IDEAS home Printed from https://ideas.repec.org/f/pmo480.html
   My authors  Follow this author

George Monokroussos

Personal Details

First Name:George
Middle Name:
Last Name:Monokroussos
Suffix:
RePEc Short-ID:pmo480
[This author has chosen not to make the email address public]
https://sites.google.com/site/georgemonokroussos/
Terminal Degree:2005 Department of Economics; University of California-San Diego (UCSD) (from RePEc Genealogy)

Affiliation

Joint Research Centre
European Commission

Ispra, Italy
https://ec.europa.eu/jrc/en/about/jrc-site/ispra
RePEc:edi:eejrcit (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Patrick Bajari & Zhihao Cen & Victor Chernozhukov & Manoj Manukonda & Suhas Vijaykumar & Jin Wang & Ramon Huerta & Junbo Li & Ling Leng & George Monokroussos & Shan Wan, 2023. "Hedonic Prices and Quality Adjusted Price Indices Powered by AI," Papers 2305.00044, arXiv.org.
  2. Langedijk, Sven & Monokroussos, George & Papanagiotou, Evangelia, 2016. "Benchmarking Liquidity Proxies: Accounting for Dynamics and Frequency Issues," Working Papers 2016-03, Joint Research Centre, European Commission.
  3. Monokroussos, George, 2015. "Nowcasting in Real Time Using Popularity Priors," MPRA Paper 68594, University Library of Munich, Germany.
  4. Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2015. "Forecasting Consumption: The Role of Consumer Confidence in Real Time with many Predictors," Working Papers 2015-02, Towson University, Department of Economics, revised Jul 2015.
  5. Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2012. "Forecasting Consumption in Real Time: The Role of Consumer Confidence Surveys," Discussion Papers 12-02, University at Albany, SUNY, Department of Economics.
  6. Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2012. "The Yield Spread Puzzle and the Information Content of SPF Forecasts," CESifo Working Paper Series 3949, CESifo.
  7. Kajal Lahiri & George Monokroussos, 2011. "Nowcasting US GDP: The role of ISM Business Surveys," Discussion Papers 11-01, University at Albany, SUNY, Department of Economics.
  8. George Monokroussos, 2009. "A Classical MCMC Approach to the Estimation of Limited Dependent Variable Models of Time Series," Discussion Papers 09-07, University at Albany, SUNY, Department of Economics.
  9. George Monokroussos, 2006. "Dynamic Limited Dependent Variable Modeling and U.S. Monetary Policy," Discussion Papers 06-02, University at Albany, SUNY, Department of Economics.
  10. George Monokroussos, 2006. "A Dynamic Tobit Model for the Open Market Desk's Daily Reaction Function," Computing in Economics and Finance 2006 390, Society for Computational Economics.
  11. Kraay, Aart & Monokroussos, George, 1999. "Growth forecasts using time series and growth models," Policy Research Working Paper Series 2224, The World Bank.

Articles

  1. Vaishal Patel & George Monokroussos & Jason Chen, 2023. "Commentary on "A New Approach to Business Planning during Crises"," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 68, pages 57-59, Q1.
  2. Alexei Alexandrov & Philip Brooks & I-Chen Lee & George Monokroussos, 2021. "Forecasting Demand during COVID-The Case of Wayfair," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 62, pages 8-13, Q3.
  3. Monokroussos, George & Zhao, Yongchen, 2020. "Nowcasting in real time using popularity priors," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1173-1180.
  4. Langedijk, Sven & Monokroussos, George & Papanagiotou, Evangelia, 2018. "Benchmarking liquidity proxies: The case of EU sovereign bonds," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 321-329.
  5. Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2016. "Forecasting Consumption: the Role of Consumer Confidence in Real Time with many Predictors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1254-1275, November.
  6. Lahiri, Kajal & Monokroussos, George & Zhao, Yongchen, 2013. "The yield spread puzzle and the information content of SPF forecasts," Economics Letters, Elsevier, vol. 118(1), pages 219-221.
  7. George Monokroussos, 2013. "A Classical MCMC Approach to the Estimation of Limited Dependent Variable Models of Time Series," Computational Economics, Springer;Society for Computational Economics, vol. 42(1), pages 71-105, June.
  8. Lahiri, Kajal & Monokroussos, George, 2013. "Nowcasting US GDP: The role of ISM business surveys," International Journal of Forecasting, Elsevier, vol. 29(4), pages 644-658.
  9. George Monokroussos, 2011. "Dynamic Limited Dependent Variable Modeling and U.S. Monetary Policy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43, pages 519-534, March.

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.

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Lahiri, Kajal & Monokroussos, George, 2013. "Nowcasting US GDP: The role of ISM business surveys," International Journal of Forecasting, Elsevier, vol. 29(4), pages 644-658.

    Mentioned in:

    1. > Econometrics > Forecasting > Nowcasting

Working papers

  1. Patrick Bajari & Zhihao Cen & Victor Chernozhukov & Manoj Manukonda & Suhas Vijaykumar & Jin Wang & Ramon Huerta & Junbo Li & Ling Leng & George Monokroussos & Shan Wan, 2023. "Hedonic Prices and Quality Adjusted Price Indices Powered by AI," Papers 2305.00044, arXiv.org.

    Cited by:

    1. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann, 2024. "Model Averaging and Double Machine Learning," Papers 2401.01645, arXiv.org, revised Sep 2024.

