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Dooruj Rambaccussing

Personal Details

First Name:Dooruj
Middle Name:
Last Name:Rambaccussing
Suffix:
RePEc Short-ID:pra400
[This author has chosen not to make the email address public]
https://sites.google.com/site/doorujrambaccussing/
3, Perth Road, Economic Studies, University of Dundee Dundee DD1 4HN
Terminal Degree:2012 Business School; University of Exeter (from RePEc Genealogy)

Affiliation

Department of Economics Studies
University of Dundee

Dundee, United Kingdom
http://www.dundee.ac.uk/econman/
RePEc:edi:dedunuk (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Tim Pawlowski & Dooruj Rambaccussing & Philip Ramirez & James & Giambattista Rossi, 2023. "Exploring Entertainment Utility from Football Games," Economics Discussion Papers em-dp2023-13, Department of Economics, University of Reading.
  2. Dooruj Rambaccussing & Craig Menzies & Andrzej Kwiatkowski, 2022. "Look who’s Talking: Individual Committee members’ impact on inflation expectations," Dundee Discussion Papers in Economics 305, Economic Studies, University of Dundee.
  3. Bill Russell & Dooruj Rambaccussing, 2016. "Breaks and the Statistical Process of Inflation: The Case of the ‘Modern’ Phillips Curve," Dundee Discussion Papers in Economics 294, Economic Studies, University of Dundee.
  4. Alasdair Brown & Dooruj Rambaccussing & J. James Reade & Giambattista Rossi, 2016. "Using Social Media to Identify Market Inefficiencies: Evidence from Twitter and Betfair," Dundee Discussion Papers in Economics 293, Economic Studies, University of Dundee.
  5. Alasdair Brown & Dooruj Rambaccussing & J. James Reade & Giambattista Rossi, 2016. "Using Social Media to Identify Market Ine!ciencies: Evidence from Twitter and Betfair," Working Papers 2016-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  6. Dooruj Rambaccussing, 2015. "Modelling Housing Prices using a Present Value State Space Model," Dundee Discussion Papers in Economics 285, Economic Studies, University of Dundee.
  7. Adam Goliński & João Madeira & Dooruj Rambaccussing, 2015. "Fractional Integration of the Price-Dividend Ratio in a Present-Value Model of Stock Prices," Dundee Discussion Papers in Economics 284, Economic Studies, University of Dundee.
  8. Rambaccussing, Dooruj, 2015. "Revisiting Shiller's excess volatility hypothesis," SIRE Discussion Papers 2015-33, Scottish Institute for Research in Economics (SIRE).
  9. Rambaccussing, Dooruj, 2015. "Revisiting Shiller’s excess volatility hypothesis," SIRE Discussion Papers 2015-82, Scottish Institute for Research in Economics (SIRE).
  10. James Davidson & Dooruj Rambaccussing, 2015. "A test of the long memory hypothesis based on self-similarity," Dundee Discussion Papers in Economics 286, Economic Studies, University of Dundee.
  11. Golinski, Adam & Madeira, Joao & Rambaccussing, Dooruj, 2014. "Fractional Integration of the Price-Dividend Ratio in a Present-Value Model," MPRA Paper 58554, University Library of Munich, Germany.

