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Filippo Moauro

Personal Details

First Name:Filippo
Middle Name:
Last Name:Moauro
Suffix:
RePEc Short-ID:pmo607

Affiliation

Istituto Nazionale di Statistica (ISTAT)

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

Research output

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Jump to: Working papers Articles

Working papers

  1. Bisio, Laura & Moauro, Filippo, 2017. "Temporal disaggregation by dynamic regressions: recent developments in Italian quarterly national accounts," MPRA Paper 80211, University Library of Munich, Germany, revised 14 Jul 2017.
  2. Moauro, Filippo, 2010. "A monthly indicator of employment in the euro area: real time analysis of indirect estimates," MPRA Paper 27797, University Library of Munich, Germany, revised 30 Dec 2010.
  3. Tommaso Proietti & Filippo Moauro, 2004. "Dynamic Factor Analysis with Nonlinear Temporal Aggregation Constraints," Econometrics 0401003, University Library of Munich, Germany.

Articles

  1. Filippo Moauro, 2014. "Monthly Employment Indicators of the Euro Area and Larger Member States: Real‐Time Analysis of Indirect Estimates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(5), pages 339-349, August.
  2. Tommaso Proietti & Filippo Moauro, 2006. "Dynamic factor analysis with non‐linear temporal aggregation constraints," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 55(2), pages 281-300, April.
  3. Filippo Moauro & Giovanni Savio, 2005. "Temporal disaggregation using multivariate structural time series models," Econometrics Journal, Royal Economic Society, vol. 8(2), pages 214-234, 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. Bisio, Laura & Moauro, Filippo, 2017. "Temporal disaggregation by dynamic regressions: recent developments in Italian quarterly national accounts," MPRA Paper 80211, University Library of Munich, Germany, revised 14 Jul 2017.

    Cited by:

    1. Sergio Destefanis & Matteo Fragetta & Nazzareno Ruggiero, 2023. "Active and passive labour-market policies: the outlook from the Beveridge curve," Applied Economics, Taylor & Francis Journals, vol. 55(55), pages 6538-6550, November.
    2. Bosco de Sousa, Faviana, 2021. "Do Political Actors Engage in Strategic Deception on Social Media?," Warwick-Monash Economics Student Papers 12, Warwick Monash Economics Student Papers.
    3. Bisio, Laura & Moauro, Filippo, 2017. "Temporal disaggregation by dynamic regressions: recent developments in Italian quarterly national accounts," MPRA Paper 80211, University Library of Munich, Germany, revised 14 Jul 2017.
    4. Christian Caamaño-Carrillo & Sergio Contreras-Espinoza & Orietta Nicolis, 2023. "Reconstructing the Quarterly Series of the Chilean Gross Domestic Product Using a State Space Approach," Mathematics, MDPI, vol. 11(8), pages 1-14, April.
    5. Proietti, Tommaso & Giovannelli, Alessandro & Ricchi, Ottavio & Citton, Ambra & Tegami, Christían & Tinti, Cristina, 2021. "Nowcasting GDP and its components in a data-rich environment: The merits of the indirect approach," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1376-1398.

  2. Tommaso Proietti & Filippo Moauro, 2004. "Dynamic Factor Analysis with Nonlinear Temporal Aggregation Constraints," Econometrics 0401003, University Library of Munich, Germany.

