April.
    7. Fischer, Kai & Reade, J. James & Schmal, W. Benedikt, 2021. "The long shadow of an infection: COVID-19 and performance at work," DICE Discussion Papers 368, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    8. Florin-Valeriu PANTELIMON & Bogdan-Stefan POSEDARU & Elena-Aura GRIGORESCU & Dimitrie-Daniel PLACINTA, 2021. "Labor Market Trends During The COVID-19 Pandemic," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 25(2), pages 50-63.

  4. Chernov, Mikhail & Augustin, Patrick & Schmid, Lukas & Song, Dongho, 2020. "The term structure of CIP violations," CEPR Discussion Papers 14774, C.E.P.R. Discussion Papers.

    Cited by:

    1. Wenxin Du & Benjamin Hébert & Wenhao Li, 2022. "Intermediary Balance Sheets and the Treasury Yield Curve," Staff Reports 1023, Federal Reserve Bank of New York.

  5. Taeyoung Doh & Dongho Song & Shu-Kuei X. Yang, 2020. "Deciphering Federal Reserve Communication via Text Analysis of Alternative FOMC Statements," Research Working Paper RWP 20-14, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Luis Felipe Gutiérrez & Neda Tavakoli & Sima Siami-Namini & Akbar Siami Namin, 2022. "Similarity analysis of federal reserve statements using document embeddings: the Great Recession vs. COVID-19," SN Business & Economics, Springer, vol. 2(7), pages 1-28, July.
    2. Ge Gao & Alex Nikolsko-Rzhevskyy & Oleksandr Talavera, 2023. "Can Central Banks Be Heard Over the Sound of Gunfire?," Discussion Papers 23-09, Department of Economics, University of Birmingham.
    3. Zahner, Johannes & Baumgärtner, Martin, 2022. "Whatever it Takes to Understand a Central Banker – Embedding their Words Using Neural Networks," VfS Annual Conference 2022 (Basel): Big Data in Economics 264019, Verein für Socialpolitik / German Economic Association.
    4. De Bandt Olivier & Bricongne Jean-Charles & Denes Julien & Dhenin Alexandre & De Gaye Annabelle & Robert Pierre-Antoine, 2023. "Using the Press to Construct a New Indicator of Inflation Perceptions in France," Working papers 921, Banque de France.
    5. Donato Masciandaro & Davide Romelli & Gaia Rubera, 2021. "Monetary policy and financial markets: evidence from Twitter traffic," BAFFI CAREFIN Working Papers 21160, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    6. Baumgärtner, Martin & Zahner, Johannes, 2023. "Whatever it takes to understand a central banker: Embedding their words using neural networks," IMFS Working Paper Series 194, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).

  6. Patrick Augustin & Mikhail Chernov & Lukas Schmid & Dongho Song, 2019. "Benchmark Interest Rates When the Government is Risky," NBER Working Papers 26429, National Bureau of Economic Research, Inc.

    Cited by:

    1. Wenxin Du & Benjamin Hébert & Wenhao Li, 2022. "Intermediary Balance Sheets and the Treasury Yield Curve," Staff Reports 1023, Federal Reserve Bank of New York.
    2. Li, Shaoyu & Zhu, Chunhui & Shang, Yuhuang, 2023. "Hedging demand and near-zero swap spreads: Evidence from the Chinese interest rate swap market," The Quarterly Review of Economics and Finance, Elsevier, vol. 91(C), pages 170-185.
    3. David Cashin & Erin E. Syron Ferris & Elizabeth Klee, 2023. "Treasury Safety, Liquidity, and Money Premium Dynamics: Evidence from Debt Limit Impasses," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(6), pages 1475-1506, September.
    4. Montes, Gabriel Caldas & Maia, João Pedro Neves, 2023. "Who speaks louder, financial instruments or credit rating agencies? Analyzing the effects of different sovereign risk measures on interest rates in Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    5. David B. Cashin & Erin E. Syron Ferris & Elizabeth C. Klee, 2020. "Treasury Safety, Liquidity, and Money Premium Dynamics: Evidence from Recent Debt Limit Impasses," Finance and Economics Discussion Series 2020-008, Board of Governors of the Federal Reserve System (U.S.).
    6. David-Pur, Lior & Galil, Koresh & Rosenboim, Mosi, 2020. "The dynamics of sovereign yields over swap rates in the Eurozone market," International Review of Financial Analysis, Elsevier, vol. 72(C).

  7. Ravi Bansal & Shane Miller & Dongho Song & Amir Yaron, 2019. "The Term Structure of Equity Risk Premia," NBER Working Papers 25690, National Bureau of Economic Research, Inc.

    Cited by:

    1. Andrei S. Gonçalves, 2021. "Reinvestment Risk and the Equity Term Structure," Journal of Finance, American Finance Association, vol. 76(5), pages 2153-2197, October.
    2. Foley, Sean & Li, Simeng & Malloch, Hamish & Svec, Jiri, 2022. "What is the expected return on Bitcoin? Extracting the term structure of returns from options prices," Economics Letters, Elsevier, vol. 210(C).
    3. Belén Nieto & Gonzalo Rubio, 2022. "The Effects of the COVID-19 Crisis on Risk Factors and Option-Implied Expected Market Risk Premia: An International Perspective," JRFM, MDPI, vol. 15(1), pages 1-29, January.
    4. A. Ronald Gallant & George Tauchen, 2021. "Cash Flows Discounted Using a Model-Free SDF Extracted under a Yield Curve Prior," JRFM, MDPI, vol. 14(3), pages 1-15, March.
    5. Pierlauro Lopez & J. David López-Salido & Francisco Vazquez-Grande, 2023. "Nominal Rigidities and the Term Structures of Equity and Bond Returns," Working Papers 23-11, Federal Reserve Bank of Cleveland.
    6. TAKAMIZAWA, Hideyuki & 高見澤, 秀幸, 2018. "An Equilibrium Model of Term Structures of Bonds and Equities," Working Paper Series G-1-19, Hitotsubashi University Center for Financial Research.
    7. Yu, Deshui & Huang, Difang, 2023. "Cross-sectional uncertainty and expected stock returns," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 321-340.
    8. Jeffrey L. Callen & Matthew R. Lyle, 2020. "The term structure of implied costs of equity capital," Review of Accounting Studies, Springer, vol. 25(1), pages 342-404, March.
    9. Patricia M. Dechow & Ryan D. Erhard & Richard G. Sloan & And Mark T. Soliman, 2021. "Implied Equity Duration: A Measure of Pandemic Shutdown Risk," Journal of Accounting Research, Wiley Blackwell, vol. 59(1), pages 243-281, March.
    10. Oliver Boguth & Murray Carlson & Adlai Fisher & Mikhail Simutin, 2023. "The Term Structure of Equity Risk Premia: Levered Noise and New Estimates," Review of Finance, European Finance Association, vol. 27(4), pages 1155-1182.
    11. Gonçalves, Andrei S., 2021. "The short duration premium," Journal of Financial Economics, Elsevier, vol. 141(3), pages 919-945.
    12. Michael Hasler & Mariana Khapko & Roberto Marfè, 2020. "Rational Learning and the Term Structures of Value and Growth Risk Premia," Carlo Alberto Notebooks 622, Collegio Carlo Alberto.
    13. Niels Joachim Gormsen & Eben Lazarus, 2023. "Duration‐Driven Returns," Journal of Finance, American Finance Association, vol. 78(3), pages 1393-1447, June.
    14. Jankauskas, Tomas, 2023. "Essays in empirical finance," Other publications TiSEM 4c319f87-ba97-44be-897e-1, Tilburg University, School of Economics and Management.
    15. Ye Li & Chen Wang, 2023. "Valuation Duration of the Stock Market," Papers 2310.07110, arXiv.org.
    16. Koichiro Moriya & Akihiko Noda, 2023. "On the Time-Varying Structure of the Arbitrage Pricing Theory using the Japanese Sector Indices," Papers 2305.05998, arXiv.org, revised Mar 2024.

  8. Chernov, Mikhail & Augustin, Patrick & Song, Dongho, 2018. "Sovereign credit risk and exchange rates: Evidence from CDS quanto spreads," CEPR Discussion Papers 12857, C.E.P.R. Discussion Papers.

    Cited by:

    1. Chernov, Mikhail & Creal, Drew & Hördahl, Peter, 2023. "Sovereign credit and exchange rate risks: Evidence from Asia-Pacific local currency bonds," Journal of International Economics, Elsevier, vol. 140(C).
    2. Marlene Amstad & Frank Packer & Jimmy Shek, 2018. "Does sovereign risk in local and foreign currency differ?," BIS Working Papers 709, Bank for International Settlements.
    3. Martin, Ian & Kremens, Lukas, 2017. "The Quanto Theory of Exchange Rates," CEPR Discussion Papers 11970, C.E.P.R. Discussion Papers.
    4. Borri, Nicola, 2019. "Redenomination-risk spillovers in the Eurozone," Economics Letters, Elsevier, vol. 174(C), pages 173-178.
    5. Andrey Itkin & Fazlollah Soleymani, 2019. "Four-factor model of Quanto CDS with jumps-at-default and stochastic recovery," Papers 1912.08713, arXiv.org.
    6. Dumitru, Ana-Maria & Holden, Thomas, 2019. "Quantifying the transmission of European sovereign default risk," EconStor Preprints 193632, ZBW - Leibniz Information Centre for Economics.
    7. Chernov, Mikhail & Schmid, Lukas & Schneider, Andres, 2016. "A Macrofinance View of U.S. Sovereign CDS Premiums," CEPR Discussion Papers 11576, C.E.P.R. Discussion Papers.
    8. Gordon Y. Liao, 2016. "Credit Migration and Covered Interest Rate Parity," Working Paper 468601, Harvard University OpenScholar.
    9. Giovanni Calice & Ming Zeng, 2021. "The term structure of sovereign credit default swap and the cross‐section of exchange rate predictability," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 445-458, January.
    10. Pelizzon, Loriana & Subrahmanyam, Marti G. & Tomio, Davide & Uno, Jun, 2018. "Central bank-driven mispricing," SAFE Working Paper Series 226, Leibniz Institute for Financial Research SAFE, revised 2018.
    11. Feng, Qianqian & Sun, Xiaolei & Liu, Chang & Li, Jianping, 2021. "Spillovers between sovereign CDS and exchange rate markets: The role of market fear," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    12. Mustafa Akay & Berat Bayram & Abdullah Kazdal & Muhammed Hasan Yilmaz, 2020. "Investigating Regime-Dependent Dynamics in Country Risk Premium: Evidence from Turkey and Emerging Markets," CBT Research Notes in Economics 2008, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    13. A. Itkin & V. Shcherbakov & A. Veygman, 2017. "Influence of jump-at-default in IR and FX on Quanto CDS prices," Papers 1711.07133, arXiv.org.

