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Roberto S. Mariano

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. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-263, July.

    Mentioned in:

    1. > Econometrics > Forecasting

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.

    Mentioned in:

    1. A new coincident index of businesscycles based on monthly and quarterly series (Journal of Applied Econometrics 2003) in ReplicationWiki ()
    2. A new coincident index of business cycles based on monthly and quarterly series (Journal of Applied Econometrics 2003) in ReplicationWiki ()
  2. Tanizaki, Hisashi & Mariano, Roberto S, 1994. "Prediction, Filtering and Smoothing in Non-linear and Non-normal Cases Using Monte Carlo Integration," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(2), pages 163-179, April-Jun.

    Mentioned in:

    1. Prediction, filtering and smoothing in non-linear and non-normal cases using Monte Carlo integration (Journal of Applied Econometrics 1994) in ReplicationWiki ()

Working papers

  1. Richard Green & Robert Mariano & Andrey Pavlov & Susan Wachter, 2009. "Misaligned Incentives and Mortgage Lending in Asia," Microeconomics Working Papers 22422, East Asian Bureau of Economic Research.

    Cited by:

    1. Susan M. Wachter, 1975. "Comment on "Housing Policy, Mortgage Policy, and the Federal Housing Administration"," NBER Chapters, in: Measuring and Managing Federal Financial Risk, pages 125-130, National Bureau of Economic Research, Inc.

  2. Hwee Kwan Chow & Peter N. Kriz & Roberto S. Mariano & Augustine H. H. Tan, 2007. "Financial Liberalization and Monetary Policy Cooperation in East Asia1," Finance Working Papers 21916, East Asian Bureau of Economic Research.

    Cited by:

    1. Peter Nicholas Kriz, 2009. "Comment on "Hong Kong and Shanghai:Yesterday, Today and Tomorrow"," NBER Chapters, in: Financial Sector Development in the Pacific Rim, pages 42-50, National Bureau of Economic Research, Inc.
    2. Hwee Kwan Chow, 2010. "Managing Capital Flows: The Case of Singapore," Chapters, in: Masahiro Kawai & Mario B. Lamberte (ed.), Managing Capital Flows, chapter 14, Edward Elgar Publishing.

  3. Celso Brunetti & Roberto S. Mariano & Chiara Scotti & Augustine H. H. Tan, 2007. "Markov switching GARCH models of currency turmoil in southeast Asia," International Finance Discussion Papers 889, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Wajih Khallouli & Rene Sandretto, 2011. "Testing for “Contagion” of the Subprime Crisis on the Middle East And North African Stock Markets: A Markov Switching EGARCH Approach," Working Papers 609, Economic Research Forum, revised 08 Jan 2011.
    2. Walid, Chkili & Chaker, Aloui & Masood, Omar & Fry, John, 2011. "Stock market volatility and exchange rates in emerging countries: A Markov-state switching approach," Emerging Markets Review, Elsevier, vol. 12(3), pages 272-292, September.
    3. Siok Kun Sek, 2023. "A new look at asymmetric effect of oil price changes on inflation: Evidence from Malaysia," Energy & Environment, , vol. 34(5), pages 1524-1547, August.
    4. Houda Rharrabti Zaid, 2015. "Transmission du stress financier de la zone euro aux Pays de l’Europe Centrale et Orientale," EconomiX Working Papers 2015-37, University of Paris Nanterre, EconomiX.
    5. Demiris, Nikolaos & Kypraios, Theodore & Smith, L. Vanessa, 2012. "On the epidemic of financial crises," MPRA Paper 46693, University Library of Munich, Germany.
    6. Aloui, Chaker & Hammoudeh, Shawkat & Hamida, Hela Ben, 2015. "Price discovery and regime shift behavior in the relationship between sharia stocks and sukuk: A two-state Markov switching analysis," Pacific-Basin Finance Journal, Elsevier, vol. 34(C), pages 121-135.
    7. Thomas Chuffart, 2013. "Selection Criteria in Regime Switching Conditional Volatility Models," AMSE Working Papers 1339, Aix-Marseille School of Economics, France, revised 14 Jul 2013.
    8. Cicih Ratnasih, 2018. "Institutional Bureaucracy and Real Sector Movement," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 31-39.
    9. Wajih Khallouli & Modibo René Sandretto, 2010. "Testing for “contagion” of the subprime crisis on the Middle East and North African stock markets : A Markov Switching EGARCH approach," Working Papers 1022, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    10. Parul Bhatia & Priya Gupta, 2020. "Sub-prime Crisis or COVID-19: A Comparative Analysis of Volatility in Indian Banking Sectoral Indices," FIIB Business Review, , vol. 9(4), pages 286-299, December.
    11. Thomas Flavin & Lisa Sheenan, 2015. "The role of U.S. subprime mortgage-backed assets in propagating the crisis:contagion or interdependence?," Economics Department Working Paper Series n260-15.pdf, Department of Economics, National University of Ireland - Maynooth.
    12. Ariannejad , Aghil & Tehrani , Reza, 2021. "Study on Gold as a Hedge or Safe Haven for the Stock Market by a Markov Switching Approach," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 16(3), pages 377-398, September.
    13. Ozdemir, Dicle, 2019. "Sectoral Business Cycle Asymmetries and Regime Shifts: Evidence from Turkey," Asian Journal of Applied Economics, Kasetsart University, Center for Applied Economics Research, vol. 26(2), December.
    14. Thibaut Duprey & Benjamin Klaus, 2017. "How to Predict Financial Stress? An Assessment of Markov Switching Models," Staff Working Papers 17-32, Bank of Canada.
    15. M. Frömmel, 2007. "Volatility Regimes in Central and Eastern European Countries’ Exchange Rates," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/487, Ghent University, Faculty of Economics and Business Administration.
    16. Psaradakis, Zacharias & Sola, Martin, 2024. "Markov-Switching Models with State-Dependent Time-Varying Transition Probabilities," Econometrics and Statistics, Elsevier, vol. 29(C), pages 49-63.
    17. Alberto Humala & Gabriel Rodriguez, 2010. "Foreign exchange intervention and exchange rate volatility in Peru," Applied Economics Letters, Taylor & Francis Journals, vol. 17(15), pages 1485-1491.
    18. Chkili, Walid, 2017. "Is gold a hedge or safe haven for Islamic stock market movements? A Markov switching approach," Journal of Multinational Financial Management, Elsevier, vol. 42, pages 152-163.
    19. Xiaoping Zhan & Tiefeng Ma & Shuangzhe Liu & Kunio Shimizu, 2018. "Markov-Switching Linked Autoregressive Model for Non-continuous Wind Direction Data," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 23(3), pages 410-425, September.
    20. T. G. Saji, 2019. "Can BRICS Form a Currency Union? An Analysis under Markov Regime-Switching Framework," Global Business Review, International Management Institute, vol. 20(1), pages 151-165, February.
    21. Giampiero Gallo & Edoardo Otranto, 2006. "Volatility Transmission Across Markets: A Multi-Chain Markov Switching Model," Econometrics Working Papers Archive wp2006_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    22. Diteboho Xaba & Ntebogang Dinah Moroke & Ishmael Rapoo, 2019. "Modeling Stock Market Returns of BRICS with a Markov-Switching Dynamic Regression Model," Journal of Economics and Behavioral Studies, AMH International, vol. 11(3), pages 10-22.
    23. Khaled Guesmi & Frédéric Teulon & Zied Ftiti, 2013. "Sudden Changes in Volatility in European Stock Markets," Working Papers 2013-32, Department of Research, Ipag Business School.
    24. Kim Liow & Zhiwei Chen & Jingran Liu, 2011. "Multiple Regimes and Volatility Transmission in Securitized Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 42(3), pages 295-328, April.
    25. Martín Solá & Zacharias Psaradakis & Fabio Spagnolo & Nicola Spagnolo, 2010. "Some Cautionary Results Concerning Markov-Switching Models with Time-Varying Transition Probabilities," Department of Economics Working Papers 2010-12, Universidad Torcuato Di Tella.
    26. Wang, Lu & Wu, Jiangbin & Cao, Yang & Hong, Yanran, 2022. "Forecasting renewable energy stock volatility using short and long-term Markov switching GARCH-MIDAS models: Either, neither or both?," Energy Economics, Elsevier, vol. 111(C).
    27. Ivana Marjanoviæ & Milan Markoviæ, 2019. "Determinants of currency crises in the Republic of Serbia," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 37(1), pages 191-212.

  4. Peter F. Christoffersen & Francis X. Diebold & Roberto S. Mariano & Anthony S. Tay & Yiu Kuen Tse, 2006. "Direction-of-Change Forecasts Based on Conditional Variance, Skewness and Kurtosis Dynamics : International Evidence," Finance Working Papers 22075, East Asian Bureau of Economic Research.

    Cited by:

    1. Stanislav Anatolyev & Nikolay Gospodinov, 2007. "Modeling Financial Return Dynamics by Decomposition," Working Papers w0095, New Economic School (NES).
    2. Papailias, Fotis & Liu, Jiadong & Thomakos, Dimitrios D., 2019. "Return Signal Momentum," QBS Working Paper Series 2019/04, Queen's University Belfast, Queen's Business School.
    3. Stelios Bekiros & Dimitris Georgoutsos, 2008. "Non-linear dynamics in financial asset returns: the predictive power of the CBOE volatility index," The European Journal of Finance, Taylor & Francis Journals, vol. 14(5), pages 397-408.
    4. Papailias, Fotis & Liu, Jiadong & Thomakos, Dimitrios D., 2021. "Return signal momentum," Journal of Banking & Finance, Elsevier, vol. 124(C).
    5. M. Bigeco & E. Grosso & E. Otranto, 2008. "Recognizing and Forecasting the Sign of Financial Local Trends using Hidden Markov Models," Working Paper CRENoS 200803, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    6. Stanislav Anatolyev & Natalia Kryzhanovskaya, 2009. "Directional Prediction of Returns under Asymmetric Loss: Direct and Indirect Approaches," Working Papers w0136, Center for Economic and Financial Research (CEFIR).
    7. Luis H. R. Alvarez E. & Paavo Salminen, 2017. "Timing in the presence of directional predictability: optimal stopping of skew Brownian motion," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 86(2), pages 377-400, October.

  5. Winston T.H. Koh & Roberto S. Mariano & Andrey Pavlovb & Sock Yong Phang & Augustine H. H. Tan & Susan M. Wachter, 2006. "Underpriced Default Spread Exacerbates Market Crashes," Finance Working Papers 22458, East Asian Bureau of Economic Research.

    Cited by:

    1. Richard K. Green & Roberto S. Mariano & Andrey D. Pavlov & Susan M. Wachter, 2007. "Misaligned Incentives and Mortgage Lending in Asia," Working Paper 9099, USC Lusk Center for Real Estate.
    2. Andrey Pavlov & Susan Wachter, 2009. "Mortgage Put Options and Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 38(1), pages 89-103, January.

  6. Roberto Mariano & Delano Villanueva, 2005. "Sustainable External Debt Levels : Estimates for Selected Asian Countries," Macroeconomics Working Papers 22468, East Asian Bureau of Economic Research.

    Cited by:

    1. Delano S Villanueva & Roberto S Mariano & Diwa C Guinigundo & Abbas Mirakhor, 2023. "External Debt, Adjustment, and Growth," World Scientific Book Chapters, in: Economic Adjustment and Growth Theory and Practice, chapter 9, pages 222-249, World Scientific Publishing Co. Pte. Ltd..

  7. Roberto S. Mariano & Delano Villanueva, 2005. "External Debt, Adjustment, and Growth," Working Papers 13-2006, Singapore Management University, School of Economics, revised May 2006.

    Cited by:

    1. Safia Shabbir, 2013. "Does External Debt Affect Economic Growth: Evidence from Developing Countries," SBP Working Paper Series 63, State Bank of Pakistan, Research Department.
    2. Siti Daud & Jan Podivinsky, 2011. "Debt–Growth Nexus: A Spatial Econometrics Approach for Developing Countries," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 18(1), pages 1-15, September.
    3. Shodiya Olayinka Abideen & Sanyaolu Wasiu Abiodun & Ojenike Joseph Olushola & Ogunmefun Gbadebo Tirimisiyu, 2019. "Shareholder Wealth Maximization and Investment Decisions of Nigerian Food and Beverage Companies," Acta Universitatis Sapientiae, Economics and Business, Sciendo, vol. 7(1), pages 47-63, December.
    4. Delano S Villanueva & Roberto S Mariano & Diwa C Guinigundo & Abbas Mirakhor, 2023. "Finance and Endogenous Growth," World Scientific Book Chapters, in: Economic Adjustment and Growth Theory and Practice, chapter 5, pages 96-118, World Scientific Publishing Co. Pte. Ltd..
    5. Siti Nurazira Mohd Daud & Jan M. Podivinsky, 2012. "Revisiting the role of external debt in economic growth of developing countries," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 13(5), pages 968-993, June.
    6. Omotor, Douglason G., 2019. "A Thrifty North and An Impecunious South: Nigeria's External Debt and the Tyranny of Political Economy," MPRA Paper 115292, University Library of Munich, Germany, revised 12 Oct 2019.
    7. Doğan, İbrahim & Bilgili, Faik, 2014. "The non-linear impact of high and growing government external debt on economic growth: A Markov Regime-switching approach," Economic Modelling, Elsevier, vol. 39(C), pages 213-220.
    8. Stylianou Tasos, 2012. "Does Government Debt Promote Economic Growth? An Empirical Analysis with Structural Breaks for the Economy of China," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 15(45), pages 229-248, December.

  8. Yasutomo Murasawa & Roberto S. Mariano, 2004. "Constructing a Coincident Index of Business Cycles Without Assuming a One-Factor Model," Econometric Society 2004 Far Eastern Meetings 710, Econometric Society.

    Cited by:

    1. Cecilia Frale & David Veredas, 2008. "A Monthly Volatility Index for the US Economy," Working Papers ECARES 2008-008, ULB -- Universite Libre de Bruxelles.
    2. Paul Viefers, 2011. "Bayesian Inference for the Mixed-Frequency VAR Model," Discussion Papers of DIW Berlin 1172, DIW Berlin, German Institute for Economic Research.
    3. 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.

  9. Celso Brunetti & Roberto S. Mariano & Chiara Scotti & Augustine H. H. Tan, 2003. "Markov Switching Garch Models of Currency Crises in Southeast Asia," PIER Working Paper Archive 03-008, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

    Cited by:

    1. Giampiero Gallo & Edoardo Otranto, 2007. "Volatility Spillovers, Interdependence and Comovements: A Markov Switching Approach," Econometrics Working Papers Archive wp2007_11, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    2. Khalifa, Ahmed A.A. & Hammoudeh, Shawkat & Otranto, Edoardo, 2014. "Patterns of volatility transmissions within regime switching across GCC and global markets," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 512-524.
    3. Alberto Humala & Gabriel Rodriguez, 2010. "Foreign exchange intervention and exchange rate volatility in Peru," Applied Economics Letters, Taylor & Francis Journals, vol. 17(15), pages 1485-1491.
    4. Giampiero Gallo & Edoardo Otranto, 2006. "Volatility Transmission Across Markets: A Multi-Chain Markov Switching Model," Econometrics Working Papers Archive wp2006_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    5. Kim Liow & Zhiwei Chen & Jingran Liu, 2011. "Multiple Regimes and Volatility Transmission in Securitized Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 42(3), pages 295-328, April.
    6. Richard D. F. Harris & Murat Mazibas, 2022. "A component Markov regime‐switching autoregressive conditional range model," Bulletin of Economic Research, Wiley Blackwell, vol. 74(2), pages 650-683, April.
    7. Hu Liang & Shin Yongcheol, 2008. "Optimal Test for Markov Switching GARCH Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(3), pages 1-27, September.

  10. Fangxiong Gong & Roberto S. Mariano, 1997. "Testing under non-standard conditions in frequency domain: with applications to Markov regime-switching models of exchange rates and federal funds rate," Staff Reports 23, Federal Reserve Bank of New York.