    Cited by:

    1. Mitchell, James & Solomou, Solomos & Weale, Martin, 2012. "Monthly GDP estimates for inter-war Britain," Explorations in Economic History, Elsevier, vol. 49(4), pages 543-556.
    2. Paul Labonne & Martin Weale, 2020. "Temporal disaggregation of overlapping noisy quarterly data: estimation of monthly output from UK value‐added tax data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 1211-1230, June.
    3. Marco Cacciotti & Cecilia Frale & Serena Teobaldo, 2013. "A new methodology for a quarterly measure of the Output Gap," Working Papers LuissLab 13103, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    4. S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2007. "Real-time measurement of business conditions," International Finance Discussion Papers 901, Board of Governors of the Federal Reserve System (U.S.).
    5. Cecilia Frale & Libero Monteforte, "undated". "FaMIDAS: A Mixed Frequency Factor Model with MIDAS structure," Working Papers 3, Department of the Treasury, Ministry of the Economy and of Finance.
    6. Maximo Camacho & Rafael Domenech, 2010. "MICA-BBVA: A Factor Model of Economic and Financial Indicators for Short-term GDP Forecasting," Working Papers 1021, BBVA Bank, Economic Research Department.
    7. Libero Monteforte & Valentina Raponi, 2019. "Short‐term forecasts of economic activity: Are fortnightly factors useful?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(3), pages 207-221, April.
    8. Bräuning, Falk & Koopman, Siem Jan, 2014. "Forecasting macroeconomic variables using collapsed dynamic factor analysis," International Journal of Forecasting, Elsevier, vol. 30(3), pages 572-584.
    9. Marco Cacciotti & Cecilia Frale & Serena Teobaldo, 2013. "A new methodology for a quarterly measure of the output gap," Working Papers 6, Department of the Treasury, Ministry of the Economy and of Finance.
    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. Peter Fuleky & Carl Bonham, 2010. "Forecasting Based on Common Trends in Mixed Frequency Samples," Working Papers 2010-17R1, University of Hawaii Economic Research Organization, University of Hawaii at Manoa, revised Jul 2013.
    12. Cecilia Frale & Massimiliano Marcellino & Gian Luigi Mazzi & Tommaso Proietti, 2009. "Survey Data as Coicident or Leading Indicators," Economics Working Papers ECO2009/19, European University Institute.
    13. Christian Glocker & Philipp Wegmüller, 2017. "Business Cycle Dating and Forecasting with Real-time Swiss GDP Data," WIFO Working Papers 542, WIFO.
    14. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 141-194, Elsevier.
    15. Foroni, Claudia & Marcellino, Massimiliano & Schumacher, Christian, 2011. "U-MIDAS: MIDAS regressions with unrestricted lag polynomials," Discussion Paper Series 1: Economic Studies 2011,35, Deutsche Bundesbank.
    16. Chan, Wai-Sum, 2022. "On temporal aggregation of some nonlinear time-series models," Econometrics and Statistics, Elsevier, vol. 21(C), pages 38-49.
    17. Bisio, Laura & Moauro, Filippo, 2017. "Temporal disaggregation by dynamic regressions: recent developments in Italian quarterly national accounts," MPRA Paper 80211, University Library of Munich, Germany, revised 14 Jul 2017.
    18. Peter Fuleky & Carl S. Bonham, 2013. "Forecasting with Mixed Frequency Samples: The Case of Common Trends," Working Papers 201305, University of Hawaii at Manoa, Department of Economics.