  9. Dongho Song & Jenny Tang, 2018. "News-driven uncertainty fluctuations," Working Papers 18-3, Federal Reserve Bank of Boston.

    Cited by:

    1. Francesco Carbonero & Jeremy Davies & Ekkehard Ernst & Sayantan Ghosal & Leaza McSorley, 2021. "Anxiety, Expectations Stabilization and Intertemporal Markets: Theory, Evidence and Policy," Working Papers 2021_12, Business School - Economics, University of Glasgow.

  10. Tzuo Hann Law & Dongho Song & Amir Yaron, 2017. "Fearing the Fed: How Wall Street Reads Main Street," 2017 Meeting Papers 1632, Society for Economic Dynamics.

    Cited by:

    1. Semyon Malamud & Andreas Schrimpf, 2018. "An intermediation-based model of exchange rates," BIS Working Papers 743, Bank for International Settlements.
    2. Semyon Malamud & Andreas Schrimpf, 2016. "Intermediation Markups and Monetary Policy Passthrough," Swiss Finance Institute Research Paper Series 16-75, Swiss Finance Institute.
    3. Pascal Paul, 2020. "The Time-Varying Effect of Monetary Policy on Asset Prices," The Review of Economics and Statistics, MIT Press, vol. 102(4), pages 690-704, October.
    4. Anthony M. Diercks & William Waller, 2017. "Taxes and the Fed : Theory and Evidence from Equities," Finance and Economics Discussion Series 2017-104, Board of Governors of the Federal Reserve System (U.S.).
    5. Kam F. Chan & Philip Gray, 2018. "Volatility jumps and macroeconomic news announcements," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(8), pages 881-897, August.

  11. Dongho Song, 2016. "Bond Market Exposures to Macroeconomic and Monetary Policy Risks," Boston College Working Papers in Economics 915, Boston College Department of Economics, revised 19 Jul 2016.

    Cited by:

    1. Mumtaz, Haroon & Theodoridis, Konstantinos, 2018. "Dynamic Effects of Monetary Policy Shocks on Macroeconomic Volatility," Cardiff Economics Working Papers E2018/21, Cardiff University, Cardiff Business School, Economics Section.
    2. Nitschka, Thomas & Satkurunathan, Shajivan, 2021. "Habits die hard: implications for bond and stock markets internationally," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242358, Verein für Socialpolitik / German Economic Association.
    3. Lakdawala, Aeimit & Wu, Shu, 2017. "Federal Reserve Credibility and the Term Structure of Interest Rates," MPRA Paper 78253, University Library of Munich, Germany.
    4. François Gourio & Phuong Ngo, 2020. "Risk Premia at the ZLB: A Macroeconomic Interpretation," Working Paper Series WP 2020-01, Federal Reserve Bank of Chicago.
    5. Ravi Bansal & Shane Miller & Dongho Song & Amir Yaron, 2019. "The Term Structure of Equity Risk Premia," NBER Working Papers 25690, National Bureau of Economic Research, Inc.
    6. Nguyen, Hoang & Javed, Farrukh, 2021. "Dynamic relationship between Stock and Bond returns: A GAS MIDAS copula approach," Working Papers 2021:15, Örebro University, School of Business.
    7. Duarte, Diogo & Saporito, Yuri F., 2019. "Endogenous asymmetric money illusion," Journal of Banking & Finance, Elsevier, vol. 109(C).
    8. Alfonso Dufour & Andrei Stancu & Simone Varotto, 2014. "The Equity-like Behaviour of Sovereign Bonds," ICMA Centre Discussion Papers in Finance icma-dp2014-16, Henley Business School, University of Reading.
    9. Jamel Boukhatem & Zied Ftiti & Jean Michel Sahut, 2021. "Bond market and macroeconomic stability in East Asia: a nonlinear causality analysis," Annals of Operations Research, Springer, vol. 297(1), pages 53-76, February.
    10. Martijn Boons & Frans de Roon & Fernando M. Duarte & Marta Szymanowska, 2013. "Time-Varying Inflation Risk and Stock Returns," Staff Reports 621, Federal Reserve Bank of New York.
    11. Gokmenoglu, Korhan K. & Hadood, Abobaker Al.Al., 2020. "Impact of US unconventional monetary policy on dynamic stock-bond correlations: Portfolio rebalancing and signalling channel effects," Finance Research Letters, Elsevier, vol. 33(C).
    12. Bodilsen, Simon & Eriksen, Jonas N. & Grønborg, Niels S., 2021. "Asset pricing and FOMC press conferences," Journal of Banking & Finance, Elsevier, vol. 128(C).
    13. Michael D. Bauer & Glenn D. Rudebusch, 2017. "Resolving the Spanning Puzzle in Macro-Finance Term Structure Models," Review of Finance, European Finance Association, vol. 21(2), pages 511-553.
    14. Bernard Dumas & Marcel Savioz, 2023. "A Theory of the Nominal Character of Stock Securities," Review of Finance, European Finance Association, vol. 27(5), pages 1615-1657.
    15. Dergunov, Ilya & Meinerding, Christoph & Schlag, Christian, 2019. "Extreme inflation and time-varying consumption growth," Discussion Papers 16/2019, Deutsche Bundesbank.
    16. Tsionas, Mike G. & Philippas, Dionisis & Philippas, Nikolaos, 2022. "Multivariate stochastic volatility for herding detection: Evidence from the energy sector," Energy Economics, Elsevier, vol. 109(C).
    17. Dohyun CHUN & Hoon CHO & Doojin RYU, 2018. "Macroeconomic Structural Changes in a Leading Emerging Market: The Effects of the Asian Financial Crisis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 22-42, December.
    18. Mohsan Bilal, 2017. "Zeroing in: Asset Pricing at the Zero Lower Bound," 2017 Meeting Papers 377, Society for Economic Dynamics.
    19. Erica X.N. Li & Tao Zha & Ji Zhang & Hao Zhou, 2020. "Stock-Bond Return Correlation, Bond Risk Premium Fundamentals, and Fiscal-Monetary Policy Regime," FRB Atlanta Working Paper 2020-19, Federal Reserve Bank of Atlanta.
    20. Geert Bekaert & Eric Engstrom & Andrey Ermolov, 2017. "Macro Risks and the Term Structure of Interest Rates," Finance and Economics Discussion Series 2017-058, Board of Governors of the Federal Reserve System (U.S.).
    21. Bianca De Paoli & Hande Küçük, 2015. "News shocks, monetary policy, and foreign currency positions," Staff Reports 750, Federal Reserve Bank of New York.
    22. Hiroatsu Tanaka, 2022. "Equilibrium Yield Curves with Imperfect Information," Finance and Economics Discussion Series 2022-086, Board of Governors of the Federal Reserve System (U.S.).
    23. Marcello Pericoli, 2020. "On risk factors of the stock–bond correlation," International Finance, Wiley Blackwell, vol. 23(3), pages 392-416, December.
    24. Marcello Pericoli, 2018. "Macroeconomics determinants of the correlation between stocks and bonds," Temi di discussione (Economic working papers) 1198, Bank of Italy, Economic Research and International Relations Area.
    25. Ermolov, Andrey, 2022. "Time-varying risk of nominal bonds: How important are macroeconomic shocks?," Journal of Financial Economics, Elsevier, vol. 145(1), pages 1-28.
    26. Nicolas Pesci & Jean-Philippe Aguilar & Victor James & Fabien Rouillé, 2022. "Inflation Forecasts and European Asset Returns: A Regime-Switching Approach," JRFM, MDPI, vol. 15(10), pages 1-20, October.
    27. Roman Sustek, 2021. "Yield curve and the business cycle in conventional times," Discussion Papers 2122, Centre for Macroeconomics (CFM).
    28. Shaliastovich, Ivan, 2015. "Learning, confidence, and option prices," Journal of Econometrics, Elsevier, vol. 187(1), pages 18-42.
    29. Kuvshinov, Dmitry & Zimmermann, Kaspar, 2020. "The Expected Return on Risky Assets: International Long-run Evidence," CEPR Discussion Papers 15610, C.E.P.R. Discussion Papers.
    30. Chernov, Mikhail & Schmid, Lukas & Schneider, Andres, 2016. "A Macrofinance View of U.S. Sovereign CDS Premiums," CEPR Discussion Papers 11576, C.E.P.R. Discussion Papers.
    31. van Holle, Frederiek, 2017. "Essays in empirical finance and monetary policy," Other publications TiSEM 30d11a4b-7bc9-4c81-ad24-5, Tilburg University, School of Economics and Management.
    32. Palazzo, Berardino & Yamarthy, Ram, 2022. "Credit risk and the transmission of interest rate shocks," Journal of Monetary Economics, Elsevier, vol. 130(C), pages 120-136.
    33. Guihai Zhao, 2020. "Ambiguity, Nominal Bond Yields, and Real Bond Yields," American Economic Review: Insights, American Economic Association, vol. 2(2), pages 177-192, June.
    34. Dergunov, Ilya & Meinerding, Christoph & Schlag, Christian, 2022. "Extreme inflation and time-varying expected consumption growth," SAFE Working Paper Series 334, Leibniz Institute for Financial Research SAFE.
    35. Pflueger, Carolin & Rinaldi, Gianluca, 2022. "Why does the Fed move markets so much? A model of monetary policy and time-varying risk aversion," Journal of Financial Economics, Elsevier, vol. 146(1), pages 71-89.
    36. Sewon Hur & Illenin O. Kondo & Fabrizio Perri, 2018. "Inflation, Debt, and Default," Working Papers (Old Series) 1812, Federal Reserve Bank of Cleveland.
    37. François Gourio & Phuong Ngo, 2024. "Downward Nominal Rigidities and Bond Premia," Working Paper Series WP 2024-09, Federal Reserve Bank of Chicago.
    38. Robert A. Connolly & Chris Stivers & Licheng Sun, 2022. "Stock returns and inflation shocks in weaker economic times," Financial Management, Financial Management Association International, vol. 51(3), pages 827-867, September.
    39. Perri, Fabrizio & Hur, Sewon & Kondo, Illenin, 2018. "Real Interest Rates, Inflation, and Default," CEPR Discussion Papers 13388, C.E.P.R. Discussion Papers.
    40. Kim, Jaeho, 2015. "Bayesian Inference in a Non-linear/Non-Gaussian Switching State Space Model: Regime-dependent Leverage Effect in the U.S. Stock Market," MPRA Paper 67153, University Library of Munich, Germany.
    41. Bahmani-Oskooee, Mohsen & Ghodsi, Seyed Hesam & Hadzic, Muris, 2020. "Asymmetric causality between stock returns and usual hedges: An industry-level analysis," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
    42. Pierlauro Lopez, 2021. "Welfare Implications of Asset Pricing Facts: Should Central Banks Fill Gaps or Remove Volatility?," Working Papers 21-16R, Federal Reserve Bank of Cleveland, revised 16 May 2023.
    43. Roberto Marfè, 2016. "Labor Rigidity, In ation Risk and Bond Returns," Carlo Alberto Notebooks 461, Collegio Carlo Alberto.
    44. Cieslak, Anna & Pang, Hao, 2020. "Common shocks in stocks and bonds," CEPR Discussion Papers 14708, C.E.P.R. Discussion Papers.
    45. Alex Hsu & Francisco J. Palomino & Charles Qian, 2017. "The Decline in Asset Return Predictability and Macroeconomic Volatility," Finance and Economics Discussion Series 2017-050, Board of Governors of the Federal Reserve System (U.S.).
    46. Liu, Yang, 2023. "Government debt and risk premia," Journal of Monetary Economics, Elsevier, vol. 136(C), pages 18-34.
    47. Li, Erica X.N. & Zha, Tao & Zhang, Ji & Zhou, Hao, 2022. "Does fiscal policy matter for stock-bond return correlation?," Journal of Monetary Economics, Elsevier, vol. 128(C), pages 20-34.
    48. Bansal, Naresh & Stivers, Chris, 2022. "Bond risk’s role in the equity risk-return tradeoff," Journal of Financial Markets, Elsevier, vol. 60(C).
    49. Gregory R Duffee, 2023. "Macroeconomic News and Stock–Bond Comovement," Review of Finance, European Finance Association, vol. 27(5), pages 1859-1882.
    50. Nikolay Gospodinov, 2017. "Asset Co-movements: Features and Challenges," FRB Atlanta Working Paper 2017-11, Federal Reserve Bank of Atlanta.
    51. Cieslak, Anna & Pang, Hao, 2021. "Common shocks in stocks and bonds," Journal of Financial Economics, Elsevier, vol. 142(2), pages 880-904.
    52. Taeyoung Doh & Shu Wu, 2016. "The Equilibrium Term Structure of Equity and Interest Rates," Research Working Paper RWP 16-11, Federal Reserve Bank of Kansas City.
    53. Alex Hsu & Francisco Palomino & Liang Qian, 2023. "Gone with the Vol: A Decline in Asset Return Predictability During the Great Moderation," Management Science, INFORMS, vol. 69(5), pages 3025-3047, May.
    54. Gozluklu, Arie & Morin, Annaïg, 2019. "Stock vs. Bond yields and demographic fluctuations," Journal of Banking & Finance, Elsevier, vol. 109(C).

