IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/22077.html
   My bibliography  Save this paper

Supervised Principal Components and Factor Instrumental Variables. An Application to Violent CrimeTrends in the US, 1982-2005

Author

Listed:
  • Travaglini, Guido

Abstract

Supervised Principal Component Analysis (SPCA) and Factor Instrumental Variables (FIV) are competing methods addressed at estimating models affected by regressor collinearity and at detecting a reduced-size instrument set from a large database, possibly dominated by non-exogeneity and weakness. While the first method stresses the role of regressors by taking account of their data-induced tie with the endogenous variable, the second places absolute relevance on the data-induced structure of the covariance matrix and selects the true common factors as instruments by means of formal statistical procedures. Theoretical analysis and Montecarlo simulations demonstrate that FIV is more efficient than SPCA and standard Generalized Method of Moments (GMM) even when the instruments are few and possibly weak. The prefered FIV estimation is then applied to a large dataset to test the more recent theories on the determinants of total violent crime and homicide trends in the United States for the period 1982-2005. Demographic variables, and especially abortion, law enforcement and unchecked gun availability are found to be the most significant determinants.

Suggested Citation

  • Travaglini, Guido, 2010. "Supervised Principal Components and Factor Instrumental Variables. An Application to Violent CrimeTrends in the US, 1982-2005," MPRA Paper 22077, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:22077
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/22077/1/MPRA_paper_22077.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kapetanios, George & Marcellino, Massimiliano, 2010. "Factor-GMM estimation with large sets of possibly weak instruments," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2655-2675, November.
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. Santos Silva, J. M. C. & Cardoso, F. N., 2001. "The Chow-Lin method using dynamic models," Economic Modelling, Elsevier, vol. 18(2), pages 269-280, April.
    4. Whitney K. Newey & Richard J. Smith, 2004. "Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators," Econometrica, Econometric Society, vol. 72(1), pages 219-255, January.
    5. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    6. Ted Joyce, 2004. "Did Legalized Abortion Lower Crime?," Journal of Human Resources, University of Wisconsin Press, vol. 39(1).
    7. Altonji, Joseph G & Segal, Lewis M, 1996. "Small-Sample Bias in GMM Estimation of Covariance Structures," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 353-366, July.
    8. Seung C. Ahn & Alex R. Horenstein, 2013. "Eigenvalue Ratio Test for the Number of Factors," Econometrica, Econometric Society, vol. 81(3), pages 1203-1227, May.
    9. John J. Donohue III & Steven D. Levitt, 2001. "The Impact of Legalized Abortion on Crime," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(2), pages 379-420.
    10. Jan J. J. Groen & George Kapetanios, 2009. "Parsimonious estimation with many instruments," Staff Reports 386, Federal Reserve Bank of New York.
    11. Andrews, Donald W.K. & Stock, James H., 2007. "Testing with many weak instruments," Journal of Econometrics, Elsevier, vol. 138(1), pages 24-46, May.
    12. Ian T. Jolliffe, 1982. "A Note on the Use of Principal Components in Regression," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 31(3), pages 300-303, November.
    13. John Lott & John Whitley, "undated". "Abortion and Crime: Unwanted Children and Out-of-Wedlock Births," Yale Law School John M. Olin Center for Studies in Law, Economics, and Public Policy Working Paper Series yale_lepp-1018, Yale Law School John M. Olin Center for Studies in Law, Economics, and Public Policy.
    14. Bai, Jushan & Ng, Serena, 2007. "Determining the Number of Primitive Shocks in Factor Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 52-60, January.
    15. John J. Donohue, III & Steven D. Levitt, 2004. "Further Evidence that Legalized Abortion Lowered Crime: A Reply to Joyce," Journal of Human Resources, University of Wisconsin Press, vol. 39(1).
    16. Donohue III, John J. & Wolfers, Justin, 2006. "Uses and Abuses of Empirical Evidence in the Death Penalty Debate," IZA Discussion Papers 1949, Institute of Labor Economics (IZA).
    17. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    18. Chow, Gregory C & Lin, An-loh, 1971. "Best Linear Unbiased Interpolation, Distribution, and Extrapolation of Time Series by Related Series," The Review of Economics and Statistics, MIT Press, vol. 53(4), pages 372-375, November.
    19. Bair, Eric & Hastie, Trevor & Paul, Debashis & Tibshirani, Robert, 2006. "Prediction by Supervised Principal Components," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 119-137, March.
    20. Fernandez, Roque B, 1981. "A Methodological Note on the Estimation of Time Series," The Review of Economics and Statistics, MIT Press, vol. 63(3), pages 471-476, August.
    21. Ehrlich, Isaac, 1975. "The Deterrent Effect of Capital Punishment: A Question of Life and Death," American Economic Review, American Economic Association, vol. 65(3), pages 397-417, June.
    22. Tommaso Proietti, 2006. "Temporal disaggregation by state space methods: Dynamic regression methods revisited," Econometrics Journal, Royal Economic Society, vol. 9(3), pages 357-372, November.
    23. Hashem Dezhbakhsh & Paul H. Rubin & Joanna M. Shepherd, 2003. "Does Capital Punishment Have a Deterrent Effect? New Evidence from Postmoratorium Panel Data," American Law and Economics Review, American Law and Economics Association, vol. 5(2), pages 344-376, August.
    24. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    25. Ted Joyce, 2001. "Did Legalized Abortion Lower Crime?," NBER Working Papers 8319, National Bureau of Economic Research, Inc.
    26. Whitney K. Newey & Frank Windmeijer, 2005. "GMM with many weak moment conditions," CeMMAP working papers CWP18/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    27. Ian Ayres & John J. Donohue III, 2002. "Shooting Down the More Guns, Less Crime Hypothesis," NBER Working Papers 9336, National Bureau of Economic Research, Inc.
    28. Baoline Chen, 2007. "An Empirical Comparison of Methods for Temporal Distribution and Interpolation at the National Accounts," BEA Papers 0077, Bureau of Economic Analysis.
    Full references (including those not matched with items on IDEAS)

