Minchul Shin
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
- Jonas E. Arias & Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez & Minchul Shin, 2022.
"The Causal Effects of Lockdown Policies on Health and Macroeconomic Outcomes,"
Working Papers
22-18, Federal Reserve Bank of Philadelphia.
- Jonas E. Arias & Jesús Fernández- Villaverde & Juan F. Rubio-Ramírez & Minchul Shin, 2023. "The Causal Effects of Lockdown Policies on Health and Macroeconomic Outcomes," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(3), pages 287-319, July.
Cited by:
- Martin, Diego A. & Romero, Dario A., 2024. "Social distancing and COVID-19 under violence: Evidence from Colombia," Journal of Development Economics, Elsevier, vol. 170(C).
- Xiwen Bai & Jesús Fernández-Villaverde & Yiliang Li & Francesco Zanetti, 2024.
"The Causal Effects of Global Supply Chain Disruptions on Macroeconomic Outcomes: Evidence and Theory,"
CESifo Working Paper Series
10930, CESifo.
- Xiwen Bai & Jesús Fernández-Villaverde & Yiliang Li & Francesco Zanetti, 2024. "The Causal Effects of Global Supply Chain Disruptions on Macroeconomic Outcomes: Evidence and Theory," NBER Working Papers 32098, National Bureau of Economic Research, Inc.
- Xiwen Bai & Jesús Fernández-Villaverde & Yiliang Li & Francesco Zanetti, 2024. "The Causal Effects of Global Supply Chain Disruptions on Macroeconomic Outcomes: Evidence and Theory," Discussion Papers 2405, Centre for Macroeconomics (CFM).
- Xiwen Bai & Jesús Fernández-Villaverde & Yiliang Li & Francesco Zanetti, 2024. "The Causal Effects of Global Supply Chain Disruptions on Macroeconomic Outcomes: Evidence and Theory," CAMA Working Papers 2024-09, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Francesco Zanetti & Xiwen Bai & Jesús Fernández-Villaverde & Yiliang Li, 2024. "The Causal Effects of Global Supply Chain Disruptions on Macroeconomic Outcomes: Evidence and Theory," CIGS Working Paper Series 24-003E, The Canon Institute for Global Studies.
- Xiwen Bai & Jesús Fernández-Villaverde & Yiliang Li & Francesco Zanetti, 2024. "The Causal Effects of Global Supply Chain Disruptions on Macroeconomic Outcomes: Evidence and Theory," PIER Working Paper Archive 24-001, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Bai, Xiwen & Fernández-Villaverde, Jesús & Li, Yiliang & Zanetti, Francesco, 2024. "The Causal Effects of Global Supply Chain Disruptions on Macroeconomic Outcomes: Evidence and Theory," CEPR Discussion Papers 18785, C.E.P.R. Discussion Papers.
- Xiwen Bai & Jesús Fernández-Villaverde & Yiliang Li & Francesco Zanetti, 2024. "The Causal Effects of Global Supply Chain Disruptions on Macroeconomic Outcomes: Evidence and Theory," Economics Series Working Papers 1033, University of Oxford, Department of Economics.
- Fernández-Villaverde, Jesús & Mineyama, Tomohide & Song, Dongho, 2024.
"Are We Fragmented Yet? Measuring Geopolitical Fragmentation and Its Causal Effects,"
CEPR Discussion Papers
19184, C.E.P.R. Discussion Papers.
- Jesús Fernández-Villaverde & Tomohide Mineyama & Dongho Song, 2024. "Are We Fragmented Yet? Measuring Geopolitical Fragmentation and Its Causal Effect," NBER Working Papers 32638, National Bureau of Economic Research, Inc.
- Jesus Fernandez-Villaverde & Tomohide Mineyama & Dongho Song, 2024. "Are We Fragmented Yet? Measuring Geopolitical Fragmentation and Its Causal Effects," PIER Working Paper Archive 24-015, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Jésus Fernández-Villaverde & Tomohide Mineyama & Dongho Song & Jesús Fernández-Villaverde, 2024. "Are We Fragmented Yet? Measuring Geopolitical Fragmentation and Its Causal Effects," CESifo Working Paper Series 11192, CESifo.
- Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.
- Paul Labonne & Leif Anders Thorsrud, 2023. "Risky news and credit market sentiment," Working Papers No 14/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
- Johnsson, I. & Pesaran, M. H. & Yang, C. F., 2023.
"Structural Econometric Estimation of the Basic Reproduction Number for Covid-19 Across U.S. States and Selected Countries,"
Cambridge Working Papers in Economics
2360, Faculty of Economics, University of Cambridge.
- Ida Johnsson & M. Hashem Pesaran & Cynthia Fan Yang, 2023. "Structural Econometric Estimation of the Basic Reproduction Number for Covid-19 Across U.S. States and Selected Countries," Papers 2309.08619, arXiv.org.
- Ida Johnsson & M. Hashem Pesaran & Cynthia Fan Yang, 2023. "Structural Econometric Estimation of the Basic Reproduction Number for Covid-19 across U.S. States and Selected Countries," CESifo Working Paper Series 10659, CESifo.
- Selien De Schryder & Nikolaos Koutounidis & Koen Schoors & Johannes Weytjens, 2024. "Assessing the Heterogeneous Impact of COVID-19 on Consumption Using Bank Transactions," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 24/1090, Ghent University, Faculty of Economics and Business Administration.
- Crudu, Federico & Di Stefano, Roberta & Mellace, Giovanni & Tiezzi, Silvia, 2024. "The gray zone: How not imposing a strict lockdown at the beginning of a pandemic can cost many lives," Labour Economics, Elsevier, vol. 89(C).
- David Albouy & Minchul Shin, 2022.
"A Statistical Learning Approach to Land Valuation: Optimizing the Use of External Information,"
Working Papers
22-38, Federal Reserve Bank of Philadelphia.
- Albouy, David & Shin, Minchul, 2022. "A statistical learning approach to land valuation: Optimizing the use of external information," Journal of Housing Economics, Elsevier, vol. 58(PA).
Cited by:
- Scott Wentland & Gary Cornwall & Jeremy G. Moulton, 2023. "For What It's Worth: Measuring Land Value in the Era of Big Data and Machine Learning," BEA Papers 0115, Bureau of Economic Analysis.
- McMillen, Daniel & Zabel, Jeffrey, 2022. "Special issue on land valuation: Introduction," Journal of Housing Economics, Elsevier, vol. 58(PB).
- Jonas E. Arias & Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez & Minchul Shin, 2021.
"Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs,"
CESifo Working Paper Series
8977, CESifo.
- Jonas E. Arias & Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez & Minchul Shin, 2021. "Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs," Working Papers 2021-09, FEDEA.
- Fernández-Villaverde, Jesús & Arias, Jonas & Rubio-RamÃrez, Juan Francisco & Shin, Minchul, 2021. "Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs," CEPR Discussion Papers 15951, C.E.P.R. Discussion Papers.
Cited by:
- Fernández-Villaverde, Jesús & Jones, Chad, 2020.
"Estimating and Simulating a SIRD Model of COVID-19 for Many Countries, States, and Cities,"
CEPR Discussion Papers
14711, C.E.P.R. Discussion Papers.
- Jesús Fernández-Villaverde & Charles I. Jones, 2020. "Estimating and Simulating a SIRD Model of COVID-19 for Many Countries, States, and Cities," NBER Working Papers 27128, National Bureau of Economic Research, Inc.
- Fernández-Villaverde, Jesús & Jones, Charles I., 2022. "Estimating and simulating a SIRD Model of COVID-19 for many countries, states, and cities," Journal of Economic Dynamics and Control, Elsevier, vol. 140(C).
- Gächter, Martin & Huber, Florian & Meier, Martin, 2022. "A shot for the US economy," Finance Research Letters, Elsevier, vol. 47(PA).
- David Turner & Balazs Egert & Yvan Guillemette & Jamila Botev, 2021.
"The Tortoise and the Hare: The Race between Vaccine Rollout and New Covid Variants,"
CESifo Working Paper Series
9151, CESifo.
- David Turner & Balázs Égert & Yvan Guillemette & Jarmila Botev, 2021. "The tortoise and the hare: The race between vaccine rollout and new COVID variants," OECD Economics Department Working Papers 1672, OECD Publishing.
- Masashige Hamano & Munechika Katayama, 2021. "Epidemics and Macroeconomic Dynamics," Working Papers e162, Tokyo Center for Economic Research.
- INOUE Tomoo & OKIMOTO Tatsuyoshi, 2022. "Exploring the Dynamic Relationship between Mobility and the Spread of COVID-19, and the Role of Vaccines," Discussion papers 22011, Research Institute of Economy, Trade and Industry (RIETI).
- 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.
- Arias, Jonas E. & Rubio-Ramírez, Juan F. & Shin, Minchul, 2023. "Macroeconomic forecasting and variable ordering in multivariate stochastic volatility models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1054-1086.
Cited by:
- Joshua C. C. Chan & Gary Koop & Xuewen Yu, 2024.
"Large Order-Invariant Bayesian VARs with Stochastic Volatility,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(2), pages 825-837, April.
- Joshua C. C. Chan & Gary Koop & Xuewen Yu, 2021. "Large Order-Invariant Bayesian VARs with Stochastic Volatility," Papers 2111.07225, arXiv.org.
- Joshua C. C. Chan & Xuewen Yu, 2022.
"Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility,"
Papers
2206.08438, arXiv.org.
- Chan, Joshua C.C. & Yu, Xuewen, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
- Joshua C.C. Chan & Xuewen Yu, 2020. "Fast and accurate variational inference for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2020-108, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Berger, Helge & Karlsson, Sune & Österholm, Pär, 2023.
"A Note of Caution on the Relation between Money Growth and Inflation,"
Working Papers
2023:9, Örebro University, School of Business.
- Mr. Helge Berger & Sune Karlsson & Pär Österholm, 2023. "A Note of Caution on the Relation Between Money Growth and Inflation," IMF Working Papers 2023/137, International Monetary Fund.
- Helge Berger & Sune Karlsson & Pär Österholm, 2023. "A note of caution on the relation between money growth and inflation," Scottish Journal of Political Economy, Scottish Economic Society, vol. 70(5), pages 479-496, November.
- Florian Huber & Gary Koop, 2023.
"Fast and Order-invariant Inference in Bayesian VARs with Non-Parametric Shocks,"
Papers
2305.16827, arXiv.org.
- Florian Huber & Gary Koop, 2024. "Fast and order‐invariant inference in Bayesian VARs with nonparametric shocks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1301-1320, November.
- Florian Huber & Gary Koop, 2023. "Fast and Order-invariant Inference in Bayesian VARs with Non-Parametric Shocks," Working Papers 2309, University of Strathclyde Business School, Department of Economics.
- Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2024.
"Addressing COVID-19 Outliers in BVARs with Stochastic Volatility,"
The Review of Economics and Statistics, MIT Press, vol. 106(5), pages 1403-1417, September.
- Marcellino, Massimiliano & Clark, Todd & Carriero, Andrea & Mertens, Elmar, 2021. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," CEPR Discussion Papers 15964, C.E.P.R. Discussion Papers.
- 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.
- Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano & Mertens, Elmar, 2022. "Addressing COVID-19 outliers in BVARs with stochastic volatility," Discussion Papers 13/2022, Deutsche Bundesbank.
- Wu, Ping & Koop, Gary, 2023. "Estimating the ordering of variables in a VAR using a Plackett–Luce prior," Economics Letters, Elsevier, vol. 230(C).
- Botelho, Vasco & Foroni, Claudia & Renzetti, Andrea, 2023. "Labour at risk," Working Paper Series 2840, European Central Bank.
- Botelho, Vasco & Foroni, Claudia & Renzetti, Andrea, 2024. "Labour at risk," European Economic Review, Elsevier, vol. 170(C).
- 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.
- Florian Huber & Gary Koop & Massimiliano Marcellino & Tobias Scheckel, 2024. "Bayesian modelling of VAR precision matrices using stochastic block networks," Papers 2407.16349, arXiv.org.
- Zhang, Bo & Nguyen, Bao H. & Sun, Chuanwang, 2024. "Forecasting oil prices: Can large BVARs help?," Energy Economics, Elsevier, vol. 137(C).
- Siddhartha Chib & Minchul Shin & Anna Simoni, 2021.
"Bayesian Estimation and Comparison of Conditional Moment Models,"
Papers
2110.13531, arXiv.org.
- Siddhartha Chib & Minchul Shin & Anna Simoni, 2022. "Bayesian estimation and comparison of conditional moment models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(3), pages 740-764, July.
- Siddhartha Chib & Minchul Shin & Anna Simoni, 2022. "Bayesian Estimation and Comparison of Conditional Moment Models," Post-Print hal-03504122, HAL.