  12. S. Boragan Aruoba & Francis X. Diebold & Jeremy J. Nalewaik & Frank Schorfheide & Dongho Song, 2013. "Improving GDP measurement: a measurement-error perspective," Working Papers 13-16, Federal Reserve Bank of Philadelphia.

    Cited by:

    1. Jeremy J. Nalewaik, 2014. "Missing Variation in the Great Moderation: Lack of Signal Error and OLS Regression," Finance and Economics Discussion Series 2014-27, Board of Governors of the Federal Reserve System (U.S.).
    2. Reinelt, Timo & Meier, Matthias, 2020. "Monetary policy, markup dispersion, and aggregate TFP," Working Paper Series 2427, European Central Bank.
    3. Francis X. Diebold & Maximilian Gobel & Philippe Goulet Coulombe & Glenn D. Rudebusch & Boyuan Zhang, 2020. "Optimal Combination of Arctic Sea Ice Extent Measures: A Dynamic Factor Modeling Approach," Papers 2003.14276, arXiv.org, revised Aug 2020.
    4. Arabinda Basistha, 2023. "Estimation of short‐run predictive factor for US growth using state employment data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 34-50, January.
    5. Daniel Aaronson & Scott A. Brave & Michael Fogarty & Ezra Karger & Spencer D. Krane, 2021. "Tracking U.S. Consumers in Real Time with a New Weekly Index of Retail Trade," Working Paper Series WP-2021-05, Federal Reserve Bank of Chicago, revised 18 Jun 2021.
    6. Michael Cai & Marco Del Negro & Marc Giannoni & Abhi Gupta & Pearl Li & Erica Moszkowski, 2018. "DSGE forecasts of the lost recovery," Staff Reports 844, Federal Reserve Bank of New York.
    7. Anesti, Nikoleta & Galvao, Ana Beatriz & Miranda-Agrippino, Silvia, 2018. "Uncertain kingdom: nowcasting GDP and its revisions," LSE Research Online Documents on Economics 90382, London School of Economics and Political Science, LSE Library.
    8. Ana Beatriz Galvão & James Mitchell, 2023. "Real‐Time Perceptions of Historical GDP Data Uncertainty," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 457-481, June.
    9. Nalewaik, Jeremy & Pinto, Eugénio, 2015. "The response of capital goods shipments to demand over the business cycle," Journal of Macroeconomics, Elsevier, vol. 43(C), pages 62-80.
    10. Sekine, Toshitaka, 2022. "Looking from Gross Domestic Income: Alternative view of Japan’s economy," Japan and the World Economy, Elsevier, vol. 64(C).
    11. John C. Williams, 2015. "The recovery’s final frontier?," Speech 150, Federal Reserve Bank of San Francisco.
    12. Petrella, Ivan & Venditti, Fabrizio & Delle Monache, Davide, 2016. "Adaptive state space models with applications to the business cycle and financial stress," CEPR Discussion Papers 11599, C.E.P.R. Discussion Papers.
    13. Matteo Barigozzi & Matteo Luciani, 2017. "Common Factors, Trends, and Cycles in Large Datasets," Finance and Economics Discussion Series 2017-111, Board of Governors of the Federal Reserve System (U.S.).
    14. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Reconciled Estimates of Monthly GDP in the US," Working Papers 22-01, Federal Reserve Bank of Cleveland.
    15. Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 147-170, National Bureau of Economic Research, Inc.
    16. Eduardo Rossi & Paolo Santucci de Magistris, 2018. "Indirect inference with time series observed with error," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(6), pages 874-897, September.
    17. Peter A.G. van Bergeijk, 2017. "Making Data Measurement Errors Transparent: The Case of the IMF," World Economics, World Economics, 1 Ivory Square, Plantation Wharf, London, United Kingdom, SW11 3UE, vol. 18(3), pages 133-154, July.
    18. Loria, Francesca & Matthes, Christian & Wang, Mu-Chun, 2022. "Economic theories and macroeconomic reality," Journal of Monetary Economics, Elsevier, vol. 126(C), pages 105-117.
    19. Daniel Rees & David Lancaster & Richard Finlay, 2014. "A State-space Approach to Australian GDP Measurement," RBA Research Discussion Papers rdp2014-12, Reserve Bank of Australia.
    20. Tom Stark, 2014. "Real-time performance of GDPplus and alternative model-based measures of GDP: 2005—2014," Research Rap Special Report, Federal Reserve Bank of Philadelphia, issue Nov.
    21. Sentana, Enrique & Almuzara, Martin & Amengual, Dante & Fiorentini, Gabriele, 2022. "GDP Solera: The Ideal Vintage Mix," CEPR Discussion Papers 17196, C.E.P.R. Discussion Papers.
    22. Boragan Aruoba & Francis X. Diebold & Jeremy Nalewaik & Frank Schorfheide & Dongho Song, 2011. "Improving GDP Measurement: A Forecast Combination Perspective," PIER Working Paper Archive 11-028, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    23. Jan-Benedict E. M. Steenkamp & Alberto Maydeu-Olivares, 2023. "Unrestricted factor analysis: A powerful alternative to confirmatory factor analysis," Journal of the Academy of Marketing Science, Springer, vol. 51(1), pages 86-113, January.
    24. Garciga, Christian & Knotek II, Edward S., 2019. "Forecasting GDP growth with NIPA aggregates: In search of core GDP," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1814-1828.
    25. Matei Demetrescu & Robinson Kruse-Becher, 2021. "Is U.S. real output growth really non-normal? Testing distributional assumptions in time-varying location-scale models," CREATES Research Papers 2021-07, Department of Economics and Business Economics, Aarhus University.
    26. Prydz, Espen Beer & Jolliffe, Dean & Serajuddin, Umar, 2021. "Mind the Gap," GLO Discussion Paper Series 944, Global Labor Organization (GLO).
    27. Eiji Goto & Jan P.A.M. Jacobs & Tara M. Sinclair & Simon van Norden, 2021. "Employment Reconciliation and Nowcasting," Working Papers 2021-007, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    28. Carriero, Andrea & Clements, Michael P. & Galvão, Ana Beatriz, 2015. "Forecasting with Bayesian multivariate vintage-based VARs," International Journal of Forecasting, Elsevier, vol. 31(3), pages 757-768.
    29. Geng, Pei, 2022. "Estimation of functional-coefficient autoregressive models with measurement error," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    30. John G. Fernald & J. Christina Wang, 2015. "Why has the cyclicality of productivity changed?: what does it mean?," Current Policy Perspectives 15-6, Federal Reserve Bank of Boston.
    31. Gospodinov, Nikolay & Komunjer, Ivana & Ng, Serena, 2017. "Simulated minimum distance estimation of dynamic models with errors-in-variables," Journal of Econometrics, Elsevier, vol. 200(2), pages 181-193.
    32. Lee, Hangyu & Kim, Tae Bong, 2023. "The effectiveness of labor market indicators for conducting monetary policy: Evidence from the Korean economy," Economic Modelling, Elsevier, vol. 118(C).
    33. Martín Almuzara & Dante Amengual & Enrique Sentana, 2019. "Normality tests for latent variables," Quantitative Economics, Econometric Society, vol. 10(3), pages 981-1017, July.
    34. John C. Williams, 2015. "Looking forward, forward looking: the path for monetary policy," Speech 138, Federal Reserve Bank of San Francisco.
    35. John C. Williams, 2015. "Data is the new black: monetary policy by the numbers," Speech 140, Federal Reserve Bank of San Francisco.
    36. Pinkwart, Nicolas, 2018. "Short-term forecasting economic activity in Germany: A supply and demand side system of bridge equations," Discussion Papers 36/2018, Deutsche Bundesbank.
    37. Ben Zeev, Nadav & Pappa, Evi, 2015. "Multipliers of unexpected increases in defense spending: An empirical investigation," Journal of Economic Dynamics and Control, Elsevier, vol. 57(C), pages 205-226.
    38. John C. Williams, 2015. "Looking forward: the path for monetary policy," FRBSF Economic Letter, Federal Reserve Bank of San Francisco.
    39. Andrew C. Chang & Phillip Li, 2018. "Measurement Error In Macroeconomic Data And Economics Research: Data Revisions, Gross Domestic Product, And Gross Domestic Income," Economic Inquiry, Western Economic Association International, vol. 56(3), pages 1846-1869, July.
    40. Wankeun Oh & Jonghyun Yoo, 2020. "Long-Term Increases and Recent Slowdowns of CO 2 Emissions in Korea," Sustainability, MDPI, vol. 12(17), pages 1-13, August.
    41. Tom Stark, 2015. "First quarters in the national income and product accounts," Research Rap Special Report, Federal Reserve Bank of Philadelphia, issue May.
    42. Dr. Yannic Stucki, 2022. "Measuring Swiss employment growth: a measurement-error approach," Working Papers 2022-11, Swiss National Bank.
    43. Nikoleta Anesti & Ana Beatriz Galvão & Silvia Miranda‐Agrippino, 2022. "Uncertain Kingdom: Nowcasting Gross Domestic Product and its revisions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 42-62, January.
    44. Nikolay Gospodinov & Ivana Komunjer & Serena Ng, 2014. "Minimum Distance Estimation of Dynamic Models with Errors-In-Variables," FRB Atlanta Working Paper 2014-11, Federal Reserve Bank of Atlanta.
    45. van Bergeijk, P.A.G., 2017. "Measurement error of global production," ISS Working Papers - General Series 632, International Institute of Social Studies of Erasmus University Rotterdam (ISS), The Hague.
    46. Alessandro Giovannelli & Marco Lippi & Tommaso Proietti, 2023. "Band-Pass Filtering with High-Dimensional Time Series," CEIS Research Paper 559, Tor Vergata University, CEIS, revised 15 Jun 2023.
    47. Kurt Graden Lunsford, 2023. "The Discrepancy Between Expenditure- and Income-Side Estimates of US Output," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2023(01), pages 1-7, January.
    48. Ammi, Mehdi & Arpin, Emmanuelle & Allin, Sara, 2021. "Interpreting forty-three-year trends of expenditures on public health in Canada: Long-run trends, temporal periods, and data differences," Health Policy, Elsevier, vol. 125(12), pages 1557-1564.
    49. Alifatussaadah, Ardiana & Primariesty, Anindya Diva & Soleh, Agus Mohamad & Andriansyah, Andriansyah, 2019. "Nowcasting Indonesia's GDP Growth: Are Fiscal Data Useful?," MPRA Paper 105252, University Library of Munich, Germany.
    50. Hu, Yingyao & Yao, Jiaxiong, 2022. "Illuminating economic growth," Journal of Econometrics, Elsevier, vol. 228(2), pages 359-378.
    51. Jan P.A.M. Jacobs & Samad Sarferaz & Simon van Norden & Jan-Egbert Sturm, 2013. "Modeling Multivariate Data Revisions," CIRANO Working Papers 2013s-44, CIRANO.
    52. Florian Eckert & Nina Mühlebach, 2023. "Global and local components of output gaps," Empirical Economics, Springer, vol. 65(5), pages 2301-2331, November.
    53. Víctor M. Guerrero & Juan A. Mendoza, 2019. "On measuring economic growth from outer space: a single country approach," Empirical Economics, Springer, vol. 57(3), pages 971-990, September.
    54. Gyurkovics, Éva & Takács, Tibor, 2022. "Robust energy-to-peak filter design for a class of unstable polytopic systems with a macroeconomic application," Applied Mathematics and Computation, Elsevier, vol. 420(C).

