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Yongchen Zhao

Personal Details

First Name:Yongchen
Middle Name:
Last Name:Zhao
Suffix:
RePEc Short-ID:pzh331
http://hzhao.net
Department of Economics College of Business and 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. Kajal Lahiri & Yongchen Zhao, 2020. "The Nordhaus Test with Many Zeros," Working Papers 2020-05, Towson University, Department of Economics, revised Jun 2020.
  2. George Monokroussos & Yongchen Zhao, 2020. "Nowcasting in Real Time Using Popularity Priors," Working Papers 2020-01, Towson University, Department of Economics, revised Feb 2020.
  3. Yongchen Zhao, 2019. "Updates to Household Inflation Expectations: Signal or Noise?," Working Papers 2019-01, Towson University, Department of Economics, revised May 2019.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. Yongchen Zhao, 2015. "Robustness of Forecast Combination in Unstable Environment: A Monte Carlo Study of Advanced Algorithms," Working Papers 2015-04, Towson University, Department of Economics, revised Mar 2020.
  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.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2012. "The yield spread puzzle and the information content of SPF forecasts," Discussion Papers 12-04, University at Albany, SUNY, Department of Economics.

Articles

  1. Zhao, Yongchen, 2019. "Updates to household inflation expectations: Signal or noise?," Economics Letters, Elsevier, vol. 181(C), pages 95-98.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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. Kajal Lahiri & Yongchen Zhao, 2020. "The Nordhaus Test with Many Zeros," Working Papers 2020-05, Towson University, Department of Economics, revised Jun 2020.

    Cited by:

    1. An, Zidong & Liu, Dingqian & Wu, Yuzheng, 2021. "Expectation formation following pandemic events," Economics Letters, Elsevier, vol. 200(C).

  2. 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. 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.

  3. 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.

  4. 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," CESifo Working Paper Series 7691, CESifo.
    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.

  5. 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. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, Open Access Journal, vol. 3(1), pages 1-22, February.
    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. 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.
    4. Ashima Goyal & Prashant Parab, 2019. "Modeling consumers' confidence and inflation expectations," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2019-025, Indira Gandhi Institute of Development Research, Mumbai, India.

  6. 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. Zhao, Yongchen, 2019. "Updates to household inflation expectations: Signal or noise?," Economics Letters, Elsevier, vol. 181(C), pages 95-98.
    2. An, Zidong & Liu, Dingqian & Wu, Yuzheng, 2021. "Expectation formation following pandemic events," Economics Letters, Elsevier, vol. 200(C).
    3. 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.
    4. 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.
    5. Kajal Lahiri & Huaming Peng & Xuguang Sheng, 2015. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," CESifo Working Paper Series 5468, CESifo.
    6. 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.
    7. 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.
    8. 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.
    9. Marwane El Alaoui & Elie Bouri & Nehme Azoury, 2020. "The Determinants of the U.S. Consumer Sentiment: Linear and Nonlinear Models," International Journal of Financial Studies, MDPI, Open Access Journal, vol. 8(3), pages 1-13, July.
    10. 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.
    11. 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.
    12. 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.
    13. Ben Zhe Wang & Jeffrey Sheen & Stefan Truck & Shih-Kang Chao & Wolfgang Karl Hardle, 2020. "A note on the impact of news on US household inflation expectations," Papers 2009.11557, arXiv.org.
    14. Liudmila Kitrar & Tamara Lipkind & Georgy Ostapkovich, 2020. "Information Content of Russian Services Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 16(1), pages 59-74, April.

  7. Yongchen Zhao, 2015. "Robustness of Forecast Combination in Unstable Environment: A Monte Carlo Study of Advanced Algorithms," Working Papers 2015-04, Towson University, Department of Economics, revised Mar 2020.