- Siddhartha Chib & Minchul Shin & Anna Simoni, 2019. "Bayesian Estimation and Comparison of Conditional Moment Models," Working Papers 19-51, Federal Reserve Bank of Philadelphia.
Cited by:
- Chung, Ray S.W. & So, Mike K.P. & Chu, Amanda M.Y. & Chan, Thomas W.C., 2020. "Regularization of Bayesian quasi-likelihoods constructed from complex estimating functions," Computational Statistics & Data Analysis, Elsevier, vol. 150(C).
- Christis Katsouris, 2023. "High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods," Papers 2308.16192, arXiv.org.
- Gael M. Martin & David T. Frazier & Christian P. Robert, 2020. "Computing Bayes: Bayesian Computation from 1763 to the 21st Century," Monash Econometrics and Business Statistics Working Papers 14/20, Monash University, Department of Econometrics and Business Statistics.
- Zhichao Liu & Catherine Forbes & Heather Anderson, 2017. "Robust Bayesian exponentially tilted empirical likelihood method," Monash Econometrics and Business Statistics Working Papers 21/17, Monash University, Department of Econometrics and Business Statistics.
- Siddhartha Chib & Minchul Shin & Fei Tan, 2021.
"DSGE-SVt: An Econometric Toolkit for High-Dimensional DSGE Models with SV and t Errors,"
Working Papers
21-02, Federal Reserve Bank of Philadelphia.
- Siddhartha Chib & Minchul Shin & Fei Tan, 2023. "DSGE-SVt: An Econometric Toolkit for High-Dimensional DSGE Models with SV and t Errors," Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 69-111, January.
Cited by:
- Li, Bing & Pei, Pei & Tan, Fei, 2021. "Financial distress and fiscal inflation," Journal of Macroeconomics, Elsevier, vol. 70(C).
- Chang, Yoosoon & Maih, Junior & Tan, Fei, 2021.
"Origins of monetary policy shifts: A New approach to regime switching in DSGE models,"
Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).
- Yoosoon Chang & Junior Maih & Fei Tan, 2018. "Origins of Monetary Policy Shifts: A New Approach to Regime Switching in DSGE Models," CAEPR Working Papers 2018-011, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
- Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2024.
"Addressing COVID-19 Outliers in BVARs with Stochastic Volatility,"
The Review of Economics and Statistics, MIT Press, vol. 106(5), pages 1403-1417, September.
- Marcellino, Massimiliano & Clark, Todd & Carriero, Andrea & Mertens, Elmar, 2021. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," CEPR Discussion Papers 15964, C.E.P.R. Discussion Papers.
- 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.
- Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano & Mertens, Elmar, 2022. "Addressing COVID-19 outliers in BVARs with stochastic volatility," Discussion Papers 13/2022, Deutsche Bundesbank.
- Jonas E. Arias & Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez & Minchul Shin, 2021.
"Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs,"
Working Papers
21-18, Federal Reserve Bank of Philadelphia.
Cited by:
- Fernández-Villaverde, Jesús & Jones, Chad, 2020.
"Estimating and Simulating a SIRD Model of COVID-19 for Many Countries, States, and Cities,"
CEPR Discussion Papers
14711, C.E.P.R. Discussion Papers.
- Jesús Fernández-Villaverde & Charles I. Jones, 2020. "Estimating and Simulating a SIRD Model of COVID-19 for Many Countries, States, and Cities," NBER Working Papers 27128, National Bureau of Economic Research, Inc.
- Fernández-Villaverde, Jesús & Jones, Charles I., 2022. "Estimating and simulating a SIRD Model of COVID-19 for many countries, states, and cities," Journal of Economic Dynamics and Control, Elsevier, vol. 140(C).
- Gächter, Martin & Huber, Florian & Meier, Martin, 2022. "A shot for the US economy," Finance Research Letters, Elsevier, vol. 47(PA).
- INOUE Tomoo & OKIMOTO Tatsuyoshi, 2022. "Exploring the Dynamic Relationship between Mobility and the Spread of COVID-19, and the Role of Vaccines," Discussion papers 22011, Research Institute of Economy, Trade and Industry (RIETI).
- Fernández-Villaverde, Jesús & Jones, Chad, 2020.
"Estimating and Simulating a SIRD Model of COVID-19 for Many Countries, States, and Cities,"
CEPR Discussion Papers
14711, C.E.P.R. Discussion Papers.
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2020.
"On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates,"
Papers
2012.11649, arXiv.org, revised Jun 2022.
- Diebold, Francis X. & Shin, Minchul & Zhang, Boyuan, 2023. "On the aggregation of probability assessments: Regularized mixtures of predictive densities for Eurozone inflation and real interest rates," Journal of Econometrics, Elsevier, vol. 237(2).
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone In?ation and Real Interest Rates," PIER Working Paper Archive 21-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2022. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," NBER Working Papers 29635, National Bureau of Economic Research, Inc.
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," Working Papers 21-06, Federal Reserve Bank of Philadelphia.
Cited by:
- Tony Chernis & Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023.
"Predictive Density Combination Using a Tree-Based Synthesis Function,"
Working Papers
23-30, Federal Reserve Bank of Cleveland.
- Tony Chernis & Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023. "Predictive Density Combination Using a Tree-Based Synthesis Function," Papers 2311.12671, arXiv.org.
- Tony Chernis & Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023. "Predictive Density Combination Using a Tree-Based Synthesis Function," Staff Working Papers 23-61, Bank of Canada.
- Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2020.
"Machine Learning Advances for Time Series Forecasting,"
Papers
2012.12802, arXiv.org, revised Apr 2021.
- Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2023. "Machine learning advances for time series forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 76-111, February.
- Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
- Chernis Tony, 2024.
"Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis,"
Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(2), pages 293-317, April.
- Tony Chernis, 2023. "Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis," Staff Working Papers 23-45, Bank of Canada.
- Anthony Garratt & Timo Henckel & Shaun P. Vahey, 2019.
"Empirically-transformed linear opinion pools,"
CAMA Working Papers
2019-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Garratt, Anthony & Henckel, Timo & Vahey, Shaun P., 2023. "Empirically-transformed linear opinion pools," International Journal of Forecasting, Elsevier, vol. 39(2), pages 736-753.
- Todd E. Clark & Gergely Ganics & Elmar Mertens, 2022.
"What is the Predictive Value of SPF Point and Density Forecasts?,"
Working Papers
22-37, Federal Reserve Bank of Cleveland.
- Ganics, Gergely & Mertens, Elmar & Clark, Todd E., 2023. "What Is the Predictive Value of SPF Point and Density Forecasts?," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277622, Verein für Socialpolitik / German Economic Association.
- Bańbura, Marta & Brenna, Federica & Paredes, Joan & Ravazzolo, Francesco, 2021. "Combining Bayesian VARs with survey density forecasts: does it pay off?," Working Paper Series 2543, European Central Bank.
- Bernaciak, Dawid & Griffin, Jim E., 2024. "A loss discounting framework for model averaging and selection in time series models," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1721-1733.
- Siddhartha Chib & Minchul Shin & Anna Simoni, 2018.
"Bayesian Estimation and Comparison of Moment Condition Models,"
Post-Print
hal-03089882, HAL.
- Siddhartha Chib & Minchul Shin & Anna Simoni, 2018. "Bayesian Estimation and Comparison of Moment Condition Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(524), pages 1656-1668, October.
Cited by:
- Siddhartha Chib & Minchul Shin & Anna Simoni, 2021.
"Bayesian Estimation and Comparison of Conditional Moment Models,"
Papers
2110.13531, arXiv.org.
- Siddhartha Chib & Minchul Shin & Anna Simoni, 2022. "Bayesian estimation and comparison of conditional moment models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(3), pages 740-764, July.
- Siddhartha Chib & Minchul Shin & Anna Simoni, 2022. "Bayesian Estimation and Comparison of Conditional Moment Models," Post-Print hal-03504122, HAL.
- Siddhartha Chib & Minchul Shin & Anna Simoni, 2019. "Bayesian Estimation and Comparison of Conditional Moment Models," Working Papers 19-51, Federal Reserve Bank of Philadelphia.
- Gyuhyeong Goh & Jisang Yu, 2022. "Causal inference with some invalid instrumental variables: A quasi‐Bayesian approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(6), pages 1432-1451, December.
- Breitenlechner, Max & Georgiadis, Georgios & Schumann, Ben, 2022.
"What goes around comes around: How large are spillbacks from US monetary policy?,"
Journal of Monetary Economics, Elsevier, vol. 131(C), pages 45-60.
- Max Breitenlechner & Georgios Georgiadis & Ben Schumann, 2021. "What goes around comes around: How large are spillbacks from US monetary policy?," GRU Working Paper Series GRU_2021_003, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
- Breitenlechner, Max & Georgiadis, Georgios & Schumann, Ben, 2021. "What goes around comes around: How large are spillbacks from US monetary policy?," Working Paper Series 2613, European Central Bank.
- Max Breitenlechner & Georgios Georgiadis & Ben Schumann, 2021. "What goes around comes around: How large are spillbacks from US monetary policy?," Working Papers 2021-05, Faculty of Economics and Statistics, Universität Innsbruck.
- Chung, Ray S.W. & So, Mike K.P. & Chu, Amanda M.Y. & Chan, Thomas W.C., 2020. "Regularization of Bayesian quasi-likelihoods constructed from complex estimating functions," Computational Statistics & Data Analysis, Elsevier, vol. 150(C).
- Sweata Sen & Damitri Kundu & Kiranmoy Das, 2023. "Variable selection for categorical response: a comparative study," Computational Statistics, Springer, vol. 38(2), pages 809-826, June.
- Bedoui, Adel & Lazar, Nicole A., 2020. "Bayesian empirical likelihood for ridge and lasso regressions," Computational Statistics & Data Analysis, Elsevier, vol. 145(C).
- Luo, Yu & Graham, Daniel J. & McCoy, Emma J., 2023. "Semiparametric Bayesian doubly robust causal estimation," LSE Research Online Documents on Economics 117944, London School of Economics and Political Science, LSE Library.
- Gallant, A. Ronald & Hong, Han & Leung, Michael P. & Li, Jessie, 2022. "Constrained estimation using penalization and MCMC," Journal of Econometrics, Elsevier, vol. 228(1), pages 85-106.
- Petrova, Katerina, 2022. "Asymptotically valid Bayesian inference in the presence of distributional misspecification in VAR models," Journal of Econometrics, Elsevier, vol. 230(1), pages 154-182.
- Gael M. Martin & David T. Frazier & Christian P. Robert, 2020. "Computing Bayes: Bayesian Computation from 1763 to the 21st Century," Monash Econometrics and Business Statistics Working Papers 14/20, Monash University, Department of Econometrics and Business Statistics.
- Rong Tang & Yun Yang, 2022. "Bayesian inference for risk minimization via exponentially tilted empirical likelihood," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1257-1286, September.
- Qiao, Zhuo & Wang, Yan & Lam, Keith S.K., 2022. "New evidence on Bayesian tests of global factor pricing models," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 160-172.
- Christopher D. Walker, 2024. "Semiparametric Bayesian Inference for a Conditional Moment Equality Model," Papers 2410.16017, arXiv.org.
- Zhichao Liu & Catherine Forbes & Heather Anderson, 2017. "Robust Bayesian exponentially tilted empirical likelihood method," Monash Econometrics and Business Statistics Working Papers 21/17, Monash University, Department of Econometrics and Business Statistics.
- Arnab Kumar Maity & Sanjib Basu & Santu Ghosh, 2021. "Bayesian criterion‐based variable selection," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 835-857, August.
- Gael M. Martin & David T. Frazier & Christian P. Robert, 2021. "Approximating Bayes in the 21st Century," Monash Econometrics and Business Statistics Working Papers 24/21, Monash University, Department of Econometrics and Business Statistics.
- Kline, Brendan, 2024. "Classical p-values and the Bayesian posterior probability that the hypothesis is approximately true," Journal of Econometrics, Elsevier, vol. 240(1).
- Ross Askanazi & Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2018.
"On the Comparison of Interval Forecasts,"
PIER Working Paper Archive
18-013, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 02 Aug 2018.
- Ross Askanazi & Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2018. "On the Comparison of Interval Forecasts," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 953-965, November.
Cited by:
- Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2019.
"Forecasting with a Panel Tobit Model,"
CAEPR Working Papers
2019-005, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
- Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2023. "Forecasting with a panel Tobit model," Quantitative Economics, Econometric Society, vol. 14(1), pages 117-159, January.
- Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2019. "Forecasting with a Panel Tobit Model," NBER Working Papers 26569, National Bureau of Economic Research, Inc.
- Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2021. "Forecasting with a Panel Tobit Model," Papers 2110.14117, arXiv.org, revised Jul 2022.
- Hyndman, Rob J., 2020.
"A brief history of forecasting competitions,"
International Journal of Forecasting, Elsevier, vol. 36(1), pages 7-14.