  2. Langedijk, Sven & Monokroussos, George & Papanagiotou, Evangelia, 2016. "Benchmarking Liquidity Proxies: Accounting for Dynamics and Frequency Issues," Working Papers 2016-03, Joint Research Centre, European Commission.

    Cited by:

    1. Langedijk, Sven & Monokroussos, George & Papanagiotou, Evangelia, 2018. "Benchmarking liquidity proxies: The case of EU sovereign bonds," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 321-329.
    2. Csóka, Péter & Havran, Dániel & Váradi, Kata, 2016. "Konferencia a pénzügyi piacok likviditásáról. Sixth Annual Financial Market Liquidity Conference, 2015 [Conference on the liquidity of financial markets. Sixth Annual Financial Market Liquidity Con," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(4), pages 461-469.

  3. Monokroussos, George, 2015. "Nowcasting in Real Time Using Popularity Priors," MPRA Paper 68594, University Library of Munich, Germany.

    Cited by:

    1. Herman O. Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    2. Monge, Manuel & Claudio-Quiroga, Gloria & Poza, Carlos, 2024. "Chinese economic behavior in times of covid-19. A new leading economic indicator based on Google trends," International Economics, Elsevier, vol. 177(C).

  4. Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2015. "Forecasting Consumption: The Role of Consumer Confidence in Real Time with many Predictors," Working Papers 2015-02, Towson University, Department of Economics, revised Jul 2015.

    Cited by:

    1. Hashmat Khan & Santosh Upadhayaya, 2017. "Does Business Confidence Matter for Investment?," Carleton Economic Papers 17-13, Carleton University, Department of Economics, revised 20 Mar 2019.
    2. Zhongchen Song & Tom Coupé, 2022. "Predicting Chinese consumption series with Baidu," Working Papers in Economics 22/19, University of Canterbury, Department of Economics and Finance.
    3. Francisco Corona & Pilar Poncela & Esther Ruiz, 2017. "Determining the number of factors after stationary univariate transformations," Empirical Economics, Springer, vol. 53(1), pages 351-372, August.
    4. Juhro, Solikin M. & Iyke, Bernard Njindan, 2020. "Consumer confidence and consumption expenditure in Indonesia," Economic Modelling, Elsevier, vol. 89(C), pages 367-377.
    5. Gustavo Adolfo HERNANDEZ DIAZ & Margarita MARÍN JARAMILLO, 2016. "Pronóstico del Consumo Privado: Usando datos de alta frecuencia para el pronóstico de variables de baja frecuencia," Archivos de Economía 14828, Departamento Nacional de Planeación.
    6. Francisco Corona & Graciela González-Farías & Pedro Orraca, 2017. "A dynamic factor model for the Mexican economy: are common trends useful when predicting economic activity?," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 26(1), pages 1-35, December.
    7. Hector H. Sandoval & Anita N. Walsh, 2021. "The role of consumer confidence in forecasting consumption, evidence from Florida," Southern Economic Journal, John Wiley & Sons, vol. 88(2), pages 757-788, October.
    8. A. Girardi & R. Golinelli & C. Pappalardo, 2014. "The Role of Indicator Selection in Nowcasting Euro Area GDP in Pseudo Real Time," Working Papers wp919, Dipartimento Scienze Economiche, Universita' di Bologna.
    9. de Bondt, Gabe & Gieseck, Arne & Herrero, Pablo & Zekaite, Zivile, 2019. "Disaggregate income and wealth effects in the largest euro area countries," Research Technical Papers 15/RT/19, Central Bank of Ireland.
    10. Lorenzo Bencivelli & Massimiliano Marcellino & Gianluca Moretti, 2017. "Forecasting economic activity by Bayesian bridge model averaging," Empirical Economics, Springer, vol. 53(1), pages 21-40, August.
    11. Christian Gayer & Alessandro Girardi & Andreas Reuter, 2016. "Replacing Judgment by Statistics: Constructing Consumer Confidence Indicators on the basis of Data-driven Techniques. The Case of the Euro Area," Working Papers LuissLab 16125, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    12. Kajal Lahiri & Yongchen Zhao, 2016. "Determinants of Consumer Sentiment over Business Cycles: Evidence from the U.S. Surveys of Consumers," Working Papers 2016-14, Towson University, Department of Economics, revised Jul 2016.
    13. Tony Chernis & Calista Cheung & Gabriella Velasco, 2017. "A Three-Frequency Dynamic Factor Model for Nowcasting Canadian Provincial GDP Growth," Discussion Papers 17-8, Bank of Canada.
    14. Tony Chernis & Rodrigo Sekkel, 2017. "A dynamic factor model for nowcasting Canadian GDP growth," Empirical Economics, Springer, vol. 53(1), pages 217-234, August.
    15. Anastasiou, Dimitris & Kallandranis, Christos & Drakos, Konstantinos, 2022. "Borrower discouragement prevalence for Eurozone SMEs: Investigating the impact of economic sentiment," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 161-171.
    16. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Empirical modelling of survey-based expectations for the design of economic indicators in five European regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 205-227, May.
    17. Adrian Fernandez‐Perez & Raquel López, 2023. "The effect of macroeconomic news announcements on the implied volatility of commodities: The role of survey releases," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(11), pages 1499-1530, November.
    18. Chandra Utama & Insukindro & Ardyanto Fitrady, 2022. "Fiscal And Monetary Policy Interactions In Indonesia During Periods Of Economic Turmoil In The Us: 2001q1-2014q4," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 25(1), pages 97-116, June.
    19. Lenka Mynaříková & Vít Pošta, 2023. "The Effect of Consumer Confidence and Subjective Well-being on Consumers’ Spending Behavior," Journal of Happiness Studies, Springer, vol. 24(2), pages 429-453, February.
    20. Gabe Jacob de Bondt & Arne Gieseck & Zivile Zekaite, 2020. "Thick modelling income and wealth effects: a forecast application to euro area private consumption," Empirical Economics, Springer, vol. 58(1), pages 257-286, January.
    21. Kevin Moran & Simplice Aimé Nono & Imad Rherrad, 2018. "Forecasting with Many Predictors: How Useful are National and International Confidence Data?," Cahiers de recherche 1814, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    22. Acuña, Guillermo, 2017. "Evaluación de la capacidad predictiva del índice de percepción del consumidor [Assessing the predictive power of the consumer perception index]," MPRA Paper 83154, University Library of Munich, Germany.
    23. Marek Rusnak, 2013. "Nowcasting Czech GDP in Real Time," Working Papers 2013/06, Czech National Bank.
    24. Hamid Baghestani & Sehar Fatima, 2021. "Growth in US Durables Spending: Assessing the Impact of Consumer Ability and Willingness to Buy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 55-69, April.
    25. Willem Vanlaer & Samantha Bielen & Wim Marneffe, 2020. "Consumer Confidence and Household Saving Behaviors: A Cross-Country Empirical Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 147(2), pages 677-721, January.
    26. Aneta Maria Kłopocka, 2017. "Does Consumer Confidence Forecast Household Saving and Borrowing Behavior? Evidence for Poland," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 133(2), pages 693-717, September.
    27. Aneta M. Klopocka & Rumiana Gorska, 2021. "Forecasting Household Saving Rate with Consumer Confidence Indicator and its Components: Panel Data Analysis of 14 European Countries," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 874-898.
    28. Ivana Lolić & Marija Logarušić & Mirjana Čižmešija, 2022. "Recent Revision of the European Consumer Confidence Indicator: Is There any additional Space for Improvement?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 159(3), pages 845-863, February.
    29. Edmond H. C. Wu & Jihao Hu & Rui Chen, 2022. "Monitoring and forecasting COVID-19 impacts on hotel occupancy rates with daily visitor arrivals and search queries," Current Issues in Tourism, Taylor & Francis Journals, vol. 25(3), pages 490-507, February.
    30. Hamid Baghestani & Ajalavat Viriyavipart, 2019. "Do factors influencing consumer home-buying attitudes explain output growth?," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 46(5), pages 1104-1115, August.
    31. Sangyyup Choi & Jaehun Jeong & Dohyeon Park & Donghoon Yoo, 2023. "News or Animal Spirits? Consumer Confidence and Economic Activity: Redux," Working papers 2023rwp-216, Yonsei University, Yonsei Economics Research Institute.
    32. Hashmat Khan & Jean-François Rouillard & Santosh Upadhayaya, 2020. "Consumer Confidence and Household Investment," Cahiers de recherche 20-15, Departement d'économique de l'École de gestion à l'Université de Sherbrooke.
    33. Gabriel Mathy & Yongchen Zhao, 2023. "Could Diffusion Indexes Have Forecasted the Great Depression?," Working Papers 2023-05, Towson University, Department of Economics, revised Sep 2023.
    34. Jean-Paul L’Huillier & Robert Waldmann & Donghoon Yoo, 2021. "What Is Consumer Confidence?," ISER Discussion Paper 1135r, Institute of Social and Economic Research, Osaka University, revised Dec 2022.
    35. Wu, Weixing & Zhao, Jing, 2022. "Economic policy uncertainty and household consumption: Evidence from Chinese households," Journal of Asian Economics, Elsevier, vol. 79(C).
    36. Vincenzo Merella & Stephen E. Satchell, 2019. "Asset pricing with utility from external anticipation," Carlo Alberto Notebooks 589, Collegio Carlo Alberto.
    37. Baghestani, Hamid, 2021. "Predicting growth in US durables spending using consumer durables-buying attitudes," Journal of Business Research, Elsevier, vol. 131(C), pages 327-336.
    38. Dimitra Kontana & Fotios Siokis, 2019. "Revisiting the Relationship between Financial Wealth, Housing Wealth, and Consumption: A Panel Analysis for the U.S," Discussion Paper Series 2019_03, Department of Economics, University of Macedonia, revised May 2019.
    39. van Giesen, Roxanne I. & Pieters, Rik, 2019. "Climbing out of an economic crisis: A cycle of consumer sentiment and personal stress," Journal of Economic Psychology, Elsevier, vol. 70(C), pages 109-124.
    40. Dimitra Kontana & Fotios Siokis, 2018. "Revisiting the Relationship between Financial Wealth, Housing Wealth, and Consumption: A Panel Analysis for the U.S," J, MDPI, vol. 1(1), pages 1-15, November.
    41. Abosedra, Salah & Laopodis, Nikiforos T. & Fakih, Ali, 2021. "Dynamics and asymmetries between consumer sentiment and consumption in pre- and during-COVID-19 time: Evidence from the US," The Journal of Economic Asymmetries, Elsevier, vol. 24(C).
    42. Marina Matosec & Zdenka Obuljen Zoricic, 2019. "Identifying the Interdependence between Consumer Confidence and Macroeconomic Developments in Croatia," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 17(2-B), pages 345-354.
    43. Diego Chávez & Javier E. Contreras-Reyes & Byron J. Idrovo-Aguirre, 2022. "A Threshold GARCH Model for Chilean Economic Uncertainty," JRFM, MDPI, vol. 16(1), pages 1-15, December.
    44. Hamid Baghestani, 2017. "Do US consumer survey data help beat the random walk in forecasting mortgage rates?," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1343017-134, January.
    45. Chi-Wei Su & Xian-Li Meng & Ran Tao & Muhammad Umar, 2023. "Chinese consumer confidence: A catalyst for the outbound tourism expenditure?," Tourism Economics, , vol. 29(3), pages 696-717, May.

