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Mu-Chun Wang

Personal Details

First Name:Mu-Chun
Middle Name:
Last Name:Wang
Suffix:
RePEc Short-ID:pwa572
[This author has chosen not to make the email address public]

Affiliation

Deutsche Bundesbank

Frankfurt, Germany
http://www.bundesbank.de/
RePEc:edi:dbbgvde (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Loria, Francesca & Matthes, Christian & Wang, Mu-Chun, 2021. "Economic theories and macroeconomic reality," Discussion Papers 56/2021, Deutsche Bundesbank.
  2. Juan Carlos Parra-Alvarez & Olaf Posch & Mu-Chun Wang, 2020. "Estimation of heterogeneous agent models: A likelihood approach," CREATES Research Papers 2020-05, Department of Economics and Business Economics, Aarhus University.
  3. Wang, Mu-Chun, 2018. "Choosing Prior Hyperparameters: With Applications To Time-Varying Parameter Models," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181621, Verein für Socialpolitik / German Economic Association.
  4. Juan Carlos Parra-Alvarez & Olaf Posch & Mu-Chun Wang, 2017. "Identification and estimation of heterogeneous agent models: A likelihood approach," CREATES Research Papers 2017-35, Department of Economics and Business Economics, Aarhus University.
  5. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2016. "Choosing Prior Hyperparameters," Working Paper 16-9, Federal Reserve Bank of Richmond.
  6. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2015. "Measurement Errors and Monetary Policy: Then and Now," Working Paper 15-13, Federal Reserve Bank of Richmond.
  7. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2014. "Drifts, Volatilities, and Impulse Responses Over the Last Century," Working Paper 14-10, Federal Reserve Bank of Richmond.
  8. Wang, Mu-Chun, 2008. "Comparing the DSGE model with the factor model: an out-of-sample forecasting experiment," Discussion Paper Series 1: Economic Studies 2008,04, Deutsche Bundesbank.

Articles

  1. Loria, Francesca & Matthes, Christian & Wang, Mu-Chun, 2022. "Economic theories and macroeconomic reality," Journal of Monetary Economics, Elsevier, vol. 126(C), pages 105-117.
  2. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2020. "Choosing Prior Hyperparameters: With Applications to Time-Varying Parameter Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 124-136, January.
  3. Amir-Ahmadi, Pooyan & Matthes, Christian & Wang, Mu-Chun, 2017. "Measurement errors and monetary policy: Then and now," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 66-78.
  4. 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.
  5. Matei Demetrescu & Mu-Chun Wang, 2014. "Incorporating Asymmetric Preferences into Fan Charts and Path Forecasts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 287-297, April.
  6. Matthes, Christian & Wang, Mu-Chun, 2012. "What drives inflation in New Keynesian models?," Economics Letters, Elsevier, vol. 114(3), pages 338-342.
  7. Mu-Chun Wang, 2009. "Comparing the DSGE model with the factor model: an out-of-sample forecasting experiment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(2), pages 167-182.

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.

Working papers

  1. Loria, Francesca & Matthes, Christian & Wang, Mu-Chun, 2021. "Economic theories and macroeconomic reality," Discussion Papers 56/2021, Deutsche Bundesbank.

    Cited by:

    1. Knut Are Aastveit & Jamie Cross & Francesco Furlanetto & Herman K. Van Dijk, 2024. "Taylor Rules with Endogenous Regimes," Tinbergen Institute Discussion Papers 24-030/III, Tinbergen Institute.
    2. Joshua Chan & Eric Eisenstat & Xuewen Yu, 2022. "Large Bayesian VARs with Factor Stochastic Volatility: Identification, Order Invariance and Structural Analysis," Papers 2207.03988, arXiv.org.
    3. Joshua C. C. Chan, 2022. "Asymmetric conjugate priors for large Bayesian VARs," Quantitative Economics, Econometric Society, vol. 13(3), pages 1145-1169, July.
    4. KANO, Takashi, 2023. "Posterior Inferences on Incomplete Structural Models : The Minimal Econometric Interpretation," Discussion paper series HIAS-E-128, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.

