Jaqueson Kingeski Galimberti

Personal Details

First Name:	Jaqueson
Middle Name:	Kingeski
Last Name:	Galimberti
Suffix:
RePEc Short-ID:	pga316
	[This author has chosen not to make the email address public]
	http://sites.google.com/site/jkgeconoeng/
Twitter:	@galimberti_jk
Terminal Degree:	2013 Department of Economics; School of Social Sciences; University of Manchester (from RePEc Genealogy)

Affiliation

(1%) Centre for Applied Macroeconomic Analysis (CAMA)
Crawford School of Public Policy
Australian National University

Canberra, Australia
https://cama.crawford.anu.edu.au/
RePEc:edi:cmanuau (more details at EDIRC)

(98%) Economics and Research Department
Asian Development Bank

Manila, Philippines
http://www.adb.org/data/main
RePEc:edi:eradbph (more details at EDIRC)

(1%) KOF Swiss Economic Institute
Department of Management, Technology and Economics (D-MTEC)
Eidgenössische Technische Hochschule Zürich (ETHZ)

Zürich, Switzerland
http://www.kof.ethz.ch/
RePEc:edi:koethch (more details at EDIRC)

Citations

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

Working papers

1. Jaqueson K. Galimberti, 2020. "Forecasting GDP growth from outer space," Working Papers 2020-02, Auckland University of Technology, Department of Economics.
   • Jaqueson K. Galimberti, 2020. "Forecasting GDP Growth from Outer Space," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(4), pages 697-722, August.
   • Jaqueson K Galimberti, 2017. "Forecasting GDP growth from the outer space," KOF Working papers 17-427, KOF Swiss Economic Institute, ETH Zurich.

   Cited by:

   1. Flávio Menezes & Vivian Figer & Fernanda Jardim & Pedro Medeiros, 2021. "Using electricity consumption to predict economic activity during COVID-19 in Brazil," Discussion Papers Series 641, School of Economics, University of Queensland, Australia.
   2. Carlo Fezzi & Valeria Fanghella, 2020. "Real-time estimation of the short-run impact of COVID-19 on economic activity using electricity market data," Papers 2007.03477, arXiv.org.
   3. Menezes, Flavio & Figer, Vivian & Jardim, Fernanda & Medeiros, Pedro, 2022. "A near real-time economic activity tracker for the Brazilian economy during the COVID-19 pandemic," Economic Modelling, Elsevier, vol. 112(C).
   4. Carlo Fezzi & Valeria Fanghella, 2020. "Real-time estimation of the short-run impact of COVID-19 on economic activity using electricity market data," DEM Working Papers 2020/8, Department of Economics and Management.
   5. Jaqueson K. Galimberti & Stefan Pichler & Regina Pleninger, 2021. "Measuring Inequality using Geospatial Data," KOF Working papers 21-493, KOF Swiss Economic Institute, ETH Zurich.
      • Jaqueson Galimberti & Stefan Pichler & Regina Pleninger, 2020. "Measuring Inequality using Geospatial Data," Working Papers 2020-07, Auckland University of Technology, Department of Economics.
      • Jaqueson K Galimberti & Stefan Pichler & Regina Pleninger, 2023. "Measuring Inequality Using Geospatial Data," The World Bank Economic Review, World Bank, vol. 37(4), pages 549-569.
   6. Mitze, Timo & Breidenbach, Philipp, 2023. "The complex regional effects of macro-institutional shocks: Evidence from EU economic integration over three decades," Ruhr Economic Papers 1007, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
   7. Francisco Corona & Elio Atenógenes Villaseñor & Jesús López-Pérez & Ranyart R. Suárez, 2023. "Estimating Mexican municipal-level economic activity indicators using nighttime lights," Empirical Economics, Springer, vol. 65(3), pages 1197-1214, September.
   8. Carlo Fezzi & Valeria Fanghella, 2020. "Real-Time Estimation of the Short-Run Impact of COVID-19 on Economic Activity Using Electricity Market Data," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 76(4), pages 885-900, August.

2. Jaqueson Galimberti & Stefan Pichler & Regina Pleninger, 2020. "Measuring Inequality using Geospatial Data," Working Papers 2020-07, Auckland University of Technology, Department of Economics.
   • Jaqueson K Galimberti & Stefan Pichler & Regina Pleninger, 2023. "Measuring Inequality Using Geospatial Data," The World Bank Economic Review, World Bank, vol. 37(4), pages 549-569.
   • Jaqueson K. Galimberti & Stefan Pichler & Regina Pleninger, 2021. "Measuring Inequality using Geospatial Data," KOF Working papers 21-493, KOF Swiss Economic Institute, ETH Zurich.

   Cited by:

   1. Nattapong Puttanapong & Amornrat Luenam & Pit Jongwattanakul, 2022. "Spatial Analysis of Inequality in Thailand: Applications of Satellite Data and Spatial Statistics/Econometrics," Sustainability, MDPI, vol. 14(7), pages 1-25, March.

3. Jaqueson K. Galimberti, 2020. "Information weighting under least squares adaptive learning," Working Papers 2020-04, Auckland University of Technology, Department of Economics.
   • Jaqueson Galimberti, 2021. "Initial Beliefs Uncertainty and Information Weighting in the Estimation of Models with Adaptive Learning," Working Papers 2021-01, Auckland University of Technology, Department of Economics.
   • Jaqueson K. Galimberti, 2021. "Initial beliefs uncertainty," CAMA Working Papers 2021-68, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
   • Jaqueson K. Galimberti, 2020. "Information weighting under least squares learning," CAMA Working Papers 2020-46, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

   Cited by:

   1. Stephen J. Cole & Fabio Milani, 2020. "Heterogeneity in Individual Expectations, Sentiment, and Constant-Gain Learning," CESifo Working Paper Series 8343, CESifo.
      • Cole, Stephen J. & Milani, Fabio, 2021. "Heterogeneity in Individual Expectations, Sentiment, and Constant-Gain Learning," Working Papers and Research 2021-05, Marquette University, Center for Global and Economic Studies and Department of Economics.
      • Stephen J. Cole & Fabio Milani, 2020. "Heterogeneity in Individual Expectations, Sentiment, and Constant-Gain Learning," Working Papers 192005, University of California-Irvine, Department of Economics.
      • Cole, Stephen J. & Milani, Fabio, 2021. "Heterogeneity in individual expectations, sentiment, and constant-gain learning," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 627-650.