- Rob J Hyndman, 2019. "A Brief History of Forecasting Competitions," Monash Econometrics and Business Statistics Working Papers 3/19, Monash University, Department of Econometrics and Business Statistics.
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021.
"On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates,"
Working Papers
21-06, Federal Reserve Bank of Philadelphia.
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone In?ation and Real Interest Rates," PIER Working Paper Archive 21-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Diebold, Francis X. & Shin, Minchul & Zhang, Boyuan, 2023. "On the aggregation of probability assessments: Regularized mixtures of predictive densities for Eurozone inflation and real interest rates," Journal of Econometrics, Elsevier, vol. 237(2).
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2022. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," NBER Working Papers 29635, National Bureau of Economic Research, Inc.
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2020. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," Papers 2012.11649, arXiv.org, revised Jun 2022.
- Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022.
"Forecasting: theory and practice,"
International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
- Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
- Arias, Jonas E. & Rubio-Ramírez, Juan F. & Shin, Minchul, 2023.
"Macroeconomic forecasting and variable ordering in multivariate stochastic volatility models,"
Journal of Econometrics, Elsevier, vol. 235(2), pages 1054-1086.
- 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.
- Nico Keilman, 2020. "Evaluating Probabilistic Population Forecasts," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 520-521, pages 49-64.
- Liu, Laura & Moon, Hyungsik Roger & Schorfheide, Frank, 2021.
"Panel forecasts of country-level Covid-19 infections,"
Journal of Econometrics, Elsevier, vol. 220(1), pages 2-22.
- Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2020. "Panel Forecasts of Country-Level Covid-19 Infections," NBER Working Papers 27248, National Bureau of Economic Research, Inc.
- Sayar Karmakar & Marek Chudý & Wei Biao Wu, 2022. "Long‐term prediction intervals with many covariates," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(4), pages 587-609, July.
- James Mitchell & Martin Weale, 2021.
"Censored Density Forecasts: Production and Evaluation,"
Working Papers
21-12R, Federal Reserve Bank of Cleveland, revised 16 Aug 2022.
- James Mitchell & Martin Weale, 2023. "Censored density forecasts: Production and evaluation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(5), pages 714-734, August.
- Makridakis, Spyros & Hyndman, Rob J. & Petropoulos, Fotios, 2020. "Forecasting in social settings: The state of the art," International Journal of Forecasting, Elsevier, vol. 36(1), pages 15-28.
- Francisca Corpas-Burgos & Miguel A. Martinez-Beneito, 2021. "An Autoregressive Disease Mapping Model for Spatio-Temporal Forecasting," Mathematics, MDPI, vol. 9(4), pages 1-17, February.
- Spyros Makridakis & Chris Fry & Fotios Petropoulos & Evangelos Spiliotis, 2022. "The Future of Forecasting Competitions: Design Attributes and Principles," INFORMS Joural on Data Science, INFORMS, vol. 1(1), pages 96-113, April.
- Francis X. Diebold & Minchul Shin, 2018.
"Machine Learning for Regularized Survey Forecast Combination: Partially-Egalitarian Lasso and its Derivatives,"
NBER Working Papers
24967, National Bureau of Economic Research, Inc.
- 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.
- Francis X. Diebold & Minchul Shin, 2018. "Machine Learning for Regularized Survey Forecast Combination: Partially Egalitarian Lasso and its Derivatives," PIER Working Paper Archive 18-014, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 17 Aug 2018.
Cited by:
- Wang, Yudong & Hao, Xianfeng, 2023. "Forecasting the real prices of crude oil: What is the role of parameter instability?," Energy Economics, Elsevier, vol. 117(C).
- Granziera, Eleonora & Sekhposyan, Tatevik, 2019.
"Predicting relative forecasting performance: An empirical investigation,"
International Journal of Forecasting, Elsevier, vol. 35(4), pages 1636-1657.
- Granziera, Eleonora & Sekhposyan, Tatevik, 2018. "Predicting relative forecasting performance: An empirical investigation," Bank of Finland Research Discussion Papers 23/2018, Bank of Finland.
- Diebold, Francis X. & Rudebusch, Glenn D., 2022.
"Probability assessments of an ice-free Arctic: Comparing statistical and climate model projections,"
Journal of Econometrics, Elsevier, vol. 231(2), pages 520-534.
- Francis X. Diebold & Glenn D. Rudebusch, 2019. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," Papers 1912.10774, arXiv.org, revised Jul 2021.
- Francis X. Diebold & Glenn D. Rudebusch, 2020. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," NBER Working Papers 28228, National Bureau of Economic Research, Inc.
- Francis X. Diebold & Glenn D. Rudebusch, 2019. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," PIER Working Paper Archive 20-001, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Francis X. Diebold & Glenn D. Rudebusch, 2020. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," Working Paper Series 2020-02, Federal Reserve Bank of San Francisco.
- Luiz Renato Lima & Lucas Lúcio Godeiro & Mohammed Mohsin, 2021. "Time-Varying Dictionary and the Predictive Power of FED Minutes," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 149-181, January.
- Roccazzella, Francesco & Gambetti, Paolo & Vrins, Frédéric, 2021.
"Optimal and robust combination of forecasts via constrained optimization and shrinkage,"
LIDAM Reprints LFIN
2021014, Université catholique de Louvain, Louvain Finance (LFIN).
- Roccazzella, Francesco & Gambetti, Paolo & Vrins, Frédéric, 2022. "Optimal and robust combination of forecasts via constrained optimization and shrinkage," International Journal of Forecasting, Elsevier, vol. 38(1), pages 97-116.
- Roccazzella, Francesco & Gambetti, Paolo & Vrins, Frédéric, 2020. "Optimal and robust combination of forecasts via constrained optimization and shrinkage," LIDAM Discussion Papers LFIN 2020006, Université catholique de Louvain, Louvain Finance (LFIN).
- Li Li & Yanfei Kang & Fotios Petropoulos & Feng Li, 2022. "Feature-based intermittent demand forecast combinations: bias, accuracy and inventory implications," Papers 2204.08283, arXiv.org, revised Aug 2022.
- Bartosz Uniejewski & Katarzyna Maciejowska, 2022.
"LASSO Principal Component Averaging -- a fully automated approach for point forecast pooling,"
Papers
2207.04794, arXiv.org.
- Uniejewski, Bartosz & Maciejowska, Katarzyna, 2023. "LASSO principal component averaging: A fully automated approach for point forecast pooling," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1839-1852.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020.
"How is Machine Learning Useful for Macroeconomic Forecasting?,"
Working Papers
20-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Aug 2020.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022. "How is machine learning useful for macroeconomic forecasting?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Papers 2008.12477, arXiv.org.
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021.
"On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates,"
Working Papers
21-06, Federal Reserve Bank of Philadelphia.
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone In?ation and Real Interest Rates," PIER Working Paper Archive 21-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Diebold, Francis X. & Shin, Minchul & Zhang, Boyuan, 2023. "On the aggregation of probability assessments: Regularized mixtures of predictive densities for Eurozone inflation and real interest rates," Journal of Econometrics, Elsevier, vol. 237(2).
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2022. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," NBER Working Papers 29635, National Bureau of Economic Research, Inc.
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2020. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," Papers 2012.11649, arXiv.org, revised Jun 2022.
- Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, vol. 76(C).
- Andrii Babii & Eric Ghysels & Jonas Striaukas, 2024.
"Econometrics of machine learning methods in economic forecasting,"
Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 10, pages 246-273,
Edward Elgar Publishing.
- Andrii Babii & Eric Ghysels & Jonas Striaukas, 2023. "Econometrics of Machine Learning Methods in Economic Forecasting," Papers 2308.10993, arXiv.org.
- Zhang, Yaojie & Wahab, M.I.M. & Wang, Yudong, 2023. "Forecasting crude oil market volatility using variable selection and common factor," International Journal of Forecasting, Elsevier, vol. 39(1), pages 486-502.
- UÄŸur Åžener & Salvatore Joseph Terregrossa, 2024. "A Transcendental LASSO Function for Combining Machine Learning and Statistical Model Forecasts," SAGE Open, , vol. 14(3), pages 21582440241, August.
- Guo, Xiaozhu & Huang, Dengshi & Li, Xiafei & Liang, Chao, 2023. "Are categorical EPU indices predictable for carbon futures volatility? Evidence from the machine learning method," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 672-693.
- Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022.
"Forecasting: theory and practice,"
International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
- Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
- Marta Poncela-Blanco & Pilar Poncela, 2021. "Improving Wind Power Forecasts: Combination through Multivariate Dimension Reduction Techniques," Energies, MDPI, vol. 14(5), pages 1-16, March.
- Jeronymo Marcondes Pinto & Emerson Fernandes Marçal, 2023. "An artificial intelligence approach to forecasting when there are structural breaks: a reinforcement learning-based framework for fast switching," Empirical Economics, Springer, vol. 65(4), pages 1729-1759, October.
- Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2020.
"Machine Learning Advances for Time Series Forecasting,"
Papers
2012.12802, arXiv.org, revised Apr 2021.
- Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2023. "Machine learning advances for time series forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 76-111, February.
- James Younker, 2022. "Calculating Effective Degrees of Freedom for Forecast Combinations and Ensemble Models," Discussion Papers 2022-19, Bank of Canada.
- Yusupova, Alisa & Pavlidis, Nicos G. & Pavlidis, Efthymios G., 2023. "Dynamic linear models with adaptive discounting," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1925-1944.
- Cakici, Nusret & Shahzad, Syed Jawad Hussain & Będowska-Sójka, Barbara & Zaremba, Adam, 2024. "Machine learning and the cross-section of cryptocurrency returns," International Review of Financial Analysis, Elsevier, vol. 94(C).
- Yoonseok Lee & Donggyu Sul, 2023.
"Depth-weighted Forecast Combination: Application to COVID-19 Cases,"
Advances in Econometrics, in: Essays in Honor of Joon Y. Park: Econometric Methodology in Empirical Applications, volume 45, pages 235-260,
Emerald Group Publishing Limited.
- Yoonseok Lee & Donggyu Sul, 2021. "Depth-Weighted Forecast Combination: Application to COVID-19 Cases," Center for Policy Research Working Papers 238, Center for Policy Research, Maxwell School, Syracuse University.
- Constantin Rudolf Salomo Bürgi, 2023.
"How to deal with missing observations in surveys of professional forecasters,"
Journal of Applied Economics, Taylor & Francis Journals, vol. 26(1), pages 2185975-218, December.
- Constantin Bürgi, 2023. "How to Deal With Missing Observations in Surveys of Professional Forecasters," CESifo Working Paper Series 10203, CESifo.
- Roccazzella, Francesco & Candelon, Bertrand, 2022. "Should we care about ECB inflation expectations?," LIDAM Discussion Papers LFIN 2022004, Université catholique de Louvain, Louvain Finance (LFIN).
- Thompson, Ryan & Qian, Yilin & Vasnev, Andrey L., 2024.
"Flexible global forecast combinations,"
Omega, Elsevier, vol. 126(C).
- Ryan Thompson & Yilin Qian & Andrey L. Vasnev, 2022. "Flexible global forecast combinations," Papers 2207.07318, arXiv.org, revised Mar 2024.
- Ryan Cumings-Menon & Minchul Shin, 2020. "Probability Forecast Combination via Entropy Regularized Wasserstein Distance," Working Papers 20-31/R, Federal Reserve Bank of Philadelphia.
- Meira, Erick & Cyrino Oliveira, Fernando Luiz & Jeon, Jooyoung, 2021. "Treating and Pruning: New approaches to forecasting model selection and combination using prediction intervals," International Journal of Forecasting, Elsevier, vol. 37(2), pages 547-568.
- Katarzyna Maciejowska & Bartosz Uniejewski & Tomasz Serafin, 2020.
"PCA forecast averaging - predicting day-ahead and intraday electricity prices,"
WORking papers in Management Science (WORMS)
WORMS/20/02, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
- Katarzyna Maciejowska & Bartosz Uniejewski & Tomasz Serafin, 2020. "PCA Forecast Averaging—Predicting Day-Ahead and Intraday Electricity Prices," Energies, MDPI, vol. 13(14), pages 1-19, July.
- Michael T. Kiley, 2020. "Financial Conditions and Economic Activity: Insights from Machine Learning," Finance and Economics Discussion Series 2020-095, Board of Governors of the Federal Reserve System (U.S.).
- Lu, Fei & Ma, Feng & Li, Pan & Huang, Dengshi, 2022. "Natural gas volatility predictability in a data-rich world," International Review of Financial Analysis, Elsevier, vol. 83(C).
- Jiun-Hua Su, 2021. "No-Regret Forecasting with Egalitarian Committees," Papers 2109.13801, arXiv.org.