    19. Tommaso Proietti, 2004. "Temporal Disaggregation by State Space Methods: Dynamic Regression Methods Revisited," Econometrics 0411011, University Library of Munich, Germany.
    20. Francisco de Castro & Francisco Martí & Antonio Montesinos & Javier J. Pérez & A. Jesús Sánchez-Fuentes, 2014. "Fiscal policies in Spain: Main stylises facts revisited," Working Papers 1408, Banco de España.
    21. Proietti, Tommaso, 2008. "Estimation of Common Factors under Cross-Sectional and Temporal Aggregation Constraints: Nowcasting Monthly GDP and its Main Components," MPRA Paper 6860, University Library of Munich, Germany.
    22. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers 2019-4, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
    23. Mahmood, Asif & Masood, Hina, 2024. "A High-frequency Monthly Measure of Real Economic Activity in Pakistan," MPRA Paper 121838, University Library of Munich, Germany.
    24. Maximo Camacho & Gabriel Perez-Quiros & Pilar Poncela, 2012. "Markov-switching dynamic factor models in real time," Working Papers 1205, Banco de España.
    25. Mitchell, J. & Solomou, S. & Weale, M., 2009. "Monthly and Quarterly GDP Estimates for Interwar Britain," Cambridge Working Papers in Economics 0949, Faculty of Economics, University of Cambridge.
    26. Joan Paredes & Diego J. Pedregal & Javier J. Pérez, 2009. "A quarterly fiscal database for the euro area based on intra-annual fiscal information," Working Papers 0935, Banco de España.
    27. Albers, Thilo & Uebele, Martin, 2015. "The global impact of the great depression," LSE Research Online Documents on Economics 64491, London School of Economics and Political Science, LSE Library.
    28. William Barnett & Marcelle Chauvetz & Danilo Leiva-Leonx, 2014. "Real-Time Nowcasting Nominal GDP Under Structural Break," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201313, University of Kansas, Department of Economics, revised Feb 2014.
    29. Cecilia Frale, "undated". "Do Surveys Help in Macroeconomic Variables Disaggregation and Estimation?," Working Papers wp2008-2, Department of the Treasury, Ministry of the Economy and of Finance.
    30. Cecilia Frale & Stefano Grassi & Massimiliano Marcellino & Gianluigi Mazzi & Tommaso Proietti, 2013. "EuroMInd-C: a Disaggregate Monthly Indicator of Economic Activity for the Euro Area and member countries," CEIS Research Paper 287, Tor Vergata University, CEIS, revised 01 Oct 2013.
    31. Maximo Camacho & Gabriel Perez-Quiros, 2008. "Introducing the EURO-STING: Short Term INdicator of Euro Area Growth," Working Papers 0807, Banco de España.
    32. Diego J. Pedregal & Javier J. Pérez & Antonio Sánchez Fuentes, 2014. "A Tookit to strengthen Government," Hacienda Pública Española / Review of Public Economics, IEF, vol. 211(4), pages 117-146, December.
    33. Teresa Leal & Diego Pedregal & Javier Pérez, 2011. "Short-term monitoring of the Spanish government balance," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 2(1), pages 97-119, March.
    34. Cecilia Frale & David Veredas, 2008. "A Monthly Volatility Index for the US Economy," Working Papers ECARES 2008-008, ULB -- Universite Libre de Bruxelles.
    35. Cecilia Frale, Serena Teobaldo, Marco Cacciotti, Alessandra Caretta, 2013. "A Quarterly Measure Of Potential Output In The New European Fiscal Framework," 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 181-197, April-Jun.
    36. Martyna Marczak & Víctor Gómez, 2017. "Monthly US business cycle indicators: a new multivariate approach based on a band-pass filter," Empirical Economics, Springer, vol. 52(4), pages 1379-1408, June.
