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Yongchen Zhao

Personal Details

First Name:Yongchen
Middle Name:
Last Name:Zhao
Suffix:
RePEc Short-ID:pzh331
[This author has chosen not to make the email address public]
Department of Economics Towson University 8000 York Road Maryland, 21252, USA

Affiliation

Department of Economics
Towson University

Towson, Maryland (United States)
http://towson.edu/cbe/departments/economics/
RePEc:edi:detowus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Gabriel Mathy & Yongchen Zhao, 2023. "Could Diffusion Indexes Have Forecasted the Great Depression?," Working Papers 2023-05, Towson University, Department of Economics, revised Sep 2023.
  2. Yongchen Zhao, 2023. "Uncertainty of Household Inflation Expectations: Reconciling Point and Density Forecasts," Working Papers 2023-09, Towson University, Department of Economics, revised Dec 2023.
  3. Yongchen Zhao, 2021. "Uncertainty and Disagreement of Inflation Expectations: Evidence from Household-Level Qualitative Survey Responses," Working Papers 2021-03, Towson University, Department of Economics, revised Dec 2021.
  4. Kajal Lahiri & Yongchen Zhao, 2020. "The Nordhaus Test with Many Zeros," CESifo Working Paper Series 8350, CESifo.
  5. George Monokroussos & Yongchen Zhao, 2020. "Nowcasting in Real Time Using Popularity Priors," Working Papers 2020-01, Towson University, Department of Economics, revised Feb 2020.
  6. Yongchen Zhao, 2019. "Updates to Household Inflation Expectations: Signal or Noise?," Working Papers 2019-01, Towson University, Department of Economics, revised May 2019.
  7. Kajal Lahiri & Yongchen Zhao, 2018. "International Propagation of Shocks: A Dynamic Factor Model Using Survey Forecasts," Working Papers 2018-04, Towson University, Department of Economics, revised Sep 2018.
  8. Abhiman Das & Kajal Lahiri & Yongchen Zhao, 2018. "Inflation Expectations in India: Learning from Household Tendency Surveys," Working Papers 2018-03, Towson University, Department of Economics, revised Aug 2018.
  9. Kajal Lahiri & Yongchen Zhao, 2016. "Determinants of Consumer Sentiment over Business Cycles: Evidence from the U.S. Surveys of Consumers," Working Papers 2016-14, Towson University, Department of Economics, revised Jul 2016.
  10. Herman O. Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  11. Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2015. "Forecasting Consumption: The Role of Consumer Confidence in Real Time with many Predictors," Working Papers 2015-02, Towson University, Department of Economics, revised Jul 2015.
  12. Yongchen Zhao, 2015. "Robustness of Forecast Combination in Unstable Environment: A Monte Carlo Study of Advanced Algorithms," Working Papers 2015-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  13. Kajal Lahiri & Yongchen Zhao, 2013. "Quantifying Heterogeneous Survey Expectations: The Carlson-Parkin Method Revisited," Discussion Papers 13-08, University at Albany, SUNY, Department of Economics.
  14. Kajal Lahiri & Huaming Peng & Yongchen Zhao, 2013. "Machine Learning and Forecast Combination in Incomplete Panels," Discussion Papers 13-01, University at Albany, SUNY, Department of Economics.
  15. Kajal Lahiri & Yongchen Zhao, 2013. "Determinants of Consumer Sentiment: Evidence from Household Survey Data," Discussion Papers 13-12, University at Albany, SUNY, Department of Economics.
  16. Kajal Lahiri & Huaming Peng & Yongchen Zhao, 2013. "Testing the Value of Probability Forecasts for Calibrated Combining," Discussion Papers 13-02, University at Albany, SUNY, Department of Economics.
  17. Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2012. "Forecasting Consumption in Real Time: The Role of Consumer Confidence Surveys," Discussion Papers 12-02, University at Albany, SUNY, Department of Economics.
  18. Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2012. "The Yield Spread Puzzle and the Information Content of SPF Forecasts," CESifo Working Paper Series 3949, CESifo.