  5. Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2012. "Forecasting Consumption in Real Time: The Role of Consumer Confidence Surveys," Discussion Papers 12-02, University at Albany, SUNY, Department of Economics.

    Cited by:

    1. Hatice Gökçe Karasoy Can & Çağlar Yüncüler, 2018. "The Explanatory Power and the Forecast Performance of Consumer Confidence Indices for Private Consumption Growth in Turkey," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(9), pages 2136-2152, July.
    2. John Khumalo, 2014. "Consumer Spending and Consumer Confidence in South Africa: Cointegration Analysis," Journal of Economics and Behavioral Studies, AMH International, vol. 6(2), pages 95-104.

  6. Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2012. "The Yield Spread Puzzle and the Information Content of SPF Forecasts," CESifo Working Paper Series 3949, CESifo.

    Cited by:

    1. Soojin Jo & Rodrigo Sekkel, 2019. "Macroeconomic Uncertainty Through the Lens of Professional Forecasters," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 436-446, July.
    2. Chatterjee, Ujjal K., 2018. "Bank liquidity creation and recessions," Journal of Banking & Finance, Elsevier, vol. 90(C), pages 64-75.
    3. Kajal Lahiri & Huaming Peng & Yongchen Zhao, 2013. "Testing the Value of Probability Forecasts for Calibrated Combining," Discussion Papers 13-02, University at Albany, SUNY, Department of Economics.
    4. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    5. Herman O. Stekler & Tianyu Ye, 2016. "Evaluating a Leading Indicator: An Application: the Term Spread," Working Papers 2016-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    6. El-Shagi, Makram, 2019. "Rationality tests in the presence of instabilities in finite samples," Economic Modelling, Elsevier, vol. 79(C), pages 242-246.
    7. Knut Lehre Seip & Dan Zhang, 2021. "The Yield Curve as a Leading Indicator: Accuracy and Timing of a Parsimonious Forecasting Model," Forecasting, MDPI, vol. 3(2), pages 1-16, May.
    8. Weiling Liu & Emanuel Moench, 2014. "What predicts U.S. recessions?," Staff Reports 691, Federal Reserve Bank of New York.
    9. Lahiri, Kajal & Yang, Liu, 2016. "Asymptotic variance of Brier (skill) score in the presence of serial correlation," Economics Letters, Elsevier, vol. 141(C), pages 125-129.
    10. Kajal Lahiri & Cheng Yang, 2023. "ROC and PRC Approaches to Evaluate Recession Forecasts," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(2), pages 119-148, September.
    11. Pablo Aguilar & Jesús Vázquez, 2018. "Term structure and real-time learning," Working Papers 1803, Banco de España.

  7. Kajal Lahiri & George Monokroussos, 2011. "Nowcasting US GDP: The role of ISM Business Surveys," Discussion Papers 11-01, University at Albany, SUNY, Department of Economics.

    Cited by:

    1. Lahiri, Kajal & Monokroussos, George & Zhao, Yongchen, 2013. "The yield spread puzzle and the information content of SPF forecasts," Economics Letters, Elsevier, vol. 118(1), pages 219-221.
    2. Lamprou, Dimitra, 2016. "Nowcasting GDP in Greece: The impact of data revisions and forecast origin on model selection and performance," The Journal of Economic Asymmetries, Elsevier, vol. 14(PA), pages 93-102.
    3. Michele Modugno & Lucrezia Reichlin & Domenico Giannone & Marta Banbura, 2012. "Nowcasting with Daily Data," 2012 Meeting Papers 555, Society for Economic Dynamics.
    4. Antonello D'Agostino & Domenico Giannone & Michele Lenza & Michele Modugno, 2015. "Nowcasting Business Cycles: a Bayesian Approach to Dynamic Heterogeneous Factor Models," Finance and Economics Discussion Series 2015-66, Board of Governors of the Federal Reserve System (U.S.).
    5. Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Post-Print hal-03647097, HAL.
    6. Chien-jung Ting & Yi-Long Hsiao & Rui-jun Su, 2022. "Application of the Real-Time Tourism Data in Nowcasting the Service Consumption in Taiwan," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 12(4), pages 1-4.
    7. Basse, Tobias & Desmyter, Steven & Saft, Danilo & Wegener, Christoph, 2023. "Leading indicators for the US housing market: New empirical evidence and thoughts about implications for risk managers and ESG investors," International Review of Financial Analysis, Elsevier, vol. 89(C).
    8. Mogliani, Matteo & Darné, Olivier & Pluyaud, Bertrand, 2017. "The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey," Economic Modelling, Elsevier, vol. 64(C), pages 26-39.
    9. Deicy J. Cristiano & Manuel D. Hernández & José David Pulido, 2012. "Pronósticos de corto plazo en tiempo real para la actividad económica colombiana," Borradores de Economia 9827, Banco de la Republica.
    10. Reichlin, Lucrezia & Giannone, Domenico & Modugno, Michele & Banbura, Marta, 2012. "Now-casting and the real-time data flow," CEPR Discussion Papers 9112, C.E.P.R. Discussion Papers.
    11. A. Girardi & R. Golinelli & C. Pappalardo, 2014. "The Role of Indicator Selection in Nowcasting Euro Area GDP in Pseudo Real Time," Working Papers wp919, Dipartimento Scienze Economiche, Universita' di Bologna.
    12. Sangeeta Das & Dipankor Coondoo, 2018. "Is PMI Useful in Quarterly GDP Growth Forecasts for India? An Exploratory Note," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(1), pages 199-207, December.
    13. Jaewoo Kim & Bryce Schonberger & Charles Wasley & Hunter Land, 2020. "Intertemporal variation in the information content of aggregate earnings and its effect on the aggregate earnings-return relation," Review of Accounting Studies, Springer, vol. 25(4), pages 1410-1443, December.
    14. Lorenzo Bencivelli & Massimiliano Marcellino & Gianluca Moretti, 2017. "Forecasting economic activity by Bayesian bridge model averaging," Empirical Economics, Springer, vol. 53(1), pages 21-40, August.
    15. Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2016. "Forecasting Consumption: the Role of Consumer Confidence in Real Time with many Predictors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1254-1275, November.
    16. Kajal Lahiri & Yongchen Zhao, 2016. "Determinants of Consumer Sentiment over Business Cycles: Evidence from the U.S. Surveys of Consumers," Working Papers 2016-14, Towson University, Department of Economics, revised Jul 2016.
    17. Bespalova, Olga, 2018. "Forecast Evaluation in Macroeconomics and International Finance. Ph.D. thesis, George Washington University, Washington, DC, USA," MPRA Paper 117706, University Library of Munich, Germany.
    18. Tony Chernis & Calista Cheung & Gabriella Velasco, 2017. "A Three-Frequency Dynamic Factor Model for Nowcasting Canadian Provincial GDP Growth," Discussion Papers 17-8, Bank of Canada.
    19. Tiziana Cesaroni & Stefano Iezzi, 2015. "The Predictive Content of Business Survey Indicators: evidence from SIGE," Working Papers LuissLab 15118, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    20. Tony Chernis & Rodrigo Sekkel, 2017. "A dynamic factor model for nowcasting Canadian GDP growth," Empirical Economics, Springer, vol. 53(1), pages 217-234, August.
    21. Danilo Cascaldi-Garcia & Thiago Revil T. Ferreira & Domenico Giannone & Michele Modugno, 2021. "Back to the Present: Learning about the Euro Area through a Now-casting Model," International Finance Discussion Papers 1313, Board of Governors of the Federal Reserve System (U.S.).
    22. Alexander Chudik & Valerie Grossman & M. Hashem Pesaran, 2014. "A multi-country approach to forecasting output growth using PMIs," Globalization Institute Working Papers 213, Federal Reserve Bank of Dallas.
    23. George Kapetanios & Fotis Papailias, 2018. "Big Data & Macroeconomic Nowcasting: Methodological Review," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-12, Economic Statistics Centre of Excellence (ESCoE).
    24. Huseyin Cagri Akkoyun & Mahmut Gunay, 2013. "Milli Gelir Buyume Tahmini : IYA ve PMI Gostergelerinin Rolu," CBT Research Notes in Economics 1331, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    25. Daniel Kaufmann & Rolf Scheufele, 2015. "Business tendency surveys and macroeconomic fluctuations," KOF Working papers 15-378, KOF Swiss Economic Institute, ETH Zurich.
    26. Iyer , Tara & Sen Gupta, Abhijit, 2019. "Nowcasting Economic Growth in India: The Role of Rainfall," ADB Economics Working Paper Series 593, Asian Development Bank.
    27. Hanslin Grossmann, Sandra & Scheufele, Rolf, 2015. "Foreign PMIs: A reliable indicator for Swiss exports," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112830, Verein für Socialpolitik / German Economic Association.
    28. Adrian Fernandez‐Perez & Raquel López, 2023. "The effect of macroeconomic news announcements on the implied volatility of commodities: The role of survey releases," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(11), pages 1499-1530, November.
    29. Radoslaw Sobko & Maria Klonowska-Matynia, 2021. "The Relationship between the Purchasing Managers’ Index (PMI) and Economic Growth: The Case for Poland," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 198-219.
    30. Dr. Alain Galli & Dr. Christian Hepenstrick & Dr. Rolf Scheufele, 2017. "Mixed-frequency models for tracking short-term economic developments in Switzerland," Working Papers 2017-02, Swiss National Bank.
    31. Ergun Ermisoglu & Yasin Akcelik & Arif Oduncu, 2013. "GDP Growth and Credit Data," Working Papers 1327, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    32. Kevin Moran & Simplice Aimé Nono & Imad Rherrad, 2018. "Forecasting with Many Predictors: How Useful are National and International Confidence Data?," Cahiers de recherche 1814, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    33. Chien-jung Ting & Yi-Long Hsiao, 2022. "Nowcasting the GDP in Taiwan and the Real-Time Tourism Data," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 12(3), pages 1-2.