  2. Juan Carlos Parra-Alvarez & Olaf Posch & Mu-Chun Wang, 2020. "Estimation of heterogeneous agent models: A likelihood approach," CREATES Research Papers 2020-05, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Khieu, Hoang & Wälde, Klaus, 2018. "Capital Income Risk and the Dynamics of the Wealth Distribution," IZA Discussion Papers 11840, Institute of Labor Economics (IZA).
    2. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2020. "Wild Bootstrap and Asymptotic Inference with Multiway Clustering," CREATES Research Papers 2020-06, Department of Economics and Business Economics, Aarhus University.
    3. Lukasz Balbus & Pawel Dziewulski & Kevin Reffett & Lukasz Wozny, 2020. "Markov distributional equilibrium dynamics in games with complementarities and no aggregate risk," KAE Working Papers 2020-052, Warsaw School of Economics, Collegium of Economic Analysis.
    4. Juan Carlos Parra-Alvarez & Olaf Posch & Mu-Chun Wang, 2020. "Estimation of heterogeneous agent models: A likelihood approach," CREATES Research Papers 2020-05, Department of Economics and Business Economics, Aarhus University.
    5. Yves Achdou & Jiequn Han & Jean-Michel Lasry & Pierre-Louis Lions & Benjamin Moll, 2017. "Income and Wealth Distribution in Macroeconomics: A Continuous-Time Approach," NBER Working Papers 23732, National Bureau of Economic Research, Inc.
    6. Laura Liu & Mikkel Plagborg-M?ller, 2021. "Full-Information Estimation of Heterogeneous Agent Models Using Macro and Micro Data," CAEPR Working Papers 2021-001 Classification- , Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    7. Fischer, Thomas, 2019. "Determinants of Wealth Inequality and Mobility in General Equilibrium," Working Papers 2019:22, Lund University, Department of Economics.
    8. Laura Liu & Mikkel Plagborg‐Møller, 2023. "Full‐information estimation of heterogeneous agent models using macro and micro data," Quantitative Economics, Econometric Society, vol. 14(1), pages 1-35, January.
    9. Glawion, Rene & Puche, Marc & Haller, Frédéric, 2020. "A General Equilibrium Model of Earnings, Income, and Wealth," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224580, Verein für Socialpolitik / German Economic Association.

  3. Wang, Mu-Chun, 2018. "Choosing Prior Hyperparameters: With Applications To Time-Varying Parameter Models," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181621, Verein für Socialpolitik / German Economic Association.

    Cited by:

    1. Peersman, Gert & Rüth, Sebastian K. & Van der Veken, Wouter, 2019. "The interplay between oil and food commodity prices: Has It changed over time?," Working Papers 0665, University of Heidelberg, Department of Economics.
    2. Rui Xiong & Wenting Liao & Rangan Gupta, 2024. "Reassessing the Macroeconomic Effects of Aggregate Skewness: A Time-Varying Perspective," Working Papers 202430, University of Pretoria, Department of Economics.
    3. Wenting Liao & Jun Ma & Chengsi Zhang, 2023. "Identifying exchange rate effects and spillovers of US monetary policy shocks in the presence of time‐varying instrument relevance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(7), pages 989-1006, November.
    4. 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.
    5. Korobilis, Dimitris & Koop, Gary, 2020. "Bayesian dynamic variable selection in high dimensions," MPRA Paper 100164, University Library of Munich, Germany.
    6. Haroon Mumtaz & Katerina Petrova, 2023. "Changing Impact of Shocks: A Time‐Varying Proxy SVAR Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(2-3), pages 635-654, March.
    7. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    8. Jamie L. Cross & Aubrey Poon, 2020. "On the contribution of international shocks in Australian business cycle fluctuations," Empirical Economics, Springer, vol. 59(6), pages 2613-2637, December.
    9. Jin-Seong Choi & So-Won Choi & Eul-Bum Lee, 2023. "Modeling of Predictive Maintenance Systems for Laser-Welders in Continuous Galvanizing Lines Based on Machine Learning with Welder Control Data," Sustainability, MDPI, vol. 15(9), pages 1-28, May.
    10. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    11. Prüser, Jan, 2021. "The horseshoe prior for time-varying parameter VARs and Monetary Policy," Journal of Economic Dynamics and Control, Elsevier, vol. 129(C).
    12. Korobilis, D, 2017. "Forecasting with many predictors using message passing algorithms," Essex Finance Centre Working Papers 19565, University of Essex, Essex Business School.
    13. Jan Prüser & Alexander Schlösser, 2020. "The effects of economic policy uncertainty on European economies: evidence from a TVP-FAVAR," Empirical Economics, Springer, vol. 58(6), pages 2889-2910, June.
    14. Gabriel Arce‐Alfaro & Boris Blagov, 2023. "Monetary Policy Uncertainty and Inflation Expectations," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(1), pages 70-94, February.
    15. Prüser, Jan & Schlösser, Alexander, 2018. "On the time-varying effects of economic policy uncertainty on the US economy," Ruhr Economic Papers 761, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    16. Jonas E. Arias & Juan F. Rubio-Ramirez & Minchul Shin, 2021. "Macroeconomic Forecasting and Variable Ordering in Multivariate Stochastic Volatility Models," Working Papers 21-21, Federal Reserve Bank of Philadelphia.
    17. 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.
    18. Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
    19. Philippe Goulet Coulombe, 2024. "The macroeconomy as a random forest," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(3), pages 401-421, April.
    20. Philippe Goulet Coulombe, 2021. "The Macroeconomy as a Random Forest," Working Papers 21-05, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    21. Hartwig, Benny, 2020. "Robust Inference in Time-Varying Structural VAR Models: The DC-Cholesky Multivariate Stochastic Volatility Model," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224528, Verein für Socialpolitik / German Economic Association.
    22. Chan, Joshua C.C., 2021. "Minnesota-type adaptive hierarchical priors for large Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1212-1226.
    23. Korobilis, Dimitris & Landau, Bettina & Musso, Alberto & Phella, Anthoulla, 2021. "The time-varying evolution of inflation risks," Working Paper Series 2600, European Central Bank.
    24. Jacobi Liana & Kwok Chun Fung & Ramírez-Hassan Andrés & Nghiem Nhung, 2024. "Posterior Manifolds over Prior Parameter Regions: Beyond Pointwise Sensitivity Assessments for Posterior Statistics from MCMC Inference," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(2), pages 403-434, April.
    25. So-Won Choi & Eul-Bum Lee, 2022. "Contractor’s Risk Analysis of Engineering Procurement and Construction (EPC) Contracts Using Ontological Semantic Model and Bi-Long Short-Term Memory (LSTM) Technology," Sustainability, MDPI, vol. 14(11), pages 1-32, June.
    26. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
    27. Su Jin Choi & So Won Choi & Jong Hyun Kim & Eul-Bum Lee, 2021. "AI and Text-Mining Applications for Analyzing Contractor’s Risk in Invitation to Bid (ITB) and Contracts for Engineering Procurement and Construction (EPC) Projects," Energies, MDPI, vol. 14(15), pages 1-28, July.
    28. Philippe Goulet Coulombe, 2020. "Time-Varying Parameters as Ridge Regressions," Papers 2009.00401, arXiv.org, revised Apr 2023.
    29. Huachen Li, 2023. "The Time‐Varying Response of Hours Worked to a Productivity Shock," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(7), pages 1907-1935, October.
    30. Arce-Alfaro, Gabriel & Blagov, Boris, 2021. "Monetary policy uncertainty and inflation expectations," Ruhr Economic Papers 899, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.

  4. Juan Carlos Parra-Alvarez & Olaf Posch & Mu-Chun Wang, 2017. "Identification and estimation of heterogeneous agent models: A likelihood approach," CREATES Research Papers 2017-35, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Yves Achdou & Jiequn Han & Jean-Michel Lasry & Pierre-Louis Lionse & Benjamin Moll, 2022. "Income and Wealth Distribution in Macroeconomics: A Continuous-Time Approach," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(1), pages 45-86.
    2. Khieu, Hoang & Wälde, Klaus, 2018. "Capital Income Risk and the Dynamics of the Wealth Distribution," IZA Discussion Papers 11840, Institute of Labor Economics (IZA).
    3. Achdou, Yves & Han, Jiequn & Lasry, Jean Michel & Lions, Pierre Louis & Moll, Ben, 2022. "Income and wealth distribution in macroeconomics: a continuous-time approach," LSE Research Online Documents on Economics 107422, London School of Economics and Political Science, LSE Library.
    4. Lukasz Balbus & Pawel Dziewulski & Kevin Reffett & Lukasz Wozny, 2020. "Markov distributional equilibrium dynamics in games with complementarities and no aggregate risk," KAE Working Papers 2020-052, Warsaw School of Economics, Collegium of Economic Analysis.
    5. Juan Carlos Parra-Alvarez & Olaf Posch & Mu-Chun Wang, 2020. "Estimation of heterogeneous agent models: A likelihood approach," CREATES Research Papers 2020-05, Department of Economics and Business Economics, Aarhus University.
    6. Yves Achdou & Jiequn Han & Jean-Michel Lasry & Pierre-Louis Lions & Benjamin Moll, 2017. "Income and Wealth Distribution in Macroeconomics: A Continuous-Time Approach," NBER Working Papers 23732, National Bureau of Economic Research, Inc.
    7. Glawion, Rene & Puche, Marc & Haller, Frédéric, 2020. "A General Equilibrium Model of Earnings, Income, and Wealth," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224580, Verein für Socialpolitik / German Economic Association.