Articles

  1. Zhao, Yongchen, 2024. "Uncertainty of household inflation expectations: Reconciling point and density forecasts," Economics Letters, Elsevier, vol. 234(C).
  2. Zhao, Yongchen, 2023. "Internal consistency of household inflation expectations: Point forecasts vs. density forecasts," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1713-1735.
  3. Yongchen Zhao, 2022. "Uncertainty and disagreement of inflation expectations: Evidence from household‐level qualitative survey responses," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 810-828, July.
  4. Thomas Rhoads & Yongchen Zhao, 2022. "Sports team performance and revenue of out-of-stadium vending operations," Applied Economics Letters, Taylor & Francis Journals, vol. 29(1), pages 8-11, January.
  5. Yongchen Zhao, 2021. "The robustness of forecast combination in unstable environments: a Monte Carlo study of advanced algorithms," Empirical Economics, Springer, vol. 61(1), pages 173-199, July.
  6. Yongchen Zhao, 2020. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 16(2), pages 77-97, November.
  7. Lahiri, Kajal & Zhao, Yongchen, 2020. "The Nordhaus test with many zeros," Economics Letters, Elsevier, vol. 193(C).
  8. Monokroussos, George & Zhao, Yongchen, 2020. "Nowcasting in real time using popularity priors," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1173-1180.
  9. Zhao, Yongchen, 2019. "Updates to household inflation expectations: Signal or noise?," Economics Letters, Elsevier, vol. 181(C), pages 95-98.
  10. Das, Abhiman & Lahiri, Kajal & Zhao, Yongchen, 2019. "Inflation expectations in India: Learning from household tendency surveys," International Journal of Forecasting, Elsevier, vol. 35(3), pages 980-993.
  11. Lahiri, Kajal & Zhao, Yongchen, 2019. "International propagation of shocks: A dynamic factor model using survey forecasts," International Journal of Forecasting, Elsevier, vol. 35(3), pages 929-947.
  12. Kajal Lahiri & Huaming Peng & Yongchen Zhao, 2017. "Online learning and forecast combination in unbalanced panels," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 257-288, March.
  13. Kajal Lahiri & Yongchen Zhao, 2016. "Determinants of Consumer Sentiment Over Business Cycles: Evidence from the US Surveys of Consumers," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(2), pages 187-215, December.
  14. Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2016. "Forecasting Consumption: the Role of Consumer Confidence in Real Time with many Predictors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1254-1275, November.
  15. Lahiri, Kajal & Peng, Huaming & Zhao, Yongchen, 2015. "Testing the value of probability forecasts for calibrated combining," International Journal of Forecasting, Elsevier, vol. 31(1), pages 113-129.
  16. Lahiri, Kajal & Zhao, Yongchen, 2015. "Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 31(1), pages 51-62.
  17. Kajal Lahiri & Hany A. Shawky & Yongchen Zhao, 2014. "Modeling Hedge Fund Returns: Selection, Nonlinearity and Managerial Efficiency," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 35(2), pages 172-187, March.
  18. Lahiri, Kajal & Monokroussos, George & Zhao, Yongchen, 2013. "The yield spread puzzle and the information content of SPF forecasts," Economics Letters, Elsevier, vol. 118(1), pages 219-221.

Citations

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

Working papers

  1. Yongchen Zhao, 2021. "Uncertainty and Disagreement of Inflation Expectations: Evidence from Household-Level Qualitative Survey Responses," Working Papers 2021-03, Towson University, Department of Economics, revised Dec 2021.

    Cited by:

    1. Zhao, Yongchen, 2024. "Uncertainty of household inflation expectations: Reconciling point and density forecasts," Economics Letters, Elsevier, vol. 234(C).
    2. Xiangdong Shen & Junbin Wang & Li Wang & Chunlan Jiao, 2023. "Forecasting the different influencing factors of household food waste behavior in China under the COVID‐19 pandemic," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2322-2340, December.

  2. Kajal Lahiri & Yongchen Zhao, 2020. "The Nordhaus Test with Many Zeros," CESifo Working Paper Series 8350, CESifo.

    Cited by:

    1. An, Zidong & Liu, Dingqian & Wu, Yuzheng, 2021. "Expectation formation following pandemic events," Economics Letters, Elsevier, vol. 200(C).
    2. Conrad, Christian & Lahiri, Kajal, 2023. "Heterogeneous expectations among professional forecasters," ZEW Discussion Papers 23-062, ZEW - Leibniz Centre for European Economic Research.

  3. George Monokroussos & Yongchen Zhao, 2020. "Nowcasting in Real Time Using Popularity Priors," Working Papers 2020-01, Towson University, Department of Economics, revised Feb 2020.

    Cited by:

    1. Herman Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-15, Towson University, Department of Economics, revised Sep 2016.

  4. Yongchen Zhao, 2019. "Updates to Household Inflation Expectations: Signal or Noise?," Working Papers 2019-01, Towson University, Department of Economics, revised May 2019.

    Cited by:

    1. Kajal Lahiri & Yongchen Zhao, 2020. "The Nordhaus Test with Many Zeros," Working Papers 2020-05, Towson University, Department of Economics, revised Jun 2020.
    2. An, Zidong & Zheng, Xinye, 2023. "Diligent forecasters can make accurate predictions despite disagreeing with the consensus," Economic Modelling, Elsevier, vol. 125(C).

  5. Kajal Lahiri & Yongchen Zhao, 2018. "International Propagation of Shocks: A Dynamic Factor Model Using Survey Forecasts," Working Papers 2018-04, Towson University, Department of Economics, revised Sep 2018.

    Cited by:

    1. Johanna Garnitz & Robert Lehmann & Klaus Wohlrabe, 2019. "Forecasting GDP all over the world using leading indicators based on comprehensive survey data," Applied Economics, Taylor & Francis Journals, vol. 51(54), pages 5802-5816, November.
    2. Beckmann, Joscha, 2021. "Measurement and effects of euro/dollar exchange rate uncertainty," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 773-790.
    3. Beckmann, Joscha & Czudaj, Robert L., 2022. "Perceived monetary policy uncertainty," MPRA Paper 114964, University Library of Munich, Germany.
    4. Sin Yee Lee & Zulkefly Abdul Karim & Norlin Khalid & Mohd Azlan Shah Zaidi, 2022. "The Spillover Effects of Chinese Shocks on the Belt and Road Initiative Economies: New Evidence Using Panel Vector Autoregression," Mathematics, MDPI, vol. 10(14), pages 1-18, July.
    5. Beckmann, Joscha & Davidson, Sharada Nia & Koop, Gary & Schüssler, Rainer, 2023. "Cross-country uncertainty spillovers: Evidence from international survey data," Journal of International Money and Finance, Elsevier, vol. 130(C).

  6. Abhiman Das & Kajal Lahiri & Yongchen Zhao, 2018. "Inflation Expectations in India: Learning from Household Tendency Surveys," Working Papers 2018-03, Towson University, Department of Economics, revised Aug 2018.