    Cited by:

    1. Yin-Wong Cheung & Ulf G. Erlandsson, 2004. "Exchange Rates and Markov Switching Dynamics," CESifo Working Paper Series 1348, CESifo.
    2. Lanouar Charfeddine & Dominique Guegan, 2008. "Is it possible to discriminate between different switching regressions models? An empirical investigation," PSE-Ecole d'économie de Paris (Postprint) halshs-00368358, HAL.
    3. Lanouar Charfeddine & Dominique Guegan, 2008. "Is it possible to discriminate between different switching regressions models? An empirical investigation," Post-Print halshs-00368358, HAL.
    4. Dewachter, Hans, 2001. "Can Markov switching models replicate chartist profits in the foreign exchange market?," Journal of International Money and Finance, Elsevier, vol. 20(1), pages 25-41, February.

  11. Francis X. Diebold & Roberto S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.

    Cited by:

    1. De Leon, Marycruz & Fullerton, Thomas M., Jr. & Kelley, Brian W., 2009. "Tolls, Exchange Rates, and Borderplex International Bridge Traffic," MPRA Paper 19861, University Library of Munich, Germany.
    2. Driffill, John & Sola, Martin & Kenc, Turalay & Spagnolo, Fabio, 2004. "On Model Selection and Markov Switching: A Empirical Examination of Term Structure Models with Regime Shifts," CEPR Discussion Papers 4165, C.E.P.R. Discussion Papers.
    3. Frédérick Demers & Annie De Champlain, 2005. "Forecasting Core Inflation in Canada: Should We Forecast the Aggregate or the Components?," Staff Working Papers 05-44, Bank of Canada.
    4. Corielli, Francesco & Marcellino, Massimiliano, 2006. "Factor based index tracking," Journal of Banking & Finance, Elsevier, vol. 30(8), pages 2215-2233, August.
    5. Wang, Yudong & Hao, Xianfeng, 2023. "Forecasting the real prices of crude oil: What is the role of parameter instability?," Energy Economics, Elsevier, vol. 117(C).
    6. Özen, Kadir & Yıldırım, Dilem, 2021. "Application of bagging in day-ahead electricity price forecasting and factor augmentation," Energy Economics, Elsevier, vol. 103(C).
    7. Christian Hutter & Enzo Weber, 2015. "Constructing a new leading indicator for unemployment from a survey among German employment agencies," Applied Economics, Taylor & Francis Journals, vol. 47(33), pages 3540-3558, July.
    8. Norman R. Swanson & Nii Ayi Armah, 2011. "Predictive Inference Under Model Misspecification with an Application to Assessing the Marginal Predictive Content of Money for Output," Departmental Working Papers 201103, Rutgers University, Department of Economics.
    9. Jose A. Lopez & Christian Walter, 2000. "Is implied correlation worth calculating? Evidence from foreign exchange options and historical data," Working Paper Series 2000-02, Federal Reserve Bank of San Francisco.
    10. Arratibel, Olga & Leiner-Killinger, Nadine & Kamps, Christophe, 2009. "Inflation forecasting in the new EU Member States," Working Paper Series 1015, European Central Bank.
    11. Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019. "From fixed-event to fixed-horizon density forecasts: Obtaining measures of multi-horizon uncertainty from survey density forecasts," Economics Working Papers 1689, Department of Economics and Business, Universitat Pompeu Fabra.
    12. Adam J. Check & Anna K Nolan & Tyler C. Schipper, 2019. "Forecasting GDP Growth using Disaggregated GDP Revisions," Economics Bulletin, AccessEcon, vol. 39(4), pages 2580-2588.
    13. Lucio Sarno & Giorgio Valente, 2009. "Exchange Rates and Fundamentals: Footloose or Evolving Relationship?," Journal of the European Economic Association, MIT Press, vol. 7(4), pages 786-830, June.
    14. Chen, Shiu-Sheng, 2013. "Forecasting Crude Oil Price Movements with Oil-Sensitive Stocks," MPRA Paper 49240, University Library of Munich, Germany.
    15. Jean-Armand Gnagne & Kevin Moran, 2020. "Forecasting Bank Failures in a Data-Rich Environment," Working Papers 20-13, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    16. Peresetsky, Anatoly & Yakubov, Ruslan, 2015. "Autocorrelation in an unobservable global trend: Does it help to forecast market returns?," MPRA Paper 64579, University Library of Munich, Germany.
    17. Kelly Burns & Imad Moosa, 2017. "Demystifying the Meese–Rogoff puzzle: structural breaks or measures of forecasting accuracy?," Applied Economics, Taylor & Francis Journals, vol. 49(48), pages 4897-4910, October.
    18. Galvão, Ana Beatriz & Giraitis, Liudas & Kapetanios, George & Petrova, Katerina, 2016. "A time varying DSGE model with financial frictions," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 690-716.
    19. Gong, Xu & Lin, Boqiang, 2018. "The incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market," Energy Economics, Elsevier, vol. 74(C), pages 370-386.
    20. Rossi, José Luiz Júnior, 2013. "Liquidity and Exchange Rates," Insper Working Papers wpe_325, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    21. Claudio, João C. & Heinisch, Katja & Holtemöller, Oliver, 2019. "Nowcasting East German GDP growth: A MIDAS approach," IWH Discussion Papers 24/2019, Halle Institute for Economic Research (IWH).
    22. Antonio Rubia & Trino-Manuel Ñíguez, 2006. "Forecasting the conditional covariance matrix of a portfolio under long-run temporal dependence," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(6), pages 439-458.
    23. Grigory Franguridi, 2014. "Higher order conditional moment dynamics and forecasting value-at-risk (in Russian)," Quantile, Quantile, issue 12, pages 69-82, February.
    24. McAleer, M.J. & Jiménez-Martín, J.A. & Pérez-Amaral, T., 2010. "GFC-Robust Risk Management Strategies under the Basel Accord," Econometric Institute Research Papers EI 2010-59, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    25. Robert Lehmann & Antje Weyh, 2016. "Forecasting Employment in Europe: Are Survey Results Helpful?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 81-117, September.
    26. Alastair Cunningham & Jana Eklund & Christopher Jeffery & George Kapetanios & Vincent Labhard, 2007. "A state space approach to extracting the signal from uncertain data," Bank of England working papers 336, Bank of England.
    27. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2022. "Machine Learning Time Series Regressions With an Application to Nowcasting," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1094-1106, June.
    28. Athanasopoulos, George & Guillen, Osmani Teixeira Carvalho & Issler, João Victor & Vahid, Farshid, 2011. "Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 713, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    29. Leal, Teresa & Pérez, Javier J. & Tujula, Mika & Vidal, Jean-Pierre, 2007. "Fiscal forecasting: lessons from the literature and challenges," Working Paper Series 843, European Central Bank.
    30. Robert Lehmann, 2016. "Economic Growth and Business Cycle Forecasting at the Regional Level," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 65.
    31. 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.
    32. Cheng, Hung-Wen & Chang, Li-Han & Lo, Chien-Ling & Tsai, Jeffrey Tzuhao, 2023. "Empirical performance of component GARCH models in pricing VIX term structure and VIX futures," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 122-142.
    33. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    34. Amélie Charles & Olivier Darné & Jae H. Kim, 2022. "Stock return predictability: Evaluation based on interval forecasts," Bulletin of Economic Research, Wiley Blackwell, vol. 74(2), pages 363-385, April.
    35. Yuchen Zhang & Shigeyuki Hamori, 2020. "The Predictability of the Exchange Rate When Combining Machine Learning and Fundamental Models," JRFM, MDPI, vol. 13(3), pages 1-16, March.
    36. Hao Chen & Qiulan Wan & Yurong Wang, 2014. "Refined Diebold-Mariano Test Methods for the Evaluation of Wind Power Forecasting Models," Energies, MDPI, vol. 7(7), pages 1-14, July.
    37. Leonardo Nogueira Ferreira & Silvia Miranda-Agrippino & Giovanni Ricco, 2023. "Bayesian Local Projections," Working Papers Series 581, Central Bank of Brazil, Research Department.
    38. Thomas A. Knetsch, 2004. "Evaluating the German Inventory Cycle – Using Data from the Ifo Business Survey," CESifo Working Paper Series 1202, CESifo.
    39. Goodness C. Aye & Stephen M. Miller & Rangan Gupta & Mehmet Balcilar, 2013. "Forecasting the US Real Private Residential Fixed Investment Using Large Number of Predictors," Working Papers 201348, University of Pretoria, Department of Economics.
    40. D'Agostino, Antonello & McQuinn, Kieran & Whelan, Karl, 2010. "Are Some Forecasters Really Better Than Others?," Research Technical Papers 5/RT/10, Central Bank of Ireland.
    41. Adam Clements & Yin Liao, 2014. "The role in index jumps and cojumps in forecasting stock index volatility: Evidence from the Dow Jones index," NCER Working Paper Series 101, National Centre for Econometric Research.
    42. Lu, Xin & Qiu, Jing & Lei, Gang & Zhu, Jianguo, 2022. "Scenarios modelling for forecasting day-ahead electricity prices: Case studies in Australia," Applied Energy, Elsevier, vol. 308(C).
    43. Granziera, Eleonora & Sekhposyan, Tatevik, 2019. "Predicting relative forecasting performance: An empirical investigation," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1636-1657.
    44. Theologos Dergiades & Apostolos Dasilas, 2010. "Modelling and forecasting mobile telecommunication services: the case of Greece," Applied Economics Letters, Taylor & Francis Journals, vol. 17(18), pages 1823-1828.
    45. Güneş Kamber & James Morley & Benjamin Wong, 2017. "Intuitive and Reliable Estimates of the Output Gap from a Beveridge-Nelson Filter," Reserve Bank of New Zealand Discussion Paper Series DP2017/01, Reserve Bank of New Zealand.
    46. Fildes, Robert & Stekler, Herman, 2002. "The state of macroeconomic forecasting," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 435-468, December.
    47. Jichang Dong & Wei Dai & Ying Liu & Lean Yu & Jie Wang, 2019. "Forecasting Chinese Stock Market Prices using Baidu Search Index with a Learning-Based Data Collection Method," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(05), pages 1605-1629, September.
    48. Kim, Jae H. & Wong, Kevin & Athanasopoulos, George & Liu, Shen, 2011. "Beyond point forecasting: Evaluation of alternative prediction intervals for tourist arrivals," International Journal of Forecasting, Elsevier, vol. 27(3), pages 887-901, July.
    49. Gaglianone, Wagner Piazza & Guillén, Osmani Teixeira de Carvalho & Figueiredo, Francisco Marcos Rodrigues, 2018. "Estimating inflation persistence by quantile autoregression with quantile-specific unit roots," Economic Modelling, Elsevier, vol. 73(C), pages 407-430.
    50. Olivier Bonroy & Jean-Philippe Gervais & Bruno Larue, 2007. "Are exports a monotonic function of exchange rate volatility? Evidence from disaggregated pork exports," Canadian Journal of Economics, Canadian Economics Association, vol. 40(1), pages 127-154, February.
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    4261. Selma Toker & Nimet Özbay & Kristofer Månsson, 2022. "Mixed data sampling regression: Parameter selection of smoothed least squares estimator," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 718-751, July.
    4262. Jonathan Hambur & Lynne Cockerell & Christopher Potter & Penelope Smith & Michelle Wright, 2015. "Modelling the Australian Dollar," RBA Research Discussion Papers rdp2015-12, Reserve Bank of Australia.
    4263. Kosei Fukuda, 2011. "Cointegration rank switching model: an application to forecasting interest rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(5), pages 509-522, August.
    4264. Ciarreta, Aitor & Martinez, Blanca & Nasirov, Shahriyar, 2023. "Forecasting electricity prices using bid data," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1253-1271.
    4265. Alizadeh, Amir H. & Thanopoulou, Helen & Yip, Tsz Leung, 2017. "Investors’ behavior and dynamics of ship prices: A heterogeneous agent model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 98-114.
    4266. Elizaveta Golovanova & Andrey Zubarev, 2021. "Forecasting Aggregate Retail Sales with Google Trends," Russian Journal of Money and Finance, Bank of Russia, vol. 80(4), pages 50-73, December.
    4267. Oscar Claveria & Enric Monte & Salvador Torra, 2021. ""Nowcasting and forecasting GDP growth with machine-learning sentiment indicators"," IREA Working Papers 202103, University of Barcelona, Research Institute of Applied Economics, revised Feb 2021.
    4268. Slim, Skander, 2016. "On the source of stochastic volatility: Evidence from CAC40 index options during the subprime crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 63-76.
    4269. Loïc Maréchal, 2021. "Do economic variables forecast commodity futures volatility?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(11), pages 1735-1774, November.
    4270. Anders Wilhelmsson, 2006. "Garch forecasting performance under different distribution assumptions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(8), pages 561-578.
    4271. Arai, Natsuki, 2020. "Investigating the inefficiency of the CBO’s budgetary projections," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1290-1300.
    4272. Lee, Hsiang-Tai, 2010. "Regime switching correlation hedging," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2728-2741, November.
    4273. Piotr Fryzlewicz & Thorsten Rheinlander & Marcela Valenzuela & Ilknur Zer, 2014. "Relative Liquidity and Future Volatility," Finance and Economics Discussion Series 2014-45, Board of Governors of the Federal Reserve System (U.S.).
    4274. Jacob Boudoukh & Matthew Richardson & Robert Whitelaw, 2005. "The Information in Long-Maturity Forward Rates: Implications for Exchange Rates and the Forward Premium Anomaly," NBER Working Papers 11840, National Bureau of Economic Research, Inc.
    4275. Hao Wu & Haiming Long & Yue Wang & Yanqi Wang, 2021. "Stock index forecasting: A new fuzzy time series forecasting method," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 653-666, July.
    4276. Byron Botha & Tim Olds & Geordie Reid & Daan Steenkamp & Rossouw van Jaarsveld, 2021. "Nowcasting South African gross domestic product using a suite of statistical models," South African Journal of Economics, Economic Society of South Africa, vol. 89(4), pages 526-554, December.
    4277. Vogt Gerit, 2007. "Analyse der Prognoseeigenschaften von ifo-Konjunkturindikatoren unter Echtzeitbedingungen / The Forecasting Performance of ifo-indicators Under Real-time Conditions," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 227(1), pages 87-101, February.
    4278. William J. Procasky & Anwen Yin, 2022. "Forecasting high‐yield equity and CDS index returns: Does observed cross‐market informational flow have predictive power?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(8), pages 1466-1490, August.
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    4283. Liu, Li & Wan, Jieqiu, 2012. "A study of Shanghai fuel oil futures price volatility based on high frequency data: Long-range dependence, modeling and forecasting," Economic Modelling, Elsevier, vol. 29(6), pages 2245-2253.
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    4289. Mihaela Simionescu, 2015. "The Improvement of Unemployment Rate Predictions Accuracy," Prague Economic Papers, Prague University of Economics and Business, vol. 2015(3), pages 274-286.
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  12. Francis X. Diebold & Roberto S. Mariano, 1991. "Comparing predictive accuracy I: an asymptotic test," Discussion Paper / Institute for Empirical Macroeconomics 52, Federal Reserve Bank of Minneapolis.