4. Jaqueson Kingeski Galimberti, 2019. "An approximation of the distribution of learning estimates in macroeconomic models," KOF Working papers 19-453, KOF Swiss Economic Institute, ETH Zurich.
   • Galimberti, Jaqueson K., 2019. "An approximation of the distribution of learning estimates in macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 102(C), pages 29-43.

   Cited by:

   1. Jaqueson Galimberti, 2021. "Initial Beliefs Uncertainty and Information Weighting in the Estimation of Models with Adaptive Learning," Working Papers 2021-01, Auckland University of Technology, Department of Economics.
      • Jaqueson K. Galimberti, 2020. "Information weighting under least squares adaptive learning," Working Papers 2020-04, Auckland University of Technology, Department of Economics.
      • Jaqueson K. Galimberti, 2021. "Initial beliefs uncertainty," CAMA Working Papers 2021-68, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
      • Jaqueson K. Galimberti, 2020. "Information weighting under least squares learning," CAMA Working Papers 2020-46, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

5. Michele Berardi & Jaqueson K Galimberti, 2017. "Smoothing-based Initialization for Learning-to-Forecast Algorithms," KOF Working papers 17-425, KOF Swiss Economic Institute, ETH Zurich.
   • Berardi, Michele & Galimberti, Jaqueson K., 2019. "Smoothing-Based Initialization For Learning-To-Forecast Algorithms," Macroeconomic Dynamics, Cambridge University Press, vol. 23(3), pages 1008-1023, April.

   Cited by:

   1. Michele Berardi & Jaqueson K Galimberti, 2016. "On the Initialization of Adaptive Learning in Macroeconomic Models," KOF Working papers 16-422, KOF Swiss Economic Institute, ETH Zurich.
      • Berardi, Michele & Galimberti, Jaqueson K., 2017. "On the initialization of adaptive learning in macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 78(C), pages 26-53.

6. Michele Berardi & Jaqueson K Galimberti, 2016. "On the Initialization of Adaptive Learning in Macroeconomic Models," KOF Working papers 16-422, KOF Swiss Economic Institute, ETH Zurich.
   • Berardi, Michele & Galimberti, Jaqueson K., 2017. "On the initialization of adaptive learning in macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 78(C), pages 26-53.

   Cited by:

   1. Berardi, Michele & Galimberti, Jaqueson K., 2017. "Empirical calibration of adaptive learning," Journal of Economic Behavior & Organization, Elsevier, vol. 144(C), pages 219-237.
      • Michele Berardi & Jaqueson K. Galimberti, 2015. "Empirical Calibration of Adaptive Learning," KOF Working papers 15-392, KOF Swiss Economic Institute, ETH Zurich.
   2. Jaqueson Galimberti, 2021. "Initial Beliefs Uncertainty and Information Weighting in the Estimation of Models with Adaptive Learning," Working Papers 2021-01, Auckland University of Technology, Department of Economics.
      • Jaqueson K. Galimberti, 2020. "Information weighting under least squares adaptive learning," Working Papers 2020-04, Auckland University of Technology, Department of Economics.
      • Jaqueson K. Galimberti, 2021. "Initial beliefs uncertainty," CAMA Working Papers 2021-68, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
      • Jaqueson K. Galimberti, 2020. "Information weighting under least squares learning," CAMA Working Papers 2020-46, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
   3. Berardi, Michele & Galimberti, Jaqueson K., 2019. "Smoothing-Based Initialization For Learning-To-Forecast Algorithms," Macroeconomic Dynamics, Cambridge University Press, vol. 23(3), pages 1008-1023, April.
      • Michele Berardi & Jaqueson K Galimberti, 2017. "Smoothing-based Initialization for Learning-to-Forecast Algorithms," KOF Working papers 17-425, KOF Swiss Economic Institute, ETH Zurich.
   4. Panovska, Irina & Ramamurthy, Srikanth, 2022. "Decomposing the output gap with inflation learning," Journal of Economic Dynamics and Control, Elsevier, vol. 136(C).
   5. Stephen J. Cole & Fabio Milani, 2020. "Heterogeneity in Individual Expectations, Sentiment, and Constant-Gain Learning," CESifo Working Paper Series 8343, CESifo.
      • Cole, Stephen J. & Milani, Fabio, 2021. "Heterogeneity in Individual Expectations, Sentiment, and Constant-Gain Learning," Working Papers and Research 2021-05, Marquette University, Center for Global and Economic Studies and Department of Economics.
      • Stephen J. Cole & Fabio Milani, 2020. "Heterogeneity in Individual Expectations, Sentiment, and Constant-Gain Learning," Working Papers 192005, University of California-Irvine, Department of Economics.
      • Cole, Stephen J. & Milani, Fabio, 2021. "Heterogeneity in individual expectations, sentiment, and constant-gain learning," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 627-650.
   6. Michele Berardi & Jaqueson K Galimberti, 2016. "On the Initialization of Adaptive Learning in Macroeconomic Models," KOF Working papers 16-422, KOF Swiss Economic Institute, ETH Zurich.
      • Berardi, Michele & Galimberti, Jaqueson K., 2017. "On the initialization of adaptive learning in macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 78(C), pages 26-53.

7. Michele Berardi & Jaqueson K. Galimberti, 2015. "Empirical Calibration of Adaptive Learning," KOF Working papers 15-392, KOF Swiss Economic Institute, ETH Zurich.
   • Berardi, Michele & Galimberti, Jaqueson K., 2017. "Empirical calibration of adaptive learning," Journal of Economic Behavior & Organization, Elsevier, vol. 144(C), pages 219-237.