    Cited by:

    1. Sheen, Jeffrey & Wang, Ben Zhe, 2021. "Measuring macroeconomic disagreement – A mixed frequency approach," Journal of Economic Behavior & Organization, Elsevier, vol. 189(C), pages 547-566.
    2. Oscar Claveria, 2020. "Business and consumer uncertainty in the face of the pandemic: A sector analysis in European countries," Papers 2012.02091, arXiv.org.
    3. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    4. Ashima Goyal & Prashant Parab, 2019. "Modeling heterogeneity and rationality of inflation expectations across Indian households," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2019-02, Indira Gandhi Institute of Development Research, Mumbai, India.
    5. Pooja Kapoor & Sujata Kar, 2022. "A Critical Evaluation of the Consumer Confidence Survey from India," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 7, pages 172-198.
    6. Ashima Goyal & Prashant Mehul Parab, 2019. "Modeling Consumers' Confidence and Inflation Expectations," Economics Bulletin, AccessEcon, vol. 39(3), pages 1817-1832.
    7. Gaurav Kumar Singh & Tathagata Bandyopadhyay, 2024. "Determinants of disagreement: Learning from inflation expectations survey of households," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 326-343, March.
    8. Yongchen Zhao, 2022. "Uncertainty and disagreement of inflation expectations: Evidence from household‐level qualitative survey responses," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 810-828, July.
    9. Young Bin Ahn & Yoichi Tsuchiya, 2022. "Consumer’s perceived and expected inflation in Japan—irrationality or asymmetric loss?," Empirical Economics, Springer, vol. 63(3), pages 1247-1292, September.

  7. Kajal Lahiri & Yongchen Zhao, 2016. "Determinants of Consumer Sentiment over Business Cycles: Evidence from the U.S. Surveys of Consumers," Working Papers 2016-14, Towson University, Department of Economics, revised Jul 2016.

    Cited by:

    1. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2021. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Working Papers 2021-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    2. Hardik A. Marfatia & Christophe Andre & Rangan Gupta, 2020. "Predicting Housing Market Sentiment: The Role of Financial, Macroeconomic and Real Estate Uncertainties," Working Papers 202061, University of Pretoria, Department of Economics.
    3. Wang, Ben Zhe & Sheen, Jeffrey & Trück, Stefan & Chao, Shih-Kang & Härdle, Wolfgang Karl, 2020. "A Note On The Impact Of News On Us Household Inflation Expectations," Macroeconomic Dynamics, Cambridge University Press, vol. 24(4), pages 995-1015, June.
    4. Daniel Borup & Jorge Wolfgang Hansen & Benjamin Dybro Liengaard & Erik Christian Montes Schütte, 2023. "Quantifying investor narratives and their role during COVID‐19," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 512-532, June.
    5. Sorić, Petar & Lolić, Ivana & Claveria, Oscar & Monte, Enric & Torra, Salvador, 2019. "Unemployment expectations: A socio-demographic analysis of the effect of news," Labour Economics, Elsevier, vol. 60(C), pages 64-74.
    6. Petar Sorić & Mirjana Čižmešija & Marina Matošec, 2020. "EU Consumer Confidence and the New Modesty Hypothesis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 152(3), pages 899-921, December.
    7. Zhao, Yongchen, 2019. "Updates to household inflation expectations: Signal or noise?," Economics Letters, Elsevier, vol. 181(C), pages 95-98.
    8. An, Zidong & Liu, Dingqian & Wu, Yuzheng, 2021. "Expectation formation following pandemic events," Economics Letters, Elsevier, vol. 200(C).
    9. E. Balatskiy V. & M. Yurevich A. & Е. Балацкий В. & М. Юревич А., 2018. "Прогнозирование инфляции: практика использования синтетических процедур // Inflation Forecasting: The Practice of Using Synthetic Procedures," Мир новой экономики // The world of new economy, Финансовый университет при Правительстве Российской Федерации // Financial University under The Governtment оf The Russian Federation, vol. 12(4), pages 20-31.
    10. Richard T. Curtin, 2022. "A New Theory of Expectations," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(3), pages 239-259, November.
    11. Camilo Alberto Cárdenas-Hurtado & María Alejandra Hernández-Montes, 2019. "Understanding the Consumer Confidence Index in Colombia: A structural FAVAR analysis," Borradores de Economia 1063, Banco de la Republica de Colombia.
    12. Douglas de Medeiros Franco, 2022. "Expectations, Economic Uncertainty, and Sentiment," RAC - Revista de Administração Contemporânea (Journal of Contemporary Administration), ANPAD - Associação Nacional de Pós-Graduação e Pesquisa em Administração, vol. 26(5), pages 210029-2100.
    13. Liudmila Kitrar & Tamara Lipkind & Georgy Ostapkovich, 2019. "Information Content Of The Russian Services Surveys," HSE Working papers WP BRP 93/STI/2019, National Research University Higher School of Economics.
    14. Petar Soric & Mateo Zokalj & Marija Logarusic, 2020. "Economic determinants of Croatian consumer confidence: real estate prices vs. macroeconomy," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 18(2B), pages 240-257.
    15. Das, Abhiman & Lahiri, Kajal & Zhao, Yongchen, 2019. "Inflation expectations in India: Learning from household tendency surveys," International Journal of Forecasting, Elsevier, vol. 35(3), pages 980-993.
    16. Yongchen Zhao, 2022. "Uncertainty and disagreement of inflation expectations: Evidence from household‐level qualitative survey responses," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 810-828, July.
    17. Allen N. Berger & Felix Irresberger & Raluca A. Roman, 2020. "Bank Size and Household Financial Sentiment: Surprising Evidence from University of Michigan Surveys of Consumers," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(S1), pages 149-191, October.
    18. Marwane El Alaoui & Elie Bouri & Nehme Azoury, 2020. "The Determinants of the U.S. Consumer Sentiment: Linear and Nonlinear Models," IJFS, MDPI, vol. 8(3), pages 1-13, July.