    34. Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 615-643, August.
    35. Kilinc, Zubeyir & Yucel, Eray, 2016. "PMI Thresholds for GDP Growth," MPRA Paper 70929, University Library of Munich, Germany.
    36. Camila Figueroa S. & Michael Pedersen, 2019. "Extracting information on economic activity from business and consumer surveys in an emerging economy (Chile)," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 22(3), pages 098-131, December.
    37. Rolando F. Peláez, 2018. "Improving the usefulness of the Purchasing Managers’ Index," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 53(4), pages 195-201, October.
    38. Zhang, Qin & Ni, He & Xu, Hao, 2023. "Nowcasting Chinese GDP in a data-rich environment: Lessons from machine learning algorithms," Economic Modelling, Elsevier, vol. 122(C).
    39. Gabe J. Bondt, 2019. "A PMI-Based Real GDP Tracker for the Euro Area," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 15(2), pages 147-170, December.
    40. Ramazan Yanik & Asfia Binte Osman & Ozcan Ozturk, 2020. "Impact of manufacturing PMI on stock market index: A study on Turkey," Journal of Administrative and Business Studies, Professor Dr. Usman Raja, vol. 6(3), pages 104-108.
    41. Khundrakpam, Jeevan Kumar & George, Asish Thomas, 2012. "An Empirical Analysis of the Relationship between WPI and PMI-Manufacturing Price Indices in India," MPRA Paper 50929, University Library of Munich, Germany.
    42. Liu, Ping & James Hueng, C., 2017. "Measuring real business condition in China," China Economic Review, Elsevier, vol. 46(C), pages 261-274.
    43. Marek Rusnak, 2013. "Nowcasting Czech GDP in Real Time," Working Papers 2013/06, Czech National Bank.
    44. Caruso, Alberto, 2019. "Macroeconomic news and market reaction: Surprise indexes meet nowcasting," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1725-1734.
    45. Kenichiro McAlinn, 2021. "Mixed‐frequency Bayesian predictive synthesis for economic nowcasting," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1143-1163, November.
    46. Christiansen, Charlotte & Eriksen, Jonas N. & Møller, Stig V., 2019. "Negative house price co-movements and US recessions," Regional Science and Urban Economics, Elsevier, vol. 77(C), pages 382-394.
    47. Liudmila Kitrar & Tamara Lipkind, 2021. "Development Of Composite Indicators Of Cyclical Response In Business Surveys Considering The Specifics Of The ‘Covid-19 Economy’," HSE Working papers WP BRP 121/STI/2021, National Research University Higher School of Economics.
    48. Pawel Krolikowski & Kurt Graden Lunsford, 2020. "Advance Layoff Notices and Aggregate Job Loss," Working Papers 20-03R, Federal Reserve Bank of Cleveland, revised 02 Feb 2022.
    49. Danilo Cascaldi-Garcia & Matteo Luciani & Michele Modugno, 2023. "Lessons from Nowcasting GDP across the World," International Finance Discussion Papers 1385, Board of Governors of the Federal Reserve System (U.S.).
    50. Edmond H. C. Wu & Jihao Hu & Rui Chen, 2022. "Monitoring and forecasting COVID-19 impacts on hotel occupancy rates with daily visitor arrivals and search queries," Current Issues in Tourism, Taylor & Francis Journals, vol. 25(3), pages 490-507, February.
    51. Hindrayanto, Irma & Koopman, Siem Jan & de Winter, Jasper, 2016. "Forecasting and nowcasting economic growth in the euro area using factor models," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1284-1305.
    52. Daniela Bragoli & Michele Modugno, 2016. "A Nowcasting Model for Canada: Do U.S. Variables Matter?," Finance and Economics Discussion Series 2016-036, Board of Governors of the Federal Reserve System (U.S.).
    53. Bragoli, Daniela, 2017. "Now-casting the Japanese economy," International Journal of Forecasting, Elsevier, vol. 33(2), pages 390-402.
    54. Gabe de Bondt, 2012. "Nowcasting: Trust the Purchasing Managers’ Index or wait for the flash GDP estimate?," EcoMod2012 3896, EcoMod.
    55. Turhan, Ibrahim M. & Sensoy, Ahmet & Hacihasanoglu, Erk, 2015. "Shaping the manufacturing industry performance: MIDAS approach," Chaos, Solitons & Fractals, Elsevier, vol. 77(C), pages 286-290.
    56. Abhiman Das & Kajal Lahiri & Yongchen Zhao, 2018. "Inflation Expectations in India: Learning from Household Tendency Surveys," Working Papers 2018-03, Towson University, Department of Economics, revised Aug 2018.
    57. Alexander James & Yaser S. Abu-Mostafa & Xiao Qiao, 2019. "Nowcasting Recessions using the SVM Machine Learning Algorithm," Papers 1903.03202, arXiv.org, revised Jun 2019.
    58. Caruso, Alberto, 2018. "Nowcasting with the help of foreign indicators: The case of Mexico," Economic Modelling, Elsevier, vol. 69(C), pages 160-168.
    59. Dr. Sandra Hanslin Grossmann & Dr. Rolf Scheufele, 2016. "Foreign PMIs: A reliable indicator for exports?," Working Papers 2016-01, Swiss National Bank.
    60. Anesti, Nikoleta & Kalamara, Eleni & Kapetanios, George, 2021. "Forecasting UK GDP growth with large survey panels," Bank of England working papers 923, Bank of England.
    61. John B. Broughton & Bento J. Lobo, 2018. "Herding and anchoring in macroeconomic forecasts: the case of the PMI," Empirical Economics, Springer, vol. 55(3), pages 1337-1355, November.
    62. Alessandro Mistretta, 2021. "Business cycle synchronization or business cycle transmission? The effect of the German slowdown on the Italian economy," Temi di discussione (Economic working papers) 1346, Bank of Italy, Economic Research and International Relations Area.
    63. Schnatz, Bernd & D'Agostino, Antonello, 2012. "Survey-based nowcasting of US growth: a real-time forecast comparison over more than 40 years," Working Paper Series 1455, European Central Bank.
    64. Tsuchiya, Yoichi, 2014. "Purchasing and supply managers provide early clues on the direction of the US economy: An application of a new market-timing test," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 599-618.
    65. Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2012. "Forecasting Consumption in Real Time: The Role of Consumer Confidence Surveys," Discussion Papers 12-02, University at Albany, SUNY, Department of Economics.
    66. Urasawa, Satoshi, 2014. "Real-time GDP forecasting for Japan: A dynamic factor model approach," Journal of the Japanese and International Economies, Elsevier, vol. 34(C), pages 116-134.
    67. Gabe J. Bondt & Stefano Schiaffi, 2015. "Confidence Matters for Current Economic Growth: Empirical Evidence for the Euro Area and the United States," Social Science Quarterly, Southwestern Social Science Association, vol. 96(4), pages 1027-1040, December.