   Cited by:

   1. Stefan Nagel & Zhengyang Xu, 2019. "Asset Pricing with Fading Memory," NBER Working Papers 26255, National Bureau of Economic Research, Inc.
      • Stefan Nagel & Zhengyang Xu, 2022. "Asset Pricing with Fading Memory," The Review of Financial Studies, Society for Financial Studies, vol. 35(5), pages 2190-2245.
      • Stefan Nagel & Zhengyang Xu, 2019. "Asset Pricing with Fading Memory," 2019 Meeting Papers 71, Society for Economic Dynamics.
      • Nagel, Stefan & Xu, Zhengyang, 2019. "Asset Pricing with Fading Memory," CEPR Discussion Papers 13973, C.E.P.R. Discussion Papers.
   2. Mayer, Alexander, 2023. "Two-step estimation in linear regressions with adaptive learning," Statistics & Probability Letters, Elsevier, vol. 195(C).
   3. Jaqueson Galimberti, 2021. "Initial Beliefs Uncertainty and Information Weighting in the Estimation of Models with Adaptive Learning," Working Papers 2021-01, Auckland University of Technology, Department of Economics.
      • Jaqueson K. Galimberti, 2020. "Information weighting under least squares adaptive learning," Working Papers 2020-04, Auckland University of Technology, Department of Economics.
      • Jaqueson K. Galimberti, 2021. "Initial beliefs uncertainty," CAMA Working Papers 2021-68, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
      • Jaqueson K. Galimberti, 2020. "Information weighting under least squares learning," CAMA Working Papers 2020-46, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
   4. Michele Berardi, 2018. "Information aggregation and learning in a dynamic asset pricing model," Centre for Growth and Business Cycle Research Discussion Paper Series 241, Economics, The University of Manchester.
   5. Cars Hommes & Kostas Mavromatis & Tolga Özden & Mei Zhu, 2023. "Behavioral learning equilibria in New Keynesian models," Quantitative Economics, Econometric Society, vol. 14(4), pages 1401-1445, November.
      • Cars Hommes & Kostas Mavromatis & Tolga Özden & Mei Zhu, 2022. "Behavioral Learning Equilibria in New Keynesian Models," Staff Working Papers 22-42, Bank of Canada.
   6. Jingru Jia & Zehua Yuan, 2024. "An Experimental Study of Competitive Market Behavior Through LLMs," Papers 2409.08357, arXiv.org, revised Oct 2024.
   7. Kobielarz, Michal, 2018. "The economics of monetary unions," Other publications TiSEM b0293536-68ec-4905-bffd-6, Tilburg University, School of Economics and Management.
   8. Koursaros, Demetris, 2019. "Learning expectations using multi-period forecasts," Journal of Economics and Business, Elsevier, vol. 102(C), pages 1-25.
   9. Jaqueson Kingeski Galimberti, 2019. "An approximation of the distribution of learning estimates in macroeconomic models," KOF Working papers 19-453, KOF Swiss Economic Institute, ETH Zurich.
      • Galimberti, Jaqueson K., 2019. "An approximation of the distribution of learning estimates in macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 102(C), pages 29-43.
   10. Michele Berardi, 2020. "A probabilistic interpretation of the constant gain learning algorithm," Bulletin of Economic Research, Wiley Blackwell, vol. 72(4), pages 393-403, October.
   11. Stephen J. Cole & Fabio Milani, 2020. "Heterogeneity in Individual Expectations, Sentiment, and Constant-Gain Learning," CESifo Working Paper Series 8343, CESifo.
       • Cole, Stephen J. & Milani, Fabio, 2021. "Heterogeneity in Individual Expectations, Sentiment, and Constant-Gain Learning," Working Papers and Research 2021-05, Marquette University, Center for Global and Economic Studies and Department of Economics.
       • Stephen J. Cole & Fabio Milani, 2020. "Heterogeneity in Individual Expectations, Sentiment, and Constant-Gain Learning," Working Papers 192005, University of California-Irvine, Department of Economics.
       • Cole, Stephen J. & Milani, Fabio, 2021. "Heterogeneity in individual expectations, sentiment, and constant-gain learning," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 627-650.
   12. Poledna, Sebastian & Miess, Michael Gregor & Hommes, Cars & Rabitsch, Katrin, 2023. "Economic forecasting with an agent-based model," European Economic Review, Elsevier, vol. 151(C).
   13. Michele Berardi, 2016. "Herding through learning in an asset pricing model," Centre for Growth and Business Cycle Research Discussion Paper Series 223, Economics, The University of Manchester.
   14. Alexander Mayer, 2022. "Estimation and inference in adaptive learning models with slowly decreasing gains," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(5), pages 720-749, September.
   15. Berardi, Michele, 2019. "A probabilistic interpretation of the constant gain algorithm," MPRA Paper 94023, University Library of Munich, Germany.

8. Jaqueson K. Galimberti & Marcelo L. Moura, 2014. "Improving the reliability of real-time Hodrick-Prescott Filtering using survey forecasts," KOF Working papers 14-360, KOF Swiss Economic Institute, ETH Zurich.
   • Jaqueson K. Galimberti & Marcelo L. Moura, 2011. "Improving the reliability of real-time Hodrick-Prescott filtering using survey forecasts," Centre for Growth and Business Cycle Research Discussion Paper Series 159, Economics, The University of Manchester.

   Cited by:

   1. Jaqueson K. Galimberti & Nicolas Suhadolnik & Sergio Silva, 2017. "Cowboying Stock Market Herds with Robot Traders," Computational Economics, Springer;Society for Computational Economics, vol. 50(3), pages 393-423, October.
      • Galimberti, Jaqueson & Suhadolnik, Nicolas & Da Silva, Sergio, 2016. "Cowboying Stock Market Herds with Robot Traders," MPRA Paper 71758, University Library of Munich, Germany.
   2. Galimberti, Jaqueson K. & Moura, Marcelo L., 2010. "Taylor Rules and Exchange Rate Predictability in Emerging Economies," Insper Working Papers wpe_214, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
      • Galimberti, Jaqueson K. & Moura, Marcelo L., 2013. "Taylor rules and exchange rate predictability in emerging economies," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 1008-1031.

