R packages

  • RATest: A collection of randomization tests. (Joint with Mauricio Olivares-Gonzalez)

    Brackground paper: Canay and Kamat (2017)

    Description: A collection of randomization tests, data sets and examples. The current version focuses on two testing problems and their implementation in empirical work. First, it facilitates the empirical researcher to test for particular hypotheses, such as comparisons of means, medians, and variances from k populations using robust permutation tests, which asymptotic validity holds under very weak assumptions, while retaining the exact rejection probability in finite samples when the underlying distributions are identical. Second, the description and implementation of a permutation test for testing the continuity assumption of the baseline covariates in the sharp regression discontinuity design (RDD) as in Canay and Kamat (2017). More specifically, it allows the user to select a set of covariates and test the aforementioned hypothesis using a permutation test based on the Cramer-von Miss test statistic. Graphical inspection of the empirical CDF and histograms for the variables of interest is also supported in the package.

  • ioanalysis. Input Output Analysis (Joint with John Wade)

    Description: Calculates fundamental IO matrices (Leontief, Wassily W. 1951, Ghosh, A. 1958) within period analysis via various rankings and coefficients (Sonis and Hewings 2006, Blair and Miller 2009, Antras et al 2012, Hummels, Ishii, and Yi 2001); across period analysis with impact analysis (Dietzenbacher, van der Linden, and Steenge 2006, Sonis, Hewings, and Guo 2006); and a variety of table operators.

Data Visualization Apps

  • Crime hotspots

    The objective is to map out crime hot spots in different cities across the US where crime data is available. Crime does not spread uniformly accross cities. On the contrary, it tends to cluster in some areas or neighbourhoods and be absent in others. Areas where crime is more concentrated are oftenly referred to as hot spots. There exist multiple ways to try to detect these areas. In this app I identify crime hotspots using a bivariate density estimation strategy. For more on crime hot spots the interested reader is encouraged to visit the National Institute of Justice web site on Hot Spot Policing

  • State and Regional Employment Indicators for Argentina (In Spanish)



Ignacio
Sarmiento Barbieri

University of Illinois