  13. Frank Schorfheide & Dongho Song & Amir Yaron, 2013. "Identifying long-run risks: a bayesian mixed-frequency approach," Working Papers 13-39, Federal Reserve Bank of Philadelphia.

    Cited by:

    1. Segal, Gill & Shaliastovich, Ivan & Yaron, Amir, 2015. "Good and bad uncertainty: Macroeconomic and financial market implications," Journal of Financial Economics, Elsevier, vol. 117(2), pages 369-397.
    2. Jaroslav Borovička & John Stachurski, 2017. "Necessary and Sufficient Conditions for Existence and Uniqueness of Recursive Utilities," NBER Working Papers 24162, National Bureau of Economic Research, Inc.
    3. Christopher Anderson, 2021. "Consumption-Based Asset Pricing When Consumers Make Mistakes," Finance and Economics Discussion Series 2021-015, Board of Governors of the Federal Reserve System (U.S.).
    4. Susanto Basu & Giacomo Candian & Ryan Chahrour & Rosen Valchev, 2021. "Risky Business Cycles," NBER Working Papers 28693, National Bureau of Economic Research, Inc.
    5. Dongho Song, 2016. "Bond Market Exposures to Macroeconomic and Monetary Policy Risks," Boston College Working Papers in Economics 915, Boston College Department of Economics, revised 19 Jul 2016.
    6. Drew D. Creal & Jing Cynthia Wu, 2020. "Bond risk premia in consumption‐based models," Quantitative Economics, Econometric Society, vol. 11(4), pages 1461-1484, November.
    7. Dalderop, Jeroen, 2023. "Semiparametric estimation of latent variable asset pricing models," Journal of Econometrics, Elsevier, vol. 236(1).
    8. Jaroslav Borovicka & John Stachurski, 2019. "Stability of Equilibrium Asset Pricing Models: A Necessary and Sufficient Condition," Papers 1910.00778, arXiv.org, revised Feb 2021.
    9. Rhys M. Bidder & Matthew E. Smith, 2013. "Doubts and Variability: A Robust Perspective on Exotic Consumption Series," Working Paper Series 2013-28, Federal Reserve Bank of San Francisco.
    10. Segal, Gill & Shaliastovich, Ivan, 2023. "Uncertainty, risk, and capital growth," SAFE Working Paper Series 388, Leibniz Institute for Financial Research SAFE.
    11. Marlène Isoré & Urszula Szczerbowicz, 2015. "Disaster Risk and Preference Shifts in a New Keynesian Model," Working Papers 2015-16, CEPII research center.
    12. David Alaminos & Ignacio Esteban & M. Belén Salas, 2023. "Neural networks for estimating Macro Asset Pricing model in football clubs," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 30(2), pages 57-75, April.
    13. de Groot, Oliver & Richter, Alexander W. & Throckmorton, Nathaniel, 2020. "Valuation Risk Revalued," CEPR Discussion Papers 14588, C.E.P.R. Discussion Papers.
    14. Pooyan Amir‐Ahmadi & Christian Matthes & Mu‐Chun Wang, 2016. "Drifts and volatilities under measurement error: Assessing monetary policy shocks over the last century," Quantitative Economics, Econometric Society, vol. 7(2), pages 591-611, July.
    15. Grammig, Joachim & Küchlin, Eva-Maria, 2017. "A two-step indirect inference approach to estimate the long-run risk asset pricing model," CFR Working Papers 17-01, University of Cologne, Centre for Financial Research (CFR).
    16. Pierlauro Lopez & J. David López-Salido & Francisco Vazquez-Grande, 2022. "Accounting for Risk in a Linearized Solution: How to Approximate the Risky Steady State and Around It," Working Papers 22-14, Federal Reserve Bank of Cleveland.
    17. Dergunov, Ilya & Meinerding, Christoph & Schlag, Christian, 2019. "Extreme inflation and time-varying consumption growth," Discussion Papers 16/2019, Deutsche Bundesbank.
    18. Zhang, Jian & Kong, Dongmin & Liu, Hening & Wu, Ji, 2019. "Asset pricing with time varying pessimism and rare disasters," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 165-175.
    19. Gao, Lin & Hitzemann, Steffen & Shaliastovich, Ivan & Xu, Lai, 2022. "Oil volatility risk," Journal of Financial Economics, Elsevier, vol. 144(2), pages 456-491.
    20. Ji Zhang & Jing Cynthia Wu, 2017. "A shadow rate New Keynesian model," 2017 Meeting Papers 11, Society for Economic Dynamics.
    21. Elmar Mertens & James M. Nason, 2018. "Inflation and professional forecast dynamics: an evaluation of stickiness, persistence, and volatility," BIS Working Papers 713, Bank for International Settlements.
    22. Ascari, Guido & Magnusson, Leandro M. & Mavroeidis, Sophocles, 2021. "Empirical evidence on the Euler equation for consumption in the US," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 129-152.
    23. Patrick J. Kehoe & Pierlauro Lopez & Virgiliu Midrigan & Elena Pastorino, 2020. "Asset Prices and Unemployment Fluctuations," Working Papers 20-10, Federal Reserve Bank of Cleveland.
    24. Patrick Augustin & Mikhail Chernov & Lukas Schmid & Dongho Song, 2019. "Benchmark Interest Rates When the Government is Risky," NBER Working Papers 26429, National Bureau of Economic Research, Inc.
    25. Ljungqvist, Lars & Sargent, Thomas, 2021. "The Fundamental Surplus Strikes Again," CEPR Discussion Papers 16077, C.E.P.R. Discussion Papers.
    26. Guy P. Nason & Ben Powell & Duncan Elliott & Paul A. Smith, 2017. "Should we sample a time series more frequently?: decision support via multirate spectrum estimation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(2), pages 353-407, February.
    27. Jing Guo & Xue Dong He, 2021. "Recursive Utility with Investment Gains and Losses: Existence, Uniqueness, and Convergence," Papers 2107.05163, arXiv.org.
    28. Dongho Song & Jenny Tang, 2018. "News-driven uncertainty fluctuations," Working Papers 18-3, Federal Reserve Bank of Boston.
    29. Geert Bekaert & Eric Engstrom & Andrey Ermolov, 2023. "The Variance Risk Premium in Equilibrium Models," Review of Finance, European Finance Association, vol. 27(6), pages 1977-2014.
    30. Christensen, Timothy M., 2022. "Existence and uniqueness of recursive utilities without boundedness," Journal of Economic Theory, Elsevier, vol. 200(C).
    31. Gregory, Richard P., 2021. "Climate disasters, carbon dioxide, and financial fundamentals," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 45-58.
    32. Fang, Xiang & Liu, Yang, 2021. "Volatility, intermediaries, and exchange rates," Journal of Financial Economics, Elsevier, vol. 141(1), pages 217-233.
    33. Walter Pohl & Karl Schmedders & Ole Wilms, 2018. "Higher Order Effects in Asset Pricing Models with Long‐Run Risks," Journal of Finance, American Finance Association, vol. 73(3), pages 1061-1111, June.
    34. Rey, Hélène & Coimbra, Nuno & Kim, Daisoon, 2021. "Central Bank Policy and the Concentration of Risk: Empirical Estimates," CEPR Discussion Papers 16221, C.E.P.R. Discussion Papers.
    35. Ermolov, Andrey, 2022. "Time-varying risk of nominal bonds: How important are macroeconomic shocks?," Journal of Financial Economics, Elsevier, vol. 145(1), pages 1-28.
    36. Shaliastovich, Ivan, 2015. "Learning, confidence, and option prices," Journal of Econometrics, Elsevier, vol. 187(1), pages 18-42.
    37. Fulop, Andras & Heng, Jeremy & Li, Junye & Liu, Hening, 2022. "Bayesian estimation of long-run risk models using sequential Monte Carlo," Journal of Econometrics, Elsevier, vol. 228(1), pages 62-84.
    38. Ankargren, Sebastian & Jonéus, Paulina, 2021. "Simulation smoothing for nowcasting with large mixed-frequency VARs," Econometrics and Statistics, Elsevier, vol. 19(C), pages 97-113.
    39. Iacopini, Matteo & Poon, Aubrey & Rossini, Luca & Zhu, Dan, 2023. "Bayesian mixed-frequency quantile vector autoregression: Eliciting tail risks of monthly US GDP," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    40. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2016. "Choosing Prior Hyperparameters," Working Paper 16-9, Federal Reserve Bank of Richmond.
    41. Favero, Carlo A. & Tamoni, Andrea & Ortu, Fulvio & Yang, Haoxi, 2016. "Implications of Return Predictability across Horizons for Asset Pricing Models," CEPR Discussion Papers 11645, C.E.P.R. Discussion Papers.
    42. GUERRON-QUINTANA, Pablo A. & JINNAI, Ryo & 陣内, 了, 2015. "Financial Frictions, Trends, and the Great Recession," Discussion paper series HIAS-E-14, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    43. Myroslav Pidkuyko & Raffaele Rossi & Klaus Reiner Schenk-Hoppé, 2019. "The Resolution of Long-Run Risk," Economics Discussion Paper Series 1908, Economics, The University of Manchester.
    44. Timothy M. Christensen, 2020. "Existence and uniqueness of recursive utilities without boundedness," Papers 2008.00963, arXiv.org, revised Aug 2021.
    45. Gouriéroux Christian & Monfort Alain & Mouabbi Sarah & Renne Jean-Paul, 2020. "Disastrous Defaults," Working papers 778, Banque de France.
    46. Binder, Michael & Lieberknecht, Philipp & Quintana, Jorge & Wieland, Volker, 2017. "Model uncertainty in macroeconomics: On the implications of financial frictions," IMFS Working Paper Series 114, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    47. Horvath, Jaroslav, 2020. "Macroeconomic disasters and the equity premium puzzle: Are emerging countries riskier?," Journal of Economic Dynamics and Control, Elsevier, vol. 112(C).
    48. G. Gopalakrishna, 2017. "Robust test of Long Run Risk and Valuation risk model," Working Papers wp1107, Dipartimento Scienze Economiche, Universita' di Bologna.
    49. Davide Pettenuzzo & Rossen Valkanov & Allan Timmermann, 2014. "A Bayesian MIDAS Approach to Modeling First and Second Moment Dynamics," Working Papers 76, Brandeis University, Department of Economics and International Business School.
    50. Pettenuzzo, Davide & Timmermann, Allan & Valkanov, Rossen, 2016. "A MIDAS approach to modeling first and second moment dynamics," Journal of Econometrics, Elsevier, vol. 193(2), pages 315-334.
    51. Ma, Qingyin & Stachurski, John & Toda, Alexis Akira, 2020. "The income fluctuation problem and the evolution of wealth," Journal of Economic Theory, Elsevier, vol. 187(C).
    52. John Stachurski & Junnan Zhang, 2019. "Dynamic Programming with State-Dependent Discounting," Papers 1908.08800, arXiv.org, revised Oct 2020.
    53. Grammig, Joachim & Küchlin, Eva-Maria, 2018. "A two-step indirect inference approach to estimate the long-run risk asset pricing model," Journal of Econometrics, Elsevier, vol. 205(1), pages 6-33.
    54. Mauro Bernardi & Daniele Bianchi & Nicolas Bianco, 2022. "Smoothing volatility targeting," Papers 2212.07288, arXiv.org.
    55. Dahlquist, Magnus & Pénasse, Julien, 2022. "The missing risk premium in exchange rates," Journal of Financial Economics, Elsevier, vol. 143(2), pages 697-715.
    56. Flint O'Neil, 2020. "Existence and Uniqueness of Recursive Utility Models in $L_p$," Papers 2005.07067, arXiv.org.
    57. Anmol Bhandari & David Evans & Mikhail Golosov & Thomas Sargent, 2019. "The Optimal Maturity of Government Debt," 2019 Meeting Papers 1011, Society for Economic Dynamics.
    58. Nam Gang Lee, 2019. "Trend Growth Shocks and Asset Prices," Working Papers 2019-4, Economic Research Institute, Bank of Korea.
    59. Jules Tinang & Nour Meddahi, 2016. "GMM estimation of the Long Run Risks model," 2016 Meeting Papers 1107, Society for Economic Dynamics.
    60. He, Yunhao & Leippold, Markus, 2020. "Short-run risk, business cycle, and the value premium," Journal of Economic Dynamics and Control, Elsevier, vol. 120(C).
    61. Pablo Guerróon‐Quintana & Molin Zhong, 2023. "Macroeconomic forecasting in times of crises," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 295-320, April.
    62. Manela, Asaf & Moreira, Alan, 2017. "News implied volatility and disaster concerns," Journal of Financial Economics, Elsevier, vol. 123(1), pages 137-162.
    63. Guanlong Ren & John Stachurski, 2018. "Dynamic Programming with Recursive Preferences: Optimality and Applications," Papers 1812.05748, arXiv.org, revised Jun 2020.
    64. Andrew Y. Chen & Rebecca Wasyk & Fabian Winkler, 2017. "A Likelihood-Based Comparison of Macro Asset Pricing Models," Finance and Economics Discussion Series 2017-024, Board of Governors of the Federal Reserve System (U.S.).
    65. David Feldman & Xin Xu, 2018. "Equilibrium-based volatility models of the market portfolio rate of return (peacock tails or stotting gazelles)," Annals of Operations Research, Springer, vol. 262(2), pages 493-518, March.
    66. Thomas J. Sargent & John Stachurski, 2024. "Dynamic Programming: Finite States," Papers 2401.10473, arXiv.org.
    67. Liu, Yang, 2023. "Government debt and risk premia," Journal of Monetary Economics, Elsevier, vol. 136(C), pages 18-34.
    68. Pohl, Walter & Schmedders, Karl & Wilms, Ole, 2021. "Asset pricing with heterogeneous agents and long-run risk," Journal of Financial Economics, Elsevier, vol. 140(3), pages 941-964.
    69. S. Boragan Aruoba, 2016. "Term structures of inflation expectations and real interest rates," Working Papers 16-9, Federal Reserve Bank of Philadelphia.
    70. Bretscher, Lorenzo & Malkhozov, Aytek & Tamoni, Andrea, 2021. "Expectations and aggregate risk," Journal of Monetary Economics, Elsevier, vol. 123(C), pages 91-108.
    71. Andreas Tryphonides, 2018. "Tilting Approximate Models," Papers 1805.10869, arXiv.org, revised Mar 2024.
    72. Grammig, Joachim & Küchlin, Eva-Maria, 2017. "A two-step indirect inference approach to estimate the long-run risk asset pricing model," CFS Working Paper Series 572, Center for Financial Studies (CFS).
    73. Taeyoung Doh & Shu Wu, 2015. "Cash flow and risk premium dynamics in an equilibrium asset-pricing model with recursive preferences," Research Working Paper RWP 15-12, Federal Reserve Bank of Kansas City.
    74. Andras Fulop & Jeremy Heng & Junye Li, 2022. "Efficient Likelihood-based Estimation via Annealing for Dynamic Structural Macrofinance Models," Papers 2201.01094, arXiv.org.
    75. Leippold, Markus & Yang, Hanlin, 2019. "Particle filtering, learning, and smoothing for mixed-frequency state-space models," Econometrics and Statistics, Elsevier, vol. 12(C), pages 25-41.
    76. Martin M. Andreasen & Kasper Jørgensen, 2016. "Explaining Asset Prices with Low Risk Aversion and Low Intertemporal Substitution," CREATES Research Papers 2016-16, Department of Economics and Business Economics, Aarhus University.

  14. Frank Schorfheide & Dongho Song, 2012. "Real-time forecasting with a mixed-frequency VAR," Working Papers 701, Federal Reserve Bank of Minneapolis.

    Cited by:

    1. Philipp Gersing & Leopold Soegner & Manfred Deistler, 2022. "Retrieval from Mixed Sampling Frequency: Generic Identifiability in the Unit Root VAR," Papers 2204.05952, arXiv.org, revised Jul 2023.
    2. Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2018. "Using low frequency information for predicting high frequency variables," International Journal of Forecasting, Elsevier, vol. 34(4), pages 774-787.
    3. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2010. "Should macroeconomic forecasters use daily financial data and how?," University of Cyprus Working Papers in Economics 09-2010, University of Cyprus Department of Economics.
    4. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Using hierarchical aggregation constraints to nowcast regional economic aggregates," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-04, Economic Statistics Centre of Excellence (ESCoE).
    5. Markus Heinrich & Magnus Reif, 2018. "Forecasting using mixed-frequency VARs with time-varying parameters," ifo Working Paper Series 273, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    6. Minsu Chang & Xiaohong Chen & Frank Schorfheide, 2021. "Heterogeneity and Aggregate Fluctuations," NBER Working Papers 28853, National Bureau of Economic Research, Inc.
    7. Scott Brave & R. Andrew Butters & Alejandro Justiniano, 2016. "Forecasting Economic Activity with Mixed Frequency Bayesian VARs," Working Paper Series WP-2016-5, Federal Reserve Bank of Chicago.
    8. Bańbura, Marta & Giannone, Domenico & Lenza, Michele, 2015. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," International Journal of Forecasting, Elsevier, vol. 31(3), pages 739-756.
    9. Koop, Gary & McIntyre, Stuart & Mitchell, James & Poon, Aubrey, 2019. "Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017," EMF Research Papers 20, Economic Modelling and Forecasting Group.
    10. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian vector autoregressions," LSE Research Online Documents on Economics 87393, London School of Economics and Political Science, LSE Library.
    11. Edward S. Knotek & Saeed Zaman, 2017. "Financial Nowcasts and Their Usefulness in Macroeconomic Forecasting," Working Papers (Old Series) 1702, Federal Reserve Bank of Cleveland.
    12. Frank Schorfheide & Dongho Song, 2015. "Real-Time Forecasting With a Mixed-Frequency VAR," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 366-380, July.
    13. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Real-time nowcasting with a Bayesian mixed frequency model with stochastic volatility," Working Papers (Old Series) 1227, Federal Reserve Bank of Cleveland.
    14. Fady Barsoum, 2015. "Point and Density Forecasts Using an Unrestricted Mixed-Frequency VAR Model," Working Paper Series of the Department of Economics, University of Konstanz 2015-19, Department of Economics, University of Konstanz.
    15. Robert Lehmann & Ida Wikman, 2022. "Quarterly GDP Estimates for the German States," ifo Working Paper Series 370, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    16. Libero Monteforte & Valentina Raponi, 2019. "Short‐term forecasts of economic activity: Are fortnightly factors useful?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(3), pages 207-221, April.
    17. Brave, Scott A. & Butters, R. Andrew & Justiniano, Alejandro, 2019. "Forecasting economic activity with mixed frequency BVARs," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1692-1707.
    18. Mawuli Segnon & Rangan Gupta & Stelios Bekiros & Mark E. Wohar, 2018. "Forecasting US GNP growth: The role of uncertainty," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 541-559, August.
    19. Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Working Paper 2013/06, Norges Bank.
    20. Anttonen, Jetro, 2018. "Nowcasting the Unemployment Rate in the EU with Seasonal BVAR and Google Search Data," ETLA Working Papers 62, The Research Institute of the Finnish Economy.
    21. Michael W. McCracken & Michael T. Owyang & Tatevik Sekhposyan, 2021. "Real-Time Forecasting and Scenario Analysis Using a Large Mixed-Frequency Bayesian VAR," International Journal of Central Banking, International Journal of Central Banking, vol. 17(71), pages 1-41, December.
    22. Stefan Bruder, 2014. "Comparing several methods to compute joint prediction regions for path forecasts generated by vector autoregressions," ECON - Working Papers 181, Department of Economics - University of Zurich, revised Dec 2015.
    23. Rachidi Kotchoni & Dalibor Stevanovic, 2020. "GDP Forecast Accuracy During Recessions," Working Papers 20-06, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    24. Laurent Ferrara & Matteo Mogliani & Jean-Guillaume Sahuc, 2020. "High-frequency monitoring of growth-at-risk," CAMA Working Papers 2020-97, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    25. Dufrénot, Gilles & Rhouzlane, Meryem & Vaccaro-Grange, Etienne, 2022. "Potential growth and natural yield curve in Japan," Journal of International Money and Finance, Elsevier, vol. 124(C).
    26. Jan Pablo Burgard & Matthias Neuenkirch & Matthias Nöckel, 2018. "State-Dependent Transmission of Monetary Policy in the Euro Area," CESifo Working Paper Series 7074, CESifo.
    27. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Reconciled Estimates of Monthly GDP in the US," Working Papers 22-01, Federal Reserve Bank of Cleveland.
    28. Fokin, Nikita, 2021. "The importance of modeling structural breaks in forecasting Russian GDP," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 63, pages 5-29.
    29. Ba Chu & Shafiullah Qureshi, 2021. "Comparing Out-of-Sample Performance of Machine Learning Methods to Forecast U.S. GDP Growth," Carleton Economic Papers 21-12, Carleton University, Department of Economics.
    30. Frank Schorfheide & Dongho Song, 2020. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," PIER Working Paper Archive 20-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    31. Boniface Yemba & Yi Duan & Nabaneeta Biswas, 2023. "Government spending news and stock price index," Economics Bulletin, AccessEcon, vol. 43(4), pages 1816-1841.
    32. Liu, Chang & Williams, Noah, 2019. "State-level implications of federal tax policies," Journal of Monetary Economics, Elsevier, vol. 105(C), pages 74-90.
    33. Antonello D’Agostino & Jacopo Cimadomo, 2015. "Combining time-variation and mixed-frequencies: an analysis of government spending multipliers in Italy," Working Papers 7, European Stability Mechanism.
    34. Florian, Huber & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2021. "Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs," Working Papers 2021-01, Joint Research Centre, European Commission.
    35. Rachidi Kotchoni & Dalibor Stevanovic, 2016. "Forecasting U.S. Recessions and Economic Activity," Working Papers hal-04141569, HAL.
    36. Andrew Martinez, 2017. "Testing for Differences in Path Forecast Accuracy: Forecast-Error Dynamics Matter," Working Papers (Old Series) 1717, Federal Reserve Bank of Cleveland.
    37. Martin Feldkircher & Florian Huber & Michael Pfarrhofer, 2020. "Measuring the Effectiveness of US Monetary Policy during the COVID-19 Recession," Papers 2007.15419, arXiv.org.
    38. Andrea Gazzani & Fabrizio Venditti & Giovanni Veronese, 2024. "Oil price shocks in real time," Temi di discussione (Economic working papers) 1448, Bank of Italy, Economic Research and International Relations Area.
    39. Jonas E. Arias & Minchul Shin, 2020. "Tracking U.S. Real GDP Growth During the Pandemic," Economic Insights, Federal Reserve Bank of Philadelphia, vol. 5(3), pages 9-14, September.
    40. Morita, Hiroshi & 森田, 裕史, 2019. "Forecasting Public Investment Using Daily Stock Returns," Discussion paper series HIAS-E-88, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    41. Lenza, Michele & Cimadomo, Jacopo & Giannone, Domenico & Monti, Francesca & Sokol, Andrej, 2021. "Nowcasting with Large Bayesian Vector Autoregressions," CEPR Discussion Papers 15854, C.E.P.R. Discussion Papers.
    42. Andrea Carriero & Galvao, Ana Beatriz & Kapetanios, George, 2016. "A comprehensive evaluation of macroeconomic forecasting methods," EMF Research Papers 10, Economic Modelling and Forecasting Group.
    43. Ramis Khabibullin & Sergei Seleznev, 2022. "Fast Estimation of Bayesian State Space Models Using Amortized Simulation-Based Inference," Papers 2210.07154, arXiv.org.
    44. Fabian Kr�ger & Todd E. Clark & Francesco Ravazzolo, 2015. "Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts," Working Papers No 8/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    45. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 141-194, Elsevier.
    46. Haroon Mumtaz & Konstantinos Theodoridis, 2017. "Fiscal Policy Shocks and Stock Prices in the United States," Working Papers 817, Queen Mary University of London, School of Economics and Finance.
    47. Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2019. "Forecasting daily electricity prices with monthly macroeconomic variables," Working Paper Series 2250, European Central Bank.
    48. Shang, Yuhuang & Zheng, Tingguo, 2018. "Fitting and forecasting yield curves with a mixed-frequency affine model: Evidence from China," Economic Modelling, Elsevier, vol. 68(C), pages 145-154.
    49. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    50. Deborah Gefang & Gary Koop & Aubrey Poon, 2020. "Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-07, Economic Statistics Centre of Excellence (ESCoE).
    51. Christiane Baumeister & Lutz Kilian, 2013. "What Central Bankers Need to Know about Forecasting Oil Prices," Staff Working Papers 13-15, Bank of Canada.