9. Michele Bernardi & Jaqueson K. Galimberti, 2014. "A Note on the Representative Adaptive Learning Algorithm," KOF Working papers 14-356, KOF Swiss Economic Institute, ETH Zurich.
   • Berardi, Michele & Galimberti, Jaqueson K., 2014. "A note on the representative adaptive learning algorithm," Economics Letters, Elsevier, vol. 124(1), pages 104-107.

   Cited by:

   1. Berardi, Michele & Galimberti, Jaqueson K., 2017. "Empirical calibration of adaptive learning," Journal of Economic Behavior & Organization, Elsevier, vol. 144(C), pages 219-237.
      • Michele Berardi & Jaqueson K. Galimberti, 2015. "Empirical Calibration of Adaptive Learning," KOF Working papers 15-392, KOF Swiss Economic Institute, ETH Zurich.
   2. Jaqueson Galimberti, 2021. "Initial Beliefs Uncertainty and Information Weighting in the Estimation of Models with Adaptive Learning," Working Papers 2021-01, Auckland University of Technology, Department of Economics.
      • Jaqueson K. Galimberti, 2020. "Information weighting under least squares adaptive learning," Working Papers 2020-04, Auckland University of Technology, Department of Economics.
      • Jaqueson K. Galimberti, 2021. "Initial beliefs uncertainty," CAMA Working Papers 2021-68, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
      • Jaqueson K. Galimberti, 2020. "Information weighting under least squares learning," CAMA Working Papers 2020-46, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
   3. Damjanovic, Tatiana & Girdėnas, Šarūnas & Liu, Keqing, 2015. "Stationarity of econometric learning with bounded memory and a predicted state variable," Economics Letters, Elsevier, vol. 130(C), pages 93-96.
      • Tatiana Damjanovic & Sarunas Girdenas & Keqing Liu, 2015. "Stationarity of Econometric Learning with Bounded Memory and a Predicted State Variable," Discussion Papers 1502, University of Exeter, Department of Economics.
   4. Panovska, Irina & Ramamurthy, Srikanth, 2022. "Decomposing the output gap with inflation learning," Journal of Economic Dynamics and Control, Elsevier, vol. 136(C).
   5. Jaqueson Kingeski Galimberti, 2019. "An approximation of the distribution of learning estimates in macroeconomic models," KOF Working papers 19-453, KOF Swiss Economic Institute, ETH Zurich.
      • Galimberti, Jaqueson K., 2019. "An approximation of the distribution of learning estimates in macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 102(C), pages 29-43.
   6. Michele Berardi & Jaqueson K Galimberti, 2016. "On the Initialization of Adaptive Learning in Macroeconomic Models," KOF Working papers 16-422, KOF Swiss Economic Institute, ETH Zurich.
      • Berardi, Michele & Galimberti, Jaqueson K., 2017. "On the initialization of adaptive learning in macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 78(C), pages 26-53.

10. Michele Berardi & Jaqueson K. Galimberti, 2012. "A note on exact correspondences between adaptive learning algorithms and the Kalman filter," Centre for Growth and Business Cycle Research Discussion Paper Series 170, Economics, The University of Manchester.
    • Berardi, Michele & Galimberti, Jaqueson K., 2013. "A note on exact correspondences between adaptive learning algorithms and the Kalman filter," Economics Letters, Elsevier, vol. 118(1), pages 139-142.

    Cited by:

    1. Marine Charlotte André & Meixing Dai, 2016. "Learning, robust monetray policy and the merit of precaution," Working Papers of BETA 2016-54, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
       • Marine Charlotte André & Meixing Dai, 2018. "Learning, robust monetary policy and the merit of precaution," Post-Print hal-03030047, HAL.
       • André Marine Charlotte & Dai Meixing, 2018. "Learning, robust monetary policy and the merit of precaution," The B.E. Journal of Macroeconomics, De Gruyter, vol. 18(2), pages 1-20, June.
    2. Berardi, Michele & Galimberti, Jaqueson K., 2017. "Empirical calibration of adaptive learning," Journal of Economic Behavior & Organization, Elsevier, vol. 144(C), pages 219-237.
       • Michele Berardi & Jaqueson K. Galimberti, 2015. "Empirical Calibration of Adaptive Learning," KOF Working papers 15-392, KOF Swiss Economic Institute, ETH Zurich.
    3. Jaqueson Galimberti, 2021. "Initial Beliefs Uncertainty and Information Weighting in the Estimation of Models with Adaptive Learning," Working Papers 2021-01, Auckland University of Technology, Department of Economics.
       • Jaqueson K. Galimberti, 2020. "Information weighting under least squares adaptive learning," Working Papers 2020-04, Auckland University of Technology, Department of Economics.
       • Jaqueson K. Galimberti, 2021. "Initial beliefs uncertainty," CAMA Working Papers 2021-68, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
       • Jaqueson K. Galimberti, 2020. "Information weighting under least squares learning," CAMA Working Papers 2020-46, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Berardi, Michele & Galimberti, Jaqueson K., 2019. "Smoothing-Based Initialization For Learning-To-Forecast Algorithms," Macroeconomic Dynamics, Cambridge University Press, vol. 23(3), pages 1008-1023, April.
       • Michele Berardi & Jaqueson K Galimberti, 2017. "Smoothing-based Initialization for Learning-to-Forecast Algorithms," KOF Working papers 17-425, KOF Swiss Economic Institute, ETH Zurich.
    5. Schaefer, Daniel & Singleton, Carl, 2018. "Unemployment and econometric learning," Research in Economics, Elsevier, vol. 72(2), pages 277-296.
       • Singleton, Carl & Schaefer, Daniel, 2015. "Unemployment and econometric learning," MPRA Paper 63162, University Library of Munich, Germany.
       • Daniel Schaefer & Carl A. Singleton, 2016. "Unemployment and econometric learning," Edinburgh School of Economics Discussion Paper Series 267, Edinburgh School of Economics, University of Edinburgh.
    6. Jaqueson Kingeski Galimberti, 2019. "An approximation of the distribution of learning estimates in macroeconomic models," KOF Working papers 19-453, KOF Swiss Economic Institute, ETH Zurich.
       • Galimberti, Jaqueson K., 2019. "An approximation of the distribution of learning estimates in macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 102(C), pages 29-43.
    7. Michele Berardi, 2020. "A probabilistic interpretation of the constant gain learning algorithm," Bulletin of Economic Research, Wiley Blackwell, vol. 72(4), pages 393-403, October.
    8. Michele Berardi & Jaqueson K. Galimberti, 2012. "A note on exact correspondences between adaptive learning algorithms and the Kalman filter," Centre for Growth and Business Cycle Research Discussion Paper Series 170, Economics, The University of Manchester.
       • Berardi, Michele & Galimberti, Jaqueson K., 2013. "A note on exact correspondences between adaptive learning algorithms and the Kalman filter," Economics Letters, Elsevier, vol. 118(1), pages 139-142.
    9. Marine Charlotte André & Meixing Dai, 2015. "Central bank accountability under adaptive learning," Working Papers of BETA 2015-32, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    10. Michele Berardi & Jaqueson K Galimberti, 2016. "On the Initialization of Adaptive Learning in Macroeconomic Models," KOF Working papers 16-422, KOF Swiss Economic Institute, ETH Zurich.
        • Berardi, Michele & Galimberti, Jaqueson K., 2017. "On the initialization of adaptive learning in macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 78(C), pages 26-53.
    11. Berardi, Michele, 2019. "A probabilistic interpretation of the constant gain algorithm," MPRA Paper 94023, University Library of Munich, Germany.
    12. Michele Berardi & Jaqueson K. Galimberti, 2012. "On the plausibility of adaptive learning in macroeconomics: A puzzling conflict in the choice of the representative algorithm," Centre for Growth and Business Cycle Research Discussion Paper Series 177, Economics, The University of Manchester.
    13. Michele Berardi & Jaqueson K. Galimberti, 2012. "On the initialization of adaptive learning algorithms: A review of methods and a new smoothing-based routine," Centre for Growth and Business Cycle Research Discussion Paper Series 175, Economics, The University of Manchester.

11. Michele Berardi & Jaqueson K. Galimberti, 2012. "On the plausibility of adaptive learning in macroeconomics: A puzzling conflict in the choice of the representative algorithm," Centre for Growth and Business Cycle Research Discussion Paper Series 177, Economics, The University of Manchester.

    Cited by:

    1. Schaefer, Daniel & Singleton, Carl, 2018. "Unemployment and econometric learning," Research in Economics, Elsevier, vol. 72(2), pages 277-296.
       • Singleton, Carl & Schaefer, Daniel, 2015. "Unemployment and econometric learning," MPRA Paper 63162, University Library of Munich, Germany.
       • Daniel Schaefer & Carl A. Singleton, 2016. "Unemployment and econometric learning," Edinburgh School of Economics Discussion Paper Series 267, Edinburgh School of Economics, University of Edinburgh.
    2. Markiewicz, Agnieszka & Pick, Andreas, 2014. "Adaptive learning and survey data," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 685-707.

12. Michele Berardi & Jaqueson K. Galimberti, 2012. "On the initialization of adaptive learning algorithms: A review of methods and a new smoothing-based routine," Centre for Growth and Business Cycle Research Discussion Paper Series 175, Economics, The University of Manchester.

    Cited by:

    1. Berardi, Michele & Galimberti, Jaqueson K., 2019. "Smoothing-Based Initialization For Learning-To-Forecast Algorithms," Macroeconomic Dynamics, Cambridge University Press, vol. 23(3), pages 1008-1023, April.
       • Michele Berardi & Jaqueson K Galimberti, 2017. "Smoothing-based Initialization for Learning-to-Forecast Algorithms," KOF Working papers 17-425, KOF Swiss Economic Institute, ETH Zurich.
    2. Berardi, Michele & Galimberti, Jaqueson K., 2014. "A note on the representative adaptive learning algorithm," Economics Letters, Elsevier, vol. 124(1), pages 104-107.
       • Michele Bernardi & Jaqueson K. Galimberti, 2014. "A Note on the Representative Adaptive Learning Algorithm," KOF Working papers 14-356, KOF Swiss Economic Institute, ETH Zurich.
    3. Markiewicz, Agnieszka & Pick, Andreas, 2014. "Adaptive learning and survey data," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 685-707.
    4. Michele Berardi & Jaqueson K. Galimberti, 2012. "On the plausibility of adaptive learning in macroeconomics: A puzzling conflict in the choice of the representative algorithm," Centre for Growth and Business Cycle Research Discussion Paper Series 177, Economics, The University of Manchester.

13. Fernando Seabra & Jaqueson K. Galimberti, 2011. "Conditioned Export-Led Growthhypothesis: A Panel Threshold Regressions Approach," Anais do XXXVIII Encontro Nacional de Economia [Proceedings of the 38th Brazilian Economics Meeting] 049, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    • Galimberti, Jaqueson K., 2009. "Conditioned Export-Led Growth Hypothesis: A Panel Threshold Regressions Approach," MPRA Paper 13417, University Library of Munich, Germany.