  8. Herman O. Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.

    Cited by:

    1. Gabriel Mathy & Yongchen Zhao, 2023. "Could Diffusion Indexes Have Forecasted the Great Depression?," Working Papers 2023-05, Towson University, Department of Economics, revised Sep 2023.

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

    Cited by:

    1. Christian Gayer & Alessandro Girardi & Andreas Reuter, 2016. "Replacing Judgment by Statistics: Constructing Consumer Confidence Indicators on the basis of Data-driven Techniques. The Case of the Euro Area," Working Papers LuissLab 16125, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    2. Aneta Maria Kłopocka, 2017. "Does Consumer Confidence Forecast Household Saving and Borrowing Behavior? Evidence for Poland," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 133(2), pages 693-717, September.
    3. Hashmat Khan & Santosh Upadhayaya, 2017. "Does Business Confidence Matter for Investment?," Carleton Economic Papers 17-13, Carleton University, Department of Economics, revised 20 Mar 2019.
    4. Chandra Utama & Insukindro & Ardyanto Fitrady, 2022. "Fiscal And Monetary Policy Interactions In Indonesia During Periods Of Economic Turmoil In The Us: 2001q1-2014q4," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 25(1), pages 97-116, June.
    5. Kajal Lahiri & Yongchen Zhao, 2016. "Determinants of Consumer Sentiment over Business Cycles: Evidence from the U.S. Surveys of Consumers," Working Papers 2016-14, Towson University, Department of Economics, revised Jul 2016.
    6. Zhongchen Song & Tom Coupé, 2022. "Predicting Chinese consumption series with Baidu," Working Papers in Economics 22/19, University of Canterbury, Department of Economics and Finance.
    7. de Bondt, Gabe & Gieseck, Arne & Zekaite, Zivile & Herrero, Pablo, 2019. "Disaggregate income and wealth effects in the largest euro area countries," Working Paper Series 2343, European Central Bank.
    8. Tony Chernis & Calista Cheung & Gabriella Velasco, 2017. "A Three-Frequency Dynamic Factor Model for Nowcasting Canadian Provincial GDP Growth," Discussion Papers 17-8, Bank of Canada.
    9. Acuña, Guillermo, 2017. "Evaluación de la capacidad predictiva del índice de percepción del consumidor [Assessing the predictive power of the consumer perception index]," MPRA Paper 83154, University Library of Munich, Germany.
    10. Marina Matosec & Zdenka Obuljen Zoricic, 2019. "Identifying the Interdependence between Consumer Confidence and Macroeconomic Developments in Croatia," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 17(2-B), pages 345-354.
    11. Diego Chávez & Javier E. Contreras-Reyes & Byron J. Idrovo-Aguirre, 2022. "A Threshold GARCH Model for Chilean Economic Uncertainty," JRFM, MDPI, vol. 16(1), pages 1-15, December.
    12. Francisco Corona & Pilar Poncela & Esther Ruiz, 2017. "Determining the number of factors after stationary univariate transformations," Empirical Economics, Springer, vol. 53(1), pages 351-372, August.
    13. Juhro, Solikin M. & Iyke, Bernard Njindan, 2020. "Consumer confidence and consumption expenditure in Indonesia," Economic Modelling, Elsevier, vol. 89(C), pages 367-377.
    14. Lenka Mynaříková & Vít Pošta, 2023. "The Effect of Consumer Confidence and Subjective Well-being on Consumers’ Spending Behavior," Journal of Happiness Studies, Springer, vol. 24(2), pages 429-453, February.
    15. Dimitra Kontana & Fotios Siokis, 2019. "Revisiting the Relationship between Financial Wealth, Housing Wealth, and Consumption: A Panel Analysis for the U.S," Discussion Paper Series 2019_03, Department of Economics, University of Macedonia, revised May 2019.
    16. Tony Chernis & Rodrigo Sekkel, 2017. "A dynamic factor model for nowcasting Canadian GDP growth," Empirical Economics, Springer, vol. 53(1), pages 217-234, August.
    17. Aneta M. Klopocka & Rumiana Gorska, 2021. "Forecasting Household Saving Rate with Consumer Confidence Indicator and its Components: Panel Data Analysis of 14 European Countries," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 874-898.
    18. Ivana Lolić & Marija Logarušić & Mirjana Čižmešija, 2022. "Recent Revision of the European Consumer Confidence Indicator: Is There any additional Space for Improvement?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 159(3), pages 845-863, February.
    19. Gabe Jacob de Bondt & Arne Gieseck & Zivile Zekaite, 2020. "Thick modelling income and wealth effects: a forecast application to euro area private consumption," Empirical Economics, Springer, vol. 58(1), pages 257-286, January.
    20. van Giesen, Roxanne I. & Pieters, Rik, 2019. "Climbing out of an economic crisis: A cycle of consumer sentiment and personal stress," Journal of Economic Psychology, Elsevier, vol. 70(C), pages 109-124.
    21. Marek Rusnak, 2013. "Nowcasting Czech GDP in Real Time," Working Papers 2013/06, Czech National Bank.
    22. Gustavo Adolfo HERNANDEZ DIAZ & Margarita MARÍN JARAMILLO, 2016. "Pronóstico del Consumo Privado: Usando datos de alta frecuencia para el pronóstico de variables de baja frecuencia," Archivos de Economía 14828, Departamento Nacional de Planeación.