    Cited by:

    1. Kenneth D. West & Dongchul Cho, 1994. "The Predictive Ability of Several Models of Exchange Rate Volatility," NBER Technical Working Papers 0152, National Bureau of Economic Research, Inc.
    2. Chan Guk Huh, 1998. "Forecasting industrial production using models with business cycle asymmetry," Economic Review, Federal Reserve Bank of San Francisco, pages 29-41.
    3. Francis X. Diebold, 2012. "Comparing Predictive Accuracy, Twenty Years Later: A Personal Perspective on the Use and Abuse of Diebold-Mariano Tests," PIER Working Paper Archive 12-035, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    4. Tazwell S. Rowe & Roy H. Webb, 1995. "An index of leading indicators for inflation," Economic Quarterly, Federal Reserve Bank of Richmond, issue Spr, pages 75-96.
    5. Meyer-Gohde, Alexander & Shabalina, Ekaterina, 2022. "Estimation and forecasting using mixed-frequency DSGE models," IMFS Working Paper Series 175, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    6. Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals: Google Trends Meets Mixed Frequency Data," MPRA Paper 90205, University Library of Munich, Germany.
    7. Lin, Wen-Ling, 1995. "Market closure and predictability of intradaily stock returns in the United States and Japan," Journal of Empirical Finance, Elsevier, vol. 2(1), pages 19-44, March.
    8. Gerdesmeier Dieter & Roffia Barbara & Reimers Hans-Eggert, 2017. "Forecasting Euro Area Inflation Using Single-Equation and Multivariate VAR–Models," Folia Oeconomica Stetinensia, Sciendo, vol. 17(2), pages 19-34, December.

  13. Mariano, Roberto S. & Constantino, Winnie, 1990. "The PIDS-NEDA Annual Macroeconometric Model, Version 1989: A Summary," Working Papers WP 1990-13, Philippine Institute for Development Studies.

    Cited by:

    1. Diokno, Benjamin E., 1992. "Philippine Macroeconomic Policies Affecting Households," Working Papers WP 1992-17, Philippine Institute for Development Studies.

Articles

  1. Roberto S. Mariano & Suleyman Ozmucur, 2021. "Predictive Performance of Mixed-Frequency Nowcasting and Forecasting Models (with Application to Philippine Inflation and GDP Growth)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 383-400, December.

    Cited by:

    1. Yong Bao & Aman Ullah, 2021. "The Special Issue in Honor of Anirudh Lal Nagar: An Introduction," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 1-8, December.

  2. Mariano, Roberto S. & Preve, Daniel, 2012. "Statistical tests for multiple forecast comparison," Journal of Econometrics, Elsevier, vol. 169(1), pages 123-130.

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    1. Kuang-Liang Chang & Charles Ka Yui Leung, 2021. "How did the asset markets change after the Global Financial Crisis?," GRU Working Paper Series GRU_2021_004, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    2. Robinson Kruse & Christian Leschinski & Michael Will, 2016. "Comparing Predictive Accuracy under Long Memory - With an Application to Volatility Forecasting," CREATES Research Papers 2016-17, Department of Economics and Business Economics, Aarhus University.
    3. Roberto S. Mariano & Suleyman Ozmucur, 2021. "Predictive Performance of Mixed-Frequency Nowcasting and Forecasting Models (with Application to Philippine Inflation and GDP Growth)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 383-400, December.
    4. Daniel Preve, "undated". "Linear programming-based estimators in nonnegative autoregression," GRU Working Paper Series GRU_2016_001, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    5. Wilmer Osvaldo Martínez-Rivera & Manuel Dario Hernández-Bejarano & Juan Manuel Julio-Román, 2014. "On Forecast Evaluation," Borradores de Economia 11604, Banco de la Republica.
    6. Drachal, Krzysztof, 2019. "Forecasting prices of selected metals with Bayesian data-rich models," Resources Policy, Elsevier, vol. 64(C).
    7. Nathan Goldstein & Ben‐Zion Zilberfarb, 2023. "The closer we get, the better we are?," Economic Inquiry, Western Economic Association International, vol. 61(2), pages 364-376, April.
    8. Marian Vavra, 2015. "On a Bootstrap Test for Forecast Evaluations," Working and Discussion Papers WP 5/2015, Research Department, National Bank of Slovakia.
    9. Kuang-Liang Chang & Nan-Kuang Chen & Charles Ka Yui Leung, 2016. "Losing Track of the Asset Markets: the Case of Housing and Stock," International Real Estate Review, Global Social Science Institute, vol. 19(4), pages 435-492.
    10. Håvard Hungnes, 2020. "Equal predictability test for multi-step-ahead system forecasts invariant to linear transformations," Discussion Papers 931, Statistics Norway, Research Department.
    11. Nuri Hacıevliyagil & Krzysztof Drachal & Ibrahim Halil Eksi, 2022. "Predicting House Prices Using DMA Method: Evidence from Turkey," Economies, MDPI, vol. 10(3), pages 1-27, March.
    12. Krzysztof Drachal, 2019. "Analysis of Agricultural Commodities Prices with New Bayesian Model Combination Schemes," Sustainability, MDPI, vol. 11(19), pages 1-23, September.
    13. Cheung, Yin-Wong & Hui, Cho-Hoi & Tsang, Andrew, 2018. "The RMB central parity formation mechanism: August 2015 to December 2016," Journal of International Money and Finance, Elsevier, vol. 86(C), pages 223-243.
    14. Drachal, Krzysztof, 2021. "Forecasting crude oil real prices with averaging time-varying VAR models," Resources Policy, Elsevier, vol. 74(C).
    15. Drachal, Krzysztof, 2021. "Forecasting selected energy commodities prices with Bayesian dynamic finite mixtures," Energy Economics, Elsevier, vol. 99(C).
    16. E. Otranto, 2024. "A Vector Multiplicative Error Model with Spillover Effects and Co-movements," Working Paper CRENoS 202404, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    17. Guzman, Giselle C., 2010. "An inflation expectations horserace," MPRA Paper 36511, University Library of Munich, Germany.
    18. Kwan, Yum K. & Leung, Charles Ka Yui & Dong, Jinyue, 2015. "Comparing consumption-based asset pricing models: The case of an Asian city," Journal of Housing Economics, Elsevier, vol. 28(C), pages 18-41.
    19. Xia, Yufei & Sang, Chong & He, Lingyun & Wang, Ziyao, 2023. "The role of uncertainty index in forecasting volatility of Bitcoin: Fresh evidence from GARCH-MIDAS approach," Finance Research Letters, Elsevier, vol. 52(C).
    20. Fawad, Muhammad & Yan, Ting & Chen, Lu & Huang, Kangdi & Singh, Vijay P., 2019. "Multiparameter probability distributions for at-site frequency analysis of annual maximum wind speed with L-Moments for parameter estimation," Energy, Elsevier, vol. 181(C), pages 724-737.
    21. 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.
    22. Rehman, Mobeen Ur & Owusu Junior, Peterson & Ahmad, Nasir & Vo, Xuan Vinh, 2022. "Time-varying risk analysis for commodity futures," Resources Policy, Elsevier, vol. 78(C).
    23. Daniel Borup & Martin Thyrsgaard, 2017. "Statistical tests for equal predictive ability across multiple forecasting methods," CREATES Research Papers 2017-19, Department of Economics and Business Economics, Aarhus University.
    24. Owusu Junior, Peterson & Alagidede, Imhotep, 2020. "Risks in emerging markets equities: Time-varying versus spatial risk analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    25. Daniel Borup & Jonas N. Eriksen & Mads M. Kjær & Martin Thyrsgaard, 2020. "Predicting bond return predictability," CREATES Research Papers 2020-09, Department of Economics and Business Economics, Aarhus University.
    26. Guzman, Giselle C., 2011. "The case for higher frequency inflation expectations," MPRA Paper 36656, University Library of Munich, Germany.

  3. Roberto S. Mariano & Yasutomo Murasawa, 2010. "A Coincident Index, Common Factors, and Monthly Real GDP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(1), pages 27-46, February.

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    3. Marcellino, Massimiliano & Sivec, Vasja, 2016. "Monetary, fiscal and oil shocks: Evidence based on mixed frequency structural FAVARs," Journal of Econometrics, Elsevier, vol. 193(2), pages 335-348.
    4. Hager Ben Romdhane, 2021. "Nowcasting in Tunisia using large datasets and mixed frequency models," IHEID Working Papers 11-2021, Economics Section, The Graduate Institute of International Studies.
    5. Pablo Aguilar & Corinna Ghirelli & Matías Pacce & Alberto Urtasun, 2020. "Can news help measure economic sentiment? An application in COVID-19 times," Working Papers 2027, Banco de España.
    6. Markus Heinrich & Magnus Reif, 2018. "Forecasting using mixed-frequency VARs with time-varying parameters," ifo Working Paper Series 273, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    7. Scott Brave & R. Andrew Butters & Alejandro Justiniano, 2016. "Forecasting Economic Activity with Mixed Frequency Bayesian VARs," Working Paper Series WP-2016-5, Federal Reserve Bank of Chicago.
    8. Koop, Gary & McIntyre, Stuart & Mitchell, James & Poon, Aubrey, 2019. "Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017," EMF Research Papers 20, Economic Modelling and Forecasting Group.
    9. Fady Barsoum, 2015. "Point and Density Forecasts Using an Unrestricted Mixed-Frequency VAR Model," Working Paper Series of the Department of Economics, University of Konstanz 2015-19, Department of Economics, University of Konstanz.
    10. Robert Lehmann & Ida Wikman, 2022. "Quarterly GDP Estimates for the German States," ifo Working Paper Series 370, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    11. 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.
    12. Paul Viefers & Ferdinand Fichtner & Simon Junker & Maximilian Podstawski, 2014. "Filtering German Economic Conditions from a Large Dataset: The New DIW Economic Barometer," Discussion Papers of DIW Berlin 1414, DIW Berlin, German Institute for Economic Research.
    13. Brave, Scott A. & Butters, R. Andrew & Justiniano, Alejandro, 2019. "Forecasting economic activity with mixed frequency BVARs," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1692-1707.
    14. Tesi Aliaj & Milos Ciganovic & Massimiliano Tancioni, 2023. "Nowcasting inflation with Lasso‐regularized vector autoregressions and mixed frequency data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 464-480, April.
    15. Messner, Wolfgang, 2023. "The contingency impact of culture on health security capacities for pandemic preparedness: A moderated Bayesian inference analysis," Journal of International Management, Elsevier, vol. 29(5).
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    18. Roberto S. Mariano & Suleyman Ozmucur, 2021. "Predictive Performance of Mixed-Frequency Nowcasting and Forecasting Models (with Application to Philippine Inflation and GDP Growth)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 383-400, December.
    19. Dufrénot, Gilles & Rhouzlane, Meryem & Vaccaro-Grange, Etienne, 2022. "Potential growth and natural yield curve in Japan," Journal of International Money and Finance, Elsevier, vol. 124(C).
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    22. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    23. 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.
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    25. Lenza, Michele & Cimadomo, Jacopo & Giannone, Domenico & Monti, Francesca & Sokol, Andrej, 2021. "Nowcasting with Large Bayesian Vector Autoregressions," CEPR Discussion Papers 15854, C.E.P.R. Discussion Papers.
    26. 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).
    27. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    28. Qian, Hang, 2012. "A Flexible State Space Model and its Applications," MPRA Paper 38455, University Library of Munich, Germany.
    29. Ghysels, Eric & Miller, J. Isaac, 2013. "Testing for Cointegration with Temporally Aggregated and Mixed-frequency Time Series," CEPR Discussion Papers 9654, C.E.P.R. Discussion Papers.
    30. Ankargren Sebastian & Unosson Måns & Yang Yukai, 2020. "A Flexible Mixed-Frequency Vector Autoregression with a Steady-State Prior," Journal of Time Series Econometrics, De Gruyter, vol. 12(2), pages 1-41, July.
    31. Schumacher, Christian & Marcellino, Massimiliano & Kuzin, Vladimir, 2009. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the Euro Area," CEPR Discussion Papers 7445, C.E.P.R. Discussion Papers.
    32. Gani Ramadani & Magdalena Petrovska & Vesna Bucevska, 2021. "Evaluation of mixed frequency approaches for tracking near-term economic developments in North Macedonia," Working Papers 2021-03, National Bank of the Republic of North Macedonia.
    33. Löchel, H. & Packham, N. & Walisch, F., 2016. "Determinants of the onshore and offshore Chinese government yield curves," Pacific-Basin Finance Journal, Elsevier, vol. 36(C), pages 77-93.
    34. Qiu, Yue, 2020. "Forecasting the Consumer Confidence Index with tree-based MIDAS regressions," Economic Modelling, Elsevier, vol. 91(C), pages 247-256.
    35. Heinisch Katja & Scheufele Rolf, 2019. "Should Forecasters Use Real-Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, De Gruyter, vol. 20(4), pages 170-200, December.
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    37. Dr. Alain Galli, 2017. "Which indicators matter? Analyzing the Swiss business cycle using a large-scale mixed-frequency dynamic factor model," Working Papers 2017-08, Swiss National Bank.
    38. Yasutomo Murasawa, 2014. "Measuring the natural rates, gaps, and deviation cycles," Empirical Economics, Springer, vol. 47(2), pages 495-522, September.
    39. Yasutomo Murasawa, 2016. "The Beveridge–Nelson decomposition of mixed-frequency series," Empirical Economics, Springer, vol. 51(4), pages 1415-1441, December.
    40. Foroni, Claudia & Marcellino, Massimiliano & Stevanović, Dalibor, 2018. "Mixed frequency models with MA components," Discussion Papers 02/2018, Deutsche Bundesbank.
    41. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2014. "Density forecasts with MIDAS models," Working Paper 2014/10, Norges Bank.
    42. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2020. "Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(2), pages 176-197, March.
    43. Ramadani Gani & Petrovska Magdalena & Bucevska Vesna, 2021. "Evaluation of Mixed Frequency Approaches for Tracking Near-Term Economic Developments in North Macedonia," South East European Journal of Economics and Business, Sciendo, vol. 16(2), pages 43-52, December.
    44. Luca Barbaglia & Lorenzo Frattarolo & Niko Hauzenberger & Dominik Hirschbuehl & Florian Huber & Luca Onorante & Michael Pfarrhofer & Luca Tiozzo Pezzoli, 2024. "Nowcasting economic activity in European regions using a mixed-frequency dynamic factor model," Papers 2401.10054, arXiv.org.
    45. Ankargren, Sebastian & Jonéus, Paulina, 2021. "Simulation smoothing for nowcasting with large mixed-frequency VARs," Econometrics and Statistics, Elsevier, vol. 19(C), pages 97-113.
    46. Iacopini, Matteo & Poon, Aubrey & Rossini, Luca & Zhu, Dan, 2023. "Bayesian mixed-frequency quantile vector autoregression: Eliciting tail risks of monthly US GDP," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
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    48. Barhoumi, K. & Darné, O. & Ferrara, L., 2013. "Dynamic Factor Models: A review of the Literature ," Working papers 430, Banque de France.
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    69. 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.
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  4. Hwee Kwan Chow & Peter Nicholas Kriz & Roberto S. Mariano & Augustine H. H. Tan, 2010. "Monetary Policy Cooperation To Support Asian Economic Integration," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 55(01), pages 83-101.

    Cited by:

    1. Pontines, Victor, 2015. "How useful is an Asian Currency Unit (ACU) index for surveillance in East Asia?," Economic Systems, Elsevier, vol. 39(2), pages 269-287.
    2. Pontines, Victor & You, Kefei, 2015. "Asian Currency Unit (ACU), deviation indicators and exchange rate coordination in East Asia: A panel-based convergence approach," Japan and the World Economy, Elsevier, vol. 36(C), pages 42-55.

  5. Carlos C. Bautista & Roberto S. Mariano & Bayani Victor Bawagan, 2009. "The NEDA quarterly macroeconomic model: theoretical structure and some empirical results," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 46(2), pages 240-260, December.

    Cited by:

    1. Bayangos, V.B. & Jansen, K., 2009. "The Macroeconomics of Remittances In the Philippines," ISS Working Papers - General Series 19676, International Institute of Social Studies of Erasmus University Rotterdam (ISS), The Hague.
    2. Bayangos, V.B., 2006. "Exchange rate uncertainty and monetary transmission in the Philippines," ISS Working Papers - General Series 19193, International Institute of Social Studies of Erasmus University Rotterdam (ISS), The Hague.
    3. Durmus Ozdemir & Mustafa Kemal Gündoğdu, 2012. "Structural Macro econometric Model of Turkey; Impact of Structural Characteristics on Macroeconomic Indicators," EcoMod2012 3886, EcoMod.