    Cited by:

    1. Fantazzini, Dean & Nigmatullin, Erik & Sukhanovskaya, Vera & Ivliev, Sergey, 2016. "Everything you always wanted to know about bitcoin modelling but were afraid to ask," MPRA Paper 71946, University Library of Munich, Germany, revised 2016.
    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. 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.
    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.

  8. 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. 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.
    2. 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.
    3. Francisco Corona & Pilar Poncela & Esther Ruiz, 2017. "Determining the number of factors after stationary univariate transformations," Empirical Economics, Springer, vol. 53(1), pages 351-372, August.
    4. Juhro, Solikin M. & Iyke, Bernard Njindan, 2020. "Consumer confidence and consumption expenditure in Indonesia," Economic Modelling, Elsevier, vol. 89(C), pages 367-377.
    5. Gustavo Adolfo HERNANDEZ DIAZ & Margarita MARÍN JARAMILLO, 2016. "Pronóstico del Consumo Privado: Usando datos de alta frecuencia para el pronóstico de variables de baja frecuencia," Archivos de Economía 014828, Departamento Nacional de Planeación.
    6. Rusnák, Marek, 2016. "Nowcasting Czech GDP in real time," Economic Modelling, Elsevier, vol. 54(C), pages 26-39.
    7. 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.
    8. A. Girardi & R. Golinelli & C. Pappalardo, 2014. "The Role of Indicator Selection in Nowcasting Euro Area GDP in Pseudo Real Time," Working Papers wp919, Dipartimento Scienze Economiche, Universita' di Bologna.
    9. Hashmat Khan & Jean-François Rouillard & Santosh Upadhayaya, 2020. "Consumer Confidence and Household Investment," Cahiers de recherche 20-15, Departement d'Economique de l'École de gestion à l'Université de Sherbrooke.
    10. Jean-Paul L’Huillier & Robert Waldmann & Donghoon Yoo, 2021. "Confidence, Fundamentals, and Consumption," ISER Discussion Paper 1135, Institute of Social and Economic Research, Osaka University.
    11. de Bondt, Gabe & Gieseck, Arne & Herrero, Pablo & Zekaite, Zivile, 2019. "Disaggregate income and wealth effects in the largest euro area countries," Research Technical Papers 15/RT/19, Central Bank of Ireland.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    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. Vincenzo Merella & Stephen E. Satchell, 2019. "Asset pricing with utility from external anticipation," Carlo Alberto Notebooks 589, Collegio Carlo Alberto.
    18. 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.
    19. 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.
    20. Hashmat Khan & Jean-François Rouillard & Santosh Upadhayaya, 2019. "Consumer Confidence and Household Investment," Carleton Economic Papers 19-06, Carleton University, Department of Economics, revised 28 Oct 2020.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.

  9. 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.

  10. 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. 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.
    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. Graham Elliott, 2017. "Forecast combination when outcomes are difficult to predict," Empirical Economics, Springer, vol. 53(1), pages 7-20, August.
    5. 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.
    6. Wei Qian & Craig A. Rolling & Gang Cheng & Yuhong Yang, 2019. "On the Forecast Combination Puzzle," Econometrics, MDPI, Open Access Journal, vol. 7(3), pages 1-26, September.

  11. 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, 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.
    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.

  12. 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. 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.
    2. Graham Elliott, 2017. "Forecast combination when outcomes are difficult to predict," Empirical Economics, Springer, vol. 53(1), pages 7-20, August.
    3. 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.

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

    Cited by:

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

  14. Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2012. "The yield spread puzzle and the information content of SPF forecasts," Discussion Papers 12-04, University at Albany, SUNY, Department of Economics.

