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Riccardo Costantini

Personal Details

First Name:Riccardo
Middle Name:
Last Name:Costantini
Suffix:
RePEc Short-ID:pco590
[This author has chosen not to make the email address public]
Department of Economics University College London Drayton House - Room G01-4 30, Gordon Street WC1H 0AX, Uk

Affiliation

Department of Economics
University College London (UCL)

London, United Kingdom
http://www.ucl.ac.uk/economics/
RePEc:edi:deucluk (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Carlo Altavilla & Riccardo Costantini & Raffaella Giacomini, 2013. "Bond returns and market expectations," CeMMAP working papers CWP20/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

Articles

  1. Marco Cipriani & Riccardo Costantini & Antonio Guarino, 2012. "A Bayesian approach to experimental analysis: trading in a laboratory financial market," Review of Economic Design, Springer;Society for Economic Design, vol. 16(2), pages 175-191, September.
  2. Riccardo Costantini, 2012. "Nuclear power generation, renewable resources and endogenous growth," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 0(1), pages 65-93.

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. Carlo Altavilla & Riccardo Costantini & Raffaella Giacomini, 2013. "Bond returns and market expectations," CeMMAP working papers CWP20/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Davide Pettenuzzo & Konstantinos Metaxoglou & Aaron Smith, 2016. "Option-Implied Equity Premium Predictions via Entropic TiltinG," Working Papers 99R, Brandeis University, Department of Economics and International Business School, revised Aug 2016.
    2. Davide Pettenuzzo & Antonio Gargano & Allan Timmermann, 2014. "Bond Return Predictability: Economic Value and Links to the Macroeconomy," Working Papers 75, Brandeis University, Department of Economics and International Business School.
    3. Fausto Vieira & Fernando Chague, Marcelo Fernandes, 2016. "A dynamic Nelson-Siegel model with forward-looking indicators for the yield curve in the US," Working Papers, Department of Economics 2016_31, University of São Paulo (FEA-USP).
    4. Raffaella Giacomini, 2014. "Economic theory and forecasting: lessons from the literature," CeMMAP working papers CWP41/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Fausto Vieira & Fernando Chague & Marcelo Fernandes, 2016. "Forecasting the Brazilian Yield Curve Using Forward-Looking Variables," Working Papers 799, Queen Mary University of London, School of Economics and Finance.
    6. Baumeister, Christiane, 2021. "Measuring Market Expectations," CEPR Discussion Papers 16520, C.E.P.R. Discussion Papers.
    7. Raffaella Giacomini, 2014. "Economic theory and forecasting: lessons from the literature," CeMMAP working papers 41/14, Institute for Fiscal Studies.
    8. Maryam Movahedifar & Hossein Hassani & Masoud Yarmohammadi & Mahdi Kalantari & Rangan Gupta, 2021. "A robust approach for outlier imputation: Singular Spectrum Decomposition," Working Papers 202164, University of Pretoria, Department of Economics.
    9. Eriksen, Jonas N., 2017. "Expected Business Conditions and Bond Risk Premia," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(4), pages 1667-1703, August.
    10. Fernandes, Marcelo & Vieira, Fausto, 2019. "A dynamic Nelson–Siegel model with forward-looking macroeconomic factors for the yield curve in the US," Journal of Economic Dynamics and Control, Elsevier, vol. 106(C), pages 1-1.

Articles

  1. Marco Cipriani & Riccardo Costantini & Antonio Guarino, 2012. "A Bayesian approach to experimental analysis: trading in a laboratory financial market," Review of Economic Design, Springer;Society for Economic Design, vol. 16(2), pages 175-191, September.

    Cited by:

    1. Puput Tri Komalasari & Marwan Asri & Bernardinus M. Purwanto & Bowo Setiyono, 2022. "Herding behaviour in the capital market: What do we know and what is next?," Management Review Quarterly, Springer, vol. 72(3), pages 745-787, September.
    2. Rolando Gonzales Martínez & Gabriela Aguilera‐Lizarazu & Andrea Rojas‐Hosse & Patricia Aranda Blanco, 2020. "The interaction effect of gender and ethnicity in loan approval: A Bayesian estimation with data from a laboratory field experiment," Review of Development Economics, Wiley Blackwell, vol. 24(3), pages 726-749, August.
    3. Seuk Yen Phoong, 2013. "Rubber Price Effect on Exchange Rate: A Bayesian Mixture Model Approach," Information Management and Business Review, AMH International, vol. 5(6), pages 263-269.
    4. Rolando Gonzales & Gabriela Aguilera-Lizarazu & Andrea Rojas-Hosse & Patricia Aranda, 2016. "Preference for women but less preference for indigenous women: A lab-field experiment of loan discrimination in a developing economy," Working Papers PIERI 2016-24, PEP-PIERI.
    5. Nicolas Vallois & Dorian Jullien, 2017. "Estimating Rationality in Economics: A History of Statistical Methods in Experimental Economics," GREDEG Working Papers 2017-20, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    6. Nicolas Vallois & Dorian Jullien, 2018. "A history of statistical methods in experimental economics," The European Journal of the History of Economic Thought, Taylor & Francis Journals, vol. 25(6), pages 1455-1492, November.
    7. Kirchkamp, Oliver & Oechssler, Joerg & Sofianos, Andis, 2021. "The Binary Lottery Procedure does not induce risk neutrality in the Holt & Laury and Eckel & Grossman tasks," Journal of Economic Behavior & Organization, Elsevier, vol. 185(C), pages 348-369.

More information

Research fields, statistics, top rankings, if available.

Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 1 paper 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-FMK: Financial Markets (1) 2013-06-09
  2. NEP-FOR: Forecasting (1) 2013-06-09

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