    37. Sieds, 2013. "Complete Volume LXVII n.2 2013," 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 1-197, April-Jun.
    38. Pérez, Javier J. & Pedregal, Diego J., 2008. "Should quarterly government finance statistics be used for fiscal surveillane in Europe?," Working Paper Series 937, European Central Bank.
    39. Maximo Camacho & Gabriel Perez-Quiros, 2009. "Ñ-STING: España Short Term INdicator of Growth," Working Papers 0912, Banco de España.
    40. Marcellino, Massimiliano & Proietti, Tommaso & Frale, Cecilia & Mazzi, Gian Luigi, 2008. "A Monthly Indicator of the Euro Area GDP," CEPR Discussion Papers 7007, C.E.P.R. Discussion Papers.
    41. William A. Barnett & Marcelle Chauvet & Danilo Leiva-Leon, 2014. "Real-Time Nowcasting of Nominal GDP Under Structural Breaks," Staff Working Papers 14-39, Bank of Canada.
    42. Paul Labonne & Martin Weale, 2018. "Temporal disaggregation of overlapping noisy quarterly data using state space models: Estimation of monthly business sector output from Value Added Tax data in the UK," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-18, Economic Statistics Centre of Excellence (ESCoE).
    43. Moauro, Filippo, 2010. "A monthly indicator of employment in the euro area: real time analysis of indirect estimates," MPRA Paper 27797, University Library of Munich, Germany, revised 30 Dec 2010.
    44. Diego J. Pedregal & Javier J. Pérez & A. Jesús Sánchez-Fuentes, 2014. "A toolkit to strengthen government budget surveillance," Working Papers 1416, Banco de España.
    45. Schumacher Christian, 2011. "Forecasting with Factor Models Estimated on Large Datasets: A Review of the Recent Literature and Evidence for German GDP," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 28-49, February.
    46. Barnett, William A. & Chauvet, Marcelle & Leiva-Leon, Danilo, 2016. "Real-time nowcasting of nominal GDP with structural breaks," Journal of Econometrics, Elsevier, vol. 191(2), pages 312-324.
    47. Albers, Thilo Nils Hendrik, 2018. "The prelude and global impact of the Great Depression: Evidence from a new macroeconomic dataset," Explorations in Economic History, Elsevier, vol. 70(C), pages 150-163.
    48. Monica Defend & Aleksey Min & Lorenzo Portelli & Franz Ramsauer & Francesco Sandrini & Rudi Zagst, 2021. "Quantifying Drivers of Forecasted Returns Using Approximate Dynamic Factor Models for Mixed-Frequency Panel Data," Forecasting, MDPI, vol. 3(1), pages 1-35, February.
    49. Miroslav Klucik, 2019. "Tracking the Course of the Economy (Nowcasting of basic macroeconomic indicators of Slovakia)," Working Papers Working Paper No. 1/2019, Council for Budget Responsibility.
    50. Javier Pérez & A. Sánchez, 2011. "Is there a signalling role for public wages? Evidence for the euro area based on macro data," Empirical Economics, Springer, vol. 41(2), pages 421-445, October.
    51. Konstantin Kuck & Karsten Schweikert, 2021. "Forecasting Baden‐Württemberg's GDP growth: MIDAS regressions versus dynamic mixed‐frequency factor models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 861-882, August.
    52. Helmut Luetkepohl, 2009. "Forecasting Aggregated Time Series Variables: A Survey," Economics Working Papers ECO2009/17, European University Institute.
    53. Paul Viefers, 2011. "Bayesian Inference for the Mixed-Frequency VAR Model," Discussion Papers of DIW Berlin 1172, DIW Berlin, German Institute for Economic Research.