  8. George Monokroussos, 2009. "A Classical MCMC Approach to the Estimation of Limited Dependent Variable Models of Time Series," Discussion Papers 09-07, University at Albany, SUNY, Department of Economics.

    Cited by:

    1. George Monokroussos, 2006. "Dynamic Limited Dependent Variable Modeling and U.S. Monetary Policy," Discussion Papers 06-02, University at Albany, SUNY, Department of Economics.
    2. George Monokroussos, 2006. "A Dynamic Tobit Model for the Open Market Desk's Daily Reaction Function," Computing in Economics and Finance 2006 390, Society for Computational Economics.

  9. George Monokroussos, 2006. "Dynamic Limited Dependent Variable Modeling and U.S. Monetary Policy," Discussion Papers 06-02, University at Albany, SUNY, Department of Economics.

    Cited by:

    1. Gurnain Pasricha, 2017. "Policy Rules for Capital Controls," Staff Working Papers 17-42, Bank of Canada.
    2. Eric Girardin & Sandrine Lunven & Guonan Ma, 2014. "Inflation and China's monetary policy reaction function: 2002-2013," BIS Papers chapters, in: Bank for International Settlements (ed.), Globalisation, inflation and monetary policy in Asia and the Pacific, volume 77, pages 159-170, Bank for International Settlements.
    3. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    4. Seibert, Armin & Sirchenko, Andrei & Müller, Gernot, 2021. "A model for policy interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 124(C).
    5. Eric Girardin & Sandrine Lunven & Guonan Ma, 2017. "China's evolving monetary policy rule: from inflation-accommodating to anti-inflation policy," BIS Working Papers 641, Bank for International Settlements.
    6. Sjoerd van den Hauwe & Dick van Dijk & Richard Paap, 2011. "Bayesian Forecasting of Federal Funds Target Rate Decisions," Tinbergen Institute Discussion Papers 11-093/4, Tinbergen Institute.
    7. George Monokroussos, 2006. "A Dynamic Tobit Model for the Open Market Desk's Daily Reaction Function," Computing in Economics and Finance 2006 390, Society for Computational Economics.
    8. Pauwels, Laurent L. & Vasnev, Andrey L., 2016. "A note on the estimation of optimal weights for density forecast combinations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 391-397.
    9. Dick van Dijk & Robin L. Lumsdaine & Michel van der Wel, 2014. "Market Set-Up in Advance of Federal Reserve Policy Decisions," NBER Working Papers 19814, National Bureau of Economic Research, Inc.
    10. Andrei Sirchenko, 2019. "A regime-switching model for the federal funds rate target," UvA-Econometrics Working Papers 19-01, Universiteit van Amsterdam, Dept. of Econometrics.
    11. Hyeongwoo Kim & Wen Shi, 2017. "The Determinants of the Benchmark Interest Rates in China: A Discrete Choice Model Approach," Auburn Economics Working Paper Series auwp2017-04, Department of Economics, Auburn University.
    12. George Monokroussos, 2009. "A Classical MCMC Approach to the Estimation of Limited Dependent Variable Models of Time Series," Discussion Papers 09-07, University at Albany, SUNY, Department of Economics.
    13. Zhang, Xinyu & Lu, Zudi & Zou, Guohua, 2013. "Adaptively combined forecasting for discrete response time series," Journal of Econometrics, Elsevier, vol. 176(1), pages 80-91.
    14. Laurent L. Pauwels & Andrey L. Vasnev, 2017. "Forecast combination for discrete choice models: predicting FOMC monetary policy decisions," Empirical Economics, Springer, vol. 52(1), pages 229-254, February.
    15. Kim, Hyeongwoo & Shi, Wen, 2018. "The determinants of the benchmark interest rates in China," Journal of Policy Modeling, Elsevier, vol. 40(2), pages 395-417.
    16. Pasricha, Gurnain K., 2022. "Estimated policy rules for capital controls," Journal of International Money and Finance, Elsevier, vol. 122(C).