Articles

  1. Dooruj Rambaccussing, 2021. "The price–rent ratio inequality in Scottish Cities: fluctuations in discount rates and expected rent growth," SN Business & Economics, Springer, vol. 1(9), pages 1-15, September.
  2. Dooruj Rambaccussing & Murat Mazibas, 2020. "True versus Spurious Long Memory in Cryptocurrencies," JRFM, MDPI, vol. 13(9), pages 1-11, August.
  3. Rambaccussing, Dooruj & Kwiatkowski, Andrzej, 2020. "Forecasting with news sentiment: Evidence with UK newspapers," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1501-1516.
  4. Bill Russell & Dooruj Rambaccussing, 2019. "Breaks and the statistical process of inflation: the case of estimating the ‘modern’ long-run Phillips curve," Empirical Economics, Springer, vol. 56(5), pages 1455-1475, May.
  5. Bowden, James & Kwiatkowski, Andrzej & Rambaccussing, Dooruj, 2019. "Economy through a lens: Distortions of policy coverage in UK national newspapers," Journal of Comparative Economics, Elsevier, vol. 47(4), pages 881-906.
  6. Dooruj Rambaccussing & David Power, 2018. "Fluctuations in the UK equity market: what drives stock returns?," The European Journal of Finance, Taylor & Francis Journals, vol. 24(6), pages 499-516, April.
  7. Dooruj Rambaccussing & David Power, 2018. "Expected returns and expected dividend growth in Europe: Legal origin, institutional, and financial determinants," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 23(4), pages 533-545, October.
  8. Alasdair Brown & Dooruj Rambaccussing & J. James Reade & Giambattista Rossi, 2018. "Forecasting With Social Media: Evidence From Tweets On Soccer Matches," Economic Inquiry, Western Economic Association International, vol. 56(3), pages 1748-1763, July.
  9. Davidson James & Rambaccussing Dooruj, 2015. "A Test of the Long Memory Hypothesis Based on Self-Similarity," Journal of Time Series Econometrics, De Gruyter, vol. 7(2), pages 115-141, July.

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. Tim Pawlowski & Dooruj Rambaccussing & Philip Ramirez & James & Giambattista Rossi, 2023. "Exploring Entertainment Utility from Football Games," Economics Discussion Papers em-dp2023-13, Department of Economics, University of Reading.

    Cited by:

    1. Travis Richardson & Georgios Nalbantis & Tim Pawlowski, 2023. "Emotional Cues and the Demand for Televised Sports: Evidence from the UEFA Champions League," Journal of Sports Economics, , vol. 24(8), pages 993-1025, December.

  2. Alasdair Brown & Dooruj Rambaccussing & J. James Reade & Giambattista Rossi, 2016. "Using Social Media to Identify Market Inefficiencies: Evidence from Twitter and Betfair," Dundee Discussion Papers in Economics 293, Economic Studies, University of Dundee.

    Cited by:

    1. Tai, Chung-Ching & Lin, Hung-Wen & Chie, Bin-Tzong & Tung, Chen-Yuan, 2019. "Predicting the failures of prediction markets: A procedure of decision making using classification models," International Journal of Forecasting, Elsevier, vol. 35(1), pages 297-312.
    2. Dave Cliff, 2021. "BBE: Simulating the Microstructural Dynamics of an In-Play Betting Exchange via Agent-Based Modelling," Papers 2105.08310, arXiv.org.
    3. Peeters, Thomas, 2018. "Testing the Wisdom of Crowds in the field: Transfermarkt valuations and international soccer results," International Journal of Forecasting, Elsevier, vol. 34(1), pages 17-29.
    4. Alasdair Brown & James Reade & Leighton Vaughan Williams, 2018. "Prediction Markets and Poll Releases: When Are Prices Most Informative?," Economics Discussion Papers em-dp2018-02, Department of Economics, University of Reading.
    5. Maribel Serna Rodríguez & Andrés Ramírez Hassan & Alexander Coad, 2019. "Uncovering Value Drivers of High Performance Soccer Players," Journal of Sports Economics, , vol. 20(6), pages 819-849, August.
    6. Dmitry Dagaev & Egor Stoyan, 2019. "Parimutuel Betting On The Esports Duels: Reverse Favourite-Longshot Bias And Its Determinants," HSE Working papers WP BRP 216/EC/2019, National Research University Higher School of Economics.

  3. Alasdair Brown & Dooruj Rambaccussing & J. James Reade & Giambattista Rossi, 2016. "Using Social Media to Identify Market Ine!ciencies: Evidence from Twitter and Betfair," Working Papers 2016-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.