  5. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2016. "Choosing Prior Hyperparameters," Working Paper 16-9, Federal Reserve Bank of Richmond.

    Cited by:

    1. Peersman, Gert & Rüth, Sebastian K. & Van der Veken, Wouter, 2019. "The interplay between oil and food commodity prices: Has It changed over time?," Working Papers 0665, University of Heidelberg, Department of Economics.
    2. 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.
    3. Simon Beyeler, 2019. "Streamlining Time-varying VAR with a Factor Structure in the Parameters," Working Papers 19.03, Swiss National Bank, Study Center Gerzensee.
    4. Jan Prüser & Alexander Schlösser, 2020. "On the Time‐Varying Effects of Economic Policy Uncertainty on the US Economy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(5), pages 1217-1237, October.
    5. Prüser, Jan & Schlösser, Alexander, 2018. "On the time-varying effects of economic policy uncertainty on the US economy," Ruhr Economic Papers 761, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    6. Jonas E. Arias & Juan F. Rubio-Ramirez & Minchul Shin, 2021. "Macroeconomic Forecasting and Variable Ordering in Multivariate Stochastic Volatility Models," Working Papers 21-21, Federal Reserve Bank of Philadelphia.
    7. 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.
    8. Hartwig, Benny, 2020. "Robust Inference in Time-Varying Structural VAR Models: The DC-Cholesky Multivariate Stochastic Volatility Model," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224528, Verein für Socialpolitik / German Economic Association.
    9. Hristov, Nikolay & Huelsewig, Oliver & Siemsen, Thomas & Wollmershaeuser, Timo, 2019. "Restoring euro area monetary transmission: Which role for government bond rates?," Munich Reprints in Economics 78269, University of Munich, Department of Economics.
    10. Korobilis, Dimitris & Landau, Bettina & Musso, Alberto & Phella, Anthoulla, 2021. "The time-varying evolution of inflation risks," Working Paper Series 2600, European Central Bank.
    11. Reusens Peter & Croux Christophe, 2017. "Detecting time variation in the price puzzle: a less informative prior choice for time varying parameter VAR models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(4), pages 1-18, September.
    12. Prüser, Jan & Schlösser, Alexander, 2017. "The effects of economic policy uncertainty on European economies: Evidence from a TVP-FAVAR," Ruhr Economic Papers 708, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    13. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.

  6. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2015. "Measurement Errors and Monetary Policy: Then and Now," Working Paper 15-13, Federal Reserve Bank of Richmond.

    Cited by:

    1. Soojin Jo & Rodrigo Sekkel, 2019. "Macroeconomic Uncertainty Through the Lens of Professional Forecasters," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 436-446, July.
    2. Christiane Baumeister & James D. Hamilton, 2019. "Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks," American Economic Review, American Economic Association, vol. 109(5), pages 1873-1910, May.
    3. Christiane Baumeister & James D. Hamilton, 2020. "Drawing Conclusions from Structural Vector Autoregressions Identified on the Basis of Sign Restrictions," NBER Working Papers 26606, National Bureau of Economic Research, Inc.
    4. Aymeric Ortmans, 2020. "Evolving Monetary Policy in the Aftermath of the Great Recession," Documents de recherche 20-01, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
    5. C. Glocker & G. Sestieri & P. Towbin, 2017. "Time-varying fiscal spending multipliers in the UK," Working papers 643, Banque de France.
    6. Glocker, Christian & Sestieri, Giulia & Towbin, Pascal, 2019. "Time-varying government spending multipliers in the UK," Journal of Macroeconomics, Elsevier, vol. 60(C), pages 180-197.
    7. Baumeister, Christiane & Hamilton, James D., 2021. "Reprint: Drawing conclusions from structural vector autoregressions identified on the basis of sign restrictions," Journal of International Money and Finance, Elsevier, vol. 114(C).
    8. Baumeister, Christiane & Hamilton, James, 2017. "Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Deman," CEPR Discussion Papers 12532, C.E.P.R. Discussion Papers.