    23. Dimitra Kontana & Fotios Siokis, 2018. "Revisiting the Relationship between Financial Wealth, Housing Wealth, and Consumption: A Panel Analysis for the U.S," J, MDPI, vol. 1(1), pages 1-15, November.
    24. Francisco Corona & Graciela González-Farías & Pedro Orraca, 2017. "A dynamic factor model for the Mexican economy: are common trends useful when predicting economic activity?," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 26(1), pages 1-35, December.
    25. Hector H. Sandoval & Anita N. Walsh, 2021. "The role of consumer confidence in forecasting consumption, evidence from Florida," Southern Economic Journal, John Wiley & Sons, vol. 88(2), pages 757-788, October.
    26. Jean-Paul L’Huillier & Robert Waldmann & Donghoon Yoo, 2021. "What Is Consumer Confidence?," ISER Discussion Paper 1135r, Institute of Social and Economic Research, Osaka University, revised Dec 2022.
    27. Alessandro Girardi & Roberto Golinelli & Carmine Pappalardo, 2017. "The role of indicator selection in nowcasting euro-area GDP in pseudo-real time," Empirical Economics, Springer, vol. 53(1), pages 79-99, August.
    28. Hamid Baghestani & Ajalavat Viriyavipart, 2019. "Do factors influencing consumer home-buying attitudes explain output growth?," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 46(5), pages 1104-1115, August.
    29. Wu, Weixing & Zhao, Jing, 2022. "Economic policy uncertainty and household consumption: Evidence from Chinese households," Journal of Asian Economics, Elsevier, vol. 79(C).
    30. Anastasiou, Dimitris & Kallandranis, Christos & Drakos, Konstantinos, 2022. "Borrower discouragement prevalence for Eurozone SMEs: Investigating the impact of economic sentiment," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 161-171.
    31. Vincenzo Merella & Stephen E. Satchell, 2019. "Asset pricing with utility from external anticipation," Carlo Alberto Notebooks 589, Collegio Carlo Alberto.
    32. Hamid Baghestani & Sehar Fatima, 2021. "Growth in US Durables Spending: Assessing the Impact of Consumer Ability and Willingness to Buy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 55-69, April.
    33. Willem Vanlaer & Samantha Bielen & Wim Marneffe, 2020. "Consumer Confidence and Household Saving Behaviors: A Cross-Country Empirical Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 147(2), pages 677-721, January.
    34. Sangyyup Choi & Jaehun Jeong & Dohyeon Park & Donghoon Yoo, 2023. "News or Animal Spirits? Consumer Confidence and Economic Activity: Redux," Working papers 2023rwp-216, Yonsei University, Yonsei Economics Research Institute.
    35. Hashmat Khan & Jean-François Rouillard & Santosh Upadhayaya, 2020. "Consumer Confidence and Household Investment," Cahiers de recherche 20-15, Departement d'économique de l'École de gestion à l'Université de Sherbrooke.
    36. Kevin Moran & Simplice Aimé Nono & Imad Rherrad, 2018. "Forecasting with Many Predictors: How Useful are National and International Confidence Data?," Cahiers de recherche 1814, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    37. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Empirical modelling of survey-based expectations for the design of economic indicators in five European regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 205-227, May.
    38. Abosedra, Salah & Laopodis, Nikiforos T. & Fakih, Ali, 2021. "Dynamics and asymmetries between consumer sentiment and consumption in pre- and during-COVID-19 time: Evidence from the US," The Journal of Economic Asymmetries, Elsevier, vol. 24(C).
    39. Gabriel Mathy & Yongchen Zhao, 2023. "Could Diffusion Indexes Have Forecasted the Great Depression?," Working Papers 2023-05, Towson University, Department of Economics, revised Sep 2023.
    40. Lorenzo Bencivelli & Massimiliano Marcellino & Gianluca Moretti, 2017. "Forecasting economic activity by Bayesian bridge model averaging," Empirical Economics, Springer, vol. 53(1), pages 21-40, August.
    41. Hamid Baghestani, 2017. "Do US consumer survey data help beat the random walk in forecasting mortgage rates?," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1343017-134, January.
    42. Chi-Wei Su & Xian-Li Meng & Ran Tao & Muhammad Umar, 2023. "Chinese consumer confidence: A catalyst for the outbound tourism expenditure?," Tourism Economics, , vol. 29(3), pages 696-717, May.
    43. Baghestani, Hamid, 2021. "Predicting growth in US durables spending using consumer durables-buying attitudes," Journal of Business Research, Elsevier, vol. 131(C), pages 327-336.
    44. Adrian Fernandez‐Perez & Raquel López, 2023. "The effect of macroeconomic news announcements on the implied volatility of commodities: The role of survey releases," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(11), pages 1499-1530, November.

  10. Yongchen Zhao, 2015. "Robustness of Forecast Combination in Unstable Environment: A Monte Carlo Study of Advanced Algorithms," Working Papers 2015-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.