    Cited by:

    1. Tai, Chung-Ching & Lin, Hung-Wen & Chie, Bin-Tzong & Tung, Chen-Yuan, 2019. "Predicting the failures of prediction markets: A procedure of decision making using classification models," International Journal of Forecasting, Elsevier, vol. 35(1), pages 297-312.
    2. Dave Cliff, 2021. "BBE: Simulating the Microstructural Dynamics of an In-Play Betting Exchange via Agent-Based Modelling," Papers 2105.08310, arXiv.org.
    3. Peeters, Thomas, 2018. "Testing the Wisdom of Crowds in the field: Transfermarkt valuations and international soccer results," International Journal of Forecasting, Elsevier, vol. 34(1), pages 17-29.
    4. Maribel Serna Rodríguez & Andrés Ramírez Hassan & Alexander Coad, 2019. "Uncovering Value Drivers of High Performance Soccer Players," Journal of Sports Economics, , vol. 20(6), pages 819-849, August.
    5. Dmitry Dagaev & Egor Stoyan, 2019. "Parimutuel Betting On The Esports Duels: Reverse Favourite-Longshot Bias And Its Determinants," HSE Working papers WP BRP 216/EC/2019, National Research University Higher School of Economics.

  4. Dooruj Rambaccussing, 2015. "Modelling Housing Prices using a Present Value State Space Model," Dundee Discussion Papers in Economics 285, Economic Studies, University of Dundee.

    Cited by:

    1. Dooruj McRambaccussing, 2015. "Moment Matching in the Present Value identity, and a New Model," Dundee Discussion Papers in Economics 291, Economic Studies, University of Dundee.

  5. Adam Goliński & João Madeira & Dooruj Rambaccussing, 2015. "Fractional Integration of the Price-Dividend Ratio in a Present-Value Model of Stock Prices," Dundee Discussion Papers in Economics 284, Economic Studies, University of Dundee.

    Cited by:

    1. Rambaccussing, Dooruj, 2015. "Modelling Housing Prices using a Present Value State Space Model," SIRE Discussion Papers 2015-80, Scottish Institute for Research in Economics (SIRE).
    2. Dooruj McRambaccussing, 2015. "Moment Matching in the Present Value identity, and a New Model," Dundee Discussion Papers in Economics 291, Economic Studies, University of Dundee.

  6. James Davidson & Dooruj Rambaccussing, 2015. "A test of the long memory hypothesis based on self-similarity," Dundee Discussion Papers in Economics 286, Economic Studies, University of Dundee.

    Cited by:

    1. Sibbertsen, Philipp & Leschinski, Christian & Holzhausen, Marie, 2015. "A Multivariate Test Against Spurious Long Memory," Hannover Economic Papers (HEP) dp-547, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    2. Less, Vivien & Sibbertsen, Philipp, 2022. "Estimation and Testing in a Perturbed Multivariate Long Memory Framework," Hannover Economic Papers (HEP) dp-704, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    3. Ata Assaf & Luis Alberiko Gil-Alana & Khaled Mokni, 2022. "True or spurious long memory in the cryptocurrency markets: evidence from a multivariate test and other Whittle estimation methods," Empirical Economics, Springer, vol. 63(3), pages 1543-1570, September.
    4. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
    5. Dooruj Rambaccussing & Murat Mazibas, 2020. "True versus Spurious Long Memory in Cryptocurrencies," JRFM, MDPI, vol. 13(9), pages 1-11, August.
    6. Yixun Xing & Wayne A. Woodward, 2021. "R-Squared-Bootstrapping for Gegenbauer-Type Long Memory," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 773-790, February.
    7. Walid Chkili, 2021. "Modeling Bitcoin price volatility: long memory vs Markov switching," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 433-448, September.

  7. Golinski, Adam & Madeira, Joao & Rambaccussing, Dooruj, 2014. "Fractional Integration of the Price-Dividend Ratio in a Present-Value Model," MPRA Paper 58554, University Library of Munich, Germany.