  7. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2014. "Drifts, Volatilities, and Impulse Responses Over the Last Century," Working Paper 14-10, Federal Reserve Bank of Richmond.

    Cited by:

    1. Amir-Ahmadi, Pooyan & Matthes, Christian & Wang, Mu-Chun, 2017. "Measurement errors and monetary policy: Then and now," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 66-78.
    2. Bataa, Erdenebat & Wohar, Mark & Vivian, Andrew, 2015. "Changes in the relationship between short-term interest rate, inflation and growth: Evidence from the UK, 1820-2014," MPRA Paper 72422, University Library of Munich, Germany.
    3. Kim Abildgren, 2016. "A century of macro-financial linkages," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 8(4), pages 458-471, November.

  8. Wang, Mu-Chun, 2008. "Comparing the DSGE model with the factor model: an out-of-sample forecasting experiment," Discussion Paper Series 1: Economic Studies 2008,04, Deutsche Bundesbank.

    Cited by:

    1. Wieland, Volker & Wolters, Maik, 2013. "Forecasting and Policy Making," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 239-325, Elsevier.
    2. Luci Alessi & Eric Ghysels & Luca Onorante & Richard Peach & Simon M. Potter, 2014. "Central bank macroeconomic forecasting during the global financial crisis: the European Central Bank and Federal Reserve Bank of New York experiences," Staff Reports 680, Federal Reserve Bank of New York.
    3. Wolters, Maik Hendrik, 2012. "Evaluating point and density forecasts of DSGE models," MPRA Paper 36147, University Library of Munich, Germany.
    4. Alain Kabundi & Rangan Gupta, 2009. "A Large Factor Model for Forecasting Macroeconomic Variables in South Africa," Working Papers 137, Economic Research Southern Africa.
    5. Falch, Nina Skrove & Nymoen, Ragnar, 2011. "The accuracy of a forecast targeting central bank," Economics Discussion Papers 2011-6, Kiel Institute for the World Economy (IfW Kiel).
    6. Raffaella Giacomini & Barbara Rossi, 2013. "Forecasting in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 17, pages 381-408, Edward Elgar Publishing.
    7. 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.
    8. Stelios Bekiros & Alessia Paccagnini, 2013. "On the predictability of time-varying VAR and DSGE models," Empirical Economics, Springer, vol. 45(1), pages 635-664, August.
    9. Gupta, Rangan & Kabundi, Alain & Miller, Stephen M., 2011. "Forecasting the US real house price index: Structural and non-structural models with and without fundamentals," Economic Modelling, Elsevier, vol. 28(4), pages 2013-2021, July.
    10. Poghosyan, K., 2012. "Structural and reduced-form modeling and forecasting with application to Armenia," Other publications TiSEM ad1a24c3-15e6-4f04-b338-3, Tilburg University, School of Economics and Management.
    11. Bušs, Ginters, 2009. "Comparing forecasts of Latvia's GDP using simple seasonal ARIMA models and direct versus indirect approach," MPRA Paper 16684, University Library of Munich, Germany.
    12. Dimitar EFTIMOSKI, 2019. "Improving Short-Term Forecasting of Macedonian GDP: Comparing the Factor Model with the Macroeconomic Structural Equation Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 32-53, June.
    13. Wieland, Volker & Wolters, Maik H., 2010. "The diversity of forecasts from macroeconomic models of the U.S. economy," CFS Working Paper Series 2010/08, Center for Financial Studies (CFS).
    14. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2010. "Forecasting with DSGE models," Working Paper Series 1185, European Central Bank.
    15. Ulrich Gunter, 2019. "Estimating and forecasting with a two-country DSGE model of the Euro area and the USA: the merits of diverging interest-rate rules," Empirical Economics, Springer, vol. 56(4), pages 1283-1323, April.

