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Suyong Song

Personal Details

First Name:Suyong
Middle Name:
Last Name:Song
Suffix:
RePEc Short-ID:pso554
[This author has chosen not to make the email address public]
https://sites.google.com/site/suyongsong/
Terminal Degree:2010 Department of Economics; University of California-San Diego (UCSD) (from RePEc Genealogy)

Affiliation

Department of Economics
Tippie College of Business
University of Iowa

Iowa City, Iowa (United States)
http://tippie.uiowa.edu/economics/
RePEc:edi:deuiaus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Geonwoo Kim & Suyong Song, 2024. "Double/Debiased CoCoLASSO of Treatment Effects with Mismeasured High-Dimensional Control Variables," Papers 2408.14671, arXiv.org.
  2. Suyong Song & Stephen S. Baek, 2019. "Shape Matters: Evidence from Machine Learning on Body Shape-Income Relationship," Papers 1906.06747, arXiv.org.
  3. Ardakani, Omid & Kishor, Kundan & Song, Suyong, 2015. "On the Effectiveness of Inflation Targeting: Evidence from a Semiparametric Approach," MPRA Paper 75091, University Library of Munich, Germany.

Articles

  1. Omid M. Ardakani & N. Kundan Kishor & Suyong Song, 2024. "Does membership of the EMU matter for economic and financial outcomes?," Contemporary Economic Policy, Western Economic Association International, vol. 42(3), pages 416-447, July.
  2. Jafar Namdar & Jennifer Blackhurst & Kang Zhao & Suyong Song, 2024. "Cascading disruptions: Impact of modularity and nexus supplier predictions," Journal of Supply Chain Management, Institute for Supply Management, vol. 60(3), pages 18-38, July.
  3. Song, Suyong & Wang, Jiawei (Brooke), 2024. "Boardroom networks and corporate investment," Journal of Corporate Finance, Elsevier, vol. 84(C).
  4. Kyoo il Kim & Suyong Song, 2022. "Control variables approach to estimate semiparametric models of mismeasured endogenous regressors with an application to U.K. twin data," Econometric Reviews, Taylor & Francis Journals, vol. 41(4), pages 448-483, April.
  5. Suyong Song & Stephen Baek, 2021. "Body shape matters: Evidence from machine learning on body shape-income relationship," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-17, July.
  6. Liqiong Chen & Antonio F. Galvao & Suyong Song, 2021. "Quantile Regression with Generated Regressors," Econometrics, MDPI, vol. 9(2), pages 1-35, April.
  7. Antonio F. Galvao & Gabriel Montes–Rojas & Jose Olmo & Suyong Song, 2018. "On solving endogeneity with invalid instruments: an application to investment equations," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(3), pages 689-716, June.
  8. Ardakani, Omid M. & Kishor, N. Kundan & Song, Suyong, 2018. "Re-evaluating the effectiveness of inflation targeting," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 76-97.
  9. Firpo, Sergio & Galvao, Antonio F. & Song, Suyong, 2017. "Measurement errors in quantile regression models," Journal of Econometrics, Elsevier, vol. 198(1), pages 146-164.
  10. Galvao, Antonio F. & Montes-Rojas, Gabriel & Song, Suyong, 2017. "Endogeneity bias modeling using observables," Economics Letters, Elsevier, vol. 152(C), pages 41-45.
  11. Kim, Kyoo il & Petrin, Amil & Song, Suyong, 2016. "Estimating production functions with control functions when capital is measured with error," Journal of Econometrics, Elsevier, vol. 190(2), pages 267-279.
  12. Song, Suyong, 2015. "Semiparametric estimation of models with conditional moment restrictions in the presence of nonclassical measurement errors," Journal of Econometrics, Elsevier, vol. 185(1), pages 95-109.
  13. Kishor, N. Kundan & Kumari, Swati & Song, Suyong, 2015. "Time variation in the relative importance of permanent and transitory components in the U.S. housing market," Finance Research Letters, Elsevier, vol. 12(C), pages 92-99.
  14. Suyong Song & Susanne M. Schennach & Halbert White, 2015. "Estimating nonseparable models with mismeasured endogenous variables," Quantitative Economics, Econometric Society, vol. 6(3), pages 749-794, November.

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

    Sorry, no citations of working papers recorded.

Articles

  1. Song, Suyong & Wang, Jiawei (Brooke), 2024. "Boardroom networks and corporate investment," Journal of Corporate Finance, Elsevier, vol. 84(C).