    Cited by:

    1. Anca Maria GHERMAN & George ȘTEFAN, 2015. "Exports – trends and impacts on Romania’s economic growth process," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(2(603), S), pages 43-54, Summer.
    2. Fatma Zeren & Burcu Kilinc Savrul, 2013. "Revisited Export-Led Growth Hypothesis For Selected European Countries: A Panel Hidden Cointegration Approach," Istanbul University Econometrics and Statistics e-Journal, Department of Econometrics, Faculty of Economics, Istanbul University, vol. 18(1), pages 134-151, May.
    3. Sahoo, Auro Kumar & Sahoo, Dukhabandhu & Sahu, Naresh Chandra, 2014. "Mining export, industrial production and economic growth: A cointegration and causality analysis for India," Resources Policy, Elsevier, vol. 42(C), pages 27-34.

14. Suhadolnik, Nicolas & Galimberti, Jaqueson & Da Silva, Sergio, 2010. "Robot traders can prevent extreme events in complex stock markets," MPRA Paper 23923, University Library of Munich, Germany.
    • Suhadolnik, Nicolas & Galimberti, Jaqueson & Da Silva, Sergio, 2010. "Robot traders can prevent extreme events in complex stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5182-5192.

    Cited by:

    1. Jaqueson K. Galimberti & Nicolas Suhadolnik & Sergio Silva, 2017. "Cowboying Stock Market Herds with Robot Traders," Computational Economics, Springer;Society for Computational Economics, vol. 50(3), pages 393-423, October.
       • Galimberti, Jaqueson & Suhadolnik, Nicolas & Da Silva, Sergio, 2016. "Cowboying Stock Market Herds with Robot Traders," MPRA Paper 71758, University Library of Munich, Germany.
    2. Da Silva, Sergio, 2014. "Why Not Use Robots to Stabilize Stock Markets?," MPRA Paper 60567, University Library of Munich, Germany.
    3. Da Silva, Sergio, 2013. "Time to abandon group thinking in economics," MPRA Paper 45660, University Library of Munich, Germany.

15. Galimberti, Jaqueson K. & Moura, Marcelo L., 2010. "Taylor Rules and Exchange Rate Predictability in Emerging Economies," Insper Working Papers wpe_214, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    • Galimberti, Jaqueson K. & Moura, Marcelo L., 2013. "Taylor rules and exchange rate predictability in emerging economies," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 1008-1031.

    Cited by:

    1. Guglielmo Maria Caporale & Abdurrahman Nazif Catik & Mohamad Husam Helmi & Faek Nemla Ali & Coskun Akdeniz, 2016. "Monetary Policy Rules in Emerging Countries: Is there an Augmented Nonlinear Taylor Rule?," CESifo Working Paper Series 5965, CESifo.
       • Guglielmo Maria Caporale & Abdurrahman Nazif Catik & Mohamad Husam Helmi & Faek Menla Ali & Coskun Akdeniz, 2016. "Monetary Policy Rules in Emerging Countries: Is There an Augmented Nonlinear Taylor Rule?," Discussion Papers of DIW Berlin 1588, DIW Berlin, German Institute for Economic Research.
       • Caporale, Guglielmo Maria & Helmi, Mohamad Husam & Çatık, Abdurrahman Nazif & Menla Ali, Faek & Akdeniz, Coşkun, 2018. "Monetary policy rules in emerging countries: Is there an augmented nonlinear taylor rule?," Economic Modelling, Elsevier, vol. 72(C), pages 306-319.
    2. Khyati Kathuria & Nand Kumar, 2022. "Pandemic‐induced fear and government policy response as a measure of uncertainty in the foreign exchange market: Evidence from (a)symmetric wild bootstrap likelihood ratio test," Pacific Economic Review, Wiley Blackwell, vol. 27(4), pages 361-379, October.
    3. Emerson Fernandes Marçal & Eli Hadad Junior, 2016. "Is It Possible to Beat the Random Walk Model in Exchange Rate Forecasting? More Evidence for Brazilian Case," Brazilian Review of Finance, Brazilian Society of Finance, vol. 14(1), pages 65-88.
    4. Rossi Junior, Jose Luiz & Felicio, Wilson Rafael de Oliveira, 2014. "Common Factors and the Exchange Rate: Results From the Brazilian Case," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 68(1), April.
       • Jose Luiz Rossi Jr & Wilson Felíci, 2014. "Common Factors And The Exchange Rate: Results From The Brazilian Case," Anais do XLI Encontro Nacional de Economia [Proceedings of the 41st Brazilian Economics Meeting] 125, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    5. Felício, Wilson Rafael de Oliveira & Rossi, José Luiz Júnior, 2013. "Common factors and the exchange rate: results from the Brazilian case," Insper Working Papers wpe_318, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
       • Jose Luiz Rossi Jr & Wilson Felíci, 2014. "Common Factors And The Exchange Rate: Results From The Brazilian Case," Anais do XLI Encontro Nacional de Economia [Proceedings of the 41st Brazilian Economics Meeting] 125, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    6. Nikola Fabris & Milena Lazić, 2022. "Evaluating the Role of the Exchange Rate in Monetary Policy Reaction Function of Advanced and Emerging Market Economies," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 11(2), pages 77-96.
    7. Moura, Marcelo L. & Pereira, Fatima R. & Attuy, Guilherme de Moraes, 2013. "Currency Wars in Action: How Foreign Exchange Interventions Work in an Emerging Economy," Insper Working Papers wpe_304, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    8. Cuiabano, Simone, 2017. "Long-run equilibrium exchange rate in Latin America and Asia: a comparison using cointegrated vector," TSE Working Papers 17-837, Toulouse School of Economics (TSE).
    9. Han, Liyan & Xu, Yang & Yin, Libo, 2018. "Does investor attention matter? The attention-return relationships in FX markets," Economic Modelling, Elsevier, vol. 68(C), pages 644-660.
    10. Ruch,Franz Ulrich, 2021. "Neutral Real Interest Rates in Inflation Targeting Emerging and Developing Economies," Policy Research Working Paper Series 9711, The World Bank.
    11. Montes, Gabriel Caldas & Ferreira, Caio Ferrari, 2020. "Does monetary policy credibility mitigate the fear of floating?," Economic Modelling, Elsevier, vol. 84(C), pages 76-87.
    12. Jaqueson K. Galimberti & Marcelo L. Moura, 2011. "Improving the reliability of real-time Hodrick-Prescott filtering using survey forecasts," Centre for Growth and Business Cycle Research Discussion Paper Series 159, Economics, The University of Manchester.
        • Jaqueson K. Galimberti & Marcelo L. Moura, 2014. "Improving the reliability of real-time Hodrick-Prescott Filtering using survey forecasts," KOF Working papers 14-360, KOF Swiss Economic Institute, ETH Zurich.
    13. Hakan Yilmazkuday, 2008. "Structural Breaks in Monetary Policy Rules: Evidence from Transition Countries," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 44(6), pages 87-97, November.
    14. Chen, Chuanglian & Yao, Shujie & Ou, Jinghua, 2017. "Exchange rate dynamics in a Taylor rule framework," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 46(C), pages 158-173.