- Tim K. Tsang & Qiurui Du & Benjamin J. Cowling & Cécile Viboud, 2024. "An adaptive weight ensemble approach to forecast influenza activity in an irregular seasonality context," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
- Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
- Godahewa, Rakshitha & Bergmeir, Christoph & Webb, Geoffrey I. & Montero-Manso, Pablo, 2023. "An accurate and fully-automated ensemble model for weekly time series forecasting," International Journal of Forecasting, Elsevier, vol. 39(2), pages 641-658.
- Daniel Borup & Jonas N. Eriksen & Mads M. Kjær & Martin Thyrsgaard, 2024.
"Predicting Bond Return Predictability,"
Management Science, INFORMS, vol. 70(2), pages 931-951, February.
- Daniel Borup & Jonas N. Eriksen & Mads M. Kjær & Martin Thyrsgaard, 2020. "Predicting bond return predictability," CREATES Research Papers 2020-09, Department of Economics and Business Economics, Aarhus University.
- Yumin Li & Ruiqi Yang & Xiaoman Wang & Jiaming Zhu & Nan Song, 2023. "Carbon Price Combination Forecasting Model Based on Lasso Regression and Optimal Integration," Sustainability, MDPI, vol. 15(12), pages 1-26, June.
- Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019.
"Macroeconomic forecast accuracy in a data‐rich environment,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1050-1072, November.
- Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019. "Macroeconomic Forecast Accuracy in data-rich environment," Post-Print hal-02435757, HAL.
- Saidjon Shiralievich Tavarov & Alexander Sidorov & Zsolt Čonka & Murodbek Safaraliev & Pavel Matrenin & Mihail Senyuk & Svetlana Beryozkina & Inga Zicmane, 2023. "Control of Operational Modes of an Urban Distribution Grid under Conditions of Uncertainty," Energies, MDPI, vol. 16(8), pages 1-18, April.
- Grzegorz Marcjasz & Bartosz Uniejewski & Rafał Weron, 2020.
"Beating the Naïve—Combining LASSO with Naïve Intraday Electricity Price Forecasts,"
Energies, MDPI, vol. 13(7), pages 1-16, April.
- Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2020. "Beating the naive: Combining LASSO with naive intraday electricity price forecasts," WORking papers in Management Science (WORMS) WORMS/20/01, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
- Qiu, Yue & Zheng, Yuchen, 2023. "Improving box office projections through sentiment analysis: Insights from regularization-based forecast combinations," Economic Modelling, Elsevier, vol. 125(C).
- Maehashi, Kohei & Shintani, Mototsugu, 2020. "Macroeconomic forecasting using factor models and machine learning: an application to Japan," Journal of the Japanese and International Economies, Elsevier, vol. 58(C).
- Philippe Goulet Coulombe & Karin Klieber & Christophe Barrette & Maximilian Goebel, 2024. "Maximally Forward-Looking Core Inflation," Papers 2404.05209, arXiv.org.
- Tae-Hwy Lee & Ekaterina Seregina, 2020.
"Learning from Forecast Errors: A New Approach to Forecast Combinations,"
Papers
2011.02077, arXiv.org, revised May 2021.
- Tae-Hwy Lee & Ekaterina Seregina, 2020. "Learning from Forecast Errors: A New Approach to Forecast Combination," Working Papers 202024, University of California at Riverside, Department of Economics.
- Qian, Yilin & Thompson, Ryan & Vasnev, Andrey L, 2022. "Global combinations of expert forecasts," Working Papers BAWP-2022-02, University of Sydney Business School, Discipline of Business Analytics.
- Kohei Maehashi & Mototsugu Shintani, 2020. "Macroeconomic Forecasting Using Factor Models and Machine Learning: An Application to Japan," CIRJE F-Series CIRJE-F-1146, CIRJE, Faculty of Economics, University of Tokyo.
- Petropoulos, Fotios & Spiliotis, Evangelos & Panagiotelis, Anastasios, 2023. "Model combinations through revised base rates," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1477-1492.
- Anthony Garratt & Timo Henckel & Shaun P. Vahey, 2019.
"Empirically-transformed linear opinion pools,"
CAMA Working Papers
2019-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Garratt, Anthony & Henckel, Timo & Vahey, Shaun P., 2023. "Empirically-transformed linear opinion pools," International Journal of Forecasting, Elsevier, vol. 39(2), pages 736-753.
- Daniel Borup & David E. Rapach & Erik Christian Montes Schütte, 2021. "Now- and Backcasting Initial Claims with High-Dimensional Daily Internet Search-Volume Data," CREATES Research Papers 2021-02, Department of Economics and Business Economics, Aarhus University.
- Bin Chen & Kenwin Maung, 2020. "Time-varying Forecast Combination for High-Dimensional Data," Papers 2010.10435, arXiv.org.
- Chen, Bin & Maung, Kenwin, 2023. "Time-varying forecast combination for high-dimensional data," Journal of Econometrics, Elsevier, vol. 237(2).
- Zhentao Shi & Liangjun Su & Tian Xie, 2020. "L2-Relaxation: With Applications to Forecast Combination and Portfolio Analysis," Papers 2010.09477, arXiv.org, revised Aug 2022.
- Xi Dong & Yan Li & David E. Rapach & Guofu Zhou, 2022. "Anomalies and the Expected Market Return," Journal of Finance, American Finance Association, vol. 77(1), pages 639-681, February.
- Jeronymo Marcondes Pinto & Jennifer L. Castle, 2022. "Machine Learning Dynamic Switching Approach to Forecasting in the Presence of Structural Breaks," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(2), pages 129-157, July.
- Wada, Tatsuma, 2022. "Out-of-sample forecasting of foreign exchange rates: The band spectral regression and LASSO," Journal of International Money and Finance, Elsevier, vol. 128(C).
- Anesti, Nikoleta & Kalamara, Eleni & Kapetanios, George, 2021. "Forecasting UK GDP growth with large survey panels," Bank of England working papers 923, Bank of England.
- Huang, Dashan & Li, Jiangyuan & Wang, Liyao, 2021. "Are disagreements agreeable? Evidence from information aggregation," Journal of Financial Economics, Elsevier, vol. 141(1), pages 83-101.
- Li Liu & Xianfeng Hao & Yudong Wang, 2024. "Solving the Forecast Combination Puzzle Using Double Shrinkages," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(3), pages 714-741, June.
- Jesús Molina‐Muñoz & Andrés Mora‐Valencia & Javier Perote, 2024. "Predicting carbon and oil price returns using hybrid models based on machine and deep learning," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 31(2), June.
- Max H. Farrell & Tengyuan Liang & Sanjog Misra, 2020. "Deep Learning for Individual Heterogeneity: An Automatic Inference Framework," Papers 2010.14694, arXiv.org, revised Jul 2021.
- Borup, Daniel & Rapach, David E. & Schütte, Erik Christian Montes, 2023. "Mixed-frequency machine learning: Nowcasting and backcasting weekly initial claims with daily internet search volume data," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1122-1144.
- Dong Jin Lee & Minchul Shin & Boyuan Zhang & Molin Zhong, 2017.
"Measuring International Uncertainty : The Case of Korea,"
Finance and Economics Discussion Series
2017-066, Board of Governors of the Federal Reserve System (U.S.).
- Shin, Minchul & Zhang, Boyuan & Zhong, Molin & Lee, Dong Jin, 2018. "Measuring international uncertainty: The case of Korea," Economics Letters, Elsevier, vol. 162(C), pages 22-26.
Cited by:
- Liang, Chin Chia & Troy, Carol & Rouyer, Ellen, 2020. "U.S. uncertainty and Asian stock prices: Evidence from the asymmetric NARDL model," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
- Mohammad R. Jahan-Parvar & Yuriy Kitsul & Jamil Rahman & Beth Anne Wilson, 2024. "Foreign economic policy uncertainty and U.S. equity returns," International Finance Discussion Papers 1401, Board of Governors of the Federal Reserve System (U.S.).
- Cho, Dooyeon & Kim, Husang, 2023. "Macroeconomic effects of uncertainty shocks: Evidence from Korea," Journal of Asian Economics, Elsevier, vol. 84(C).
- Sangyup Choi & Myungkyu Shim, 2019.
"Financial vs. Policy Uncertainty in Emerging Market Economies,"
Open Economies Review, Springer, vol. 30(2), pages 297-318, April.
- Sangyup Choi & Myungkyu Shim, 2018. "Financial vs. Policy Uncertainty in Emerging Market Economies," Working papers 2018rwp-116, Yonsei University, Yonsei Economics Research Institute.
- Tran, Quoc Trung, 2020. "Creditor protection, shareholder protection and investment efficiency: New evidence," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
- Avellán, Guillermo & González-Astudillo, Manuel & Salcedo, Juan José, 2020. "A Streamlined Procedure to Construct a Macroeconomic Uncertainty Index with an Application to the Ecuadorian Economy," MPRA Paper 102593, University Library of Munich, Germany.
- Park, Jin Seok & Suh, Donghyun, 2019. "Uncertainty and household portfolio choice : Evidence from South Korea," Economics Letters, Elsevier, vol. 180(C), pages 21-24.
- Quoc Trung Tran, 2020. "Corporate cash holdings and financial crisis: new evidence from an emerging market," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 10(2), pages 271-285, June.
- Serdar Ongan & Ismet Gocer, 2022. "Japan-US bilateral commodity-level trade and trade policy-related uncertainty under the COVID-19 pandemic: the nonlinear ARDL model," Economic Change and Restructuring, Springer, vol. 55(3), pages 1397-1418, August.
- Youngjoon Lee & Soohyon Kim & Ki Young Park, 2018. "Deciphering Monetary Policy Committee Minutes with Text Mining Approach: A Case of South Korea," Working papers 2018rwp-132, Yonsei University, Yonsei Economics Research Institute.
- Ioannis Dokas & Georgios Oikonomou & Minas Panagiotidis & Eleftherios Spyromitros, 2023. "Macroeconomic and Uncertainty Shocks’ Effects on Energy Prices: A Comprehensive Literature Review," Energies, MDPI, vol. 16(3), pages 1-35, February.
- Aviral Kumar Tiwari & Muhammad Ali Nasir & Muhammad Shahbaz, 2021. "Synchronisation of policy related uncertainty, financial stress and economic activity in the United States," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 6406-6415, October.
- Wang, Xinya & Xu, Xin & Rong, Xueyun & Xuan, Siyuan, 2024. "Identification of the contagion effect in China's financial market uncertainties: A multiscale and dynamic perspective," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 1340-1362.
- Śmiech, Sławomir & Papież, Monika & Dąbrowski, Marek A., 2019. "How important are different aspects of uncertainty in driving industrial production in the CEE countries?," Research in International Business and Finance, Elsevier, vol. 50(C), pages 252-266.
- Tran, Quoc Trung, 2021. "Economic policy uncertainty and cost of debt financing: International evidence," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
- Ogbuabor, Jonathan E. & Ukwueze, Ezebuilo R. & Mba, Ifeoma C. & Ojonta, Obed I. & Orji, Anthony, 2023. "The asymmetric impact of economic policy uncertainty on global retail energy markets: Are the markets responding to the fear of the unknown?," Applied Energy, Elsevier, vol. 334(C).
- Kevin Larcher & Jaebeom Kim & Youngju Kim, 2019.
"Uncertainty shocks and asymmetric dynamics in Korea: a non-linear approach,"
Applied Economics, Taylor & Francis Journals, vol. 51(6), pages 594-610, February.
- Kevin Larcher & Jaebeom Kim & Youngju Kim, 2018. "Uncertainty Shocks and Asymmetric Dynamics in Korea: A Nonlinear Approach," Working Papers 2018-12, Economic Research Institute, Bank of Korea.
- Lin Liu, 2022. "Economic Uncertainty and Exchange Market Pressure: Evidence From China," SAGE Open, , vol. 12(1), pages 21582440211, January.
- Bukalska Elżbieta & Maziarczyk Anna, 2023. "Impact of financial constraints and financial distress on cash holdings," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 59(1), pages 13-31, March.
- Guillermo Avellán & Manuel González-Astudillo & Juan José Salcedo Cruz, 2022. "Measuring uncertainty: A streamlined application for the Ecuadorian economy," Empirical Economics, Springer, vol. 62(4), pages 1517-1542, April.
- Hwang, So Jung & Suh, Hyunduk, 2021. "Overall and time-varying effects of global and domestic uncertainty on the Korean economy," Journal of Asian Economics, Elsevier, vol. 76(C).
- 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.
Cited by:
- Daniele Bianchi & Kenichiro McAlinn, 2018. "Large-Scale Dynamic Predictive Regressions," Papers 1803.06738, arXiv.org.
- Warwick Smith & Anca M. Hanea & Mark A. Burgman, 2022. "Can Groups Improve Expert Economic and Financial Forecasts?," Forecasting, MDPI, vol. 4(3), pages 1-18, August.
- Nir Billfeld & Moshe Kim, 2019. "Semiparametric correction for endogenous truncation bias with Vox Populi based participation decision," Papers 1902.06286, arXiv.org.
