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Differential-Privacy

Replication Package for "A Practical Method to Reduce Privacy Loss when Disclosing Statistics Based on Small Samples"

Figures Replication

This folder contains the Stata code to reproduce figures 1 to 3 in “A Practical Method to Reduce Privacy Loss when Disclosing Statistics Based on Small Samples” by Chetty and Friedman (2019).

To run the code, please set the file paths in in the do-file all_figures_paper.do to the files contained in this replication package (tract_covariates.dta and tract_outcomes_early_dta_dp.dta).

Implementation of Noise-Infusion Algorithm: Example Code

The sub-folder example_code_implementation_guide contains two examples of how to implement the noise-infusion algorithm outlined in the Appendix A of “A Practical Method to Reduce Privacy Loss when Disclosing Statistics Based on Small Samples” by Chetty and Friedman (2019). The three files in the sub-folder contain the following:

Example 1 – Simple regression coefficient as statistic of interest

Implementation_guide_simple_reg.do

Stata do-file showing a step-by-step example of how to apply the noise-infusion algorithm to publicly release the estimated coefficients of a simple regression estimate of child income rank on parent income rank in each of the cells of a simulated dataset.

Example 2 – Predicted value of Y at a certain value of X as statistic of interest

Implementation_guide_p_25_prediction.do

Stata do-file showing a step-by-step example of how to apply the noise-infusion algorithm to publicly release the predicted value of child income rank at the 25th percentile of the parental income distribution in each of the cells of a simulated dataset.

Dataset

private_data_by_cells.dta

Simulated dataset in Stata format containing information on child income rank and parent income rank of 10,000 fictitious individuals grouped in 111 cells.Variable names: parent_rank, kid_rank, cell.

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Replication Package for "A Practical Method to Reduce Privacy Loss when Disclosing Statistics Based on Small Samples"

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