  6. Brunetti, Celso & Scotti, Chiara & Mariano, Roberto S. & Tan, Augustine H.H., 2008. "Markov switching GARCH models of currency turmoil in Southeast Asia," Emerging Markets Review, Elsevier, vol. 9(2), pages 104-128, June.
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  7. Winston Koh & Roberto Mariano & Yiu Kuen Tse, 2007. "Open vs. sealed-bid auctions: testing for revenue equivalence under Singapore's vehicle quota system," Applied Economics, Taylor & Francis Journals, vol. 39(1), pages 125-134.

    Cited by:

    1. Singfat Chu, 2011. "Sealed v/s open bids for certificates of entitlement under the vehicle quota system in Singapore," Transportation, Springer, vol. 38(2), pages 215-226, March.

  8. Koh, Winston T.H. & Mariano, Roberto S. & Pavlov, Andrey & Phang, Sock Yong & Tan, Augustine H.H. & Wachter, Susan M., 2005. "Bank lending and real estate in Asia: market optimism and asset bubbles," Journal of Asian Economics, Elsevier, vol. 15(6), pages 1103-1118, January.

    Cited by:

    1. José De Gregorio, 2009. "Implementation of Inflation Targets in Emerging Markets," Chapters, in: Gill Hammond & Ravi Kanbur & Eswar Prasad (ed.), Monetary Policy Frameworks for Emerging Markets, chapter 3, Edward Elgar Publishing.
    2. Liang, Qi & Cao, Hua, 2007. "Property prices and bank lending in China," Journal of Asian Economics, Elsevier, vol. 18(1), pages 63-75, February.
    3. Richard K. Green & Roberto S. Mariano & Andrey D. Pavlov & Susan M. Wachter, 2007. "Misaligned Incentives and Mortgage Lending in Asia," Working Paper 9099, USC Lusk Center for Real Estate.
    4. John Lipsky, 2009. "Asia, the financial crisis, and global economic governance - closing remarks," Proceedings, Federal Reserve Bank of San Francisco, issue Oct, pages 347-353.
    5. Torsten Wezel & Mr. Mario Mansilla & Gustavo Adler, 2009. "Modernizing Bank Regulation in Support of Financial Deepening: The Case of Uruguay," IMF Working Papers 2009/199, International Monetary Fund.
    6. Kyungwon Kim & Jae Wook Song, 2018. "Managing Bubbles in the Korean Real Estate Market: A Real Options Framework," Sustainability, MDPI, vol. 10(8), pages 1-25, August.
    7. Svante Mandell & Han-Suck Song & Abukar Warsame & Mats Wilhelmsson, 2011. "Bank Lending and House Prices in Sweden 1992-2010," ERES eres2011_91, European Real Estate Society (ERES).
    8. Maurice Obstfeld & Kenneth S. Rogoff, 2009. "Global imbalances and the financial crisis: products of common causes," Proceedings, Federal Reserve Bank of San Francisco, issue Oct, pages 131-172.
    9. Armand Fouejieu,, 2017. "Inflation targeting and financial stability in emerging markets," Economic Modelling, Elsevier, vol. 60(C), pages 51-70.
    10. Chen, Y. & He, M. & Rudkin, S., 2017. "Understanding Chinese provincial real estate investment: A Global VAR perspective," Economic Modelling, Elsevier, vol. 67(C), pages 248-260.
    11. Lucia Gibilaro & Gianluca Mattarocci, 2016. "Are Real Estate Banks More Affected by Real Estate Market Dynamics?," International Real Estate Review, Global Social Science Institute, vol. 19(2), pages 151-170.
    12. Mylène Gaulard, 2014. "La burbuja inmobiliaria en China," Post-Print halshs-01086912, HAL.
    13. Ramón Moreno, 2008. "Experiences with Current Account Deficits in Southeast Asia," Central Banking, Analysis, and Economic Policies Book Series, in: Kevin Cowan & Sebastián Edwards & Rodrigo O. Valdés & Norman Loayza (Series Editor) & Klaus Schmidt- (ed.),Current Account and External Financing, edition 1, volume 12, chapter 14, pages 537-582, Central Bank of Chile.
    14. Mylène Gaulard, 2014. "Les dangers de la bulle immobilière chinoise," Post-Print halshs-01083047, HAL.
    15. Heeho Kim & SaeWoon Park & Sun Hye Lee, 2012. "House Price and Bank Lending in a Premium Submarket in Korea," International Real Estate Review, Global Social Science Institute, vol. 15(1), pages 1-42.

  9. Mariano Roberto S & Gultekin Bulent N & Ozmucur Suleyman & Shabbir Tayyeb & Alper C. Emre, 2004. "Prediction of Currency Crises: Case of Turkey," Review of Middle East Economics and Finance, De Gruyter, vol. 2(2), pages 1-21, August.

    Cited by:

    1. Wajih Khallouli & Rene Sandretto, 2011. "Testing for “Contagion” of the Subprime Crisis on the Middle East And North African Stock Markets: A Markov Switching EGARCH Approach," Working Papers 609, Economic Research Forum, revised 08 Jan 2011.
    2. Feridun, Mete, 2008. "Currency crises in emerging markets: The case of post-liberalization Turkey," Greenwich Papers in Political Economy 7922, University of Greenwich, Greenwich Political Economy Research Centre.
    3. Balaga Mohana Rao & Puja Padhi, 2019. "Identifying the Early Warnings of Currency Crisis in India," Foreign Trade Review, , vol. 54(4), pages 269-299, November.
    4. Joscha Beckmann & Robert L. Czudaj, 2023. "The role of expectations for currency crisis dynamics—The case of the Turkish lira," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 625-642, April.
    5. Omotosho, Babatunde S., 2015. "Is Real Exchange Rate Misalignment a Leading Indicator of Currency Crises in Nigeria?," MPRA Paper 98353, University Library of Munich, Germany.
    6. Wajih Khallouli & Mahmoud Sami Nabi, 2010. "Financial Crises’ Prevention and Recovery," Working Papers 529, Economic Research Forum, revised 06 Jan 2010.
    7. Wajih Khallouli & Modibo René Sandretto, 2010. "Testing for “contagion” of the subprime crisis on the Middle East and North African stock markets : A Markov Switching EGARCH approach," Working Papers 1022, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    8. El-Shagi, Makram & Knedlik, Tobias & von Schweinitz, Gregor, 2012. "Predicting Financial Crises: The (Statistical) Significance of the Signals Approach," IWH Discussion Papers 3/2012, Halle Institute for Economic Research (IWH).
    9. Katircioglu, Salih Turan & Feridun, Mete, 2010. "Do macroeconomic fundamentals affect exchange market pressure? Evidence from bounds testing approach for Turkey," Greenwich Papers in Political Economy 7916, University of Greenwich, Greenwich Political Economy Research Centre.
    10. Mete Feridun, 2009. "Determinants of Exchange Market Pressure in Turkey: An Econometric Investigation," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 45(2), pages 65-81, March.
    11. Ari, Ali, 2012. "Early warning systems for currency crises: The Turkish case," Economic Systems, Elsevier, vol. 36(3), pages 391-410.
    12. Panayotis Michaelides & Mike Tsionas & Panos Xidonas, 2020. "A Bayesian Signals Approach for the Detection of Crises," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 551-585, September.

  10. Roberto S. Mariano & Francisco G. Dakila Jr. & Racquel A. Claveria, 2003. "The Bangko Sentral’s structural long-term inflation forecasting model for the Philippines," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 40(1), pages 58-72, June.

    Cited by:

    1. Cruz, Christopher John & Mapa, Dennis, 2013. "An Early Warning System for Inflation in the Philippines Using Markov-Switching and Logistic Regression Models," MPRA Paper 50078, University Library of Munich, Germany.

  11. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.

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    4. Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
    5. Markus Leippold & Hanlin Yang, 2023. "Mixed‐frequency predictive regressions with parameter learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 1955-1972, December.
    6. Qian, Hang, 2012. "Essays on statistical inference with imperfectly observed data," ISU General Staff Papers 201201010800003618, Iowa State University, Department of Economics.
    7. Antonio Diez de los Rios & Enrique Sentana, 2011. "Testing Uncovered Interest Parity: A Continuous‐Time Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(4), pages 1215-1251, November.
    8. Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2018. "Using low frequency information for predicting high frequency variables," International Journal of Forecasting, Elsevier, vol. 34(4), pages 774-787.
    9. Michele Modugno & Lucrezia Reichlin & Domenico Giannone & Marta Banbura, 2012. "Nowcasting with Daily Data," 2012 Meeting Papers 555, Society for Economic Dynamics.
    10. 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.).
    11. Marcellino, Massimiliano & Sivec, Vasja, 2016. "Monetary, fiscal and oil shocks: Evidence based on mixed frequency structural FAVARs," Journal of Econometrics, Elsevier, vol. 193(2), pages 335-348.
    12. Gian Luigi Mazzi & James Mitchell & Gaetana Montana, 2014. "Density Nowcasts and Model Combination: Nowcasting Euro-Area GDP Growth over the 2008–09 Recession," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 233-256, April.
    13. Hager Ben Romdhane, 2021. "Nowcasting in Tunisia using large datasets and mixed frequency models," IHEID Working Papers 11-2021, Economics Section, The Graduate Institute of International Studies.
    14. Boriss Siliverstovs, 2016. "The franc shock and Swiss GDP: how long does it take to start feeling the pain?," Applied Economics, Taylor & Francis Journals, vol. 48(36), pages 3432-3441, August.
    15. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2010. "Should macroeconomic forecasters use daily financial data and how?," University of Cyprus Working Papers in Economics 09-2010, University of Cyprus Department of Economics.
    16. João Victor Issler & Hilton Hostalacio Notini & Claudia Fontoura Rodrigues, 2013. "Constructing coincident and leading indices of economic activity for the Brazilian economy," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2012(2), pages 43-65.
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    20. Klaus Abberger & Michael Graff & Boriss Siliverstovs & Jan-Egbert Sturm, 2014. "The KOF Economic Barometer, Version 2014," KOF Working papers 14-353, KOF Swiss Economic Institute, ETH Zurich.
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    34. Paul Viefers & Ferdinand Fichtner & Simon Junker & Maximilian Podstawski, 2014. "Filtering German Economic Conditions from a Large Dataset: The New DIW Economic Barometer," Discussion Papers of DIW Berlin 1414, DIW Berlin, German Institute for Economic Research.
    35. Brave, Scott A. & Butters, R. Andrew & Justiniano, Alejandro, 2019. "Forecasting economic activity with mixed frequency BVARs," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1692-1707.
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    37. Daniel Aaronson & Scott A. Brave & Michael Fogarty & Ezra Karger & Spencer D. Krane, 2021. "Tracking U.S. Consumers in Real Time with a New Weekly Index of Retail Trade," Working Paper Series WP-2021-05, Federal Reserve Bank of Chicago, revised 18 Jun 2021.
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    40. Gonzalo Echavarría M. & Wildo González P, 2011. "Un Modelo de Factores Dinámicos de Pequeña Escala para el Imacec," Notas de Investigación Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 14(2), pages 109-118, August.
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    44. David Havrlant & Peter Tóth & Julia Wörz, 2016. "On the optimal number of indicators – nowcasting GDP growth in CESEE," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 4, pages 54-72.
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    339. Ademmer, Martin & Boysen-Hogrefe, Jens & Fiedler, Salomon & Groll, Dominik & Hauber, Philipp & Jannsen, Nils & Kooths, Stefan & Potjagailo, Galina, 2018. "Deutsche Konjunktur im Frühjahr 2018 - Deutsche Wirtschaft näher am Limit [German Economy Spring 2018 - German economy closer to its limit]," Kieler Konjunkturberichte 41, Kiel Institute for the World Economy (IfW Kiel).
    340. Kihwan Kim & Norman Swanson, 2013. "Diffusion Index Model Specification and Estimation Using Mixed Frequency Datasets," Departmental Working Papers 201315, Rutgers University, Department of Economics.
    341. Cecilia Frale & Valentina Raponi, 2011. "Revisions in ocial data and forecasting," Working Papers LuissLab 1194, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    342. María Gil & Danilo Leiva-Leon & Javier J. Pérez & Alberto Urtasun, 2019. "An application of dynamic factor models to nowcast regional economic activity in Spain," Occasional Papers 1904, Banco de España.
    343. Edoardo Otranto, 2005. "Extraction of Common Signal from Series with Different Frequency," Econometrics 0502011, University Library of Munich, Germany.
    344. William Barcelona & Danilo Cascaldi-Garcia & Jasper Hoek & Eva Van Leemput, 2022. "What Happens in China Does Not Stay in China," International Finance Discussion Papers 1360, Board of Governors of the Federal Reserve System (U.S.).
    345. Jennifer Castle & David Hendry & Oleg Kitov, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.
    346. Ángel Cuevas & Ramiro Ledo & Enrique M. Quilis, 2021. "Seasonal adjustment of the Spanish sales daily data," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 12(4), pages 687-708, December.
    347. Davor Kunovac & Borna Špalat, 2014. "Nowcasting GDP Using Available Monthly Indicators," Working Papers 39, The Croatian National Bank, Croatia.
    348. Eraslan, Sercan & Götz, Thomas, 2020. "An unconventional weekly economic activity index for Germany," Technical Papers 02/2020, Deutsche Bundesbank.
    349. Dimitris Korobilis & Maximilian Schröder, 2023. "Probabilistic Quantile Factor Analysis," Working Papers No 05/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    350. Paul Viefers, 2011. "Bayesian Inference for the Mixed-Frequency VAR Model," Discussion Papers of DIW Berlin 1172, DIW Berlin, German Institute for Economic Research.
    351. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    352. Thomas Walther & Lanouar Charfeddine & Tony Klein, 2018. "Oil Price Changes and U.S. Real GDP Growth: Is this Time Different?," Working Papers on Finance 1816, University of St. Gallen, School of Finance.
    353. Keeney, Mary & Kennedy, Bernard & Liebermann, Joelle, 2012. "The value of hard and soft data for short-term forecasting of GDP," Economic Letters 11/EL/12, Central Bank of Ireland.
    354. Sebastian Ankargren & Måns Unosson & Yukai Yang, 2018. "A mixed-frequency Bayesian vector autoregression with a steady-state prior," CREATES Research Papers 2018-32, Department of Economics and Business Economics, Aarhus University.
    355. González-Astudillo, Manuel & Baquero, Daniel, 2019. "A nowcasting model for Ecuador: Implementing a time-varying mean output growth," Economic Modelling, Elsevier, vol. 82(C), pages 250-263.
    356. Camacho, Maximo, 2013. "Mixed-frequency VAR models with Markov-switching dynamics," Economics Letters, Elsevier, vol. 121(3), pages 369-373.
    357. Ruey Yau & C. James Hueng, 2019. "Nowcasting GDP Growth for Small Open Economies with a Mixed-Frequency Structural Model," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 177-198, June.
    358. Matteo Barigozzi & Matteo Luciani, 2019. "Quasi Maximum Likelihood Estimation and Inference of Large Approximate Dynamic Factor Models via the EM algorithm," Papers 1910.03821, arXiv.org, revised Feb 2022.
    359. Paul Labonne, 2020. "Capturing GDP nowcast uncertainty in real time," Papers 2012.02601, arXiv.org, revised Oct 2021.
    360. Wichitaksorn, Nuttanan, 2022. "Analyzing and forecasting Thai macroeconomic data using mixed-frequency approach," Journal of Asian Economics, Elsevier, vol. 78(C).
    361. Koki Kyo & Hideo Noda & Genshiro Kitagawa, 2022. "Co-movement of Cyclical Components Approach to Construct a Coincident Index of Business Cycles," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(1), pages 101-127, March.
    362. 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.
    363. Leippold, Markus & Yang, Hanlin, 2019. "Particle filtering, learning, and smoothing for mixed-frequency state-space models," Econometrics and Statistics, Elsevier, vol. 12(C), pages 25-41.

  12. Tanizaki, Hisashi & Mariano, Roberto S., 1998. "Nonlinear and non-Gaussian state-space modeling with Monte Carlo simulations," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 263-290.