Articles

  1. Filippo Moauro, 2014. "Monthly Employment Indicators of the Euro Area and Larger Member States: Real‐Time Analysis of Indirect Estimates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(5), pages 339-349, August.

    Cited by:

    1. Bisio, Laura & Moauro, Filippo, 2017. "Temporal disaggregation by dynamic regressions: recent developments in Italian quarterly national accounts," MPRA Paper 80211, University Library of Munich, Germany, revised 14 Jul 2017.
    2. María Gil & Javier J. Pérez & Alberto Urtasun, 2019. "Nowcasting private consumption: traditional indicators, uncertainty measures, credit cards and some internet data," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.

  2. Tommaso Proietti & Filippo Moauro, 2006. "Dynamic factor analysis with non‐linear temporal aggregation constraints," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 55(2), pages 281-300, April.
    See citations under working paper version above.
  3. Filippo Moauro & Giovanni Savio, 2005. "Temporal disaggregation using multivariate structural time series models," Econometrics Journal, Royal Economic Society, vol. 8(2), pages 214-234, July.

    Cited by:

    1. Paul Labonne & Martin Weale, 2020. "Temporal disaggregation of overlapping noisy quarterly data: estimation of monthly output from UK value‐added tax data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 1211-1230, June.
    2. Cecilia Frale & Libero Monteforte, "undated". "FaMIDAS: A Mixed Frequency Factor Model with MIDAS structure," Working Papers 3, Department of the Treasury, Ministry of the Economy and of Finance.
    3. Klaus Abberger & Michael Graff & Oliver Müller & Boriss Silverstovs, 2022. "Imputing monthly values for quarterly time series. An application performed with Swiss business cycle data," KOF Working papers 22-509, KOF Swiss Economic Institute, ETH Zurich.
    4. Eliana González & Luis F. Melo & Luis E. Rojas & Brayan Rojas, 2010. "Estimations of the natural rate of interest in Colombia," Borradores de Economia 626, Banco de la Republica de Colombia.
    5. Cecilia Frale & Massimiliano Marcellino & Gian Luigi Mazzi & Tommaso Proietti, 2009. "Survey Data as Coicident or Leading Indicators," Economics Working Papers ECO2009/19, European University Institute.
    6. Michael Zhemkov, 2022. "Assessment of Monthly GDP Growth Using Temporal Disaggregation Methods," Russian Journal of Money and Finance, Bank of Russia, vol. 81(2), pages 79-104, June.
    7. K. Triantafyllopoulos, 2007. "Covariance estimation for multivariate conditionally Gaussian dynamic linear models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(8), pages 551-569.
    8. Tommaso Proietti & Alessandro Giovannelli, 2020. "Nowcasting Monthly GDP with Big Data: a Model Averaging Approach," CEIS Research Paper 482, Tor Vergata University, CEIS, revised 12 May 2020.
    9. Bisio, Laura & Moauro, Filippo, 2017. "Temporal disaggregation by dynamic regressions: recent developments in Italian quarterly national accounts," MPRA Paper 80211, University Library of Munich, Germany, revised 14 Jul 2017.
    10. Tommaso Proietti, 2004. "Temporal Disaggregation by State Space Methods: Dynamic Regression Methods Revisited," Econometrics 0411011, University Library of Munich, Germany.
    11. Francisco de Castro & Francisco Martí & Antonio Montesinos & Javier J. Pérez & A. Jesús Sánchez-Fuentes, 2014. "Fiscal policies in Spain: Main stylises facts revisited," Working Papers 1408, Banco de España.
    12. Proietti, Tommaso, 2008. "Estimation of Common Factors under Cross-Sectional and Temporal Aggregation Constraints: Nowcasting Monthly GDP and its Main Components," MPRA Paper 6860, University Library of Munich, Germany.
    13. Simeon Vosen & Torsten Schmidt, 2012. "A monthly consumption indicator for Germany based on Internet search query data," Applied Economics Letters, Taylor & Francis Journals, vol. 19(7), pages 683-687, May.
    14. Víctor Gómez & Félix Aparicio‐Pérez, 2009. "A new state–space methodology to disaggregate multivariate time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(1), pages 97-124, January.
    15. John McDermott & Viv B. Hall, "undated". "A quarterly Post-World War II Real GDP Series for New Zealand," Reserve Bank of New Zealand Discussion Paper Series DP2009/12, Reserve Bank of New Zealand.