    Cited by:

    1. Constantin Bürgi, 2023. "How to Deal With Missing Observations in Surveys of Professional Forecasters," CESifo Working Paper Series 10203, CESifo.
    2. Fantazzini, Dean & Nigmatullin, Erik & Sukhanovskaya, Vera & Ivliev, Sergey, 2016. "Everything you always wanted to know about bitcoin modelling but were afraid to ask. I," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 44, pages 5-24.
    3. Constantin Bürgi & Tara M. Sinclair, 2015. "A Nonparametric Approach to Identifying a Subset of Forecasters that Outperforms the Simple Average," Working Papers 2015-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    4. Fantazzini, Dean & Nigmatullin, Erik & Sukhanovskaya, Vera & Ivliev, Sergey, 2017. "Everything you always wanted to know about bitcoin modelling but were afraid to ask. Part 2," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 45, pages 5-28.
    5. Herman Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-15, Towson University, Department of Economics, revised Sep 2016.

  11. Kajal Lahiri & Yongchen Zhao, 2013. "Quantifying Heterogeneous Survey Expectations: The Carlson-Parkin Method Revisited," Discussion Papers 13-08, University at Albany, SUNY, Department of Economics.

    Cited by:

    1. Binder, Carola Conces, 2016. "Estimation of historical inflation expectations," Explorations in Economic History, Elsevier, vol. 61(C), pages 1-31.

  12. Kajal Lahiri & Huaming Peng & Yongchen Zhao, 2013. "Machine Learning and Forecast Combination in Incomplete Panels," Discussion Papers 13-01, University at Albany, SUNY, Department of Economics.

    Cited by:

    1. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    2. Wei Qian & Craig A. Rolling & Gang Cheng & Yuhong Yang, 2015. "On the Forecast Combination Puzzle," Papers 1505.00475, arXiv.org.
    3. Cheng, Gang & Yang, Yuhong, 2015. "Forecast combination with outlier protection," International Journal of Forecasting, Elsevier, vol. 31(2), pages 223-237.
    4. Wei Qian & Craig A. Rolling & Gang Cheng & Yuhong Yang, 2019. "On the Forecast Combination Puzzle," Econometrics, MDPI, vol. 7(3), pages 1-26, September.
    5. Graham Elliott, 2017. "Forecast combination when outcomes are difficult to predict," Empirical Economics, Springer, vol. 53(1), pages 7-20, August.
    6. Zvi Schwartz & Timothy Webb & Jean-Pierre I van der Rest & Larissa Koupriouchina, 2021. "Enhancing the accuracy of revenue management system forecasts: The impact of machine and human learning on the effectiveness of hotel occupancy forecast combinations across multiple forecasting horizo," Tourism Economics, , vol. 27(2), pages 273-291, March.

  13. Kajal Lahiri & Yongchen Zhao, 2013. "Determinants of Consumer Sentiment: Evidence from Household Survey Data," Discussion Papers 13-12, University at Albany, SUNY, Department of Economics.

    Cited by:

    1. Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2015. "Forecasting Consumption: The Role of Consumer Confidence in Real Time with many Predictors," Working Papers 2015-02, Towson University, Department of Economics, revised Jul 2015.
    2. Dilyara Ibragimova, 2014. "Consumer Expectations Of Russian Populations: Cohort Analysis (1996–2009)," HSE Working papers WP BRP 41/SOC/2014, National Research University Higher School of Economics.

  14. Kajal Lahiri & Huaming Peng & Yongchen Zhao, 2013. "Testing the Value of Probability Forecasts for Calibrated Combining," Discussion Papers 13-02, University at Albany, SUNY, Department of Economics.

    Cited by:

    1. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
    2. Constantin Bürgi & Tara M. Sinclair, 2015. "A Nonparametric Approach to Identifying a Subset of Forecasters that Outperforms the Simple Average," Working Papers 2015-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    3. Valentina Corradi & Sainan Jin & Norman R. Swanson, 2023. "Robust forecast superiority testing with an application to assessing pools of expert forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 596-622, June.
    4. Graham Elliott, 2017. "Forecast combination when outcomes are difficult to predict," Empirical Economics, Springer, vol. 53(1), pages 7-20, August.
    5. Herman Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-15, Towson University, Department of Economics, revised Sep 2016.
    6. Yuri S. Popkov & Yuri A. Dubnov & Alexey Yu. Popkov, 2016. "New Method of Randomized Forecasting Using Entropy-Robust Estimation: Application to the World Population Prediction," Mathematics, MDPI, vol. 4(1), pages 1-16, March.

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

    Cited by:

    1. John Khumalo, 2014. "Consumer Spending and Consumer Confidence in South Africa: Cointegration Analysis," Journal of Economics and Behavioral Studies, AMH International, vol. 6(2), pages 95-104.
    2. Hatice Gokce Karasoy & Caglar Yunculer, 2015. "The Explanatory Power and the Forecast Performance of Consumer Confidence Indices for Private Consumption Growth in Turkey," Working Papers 1519, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.