- Nikodinoska, Dragana & Käso, Mathias & Müsgens, Felix, 2022. "Solar and wind power generation forecasts using elastic net in time-varying forecast combinations," Applied Energy, Elsevier, vol. 306(PA).
- Camila Figueroa S. & Michael Pedersen, 2019. "A system for forecasting Chilean cash demand – the role of forecast combinations," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 22(2), pages 040-068, August.
- Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2016.
"Real-Time Forecast Evaluation of DSGE Models with Stochastic Volatility,"
NBER Working Papers
22615, National Bureau of Economic Research, Inc.
- Diebold, Francis X. & Schorfheide, Frank & Shin, Minchul, 2017. "Real-time forecast evaluation of DSGE models with stochastic volatility," Journal of Econometrics, Elsevier, vol. 201(2), pages 322-332.
- Diebold, Francis X. & Schorfheide, Frank & Shin, Minchul, 2017. "Real-time forecast evaluation of DSGE models with stochastic volatility," CFS Working Paper Series 577, Center for Financial Studies (CFS).
- Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2015. "Real-Time Forecast Evaluation of DSGE Models with Stochastic Volatility," PIER Working Paper Archive 15-018, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 May 2015.
Cited by:
- Wang, Yudong & Liu, Li & Wu, Chongfeng, 2020. "Forecasting commodity prices out-of-sample: Can technical indicators help?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 666-683.
- Ivashchenko, S., 2020. "Long-term growth sources for sectors of Russian economy," Journal of the New Economic Association, New Economic Association, vol. 48(4), pages 86-112.
- Jan Philipp Fritsche & Mathias Klein & Malte Rieth, 2020.
"Government Spending Multipliers in (Un)certain Times,"
Discussion Papers of DIW Berlin
1901, DIW Berlin, German Institute for Economic Research.
- Fritsche, Jan Philipp & Klein, Mathias & Rieth, Malte, 2021. "Government spending multipliers in (un)certain times," Journal of Public Economics, Elsevier, vol. 203(C).
- Jonathan Benchimol & Sergey Ivashchenko, 2020.
"Switching Volatility in a Nonlinear Open Economy,"
CFDS Discussion Paper Series
2020/8, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China.
- Jonathan Benchimol & Sergey Ivashchenko, 2020. "Switching Volatility in a Nonlinear Open Economy," Bank of Israel Working Papers 2020.04, Bank of Israel.
- Jonathan Benchimol & Sergey Ivashchenko, 2020. "Switching Volatility in a Nonlinear Open Economy," Globalization Institute Working Papers 386, Federal Reserve Bank of Dallas.
- Benchimol, Jonathan & Ivashchenko, Sergey, 2021. "Switching volatility in a nonlinear open economy," Journal of International Money and Finance, Elsevier, vol. 110(C).
- Jonathan Benchimol & Sergey Ivashchenko, 2021. "Switching volatility in a nonlinear open economy," Post-Print halshs-03248949, HAL.
- Benchimol, Jonathan & Ivashchenko, Sergey, 2020. "Switching Volatility in a Nonlinear Open Economy," Dynare Working Papers 60, CEPREMAP.
- Gary Koop & Dimitris Korobilis, 2018.
"Forecasting with High-Dimensional Panel VARs,"
Working Paper series
18-20, Rimini Centre for Economic Analysis.
- Koop, Gary & Korobilis, Dimitris, 2015. "Forecasting with High-Dimensional Panel VARs," MPRA Paper 84275, University Library of Munich, Germany, revised 31 Jan 2018.
- Koop, G & Korobilis, D, 2018. "Forecasting with High-Dimensional Panel VARs," Essex Finance Centre Working Papers 21329, University of Essex, Essex Business School.
- Gary Koop & Dimitris Korobilis, 2019. "Forecasting with High‐Dimensional Panel VARs," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(5), pages 937-959, October.
- Gary Koop & Dimitris Korobilis, 2015. "Forecasting With High Dimensional Panel VARs," Working Papers 2015_25, Business School - Economics, University of Glasgow.
- Sergey Ivashchenko, 2022. "Dynamic Stochastic General Equilibrium Model with Multiple Trends and Structural Breaks," Russian Journal of Money and Finance, Bank of Russia, vol. 81(1), pages 46-72, March.
- Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
- S. Boragan Aruoba & Luigi Bocola & Frank Schorfheide, 2013.
"Assessing DSGE model nonlinearities,"
Working Papers
13-47, Federal Reserve Bank of Philadelphia.
- Aruoba, S. Borağan & Bocola, Luigi & Schorfheide, Frank, 2017. "Assessing DSGE model nonlinearities," Journal of Economic Dynamics and Control, Elsevier, vol. 83(C), pages 34-54.
- S. Borağan Aruoba & Luigi Bocola & Frank Schorfheide, 2013. "Assessing DSGE Model Nonlinearities," NBER Working Papers 19693, National Bureau of Economic Research, Inc.
- Michael Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019.
"Online Estimation of DSGE Models,"
Liberty Street Economics
20190821, Federal Reserve Bank of New York.
- Michael Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," Staff Reports 893, Federal Reserve Bank of New York.
- Michael D. Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2020. "Online Estimation of DSGE Models," NBER Working Papers 26826, National Bureau of Economic Research, Inc.
- Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2021. "Online estimation of DSGE models," The Econometrics Journal, Royal Economic Society, vol. 24(1), pages 33-58.
- Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," PIER Working Paper Archive 19-014, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Michael Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2020. "Online Estimation of DSGE Models," Finance and Economics Discussion Series 2020-023, Board of Governors of the Federal Reserve System (U.S.).
- Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2020.
"Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors,"
The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 17-33, March.
- Todd E Clark & Michael W McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," BIS Working Papers 667, Bank for International Settlements.
- Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers 17-15R, Federal Reserve Bank of Cleveland.
- Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers (Old Series) 1715, Federal Reserve Bank of Cleveland.
- Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," Working Papers 2017-026, Federal Reserve Bank of St. Louis.
- James Morley & Irina B Panovska, 2016.
"Is Business Cycle Asymmetry Intrinsic in Industrialized Economies?,"
Discussion Papers
2016-12, School of Economics, The University of New South Wales.
- Morley, James & Panovska, Irina B., 2020. "Is Business Cycle Asymmetry Intrinsic In Industrialized Economies?," Macroeconomic Dynamics, Cambridge University Press, vol. 24(6), pages 1403-1436, September.
- James Morley & Irina B Panovska, 2017. "Is Business Cycle Asymmetry Intrinsic in Industrialized Economies?," Discussion Papers 2016-12A, School of Economics, The University of New South Wales.
- Ramis Khabibullin & Sergei Seleznev, 2022.
"Fast Estimation of Bayesian State Space Models Using Amortized Simulation-Based Inference,"
Papers
2210.07154, arXiv.org.
- Ramis Khabibullin & Sergei Seleznev, 2022. "Fast Estimation of Bayesian State Space Models Using Amortized Simulation-Based Inference," Bank of Russia Working Paper Series wps104, Bank of Russia.
- Di Bartolomeo, Giovanni & Serpieri, Carolina, 2024.
"Optimal monetary policy and the time-dependent price and wage Phillips curves: An international comparison,"
Journal of International Money and Finance, Elsevier, vol. 146(C).
- Giovanni Di Bartolomeo & Carolina Serpieri, 2024. "Optimal monetary policy and the time-dependent price and wage Phillips curves: An international comparison," Working Papers in Public Economics 249, Department of Economics and Law, Sapienza University of Roma.
- Angelini, Giovanni & Gorgi, Paolo, 2018. "DSGE Models with observation-driven time-varying volatility," Economics Letters, Elsevier, vol. 171(C), pages 169-171.
- Yantao Gao & Xilong Yao & Wenxi Wang & Xin Liu, 2019. "Dynamic effect of environmental tax on export trade: Based on DSGE mode," Energy & Environment, , vol. 30(7), pages 1275-1290, November.
- Diebold, Francis X. & Schorfheide, Frank & Shin, Minchul, 2017.
"Real-time forecast evaluation of DSGE models with stochastic volatility,"
CFS Working Paper Series
577, Center for Financial Studies (CFS).
- Diebold, Francis X. & Schorfheide, Frank & Shin, Minchul, 2017. "Real-time forecast evaluation of DSGE models with stochastic volatility," Journal of Econometrics, Elsevier, vol. 201(2), pages 322-332.
- Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2016. "Real-Time Forecast Evaluation of DSGE Models with Stochastic Volatility," NBER Working Papers 22615, National Bureau of Economic Research, Inc.
- Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2015. "Real-Time Forecast Evaluation of DSGE Models with Stochastic Volatility," PIER Working Paper Archive 15-018, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 May 2015.
- Siddhartha Chib & Minchul Shin & Fei Tan, 2020. "High-Dimensional DSGE Models: Pointers on Prior, Estimation, Comparison, and Prediction∗," Working Papers 20-35, Federal Reserve Bank of Philadelphia.
- Farooq Akram & Andrew Binning & Junior Maih, 2016.
"Joint prediction bands for macroeconomic risk management,"
Working Paper
2016/7, Norges Bank.
- Farooq Akram & Andrew Binning & Junior Maih, 2016. "Joint Prediction Bands for Macroeconomic Risk Management," Working Papers No 5/2016, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
- Reifschneider, David & Tulip, Peter, 2019. "Gauging the uncertainty of the economic outlook using historical forecasting errors: The Federal Reserve’s approach," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1564-1582.
- Li, Chenxing & Maheu, John M & Yang, Qiao, 2022.
"An Infinite Hidden Markov Model with Stochastic Volatility,"
MPRA Paper
115456, University Library of Munich, Germany.
- Chenxing Li & John M. Maheu & Qiao Yang, 2024. "An infinite hidden Markov model with stochastic volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2187-2211, September.
- Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2016. "Choosing Prior Hyperparameters," Working Paper 16-9, Federal Reserve Bank of Richmond.
- Poledna, Sebastian & Miess, Michael Gregor & Hommes, Cars & Rabitsch, Katrin, 2023. "Economic forecasting with an agent-based model," European Economic Review, Elsevier, vol. 151(C).
- 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.
- Cars Hommes & Mario He & Sebastian Poledna & Melissa Siqueira & Yang Zhang, 2022. "CANVAS: A Canadian Behavioral Agent-Based Model," Staff Working Papers 22-51, Bank of Canada.
- Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2021.
"Using time-varying volatility for identification in Vector Autoregressions: An application to endogenous uncertainty,"
Journal of Econometrics, Elsevier, vol. 225(1), pages 47-73.
- Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2021. "Using Time-Varying Volatility for Identification in Vector Autoregressions: An Application to Endogenous Uncertainty," CEPR Discussion Papers 16346, C.E.P.R. Discussion Papers.
- Jinshun Wu & Luyao Wu, 2024. "Bayesian Local Likelihood Estimation of Time-Varying DSGE Models: Allowing for Indeterminacy," Computational Economics, Springer;Society for Computational Economics, vol. 64(4), pages 2437-2476, October.
- Yolanda S. Stander, 2023. "The Governance and Disclosure of IFRS 9 Economic Scenarios," JRFM, MDPI, vol. 16(1), pages 1-27, January.
- Sergey Ivashchenko & Semih Emre Cekin & Rangan Gupta & Chien-Chiang Lee, 2022.
"Real-Time Forecast of DSGE Models with Time-Varying Volatility in GARCH Form,"
Working Papers
202204, University of Pretoria, Department of Economics.
- Çekin, Semih Emre & Ivashchenko, Sergey & Gupta, Rangan & Lee, Chien-Chiang, 2024. "Real-time forecast of DSGE models with time-varying volatility in GARCH form," International Review of Financial Analysis, Elsevier, vol. 93(C).
- Dmitry Kreptsev & Sergei Seleznev, 2018. "Forecasting for the Russian Economy Using Small-Scale DSGE Models," Russian Journal of Money and Finance, Bank of Russia, vol. 77(2), pages 51-67, June.
- Siddhartha Chib & Minchul Shin & Fei Tan, 2023.
"DSGE-SVt: An Econometric Toolkit for High-Dimensional DSGE Models with SV and t Errors,"
Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 69-111, January.
- Siddhartha Chib & Minchul Shin & Fei Tan, 2021. "DSGE-SVt: An Econometric Toolkit for High-Dimensional DSGE Models with SV and t Errors," Working Papers 21-02, Federal Reserve Bank of Philadelphia.
- Bäurle Gregor & Kaufmann Daniel & Kaufmann Sylvia & Strachan Rodney, 2020. "Constrained interest rates and changing dynamics at the zero lower bound," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(2), pages 1-26, April.
- Michael P Clements & Ana Beatriz Galvao, 2017. "Data Revisions and Real-time Probabilistic Forecasting of Macroeconomic Variables," ICMA Centre Discussion Papers in Finance icma-dp2017-01, Henley Business School, University of Reading.
