IDEAS home Printed from https://ideas.repec.org/e/pfi75.html
   My authors  Follow this author

Marco Fioramanti

Personal Details

First Name:Marco
Middle Name:
Last Name:Fioramanti
Suffix:
RePEc Short-ID:pfi75
[This author has chosen not to make the email address public]

Affiliation

Ufficio Parlamentare di Bilancio
Government of Italy

Roma, Italy
http://www.upbilancio.it/
RePEc:edi:upbgvit (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Fioramanti, Marco & Waldmann, Robert J., 2017. "The Econometrics of the EU Fiscal Governance: is the European Commission methodology still adequate?," MPRA Paper 81858, University Library of Munich, Germany.
  2. Marco Fioramanti, ISTAT & Laura González Cabanillas & Bjorn Roelstraete & Salvador Adrian Ferrandis Vallterra, 2016. "European Commission's Forecasts Accuracy Revisited: Statistical Properties and Possible Causes of Forecast Errors," European Economy - Discussion Papers 027, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
  3. Fioramanti, Marco, 2016. "Potential Output, Output Gap and Fiscal Stance: is the EC estimation of the NAWRU too sensitive to be reliable?," MPRA Paper 73762, University Library of Munich, Germany, revised Sep 2016.
  4. Fioramanti, Marco, 2011. "Knock-on effect of non-manufacturing regulation on manufacturing sectors efficiency and productivity," MPRA Paper 32237, University Library of Munich, Germany.
  5. Fioramanti, Marco & Vicarelli, Claudio, 2011. "The New Stability and Growth Pact: Primum non nocere," CEPS Papers 4370, Centre for European Policy Studies.
  6. Marco Fioramanti, 2009. "Estimation and Decomposition of Total Factor Productivity Growth in the EU Manufacturing Sector: a Stochastic Frontier Approach," ISAE Working Papers 114, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
  7. Marco Fioramanti, 2006. "Predicting Sovereign Debt Crises Using Artificial Neural Networks: A Comparative Approach," ISAE Working Papers 72, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).

Articles

  1. Tommaso Proietti & Marco Fioramanti & Cecilia Frale & Libero Monteforte, 2020. "A Systemic Approach to Estimating the Output Gap for the Italian Economy," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 62(3), pages 465-493, September.
  2. Fabio Bacchini & Cristina Brandimarte & Piero Crivelli & Roberta De Santis & Marco Fioramanti & Alessandro Girardi & Roberto Golinelli & Cecilia Jona-Lasinio & Massimo Mancini & Carmine Pappalardo & D, 2013. "Building the core of the Istat system of models for forecasting the Italian economy: MeMo-It," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 15(1), pages 17-45.
  3. Marco FIORAMANTI, 2010. "Estimation And Decomposition Of Total Factor Productivity Growth In The Eu Manufacturing Sector: A Long Run Perspective," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 5(3(13)/Fal), pages 217-230.
  4. Fioramanti, Marco, 2008. "Predicting sovereign debt crises using artificial neural networks: A comparative approach," Journal of Financial Stability, Elsevier, vol. 4(2), pages 149-164, June.
  5. Fioramanti, Marco, 2005. "Free Internet access: When is it suitable?," Information Economics and Policy, Elsevier, vol. 17(3), pages 302-316, July.
  6. Alberto Iozzi & Marco Fioramanti, 2004. "Strategic Choice of the Price Structure and Entry Deterrence Under Price Cap Regulation," Bulletin of Economic Research, Wiley Blackwell, vol. 56(4), pages 333-352, October.

Citations

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

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Author Profile
    1. Phillips curve Philippic I
      by Robert in Robert's Stochastic Thoughts on 2015-12-06 13:44:00

Working papers

  1. Fioramanti, Marco & Waldmann, Robert J., 2017. "The Econometrics of the EU Fiscal Governance: is the European Commission methodology still adequate?," MPRA Paper 81858, University Library of Munich, Germany.