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

    Cited by:

    1. Herman O. Stekler & Tianyu Ye, 2017. "Evaluating a leading indicator: an application—the term spread," Empirical Economics, Springer, vol. 53(1), pages 183-194, August.
    2. Soojin Jo & Rodrigo Sekkel, 2019. "Macroeconomic Uncertainty Through the Lens of Professional Forecasters," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 436-446, July.
    3. Kajal Lahiri & Cheng Yang, 2023. "ROC and PRC Approaches to Evaluate Recession Forecasts," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(2), pages 119-148, September.
    4. El-Shagi, Makram, 2019. "Rationality tests in the presence of instabilities in finite samples," Economic Modelling, Elsevier, vol. 79(C), pages 242-246.
    5. Knut Lehre Seip & Dan Zhang, 2021. "The Yield Curve as a Leading Indicator: Accuracy and Timing of a Parsimonious Forecasting Model," Forecasting, MDPI, vol. 3(2), pages 1-16, May.
    6. Weiling Liu & Emanuel Moench, 2014. "What predicts U.S. recessions?," Staff Reports 691, Federal Reserve Bank of New York.
    7. Kajal Lahiri & Liu Yang, 2015. "Asymptotic Variance of Brier (Skill) Score in the Presence of Serial Correlation," CESifo Working Paper Series 5290, CESifo.
    8. Lahiri, Kajal & Peng, Huaming & Zhao, Yongchen, 2015. "Testing the value of probability forecasts for calibrated combining," International Journal of Forecasting, Elsevier, vol. 31(1), pages 113-129.
    9. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    10. Chatterjee, Ujjal K., 2018. "Bank liquidity creation and recessions," Journal of Banking & Finance, Elsevier, vol. 90(C), pages 64-75.
    11. Pablo Aguilar & Jesús Vázquez, 2018. "Term structure and real-time learning," Working Papers 1803, Banco de España.

Articles

  1. Zhao, Yongchen, 2023. "Internal consistency of household inflation expectations: Point forecasts vs. density forecasts," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1713-1735.

    Cited by:

    1. Goldfayn-Frank, Olga & Kieren, Pascal & Trautmann, Stefan, 2024. "A Choice-Based Approach to the Measurement of Inflation Expectations," Working Papers 0742, University of Heidelberg, Department of Economics.
    2. Becker, Christoph & Dürsch, Peter & Eife, Thomas A. & Glas, Alexander, 2023. "Households' probabilistic inflation expectations in high-inflation regimes," FAU Discussion Papers in Economics 01/2023, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.

  2. Yongchen Zhao, 2022. "Uncertainty and disagreement of inflation expectations: Evidence from household‐level qualitative survey responses," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 810-828, July.
    See citations under working paper version above.
  3. Yongchen Zhao, 2021. "The robustness of forecast combination in unstable environments: a Monte Carlo study of advanced algorithms," Empirical Economics, Springer, vol. 61(1), pages 173-199, July.
    See citations under working paper version above.
  4. Yongchen Zhao, 2020. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 16(2), pages 77-97, November.
    See citations under working paper version above.
  5. Lahiri, Kajal & Zhao, Yongchen, 2020. "The Nordhaus test with many zeros," Economics Letters, Elsevier, vol. 193(C).
    See citations under working paper version above.
  6. Monokroussos, George & Zhao, Yongchen, 2020. "Nowcasting in real time using popularity priors," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1173-1180.
    See citations under working paper version above.
  7. Zhao, Yongchen, 2019. "Updates to household inflation expectations: Signal or noise?," Economics Letters, Elsevier, vol. 181(C), pages 95-98.
    See citations under working paper version above.
  8. Das, Abhiman & Lahiri, Kajal & Zhao, Yongchen, 2019. "Inflation expectations in India: Learning from household tendency surveys," International Journal of Forecasting, Elsevier, vol. 35(3), pages 980-993.
    See citations under working paper version above.
  9. Lahiri, Kajal & Zhao, Yongchen, 2019. "International propagation of shocks: A dynamic factor model using survey forecasts," International Journal of Forecasting, Elsevier, vol. 35(3), pages 929-947.
    See citations under working paper version above.
  10. Kajal Lahiri & Huaming Peng & Yongchen Zhao, 2017. "Online learning and forecast combination in unbalanced panels," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 257-288, March.

    Cited by:

    1. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2021. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Working Papers 2021-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    2. Constantin Bürgi, 2023. "How to Deal With Missing Observations in Surveys of Professional Forecasters," CESifo Working Paper Series 10203, CESifo.
    3. Glas, Alexander & Hartmann, Matthias, 2016. "Inflation uncertainty, disagreement and monetary policy: Evidence from the ECB Survey of Professional Forecasters," Journal of Empirical Finance, Elsevier, vol. 39(PB), pages 215-228.
    4. Yongchen Zhao, 2015. "Robustness of Forecast Combination in Unstable Environment: A Monte Carlo Study of Advanced Algorithms," Working Papers 2015-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    5. Meryem Duygun & Jiaqi Hao & Anders Isaksson & Robin C. Sickles, 2017. "World Productivity Growth: A Model Averaging Approach," Pacific Economic Review, Wiley Blackwell, vol. 22(4), pages 587-619, October.
    6. Qian, Wei & Rolling, Craig A. & Cheng, Gang & Yang, Yuhong, 2022. "Combining forecasts for universally optimal performance," International Journal of Forecasting, Elsevier, vol. 38(1), pages 193-208.
    7. Antonio Martin Arroyo & Aranzazu de Juan Fernandez, 2020. "Split-then-Combine simplex combination and selection of forecasters," Papers 2012.11935, arXiv.org.
    8. Constantin Bürgi & Tara M. Sinclair, 2015. "A Nonparametric Approach to Identifying a Subset of Forecasters that Outperforms the Simple Average," Working Papers 2015-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    9. Wei Qian & Craig A. Rolling & Gang Cheng & Yuhong Yang, 2019. "On the Forecast Combination Puzzle," Econometrics, MDPI, vol. 7(3), pages 1-26, September.
    10. Valentina Corradi & Sainan Jin & Norman R. Swanson, 2023. "Robust forecast superiority testing with an application to assessing pools of expert forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 596-622, June.
    11. Hounyo, Ulrich & Lahiri, Kajal, 2023. "Estimating the variance of a combined forecast: Bootstrap-based approach," Journal of Econometrics, Elsevier, vol. 232(2), pages 445-468.
    12. Ulrich Hounyo & Kajal Lahiri, 2023. "Are Some Forecasters Really Better than Others? A Note," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(2-3), pages 577-593, March.