- 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).
- Mertens, Elmar, 2023. "Precision-based sampling for state space models that have no measurement error," Discussion Papers 25/2023, Deutsche Bundesbank.
- Carriero, Andrea & Galvão, Ana Beatriz & Kapetanios, George, 2019. "A comprehensive evaluation of macroeconomic forecasting methods," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1226-1239.
- Musa Abdu & Adamu Jibir & Salihu Abdullahi & Aisha Adamu Hassan, 2021. "Drivers of manufacturing firms’ productivity: a micro-perspective to industrialization in Nigeria," SN Business & Economics, Springer, vol. 1(2), pages 1-17, February.
- David L. Reifschneider & Peter Tulip, 2017.
"Gauging the Uncertainty of the Economic Outlook Using Historical Forecasting Errors : The Federal Reserve's Approach,"
Finance and Economics Discussion Series
2017-020, Board of Governors of the Federal Reserve System (U.S.).
- David Reifschneider & Peter Tulip, 2017. "Gauging the Uncertainty of the Economic Outlook Using Historical Forecasting Errors: The Federal Reserve's Approach," RBA Research Discussion Papers rdp2017-01, Reserve Bank of Australia.
- James Morley, 2019. "The business cycle: periodic pandemic or rollercoaster ride?," International Journal of Economic Policy Studies, Springer, vol. 13(2), pages 425-431, August.
- Sun Xiaojin & Tsang Kwok Ping, 2019. "What cycles? Data detrending in DSGE models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 23(3), pages 1-23, June.
- Sergey M. Ivashchenko, 2019. "DSGE Models: Problem of Trends," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 2, pages 81-95, April.
- Xiao-Li Gong & Jin-Yan Lu & Xiong Xiong & Wei Zhang, 2022. "Higher-order dynamic effects of uncertainty risk under thick-tailed stochastic volatility," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-22, December.
- Siddharta Chib & Minchul Shin & Anna Simoni, 2016.
"Bayesian Empirical Likelihood Estimation and Comparison of Moment Condition Models,"
Working Papers
2016-21, Center for Research in Economics and Statistics.
Cited by:
- Zhichao Liu & Catherine Forbes & Heather Anderson, 2017. "Robust Bayesian exponentially tilted empirical likelihood method," Monash Econometrics and Business Statistics Working Papers 21/17, Monash University, Department of Econometrics and Business Statistics.
- Minchul Shin & Molin Zhong, 2016.
"A New Approach to Identifying the Real Effects of Uncertainty Shocks,"
Finance and Economics Discussion Series
2016-040, Board of Governors of the Federal Reserve System (U.S.).
- Minchul Shin & Molin Zhong, 2020. "A New Approach to Identifying the Real Effects of Uncertainty Shocks," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 367-379, April.
Cited by:
- Joshua C. C. Chan & Xuewen Yu, 2022.
"Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility,"
Papers
2206.08438, arXiv.org.
- Chan, Joshua C.C. & Yu, Xuewen, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
- Joshua C.C. Chan & Xuewen Yu, 2020. "Fast and accurate variational inference for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2020-108, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2018.
"Measuring Uncertainty and Its Impact on the Economy,"
The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 799-815, December.
- Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Measuring Uncertainty and Its Impact on the Economy," BAFFI CAREFIN Working Papers 1639, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
- Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2016. "Measuring Uncertainty and Its Impact on the Economy," Working Papers (Old Series) 1622, Federal Reserve Bank of Cleveland.
- Joshua C. C. Chan, 2024.
"BVARs and stochastic volatility,"
Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 3, pages 43-67,
Edward Elgar Publishing.
- Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
- Hernández Vega Marco A., 2021. "The Nonlinear Effect of Uncertainty in Portfolio Flows to Mexico," Working Papers 2021-11, Banco de México.
- Olli Palm'en, 2022. "Macroeconomic Effect of Uncertainty and Financial Shocks: a non-Gaussian VAR approach," Papers 2202.10834, arXiv.org.
- 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.
- Mawuli Segnon & Rangan Gupta & Stelios Bekiros & Mark E. Wohar, 2016. "Forecasting US GNP Growth: The Role of Uncertainty," Working Papers 201667, University of Pretoria, Department of Economics.
- Andrea Carriero & Alessio Volpicella, 2022. "Generalizing the Max Share Identification to multiple shocks identification: an Application to Uncertainty," School of Economics Discussion Papers 0322, School of Economics, University of Surrey.
- Shin, Minchul & Zhang, Boyuan & Zhong, Molin & Lee, Dong Jin, 2018.
"Measuring international uncertainty: The case of Korea,"
Economics Letters, Elsevier, vol. 162(C), pages 22-26.
- Dong Jin Lee & Minchul Shin & Boyuan Zhang & Molin Zhong, 2017. "Measuring International Uncertainty : The Case of Korea," Finance and Economics Discussion Series 2017-066, Board of Governors of the Federal Reserve System (U.S.).
- Danilo Cascaldi-Garcia & Ana Beatriz Galvao, 2018.
"News and Uncertainty Shocks,"
International Finance Discussion Papers
1240, Board of Governors of the Federal Reserve System (U.S.).
- Danilo Cascaldi‐Garcia & Ana Beatriz Galvao, 2021. "News and Uncertainty Shocks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(4), pages 779-811, June.
- Härtl, Tilmann, 2022. "Identifying Proxy VARs with Restrictions on the Forecast Error Variance," VfS Annual Conference 2022 (Basel): Big Data in Economics 264071, Verein für Socialpolitik / German Economic Association.
- Danilo Cascaldi-Garcia & Cisil Sarisoy & Juan M. Londono & Bo Sun & Deepa D. Datta & Thiago Ferreira & Olesya Grishchenko & Mohammad R. Jahan-Parvar & Francesca Loria & Sai Ma & Marius Rodriguez & Ilk, 2023.
"What Is Certain about Uncertainty?,"
Journal of Economic Literature, American Economic Association, vol. 61(2), pages 624-654, June.
- Danilo Cascaldi-Garcia & Deepa Dhume Datta & Thiago Revil T. Ferreira & Olesya V. Grishchenko & Mohammad R. Jahan-Parvar & Juan M. Londono & Francesca Loria & Sai Ma & Marius del Giudice Rodriguez & J, 2020. "What is Certain about Uncertainty?," International Finance Discussion Papers 1294, Board of Governors of the Federal Reserve System (U.S.).
- Laura E. Jackson & Kevin L. Kliesen & Michael T. Owyang, 2018.
"The Nonlinear Effects of Uncertainty Shocks,"
Working Papers
2018-035, Federal Reserve Bank of St. Louis.
- Jackson Laura E. & Kliesen Kevin L. & Owyang Michael T., 2020. "The nonlinear effects of uncertainty shocks," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(4), pages 1-19, September.
- Boyan Jovanovic & Sai Ma, 2020.
"Uncertainty and Growth Disasters,"
NBER Working Papers
28024, National Bureau of Economic Research, Inc.
- Boyan Jovanovic & Sai Ma, 2020. "Uncertainty and Growth Disasters," International Finance Discussion Papers 1279, Board of Governors of the Federal Reserve System (U.S.).
- Boyan Jovanovic & Sai Ma, 2022. "Uncertainty and Growth Disasters," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 44, pages 33-64, April.
- Arias, Jonas E. & Rubio-Ramírez, Juan F. & Shin, Minchul, 2023.
"Macroeconomic forecasting and variable ordering in multivariate stochastic volatility models,"
Journal of Econometrics, Elsevier, vol. 235(2), pages 1054-1086.
- 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.
- Maria Elena Bontempi & Michele Frigeri & Roberto Golinelli & Matteo Squadrani, 2021. "EURQ: A New Web Search‐based Uncertainty Index," Economica, London School of Economics and Political Science, vol. 88(352), pages 969-1015, October.
- María T. González-Pérez, 2021. "Lessons from estimating the average option-implied volatility term structure for the Spanish banking sector," Working Papers 2128, Banco de España.
- Danilo Cascaldi-Garcia, 2017. "Amplification effects of news shocks through uncertainty," 2017 Papers pca1251, Job Market Papers.
- Josué Diwambuena & Jean-Paul K. Tsasa, 2021. "The Real Effects of Uncertainty Shocks: New Evidence from Linear and Nonlinear SVAR Models," BEMPS - Bozen Economics & Management Paper Series BEMPS87, Faculty of Economics and Management at the Free University of Bozen.
- Helena Chuliá & Rangan Gupta & Jorge M. Uribe & Mark E. Wohar, 2016.
"Impact of US Uncertainties on Emerging and Mature Markets: Evidence from a Quantile-Vector Autoregressive Approach,"
Working Papers
201656, University of Pretoria, Department of Economics.
- Chuliá, Helena & Gupta, Rangan & Uribe, Jorge M. & Wohar, Mark E., 2017. "Impact of US uncertainties on emerging and mature markets: Evidence from a quantile-vector autoregressive approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 48(C), pages 178-191.
- Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Papers 2311.16333, arXiv.org, revised Apr 2024.
- Rangan Gupta & Chi Keung Marco Lau & Mark E. Wohar, 2016.
"The Impact of US Uncertainty on the Euro Area in Good and Bad Times: Evidence from a Quantile Structural Vector Autoregressive Model,"
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201681, University of Pretoria, Department of Economics.
- Rangan Gupta & Chi Keung Marco Lau & Mark E. Wohar, 2019. "The impact of US uncertainty on the Euro area in good and bad times: evidence from a quantile structural vector autoregressive model," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 353-368, May.
- Mario Forni & Luca Gambetti & Nicolò Maffei-Faccioli & Luca Sala, 2023. "The impact of financial shocks on the forecast distribution of output and inflation," Working Paper 2023/3, Norges Bank.
- Awijen, Haithem & Ben Zaied, Younes & Nguyen, Duc Khuong & Sensoy, Ahmet, 2020. "Endogenous Financial Uncertainty and Macroeconomic Volatility: Evidence from the United States," MPRA Paper 101276, University Library of Munich, Germany, revised Jun 2020.
- Laurent Ferrara & Stéphane Lhuissier & Fabien Tripier, 2018.
"Uncertainty Fluctuations: Measures, Effects and Macroeconomic Policy Challenges,"
Financial and Monetary Policy Studies, in: Laurent Ferrara & Ignacio Hernando & Daniela Marconi (ed.), International Macroeconomics in the Wake of the Global Financial Crisis, pages 159-181,
Springer.
- Laurent Ferrara & Stéphane Lhuissier & Fabien Tripier, 2017. "Uncertainty Fluctuations: Measures, Effects and Macroeconomic Policy Challenges," CEPII Policy Brief 2017-20, CEPII research center.
- Ma, Xiaohan & Samaniego, Roberto, 2020. "The macroeconomic impact of oil earnings uncertainty: New evidence from analyst forecasts," Energy Economics, Elsevier, vol. 90(C).
- Pierdzioch Christian & Gupta Rangan, 2020.
"Uncertainty and Forecasts of U.S. Recessions,"
Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(4), pages 1-20, September.
- Christian Pierdzioch & Rangan Gupta, 2017. "Uncertainty and Forecasts of U.S. Recessions," Working Papers 201732, University of Pretoria, Department of Economics.
- Emanuele Bacchiocchi & Catalin Dragomirescu-Gaina, 2022.
"Uncertainty spill-overs: when policy and financial realms overlap,"
Working Papers
wp1174, Dipartimento Scienze Economiche, Universita' di Bologna.
- Bacchiocchi, Emanuele & Dragomirescu-Gaina, Catalin, 2024. "Uncertainty spill-overs: When policy and financial realms overlap," Journal of International Money and Finance, Elsevier, vol. 143(C).
- Emanuele Bacchiocchi & Catalin Dragomirescu-Gaina, 2021. "Uncertainty spill-overs: when policy and financial realms overlap," Papers 2102.06404, arXiv.org.
- 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.
- Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2021.
"Using time-varying volatility for identification in Vector Autoregressions: An application to endogenous uncertainty,"
Journal of Econometrics, Elsevier, vol. 225(1), pages 47-73.
- Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2021. "Using Time-Varying Volatility for Identification in Vector Autoregressions: An Application to Endogenous Uncertainty," CEPR Discussion Papers 16346, C.E.P.R. Discussion Papers.
- Jonas E. Arias & Juan F. Rubio-Ramirez & Daniel F. Waggoner, 2020.
"Uniform Priors for Impulse Responses,"
Working Papers
22-30, Federal Reserve Bank of Philadelphia.
- Jonas E. Arias & Juan F. Rubio-Ramirez & Daniel F. Waggoner, 2023. "Uniform Priors for Impulse Responses," FRB Atlanta Working Paper 2023-13, Federal Reserve Bank of Atlanta.