Articles

  1. Loria, Francesca & Matthes, Christian & Wang, Mu-Chun, 2022. "Economic theories and macroeconomic reality," Journal of Monetary Economics, Elsevier, vol. 126(C), pages 105-117.
    See citations under working paper version above.
  2. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2020. "Choosing Prior Hyperparameters: With Applications to Time-Varying Parameter Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 124-136, January.
    See citations under working paper version above.
  3. Amir-Ahmadi, Pooyan & Matthes, Christian & Wang, Mu-Chun, 2017. "Measurement errors and monetary policy: Then and now," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 66-78.
    See citations under working paper version above.
  4. 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.

    Cited by:

    1. Horvath, Jaroslav, 2020. "Macroeconomic disasters and the equity premium puzzle: Are emerging countries riskier?," Journal of Economic Dynamics and Control, Elsevier, vol. 112(C).
    2. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2020. "Choosing Prior Hyperparameters: With Applications to Time-Varying Parameter Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 124-136, January.
    3. Amir-Ahmadi, Pooyan & Matthes, Christian & Wang, Mu-Chun, 2017. "Measurement errors and monetary policy: Then and now," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 66-78.
    4. S. Boragan Aruoba & Luigi Bocola & Frank Schorfheide, 2013. "Assessing DSGE model nonlinearities," Working Papers 13-47, Federal Reserve Bank of Philadelphia.
    5. Thomas A. Lubik & Christian Matthes & Andrew Owens, 2016. "Beveridge Curve Shifts and Time-Varying Parameter VARs," Economic Quarterly, Federal Reserve Bank of Richmond, issue 3Q, pages 197-226.
    6. Martin Gachter & Elias Hasler & Florian Huber, 2023. "A tale of two tails: 130 years of growth-at-risk," Papers 2302.08920, arXiv.org.
    7. Taeyoung Doh, 2017. "Trend and Uncertainty in the Long-Term Real Interest Rate: Bayesian Exponential Tilting with Survey Data," Research Working Paper RWP 17-8, Federal Reserve Bank of Kansas City.
    8. Jansson, Walter, 2018. "Stock markets, banks and economic growth in the UK, 1850–1913," Financial History Review, Cambridge University Press, vol. 25(3), pages 263-296, December.
    9. Njindan Iyke, Bernard, 2016. "Are Monetary Policy Disturbances Important in Ghana? Some Evidence from Agnostic Identification," MPRA Paper 70205, University Library of Munich, Germany.
    10. James M. Nason & Gregor W. Smith, 2023. "Uk Inflation Dynamics Since The Thirteenth Century," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(4), pages 1595-1614, November.
    11. Laura Liu & Christian Matthes & Katerina Petrova & Jessica Sackett Romero, 2019. "Monetary Policy across Space and Time," Richmond Fed Economic Brief, Federal Reserve Bank of Richmond, issue August.
    12. Christiane Baumeister & James D. Hamilton, 2020. "Drawing Conclusions from Structural Vector Autoregressions Identified on the Basis of Sign Restrictions," NBER Working Papers 26606, National Bureau of Economic Research, Inc.
    13. Aymeric Ortmans, 2020. "Evolving Monetary Policy in the Aftermath of the Great Recession," Documents de recherche 20-01, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
    14. Szafranek Karol & Rubaszek Michał, 2024. "Have European natural gas prices decoupled from crude oil prices? Evidence from TVP-VAR analysis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(3), pages 507-530.
    15. Thore Schlaak & Malte Rieth & Maximilian Podstawski, 2018. "Monetary Policy, External Instruments and Heteroskedasticity," Discussion Papers of DIW Berlin 1749, DIW Berlin, German Institute for Economic Research.
    16. Victor Pontines, 2020. "The real effects of loan-to-value limits: Empirical evidence from Korea," CAMA Working Papers 2020-02, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    17. Thomas A. Lubik & Christian Matthes, 2015. "Time-Varying Parameter Vector Autoregressions: Specification, Estimation, and an Application," Economic Quarterly, Federal Reserve Bank of Richmond, issue 4Q, pages 323-352.
    18. Solikin M. Juhro & Paresh Kumar Narayan & Bernard Njindan Iyke, 2022. "Understanding monetary and fiscal policy rule interactions in Indonesia," Applied Economics, Taylor & Francis Journals, vol. 54(45), pages 5190-5208, September.
    19. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2016. "Choosing Prior Hyperparameters," Working Paper 16-9, Federal Reserve Bank of Richmond.
    20. Baumeister, Christiane & Hamilton, James D., 2021. "Reprint: Drawing conclusions from structural vector autoregressions identified on the basis of sign restrictions," Journal of International Money and Finance, Elsevier, vol. 114(C).

