Travaglini, Guido (2010): Supervised Principal Components and Factor Instrumental Variables. An Application to Violent CrimeTrends in the US, 19822005.

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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 reducedsize instrument set from a large database, possibly dominated by nonexogeneity and weakness. While the first method stresses the role of regressors by taking account of their datainduced tie with the endogenous variable, the second places absolute relevance on the datainduced 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 19822005. Demographic variables, and especially abortion, law enforcement and unchecked gun availability are found to be the most significant determinants.
Item Type:  MPRA Paper 

Original Title:  Supervised Principal Components and Factor Instrumental Variables. An Application to Violent CrimeTrends in the US, 19822005. 
Language:  English 
Keywords:  Principal Components; Instrumental Variables; Generalized Method of Moments; Crime; Law and Order. 
Subjects:  C  Mathematical and Quantitative Methods > C2  Single Equation Models; Single Variables > C22  TimeSeries Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models K  Law and Economics > K1  Basic Areas of Law > K14  Criminal Law C  Mathematical and Quantitative Methods > C0  General > C01  Econometrics 
Item ID:  22077 
Depositing User:  Guido Travaglini 
Date Deposited:  14. Apr 2010 23:18 
Last Modified:  12. Feb 2013 14:21 
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URI:  http://mpra.ub.unimuenchen.de/id/eprint/22077 