- Mario Forni & Luca Gambetti & Luca Sala, 2020.
"Macroeconomic Uncertainty and Vector Autoregressions,"
Center for Economic Research (RECent)
148, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
- Forni, Mario & Gambetti, Luca & Sala, Luca, 2021. "Macroeconomic Uncertainty and Vector Autoregressions," CEPR Discussion Papers 15692, C.E.P.R. Discussion Papers.
- Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Large Vector Autoregressions with Stochastic Volatility and Flexible Priors," Working Papers (Old Series) 1617, Federal Reserve Bank of Cleveland.
- Johnson Worlanyo Ahiadorme, 2022. "On the aggregate effects of global uncertainty: Evidence from an emerging economy," South African Journal of Economics, Economic Society of South Africa, vol. 90(3), pages 390-407, September.
- Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Working Papers 23-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Nov 2023.
- Ma, Xiaohan & Samaniego, Roberto, 2019. "Deconstructing uncertainty," European Economic Review, Elsevier, vol. 119(C), pages 22-41.
- Vivek Sharma & Edgar Silgado-Gómez, 2019. "Sovereign Spread Volatility and Banking Sector," CEIS Research Paper 454, Tor Vergata University, CEIS, revised 08 Mar 2019.
- Juan M. Londono & Sai Ma & Beth Anne Wilson, 2021. "The Global Transmission of Real Economic Uncertainty," International Finance Discussion Papers 1317, Board of Governors of the Federal Reserve System (U.S.).
- Dario Caldara & Chiara Scotti & Molin Zhong, 2021. "Macroeconomic and Financial Risks: A Tale of Mean and Volatility," International Finance Discussion Papers 1326, Board of Governors of the Federal Reserve System (U.S.).
- Francis X. Diebold & Minchul Shin, 2016.
"Assessing Point Forecast Accuracy by Stochastic Error Distance,"
NBER Working Papers
22516, National Bureau of Economic Research, Inc.
- Francis X. Diebold & Minchul Shin, 2017. "Assessing point forecast accuracy by stochastic error distance," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 588-598, October.
- Francis X. Diebold & Minchul Shin, 2014. "Assessing Point Forecast Accuracy by Stochastic Error Distance," PIER Working Paper Archive 14-038, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
Cited by:
- Borgonovo, Emanuele & Hazen, Gordon B. & Jose, Victor Richmond R. & Plischke, Elmar, 2021. "Probabilistic sensitivity measures as information value," European Journal of Operational Research, Elsevier, vol. 289(2), pages 595-610.
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021.
"On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates,"
Working Papers
21-06, Federal Reserve Bank of Philadelphia.
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone In?ation and Real Interest Rates," PIER Working Paper Archive 21-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Diebold, Francis X. & Shin, Minchul & Zhang, Boyuan, 2023. "On the aggregation of probability assessments: Regularized mixtures of predictive densities for Eurozone inflation and real interest rates," Journal of Econometrics, Elsevier, vol. 237(2).
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2022. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," NBER Working Papers 29635, National Bureau of Economic Research, Inc.
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2020. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," Papers 2012.11649, arXiv.org, revised Jun 2022.
- Diebold, Francis X. & Shin, Minchul, 2015. "Assessing point forecast accuracy by stochastic loss distance," Economics Letters, Elsevier, vol. 130(C), pages 37-38.
- Emilian Dobrescu, 2014. "Attempting to Quantify the Accuracy of Complex Macroeconomic Forecasts," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 5-21, December.
- Tomás Marinozzi, 2023. "Forecasting Inflation in Argentina: A Probabilistic Approach," Ensayos Económicos, Central Bank of Argentina, Economic Research Department, vol. 1(81), pages 81-110, May.
- Jin, Sainan & Corradi, Valentina & Swanson, Norman R., 2017.
"Robust Forecast Comparison,"
Econometric Theory, Cambridge University Press, vol. 33(6), pages 1306-1351, December.
- Sainan Jin & Valentina Corradi & Norman Swanson, 2015. "Robust Forecast Comparison," Departmental Working Papers 201502, Rutgers University, Department of Economics.
- Valentina Corradi & Sainan Jin & Norman R. Swanson, 2023. "Robust forecast superiority testing with an application to assessing pools of expert forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 596-622, June.
- Hiroyuki Kawakatsu, 2020. "Recovering Yield Curves from Dynamic Term Structure Models with Time-Varying Factors," Stats, MDPI, vol. 3(3), pages 1-46, August.
- Minchul Shin & Molin Zhong, 2015.
"Does Realized Volatility Help Bond Yield Density Prediction?,"
Finance and Economics Discussion Series
2015-115, Board of Governors of the Federal Reserve System (U.S.).
- Shin, Minchul & Zhong, Molin, 2017. "Does realized volatility help bond yield density prediction?," International Journal of Forecasting, Elsevier, vol. 33(2), pages 373-389.
- Minchul Shin & Molin Zhong, 2013. "Does realized volatility help bond yield density prediction?," PIER Working Paper Archive 13-064, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
Cited by:
- Hitesh Doshi & Kris Jacobs & Rui Liu, 2021. "Information in the Term Structure: A Forecasting Perspective," Management Science, INFORMS, vol. 67(8), pages 5255-5277, August.
- Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2014.
"No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates,"
CEPR Discussion Papers
9848, C.E.P.R. Discussion Papers.
- Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2021. "No‐arbitrage priors, drifting volatilities, and the term structure of interest rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 495-516, August.
- Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "No-Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," Working Papers 20-27, Federal Reserve Bank of Cleveland.
- Xu Gong & Boqiang Lin, 2022. "Predicting the volatility of crude oil futures: The roles of leverage effects and structural changes," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 610-640, January.
Articles
- Diebold, Francis X. & Shin, Minchul & Zhang, Boyuan, 2023.
"On the aggregation of probability assessments: Regularized mixtures of predictive densities for Eurozone inflation and real interest rates,"
Journal of Econometrics, Elsevier, vol. 237(2).
See citations under working paper version above.
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone In?ation and Real Interest Rates," PIER Working Paper Archive 21-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2022. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," NBER Working Papers 29635, National Bureau of Economic Research, Inc.
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2020. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," Papers 2012.11649, arXiv.org, revised Jun 2022.
- Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," Working Papers 21-06, Federal Reserve Bank of Philadelphia.
- Jonas E. Arias & Jesús Fernández- Villaverde & Juan F. Rubio-Ramírez & Minchul Shin, 2023.
"The Causal Effects of Lockdown Policies on Health and Macroeconomic Outcomes,"
American Economic Journal: Macroeconomics, American Economic Association, vol. 15(3), pages 287-319, July.
See citations under working paper version above.
- Jonas E. Arias & Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez & Minchul Shin, 2022. "The Causal Effects of Lockdown Policies on Health and Macroeconomic Outcomes," Working Papers 22-18, Federal Reserve Bank of Philadelphia.
- Siddhartha Chib & Minchul Shin & Fei Tan, 2023.
"DSGE-SVt: An Econometric Toolkit for High-Dimensional DSGE Models with SV and t Errors,"
Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 69-111, January.
See citations under working paper version above.
- Siddhartha Chib & Minchul Shin & Fei Tan, 2021. "DSGE-SVt: An Econometric Toolkit for High-Dimensional DSGE Models with SV and t Errors," Working Papers 21-02, Federal Reserve Bank of Philadelphia.
- Arias, Jonas E. & Rubio-Ramírez, Juan F. & Shin, Minchul, 2023.
"Macroeconomic forecasting and variable ordering in multivariate stochastic volatility models,"
Journal of Econometrics, Elsevier, vol. 235(2), pages 1054-1086.
See citations under working paper version above.
- 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.
- Siddhartha Chib & Minchul Shin & Anna Simoni, 2022.
"Bayesian estimation and comparison of conditional moment models,"
Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(3), pages 740-764, July.
See citations under working paper version above.
- Siddhartha Chib & Minchul Shin & Anna Simoni, 2022. "Bayesian Estimation and Comparison of Conditional Moment Models," Post-Print hal-03504122, HAL.
- Siddhartha Chib & Minchul Shin & Anna Simoni, 2019. "Bayesian Estimation and Comparison of Conditional Moment Models," Working Papers 19-51, Federal Reserve Bank of Philadelphia.
- Siddhartha Chib & Minchul Shin & Anna Simoni, 2021. "Bayesian Estimation and Comparison of Conditional Moment Models," Papers 2110.13531, arXiv.org.
- Albouy, David & Shin, Minchul, 2022.
"A statistical learning approach to land valuation: Optimizing the use of external information,"
Journal of Housing Economics, Elsevier, vol. 58(PA).
See citations under working paper version above.
- David Albouy & Minchul Shin, 2022. "A Statistical Learning Approach to Land Valuation: Optimizing the Use of External Information," Working Papers 22-38, Federal Reserve Bank of Philadelphia.
- Minchul Shin & Molin Zhong, 2020.
"A New Approach to Identifying the Real Effects of Uncertainty Shocks,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 367-379, April.
See citations under working paper version above.
- Minchul Shin & Molin Zhong, 2016. "A New Approach to Identifying the Real Effects of Uncertainty Shocks," Finance and Economics Discussion Series 2016-040, Board of Governors of the Federal Reserve System (U.S.).
- 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.
See citations under working paper version above.
- Francis X. Diebold & Minchul Shin, 2018. "Machine Learning for Regularized Survey Forecast Combination: Partially-Egalitarian Lasso and its Derivatives," NBER Working Papers 24967, National Bureau of Economic Research, Inc.
- Francis X. Diebold & Minchul Shin, 2018. "Machine Learning for Regularized Survey Forecast Combination: Partially Egalitarian Lasso and its Derivatives," PIER Working Paper Archive 18-014, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 17 Aug 2018.
- Shin, Minchul & Zhang, Boyuan & Zhong, Molin & Lee, Dong Jin, 2018.
"Measuring international uncertainty: The case of Korea,"
Economics Letters, Elsevier, vol. 162(C), pages 22-26.
See citations under working paper version above.
- Dong Jin Lee & Minchul Shin & Boyuan Zhang & Molin Zhong, 2017. "Measuring International Uncertainty : The Case of Korea," Finance and Economics Discussion Series 2017-066, Board of Governors of the Federal Reserve System (U.S.).
- Ross Askanazi & Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2018.
"On the Comparison of Interval Forecasts,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 953-965, November.
See citations under working paper version above.
- Ross Askanazi & Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2018. "On the Comparison of Interval Forecasts," PIER Working Paper Archive 18-013, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 02 Aug 2018.
- David Albouy & Gabriel Ehrlich & Minchul Shin, 2018.
"Metropolitan Land Values,"
The Review of Economics and Statistics, MIT Press, vol. 100(3), pages 454-466, July.
Cited by:
- Juan Carlos Suárez Serrato & Owen Zidar, 2015.
"Who benefits from state corporate tax cuts? A local labour markets approach with heterogeneous firms,"
Working Papers
1502, Oxford University Centre for Business Taxation.
- Juan Carlos Suárez Serrato & Owen Zidar, 2014. "Who Benefits from State Corporate Tax Cuts? A Local Labor Markets Approach with Heterogeneous Firms," NBER Working Papers 20289, National Bureau of Economic Research, Inc.
- Juan Carlos Suárez Serrato & Owen Zidar, 2016. "Who Benefits from State Corporate Tax Cuts? A Local Labor Markets Approach with Heterogeneous Firms," American Economic Review, American Economic Association, vol. 106(9), pages 2582-2624, September.
- Matthias Kehrig & Nicolas L. Ziebarth, 2017.
"The Effects of the Real Oil Price on Regional Wage Dispersion,"
CESifo Working Paper Series
6408, CESifo.
- Matthias Kehrig & Nicolas L. Ziebarth, 2017. "The Effects of the Real Oil Price on Regional Wage Dispersion," American Economic Journal: Macroeconomics, American Economic Association, vol. 9(2), pages 115-148, April.
- Combes, Pierre-Philippe & Duranton, Gilles & Gobillon, Laurent, 2016.
"The Production Function for Housing: Evidence from France,"
CEPR Discussion Papers
11669, C.E.P.R. Discussion Papers.
- Pierre-Philippe Combes & Gilles Duranton & Laurent Gobillon, 2016. "The Production Function for Housing: Evidence from France," SciencePo Working papers Main halshs-01412393, HAL.
- Pierre-Philippe Combes & Gilles Duranton & Laurent Gobillon, 2021. "The Production Function for Housing: Evidence from France," Journal of Political Economy, University of Chicago Press, vol. 129(10), pages 2766-2816.
- Pierre-Philippe Combes & Gilles Duranton & Laurent Gobillon, 2016. "The Production Function for Housing: Evidence from France," Working Papers 1637, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
- Pierre-Philippe Combes & Gilles Duranton & Laurent Gobillon, 2021. "The Production Function for Housing: Evidence from France," PSE-Ecole d'économie de Paris (Postprint) halshs-03342578, HAL.