    Cited by:

    1. Mikael Bask & João Madeira, 2021. "Extrapolative expectations and macroeconomic dynamics: Evidence from an estimated DSGE model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1101-1111, January.

Articles

  1. Dooruj Rambaccussing & Murat Mazibas, 2020. "True versus Spurious Long Memory in Cryptocurrencies," JRFM, MDPI, vol. 13(9), pages 1-11, August.

    Cited by:

    1. Ata Assaf & Luis Alberiko Gil-Alana & Khaled Mokni, 2022. "True or spurious long memory in the cryptocurrency markets: evidence from a multivariate test and other Whittle estimation methods," Empirical Economics, Springer, vol. 63(3), pages 1543-1570, September.
    2. Thanasis Stengos, 2021. "Recent Developments in Cryptocurrency Markets: Co-Movements, Spillovers and Forecasting," JRFM, MDPI, vol. 14(3), pages 1-3, February.
    3. Kerolly Kedma Felix do Nascimento & Fábio Sandro dos Santos & Jader Silva Jale & Silvio Fernando Alves Xavier Júnior & Tiago A. E. Ferreira, 2023. "Extracting Rules via Markov Chains for Cryptocurrencies Returns Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 61(3), pages 1095-1114, March.
    4. Assaf, Ata & Mokni, Khaled & Yousaf, Imran & Bhandari, Avishek, 2023. "Long memory in the high frequency cryptocurrency markets using fractal connectivity analysis: The impact of COVID-19," Research in International Business and Finance, Elsevier, vol. 64(C).
    5. Walid Chkili, 2021. "Modeling Bitcoin price volatility: long memory vs Markov switching," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 433-448, September.

  2. Rambaccussing, Dooruj & Kwiatkowski, Andrzej, 2020. "Forecasting with news sentiment: Evidence with UK newspapers," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1501-1516.

    Cited by:

    1. Nyman, Rickard & Kapadia, Sujit & Tuckett, David & Gregory, David & Ormerod, Paul & Smith, Robert, 2018. "News and narratives in financial systems: exploiting big data for systemic risk assessment," Bank of England working papers 704, Bank of England.
    2. Valentina Aprigliano & Simone Emiliozzi & Gabriele Guaitoli & Andrea Luciani & Juri Marcucci & Libero Monteforte, 2021. "The power of text-based indicators in forecasting the Italian economic activity," Temi di discussione (Economic working papers) 1321, Bank of Italy, Economic Research and International Relations Area.
    3. Erik Andres-Escayola & Corinna Ghirelli & Luis Molina & Javier J. Pérez & Elena Vidal, 2022. "Using newspapers for textual indicators: which and how many?," Working Papers 2235, Banco de España.
    4. Kalamara, Eleni & Turrell, Arthur & Redl, Chris & Kapetanios, George & Kapadia, Sujit, 2020. "Making text count: economic forecasting using newspaper text," Bank of England working papers 865, Bank of England.
    5. Dooruj Rambaccussing & Craig Menzies & Andrzej Kwiatkowski, 2022. "Look who’s Talking: Individual Committee members’ impact on inflation expectations," Dundee Discussion Papers in Economics 305, Economic Studies, University of Dundee.
    6. Douglas de Medeiros Franco, 2022. "Expectations, Economic Uncertainty, and Sentiment," RAC - Revista de Administração Contemporânea (Journal of Contemporary Administration), ANPAD - Associação Nacional de Pós-Graduação e Pesquisa em Administração, vol. 26(5), pages 210029-2100.
    7. Dorinth van Dijk & Jasper de Winter, 2023. "Nowcasting GDP using tone-adjusted time varying news topics: Evidence from the financial press," Working Papers 766, DNB.
    8. Doris Chenguang Wu & Shiteng Zhong & Richard T R Qiu & Ji Wu, 2022. "Are customer reviews just reviews? Hotel forecasting using sentiment analysis," Tourism Economics, , vol. 28(3), pages 795-816, May.
    9. María del Pilar Cruz N. & Hugo Peralta V. & Juan Pablo Cova M., 2022. "Utilización de noticias de prensa como indicador de confianza económica en tiempo real," Working Papers Central Bank of Chile 938, Central Bank of Chile.
    10. Kwon, Yujin & Park, Sung Y., 2023. "Modeling an early warning system for household debt risk in Korea: A simple deep learning approach," Journal of Asian Economics, Elsevier, vol. 84(C).
    11. Yongan Xu & Jianqiong Wang & Zhonglu Chen & Chao Liang, 2023. "Sentiment indices and stock returns: Evidence from China," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 1063-1080, January.
    12. De Bandt Olivier & Bricongne Jean-Charles & Denes Julien & Dhenin Alexandre & De Gaye Annabelle & Robert Pierre-Antoine, 2023. "Using the Press to Construct a New Indicator of Inflation Perceptions in France," Working papers 921, Banque de France.