16. Galimberti, Jaqueson Kingeski & Cupertino, César Medeiros, 2009. "Explaining earnings persistence: a threshold autoregressive panel unit root approach," MPRA Paper 14237, University Library of Munich, Germany.

    Cited by:

    1. Yosra Koubaa, 2017. "Tunisian Labor Market and Regional Heterogeneity: Application of PSTR Model," International Journal of Regional Development, Macrothink Institute, vol. 4(1), pages 1-51, December.
    2. Timothy P. Sharpe, 2013. "Institutional arrangements and public debt threshold limits," International Review of Applied Economics, Taylor & Francis Journals, vol. 27(6), pages 707-728, November.
    3. Kimouche Bilal, 2021. "Persistence and Predictive Ability of Earnings: Evidence from France and the UK," Economics and Business, Sciendo, vol. 35(1), pages 190-200, January.
    4. Timothy P. Sharpe, 2013. "A Modern Money Perspective on Financial Crowding-out," Review of Political Economy, Taylor & Francis Journals, vol. 25(4), pages 586-606, October.

Articles

1. Galimberti Jaqueson K., 2024. "Initial Beliefs Uncertainty," The B.E. Journal of Macroeconomics, De Gruyter, vol. 24(1), pages 45-96, January.
   • Jaqueson K. Galimberti, 2021. "Initial beliefs uncertainty," CAMA Working Papers 2021-68, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

   Cited by:

   1. Stephen J. Cole & Fabio Milani, 2020. "Heterogeneity in Individual Expectations, Sentiment, and Constant-Gain Learning," CESifo Working Paper Series 8343, CESifo.
      • Cole, Stephen J. & Milani, Fabio, 2021. "Heterogeneity in Individual Expectations, Sentiment, and Constant-Gain Learning," Working Papers and Research 2021-05, Marquette University, Center for Global and Economic Studies and Department of Economics.
      • Stephen J. Cole & Fabio Milani, 2020. "Heterogeneity in Individual Expectations, Sentiment, and Constant-Gain Learning," Working Papers 192005, University of California-Irvine, Department of Economics.
      • Cole, Stephen J. & Milani, Fabio, 2021. "Heterogeneity in individual expectations, sentiment, and constant-gain learning," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 627-650.

2. Jaqueson K Galimberti & Stefan Pichler & Regina Pleninger, 2023. "Measuring Inequality Using Geospatial Data," The World Bank Economic Review, World Bank, vol. 37(4), pages 549-569.
   • Jaqueson Galimberti & Stefan Pichler & Regina Pleninger, 2020. "Measuring Inequality using Geospatial Data," Working Papers 2020-07, Auckland University of Technology, Department of Economics.
   • Jaqueson K. Galimberti & Stefan Pichler & Regina Pleninger, 2021. "Measuring Inequality using Geospatial Data," KOF Working papers 21-493, KOF Swiss Economic Institute, ETH Zurich.
   See citations under working paper version above.
3. Jaqueson K. Galimberti, 2020. "Forecasting GDP Growth from Outer Space," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(4), pages 697-722, August.
   • Jaqueson K Galimberti, 2017. "Forecasting GDP growth from the outer space," KOF Working papers 17-427, KOF Swiss Economic Institute, ETH Zurich.
   • Jaqueson K. Galimberti, 2020. "Forecasting GDP growth from outer space," Working Papers 2020-02, Auckland University of Technology, Department of Economics.
   See citations under working paper version above.
4. Berardi, Michele & Galimberti, Jaqueson K., 2019. "Smoothing-Based Initialization For Learning-To-Forecast Algorithms," Macroeconomic Dynamics, Cambridge University Press, vol. 23(3), pages 1008-1023, April.
   • Michele Berardi & Jaqueson K Galimberti, 2017. "Smoothing-based Initialization for Learning-to-Forecast Algorithms," KOF Working papers 17-425, KOF Swiss Economic Institute, ETH Zurich.
   See citations under working paper version above.
5. Galimberti, Jaqueson K., 2019. "An approximation of the distribution of learning estimates in macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 102(C), pages 29-43.
   • Jaqueson Kingeski Galimberti, 2019. "An approximation of the distribution of learning estimates in macroeconomic models," KOF Working papers 19-453, KOF Swiss Economic Institute, ETH Zurich.
   See citations under working paper version above.
6. Berardi, Michele & Galimberti, Jaqueson K., 2017. "Empirical calibration of adaptive learning," Journal of Economic Behavior & Organization, Elsevier, vol. 144(C), pages 219-237.
   • Michele Berardi & Jaqueson K. Galimberti, 2015. "Empirical Calibration of Adaptive Learning," KOF Working papers 15-392, KOF Swiss Economic Institute, ETH Zurich.
   See citations under working paper version above.
7. Berardi, Michele & Galimberti, Jaqueson K., 2017. "On the initialization of adaptive learning in macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 78(C), pages 26-53.
   • Michele Berardi & Jaqueson K Galimberti, 2016. "On the Initialization of Adaptive Learning in Macroeconomic Models," KOF Working papers 16-422, KOF Swiss Economic Institute, ETH Zurich.
   See citations under working paper version above.
8. Galimberti, Jaqueson K. & Moura, Marcelo L., 2016. "Improving the reliability of real-time output gap estimates using survey forecasts," International Journal of Forecasting, Elsevier, vol. 32(2), pages 358-373.