    Cited by:

    1. Florian Heiss, 2008. "Sequential numerical integration in nonlinear state space models for microeconometric panel data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 373-389.
    2. Motta, Anderson C. O. & Hotta, Luiz K., 2003. "Exact Maximum Likelihood and Bayesian Estimation of the Stochastic Volatility Model," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 23(2), November.
    3. Pablo Marshall, 2000. "Difusion De Internet En Chile," Abante, Escuela de Administracion. Pontificia Universidad Católica de Chile., vol. 3(2), pages 143-163.
    4. Yasuhiro Omori & Toshiaki Watanabe, 2007. "Block Sampler and Posterior Mode Estimation for A Nonlinear and Non-Gaussian State-Space Model with Correlated Errors," CARF F-Series CARF-F-104, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    5. Siddhartha Chib & Yasuhiro Omori & Manabu Asai, 2007. "Multivariate stochastic volatility (Revised in May 2007, Handbook of Financial Time Series (Published in "Handbook of Financial Time Series" (eds T.G. Andersen, R.A. Davis, Jens-Peter Kreiss," CARF F-Series CARF-F-094, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    6. Geweke, John & Tanizaki, Hisashi, 2001. "Bayesian estimation of state-space models using the Metropolis-Hastings algorithm within Gibbs sampling," Computational Statistics & Data Analysis, Elsevier, vol. 37(2), pages 151-170, August.
    7. Cadini, F. & Zio, E. & Avram, D., 2009. "Model-based Monte Carlo state estimation for condition-based component replacement," Reliability Engineering and System Safety, Elsevier, vol. 94(3), pages 752-758.
    8. Miller, J. Isaac & Park, Joon Y., 2005. "How They Interact to Generate Persistency in Memory," Working Papers 2005-01, Rice University, Department of Economics.
    9. Timothy Cogley, 2005. "Changing Beliefs and the Term Structure of Interest Rates: Cross-Equation Restrictions with Drifting Parameters," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 420-451, April.
    10. Creal, D., 2009. "A survey of sequential Monte Carlo methods for economics and finance," Serie Research Memoranda 0018, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    11. Silvia Cagnone & Francesco Bartolucci, 2017. "Adaptive Quadrature for Maximum Likelihood Estimation of a Class of Dynamic Latent Variable Models," Computational Economics, Springer;Society for Computational Economics, vol. 49(4), pages 599-622, April.
    12. Cui, Qiurong & Xu, Yuqing & Zhang, Zhengjun & Chan, Vincent, 2021. "Max-linear regression models with regularization," Journal of Econometrics, Elsevier, vol. 222(1), pages 579-600.
    13. Levent Ozbek & Umit Ozlale & Fikri Ozturk, 2003. "Employing Extended Kalman Filter in a Simple Macroeconomic Model," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 3(1), pages 53-65.
    14. Tokovenko, Oleksiy & Gunter, Lewell F., 2008. "Quarterly Storage Model of U.S. Cotton Market: Estimation of the Basis under Rational Expectations," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6435, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    15. J. Huston McCulloch & Prasad V. Bidarkota, 2003. "Signal Extraction can Generate Volatility Clusters," Computing in Economics and Finance 2003 59, Society for Computational Economics.
    16. J. Huston McCulloch & Prasad V. Bidarkota, 2002. "Signal Extraction Can Generate Volatility Clusters From IID Shocks," Working Papers 02-04, Ohio State University, Department of Economics.
    17. Cagnone, Silvia & Bartolucci, Francesco, 2013. "Adaptive quadrature for likelihood inference on dynamic latent variable models for time-series and panel data," MPRA Paper 51037, University Library of Munich, Germany.
    18. Tomohiro Ando, 2008. "Measuring the baseline sales and the promotion effect for incense products: a Bayesian state-space modeling approach," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(4), pages 763-780, December.
    19. F Cadini & D Avram & E Zio, 2010. "System state estimation by particle filtering for fault diagnosis and prognosis," Journal of Risk and Reliability, , vol. 224(3), pages 149-158, September.
    20. Chiachío, Juan & Chiachío, Manuel & Sankararaman, Shankar & Saxena, Abhinav & Goebel, Kai, 2015. "Condition-based prediction of time-dependent reliability in composites," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 134-147.
    21. Siem Jan Koopman & Kai Ming Lee, 2005. "Measuring Asymmetric Stochastic Cycle Components in U.S. Macroeconomic Time Series," Tinbergen Institute Discussion Papers 05-081/4, Tinbergen Institute.

  13. Fangxiong Gong & Roberto Mariano, 1997. "Stock Market Returns and Economic Fundamentals in an Emerging Market: The Case of Korea," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 4(2), pages 147-169, May.

    Cited by:

    1. Esref Savas BASCI & S leyman Serdar KARACA, 2013. "The Determinants of Stock Market Index: VAR Approach to Turkish Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 3(1), pages 163-171.

  14. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-263, July.
    See citations under working paper version above.
  15. Tanizaki, Hisashi & Mariano, Roberto S, 1994. "Prediction, Filtering and Smoothing in Non-linear and Non-normal Cases Using Monte Carlo Integration," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(2), pages 163-179, April-Jun.

    Cited by:

    1. Florian Heiss, 2008. "Sequential numerical integration in nonlinear state space models for microeconometric panel data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 373-389.
    2. Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez, 2007. "Estimating Macroeconomic Models: A Likelihood Approach," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 74(4), pages 1059-1087.
    3. Motta, Anderson C. O. & Hotta, Luiz K., 2003. "Exact Maximum Likelihood and Bayesian Estimation of the Stochastic Volatility Model," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 23(2), November.
    4. Florian Heiss, 2006. "Nonlinear State-Space Models for Microeconometric Panel Data," Computing in Economics and Finance 2006 285, Society for Computational Economics.
    5. Panayotis G. Michaelides & Efthymios G. Tsionas & Angelos T. Vouldis & Konstantinos N. Konstantakis & Panagiotis Patrinos, 2018. "A Semi-Parametric Non-linear Neural Network Filter: Theory and Empirical Evidence," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 637-675, March.
    6. S. Boragan Aruoba, 2008. "Data Revisions Are Not Well Behaved," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(2-3), pages 319-340, March.
    7. Jesus Fernandez-Villaverde & Juan F. Rubio-Ramirez, 2004. "Estimating Nonlinear Dynamic Equilibrium economies: A Likelihood Approach," PIER Working Paper Archive 04-001, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    8. Tanizaki, Hisashi, 1997. "Nonlinear and nonnormal filters using Monte Carlo methods," Computational Statistics & Data Analysis, Elsevier, vol. 25(4), pages 417-439, September.
    9. Tanizaki, Hisashi & Mariano, Roberto S., 1998. "Nonlinear and non-Gaussian state-space modeling with Monte Carlo simulations," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 263-290.
    10. Hermann Singer, 2003. "Simulated Maximum Likelihood in Nonlinear Continuous-Discrete State Space Models: Importance Sampling by Approximate Smoothing," Computational Statistics, Springer, vol. 18(1), pages 79-106, March.

  16. Brown, Bryan W & Mariano, Roberto S, 1989. "Measures of Deterministic Prediction Bias in Nonlinear Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(3), pages 667-684, August.

    Cited by:

    1. McMillan, David G., 2009. "The confusing time-series behaviour of real exchange rates: Are asymmetries important?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(4), pages 692-711, October.
    2. Gajda, Jan B. & Markowski, Aleksander, 1998. "Model Evaluation Using Stochastic Simulations: The Case of the Econometric Model KOSMOS," Working Papers 61, National Institute of Economic Research.
    3. M. Hashem Pesaran & Andreas Pick & Allan Timmermann, 2009. "Variable Selection and Inference for Multi-period Forecasting Problems," CESifo Working Paper Series 2543, CESifo.
    4. Hännikäinen, Jari, 2014. "Multi-step forecasting in the presence of breaks," MPRA Paper 55816, University Library of Munich, Germany.
    5. Michael Wegener & Göran Kauermann, 2017. "Forecasting in nonlinear univariate time series using penalized splines," Statistical Papers, Springer, vol. 58(3), pages 557-576, September.
    6. Pesaran, M. Hashem & Pick, Andreas & Timmermann, Allan, 2011. "Variable selection, estimation and inference for multi-period forecasting problems," Journal of Econometrics, Elsevier, vol. 164(1), pages 173-187, September.
    7. Tanizaki, Hisashi, 1997. "Nonlinear and nonnormal filters using Monte Carlo methods," Computational Statistics & Data Analysis, Elsevier, vol. 25(4), pages 417-439, September.
    8. Tanizaki, Hisashi & Mariano, Roberto S., 1998. "Nonlinear and non-Gaussian state-space modeling with Monte Carlo simulations," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 263-290.
    9. David McMillan, 2008. "Non-linear cointegration and adjustment: an asymmetric exponential smooth-transition model for US interest rates," Empirical Economics, Springer, vol. 35(3), pages 591-606, November.
    10. Dag Kolsrud, 2008. "Stochastic Ceteris Paribus Simulations," Computational Economics, Springer;Society for Computational Economics, vol. 31(1), pages 21-43, February.

  17. Brown, Bryan W. & Mariano, Roberto S., 1989. "Predictors in Dynamic Nonlinear Models: Large-Sample Behavior," Econometric Theory, Cambridge University Press, vol. 5(3), pages 430-452, December.

    Cited by:

    1. Neil R. Ericsson & Jaime R. Marquez, 1990. "Evaluating the predictive performance of trade-account models," International Finance Discussion Papers 377, Board of Governors of the Federal Reserve System (U.S.).
    2. Gajda, Jan B. & Markowski, Aleksander, 1998. "Model Evaluation Using Stochastic Simulations: The Case of the Econometric Model KOSMOS," Working Papers 61, National Institute of Economic Research.
    3. Phillip Rothman & Dick van Dijk & Philip Hans Franses, 2000. "A Multivariate STAR Analysis of the Relationship Between Money and Output," Working Papers 0012, East Carolina University, Department of Economics.
    4. Giacomini, Raffaella & Granger, Clive W.J., 2001. "Aggregationn of Space-Time Processes," University of California at San Diego, Economics Working Paper Series qt77f76455, Department of Economics, UC San Diego.
    5. van Garderen, Kees Jan, 2001. "Optimal prediction in loglinear models," Journal of Econometrics, Elsevier, vol. 104(1), pages 119-140, August.
    6. Richard H. Clarida & Lucio Sarno & Mark P. Taylor & Giorgio Valente, 2006. "The Role of Asymmetries and Regime Shifts in the Term Structure of Interest Rates," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1193-1224, May.
    7. Richard Clarida & Lucio Sarno & Mark Taylor & Giorgio Valente, 2001. "The Out-of-Sample Success of Term Structure Models as Exchange Rate Predictors: A Step Beyond," NBER Working Papers 8601, National Bureau of Economic Research, Inc.
    8. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415.
    9. George Milunovich, 2020. "Forecasting Australia's real house price index: A comparison of time series and machine learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1098-1118, November.
    10. van Garderen, Kees Jan & Lee, Kevin & Pesaran, M. Hashem, 2000. "Cross-sectional aggregation of non-linear models," Journal of Econometrics, Elsevier, vol. 95(2), pages 285-331, April.
    11. Neil R. Ericsson & Jaime R. Marquez, 1998. "A framework for economic forecasting," International Finance Discussion Papers 626, Board of Governors of the Federal Reserve System (U.S.).
    12. Bryan W. Brown, 2000. "Efficient Semiparametric Prediction Intervals," Econometric Society World Congress 2000 Contributed Papers 1633, Econometric Society.
    13. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707.
    14. Giorgio Valente & Lucio Sarno, 2005. "Modelling and forecasting stock returns: exploiting the futures market, regime shifts and international spillovers," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(3), pages 345-376.
    15. Milena Hoyos & Mario Galindo, 2011. "Comparación de los modelos SETAR y STAR para el índice de empleo industrial colombiano," Documentos de Trabajo, Escuela de Economía 8347, Universidad Nacional de Colombia, FCE, CID.
    16. Jeon, Byung M. & Brown, Bryan, 2001. "Efficient Semiparametric Estimation of Expectations in Dynamic Nonlinear Systems," Working Papers 2001-09, Rice University, Department of Economics.
    17. Dag Kolsrud, 2008. "Stochastic Ceteris Paribus Simulations," Computational Economics, Springer;Society for Computational Economics, vol. 31(1), pages 21-43, February.
    18. Kasai, Ndahiriwe & Naraidoo, Ruthira, 2011. "Evaluating the forecasting performance of linear and nonlinear monetary policy rules for South Africa," MPRA Paper 40699, University Library of Munich, Germany.
    19. Amendola, Alessandra & Christian, Francq, 2009. "Concepts and tools for nonlinear time series modelling," MPRA Paper 15140, University Library of Munich, Germany.
    20. Eraslan, Sercan & Nöller, Marvin, 2020. "Recession probabilities falling from the STARs," Discussion Papers 08/2020, Deutsche Bundesbank.

  18. Seater, John J. & Mariano, Roberto S., 1985. "New tests of the life cycle and tax discounting hypotheses," Journal of Monetary Economics, Elsevier, vol. 15(2), pages 195-215, March.

    Cited by:

    1. Basil Dalamagas, 1994. "Testing the Debt-Illusion Hypothesis," Revue Économique, Programme National Persée, vol. 45(4), pages 1079-1094.
    2. Brunila, Anne, 1997. "Current income and private consumption: Saving decisions: Testing the finite horizon model," Bank of Finland Research Discussion Papers 6/1997, Bank of Finland.
    3. Khalid, Ahmed M., 1996. "Ricardian equivalence: Empirical evidence from developing economies," Journal of Development Economics, Elsevier, vol. 51(2), pages 413-432, December.
    4. Mariusz Jarmuzek, 2005. "Are the EU new member states fiscally sustainable? An empirical analysis," UCL SSEES Economics and Business working paper series 51, UCL School of Slavonic and East European Studies (SSEES).
    5. Waqas, Muhammad & Awan, Masood Sarwar, 2011. "Are Pakistani Consumers Ricardian?," MPRA Paper 35375, University Library of Munich, Germany.
    6. Douglas W. Elmendorf & N. Gregory Mankiw, 1998. "Government Debt," NBER Working Papers 6470, National Bureau of Economic Research, Inc.
    7. Reitschuler, Gerhard, 2008. "Assessing Ricardian equivalence for the New Member States: Does debt-neutrality matter?," Economic Systems, Elsevier, vol. 32(2), pages 119-128, June.
    8. Giavazzi, Francesco & Pagano, Marco, 1990. "Can Severe Fiscal Contractions Be Expansionary? Tales of Two Small European Countries," CEPR Discussion Papers 417, C.E.P.R. Discussion Papers.
    9. Terézia Vančová, 2019. "The Excess Smoothness and Sensitivity of Consumption in the V4 Countries," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 67(6), pages 1653-1663.
    10. Waqas, Muhamad & Awan, Masood Sarwar & Aslam, Muhammad Amir, 2011. "We are living on the cost of our children," MPRA Paper 32044, University Library of Munich, Germany.
    11. B. Douglas Bernheim, 1987. "Ricardian Equivalence: An Evaluation of Theory and Evidence," NBER Working Papers 2330, National Bureau of Economic Research, Inc.
    12. Pradhan, Krishanu, 2015. "Ricardian approach to fiscal sustainability in India," Working Papers 335, Institute for Social and Economic Change, Bangalore.
    13. Mark Wheeler, 1999. "The macroeconomic impacts of government debt: An empirical analysis of the 1980s and 1990s," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 27(3), pages 273-284, September.
    14. Berrittella, Maria & Zhang, Jian, 2015. "Fiscal sustainability in the EU: From the short-term risk to the long-term challenge," Journal of Policy Modeling, Elsevier, vol. 37(2), pages 261-280.
    15. Alpha C. Chiang & Stephen M. Miller, 1998. "The Perception of Government Bonds and Money as Net Wealth: An Integrated Approach," Working papers 1998-05, University of Connecticut, Department of Economics.
    16. Brunila, Anne, 1996. "Fiscal policy and private consumption: Saving decisions: Evidence from Finland," Bank of Finland Research Discussion Papers 28/1996, Bank of Finland.
    17. Bilgili, Faik, 1999. "Yeni Klasik kurama göre bütçe politikalarının değerlendirilmesi [An evaluation of New Classical arguments on budget policies]," MPRA Paper 80771, University Library of Munich, Germany.
    18. Bilgili, Faik, 2006. "Random walk, excess smoothness or excess sensitivity? Evidence from literature and an application for Turkish economy," MPRA Paper 24086, University Library of Munich, Germany, revised 14 Jul 2010.
    19. David Alan Aschauer, 1990. "Is Government Spending Stimulative?," Contemporary Economic Policy, Western Economic Association International, vol. 8(4), pages 30-46, October.
    20. Robert J. Barro, 1988. "The Ricardian Approach to Budget Deficits," NBER Working Papers 2685, National Bureau of Economic Research, Inc.
    21. Ghassan, Hassan B., 2003. "آثار عجز الميزانية على الإدخار الخاص في الإقتصاد المغربي عبر نمذجة التقهقر الذاتي البنيوي [Effects of Budget Deficit on Private Savings in Moroccan Economy using SVAR Modeling]," MPRA Paper 56435, University Library of Munich, Germany, revised 07 Feb 2004.
    22. Saha, Sarani & Roy, Poulomi & Kar, Saibal, 2014. "Public and private sector jobs, unreported income and consumption gap in India: Evidence from micro-data," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 285-300.
    23. Riccardo Fiorito & Lorenzo Pecchi & Giorgio Valente, 2002. "The Market Value of Italian Government Debt, 1970-1996," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 61(1), pages 1-28, June.
    24. Darby, Michael R., 1986. "The internationalization of American banking and finance: Structure, risk, and world interest rates," Journal of International Money and Finance, Elsevier, vol. 5(4), pages 403-428, December.
    25. Matteo Formenti, 2008. "Indicators and Tests of Sustainability: The Italian Case," Rivista di Politica Economica, SIPI Spa, vol. 98(6), pages 123-160, November-.
    26. Roberto Ricciuti, 2003. "Assessing Ricardian Equivalence," Journal of Economic Surveys, Wiley Blackwell, vol. 17(1), pages 55-78, February.
    27. Ghatak, Anita & Ghatak, Subrata, 1996. "Budgetary deficits and Ricardian equivalence: The case of India, 1950-1986," Journal of Public Economics, Elsevier, vol. 60(2), pages 267-282, May.
    28. Gochoco, Maria Socorro H., 1988. "Financing the Budget Deficit in a Small Open Economy: The Case of the Philippines, 1981-1986," Working Papers WP 1988-10, Philippine Institute for Development Studies.
    29. Koumparoulis, Dimitrios, 2006. "Ευρωπαϊκή Δημοσιονομική Πολιτική Και Οικονομική Μεγέθυνση: Η Νεοκλασική Οικονομική Θεωρία Για Την Περίπτωση Της Ελλάδας [European Fiscal Policy and Economic Growth: The Neoclassical Economic Theory," MPRA Paper 44310, University Library of Munich, Germany.
    30. Pierre Duguay & Yves Rabeau, 1989. "Les effets macro-économiques de la politique budgétaire : de Keynes à la synthèse néo-classique," Revue Économique, Programme National Persée, vol. 40(4), pages 597-620.
    31. Serletis, Apostolos & Shahmoradi, Asghar, 2010. "Consumption effects of government purchases," Journal of Macroeconomics, Elsevier, vol. 32(3), pages 892-905, September.
    32. Agustín García & Julián Ramajo, "undated". "Los Efectos De La Política Fiscal Sobre El Consumo Privado: Nueva Evidencia Para El Caso Español," Working Papers 13-02 Classification-JEL , Instituto de Estudios Fiscales.
    33. Sahar Bahmani, 2007. "Do budget deficits follow a linear or non-linear path?," Economics Bulletin, AccessEcon, vol. 5(14), pages 1-9.
    34. Onur Ozsoy, 2008. "Government Budget Deficits, Defence Expenditure And Income Distribution: The Case Of Turkey," Defence and Peace Economics, Taylor & Francis Journals, vol. 19(1), pages 61-75.
    35. Islam, Roumeen & Wetzel, Deborah L., 1991. "The macroeconomics of public sector deficits : the case of Ghana," Policy Research Working Paper Series 672, The World Bank.

  19. Brown, Bryan W & Mariano, Roberto S, 1984. "Residual-Based Procedures for Prediction and Estimation in a Nonlinear Simultaneous System," Econometrica, Econometric Society, vol. 52(2), pages 321-343, March.

    Cited by:

    1. Neil R. Ericsson & Jaime R. Marquez, 1990. "Evaluating the predictive performance of trade-account models," International Finance Discussion Papers 377, Board of Governors of the Federal Reserve System (U.S.).
    2. Calzolari, Giorgio & Panattoni, Lorenzo, 1990. "Mode predictors in nonlinear systems with identities," International Journal of Forecasting, Elsevier, vol. 6(3), pages 317-326, October.
    3. Gajda, Jan B. & Markowski, Aleksander, 1998. "Model Evaluation Using Stochastic Simulations: The Case of the Econometric Model KOSMOS," Working Papers 61, National Institute of Economic Research.
    4. Barrell, R. & Pina, A.M., 2000. "How Important are Automatic Stabilizers in Europe? A Stochastic Simulation Assessment," Economics Working Papers eco2000/2, European University Institute.
    5. Jaime R. Marquez, 1988. "Income and price elasticities of foreign trade flows: econometric estimation and analysis of the U.S. trade deficit," International Finance Discussion Papers 324, Board of Governors of the Federal Reserve System (U.S.).
    6. van Garderen, Kees Jan, 2001. "Optimal prediction in loglinear models," Journal of Econometrics, Elsevier, vol. 104(1), pages 119-140, August.
    7. Franz, Wolfgang & Göggelmann, Klaus & Schellhorn, Martin & Winker, Peter, 1998. "Quasi-Monte Carlo Methods in Stochastic Simulations: An Application to Fiscal Policy Simulations using an Aggregate Disequilibrium Model of the West German Economy," ZEW Discussion Papers 98-03, ZEW - Leibniz Centre for European Economic Research.
    8. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 8, pages 413-457, Elsevier.
    9. Magdalena Osinska & Tadeusz Kufel & Marcin Blazejowski & Pawel Kufel, 2016. "Modelling and Forecasting Business Cycle in CEE Countries using a Threshold Approach," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 16, pages 145-164.
    10. Bianchi, Carlo & Calzolari, Giorgio & Weihs, Claus, 1986. "Parametric and nonparametric Monte Carlo estimates of standard errors of forecasts in econometric models," MPRA Paper 29120, University Library of Munich, Germany.
    11. Rainer Schulz & Martin Wersing & Axel Werwatz, 2014. "Automated valuation modelling: a specification exercise," Journal of Property Research, Taylor & Francis Journals, vol. 31(2), pages 131-153, June.
    12. George Milunovich, 2020. "Forecasting Australia's real house price index: A comparison of time series and machine learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1098-1118, November.
    13. van Garderen, Kees Jan & Lee, Kevin & Pesaran, M. Hashem, 2000. "Cross-sectional aggregation of non-linear models," Journal of Econometrics, Elsevier, vol. 95(2), pages 285-331, April.
    14. Bianchi, Carlo & Calzolari, Giorgio & Brillet, Jean-Louis, 1987. "Measuring forecast uncertainty : A review with evaluation based on a macro model of the French economy," International Journal of Forecasting, Elsevier, vol. 3(2), pages 211-227.
    15. Bryan W. Brown, 2000. "Efficient Semiparametric Prediction Intervals," Econometric Society World Congress 2000 Contributed Papers 1633, Econometric Society.
    16. Ray C. Fair, 2001. "Bootstrapping Macroeconometric Models," Cowles Foundation Discussion Papers 1345, Cowles Foundation for Research in Economics, Yale University, revised Jun 2003.
    17. Calzolari, Giorgio, 1987. "La varianza delle previsioni nei modelli econometrici [Forecast variance in econometric models]," MPRA Paper 23866, University Library of Munich, Germany.
    18. Tanizaki, Hisashi, 1997. "Nonlinear and nonnormal filters using Monte Carlo methods," Computational Statistics & Data Analysis, Elsevier, vol. 25(4), pages 417-439, September.
    19. Mariano, Roberto S., 1985. "Finite-Sample Properties Of Stochastic Predictors In Nonlinear Systems: Some Initial Results," Economic Research Papers 269232, University of Warwick - Department of Economics.
    20. Tanizaki, Hisashi & Mariano, Roberto S., 1998. "Nonlinear and non-Gaussian state-space modeling with Monte Carlo simulations," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 263-290.
    21. Barrell, Ray & Dury, Karen & Hurst, Ian, 2003. "International monetary policy coordination: an evaluation using a large econometric model," Economic Modelling, Elsevier, vol. 20(3), pages 507-527, May.
    22. Jeon, Byung M. & Brown, Bryan, 2001. "Efficient Semiparametric Estimation of Expectations in Dynamic Nonlinear Systems," Working Papers 2001-09, Rice University, Department of Economics.
    23. Dag Kolsrud, 2008. "Stochastic Ceteris Paribus Simulations," Computational Economics, Springer;Society for Computational Economics, vol. 31(1), pages 21-43, February.
    24. Delgado, Miguel A., 1992. "Computing nonparametric functional estimates in semiparametric problems," UC3M Working papers. Economics 5821, Universidad Carlos III de Madrid. Departamento de Economía.
    25. Brillet, Jean-Louis & Calzolari, Giorgio & Panattoni, Lorenzo, 1986. "Coherent optimal prediction with large nonlinear systems: an example based on a French model," MPRA Paper 29057, University Library of Munich, Germany.

  20. Mariano, Roberto S & Brown, Bryan W, 1983. "Asymptotic Behavior of Predictors in a Nonlinear Simultaneous System," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 24(3), pages 523-536, October.

    Cited by:

    1. Neil R. Ericsson & Jaime R. Marquez, 1990. "Evaluating the predictive performance of trade-account models," International Finance Discussion Papers 377, Board of Governors of the Federal Reserve System (U.S.).
    2. Calzolari, Giorgio & Panattoni, Lorenzo, 1990. "Mode predictors in nonlinear systems with identities," International Journal of Forecasting, Elsevier, vol. 6(3), pages 317-326, October.
    3. Gajda, Jan B. & Markowski, Aleksander, 1998. "Model Evaluation Using Stochastic Simulations: The Case of the Econometric Model KOSMOS," Working Papers 61, National Institute of Economic Research.
    4. van Garderen, Kees Jan, 2001. "Optimal prediction in loglinear models," Journal of Econometrics, Elsevier, vol. 104(1), pages 119-140, August.
    5. Bianchi, Carlo & Calzolari, Giorgio, 1983. "Standard errors of forecasts in dynamic simulation of nonlinear econometric models: some empirical results," MPRA Paper 22657, University Library of Munich, Germany, revised 1983.
    6. Arthur Hsu & Ronald T. Wilcox, 2000. "Stochastic Prediction in Multinomial Logit Models," Management Science, INFORMS, vol. 46(8), pages 1137-1144, August.
    7. Bianchi, Carlo & Calzolari, Giorgio & Weihs, Claus, 1986. "Parametric and nonparametric Monte Carlo estimates of standard errors of forecasts in econometric models," MPRA Paper 29120, University Library of Munich, Germany.
    8. Yock Y. Chong & David F. Hendry, 1986. "Econometric Evaluation of Linear Macro-Economic Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 53(4), pages 671-690.
    9. Bryan W. Brown, 2000. "Efficient Semiparametric Prediction Intervals," Econometric Society World Congress 2000 Contributed Papers 1633, Econometric Society.
    10. Hendry, David F., 1984. "Monte carlo experimentation in econometrics," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 16, pages 937-976, Elsevier.
    11. Calzolari, Giorgio, 1987. "La varianza delle previsioni nei modelli econometrici [Forecast variance in econometric models]," MPRA Paper 23866, University Library of Munich, Germany.
    12. Tanizaki, Hisashi, 1997. "Nonlinear and nonnormal filters using Monte Carlo methods," Computational Statistics & Data Analysis, Elsevier, vol. 25(4), pages 417-439, September.
    13. Mariano, Roberto S., 1985. "Finite-Sample Properties Of Stochastic Predictors In Nonlinear Systems: Some Initial Results," Economic Research Papers 269232, University of Warwick - Department of Economics.
    14. Tanizaki, Hisashi & Mariano, Roberto S., 1998. "Nonlinear and non-Gaussian state-space modeling with Monte Carlo simulations," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 263-290.
    15. Bianchi, Carlo & Calzolari, Giorgio, 1983. "Confidence intervals of forecasts from nonlinear econometric models," MPRA Paper 29025, University Library of Munich, Germany.
    16. Eraslan, Sercan & Nöller, Marvin, 2020. "Recession probabilities falling from the STARs," Discussion Papers 08/2020, Deutsche Bundesbank.
    17. Brillet, Jean-Louis & Calzolari, Giorgio & Panattoni, Lorenzo, 1986. "Coherent optimal prediction with large nonlinear systems: an example based on a French model," MPRA Paper 29057, University Library of Munich, Germany.

  21. Mariano, Roberto S, 1982. "Analytical Small-Sample Distribution Theory in Econometrics: The Simultaneous-Equations Case," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 23(3), pages 503-533, October.