    Cited by:

    1. Cave, Joshua & Lancheros, Sandra, 2024. "Local peer influence on dividend payout decisions," Journal of Banking & Finance, Elsevier, vol. 164(C).

  2. Liqiong Chen & Antonio F. Galvao & Suyong Song, 2021. "Quantile Regression with Generated Regressors," Econometrics, MDPI, vol. 9(2), pages 1-35, April.

    Cited by:

    1. Hartwig, Benny & Meinerding, Christoph & Schüler, Yves S., 2021. "Identifying indicators of systemic risk," Journal of International Economics, Elsevier, vol. 132(C).
    2. Christis Katsouris, 2023. "Estimating Conditional Value-at-Risk with Nonstationary Quantile Predictive Regression Models," Papers 2311.08218, arXiv.org, revised Apr 2024.
    3. Jayeeta Bhattacharya, 2020. "Quantile regression with generated dependent variable and covariates," Papers 2012.13614, arXiv.org.
    4. Inuwa, Nasiru & Adamu, Sagir & Hamza, Yusuf & Sani, Mohammed Bello, 2023. "Does dichotomy between resource dependence and resource abundance matters for resource curse hypothesis? New evidence from quantiles via moments," Resources Policy, Elsevier, vol. 81(C).
    5. Khan, Yasir & Hassan, Taimoor & Guiqin, Huang & Nabi, Ghulam, 2023. "Analyzing the impact of natural resources and rule of law on sustainable environment: A proposed policy framework for BRICS economies," Resources Policy, Elsevier, vol. 86(PA).
    6. Dianliang Deng & Mashfiqul Huq Chowdhury, 2022. "Quantile Regression Approach for Analyzing Similarity of Gene Expressions under Multiple Biological Conditions," Stats, MDPI, vol. 5(3), pages 1-23, July.

  3. Antonio F. Galvao & Gabriel Montes–Rojas & Jose Olmo & Suyong Song, 2018. "On solving endogeneity with invalid instruments: an application to investment equations," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(3), pages 689-716, June.

    Cited by:

    1. Ali Al-Sharadqah & Majid Mojirsheibani & William Pouliot, 2020. "On the performance of weighted bootstrapped kernel deconvolution density estimators," Statistical Papers, Springer, vol. 61(4), pages 1773-1798, August.

  4. Ardakani, Omid M. & Kishor, N. Kundan & Song, Suyong, 2018. "Re-evaluating the effectiveness of inflation targeting," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 76-97.

    Cited by:

    1. Apeti, Ablam Estel & Combes, Jean-Louis & Minea, Alexandru, 2024. "Inflation targeting and fiscal policy volatility: Evidence from developing countries," Journal of International Money and Finance, Elsevier, vol. 141(C).
    2. Ahmad Zubaidi Baharumshah & Siew-Voon Soon & Mark E. Wohar, 2021. "Phillips Curve for the Asian Economies: A Nonlinear Perspective," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 57(12), pages 3508-3537, September.
    3. Haryo Kuncoro, 2024. "Inflation and Its Uncertainty: Evidence from Indonesia and the Philippines," Global Journal of Emerging Market Economies, Emerging Markets Forum, vol. 16(2), pages 231-247, May.
    4. Geoffrey R. Dunbar & Amy (Qijia) Li, 2019. "The Effects of Inflation Targeting for Financial Development," Staff Analytical Notes 2019-21, Bank of Canada.
    5. Goran Petrevski, 2023. "Macroeconomic Effects of Inflation Targeting: A Survey of the Empirical Literature," Papers 2305.17474, arXiv.org.
    6. Bambe, Bao-We-Wal & Combes, Jean-Louis & Kaba, Kabinet & Minea, Alexandru, 2024. "Inflation targeting and firm performance in developing countries," Journal of Economic Dynamics and Control, Elsevier, vol. 163(C).
    7. Victor Pontines, 2020. "The real effects of loan-to-value limits: Empirical evidence from Korea," CAMA Working Papers 2020-02, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    8. Stojanovikj, Martin & Petrevski, Goran, 2024. "The choice of monetary regimes in emerging market economies: Inflation targeting versus its alternatives," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 237-260.
    9. Stojanovikj, Martin & Petrevski, Goran, 2020. "Inflation targeting and disinflation costs in emerging market economies," MPRA Paper 115798, University Library of Munich, Germany.
    10. Antonakakis, Nikolaos & Christou, Christina & Gil-Alana, Luis A. & Gupta, Rangan, 2021. "Inflation-targeting and inflation volatility: International evidence from the cosine-squared cepstrum," International Economics, Elsevier, vol. 167(C), pages 29-38.
    11. Ablam Estel Apeti & Jean-Louis Combes & Alexandru Minea, 2023. "Inflation targeting and the composition of public expenditure: Evidence from developing countries," Post-Print hal-04072840, HAL.
    12. Bruno Ferreira Frascaroli & Wellington Charles Lacerda Nobrega, 2019. "Inflation Targeting and Inflation Risk in Latin America," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(11), pages 2389-2408, September.
    13. López-Villavicencio, Antonia & Pourroy, Marc, 2019. "Does inflation targeting always matter for the ERPT? A robust approach," Journal of Macroeconomics, Elsevier, vol. 60(C), pages 360-377.
    14. Farvaque, Etienne & Malan, Franck & Stanek, Piotr, 2020. "Misplaced childhood: When recession children grow up as central bankers," Journal of Economic Dynamics and Control, Elsevier, vol. 110(C).
    15. Suh, Sangwon & Kim, Daehwan, 2021. "Inflation targeting and expectation anchoring: Evidence from developed and emerging market economies," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    16. Martin Stojanovikj & Goran Petrevski, 2021. "Macroeconomic effects of inflation targeting in emerging market economies," Empirical Economics, Springer, vol. 61(5), pages 2539-2585, November.
    17. Adina Ionela Străchinaru & Bogdan Andrei Dumitrescu, 2019. "Assessing the Sustainability of Inflation Targeting: Evidence from EU Countries with Non-EURO Currencies," Sustainability, MDPI, vol. 11(20), pages 1-13, October.
    18. Petrevski, Goran, 2023. "Determinants of Inflation Targeting: A Survey of Empirical Literature," EconStor Preprints 271121, ZBW - Leibniz Information Centre for Economics.
    19. Stojanovikj, Martin & Petrevski, Goran, 2019. "Adopting inflation targeting in emerging markets: exploring the factors behind the decision," MPRA Paper 115797, University Library of Munich, Germany, revised 18 Jun 2020.
    20. Bao-We-Wal Bambe, 2023. "Inflation Targeting and Private Domestic Investment in Developing Countries," Post-Print hal-04227639, HAL.

  5. Firpo, Sergio & Galvao, Antonio F. & Song, Suyong, 2017. "Measurement errors in quantile regression models," Journal of Econometrics, Elsevier, vol. 198(1), pages 146-164.

    Cited by:

    1. Battistin, Erich & Lamarche, Carlos & Rettore, Enrico, 2020. "Quantiles of the Gain Distribution of an Early Childhood Intervention," IZA Discussion Papers 13101, Institute of Labor Economics (IZA).
    2. Battistin, Erich & Lamarche, Carlos & Rettore, Enrico, 2020. "Quantiles of the Gain Distribution of an Early Child Intervention," CEPR Discussion Papers 14721, C.E.P.R. Discussion Papers.
    3. Andrew Chesher, 2017. "Understanding the effect of measurement error on quantile regressions," CeMMAP working papers CWP19/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Wei Fang & Zhenyu Yang & Zhen Liu & Assem Abu Hatab, 2023. "Green recovery of cropland carrying capacity in developed regions: empirical evidence from Guangdong, China," Economic Change and Restructuring, Springer, vol. 56(4), pages 2405-2436, August.
    5. Zongwu Cai & Ying Fang & Ming Lin & Shengfang Tang, 2021. "A Nonparametric Test for Testing Heterogeneity in Conditional Quantile Treatment Effects," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202117, University of Kansas, Department of Economics, revised Aug 2021.
    6. Brantly Callaway & Tong Li & Irina Murtazashvili, 2021. "Distributional Effects with Two-Sided Measurement Error: An Application to Intergenerational Income Mobility," Papers 2107.09235, arXiv.org, revised Jun 2024.
    7. Kengo Kato & Yuya Sasaki & Takuya Ura, 2021. "Robust inference in deconvolution," Quantitative Economics, Econometric Society, vol. 12(1), pages 109-142, January.
    8. Zongwu Cai & Ying Fang & Ming Lin & Shengfang Tang, 2020. "Inferences for Partially Conditional Quantile Treatment Effect Model," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202005, University of Kansas, Department of Economics, revised Feb 2020.
    9. Liqiong Chen & Antonio F. Galvao & Suyong Song, 2021. "Quantile Regression with Generated Regressors," Econometrics, MDPI, vol. 9(2), pages 1-35, April.