    52. Bacchiocchi, Emanuele & Bastianin, Andrea & Missale, Alessandro & Rossi, Eduardo, 2016. "Structural analysis with mixed frequencies: monetary policy, uncertainty and gross capital flows," Working Papers 2016-04, Joint Research Centre, European Commission.
    53. Frank Schorfheide & Dongho Song & Amir Yaron, 2014. "Identifying Long-Run Risks: A Bayesian Mixed-Frequency Approach," NBER Working Papers 20303, National Bureau of Economic Research, Inc.
    54. Ankargren Sebastian & Unosson Måns & Yang Yukai, 2020. "A Flexible Mixed-Frequency Vector Autoregression with a Steady-State Prior," Journal of Time Series Econometrics, De Gruyter, vol. 12(2), pages 1-41, July.
    55. Daniel Hopp, 2022. "Benchmarking Econometric and Machine Learning Methodologies in Nowcasting," Papers 2205.03318, arXiv.org.
    56. Meyer-Gohde, Alexander & Shabalina, Ekaterina, 2022. "Estimation and forecasting using mixed-frequency DSGE models," IMFS Working Paper Series 175, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    57. Guy P. Nason & Ben Powell & Duncan Elliott & Paul A. Smith, 2017. "Should we sample a time series more frequently?: decision support via multirate spectrum estimation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(2), pages 353-407, February.
    58. Thomas B. Götz & Alain W. Hecq, 2019. "Granger Causality Testing in Mixed‐Frequency VARs with Possibly (Co)Integrated Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 40(6), pages 914-935, November.
    59. Paul Ho, 2021. "Forecasting in the Absence of Precedent," Working Paper 21-10, Federal Reserve Bank of Richmond.
    60. Canova, Fabio & Ferroni, Filippo, 2020. "A hitchhiker guide to empirical macro models," CEPR Discussion Papers 15446, C.E.P.R. Discussion Papers.
    61. Qiu, Yue, 2020. "Forecasting the Consumer Confidence Index with tree-based MIDAS regressions," Economic Modelling, Elsevier, vol. 91(C), pages 247-256.
    62. Claudia Foroni & Francesco Ravazzolo & Luca Rossini, 2020. "Are low frequency macroeconomic variables important for high frequency electricity prices?," Papers 2007.13566, arXiv.org, revised Dec 2022.
    63. Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
    64. Heinisch Katja & Scheufele Rolf, 2019. "Should Forecasters Use Real-Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, De Gruyter, vol. 20(4), pages 170-200, December.
    65. Pirschel, Inske, 2016. "Forecasting euro area recessions in real-time," Kiel Working Papers 2020, Kiel Institute for the World Economy (IfW Kiel).
    66. William Barnett & Marcelle Chauvetz & Danilo Leiva-Leonx, 2014. "Real-Time Nowcasting Nominal GDP Under Structural Break," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201313, University of Kansas, Department of Economics, revised Feb 2014.
    67. William Barnett & Hyun Park, 2023. "Have Credit Card Services Become Important to Monetary Aggregation? An Application of Sign Restricted Bayesian VAR," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202304, University of Kansas, Department of Economics.
    68. Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 615-643, August.
    69. John Cotter & Mark Hallam & Kamil Yilmaz, 2020. "Macro-Financial Spillovers," Working Papers 202005, Geary Institute, University College Dublin.
    70. Enrique M. Quilis, 2018. "Temporal disaggregation of economic time series: The view from the trenches," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(4), pages 447-470, November.
    71. Boriss Siliverstovs, 2019. "Assessing Nowcast Accuracy of US GDP Growth in Real Time: The Role of Booms and Busts," Working Papers 2019/01, Latvijas Banka.
    72. Bańbura, Marta & Belousova, Irina & Bodnár, Katalin & Tóth, Máté Barnabás, 2023. "Nowcasting employment in the euro area," Working Paper Series 2815, European Central Bank.
    73. Erlan Konebayev, 2023. "Forecasting a Commodity-Exporting Small Open Developing Economy Using DSGE and DSGE-BVAR," International Economic Journal, Taylor & Francis Journals, vol. 37(1), pages 39-70, January.
    74. Yasutomo Murasawa, 2016. "The Beveridge–Nelson decomposition of mixed-frequency series," Empirical Economics, Springer, vol. 51(4), pages 1415-1441, December.
    75. Robert Lehmann & Ida Wikman, 2023. "Eine Analyse der Konjunkturzyklen für die deutschen Bundesländer," ifo Dresden berichtet, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 30(02), pages 15-21, April.
    76. Foroni, Claudia & Marcellino, Massimiliano & Stevanović, Dalibor, 2018. "Mixed frequency models with MA components," Discussion Papers 02/2018, Deutsche Bundesbank.
    77. Tino Berger & James Morley & Benjamin Wong, 2020. "Nowcasting the output gap," CAMA Working Papers 2020-78, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    78. Götz, Thomas B. & Hecq, Alain & Smeekes, Stephan, 2015. "Testing for Granger causality in large mixed-frequency VARs," Discussion Papers 45/2015, Deutsche Bundesbank.
    79. Bacchiocchi, Emanuele & Bastianin, Andrea & Missale, Alessandro & Rossi, Eduardo, 2020. "Structural analysis with mixed-frequency data: A model of US capital flows," Economic Modelling, Elsevier, vol. 89(C), pages 427-443.
    80. Kenneth Beauchemin, 2013. "A 14-Variable Mixed-Frequency VAR Model," Staff Report 493, Federal Reserve Bank of Minneapolis.
    81. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2020. "Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(2), pages 176-197, March.
    82. Ghysels, Eric, 2016. "Macroeconomics and the reality of mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 294-314.
    83. Marek Rusnak, 2013. "Nowcasting Czech GDP in Real Time," Working Papers 2013/06, Czech National Bank.
    84. Dudda, Tom L. & Klein, Tony & Nguyen, Duc Khuong & Walther, Thomas, 2022. "Common Drivers of Commodity Futures?," QBS Working Paper Series 2022/05, Queen's University Belfast, Queen's Business School.
    85. Luca Barbaglia & Lorenzo Frattarolo & Niko Hauzenberger & Dominik Hirschbuehl & Florian Huber & Luca Onorante & Michael Pfarrhofer & Luca Tiozzo Pezzoli, 2024. "Nowcasting economic activity in European regions using a mixed-frequency dynamic factor model," Papers 2401.10054, arXiv.org.
    86. Ankargren, Sebastian & Jonéus, Paulina, 2021. "Simulation smoothing for nowcasting with large mixed-frequency VARs," Econometrics and Statistics, Elsevier, vol. 19(C), pages 97-113.
    87. Iacopini, Matteo & Poon, Aubrey & Rossini, Luca & Zhu, Dan, 2023. "Bayesian mixed-frequency quantile vector autoregression: Eliciting tail risks of monthly US GDP," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    88. Michal Franta & David Havrlant & Marek Rusnak, 2014. "Forecasting Czech GDP Using Mixed-Frequency Data Models," Working Papers 2014/08, Czech National Bank.
    89. Dmytro Krukovets & Olesia Verchenko, 2019. "Short-Run Forecasting of Core Inflation in Ukraine: a Combined ARMA Approach," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 248, pages 11-20.
    90. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
    91. Qian, Hang, 2016. "A computationally efficient method for vector autoregression with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 433-437.
    92. Sergio Afonso Lago Alves & Angelo Marsiglia Fasolo, 2015. "Not Just Another Mixed Frequency Paper," Working Papers Series 400, Central Bank of Brazil, Research Department.
    93. Thomas B Götz & Klemens Hauzenberger, 2021. "Large mixed-frequency VARs with a parsimonious time-varying parameter structure," The Econometrics Journal, Royal Economic Society, vol. 24(3), pages 442-461.
    94. Edward S. Knotek & Saeed Zaman, 2017. "Nowcasting U.S. Headline and Core Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 931-968, August.
    95. Schmidt, Torsten & Barabas, György & Benner, Niklas & Blagov, Boris & Dirks, Maximilian & Grozea-Helmenstein, Daniela & Isaak, Niklas & Jessen, Robin & Kirsch, Florian & Schacht, Philip & Weyerstrass,, 2023. "Frühjahr 2023: Kaufkraftentzug bremst die konjunkturelle Erholung in Deutschland," RWI Konjunkturberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, vol. 74(1), pages 5-45.
    96. David Alaminos & M. Belén Salas & Manuel A. Fernández-Gámez, 2022. "Quantum Computing and Deep Learning Methods for GDP Growth Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 803-829, February.
    97. Nicolo Maffei-Faccioli & Eugenia Vella, 2021. "Does Immigration Grow the Pie? Asymmetric Evidence from Germany," DEOS Working Papers 2105, Athens University of Economics and Business.
    98. Gary Koop & Stuart McIntyre & James Mitchell, 2018. "UK Regional Nowcasting using a Mixed Frequency Vector Autoregressive Model," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-07, Economic Statistics Centre of Excellence (ESCoE).
    99. Anastasiou, Dimitrios & Drakos, Konstantinos, 2021. "European depositors’ behavior and crisis sentiment," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 117-136.
    100. Hassani, Hossein & Rua, António & Silva, Emmanuel Sirimal & Thomakos, Dimitrios, 2019. "Monthly forecasting of GDP with mixed-frequency multivariate singular spectrum analysis," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1263-1272.
    101. Baumeister, Christiane & Guérin, Pierre & Kilian, Lutz, 2015. "Do high-frequency financial data help forecast oil prices? The MIDAS touch at work," International Journal of Forecasting, Elsevier, vol. 31(2), pages 238-252.
    102. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2020. "Nowcasting Norwegian household consumption with debit card transaction data," Working Paper 2020/17, Norges Bank.
    103. Alain Hecq & Marie Ternes & Ines Wilms, 2021. "Hierarchical Regularizers for Mixed-Frequency Vector Autoregressions," Papers 2102.11780, arXiv.org, revised Mar 2022.