    Cited by:

    1. Tommaso Proietti & Marco Fioramanti & Cecilia Frale & Libero Monteforte, 2020. "A Systemic Approach to Estimating the Output Gap for the Italian Economy," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 62(3), pages 465-493, September.

  2. Marco Fioramanti, ISTAT & Laura González Cabanillas & Bjorn Roelstraete & Salvador Adrian Ferrandis Vallterra, 2016. "European Commission's Forecasts Accuracy Revisited: Statistical Properties and Possible Causes of Forecast Errors," European Economy - Discussion Papers 027, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.

    Cited by:

    1. Agnes Benassy-Quere, 2016. "Euro-Area Fiscal Stance: From Theory to Practical Implementation," CESifo Working Paper Series 6040, CESifo.
    2. Cardi, Olivier & Restout, Romain, 2023. "Sectoral fiscal multipliers and technology in open economy," Journal of International Economics, Elsevier, vol. 144(C).
    3. Larch, Martin & Cugnasca, Alessandro & Kumps, Diederik & Orseau, Eloïse, 2019. "Fiscal policy and the assessment of output gaps in real time: An exercise in risk management," ZEW Discussion Papers 19-013, ZEW - Leibniz Centre for European Economic Research.
    4. Nicolas Reigl, 2023. "Noise shocks and business cycle fluctuations in three major European Economies," Empirical Economics, Springer, vol. 64(2), pages 603-657, February.
    5. Cronin, David & McInerney, Niall, 2023. "Official fiscal forecasts in EU member states under the European Semester and Fiscal Compact – An empirical assessment," European Journal of Political Economy, Elsevier, vol. 76(C).
    6. Sabaj, Ernil & Kahveci, Mustafa, 2018. "Forecasting tax revenues in an emerging economy: The case of Albania," MPRA Paper 84404, University Library of Munich, Germany.
    7. Glas, Alexander & Heinisch, Katja, 2021. "Conditional macroeconomic forecasts: Disagreement, revisions and forecast errors," IWH Discussion Papers 7/2021, Halle Institute for Economic Research (IWH).
    8. Fioramanti, Marco & Waldmann, Robert J., 2017. "The Econometrics of the EU Fiscal Governance: is the European Commission methodology still adequate?," MPRA Paper 81858, University Library of Munich, Germany.
    9. Larch, Martin & Kumps, Diederik & Cugnasca, Alessandro, 2021. "Fiscal stabilisation in real time: An exercise in risk management," Economic Modelling, Elsevier, vol. 99(C).
    10. Engelke, Carola & Heinisch, Katja & Schult, Christoph, 2019. "How forecast accuracy depends on conditioning assumptions," IWH Discussion Papers 18/2019, Halle Institute for Economic Research (IWH).
    11. Andras Chabin & Sébastien Lamproye & Milan Výškrabka, 2020. "Are We More Accurate? Revisiting the European Commission’s Macroeconomic Forecasts," European Economy - Discussion Papers 128, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.

  3. Fioramanti, Marco, 2016. "Potential Output, Output Gap and Fiscal Stance: is the EC estimation of the NAWRU too sensitive to be reliable?," MPRA Paper 73762, University Library of Munich, Germany, revised Sep 2016.

    Cited by:

    1. Schuster, Florian & Krahé, Max & Schneemelcher, Pola & Sigl-Glöckner, Philippa, 2022. "Do the MTO's cyclically adjusted budget balances serve their purpose? An analysis and a reform proposal," Papers 277894, Dezernat Zukunft - Institute for Macrofinance, Berlin.
    2. Schuster, Florian & Krahé, Max & Sigl-Glöckner, Philippa & Leusder, Dominik, 2021. "The cyclical component of the debt brake: Analysis and a reform proposal," Papers 277890, Dezernat Zukunft - Institute for Macrofinance, Berlin.
    3. Max Krahé & Florian Schuster & Philippa Sigl-Glöckner, 2021. "Wird die Konjunkturkomponente der Schuldenbremse ihrer Aufgabe noch gerecht? [Is the Cyclical Component of the Debt Brake Still Up to Its Task?]," Wirtschaftsdienst, Springer;ZBW - Leibniz Information Centre for Economics, vol. 101(8), pages 621-628, August.
    4. Fioramanti, Marco & Waldmann, Robert J., 2017. "The Econometrics of the EU Fiscal Governance: is the European Commission methodology still adequate?," MPRA Paper 81858, University Library of Munich, Germany.
    5. Tommaso Proietti & Marco Fioramanti & Cecilia Frale & Libero Monteforte, 2020. "A Systemic Approach to Estimating the Output Gap for the Italian Economy," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 62(3), pages 465-493, September.
    6. Ademmer, Martin & Boysen-Hogrefe, Jens & Carstensen, Kai & Hauber, Philipp & Jannsen, Nils & Kooths, Stefan & Rossian, Thies & Stolzenburg, Ulrich, 2019. "Schätzung von Produktionspotenzial und -lücke: Eine Analyse des EU-Verfahrens und mögliche Verbesserungen," Kieler Beiträge zur Wirtschaftspolitik 19, Kiel Institute for the World Economy (IfW Kiel).
    7. Eddie Casey, 2019. "Inside the "Upside Down": Estimating Ireland's Output Gap," The Economic and Social Review, Economic and Social Studies, vol. 50(1), pages 5-34.

  4. Fioramanti, Marco & Vicarelli, Claudio, 2011. "The New Stability and Growth Pact: Primum non nocere," CEPS Papers 4370, Centre for European Policy Studies.

    Cited by:

    1. Douglas Sutherland & Peter Hoeller & Rossana Merola, 2012. "Fiscal Consolidation: Part 1. How Much is Needed and How to Reduce Debt to a Prudent Level?," OECD Economics Department Working Papers 932, OECD Publishing.

  5. Marco Fioramanti, 2006. "Predicting Sovereign Debt Crises Using Artificial Neural Networks: A Comparative Approach," ISAE Working Papers 72, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).

    Cited by:

    1. Tölö, Eero, 2019. "Predicting systemic financial crises with recurrent neural networks," Bank of Finland Research Discussion Papers 14/2019, Bank of Finland.
    2. Dawood, Mary & Horsewood, Nicholas & Strobel, Frank, 2017. "Predicting sovereign debt crises: An Early Warning System approach," Journal of Financial Stability, Elsevier, vol. 28(C), pages 16-28.
    3. Makram El-Shagi & Gregor von Schweinitz, 2016. "Qual VAR revisited: Good forecast, bad story," Journal of Applied Economics, Universidad del CEMA, vol. 19, pages 293-322, November.
    4. Petr Hájek & Michal Střižík & Pavel Praks & Petr Kadeřábek, 2009. "Možnosti využití přístupu latentní sémantiky při předpovídání finančních krizí [Possibilities of Financial Crises Forecasting with Latent Semantic Indexing]," Politická ekonomie, Prague University of Economics and Business, vol. 2009(6), pages 754-768.
    5. Mioara CHIRITA & Daniela SARPE, 2011. "Usefulness of Artificial Neural Networks for Predicting Financial and Economic Crisis," Risk in Contemporary Economy, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, pages 44-48.
    6. Sebastián Nieto Parra, 2008. "Who Saw Sovereign Debt Crises Coming?," OECD Development Centre Working Papers 274, OECD Publishing.
    7. Patrycja Klusak & Matthew Agarwala & Matt Burke & Moritz Kraemer & Kamiar Mohaddes, 2021. "Rising temperatures, falling ratings: The effect of climate change on sovereign creditworthiness," CAMA Working Papers 2021-34, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    8. León, Carlos & Barucca, Paolo & Acero, Oscar & Gage, Gerardo & Ortega, Fabio, 2020. "Pattern recognition of financial institutions’ payment behavior," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
    9. Sevim, Cuneyt & Oztekin, Asil & Bali, Ozkan & Gumus, Serkan & Guresen, Erkam, 2014. "Developing an early warning system to predict currency crises," European Journal of Operational Research, Elsevier, vol. 237(3), pages 1095-1104.
    10. Maximilian Gobel & Tanya Araújo, 2020. "Indicators of Economic Crises: A Data-Driven Clustering Approach," Working Papers REM 2020/0128, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    11. Arazmuradov, Annageldy, 2016. "Assessing sovereign debt default by efficiency," The Journal of Economic Asymmetries, Elsevier, vol. 13(C), pages 100-113.
    12. Tölö, Eero, 2020. "Predicting systemic financial crises with recurrent neural networks," Journal of Financial Stability, Elsevier, vol. 49(C).
    13. Jorge M. Uribe, 2023. ""Fiscal crises and climate change"," IREA Working Papers 202303, University of Barcelona, Research Institute of Applied Economics, revised Feb 2023.
    14. Eleftherios Giovanis, 2010. "Application of logit model and self‐organizing maps (SOMs) for the prediction of financial crisis periods in US economy," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 2(2), pages 98-125, June.
    15. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Self-organizing map analysis of agents’ expectations. Different patterns of anticipation of the 2008 financial crisis”," AQR Working Papers 201508, University of Barcelona, Regional Quantitative Analysis Group, revised Mar 2015.
    16. Elgin, C. & Uras, R.B., 2013. "Public debt, sovereign default risk and shadow economy," Other publications TiSEM c3f85480-587f-464d-a748-a, Tilburg University, School of Economics and Management.
    17. Panizza, Ugo & Caselli, Francesca & Faralli, Matilde & Manasse, Paolo, 2021. "On the Benefits of Repaying," CEPR Discussion Papers 16539, C.E.P.R. Discussion Papers.
    18. Tamás Kristóf, 2021. "Sovereign Default Forecasting in the Era of the COVID-19 Crisis," JRFM, MDPI, vol. 14(10), pages 1-24, October.
    19. Mioara CHIRITA, 2012. "Usefulness of Artificial Neural Networks for Predicting Financial and Economic Crisis," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 2, pages 61-66.