    16. Willie Lahari & Alfred A. Haug & Arlene Garces-Ozanne, 2011. "Estimating Quarterly Gdp Data For The South Pacific Island Nations," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 56(01), pages 97-112.
    17. Joan Paredes & Diego J. Pedregal & Javier J. Pérez, 2009. "A quarterly fiscal database for the euro area based on intra-annual fiscal information," Working Papers 0935, Banco de España.
    18. Cecilia Frale, "undated". "Do Surveys Help in Macroeconomic Variables Disaggregation and Estimation?," Working Papers wp2008-2, Department of the Treasury, Ministry of the Economy and of Finance.
    19. Yoshida, Wataru & Hirose, Kei, 2024. "Fast same-step forecast in SUTSE model and its theoretical properties," Computational Statistics & Data Analysis, Elsevier, vol. 190(C).
    20. Guay, Alain & Maurin, Alain, 2015. "Disaggregation methods based on MIDAS regression," Economic Modelling, Elsevier, vol. 50(C), pages 123-129.
    21. Diego J. Pedregal & Javier J. Pérez & Antonio Sánchez Fuentes, 2014. "A Tookit to strengthen Government," Hacienda Pública Española / Review of Public Economics, IEF, vol. 211(4), pages 117-146, December.
    22. Teresa Leal & Diego Pedregal & Javier Pérez, 2011. "Short-term monitoring of the Spanish government balance," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 2(1), pages 97-119, March.
    23. Cecilia Frale & David Veredas, 2008. "A Monthly Volatility Index for the US Economy," Working Papers ECARES 2008-008, ULB -- Universite Libre de Bruxelles.
    24. Yueqing Jia, 2011. "A New Look at China’s Output Fluctuations: Quarterly GDP Estimation with an Unobserved Components Approach," Working Papers 2011-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    25. Cecilia Frale, Serena Teobaldo, Marco Cacciotti, Alessandra Caretta, 2013. "A Quarterly Measure Of Potential Output In The New European Fiscal Framework," 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 181-197, April-Jun.
    26. Sieds, 2013. "Complete Volume LXVII n.2 2013," 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 1-197, April-Jun.
    27. Müller-Kademann Christian, 2015. "Internal Validation of Temporal Disaggregation: A Cloud Chamber Approach," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 235(3), pages 298-319, June.
    28. Pérez, Javier J. & Pedregal, Diego J., 2008. "Should quarterly government finance statistics be used for fiscal surveillane in Europe?," Working Paper Series 937, European Central Bank.
    29. Marcellino, Massimiliano & Proietti, Tommaso & Frale, Cecilia & Mazzi, Gian Luigi, 2008. "A Monthly Indicator of the Euro Area GDP," CEPR Discussion Papers 7007, C.E.P.R. Discussion Papers.
    30. Moauro, Filippo, 2010. "A monthly indicator of employment in the euro area: real time analysis of indirect estimates," MPRA Paper 27797, University Library of Munich, Germany, revised 30 Dec 2010.
    31. Diego J. Pedregal & Javier J. Pérez & A. Jesús Sánchez-Fuentes, 2014. "A toolkit to strengthen government budget surveillance," Working Papers 1416, Banco de España.
    32. Orair, Rodrigo Octávio & Silva, Wesley de Jesus, 2013. "Subnational Government Investment in Brazil: Estimation and Analysis by State Space Models," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 33(1), September.
    33. Weigand Roland & Wanger Susanne & Zapf Ines, 2018. "Factor Structural Time Series Models for Official Statistics with an Application to Hours Worked in Germany," Journal of Official Statistics, Sciendo, vol. 34(1), pages 265-301, March.
    34. Abdullah Tahir & Jameel Ahmed & Waqas Ahmed, 2018. "Robust Quarterization of GDP and Determination of Business Cycle Dates for IGC Partner Countries," SBP Working Paper Series 97, State Bank of Pakistan, Research Department.
    35. Marek Luboš & Hronová Stanislava & Hindis Richard, 2017. "Option for Predicting the Czech Republic’S Foreign Trade Time Series as Components in Gross Domestic Product," Statistics in Transition New Series, Polish Statistical Association, vol. 18(3), pages 481-500, September.
    36. Bu Hyoung Lee, 2022. "Bootstrap Prediction Intervals of Temporal Disaggregation," Stats, MDPI, vol. 5(1), pages 1-13, February.

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 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-ECM: Econometrics (3) 2004-01-25 2011-01-16 2017-07-23
  2. NEP-EEC: European Economics (1) 2011-01-16
  3. NEP-ETS: Econometric Time Series (1) 2004-01-12

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