   Cited by:

   1. Jaqueson K. Galimberti & Nicolas Suhadolnik & Sergio Silva, 2017. "Cowboying Stock Market Herds with Robot Traders," Computational Economics, Springer;Society for Computational Economics, vol. 50(3), pages 393-423, October.
      • Galimberti, Jaqueson & Suhadolnik, Nicolas & Da Silva, Sergio, 2016. "Cowboying Stock Market Herds with Robot Traders," MPRA Paper 71758, University Library of Munich, Germany.
   2. Calista Cheung & Luke Frymire & Lise Pichette, 2020. "Can the Business Outlook Survey Help Improve Estimates of the Canadian Output Gap?," Discussion Papers 2020-14, Bank of Canada.
   3. Dimitris Kenourgios & Stephanos Papadamou & Dimitrios Dimitriou & Constantin Zopounidis, 2020. "Modelling the dynamics of unconventional monetary policies’ impact on professionals’ forecasts," Post-Print hal-02880071, HAL.
      • Kenourgios, Dimitris & Papadamou, Stephanos & Dimitriou, Dimitrios & Zopounidis, Constantin, 2020. "Modelling the dynamics of unconventional monetary policies’ impact on professionals’ forecasts," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 64(C).

9. Berardi, Michele & Galimberti, Jaqueson K., 2014. "A note on the representative adaptive learning algorithm," Economics Letters, Elsevier, vol. 124(1), pages 104-107.
   • Michele Bernardi & Jaqueson K. Galimberti, 2014. "A Note on the Representative Adaptive Learning Algorithm," KOF Working papers 14-356, KOF Swiss Economic Institute, ETH Zurich.
   See citations under working paper version above.
10. Galimberti, Jaqueson K. & Moura, Marcelo L., 2013. "Taylor rules and exchange rate predictability in emerging economies," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 1008-1031.
    • Galimberti, Jaqueson K. & Moura, Marcelo L., 2010. "Taylor Rules and Exchange Rate Predictability in Emerging Economies," Insper Working Papers wpe_214, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    See citations under working paper version above.
11. Berardi, Michele & Galimberti, Jaqueson K., 2013. "A note on exact correspondences between adaptive learning algorithms and the Kalman filter," Economics Letters, Elsevier, vol. 118(1), pages 139-142.
    • Michele Berardi & Jaqueson K. Galimberti, 2012. "A note on exact correspondences between adaptive learning algorithms and the Kalman filter," Centre for Growth and Business Cycle Research Discussion Paper Series 170, Economics, The University of Manchester.
    See citations under working paper version above.
12. Suhadolnik, Nicolas & Galimberti, Jaqueson & Da Silva, Sergio, 2010. "Robot traders can prevent extreme events in complex stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5182-5192.
    • Suhadolnik, Nicolas & Galimberti, Jaqueson & Da Silva, Sergio, 2010. "Robot traders can prevent extreme events in complex stock markets," MPRA Paper 23923, University Library of Munich, Germany.
    See citations under working paper version above.

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1. Learning and Expectations Macroeconomists

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NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 26 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-MAC: Macroeconomics (11) 2014-05-04 2014-07-28 2015-09-18 2020-02-03 2020-02-10 2020-06-15 2020-07-27 2020-08-17 2021-03-01 2021-03-29 2021-08-16. Author is listed
2. NEP-FOR: Forecasting (8) 2011-09-16 2012-08-23 2012-11-17 2014-05-04 2014-07-28 2015-09-18 2017-07-02 2020-02-10. Author is listed
3. NEP-ORE: Operations Research (7) 2014-05-04 2016-06-18 2020-02-03 2020-06-15 2020-07-27 2021-03-01 2021-08-16. Author is listed
4. NEP-CMP: Computational Economics (5) 2012-10-20 2016-06-18 2017-07-02 2020-06-15 2020-07-27. Author is listed
5. NEP-BIG: Big Data (4) 2017-07-02 2020-02-10 2020-08-17 2021-03-29
6. NEP-ETS: Econometric Time Series (4) 2012-08-23 2020-02-03 2020-06-15 2021-03-01
7. NEP-GEO: Economic Geography (3) 2020-02-10 2020-08-17 2021-03-29
8. NEP-RMG: Risk Management (3) 2010-07-24 2022-11-28 2023-10-09
9. NEP-UPT: Utility Models and Prospect Theory (3) 2012-11-17 2020-02-03 2020-06-15
10. NEP-ECM: Econometrics (2) 2011-09-16 2017-03-05
11. NEP-MON: Monetary Economics (2) 2023-07-17 2024-01-08
12. NEP-URE: Urban and Real Estate Economics (2) 2022-11-28 2023-10-09
13. NEP-ACC: Accounting and Auditing (1) 2009-03-28
14. NEP-AGE: Economics of Ageing (1) 2020-02-03
15. NEP-CBA: Central Banking (1) 2011-09-16
16. NEP-CBE: Cognitive and Behavioural Economics (1) 2012-11-17
17. NEP-DEV: Development (1) 2009-02-22
18. NEP-DGE: Dynamic General Equilibrium (1) 2020-07-27
19. NEP-EVO: Evolutionary Economics (1) 2015-09-18
20. NEP-FDG: Financial Development and Growth (1) 2009-02-22
21. NEP-FMK: Financial Markets (1) 2016-06-18
22. NEP-HME: Heterodox Microeconomics (1) 2016-06-18
23. NEP-ISF: Islamic Finance (1) 2021-08-16
24. NEP-LAB: Labour Economics (1) 2009-03-28

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