    20. Peter Sarlin & Dorina Marghescu, 2011. "Visual predictions of currency crises using self‐organizing maps," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 18(1), pages 15-38, January.
    21. Ayşe Özmen & Gerhard-Wilhelm Weber & Zehra Çavuşoğlu & Özlem Defterli, 2013. "The new robust conic GPLM method with an application to finance: prediction of credit default," Journal of Global Optimization, Springer, vol. 56(2), pages 233-249, June.
    22. Markus Holopainen & Peter Sarlin, 2015. "Toward robust early-warning models: A horse race, ensembles and model uncertainty," Papers 1501.04682, arXiv.org, revised Apr 2016.
    23. Eleftherios Giovanis, 2012. "Study of Discrete Choice Models and Adaptive Neuro-Fuzzy Inference System in the Prediction of Economic Crisis Periods in USA," Economic Analysis and Policy, Elsevier, vol. 42(1), pages 79-96, March.
    24. Bandiera, Luca & Cuaresma, Jesus Crespo & Vincelette, Gallina A., 2010. "Unpleasant surprises : sovereign default determinants and prospects," Policy Research Working Paper Series 5401, The World Bank.
    25. Moreno Badia, Marialuz & Medas, Paulo & Gupta, Pranav & Xiang, Yuan, 2022. "Debt is not free," Journal of International Money and Finance, Elsevier, vol. 127(C).
    26. Barbara Jarmulska, 2022. "Random forest versus logit models: Which offers better early warning of fiscal stress?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 455-490, April.
    27. Lean Yu & Xinxie Li & Ling Tang & Zongyi Zhang & Gang Kou, 2015. "Social credit: a comprehensive literature review," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 1(1), pages 1-18, December.
    28. Raffaele De Marchi & Alessandro Moro, 2023. "Forecasting fiscal crises in emerging markets and low-income countries with machine learning models," Temi di discussione (Economic working papers) 1405, Bank of Italy, Economic Research and International Relations Area.
    29. Kim Ristolainen, 2015. "Were the Scandinavian Banking Crises Predictable? A Neural Network Approach," Discussion Papers 99, Aboa Centre for Economics.
    30. Peter Sarlin & Dorina Marghescu, 2011. "Neuro‐Genetic Predictions Of Currency Crises," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 18(4), pages 145-160, October.
    31. León, C. & Moreno, José Fernando & Cely, Jorge, 2017. "Whose Balance Sheet is this? Neural Networks for Banks' Pattern Recognition," Discussion Paper 2017-009, Tilburg University, Center for Economic Research.
    32. Fu, Junhui & Zhou, Qingling & Liu, Yufang & Wu, Xiang, 2020. "Predicting stock market crises using daily stock market valuation and investor sentiment indicators," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    33. Sarlin, Peter & Peltonen, Tuomas A., 2013. "Mapping the state of financial stability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 46-76.
    34. Sarlin, Peter & Peltonen, Tuomas A., 2011. "Mapping the state of financial stability," BOFIT Discussion Papers 18/2011, Bank of Finland Institute for Emerging Economies (BOFIT).
    35. Jian Min & Jiaojiao Zhu & Jian-Bo Yang, 2020. "The Risk Monitoring of the Financial Ecological Environment in Chinese Outward Foreign Direct Investment Based on a Complex Network," Sustainability, MDPI, vol. 12(22), pages 1-26, November.
    36. Lanbiao Liu & Chen Chen & Bo Wang, 2022. "Predicting financial crises with machine learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 871-910, August.
    37. Bitetto, Alessandro & Cerchiello, Paola & Mertzanis, Charilaos, 2023. "Measuring financial soundness around the world: A machine learning approach," International Review of Financial Analysis, Elsevier, vol. 85(C).
    38. Kinsella, Stephen, 2019. "Visualising economic crises using accounting models," Accounting, Organizations and Society, Elsevier, vol. 75(C), pages 1-16.