- Pierre-Philippe Combes & Gilles Duranton & Laurent Gobillon, 2021. "The Production Function for Housing: Evidence from France," Post-Print halshs-03342578, HAL.
- Pierre-Philippe Combes & Gilles Duranton & Laurent Gobillon, 2016. "The Production Function for Housing: Evidence from France," SciencePo Working papers Main halshs-01400852, HAL.
- Pierre-Philippe Combes & Gilles Duranton & Laurent Gobillon, 2017. "The Production Function for Housing: Evidence from France," Post-Print halshs-01661748, HAL.
- Pierre-Philippe Combes & Gilles Duranton & Laurent Gobillon, 2016. "The Production Function for Housing: Evidence from France," PSE Working Papers halshs-01400852, HAL.
- Pierre-Philippe Combes & Gilles Duranton & Laurent Gobillon, 2021. "The Production Function for Housing: Evidence from France," SciencePo Working papers Main halshs-03342578, HAL.
- Combes, Pierre-Philippe & Duranton, Gilles & Gobillon, Laurent, 2016. "The Production Function for Housing: Evidence from France," IZA Discussion Papers 10373, Institute of Labor Economics (IZA).
- Pierre-Philippe Combes & Gilles Duranton & Laurent Gobillon, 2016. "The Production Function for Housing: Evidence from France," Working Papers halshs-01400852, HAL.
- Pierre-Philippe Combes & Gilles Duranton & Laurent Gobillon, 2016. "The Production Function for Housing: Evidence from France," Working Papers halshs-01412393, HAL.
- Pierre-Philippe Combes & Gilles Duranton & Laurent Gobillon, 2017. "The Production Function for Housing: Evidence from France," SciencePo Working papers Main halshs-01661748, HAL.
- Pierre-Philippe Combes & Gilles Duranton & Laurent Gobillon, 2017. "The production function for housing: evidence from France," Working Papers 2017/07, Institut d'Economia de Barcelona (IEB).
- Scott Wentland & Gary Cornwall & Jeremy G. Moulton, 2023. "For What It's Worth: Measuring Land Value in the Era of Big Data and Machine Learning," BEA Papers 0115, Bureau of Economic Analysis.
- Jan K. Brueckner & Ruchi Singh, 2018.
"Stringency of Land-Use Regulation: Building Heights in US Cities,"
CESifo Working Paper Series
6978, CESifo.
- Brueckner, Jan K. & Singh, Ruchi, 2020. "Stringency of land-use regulation: Building heights in US cities," Journal of Urban Economics, Elsevier, vol. 116(C).
- Thisse, Jacques-François & Takayama, Yuki & Ikeda, Kiyohiro, 2020.
"Stability and sustainability of urban systems under commuting and transportation costs,"
CEPR Discussion Papers
14728, C.E.P.R. Discussion Papers.
- Takayama, Yuki & Ikeda, Kiyohiro & Thisse, Jacques-François, 2020. "Stability and sustainability of urban systems under commuting and transportation costs," Regional Science and Urban Economics, Elsevier, vol. 84(C).
- TAKAYAMA Yuki, & IKEDA Kiyohiro, & THISSE Jacques-François,, 2020. "Stability and sustainability of urban systems under commuting and transportation costs," LIDAM Discussion Papers CORE 2020005, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Brunetti, Roberto & Gaigné, Carl & Moizeau, Fabien, 2024.
"Land, Wealth, and Taxation,"
Working Papers
348477, Institut National de la recherche Agronomique (INRA), Departement Sciences Sociales, Agriculture et Alimentation, Espace et Environnement (SAE2).
- Roberto Brunetti & Carl Gaigné & Fabien Moizeau, 2023. "Land, Wealth, and Taxation," Economics Working Paper Archive (University of Rennes & University of Caen) 2023-06, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.
- Coenraad N. Teulings & Ioulia V. Ossokina & Henri L.F. de Groot, 2014.
"Welfare Benefits of Agglomeration and Worker Heterogeneity,"
CESifo Working Paper Series
4939, CESifo.
- Coen Teulings & Ioulia Ossokina & Henri L.F. de Groot, 2014. "Welfare Benefits of Agglomeration and Worker Heterogeneity," Tinbergen Institute Discussion Papers 14-101/VI, Tinbergen Institute.
- Ioulia Ossokina & Coen Teulings & Henri de Groot, 2014. "Welfare Benefits of Agglomeration and Worker Heterogeneity," CPB Discussion Paper 289, CPB Netherlands Bureau for Economic Policy Analysis.
- Teulings, Coen & Ossokina, Ioulia V. & de Groot, Henri L.F., 2014. "Welfare Benefits of Agglomeration and Worker Heterogeneity," IZA Discussion Papers 8382, Institute of Labor Economics (IZA).
- Ahlfeldt, Gabriel & Holman, Nancy, 2016.
"Distinctively Different: A New Approach to Valuing Architectural Amenities,"
CEPR Discussion Papers
11439, C.E.P.R. Discussion Papers.
- Ahlfeldt, Gabriel M. & Holman, Nancy, 2018. "Distinctively different: a new approach to valuing architectural amenities," LSE Research Online Documents on Economics 66241, London School of Economics and Political Science, LSE Library.
- Ahlfeldt, Gabriel M. & Holman, Nancy, 2015. "Distinctively different: a new approach to valuing architectural amenities," LSE Research Online Documents on Economics 64506, London School of Economics and Political Science, LSE Library.
- Gabriel Ahlfeldt & Nancy Holman, 2015. "Distinctively different: A new approach to valuing architectural amenities," ERSA conference papers ersa15p61, European Regional Science Association.
- Gabriel M. Ahlfeldt & Nancy Holman, 2018. "Distinctively Different: A New Approach to Valuing Architectural Amenities," Economic Journal, Royal Economic Society, vol. 128(608), pages 1-33, February.
- Gabriel M. Ahlfeldt & Nancy Holman, 2015. "Distinctively Different: A New Approach to Valuing Architectural Amenities," CESifo Working Paper Series 5221, CESifo.
- Gabriel M. Ahlfeldt & Nancy Holman, 2015. "Distinctively Different: A New Approach to Valuing Architectural Amenities," SERC Discussion Papers 0171, Centre for Economic Performance, LSE.
- Teulings, Coen & Lange, Rutger-Jan, 2021.
"The option value of vacant land: Don't build when demand for housing is booming,"
CEPR Discussion Papers
16023, C.E.P.R. Discussion Papers.
- Rutger-Jan Lange & Coen N. Teulings, 2021. "The option value of vacant land: Don't build when demand for housing is booming," Tinbergen Institute Discussion Papers 21-022/IV, Tinbergen Institute.
- Gaigné, Carl & Thisse, Jacques-François, 2013.
"New Economic Geography and the City,"
Working Papers
207859, Institut National de la recherche Agronomique (INRA), Departement Sciences Sociales, Agriculture et Alimentation, Espace et Environnement (SAE2).
- Thisse, Jacques-François & Gaigné, Carl, 2019. "New Economic Geography and the City," CEPR Discussion Papers 13638, C.E.P.R. Discussion Papers.
- Carl Gaigné & Jacques-François Thisse, 2013. "New economic geography and the city," Working Papers hal-01208856, HAL.
- Carl Gaigné & Jacques-François Thisse, 2013. "New Economic Geography and the City," Working Papers SMART 13-02, INRAE UMR SMART.
- William Larson, 2015. "New Estimates of Value of Land of the United States," BEA Working Papers 0120, Bureau of Economic Analysis.
- Van Nieuwerburgh, Stijn & Gupta, Arpit & Mittal, Vrinda & Peeters, Jonas, 2021.
"Flattening the Curve: Pandemic-Induced Revaluation of Urban Real Estate,"
CEPR Discussion Papers
16080, C.E.P.R. Discussion Papers.
- Gupta, Arpit & Mittal, Vrinda & Peeters, Jonas & Van Nieuwerburgh, Stijn, 2022. "Flattening the curve: Pandemic-Induced revaluation of urban real estate," Journal of Financial Economics, Elsevier, vol. 146(2), pages 594-636.
- Arpit Gupta & Vrinda Mittal & Jonas Peeters & Stijn Van Nieuwerburgh, 2021. "Flattening the Curve: Pandemic-Induced Revaluation of Urban Real Estate," NBER Working Papers 28675, National Bureau of Economic Research, Inc.
- Lange, Rutger-Jan & Teulings, Coen N., 2024. "Irreversible investment under predictable growth: Why land stays vacant when housing demand is booming," Journal of Economic Theory, Elsevier, vol. 215(C).
- Pierre-Philippe Combes & Gilles Duranton & Laurent Gobillon, 2012.
"The Costs of Agglomeration: Land Prices in French Cities,"
AMSE Working Papers
1235, Aix-Marseille School of Economics, France.
- Pierre-Philippe Combes & Gilles Duranton & Laurent Gobillon, 2013. "The Costs of Agglomeration: Land Prices in French Cities," Working Papers halshs-00849078, HAL.
- Pierre-Philippe Combes & Gilles Duranton & Laurent Gobillon, 2012. "The Costs of Agglomeration: Land Prices in French Cities," PSE Working Papers halshs-00793632, HAL.
- Pierre-Philippe Combes & Gilles Duranton & Laurent Gobillon, 2013. "The Costs of Agglomeration: Land Prices in French Cities," PSE Working Papers halshs-00849078, HAL.
- Pierre-Philippe Combes & Gilles Duranton & Laurent Gobillon, 2012. "The Costs of Agglomeration: Land Prices in French Cities," Working Papers halshs-00793632, HAL.
- Combes, Pierre-Philippe & Duranton, Gilles & Gobillon, Laurent, 2012. "The Costs of Agglomeration: Land Prices in French Cities," IZA Discussion Papers 7027, Institute of Labor Economics (IZA).
- Murray, Cameron, 2019. "Marginal and average prices of land lots should not be equal: A critique of Glaeser and Gyourko’s method for identifying residential price effects of town planning regulations," OSF Preprints fnz7v, Center for Open Science.
- Bonnet, Odran & Chapelle, Guillaume & Trannoy, Alain & Wasmer, Etienne, 2021.
"Land is back, it should be taxed, it can be taxed,"
European Economic Review, Elsevier, vol. 134(C).
- Wasmer, Etienne & Bonnet, Odran & Chapelle, Guillaume & Trannoy, Alain, 2021. "Land is back, it should be taxed, it can be taxed," CEPR Discussion Papers 15845, C.E.P.R. Discussion Papers.
- Odran Bonnet & Guillaume Chapelle & Alain Trannoy & Etienne Wasmer, 2021. "Land is back, it should be taxed, it can be taxed," Post-Print hal-03238443, HAL.
- Odran Bonnet & Guillaume Flamerie de La Chapelle & Alain Trannoy & Etienne Wasmer, 2019.
"Secular Trends in Wealth and Heterogeneous Capital: Land is Back... and Should Be Taxed,"
SciencePo Working papers Main
hal-03570837, HAL.
- Odran Bonnet & Guillaume Flamerie de La Chapelle & Alain Trannoy & Etienne Wasmer, 2019. "Secular trends in Wealth and Heterogeneous Capital: Land is back...and should be taxed," Working Papers hal-03541411, HAL.
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- Odran Bonnet & Guillaume Flamerie de La Chapelle & Alain Trannoy & Etienne Wasmer, 2019. "Secular Trends in Wealth and Heterogeneous Capital: Land is Back... and Should Be Taxed," Working Papers hal-03570837, HAL.
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- Norman R. Swanson & Weiqi Xiong, 2018.
"Big data analytics in economics: What have we learned so far, and where should we go from here?,"
Canadian Journal of Economics, Canadian Economics Association, vol. 51(3), pages 695-746, August.
- Norman R. Swanson & Weiqi Xiong, 2018. "Big data analytics in economics: What have we learned so far, and where should we go from here?," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 51(3), pages 695-746, August.
- Emilian Dobrescu, 2014. "Attempting to Quantify the Accuracy of Complex Macroeconomic Forecasts," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 5-21, December.
- Jin, Sainan & Corradi, Valentina & Swanson, Norman R., 2017.
"Robust Forecast Comparison,"
Econometric Theory, Cambridge University Press, vol. 33(6), pages 1306-1351, December.
- Sainan Jin & Valentina Corradi & Norman Swanson, 2015. "Robust Forecast Comparison," Departmental Working Papers 201502, Rutgers University, Department of Economics.
- Valentina Corradi & Sainan Jin & Norman R. Swanson, 2023. "Robust forecast superiority testing with an application to assessing pools of expert forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 596-622, June.
- Yen, Yu-Min & Yen, Tso-Jung, 2021. "Testing forecast accuracy of expectiles and quantiles with the extremal consistent loss functions," International Journal of Forecasting, Elsevier, vol. 37(2), pages 733-758.