    Cited by:

    1. Soojin Jo & Rodrigo Sekkel, 2019. "Macroeconomic Uncertainty Through the Lens of Professional Forecasters," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 436-446, July.
    2. Weiling Liu & Emanuel Moench, 2014. "What predicts U.S. recessions?," Staff Reports 691, Federal Reserve Bank of New York.
    3. Chatterjee, Ujjal K., 2018. "Bank liquidity creation and recessions," Journal of Banking & Finance, Elsevier, vol. 90(C), pages 64-75.
    4. Lahiri, Kajal & Yang, Liu, 2016. "Asymptotic variance of Brier (skill) score in the presence of serial correlation," Economics Letters, Elsevier, vol. 141(C), pages 125-129.
    5. 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.
    6. 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.
    7. 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.
    8. El-Shagi, Makram, 2019. "Rationality tests in the presence of instabilities in finite samples," Economic Modelling, Elsevier, vol. 79(C), pages 242-246.
    9. Pablo Aguilar & Jesús Vázquez, 2018. "Term structure and real-time learning," Working Papers 1803, Banco de España.

Articles

  1. 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.
  2. 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.
  3. 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.
  4. 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. Duygun, Meryem & Hao, Jiaqi & Isaksson, Anders & Sickles, Robin C., 2015. "World Productivity Growth: A Model Averaging Approach," Working Papers 15-011, Rice University, Department of Economics.
    2. Kajal Lahiri & Huaming Peng & Xuguang Sheng, 2015. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," CESifo Working Paper Series 5468, CESifo.
    3. Glas, Alexander & Hartmann, Matthias, 2016. "Inflation uncertainty, disagreement and monetary policy: Evidence from the ECB Survey of Professional Forecasters," Working Papers 0612, University of Heidelberg, Department of Economics.
    4. Antonio Martin Arroyo & Aranzazu de Juan Fernandez, 2020. "Split-then-Combine simplex combination and selection of forecasters," Papers 2012.11935, arXiv.org.
    5. 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.
    6. 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.
    7. Yongchen Zhao, 2015. "Robustness of Forecast Combination in Unstable Environment: A Monte Carlo Study of Advanced Algorithms," Working Papers 2015-04, Towson University, Department of Economics, revised Mar 2020.
    8. Wei Qian & Craig A. Rolling & Gang Cheng & Yuhong Yang, 2019. "On the Forecast Combination Puzzle," Econometrics, MDPI, Open Access Journal, vol. 7(3), pages 1-26, September.

  5. 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.
  6. 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.
  7. 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.
  8. 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. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," IREA Working Papers 201801, University of Barcelona, Research Institute of Applied Economics, revised Jan 2018.
    2. Rina Rosenblatt-Wisch & Rolf Scheufele, 2015. "Quantification and characteristics of household inflation expectations in Switzerland," Applied Economics, Taylor & Francis Journals, vol. 47(26), pages 2699-2716, June.
    3. 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.
    4. 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.
    5. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming”," AQR Working Papers 201706, University of Barcelona, Regional Quantitative Analysis Group, revised May 2017.
    6. Yasutomo Murasawa, 2020. "Measuring public inflation perceptions and expectations in the UK," Empirical Economics, Springer, vol. 59(1), pages 315-344, July.
    7. 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.
    8. 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.
    9. 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.
    10. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, Open Access Journal, vol. 3(1), pages 1-22, February.
    11. Murasawa, Yasutomo, 2017. "Measuring the Distributions of Public Inflation Perceptions and Expectations in the UK," MPRA Paper 76244, University Library of Munich, Germany.
    12. 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.

  9. 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.

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Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 16 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 (10) 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. 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-ETS: Econometric Time Series (2) 2016-05-08 2018-09-24
  4. NEP-MON: Monetary Economics (2) 2018-09-03 2019-05-20
  5. NEP-ORE: Operations Research (2) 2019-05-20 2020-02-17
  6. NEP-BEC: Business Economics (1) 2019-05-20
  7. NEP-BIG: Big Data (1) 2020-02-17
  8. NEP-DCM: Discrete Choice Models (1) 2013-05-22
  9. NEP-ECM: Econometrics (1) 2015-12-28
  10. NEP-MKT: Marketing (1) 2016-07-30
  11. NEP-PKE: Post Keynesian Economics (1) 2016-05-08

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