IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2201.02292.html
   My bibliography  Save this paper

Unconditional Effects of General Policy Interventions

Author

Listed:
  • Julian Martinez-Iriarte
  • Gabriel Montes-Rojas
  • Yixiao Sun

Abstract

This paper studies the unconditional effects of a general policy intervention, which includes location-scale shifts and simultaneous shifts as special cases. The location-scale shift is intended to study a counterfactual policy aimed at changing not only the mean or location of a covariate but also its dispersion or scale. The simultaneous shift refers to the situation where shifts in two or more covariates take place simultaneously. For example, a shift in one covariate is compensated at a certain rate by a shift in another covariate. Not accounting for these possible scale or simultaneous shifts will result in an incorrect assessment of the potential policy effects on an outcome variable of interest. The unconditional policy parameters are estimated with simple semiparametric estimators, for which asymptotic properties are studied. Monte Carlo simulations are implemented to study their finite sample performances. The proposed approach is applied to a Mincer equation to study the effects of changing years of education on wages and to study the effect of smoking during pregnancy on birth weight.

Suggested Citation

  • Julian Martinez-Iriarte & Gabriel Montes-Rojas & Yixiao Sun, 2022. "Unconditional Effects of General Policy Interventions," Papers 2201.02292, arXiv.org, revised Jul 2023.
  • Handle: RePEc:arx:papers:2201.02292
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2201.02292
    File Function: Latest version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. David H. Autor & Lawrence F. Katz & Melissa S. Kearney, 2005. "Rising Wage Inequality: The Role of Composition and Prices," NBER Working Papers 11628, National Bureau of Economic Research, Inc.
    2. Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Julian Martinez-Iriarte & YiXiao Sun, 2022. "Identification and Estimation of Unconditional Policy Effects of an Endogenous Binary Treatment: an Unconditional MTE Approach," Working Papers 131, Red Nacional de Investigadores en Economía (RedNIE).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Martinez-Iriarte, Julian & Montes-Rojas, Gabriel & Sun, Yixiao, 2022. "Location-Scale and Compensated Effects in Unconditional Quantile Regressions," University of California at San Diego, Economics Working Paper Series qt89z1w74z, Department of Economics, UC San Diego.
    2. Eric Ghysels & Leonardo Iania & Jonas Striaukas, 2018. "Quantile-based Inflation Risk Models," Working Paper Research 349, National Bank of Belgium.
    3. Jae Song & David J Price & Fatih Guvenen & Nicholas Bloom & Till von Wachter, 2019. "Firming Up Inequality," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 134(1), pages 1-50.
    4. Gaglianone, Wagner Piazza & Guillén, Osmani Teixeira de Carvalho & Figueiredo, Francisco Marcos Rodrigues, 2018. "Estimating inflation persistence by quantile autoregression with quantile-specific unit roots," Economic Modelling, Elsevier, vol. 73(C), pages 407-430.
    5. Philipp Ratz, 2022. "Nonparametric Value-at-Risk via Sieve Estimation," Papers 2205.07101, arXiv.org.
    6. Demiralay, Sercan & Ulusoy, Veysel, 2014. "Value-at-risk Predictions of Precious Metals with Long Memory Volatility Models," MPRA Paper 53229, University Library of Munich, Germany.
    7. repec:spo:wpecon:info:hdl:2441/eu4vqp9ompqllr09i8hjg0kpi is not listed on IDEAS
    8. Zsófia L. Bárány, 2016. "The Minimum Wage and Inequality: The Effects of Education and Technology," Journal of Labor Economics, University of Chicago Press, vol. 34(1), pages 237-274.
    9. Nowotarski, Jakub & Weron, Rafał, 2018. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
    10. Nicholas Apergis, 2015. "Money Demand Sensitivity to Interest Rates: The Case of Japans Zero-Interest Rate Policy," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 5(9), pages 1043-1049, September.
    11. Chao, Shih-Kang & Härdle, Wolfgang K. & Yuan, Ming, 2021. "Factorisable Multitask Quantile Regression," Econometric Theory, Cambridge University Press, vol. 37(4), pages 794-816, August.
    12. Xiaohong Chen & Roger Koenker & Zhijie Xiao, 2009. "Copula-based nonlinear quantile autoregression," Econometrics Journal, Royal Economic Society, vol. 12(s1), pages 50-67, January.
    13. repec:wyi:journl:002087 is not listed on IDEAS
    14. Herrera, Rodrigo & González, Nicolás, 2014. "The modeling and forecasting of extreme events in electricity spot markets," International Journal of Forecasting, Elsevier, vol. 30(3), pages 477-490.
    15. Chen, Cathy W.S. & Gerlach, Richard & Hwang, Bruce B.K. & McAleer, Michael, 2012. "Forecasting Value-at-Risk using nonlinear regression quantiles and the intra-day range," International Journal of Forecasting, Elsevier, vol. 28(3), pages 557-574.
    16. Hamidi, Benjamin & Maillet, Bertrand & Prigent, Jean-Luc, 2014. "A dynamic autoregressive expectile for time-invariant portfolio protection strategies," Journal of Economic Dynamics and Control, Elsevier, vol. 46(C), pages 1-29.
    17. Jorge E. Galán & María Rodríguez Moreno, 2020. "At-risk measures and financial stability," Financial Stability Review, Banco de España, issue Autumn.
    18. Alex Huang, 2013. "Value at risk estimation by quantile regression and kernel estimator," Review of Quantitative Finance and Accounting, Springer, vol. 41(2), pages 225-251, August.
    19. So Yeon Chun & Alexander Shapiro & Stan Uryasev, 2012. "Conditional Value-at-Risk and Average Value-at-Risk: Estimation and Asymptotics," Operations Research, INFORMS, vol. 60(4), pages 739-756, August.
    20. Jozef Baruník & Tobias Kley, 2019. "Quantile coherency: A general measure for dependence between cyclical economic variables," The Econometrics Journal, Royal Economic Society, vol. 22(2), pages 131-152.
    21. Samit Paul & Madhusudan Karmakar, 2017. "Relative Efficiency of Component GARCH-EVT Approach in Managing Intraday Market Risk," Multinational Finance Journal, Multinational Finance Journal, vol. 21(4), pages 247-283, December.
    22. Fatih Guvenen & Burhanettin Kuruscu, 2010. "A Quantitative Analysis of the Evolution of the US Wage Distribution, 1970–2000," NBER Chapters, in: NBER Macroeconomics Annual 2009, Volume 24, pages 227-276, National Bureau of Economic Research, Inc.

    More about this item

    JEL classification:

    • J01 - Labor and Demographic Economics - - General - - - Labor Economics: General
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2201.02292. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.