  6. Galvao, Antonio F. & Montes-Rojas, Gabriel & Song, Suyong, 2017. "Endogeneity bias modeling using observables," Economics Letters, Elsevier, vol. 152(C), pages 41-45.

    Cited by:

    1. Hoedoafia, Mabel Akosua, 2020. "On the Link between Trade Liberalization and Firm Productivity: Panel Data Evidence from Private Firms in Ghana," MPRA Paper 99568, University Library of Munich, Germany.
    2. Antonio F. Galvao & Gabriel Montes–Rojas & Jose Olmo & Suyong Song, 2018. "On solving endogeneity with invalid instruments: an application to investment equations," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(3), pages 689-716, June.

  7. Kim, Kyoo il & Petrin, Amil & Song, Suyong, 2016. "Estimating production functions with control functions when capital is measured with error," Journal of Econometrics, Elsevier, vol. 190(2), pages 267-279.

    Cited by:

    1. Sahoo, Pradipta Kumar & Rath, Badri Narayan & Le, Viet, 2022. "Nexus between export, productivity, and competitiveness in the Indian manufacturing sector," Journal of Asian Economics, Elsevier, vol. 79(C).
    2. Miao, Chenglin & Fang, Debin & Sun, Liyan & Luo, Qiaoling, 2017. "Natural resources utilization efficiency under the influence of green technological innovation," Resources, Conservation & Recycling, Elsevier, vol. 126(C), pages 153-161.
    3. Tsionas, Mike G. & Mallick, Sushanta K., 2019. "A Bayesian semiparametric approach to stochastic frontiers and productivity," European Journal of Operational Research, Elsevier, vol. 274(1), pages 391-402.
    4. Junrong Liu & Robin C. Sickles & E. G. Tsionas, 2017. "Bayesian Treatments for Panel Data Stochastic Frontier Models with Time Varying Heterogeneity," Econometrics, MDPI, vol. 5(3), pages 1-21, July.
    5. Hu, Yingyao & Huang, Guofang & Sasaki, Yuya, 2020. "Estimating production functions with robustness against errors in the proxy variables," Journal of Econometrics, Elsevier, vol. 215(2), pages 375-398.
    6. Fu, Shihe & Xu, Xiaocong & Zhang, Junfu, 2021. "Land conversion across cities in China," Regional Science and Urban Economics, Elsevier, vol. 87(C).
    7. Abito, Jose Miguel, 2019. "Estimating Production Functions with Fixed Effects," MPRA Paper 97825, University Library of Munich, Germany.
    8. De loecker, Jan & Collard-Wexler, Allan, 2016. "Production Function Estimation with Measurement Error in Inputs," CEPR Discussion Papers 11399, C.E.P.R. Discussion Papers.
    9. Josh Martin & Rebecca Riley, 2023. "Productivity measurement - Reassessing the production function from micro to macro," Working Papers 033, The Productivity Institute.
    10. Allan Collard-Wexler & Jan De Loecker, 2016. "Production Function Estimation and Capital Measurement Error," NBER Working Papers 22437, National Bureau of Economic Research, Inc.
    11. Daniel Gurara & Dawit Tessema, 2018. "Losing to Blackouts: Evidence from Firm Level Data," IMF Working Papers 2018/159, International Monetary Fund.
    12. Daniel A. Ackerberg & Kevin Caves & Garth Frazer, 2015. "Identification Properties of Recent Production Function Estimators," Econometrica, Econometric Society, vol. 83, pages 2411-2451, November.
    13. Yismaw Ayelign & Lakhwinder Singh, 2019. "Comparison of Recent Developments in Productivity Estimation: Application on Ethiopian Manufacturing Sector," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 5(3), pages 20-31, September.

  8. Song, Suyong, 2015. "Semiparametric estimation of models with conditional moment restrictions in the presence of nonclassical measurement errors," Journal of Econometrics, Elsevier, vol. 185(1), pages 95-109.