    104. Stankevich, Ivan, 2023. "Application of Markov-Switching MIDAS models to nowcasting of GDP and its components," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 70, pages 122-143.
    105. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    106. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    107. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    108. William A. Barnett & Marcelle Chauvet & Danilo Leiva-Leon, 2014. "Real-Time Nowcasting of Nominal GDP Under Structural Breaks," Staff Working Papers 14-39, Bank of Canada.
    109. Jian Chai & Puju Cao & Xiaoyang Zhou & Kin Keung Lai & Xiaofeng Chen & Siping (Sue) Su, 2018. "The Conductive and Predictive Effect of Oil Price Fluctuations on China’s Industry Development Based on Mixed-Frequency Data," Energies, MDPI, vol. 11(6), pages 1-14, May.
    110. McElroy, Tucker S. & Wildi, Marc, 2020. "The Multivariate Linear Prediction Problem: Model-Based and Direct Filtering Solutions," Econometrics and Statistics, Elsevier, vol. 14(C), pages 112-130.
    111. Paul Labonne, 2022. "Asymmetric Uncertainty: Nowcasting Using Skewness in Real-time Data," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-23, Economic Statistics Centre of Excellence (ESCoE).
    112. Mertens, Karel, 2019. "State-level implications of federal tax policies: Comments," Journal of Monetary Economics, Elsevier, vol. 105(C), pages 91-93.
    113. Blagov, Boris & Döhrn, Roland & Grozea-Helmenstein, Daniela & Jäger, Philipp & Micheli, Martin & Weyerstrass, Klaus, 2020. "Die wirtschaftliche Entwicklung im Ausland: COVID-19 hält Weltkonjunktur in Atem," RWI Konjunkturberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, vol. 71(1), pages 5-40.
    114. Yemba, Boniface P. & Otunuga, Olusegun Michael & Tang, Biyan & Biswas, Nabaneeta, 2023. "Nowcasting of the Short-run Euro-Dollar Exchange Rate with Economic Fundamentals and Time-varying Parameters," Finance Research Letters, Elsevier, vol. 52(C).
    115. 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.
    116. Heinrich, Markus, 2020. "Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach," EconStor Preprints 219312, ZBW - Leibniz Information Centre for Economics.
    117. Ali B. Barlas & Seda Guler Mert & Berk Orkun Isa & Alvaro Ortiz & Tomasa Rodrigo & Baris Soybilgen & Ege Yazgan, 2021. "Big Data Information and Nowcasting: Consumption and Investment from Bank Transactions in Turkey," Papers 2107.03299, arXiv.org.
    118. Barnett, William A. & Chauvet, Marcelle & Leiva-Leon, Danilo, 2016. "Real-time nowcasting of nominal GDP with structural breaks," Journal of Econometrics, Elsevier, vol. 191(2), pages 312-324.
    119. Tony Chernis & Rodrigo Sekkel, 2018. "Nowcasting Canadian Economic Activity in an Uncertain Environment," Discussion Papers 18-9, Bank of Canada.
    120. Qian, Hang, 2013. "Vector Autoregression with Mixed Frequency Data," MPRA Paper 47856, University Library of Munich, Germany.
    121. Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023. "High-dimensional conditionally Gaussian state space models with missing data," Journal of Econometrics, Elsevier, vol. 236(1).
    122. Zeyyad Mandalinci, 2015. "Effects of Monetary Policy Shocks on UK Regional Activity: A Constrained MFVAR Approach," Working Papers 758, Queen Mary University of London, School of Economics and Finance.
    123. Dhaene, Geert & Wu, Jianbin, 2020. "Incorporating overnight and intraday returns into multivariate GARCH volatility models," Journal of Econometrics, Elsevier, vol. 217(2), pages 471-495.
    124. Götz, Thomas B. & Hauzenberger, Klemens, 2018. "Large mixed-frequency VARs with a parsimonious time-varying parameter structure," Discussion Papers 40/2018, Deutsche Bundesbank.
    125. Marcellino, Massimiliano & Foroni, Claudia, 2014. "Markov-Switching Mixed-Frequency VAR Models," CEPR Discussion Papers 9815, C.E.P.R. Discussion Papers.
    126. Serena Ng & Susannah Scanlan, 2023. "Constructing High Frequency Economic Indicators by Imputation," Papers 2303.01863, arXiv.org, revised Oct 2023.
    127. Alain Hecq & Marie Ternes & Ines Wilms, 2023. "Hierarchical Regularizers for Reverse Unrestricted Mixed Data Sampling Regressions," Papers 2301.10592, arXiv.org.
    128. Ba Chu & Shafiullah Qureshi, 2023. "Comparing Out-of-Sample Performance of Machine Learning Methods to Forecast U.S. GDP Growth," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1567-1609, December.
    129. Eraslan, Sercan & Schröder, Maximilian, 2019. "Nowcasting GDP with a large factor model space," Discussion Papers 41/2019, Deutsche Bundesbank.
    130. John Cotter & Mark Hallam & Kamil Yilmaz, 2017. "Mixed-frequency macro-financial spillovers," Working Papers 201704, Geary Institute, University College Dublin.
    131. Barbaglia, Luca & Frattarolo, Lorenzo & Onorante, Luca & Pericoli, Filippo Maria & Ratto, Marco & Tiozzo Pezzoli, Luca, 2022. "Testing big data in a big crisis: Nowcasting under COVID-19," Working Papers 2022-06, Joint Research Centre, European Commission.
    132. L. Vanessa Smith & Nori Tarui & Takashi Yamagata, 2020. "Global fossil fuel consumption and carbon pricing: Forecasting and counterfactual analysis under alternative GDP scenarios," RIEEM Discussion Paper Series 2004, Research Institute for Environmental Economics and Management, Waseda University.
    133. Stefan Neuwirth, 2017. "Time-varying mixed frequency forecasting: A real-time experiment," KOF Working papers 17-430, KOF Swiss Economic Institute, ETH Zurich.
    134. Robert Lehmann, 2023. "READ-GER: Introducing German Real-Time Regional Accounts Data for Revision Analysis and Nowcasting," CESifo Working Paper Series 10315, CESifo.
    135. Heinisch, Katja, 2016. "A real-time analysis on the importance of hard and soft data for nowcasting German GDP," VfS Annual Conference 2016 (Augsburg): Demographic Change 145864, Verein für Socialpolitik / German Economic Association.
    136. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
    137. Mertens, Elmar, 2023. "Precision-based sampling for state space models that have no measurement error," Journal of Economic Dynamics and Control, Elsevier, vol. 154(C).
    138. Piergiorgio Alessandri & Andrea Gazzani & Alejandro Vicondoa, 2023. "Are the Effects of Uncertainty Shocks Big or Small?," Working Papers 244, Red Nacional de Investigadores en Economía (RedNIE).
    139. Claudia Foroni & Massimiliano Marcellino, 2014. "Mixed frequency structural VARs," Working Paper 2014/01, Norges Bank.
    140. Giusto Andrea & İşcan Talan B., 2018. "The Rescaled VAR Model with an Application to Mixed-Frequency Macroeconomic Forecasting," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(4), pages 1-16, September.
    141. Ling Lin & Qiumei Li & Jin Li & Zuominyang Zhang & Xuan Zhong, 2023. "Industry Volatility and Employment Extreme Risk Transmission: Evidence from China," Sustainability, MDPI, vol. 15(17), pages 1-22, August.
    142. Bent Jesper Christensen & Olaf Posch & Michel van der Wel, 2014. "Estimating Dynamic Equilibrium Models Using Mixed Frequency Macro and Financial Data," CESifo Working Paper Series 5030, CESifo.
    143. Pirschel, Inske, 2015. "Forecasting Euro Area Recessions in real-time with a mixed-frequency Bayesian VAR," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113031, Verein für Socialpolitik / German Economic Association.
    144. Dieppe, Alistair & van Roye, Björn & Legrand, Romain, 2016. "The BEAR toolbox," Working Paper Series 1934, European Central Bank.
    145. Jürgen Antony & D. Broer, 2015. "Euro area financial shocks and economic activity in The Netherlands," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 42(3), pages 571-595, August.
    146. Heiner Mikosch & Ying Zhang, 2014. "Forecasting Chinese GDP Growth with Mixed Frequency Data," KOF Working papers 14-359, KOF Swiss Economic Institute, ETH Zurich.
    147. Sebastian Ankargren & Måns Unosson & Yukai Yang, 2018. "A mixed-frequency Bayesian vector autoregression with a steady-state prior," CREATES Research Papers 2018-32, Department of Economics and Business Economics, Aarhus University.
    148. Homolka, Lubor & Ngo, Vu Minh & Pavelková, Drahomíra & Le, Bach Tuan & Dehning, Bruce, 2020. "Short- and medium-term car registration forecasting based on selected macro and socio-economic indicators in European countries," Research in Transportation Economics, Elsevier, vol. 80(C).
    149. Nataliia Ostapenko, 2022. "Do output gap estimates improve inflation forecasts in Slovakia?," Working and Discussion Papers WP 4/2022, Research Department, National Bank of Slovakia.
    150. Ruey Yau & C. James Hueng, 2019. "Nowcasting GDP Growth for Small Open Economies with a Mixed-Frequency Structural Model," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 177-198, June.
    151. Jan P.A.M. Jacobs & Samad Sarferaz & Simon van Norden & Jan-Egbert Sturm, 2013. "Modeling Multivariate Data Revisions," CIRANO Working Papers 2013s-44, CIRANO.
    152. Trujillo-Barrera, Andres & Pennings, Joost M.E., 2013. "Energy and Food Commodity Prices Linkage: An Examination with Mixed-Frequency Data," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150465, Agricultural and Applied Economics Association.
    153. Consolo, Agostino & Foroni, Claudia & Martínez Hernández, Catalina, 2021. "A mixed frequency BVAR for the euro area labour market," Working Paper Series 2601, European Central Bank.
    154. Yun-Yeong Kim, 2016. "Dynamic Analyses Using VAR Model with Mixed Frequency Data through Observable Representation," Korean Economic Review, Korean Economic Association, vol. 32, pages 41-75.
    155. Leippold, Markus & Yang, Hanlin, 2019. "Particle filtering, learning, and smoothing for mixed-frequency state-space models," Econometrics and Statistics, Elsevier, vol. 12(C), pages 25-41.