  5. Matei Demetrescu & Mu-Chun Wang, 2014. "Incorporating Asymmetric Preferences into Fan Charts and Path Forecasts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 287-297, April.

    Cited by:

    1. Yim, Ha-Neul & Riddell, Jordan R. & Wheeler, Andrew P., 2020. "Is the recent increase in national homicide abnormal? Testing the application of fan charts in monitoring national homicide trends over time," Journal of Criminal Justice, Elsevier, vol. 66(C).
    2. Anna Staszewska-Bystrova & Peter Winker, 2014. "Measuring Forecast Uncertainty of Corporate Bond Spreads by Bonferroni-Type Prediction Bands," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 6(2), pages 89-104, June.
    3. Wojciech Charemza & Carlos Diaz Vela & Svetlana Makarova, 2013. "Inflation fan charts, monetary policy and skew normal distribution," Discussion Papers in Economics 13/06, Division of Economics, School of Business, University of Leicester.
    4. Ohnsorge,Franziska Lieselotte & Stocker,Marc & Some,Modeste Y., 2016. "Quantifying uncertainties in global growth forecasts," Policy Research Working Paper Series 7770, The World Bank.
    5. Yim, Ha-Neul & Riddell, Jordan R. & Wheeler, Andrew Palmer, 2019. "Is the recent increase in national homicide abnormal? Testing the application of fan charts in monitoring national homicide trends over time," SocArXiv 7g32n, Center for Open Science.

  6. Matthes, Christian & Wang, Mu-Chun, 2012. "What drives inflation in New Keynesian models?," Economics Letters, Elsevier, vol. 114(3), pages 338-342.

    Cited by:

    1. Markku Lanne & Jani Luoto, 2014. "Does Output Gap, Labour's Share or Unemployment Rate Drive Inflation?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(5), pages 715-726, October.
    2. Selen Başer Andiç & Hande Küçük & Fethi Öğünç, 2015. "Inflation Dynamics in Turkey: In Pursuit of a Domestic Cost Measure," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 51(2), pages 418-431, March.
    3. Zhao Han & Xiaohan Ma & Ruoyun Mao, 2023. "The Role of Dispersed Information in Inflation and Inflation Expectations," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 48, pages 72-106, April.
    4. Ooft, Gavin, 2018. "Modelling and Forecasting Inflation for the Economy of Suriname," EconStor Preprints 215534, ZBW - Leibniz Information Centre for Economics.
    5. Ooft, Gavin, 2020. "Forecasting Monthly Inflation: An Application To Suriname," Studies in Applied Economics 144, The Johns Hopkins Institute for Applied Economics, Global Health, and the Study of Business Enterprise.

  7. Mu-Chun Wang, 2009. "Comparing the DSGE model with the factor model: an out-of-sample forecasting experiment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(2), pages 167-182.
    See citations under working paper version above.

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Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 10 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-MAC: Macroeconomics (8) 2008-04-04 2014-04-29 2015-02-16 2015-12-08 2017-11-12 2020-06-08 2020-09-14 2022-02-14. Author is listed
  2. NEP-ECM: Econometrics (6) 2008-04-04 2015-12-08 2016-09-04 2017-11-12 2018-11-12 2022-02-14. Author is listed
  3. NEP-ORE: Operations Research (4) 2017-11-12 2018-11-12 2020-06-08 2020-09-14
  4. NEP-CBA: Central Banking (3) 2008-04-04 2015-02-16 2015-12-08
  5. NEP-HIS: Business, Economic and Financial History (3) 2014-04-29 2015-02-16 2022-02-14
  6. NEP-MON: Monetary Economics (3) 2014-04-29 2015-02-16 2015-12-08
  7. NEP-DGE: Dynamic General Equilibrium (2) 2008-04-04 2022-02-14
  8. NEP-CWA: Central and Western Asia (1) 2022-02-14
  9. NEP-ETS: Econometric Time Series (1) 2016-09-04
  10. NEP-FOR: Forecasting (1) 2008-04-04

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