  10. Kraay, Aart & Monokroussos, George, 1999. "Growth forecasts using time series and growth models," Policy Research Working Paper Series 2224, The World Bank.

    Cited by:

    1. Bloom, David E. & Canning, David & Fink, Gunther & Finlay, Jocelyn E., 2007. "Does age structure forecast economic growth?," International Journal of Forecasting, Elsevier, vol. 23(4), pages 569-585.
    2. Ahlburg, Dennis & Lindh, Thomas, 2007. "Long-run income forecasting," International Journal of Forecasting, Elsevier, vol. 23(4), pages 533-538.
    3. Ianchovichina, Elena & Kacker, Pooja, 2005. "Growth trends in the developing world : country forecasts and determinants," Policy Research Working Paper Series 3775, The World Bank.
    4. Qin, Duo & Cagas, Marie Anne & Ducanes, Geoffrey & Magtibay-Ramos, Nedelyn & Quising, Pilipinas, 2008. "Automatic leading indicators versus macroeconometric structural models: A comparison of inflation and GDP growth forecasting," International Journal of Forecasting, Elsevier, vol. 24(3), pages 399-413.
    5. Ignacio Mauleón, 2021. "Aggregated World Energy Demand Projections: Statistical Assessment," Energies, MDPI, vol. 14(15), pages 1-13, July.

Articles

  1. Monokroussos, George & Zhao, Yongchen, 2020. "Nowcasting in real time using popularity priors," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1173-1180.
    See citations under working paper version above.
  2. Langedijk, Sven & Monokroussos, George & Papanagiotou, Evangelia, 2018. "Benchmarking liquidity proxies: The case of EU sovereign bonds," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 321-329.

    Cited by:

    1. Emre Su & Kaya Tokmakçıoğlu, 2023. "Determinants of bid-ask spread in emerging sovereign bond markets," Journal of Asset Management, Palgrave Macmillan, vol. 24(5), pages 346-352, September.
    2. Díaz, Antonio & Escribano, Ana, 2020. "Measuring the multi-faceted dimension of liquidity in financial markets: A literature review," Research in International Business and Finance, Elsevier, vol. 51(C).
    3. Hamill, Philip A. & Li, Youwei & Pantelous, Athanasios A. & Vigne, Samuel A. & Waterworth, James, 2021. "Was a deterioration in ‘connectedness’ a leading indicator of the European sovereign debt crisis?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    4. Srivastava, Nikhil & Tripe, David & Yuen, Mui Kuen, 2023. "Healthcare expenditure and bank deposits," Finance Research Letters, Elsevier, vol. 58(PC).
    5. Kang-Soek Lee, 2020. "Macroprudential stress testing: A proposal for the Luxembourg investment fund sector," BCL working papers 141, Central Bank of Luxembourg.
    6. Richter, Thomas Julian, 2022. "Liquidity commonality in sovereign bond markets," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 501-518.

  3. Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2016. "Forecasting Consumption: the Role of Consumer Confidence in Real Time with many Predictors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1254-1275, November.
    See citations under working paper version above.
  4. Lahiri, Kajal & Monokroussos, George & Zhao, Yongchen, 2013. "The yield spread puzzle and the information content of SPF forecasts," Economics Letters, Elsevier, vol. 118(1), pages 219-221.
    See citations under working paper version above.
  5. George Monokroussos, 2013. "A Classical MCMC Approach to the Estimation of Limited Dependent Variable Models of Time Series," Computational Economics, Springer;Society for Computational Economics, vol. 42(1), pages 71-105, June.
    See citations under working paper version above.
  6. Lahiri, Kajal & Monokroussos, George, 2013. "Nowcasting US GDP: The role of ISM business surveys," International Journal of Forecasting, Elsevier, vol. 29(4), pages 644-658.
    See citations under working paper version above.
  7. George Monokroussos, 2011. "Dynamic Limited Dependent Variable Modeling and U.S. Monetary Policy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43, pages 519-534, March.
    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 13 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 (7) 2005-11-19 2006-07-15 2011-11-28 2015-07-25 2016-01-03 2020-02-17 2023-05-29. Author is listed
  2. NEP-FOR: Forecasting (4) 2012-06-25 2012-10-06 2015-07-25 2016-01-03
  3. NEP-BIG: Big Data (3) 2020-02-17 2023-05-29 2023-06-12
  4. NEP-ECM: Econometrics (3) 2006-07-15 2009-11-07 2016-01-03
  5. NEP-CMP: Computational Economics (2) 2023-05-29 2023-06-12
  6. NEP-ETS: Econometric Time Series (2) 2009-11-07 2016-01-03
  7. NEP-MST: Market Microstructure (2) 2015-02-11 2017-08-27
  8. NEP-BEC: Business Economics (1) 2011-11-28
  9. NEP-CBA: Central Banking (1) 2005-11-19
  10. NEP-DES: Economic Design (1) 2023-05-29
  11. NEP-FMK: Financial Markets (1) 2006-07-15
  12. NEP-HIS: Business, Economic and Financial History (1) 2005-11-19
  13. NEP-MON: Monetary Economics (1) 2005-11-19
  14. NEP-ORE: Operations Research (1) 2020-02-17

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, George Monokroussos 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.