  11. Kajal Lahiri & Yongchen Zhao, 2016. "Determinants of Consumer Sentiment Over Business Cycles: Evidence from the US Surveys of Consumers," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(2), pages 187-215, December.
    See citations under working paper version above.
  12. Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2016. "Forecasting Consumption: the Role of Consumer Confidence in Real Time with many Predictors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1254-1275, November.
    See citations under working paper version above.
  13. Lahiri, Kajal & Peng, Huaming & Zhao, Yongchen, 2015. "Testing the value of probability forecasts for calibrated combining," International Journal of Forecasting, Elsevier, vol. 31(1), pages 113-129.
    See citations under working paper version above.
  14. Lahiri, Kajal & Zhao, Yongchen, 2015. "Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 31(1), pages 51-62.

    Cited by:

    1. Bespalova, Olga, 2018. "Forecast Evaluation in Macroeconomics and International Finance. Ph.D. thesis, George Washington University, Washington, DC, USA," MPRA Paper 117706, University Library of Munich, Germany.
    2. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Self-organizing map analysis of agents’ expectations. Different patterns of anticipation of the 2008 financial crisis”," AQR Working Papers 201508, University of Barcelona, Regional Quantitative Analysis Group, revised Mar 2015.
    3. Yasutomo Murasawa, 2020. "Measuring public inflation perceptions and expectations in the UK," Empirical Economics, Springer, vol. 59(1), pages 315-344, July.
    4. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    5. Murasawa, Yasutomo, 2017. "Measuring the Distributions of Public Inflation Perceptions and Expectations in the UK," MPRA Paper 76244, University Library of Munich, Germany.
    6. Alex Botsis & Kevin Lee, 2022. "Nowcasting Using Firm-Level Survey Data; Tracking UK Output Fluctuations and Recessionary Events," Economic Statistics Centre of Excellence (ESCoE) Technical Reports ESCOE-TR-20, Economic Statistics Centre of Excellence (ESCoE).
    7. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," AQR Working Papers 201801, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2018.
    8. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Evolutionary Computation for Macroeconomic Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 833-849, February.
    9. Aleksandra Rutkowska & Magdalena Szyszko, 2022. "New DTW Windows Type for Forward- and Backward-Lookingness Examination. Application for Inflation Expectation," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 701-718, February.
    10. Dr. Rina Rosenblatt-Wisch & Dr. Rolf Scheufele, 2014. "Quantification and characteristics of household inflation expectations in Switzerland," Working Papers 2014-11, Swiss National Bank.
    11. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Empirical modelling of survey-based expectations for the design of economic indicators in five European regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 205-227, May.
    12. Das, Abhiman & Lahiri, Kajal & Zhao, Yongchen, 2019. "Inflation expectations in India: Learning from household tendency surveys," International Journal of Forecasting, Elsevier, vol. 35(3), pages 980-993.
    13. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "A new approach for the quantification of qualitative measures of economic expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2685-2706, November.
    14. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming," IREA Working Papers 201711, University of Barcelona, Research Institute of Applied Economics, revised May 2017.
    15. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "A Data-Driven Approach to Construct Survey-Based Indicators by Means of Evolutionary Algorithms," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 1-14, January.

  15. Lahiri, Kajal & Monokroussos, George & Zhao, Yongchen, 2013. "The yield spread puzzle and the information content of SPF forecasts," Economics Letters, Elsevier, vol. 118(1), pages 219-221.
    See citations under working paper version above.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 19 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-MAC: Macroeconomics (11) 2015-07-25 2016-07-30 2016-09-25 2016-10-16 2018-09-03 2018-09-24 2019-05-20 2020-02-17 2020-06-15 2020-07-27 2021-12-13. Author is listed
  2. NEP-FOR: Forecasting (7) 2012-06-25 2012-10-06 2013-04-27 2015-07-25 2015-12-28 2016-05-08 2016-09-25. Author is listed
  3. NEP-MON: Monetary Economics (4) 2018-09-03 2019-05-20 2021-12-13 2023-12-18
  4. NEP-ETS: Econometric Time Series (2) 2016-05-08 2018-09-24
  5. NEP-ORE: Operations Research (2) 2019-05-20 2020-02-17
  6. NEP-BAN: Banking (1) 2023-12-18
  7. NEP-BEC: Business Economics (1) 2019-05-20
  8. NEP-BIG: Big Data (1) 2020-02-17
  9. NEP-CWA: Central and Western Asia (1) 2021-12-13
  10. NEP-DCM: Discrete Choice Models (1) 2013-05-22
  11. NEP-ECM: Econometrics (1) 2015-12-28
  12. NEP-HIS: Business, Economic and Financial History (1) 2023-10-09
  13. NEP-MKT: Marketing (1) 2016-07-30
  14. NEP-PKE: Post Keynesian Economics (1) 2016-05-08

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