Articles

  1. Tommaso Proietti & Marco Fioramanti & Cecilia Frale & Libero Monteforte, 2020. "A Systemic Approach to Estimating the Output Gap for the Italian Economy," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 62(3), pages 465-493, September.

    Cited by:

    1. Martin Boďa & Mariana Považanová, 2023. "How credible are Okun coefficients? The gap version of Okun’s law for G7 economies," Economic Change and Restructuring, Springer, vol. 56(3), pages 1467-1514, June.

  2. Fabio Bacchini & Cristina Brandimarte & Piero Crivelli & Roberta De Santis & Marco Fioramanti & Alessandro Girardi & Roberto Golinelli & Cecilia Jona-Lasinio & Massimo Mancini & Carmine Pappalardo & D, 2013. "Building the core of the Istat system of models for forecasting the Italian economy: MeMo-It," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 15(1), pages 17-45.

    Cited by:

    1. Ilenia Romani & Marzio Galeotti & Alessandro Lanza, 2022. "Besides promising economic growth, will the Italian NRRP also produce fewer emissions?," Working Papers 2022.08, Fondazione Eni Enrico Mattei.
    2. Hjelm, Göran & Bornevall, Helena & Fromlet, Pia & Nilsson, Jonny & Stockhammar , Pär & Wiberg, Magnus, 2015. "Appropriate Macroeconomic Model Support for the Ministry of Finance and the National Institute of Economic Research: A Pilot Study," Working Papers 137, National Institute of Economic Research.
    3. Romani, Ilenia & Galeotti, Marzio & Lanza, Alessandro, 2022. "Besides promising economic growth, will the Italian NRRP also produce fewer emissions?," FEEM Working Papers 319781, Fondazione Eni Enrico Mattei (FEEM).
    4. Francesco Zezza & Gennaro Zezza, 2020. "A Stock-Flow Consistent Quarterly Model of the Italian Economy," Economics Working Paper Archive wp_958, Levy Economics Institute.
    5. F. Bacchini & M. E. Bontempi & R. Golinelli & C. Jona Lasinio, 2014. "ICT and Non-ICT investments: short and long run macro dynamics," Working Papers wp956, Dipartimento Scienze Economiche, Universita' di Bologna.
    6. Alberto Bagnai & Christian Alexander Mongeau Ospina, 2014. "The a/simmetrie annual macroeconometric model of the Italian economy: structure and properties," a/ Working Papers Series 1405, Italian Association for the Study of Economic Asymmetries, Rome (Italy).
    7. Fabio Bacchini & Maria Elena Bontempi & Roberto Golinelli & Cecilia Jona-Lasinio, 2018. "Short- and long-run heterogeneous investment dynamics," Empirical Economics, Springer, vol. 54(2), pages 343-378, March.
    8. Bagnai, Alberto & Granville, Brigitte & Mongeau Ospina, Christian A., 2017. "Withdrawal of Italy from the euro area: Stochastic simulations of a structural macroeconometric model," Economic Modelling, Elsevier, vol. 64(C), pages 524-538.
    9. Samvel S. Lazaryan & Evgenii V. Mayorov, 2018. "Prospects for the Use of DSGE Models by Finance Ministries: The Experience of Global Regulators," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 5, pages 70-82, October.
    10. Fabio Bacchini, Maria Elena Bontempi, Cristina Brandimarte, Roberto Golinelli, Cecilia Jona-Lasinio, Carmine Pappalardo, 2013. "The Macroeconometric Models For Italy (Memo-It): Policy Evaluation And Future Challanges," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 67(2), pages 172-179, April-Jun.

  3. Fioramanti, Marco, 2008. "Predicting sovereign debt crises using artificial neural networks: A comparative approach," Journal of Financial Stability, Elsevier, vol. 4(2), pages 149-164, June.
    See citations under working paper version above.
  4. Alberto Iozzi & Marco Fioramanti, 2004. "Strategic Choice of the Price Structure and Entry Deterrence Under Price Cap Regulation," Bulletin of Economic Research, Wiley Blackwell, vol. 56(4), pages 333-352, October.

    Cited by:

    1. Alberto Iozzi & Roberta Sestini & Edilio Valentini, 2005. "Pricing Discretion and Price Regulation in Competitive Industries," CEIS Research Paper 69, Tor Vergata University, CEIS.
    2. Graeme Guthrie, 2006. "Regulating Infrastructure: The Impact on Risk and Investment," Journal of Economic Literature, American Economic Association, vol. 44(4), pages 925-972, December.
    3. Guthrie, Graeme, 2006. "Regulating Infrastructure: The Impact on Risk and Investment," Working Paper Series 18946, Victoria University of Wellington, The New Zealand Institute for the Study of Competition and Regulation.
    4. Kevin Currier, 2009. "Price cap regulation of a dominant firm facing competition," Journal of Economics, Springer, vol. 98(3), pages 221-233, December.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

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 6 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-EEC: European Economics (3) 2009-07-28 2016-07-23 2017-10-15
  2. NEP-EFF: Efficiency and Productivity (2) 2009-07-28 2011-07-27
  3. NEP-MAC: Macroeconomics (2) 2016-09-25 2017-10-15
  4. NEP-CMP: Computational Economics (1) 2007-02-24
  5. NEP-ECM: Econometrics (1) 2007-02-24
  6. NEP-FOR: Forecasting (1) 2016-07-23
  7. NEP-ICT: Information and Communication Technologies (1) 2007-02-24
  8. NEP-NEU: Neuroeconomics (1) 2007-02-24
  9. NEP-REG: Regulation (1) 2011-07-27

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Marco Fioramanti should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.