    Cited by:

    1. Paul A. Bekker & Jan van der Ploeg, 2000. "Instrumental Variable Estimation Based on Grouped Data," Econometric Society World Congress 2000 Contributed Papers 1862, Econometric Society.
    2. Anderson, T.W. & Kunitomo, Naoto & Matsushita, Yukitoshi, 2011. "On finite sample properties of alternative estimators of coefficients in a structural equation with many instruments," Journal of Econometrics, Elsevier, vol. 165(1), pages 58-69.
    3. Rodrigo Alfaro, 2008. "Higher Order Properties of the Symmetricallr Normalized Instrumental Variable Estimator," Working Papers Central Bank of Chile 500, Central Bank of Chile.
    4. Gajda, Jan B. & Markowski, Aleksander, 1998. "Model Evaluation Using Stochastic Simulations: The Case of the Econometric Model KOSMOS," Working Papers 61, National Institute of Economic Research.
    5. Moon, Hyungsik Roger & Schorfheide, Frank, 2009. "Estimation with overidentifying inequality moment conditions," Journal of Econometrics, Elsevier, vol. 153(2), pages 136-154, December.
    6. Bekker, Paul A. & Ploeg, Jan van der, 2000. "Instrumental variable estimation based on grouped data," CCSO Working Papers 200009, University of Groningen, CCSO Centre for Economic Research.
    7. Poskitt, D.S. & Skeels, C.L., 2007. "Approximating the distribution of the two-stage least squares estimator when the concentration parameter is small," Journal of Econometrics, Elsevier, vol. 139(1), pages 217-236, July.
    8. Bianchi, Carlo & Calzolari, Giorgio, 1983. "Standard errors of forecasts in dynamic simulation of nonlinear econometric models: some empirical results," MPRA Paper 22657, University Library of Munich, Germany, revised 1983.
    9. D. S. Poskitt & C. L. Skeels, 2004. "Assessing the Magnitude of the Concentration Parameter in a Simultaneous Equations Model," Monash Econometrics and Business Statistics Working Papers 29/04, Monash University, Department of Econometrics and Business Statistics.
    10. Patrick J. Curran & Kenneth A. Bollen & Feinian Chen & Pamela Paxton & James B. Kirby, 2003. "Finite Sampling Properties of the Point Estimates and Confidence Intervals of the RMSEA," Sociological Methods & Research, , vol. 32(2), pages 208-252, November.
    11. Blomquist, Soren & Dahlberg, Matz, 1999. "Small Sample Properties of LIML and Jackknife IV Estimators: Experiments with Weak Instruments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(1), pages 69-88, Jan.-Feb..
    12. Bianchi, Carlo & Calzolari, Giorgio, 1982. "Evaluating forecast uncertainty due to errors in estimated coefficients: empirical comparison of alternative methods," MPRA Paper 22559, University Library of Munich, Germany.
    13. Yong Bao & Aman Ullah, 2021. "Analytical Finite Sample Econometrics: From A. L. Nagar to Now," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 17-37, December.
    14. Bianchi, Carlo & Calzolari, Giorgio & Weihs, Claus, 1986. "Parametric and nonparametric Monte Carlo estimates of standard errors of forecasts in econometric models," MPRA Paper 29120, University Library of Munich, Germany.
    15. Calzolari, Giorgio & Bianchi, Carlo & Corsi, Paolo & Panattoni, Lorenzo, 1982. "Uncertainty of policy recommendations for nonlinear econometric models: some empirical results," MPRA Paper 28846, University Library of Munich, Germany.
    16. John C. Chao & Peter C.B. Phillips, 1996. "Bayesian Posterior Distributions in Limited Information Analysis of the Simultaneous Equations Model Using the Jeffreys Prior," Cowles Foundation Discussion Papers 1137, Cowles Foundation for Research in Economics, Yale University.
    17. Bianchi, Carlo & Calzolari, Giorgio & Brillet, Jean-Louis, 1987. "Measuring forecast uncertainty : A review with evaluation based on a macro model of the French economy," International Journal of Forecasting, Elsevier, vol. 3(2), pages 211-227.
    18. Gao, Chuanming & Lahiri, Kajal, 2000. "Further consequences of viewing LIML as an iterated Aitken estimator," Journal of Econometrics, Elsevier, vol. 98(2), pages 187-202, October.
    19. Maronna, Ricardo A. & Yohai, Víctor J., 1994. "Robust estimation in simultaneous equations models," DES - Working Papers. Statistics and Econometrics. WS 3956, Universidad Carlos III de Madrid. Departamento de Estadística.
    20. Calzolari, Giorgio, 1992. "Stima delle equazioni simultanee non-lineari: una rassegna [Estimation of nonlinear simultaneous equations: a survey]," MPRA Paper 24123, University Library of Munich, Germany, revised 1992.
    21. Chao, John C. & Phillips, Peter C. B., 2002. "Jeffreys prior analysis of the simultaneous equations model in the case with n+1 endogenous variables," Journal of Econometrics, Elsevier, vol. 111(2), pages 251-283, December.
    22. Joaquim Ramalho, 2003. "Small Sample Bias of Alternative Estimation Methods for Moment Condition Models: Monte Carlo Evidence for Covariance Structures and Instrumental Variables," Economics Working Papers 9_2003, University of Évora, Department of Economics (Portugal).
    23. Hendry, David F., 1984. "Monte carlo experimentation in econometrics," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 16, pages 937-976, Elsevier.
    24. T. W. Anderson & Naoto Kunitomo & Yukitoshi Matsushita, 2008. "On Finite Sample Properties of Alternative Estimators of Coefficients in a Structural Equation with Many Instruments," CIRJE F-Series CIRJE-F-577, CIRJE, Faculty of Economics, University of Tokyo.
    25. Gao, Chuanming & Lahiri, Kajal, 2002. "A note on the double k-class estimator in simultaneous equations," Journal of Econometrics, Elsevier, vol. 108(1), pages 101-111, May.
    26. Schorfheide, Frank & Moon, Hyungsik Roger, 2006. "Boosting Your Instruments: Estimation with Overidentifying Inequality Moment Conditions," CEPR Discussion Papers 5605, C.E.P.R. Discussion Papers.
    27. Kenneth A. Bollen & James B. Kirby & Patrick J. Curran & Pamela M. Paxton & Feinian Chen, 2007. "Latent Variable Models Under Misspecification: Two-Stage Least Squares (2SLS) and Maximum Likelihood (ML) Estimators," Sociological Methods & Research, , vol. 36(1), pages 48-86, August.
    28. Douglas Staiger & James H. Stock, 1994. "Instrumental Variables Regression with Weak Instruments," NBER Technical Working Papers 0151, National Bureau of Economic Research, Inc.
    29. Bianchi, Carlo & Calzolari, Giorgio, 1983. "Confidence intervals of forecasts from nonlinear econometric models," MPRA Paper 29025, University Library of Munich, Germany.
    30. Chao, J. C. & Phillips, P. C. B., 1998. "Posterior distributions in limited information analysis of the simultaneous equations model using the Jeffreys prior," Journal of Econometrics, Elsevier, vol. 87(1), pages 49-86, August.
    31. Joaquim Ramalho, 2005. "Feasible bias-corrected OLS, within-groups, and first-differences estimators for typical micro and macro AR(1) panel data models," Empirical Economics, Springer, vol. 30(3), pages 735-748, October.
    32. D. S. Poskitt & C. L. Skeels, 2004. "Approximating the Distribution of the Instrumental Variables Estimator when the Concentration Parameter is Small," Monash Econometrics and Business Statistics Working Papers 19/04, Monash University, Department of Econometrics and Business Statistics.
    33. Oberhelman, Dennis & Rao Kadiyala, K., 2000. "Asymptotic probability concentrations and finite sample properties of modified LIML estimators for equations with more than two endogenous variables," Journal of Econometrics, Elsevier, vol. 98(1), pages 163-185, September.

  22. Mariano, Roberto S, 1977. "Finite Sample Properties of Instrumental Variable Estimators of Structural Coefficients," Econometrica, Econometric Society, vol. 45(2), pages 487-496, March.

    Cited by:

    1. Poskitt, D.S. & Skeels, C.L., 2007. "Approximating the distribution of the two-stage least squares estimator when the concentration parameter is small," Journal of Econometrics, Elsevier, vol. 139(1), pages 217-236, July.
    2. Peter C.B. Phillips, 1982. "The Exact Distribution of LIML: I," Cowles Foundation Discussion Papers 658, Cowles Foundation for Research in Economics, Yale University.
    3. Peter C.B. Phillips, 1982. "On the Exact Distribution of LIML (revised and extended, see CFDP 658)," Cowles Foundation Discussion Papers 626, Cowles Foundation for Research in Economics, Yale University.
    4. Kenneth A. Bollen & Daniel J. Bauer, 2004. "Automating the Selection of Model-Implied Instrumental Variables," Sociological Methods & Research, , vol. 32(4), pages 425-452, May.
    5. Christopher R. Walters, 2015. "Inputs in the Production of Early Childhood Human Capital: Evidence from Head Start," American Economic Journal: Applied Economics, American Economic Association, vol. 7(4), pages 76-102, October.
    6. D. S. Poskitt & C. L. Skeels, 2004. "Approximating the Distribution of the Instrumental Variables Estimator when the Concentration Parameter is Small," Monash Econometrics and Business Statistics Working Papers 19/04, Monash University, Department of Econometrics and Business Statistics.
    7. Jarque, C.M. & McKenzie, C.R., 1995. "Testing for multivariate normality in simultaneous equations models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 39(3), pages 323-328.

  23. Mariano, Roberto S., 1975. "Some large-concentration-parameter asymptotics for the k-class estimators," Journal of Econometrics, Elsevier, vol. 3(2), pages 171-177, May.

    Cited by:

    1. Martin Emil Jakobsen & Jonas Peters, 2022. "Distributional robustness of K-class estimators and the PULSE [The colonial origins of comparative development: An empirical investigation]," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 404-432.

  24. Mariano, Roberto S, 1973. "Approximations to the Distribution Functions of Theil's K-Class Estimators," Econometrica, Econometric Society, vol. 41(4), pages 715-721, July.

    Cited by:

    1. Michal Kolesár & Raj Chetty & John N. Friedman & Edward L. Glaeser & Guido W. Imbens, 2011. "Identification and Inference with Many Invalid Instruments," NBER Working Papers 17519, National Bureau of Economic Research, Inc.
    2. Guo, Zijian & Kang, Hyunseung & Cai, T. Tony & Small, Dylan S., 2018. "Testing endogeneity with high dimensional covariates," Journal of Econometrics, Elsevier, vol. 207(1), pages 175-187.

  25. Mariano, Roberto S, 1973. "Approximations to the Distribution Functions of the Ordinary Least-Squares and Two-Stage Least-Squares Estimators in the Case of Two Included Endogenous Variables," Econometrica, Econometric Society, vol. 41(1), pages 67-77, January.

    Cited by:

    1. Saman Banafti & Tae-Hwy Lee, 2022. "Inferential Theory for Granular Instrumental Variables in High Dimensions," Papers 2201.06605, arXiv.org, revised Sep 2023.
    2. Jan F. Kiviet, 2013. "Identification and inference in a simultaneous equation under alternative information sets and sampling schemes," Econometrics Journal, Royal Economic Society, vol. 16(1), pages 24-59, February.
    3. Jan F. KIVIET & Jerzy NIEMCZYK, 2013. "On the limiting and empirical distributions of IV estimators when some of the instruments are actually endogenous," Economic Growth Centre Working Paper Series 1311, Nanyang Technological University, School of Social Sciences, Economic Growth Centre.
    4. M. Dolores de Prada & Luis M. Borge, 1997. "Some methods for comparing first-order asymptotically equivalent estimators," Investigaciones Economicas, Fundación SEPI, vol. 21(3), pages 473-500, September.

  26. Mariano, Roberto S, 1972. "The Existence of Moments of the Ordinary Least Squares and Two-Stage Least Squares Estimators," Econometrica, Econometric Society, vol. 40(4), pages 643-652, July.

    Cited by:

    1. Kim, Min Seong & Sun, Yixiao, 2013. "Heteroskedasticity and spatiotemporal dependence robust inference for linear panel models with fixed effects," Journal of Econometrics, Elsevier, vol. 177(1), pages 85-108.
    2. Iglesias, Emma M. & Phillips, Garry D.A., 2011. "Almost Unbiased Estimation in Simultaneous Equations Models with Strong and / or Weak Instruments," Cardiff Economics Working Papers E2011/19, Cardiff University, Cardiff Business School, Economics Section.
    3. Koen Jochmans, 2023. "Peer effects and endogenous social interactions," Post-Print hal-04164668, HAL.
    4. Martin Emil Jakobsen & Jonas Peters, 2022. "Distributional robustness of K-class estimators and the PULSE [The colonial origins of comparative development: An empirical investigation]," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 404-432.
    5. Kenneth A. Bollen & James B. Kirby & Patrick J. Curran & Pamela M. Paxton & Feinian Chen, 2007. "Latent Variable Models Under Misspecification: Two-Stage Least Squares (2SLS) and Maximum Likelihood (ML) Estimators," Sociological Methods & Research, , vol. 36(1), pages 48-86, August.
    6. Chao, J. C. & Phillips, P. C. B., 1998. "Posterior distributions in limited information analysis of the simultaneous equations model using the Jeffreys prior," Journal of Econometrics, Elsevier, vol. 87(1), pages 49-86, August.

Chapters

  1. Delano S Villanueva & Roberto S Mariano & Diwa C Guinigundo & Abbas Mirakhor, 2023. "Openness, Human Development, and Fiscal Policies," World Scientific Book Chapters, in: Economic Adjustment and Growth Theory and Practice, chapter 6, pages 119-165, World Scientific Publishing Co. Pte. Ltd..

    Cited by:

    1. Mr. Philip R. Gerson, 1998. "The Impact of Fiscal Policy Variables on Output Growth," IMF Working Papers 1998/001, International Monetary Fund.
    2. Robert Holzmann & Christian Thimann & Angela Petz, 1994. "Pressure to Adjust: Consequences for the OECD Countries from Reforms in Eastern Europe," International Trade 9403001, University Library of Munich, Germany.
    3. Holzmann, Robert, 1996. "Fiscal issues of shifting from unfunded to funded pension," Sede de la CEPAL en Santiago (Estudios e Investigaciones) 34300, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
    4. Delano S Villanueva & Roberto S Mariano & Diwa C Guinigundo & Abbas Mirakhor, 2023. "A Modified Neoclassical Growth Model with Endogenous Labor Participation," World Scientific Book Chapters, in: Economic Adjustment and Growth Theory and Practice, chapter 3, pages 44-64, World Scientific Publishing Co. Pte. Ltd..

  2. Delano S Villanueva & Roberto S Mariano & Diwa C Guinigundo & Abbas Mirakhor, 2023. "A Modified Neoclassical Growth Model with Endogenous Labor Participation," World Scientific Book Chapters, in: Economic Adjustment and Growth Theory and Practice, chapter 3, pages 44-64, World Scientific Publishing Co. Pte. Ltd..

    Cited by:

    1. Delano S Villanueva & Roberto S Mariano & Diwa C Guinigundo & Abbas Mirakhor, 2023. "Finance and Endogenous Growth," World Scientific Book Chapters, in: Economic Adjustment and Growth Theory and Practice, chapter 5, pages 96-118, World Scientific Publishing Co. Pte. Ltd..

  3. Delano S Villanueva & Roberto S Mariano & Diwa C Guinigundo & Abbas Mirakhor, 2023. "Testing the Neoclassical Theory of Economic Growth: A Panel Data Approach," World Scientific Book Chapters, in: Economic Adjustment and Growth Theory and Practice, chapter 2, pages 10-43, World Scientific Publishing Co. Pte. Ltd..

    Cited by:

    1. AfDB AfDB, 2016. "North Africa - Working paper – Public Investment and Growth in the Maghreb Countries," Working Paper Series 2335, African Development Bank.
    2. Etsuro Shioji, 1997. "It's still 2%: evidence on convergence from 116 years of the US States panel data," Economics Working Papers 236, Department of Economics and Business, Universitat Pompeu Fabra.
    3. Kurt A. Hafner & David Mayer-Foulkes, 2012. "Fertility, Human Development, and Economic Growth: Long- term Short-term Causal Links," DEGIT Conference Papers c017_024, DEGIT, Dynamics, Economic Growth, and International Trade.
    4. Neil R. Ericsson & John S. Irons & Ralph W. Tryon, 2001. "Output and inflation in the long run," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 241-253.
    5. Lee, Angela Y. & Aaker, Jennifer L., 2006. "A Monte Carlo Study of Growth Regressions," Research Papers 1836r1, Stanford University, Graduate School of Business.
    6. Jérôme Creel & Francesco Saraceno & Paola Veroni, 2007. "Has the Golden Rule of Public Finance Made a difference in the UK," Sciences Po publications 2007-13, Sciences Po.
    7. Mr. Dhaneshwar Ghura, 1997. "Private Investment and Endogenous Growth: Evidence From Cameroon," IMF Working Papers 1997/165, International Monetary Fund.
    8. Shi, Yingying, 2012. "The Role of Infrastructure Capital in China’s Regional Economic Growth," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126547, International Association of Agricultural Economists.
    9. de la Fuente, Angel, 2000. "Convergence Across Countries And Regions: Theory And Empirics," CEPR Discussion Papers 2465, C.E.P.R. Discussion Papers.
    10. Awaworyi Churchill Sefa & Ugur Mehmet & Yew Siew Ling, 2017. "Government education expenditures and economic growth: a meta-analysis," The B.E. Journal of Macroeconomics, De Gruyter, vol. 17(2), pages 1-17, June.
    11. Chirwa, Themba Gilbert & Odhiambo, Nicholas Mbaya, 2016. "An empirical test of the exogenous growth models: Evidence from three Southern African countries," Working Papers 21083, University of South Africa, Department of Economics.
    12. Yves Abessolo, 2005. "Ouverture commerciale : condition de la contribution effective du capital humain à la croissance économique des pays en développement," Documents de travail 109, Groupe d'Economie du Développement de l'Université Montesquieu Bordeaux IV.
    13. Mr. Dhaneshwar Ghura & E. Murat Ucer & Mr. Martin Mühleisen & Mr. Michael T. Hadjimichael & Mr. Roger Nord, 1994. "Effects of Macroeconomic Stabilityon Growth, Savings, and Investment in Sub-Saharan Africa: An Empirical Investigation," IMF Working Papers 1994/098, International Monetary Fund.
    14. Chirwa, Themba G. & Odhiambo, Nicholas M., 2016. "What Drives Long-Run Economic Growth? Empirical Evidence from South Africa," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 69(4), pages 429-456.
    15. Angel de la Fuente & Antonio Ciccone, 2003. "Human capital in a global and knowledge-based economy," Working Papers 70, Barcelona School of Economics.
    16. Jesús Rodríguez López & Diego Martínez López & Diego Romero de Ávila Torrijos, 2006. "Persistence in inequalities across the Spanish regions," Working Papers 06.07, Universidad Pablo de Olavide, Department of Economics.
    17. Mie Augier & Robert McNab & Jerry Guo & Phillip Karber, 2017. "Defense spending and economic growth: evidence from China, 1952–2012," Defence and Peace Economics, Taylor & Francis Journals, vol. 28(1), pages 65-90, January.
    18. Markus Eberhardt & Francis Teal, 2011. "Econometrics For Grumblers: A New Look At The Literature On Cross‐Country Growth Empirics," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 109-155, February.
    19. Javier Andrés & Ignacio Hernando & J. David López-Salido, 1999. "The Role of the Financial System in the Growth-Inflation Link: the OECD Experience," Working Papers 9920, Banco de España.
    20. Celine Kauffmann, 2000. "The interactive effect of trade and education on growth," Post-Print halshs-03721622, HAL.
    21. Giorgio d'Agostino & Luca Pieroni & J Paul Dunne, 2010. "Assessing the Effects of Military Expenditure on Growth," Working Papers 1012, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
    22. M.Mete Doganay, 2003. "Forecasting the Volatilities and Covariances of ISE Government Debt Securities Indices," Istanbul Stock Exchange Review, Research and Business Development Department, Borsa Istanbul, vol. 7(27), pages 15-34.
    23. Arsham Reisinezhad, 2020. "Absorption capacity and Natural Resource Curse," Working Papers halshs-03012661, HAL.
    24. Jean-Claude Berthelémy & Sophie Chauvin, 2000. "Structural Changes in Asia and Growth Prospects After the Crisis," Working Papers 2000-09, CEPII research center.
    25. Omay, Tolga & Öznur Kan, Elif, 2010. "Re-examining the threshold effects in the inflation-growth nexus with cross-sectionally dependent non-linear panel: Evidence from six industrialized economies," Economic Modelling, Elsevier, vol. 27(5), pages 996-1005, September.
    26. Bouton, L. & Sumlinski, M.A., 2000. "Trends in Private Investment in Developing Countries. Statistics for 1970-1998," Papers 41, World Bank - International Finance Corporation.
    27. Gabriele Tondl & Harald Badinger & Werner Müller, 2003. "Regional convergence in the European Union (1985-1999). A spatial dynamic panel analysis," ERSA conference papers ersa03p455, European Regional Science Association.
    28. Funke, Michael & Strulik, Holger, 1999. "Regional growth in West Germany: convergence or divergence?," Economic Modelling, Elsevier, vol. 16(4), pages 489-502, December.
    29. Chirwa Themba G. & Odhiambo Nicholas M., 2016. "Macroeconomic Determinants of Economic Growth: A Review of International Literature," South East European Journal of Economics and Business, Sciendo, vol. 11(2), pages 33-47, December.
    30. Elbadawi, Ibrahim A, 2005. "Reviving Growth in the Arab World," Economic Development and Cultural Change, University of Chicago Press, vol. 53(2), pages 293-326, January.
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  4. Roberto S. Mariano & Suleyman Ozmucur, 2018. "High-mixed-frequency forecasting models for GDP and inflation," World Scientific Book Chapters, in: Peter Pauly (ed.), Global Economic Modeling A Volume in Honor of Lawrence R. Klein, chapter 2, pages 2-29, World Scientific Publishing Co. Pte. Ltd..

    Cited by:

    1. Roberto S. Mariano & Suleyman Ozmucur, 2021. "Predictive Performance of Mixed-Frequency Nowcasting and Forecasting Models (with Application to Philippine Inflation and GDP Growth)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 383-400, December.

  5. Richard Green & Roberto Mariano & Andrey Pavlov & Susan Wachter, 2009. "Misaligned Incentives and Mortgage Lending in Asia," NBER Chapters, in: Financial Sector Development in the Pacific Rim, pages 95-111, National Bureau of Economic Research, Inc.
    See citations under working paper version above.
  6. Delano P. Villanueva & Roberto S. Mariano, 2007. "External Debt, Adjustment, and Growth," NBER Chapters, in: Fiscal Policy and Management in East Asia, pages 199-221, National Bureau of Economic Research, Inc.
    See citations under working paper version above.
  7. Roberto S Mariano Delano & Delano P Villanueva, 2006. "Monetary policy approaches and implementation in Asia: the Philippines and Indonesia," BIS Papers chapters, in: Bank for International Settlements (ed.), Monetary policy in Asia: approaches and implementation, volume 31, pages 207-226, Bank for International Settlements.

    Cited by:

    1. Kim Edwards & Sahminan, 2008. "Exchange Rate Movements in Indonesia: Determinants, Effects, and Policy Challenges," Working Papers WP/25/2008, Bank Indonesia.
    2. Inoue, Takeshi & Toyoshima, Yuki & Hamori, Shigeyuki, 2012. "Inflation targeting in Korea, Indonesia, Thailand, and the Philippines : the impact on business cycle synchronization between each country and the world," IDE Discussion Papers 328, Institute of Developing Economies, Japan External Trade Organization(JETRO).

Books

  1. Mariano,Roberto & Schuermann,Til & Weeks,Melvyn J. (ed.), 2000. "Simulation-based Inference in Econometrics," Cambridge Books, Cambridge University Press, number 9780521591126.

    Cited by:

    1. Christian Belzil & Arnaud Maurel & Modibo Sidibé, 2021. "Estimating the Value of Higher Education Financial Aid: Evidence from a Field Experiment," Journal of Labor Economics, University of Chicago Press, vol. 39(2), pages 361-395.
    2. Aguirregabiria, Victor & Mira, Pedro, 2010. "Dynamic discrete choice structural models: A survey," Journal of Econometrics, Elsevier, vol. 156(1), pages 38-67, May.
    3. Arvanitis Stelios & Demos Antonis, 2018. "On the Validity of Edgeworth Expansions and Moment Approximations for Three Indirect Inference Estimators," Journal of Econometric Methods, De Gruyter, vol. 7(1), pages 1-38, January.
    4. Nathalie Havet, 2006. "La valorisation salariale et professionnelle de la formation en entreprise diffère-t-elle selon le sexe ? : l’exemple canadien," Working Papers 0602, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    5. Pablo Mitnik & Sunyoung Baek, 2013. "The Kumaraswamy distribution: median-dispersion re-parameterizations for regression modeling and simulation-based estimation," Statistical Papers, Springer, vol. 54(1), pages 177-192, February.
    6. Matteo Richiardi, 2003. "The Promises and Perils of Agent-Based Computational Economics," LABORatorio R. Revelli Working Papers Series 29, LABORatorio R. Revelli, Centre for Employment Studies.
    7. Samuel Hurtado, 2013. "DSGE Models and the Lucas critique," Working Papers 1310, Banco de España.
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    9. Dennis Kristensen & Bernard Salanie, 2013. "Higher-order properties of approximate estimators," CeMMAP working papers 45/13, Institute for Fiscal Studies.
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    11. Rousselière, Damien & Rousselière, Samira, 2010. "On the impact of trust on consumer willingness to purchase GM food:Evidence from a European survey," Review of Agricultural and Environmental Studies - Revue d'Etudes en Agriculture et Environnement (RAEStud), Institut National de la Recherche Agronomique (INRA), vol. 91(1).
    12. Aiste Ruseckaite & Dennis Fok & Peter Goos, 2016. "Flexible Mixture-Amount Models for Business and Industry using Gaussian Processes," Tinbergen Institute Discussion Papers 16-075/III, Tinbergen Institute.
    13. Aguirregabiria, Victor & Magesan, Arvind, 2013. "Euler Equations for the Estimation of Dynamic Discrete Choice Structural," MPRA Paper 46056, University Library of Munich, Germany.
    14. Sumeetpal S. Singh & Nicolas Chopin & Nick Whiteley, 2010. "Bayesian Learning of Noisy Markov Decision Processes," Working Papers 2010-36, Center for Research in Economics and Statistics.
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    16. Canova, Fabio & Ciccarelli, Matteo, 2013. "Panel Vector Autoregressive Models: A Survey," CEPR Discussion Papers 9380, C.E.P.R. Discussion Papers.
    17. Vázquez Pérez, Jesús & María-Dolores, Ramón & Londoño Yarce, Juan Miguel, 2012. "The Effect of Data Revisions on the Basic New Keynesian Model," DFAEII Working Papers 1988-088X, University of the Basque Country - Department of Foundations of Economic Analysis II.
    18. Peter C.B. Phillips, 2011. "Folklore Theorems, Implicit Maps and New Unit Root Limit Theory," Cowles Foundation Discussion Papers 1781, Cowles Foundation for Research in Economics, Yale University.
    19. Hielke Buddelmeyer & Kenneth Troske, 2004. "Joint estimation of sequential labor force participation and fertility decisions using Markov chain Monte Carlo techniques," Econometric Society 2004 North American Winter Meetings 334, Econometric Society.
    20. Giorgio Calzolari & Laura Neri, 2010. "The Method of Simulated Scores for Estimating Multinormal Regression Models with Missing Values," Econometrics Working Papers Archive wp2010_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    21. Peter Winker & Manfred Gilli & Vahidin Jeleskovic, 2007. "An Objective Function for Simulation Based Inference on Exchange Rate Data," Swiss Finance Institute Research Paper Series 07-01, Swiss Finance Institute.
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    24. Peter C.B. Phillips & Yangru Wu & Jun Yu, 2009. "Explosive Behavior in the 1990s Nasdaq: When Did Exuberance Escalate Asset Values?," Cowles Foundation Discussion Papers 1699, Cowles Foundation for Research in Economics, Yale University.
    25. Xiaojin Sun & Kwok Ping Tsang, 2018. "The impact of monetary policy on local housing markets: Do regulations matter?," Empirical Economics, Springer, vol. 54(3), pages 989-1015, May.
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    31. Keane, M.P. & Thorp, S., 2016. "Complex Decision Making," Handbook of the Economics of Population Aging, in: Piggott, John & Woodland, Alan (ed.), Handbook of the Economics of Population Aging, edition 1, volume 1, chapter 0, pages 661-709, Elsevier.
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    50. Ching, Andrew, 2008. "Consumer Learning and Heterogeneity: Dynamics of Demand for Prescription Drugs after Patent Expiration," MPRA Paper 7265, University Library of Munich, Germany.
    51. Geweke, John & Tanizaki, Hisashi, 2001. "Bayesian estimation of state-space models using the Metropolis-Hastings algorithm within Gibbs sampling," Computational Statistics & Data Analysis, Elsevier, vol. 37(2), pages 151-170, August.
    52. Dennis Kristensen & Bernard Salanié, 2010. "Higher Order Improvements for Approximate Estimators," CAM Working Papers 2010-04, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
    53. Yu, Jun, 2014. "Econometric Analysis Of Continuous Time Models: A Survey Of Peter Phillips’S Work And Some New Results," Econometric Theory, Cambridge University Press, vol. 30(4), pages 737-774, August.
    54. Daziano, Ricardo A. & Achtnicht, Martin, 2014. "Accounting for uncertainty in willingness to pay for environmental benefits," Energy Economics, Elsevier, vol. 44(C), pages 166-177.
    55. Pierre Mohnen & Lars-Hendrick Röller, 2001. "Complementarities in Innovation Policy," CIRANO Working Papers 2001s-28, CIRANO.
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    57. Panle Jia Barwick & Parag A. Pathak, 2011. "The Costs of Free Entry: An Empirical Study of Real Estate Agents in Greater Boston," NBER Working Papers 17227, National Bureau of Economic Research, Inc.
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    59. Grazzini, Jakob & Richiardi, Matteo, 2013. "Consistent Estimation of Agent-Based Models by Simulated Minimum Distance," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201335, University of Turin.
    60. Michelle Sovinsky Goeree, 2005. "Advertising in the US Personal Computer Industry," Industrial Organization 0503002, University Library of Munich, Germany.
    61. Canova, Fabio & Ciccarelli, Matteo & Ortega, Eva, 2012. "Do institutional changes affect business cycles? Evidence from Europe," Journal of Economic Dynamics and Control, Elsevier, vol. 36(10), pages 1520-1533.
    62. Fontana, Magda & Iori, Martina & Nava, Consuelo Rubina, 2019. "Switching behavior in the Italian electricity retail market: Logistic and mixed effect Bayesian estimations of consumer choice," Energy Policy, Elsevier, vol. 129(C), pages 339-351.
    63. Richard A. Davis & Thiago do Rêgo Sousa & Claudia Klüppelberg, 2021. "Indirect inference for time series using the empirical characteristic function and control variates," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(5-6), pages 653-684, September.
    64. Vázquez Pérez, Jesús, 2006. "The Importance of Stock Market Returns in Estimated Monetary Policy Rules: a Structural Approach," DFAEII Working Papers 1988-088X, University of the Basque Country - Department of Foundations of Economic Analysis II.
    65. Belzil, Christian & Hansen, Jörgen & Liu, Xingfei, 2017. "Dynamic Skill Accumulation, Education Policies and the Return to Schooling," IZA Discussion Papers 10613, Institute of Labor Economics (IZA).
    66. Vicky Fasen‐Hartmann & Sebastian Kimmig, 2020. "Robust estimation of stationary continuous‐time arma models via indirect inference," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(5), pages 620-651, September.
    67. Alan L. Montgomery & Shibo Li & Kannan Srinivasan & John C. Liechty, 2004. "Modeling Online Browsing and Path Analysis Using Clickstream Data," Marketing Science, INFORMS, vol. 23(4), pages 579-595, November.
    68. DEMOS Antonis, & KYRIAKOPOULOU Dimitra,, 2018. "Finite sample theory and bias correction of maximum likelihood estimators in the EGARCH model," LIDAM Discussion Papers CORE 2018007, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    69. Anindya Ghose & Sang Pil Han, 2009. "A Dynamic Structural Model of User Learning in Mobile Media Content," Working Papers 09-24, NET Institute, revised Oct 2009.
    70. Gould, Brian W. & Yen, Steven T., 2002. "Food Demand In Mexico: A Quasi-Maximum Likelihood Approach," 2002 Annual meeting, July 28-31, Long Beach, CA 19667, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    71. Jun Yu, 2009. "Econometric Analysis of Continuous Time Models : A Survey of Peter Phillips’ Work and Some New Results," Microeconomics Working Papers 23046, East Asian Bureau of Economic Research.
    72. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2014. "A Simple Method to Estimate the Roles of Learning, Inventories and Category Consideration in Consumer Choice," Economics Papers 2014-W01, Economics Group, Nuffield College, University of Oxford.
    73. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2017. "Empirical Models of Learning Dynamics: A Survey of Recent Developments," International Series in Operations Research & Management Science, in: Berend Wierenga & Ralf van der Lans (ed.), Handbook of Marketing Decision Models, edition 2, chapter 0, pages 223-257, Springer.
    74. David J. Lewis & Andrew J. Plantinga, 2007. "Policies for Habitat Fragmentation: Combining Econometrics with GIS-Based Landscape Simulations," Land Economics, University of Wisconsin Press, vol. 83(2), pages 109-127.
    75. Jacob Grazzini & Matteo Richiardi & Lisa Sella, 2012. "Indirect estimation of agent-based models.An application to a simple diffusion model," LABORatorio R. Revelli Working Papers Series 118, LABORatorio R. Revelli, Centre for Employment Studies.
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