    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. Gebhard Kirchgässner, 2011. "Econometric Estimates of Deterrence of the Death Penalty: Facts or Ideology?," Kyklos, Wiley Blackwell, vol. 64(3), pages 448-478, August.
    2. Travaglini, Guido, 2010. "Dynamic Econometric Testing of Climate Change and of its Causes," MPRA Paper 23600, University Library of Munich, Germany.
    3. Durlauf, Steven N. & Navarro, Salvador & Rivers, David A., 2010. "Understanding aggregate crime regressions," Journal of Econometrics, Elsevier, vol. 158(2), pages 306-317, October.
    4. Travaglini, Guido, 2011. "Principal Components and Factor Analysis. A Comparative Study," MPRA Paper 35486, University Library of Munich, Germany.
    5. Steven D. Levitt, 2004. "Understanding Why Crime Fell in the 1990s: Four Factors that Explain the Decline and Six that Do Not," Journal of Economic Perspectives, American Economic Association, vol. 18(1), pages 163-190, Winter.
    6. Julio Cáceres-Delpiano & Eugenio Giolito, 2012. "The Impact of Unilateral Divorce on Crime," Journal of Labor Economics, University of Chicago Press, vol. 30(1), pages 215-248.
    7. Angela K. Dills & Jeffrey A. Miron & Garrett Summers, 2010. "What Do Economists Know about Crime?," NBER Chapters, in: The Economics of Crime: Lessons For and From Latin America, pages 269-302, National Bureau of Economic Research, Inc.
    8. Todd D. Kendall & Robert Tamura, 2010. "Unmarried Fertility, Crime, and Social Stigma," Journal of Law and Economics, University of Chicago Press, vol. 53(1), pages 185-221, February.
    9. Abberger, Klaus & Graff, Michael & Siliverstovs, Boriss & Sturm, Jan-Egbert, 2018. "Using rule-based updating procedures to improve the performance of composite indicators," Economic Modelling, Elsevier, vol. 68(C), pages 127-144.
    10. Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," CIRJE F-Series CIRJE-F-430, CIRJE, Faculty of Economics, University of Tokyo.
    11. Huang, Huichou & MacDonald, Ronald & Zhao, Yang, 2012. "Global Currency Misalignments, Crash Sensitivity, and Downside Insurance Costs," MPRA Paper 53745, University Library of Munich, Germany, revised 18 Nov 2013.
    12. Campbell Leith & Jim Malley, 2007. "A Sectoral Analysis of Price-Setting Behavior in U.S. Manufacturing Industries," The Review of Economics and Statistics, MIT Press, vol. 89(2), pages 335-342, May.
    13. Russell Davidson & Victoria Zinde‐Walsh, 2017. "Advances in specification testing," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 50(5), pages 1595-1631, December.
    14. Cuevas Ángel & Quilis Enrique M. & Espasa Antoni, 2015. "Quarterly Regional GDP Flash Estimates by Means of Benchmarking and Chain Linking," Journal of Official Statistics, Sciendo, vol. 31(4), pages 627-647, December.
    15. François, Abel & Magni-Berton, Raul & Weill, Laurent, 2014. "Abortion and crime: Cross-country evidence from Europe," International Review of Law and Economics, Elsevier, vol. 40(C), pages 24-35.
    16. La Vecchia, Davide & Moor, Alban & Scaillet, Olivier, 2023. "A higher-order correct fast moving-average bootstrap for dependent data," Journal of Econometrics, Elsevier, vol. 235(1), pages 65-81.
    17. Yamamoto, Yohei & Tanaka, Shinya, 2015. "Testing for factor loading structural change under common breaks," Journal of Econometrics, Elsevier, vol. 189(1), pages 187-206.
    18. Jürgen Bierbaumer & Sandra Bilek-Steindl, 2017. "Quarterly National Accounts – Manual for Austria. Description of Applied Methods and Data Sources," WIFO Studies, WIFO, number 60427, April.
    19. Vasilis Sarafidis & Tom Wansbeek, 2012. "Cross-Sectional Dependence in Panel Data Analysis," Econometric Reviews, Taylor & Francis Journals, vol. 31(5), pages 483-531, September.
    20. Huang, Yu-Lieh, 2012. "Measuring business cycles: A temporal disaggregation model with regime switching," Economic Modelling, Elsevier, vol. 29(2), pages 283-290.

    More about this item

    Keywords

    Principal Components; Instrumental Variables; Generalized Method of Moments; Crime; Law and Order.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • K14 - Law and Economics - - Basic Areas of Law - - - Criminal Law
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

    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:pra:mprapa:22077. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    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.