  3. Bowden, James & Kwiatkowski, Andrzej & Rambaccussing, Dooruj, 2019. "Economy through a lens: Distortions of policy coverage in UK national newspapers," Journal of Comparative Economics, Elsevier, vol. 47(4), pages 881-906.

    Cited by:

    1. Dooruj Rambaccussing & Craig Menzies & Andrzej Kwiatkowski, 2022. "Look who’s Talking: Individual Committee members’ impact on inflation expectations," Dundee Discussion Papers in Economics 305, Economic Studies, University of Dundee.
    2. Rambaccussing, Dooruj & Kwiatkowski, Andrzej, 2020. "Forecasting with news sentiment: Evidence with UK newspapers," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1501-1516.

  4. Dooruj Rambaccussing & David Power, 2018. "Expected returns and expected dividend growth in Europe: Legal origin, institutional, and financial determinants," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 23(4), pages 533-545, October.

    Cited by:

    1. Ed-Dafali, Slimane & Patel, Ritesh & Iqbal, Najaf, 2023. "A bibliometric review of dividend policy literature," Research in International Business and Finance, Elsevier, vol. 65(C).
    2. Glauco De Vita & Chengchun Li & Yun Luo, 2022. "Legal origin and financial development: A propensity score matching analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 535-553, January.

  5. Alasdair Brown & Dooruj Rambaccussing & J. James Reade & Giambattista Rossi, 2018. "Forecasting With Social Media: Evidence From Tweets On Soccer Matches," Economic Inquiry, Western Economic Association International, vol. 56(3), pages 1748-1763, July.

    Cited by:

    1. Tao Chen & Erin P. K. So & Isabel K. M. Yan, 2021. "Are crises sentimental?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 962-985, January.
    2. Butler, David & Butler, Robert & Eakins, John, 2021. "Expert performance and crowd wisdom: Evidence from English Premier League predictions," European Journal of Operational Research, Elsevier, vol. 288(1), pages 170-182.
    3. He, Xue-Zhong & Treich, Nicolas, 2017. "Prediction market prices under risk aversion and heterogeneous beliefs," Journal of Mathematical Economics, Elsevier, vol. 70(C), pages 105-114.
    4. Ramirez, Philip & Reade, J. James & Singleton, Carl, 2023. "Betting on a buzz: Mispricing and inefficiency in online sportsbooks," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1413-1423.
    5. Philip ME Garboden, 2019. "Sources and Types of Big Data for Macroeconomic Forecasting," Working Papers 2019-3, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
    6. Ruud H. Koning & Renske Zijm, 2023. "Betting market efficiency and prediction in binary choice models," Annals of Operations Research, Springer, vol. 325(1), pages 135-148, June.
    7. Singleton, Carl & Reade, J. James & Brown, Alasdair, 2020. "Going with your gut: The (In)accuracy of forecast revisions in a football score prediction game," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 89(C).
    8. Pascal Flurin Meier & Raphael Flepp & Egon Franck, 2021. "Are sports betting markets semistrong efficient? Evidence from the COVID-19 pandemic," Working Papers 387, University of Zurich, Department of Business Administration (IBW).
    9. Merz, Oliver & Flepp, Raphael & Franck, Egon, 2021. "Sonic Thunder vs. Brian the Snail: Are people affected by uninformative racehorse names?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 93(C).
    10. Arif Yüce & Sevda Gökce Yüce & Hakan Katırcı & Volkan Aydoğdu & Weisheng Chiu & Mark D. Griffiths, 2023. "The Effect of the COVID-19 Pandemic on Sports Betting Tipsters as Professional Bettors: A Qualitative Interview Study," Sustainability, MDPI, vol. 15(9), pages 1-19, May.
    11. Raphael Flepp & Oliver Merz & Egon Franck, 2024. "When the league table lies: Does outcome bias lead to informationally inefficient markets?," Economic Inquiry, Western Economic Association International, vol. 62(1), pages 414-429, January.
    12. Schlembach, Christoph & Schmidt, Sascha L. & Schreyer, Dominik & Wunderlich, Linus, 2022. "Forecasting the Olympic medal distribution – A socioeconomic machine learning model," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    13. Christoph Schlembach & Sascha L. Schmidt & Dominik Schreyer & Linus Wunderlich, 2020. "Forecasting the Olympic medal distribution during a pandemic: a socio-economic machine learning model," Papers 2012.04378, arXiv.org, revised Jun 2021.
    14. Brown, Alasdair & Reade, J. James, 2019. "The wisdom of amateur crowds: Evidence from an online community of sports tipsters," European Journal of Operational Research, Elsevier, vol. 272(3), pages 1073-1081.
    15. Cano-Marin, Enrique & Mora-Cantallops, Marçal & Sánchez-Alonso, Salvador, 2023. "Twitter as a predictive system: A systematic literature review," Journal of Business Research, Elsevier, vol. 157(C).
    16. Brown, Alasdair & Reade, J. James & Vaughan Williams, Leighton, 2019. "When are prediction market prices most informative?," International Journal of Forecasting, Elsevier, vol. 35(1), pages 420-428.
    17. Bowden, James & Kwiatkowski, Andrzej & Rambaccussing, Dooruj, 2019. "Economy through a lens: Distortions of policy coverage in UK national newspapers," Journal of Comparative Economics, Elsevier, vol. 47(4), pages 881-906.
    18. Rambaccussing, Dooruj & Kwiatkowski, Andrzej, 2020. "Forecasting with news sentiment: Evidence with UK newspapers," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1501-1516.

  6. Davidson James & Rambaccussing Dooruj, 2015. "A Test of the Long Memory Hypothesis Based on Self-Similarity," Journal of Time Series Econometrics, De Gruyter, vol. 7(2), pages 115-141, July.
    See citations under working paper version above.

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 9 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-FOR: Forecasting (2) 2015-03-13 2015-03-22
  2. NEP-MAC: Macroeconomics (2) 2016-03-17 2022-06-27
  3. NEP-MST: Market Microstructure (2) 2016-04-30 2016-05-08
  4. NEP-BAN: Banking (1) 2022-06-27
  5. NEP-CBA: Central Banking (1) 2022-06-27
  6. NEP-CUL: Cultural Economics (1) 2023-08-28
  7. NEP-ECM: Econometrics (1) 2015-03-13
  8. NEP-ETS: Econometric Time Series (1) 2015-03-13
  9. NEP-MON: Monetary Economics (1) 2022-06-27
  10. NEP-PKE: Post Keynesian Economics (1) 2016-05-08
  11. NEP-SPO: Sports and Economics (1) 2023-08-28
  12. NEP-URE: Urban and Real Estate Economics (1) 2015-03-13

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