    Cited by:

    1. Francis J. DiTraglia & Camilo Garcia-Jimeno, 2020. "Identifying the effect of a mis-classified, binary, endogenous regressor," Papers 2011.07272, arXiv.org.
    2. Francis DiTraglia & Camilo Garcia-Jimeno, 2015. "On Mis-measured Binary Regressors: New Results And Some Comments on the Literature, Second Version," PIER Working Paper Archive 15-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 11 Nov 2015.
    3. Francis DiTraglia & Camilo Garcia-Jimeno, 2015. "On Mis-measured Binary Regressors: New Results And Some Comments on the Literature, Third Version," PIER Working Paper Archive 15-040, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 24 Nov 2015.
    4. DiTraglia, Francis J. & García-Jimeno, Camilo, 2019. "Identifying the effect of a mis-classified, binary, endogenous regressor," Journal of Econometrics, Elsevier, vol. 209(2), pages 376-390.
    5. Suyong Song & Stephen S. Baek, 2019. "Shape Matters: Evidence from Machine Learning on Body Shape-Income Relationship," Papers 1906.06747, arXiv.org.
    6. Francis J. DiTraglia & Camilo García-Jimeno, 2017. "Mis-classified, Binary, Endogenous Regressors: Identification and Inference," NBER Working Papers 23814, National Bureau of Economic Research, Inc.
    7. Andrews, Donald W.K., 2017. "Examples of L2-complete and boundedly-complete distributions," Journal of Econometrics, Elsevier, vol. 199(2), pages 213-220.
    8. Andrei Zeleneev & Kirill Evdokimov, 2023. "Simple estimation of semiparametric models with measurement errors," CeMMAP working papers 10/23, Institute for Fiscal Studies.
    9. Kirill S. Evdokimov & Andrei Zeleneev, 2023. "Simple Estimation of Semiparametric Models with Measurement Errors," Papers 2306.14311, arXiv.org, revised Mar 2024.
    10. Kim, Kyoo il & Petrin, Amil & Song, Suyong, 2016. "Estimating production functions with control functions when capital is measured with error," Journal of Econometrics, Elsevier, vol. 190(2), pages 267-279.

  9. Suyong Song & Susanne M. Schennach & Halbert White, 2015. "Estimating nonseparable models with mismeasured endogenous variables," Quantitative Economics, Econometric Society, vol. 6(3), pages 749-794, November.

    Cited by:

    1. Daniel Wilhelm, 2019. "Testing for the presence of measurement error," CeMMAP working papers CWP48/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Denni Tommasi & Arthur Lewbel & Rossella Calvi, 2017. "LATE with Mismeasured or Misspecified Treatment: An application to Women's Empowerment in India," Working Papers ECARES ECARES 2017-27, ULB -- Universite Libre de Bruxelles.
    3. Karun Adusumilli & Taisuke Otsu, 2015. "Nonparametric instrumental regression with errors in variables," STICERD - Econometrics Paper Series /2015/585, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    4. Takahide Yanagi, 2019. "Inference on local average treatment effects for misclassified treatment," Econometric Reviews, Taylor & Francis Journals, vol. 38(8), pages 938-960, September.
    5. Shiu, Ji-Liang, 2016. "Identification and estimation of endogenous selection models in the presence of misclassification errors," Economic Modelling, Elsevier, vol. 52(PB), pages 507-518.
    6. Francis J. DiTraglia & Camilo García-Jimeno, 2017. "Mis-classified, Binary, Endogenous Regressors: Identification and Inference," NBER Working Papers 23814, National Bureau of Economic Research, Inc.
    7. Song, Suyong, 2015. "Semiparametric estimation of models with conditional moment restrictions in the presence of nonclassical measurement errors," Journal of Econometrics, Elsevier, vol. 185(1), pages 95-109.
    8. Kengo Kato & Yuya Sasaki & Takuya Ura, 2021. "Robust inference in deconvolution," Quantitative Economics, Econometric Society, vol. 12(1), pages 109-142, January.

More information

Research fields, statistics, top rankings, if available.

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 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-AGR: Agricultural Economics (1) 2019-06-24. Author is listed
  2. NEP-BIG: Big Data (1) 2019-06-24. Author is listed
  3. NEP-CBA: Central Banking (1) 2016-11-27. Author is listed
  4. NEP-ECM: Econometrics (1) 2024-09-30. Author is listed
  5. NEP-MAC: Macroeconomics (1) 2016-11-27. Author is listed
  6. NEP-MON: Monetary Economics (1) 2016-11-27. Author is listed
  7. NEP-PAY: Payment Systems and Financial Technology (1) 2019-06-24. Author is listed

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