  15. S. Boragan Aruoba & Francis X. Diebold & Jeremy J. Nalewaik & Frank Schorfheide & Dongho Song, 2011. "Improving GDP measurement: a forecast combination perspective," Working Papers 11-41, Federal Reserve Bank of Philadelphia.

    Cited by:

    1. Jeremy J. Nalewaik, 2014. "Missing Variation in the Great Moderation: Lack of Signal Error and OLS Regression," Finance and Economics Discussion Series 2014-27, Board of Governors of the Federal Reserve System (U.S.).
    2. Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 147-170, National Bureau of Economic Research, Inc.
    3. Aruoba, S. Borağan & Diebold, Francis X. & Nalewaik, Jeremy & Schorfheide, Frank & Song, Dongho, 2016. "Improving GDP measurement: A measurement-error perspective," Journal of Econometrics, Elsevier, vol. 191(2), pages 384-397.
    4. Tom Stark, 2014. "Real-time performance of GDPplus and alternative model-based measures of GDP: 2005—2014," Research Rap Special Report, Federal Reserve Bank of Philadelphia, issue Nov.
    5. Francis X. Diebold & Minchul Shin, 2017. "Beating the Simple Average: Egalitarian LASSO for Combining Economic Forecasts," PIER Working Paper Archive 17-017, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 20 Aug 2017.
    6. Diebold, Francis X. & Shin, Minchul, 2019. "Machine learning for regularized survey forecast combination: Partially-egalitarian LASSO and its derivatives," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1679-1691.
    7. Cobb, Marcus P A, 2018. "Improving Underlying Scenarios for Aggregate Forecasts: A Multi-level Combination Approach," MPRA Paper 88593, University Library of Munich, Germany.
    8. James Bishop & Troy Gill & David Lancaster, 2013. "GDP Revisions: Measurement and Implications," RBA Bulletin (Print copy discontinued), Reserve Bank of Australia, pages 11-22, March.
    9. Mary C. Daly & John G. Fernald & Òscar Jordà & Fernanda Nechio, 2013. "Shocks and Adjustments," Working Paper Series 2013-32, Federal Reserve Bank of San Francisco.
    10. Marius Cristian Acatrinei, 2020. "Financial stability indicator for non-banking markets," Journal of Financial Studies, Institute of Financial Studies, vol. 9(5), pages 3-9, November.
    11. Jan P.A.M. Jacobs & Samad Sarferaz & Simon van Norden & Jan-Egbert Sturm, 2013. "Modeling Multivariate Data Revisions," CIRANO Working Papers 2013s-44, CIRANO.

Articles

  1. Bianchi, Francesco & Bianchi, Giada & Song, Dongho, 2023. "The long-term impact of the COVID-19 unemployment shock on life expectancy and mortality rates," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    See citations under working paper version above.
  2. Augustin, P. & Chernov, M. & Schmid, L. & Song, D., 2021. "Benchmark interest rates when the government is risky," Journal of Financial Economics, Elsevier, vol. 140(1), pages 74-100.
    See citations under working paper version above.
  3. Bansal, Ravi & Miller, Shane & Song, Dongho & Yaron, Amir, 2021. "The term structure of equity risk premia," Journal of Financial Economics, Elsevier, vol. 142(3), pages 1209-1228.
    See citations under working paper version above.
  4. Frank Schorfheide & Dongho Song & Amir Yaron, 2018. "Identifying Long‐Run Risks: A Bayesian Mixed‐Frequency Approach," Econometrica, Econometric Society, vol. 86(2), pages 617-654, March.
    See citations under working paper version above.
  5. Dongho Song, 2017. "Bond Market Exposures to Macroeconomic and Monetary Policy Risks," The Review of Financial Studies, Society for Financial Studies, vol. 30(8), pages 2761-2817.
    See citations under working paper version above.
  6. Aruoba, S. Borağan & Diebold, Francis X. & Nalewaik, Jeremy & Schorfheide, Frank & Song, Dongho, 2016. "Improving GDP measurement: A measurement-error perspective," Journal of Econometrics, Elsevier, vol. 191(2), pages 384-397.
    See citations under working paper version above.
  7. Frank Schorfheide & Dongho Song, 2015. "Real-Time Forecasting With a Mixed-Frequency VAR," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 366-380, July.
    See citations under working paper version above.Sorry, no citations of articles recorded.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.