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The PolicyEngine US Python package contains a rules engine of the US tax-benefit system, and microdata generation for microsimulation analysis.

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![MS adoption credit](https://github.com/user-attachments/assets/b132dce9-72d9-41b0-bcf8-1bce179147b4) ![MS chartiable credit 2023](https://github.com/user-attachments/assets/e6009770-87cb-4598-ac2d-57aca4e75dcf) [Reference](https://www.dor.ms.gov/sites/default/files/Forms/Individual/80100231.pdf)

states/ms
2023

![NE stillborn credit](https://github.com/user-attachments/assets/e2eca2b5-cd10-46e2-81a8-feeca4a39268) [Reference](https://revenue.nebraska.gov/sites/revenue.nebraska.gov/files/doc/2022_Ne_Individual_Income_Tax_Booklet_8-307-2022_final_8.pdf)

states/ne
2022

![ND Stillborn deduction](https://github.com/user-attachments/assets/054d466f-3191-4b39-8591-b02fcb0ccbdb) [Reference](https://www.tax.nd.gov/sites/www/files/documents/forms/individual/2022-iit/2022-individual-income-tax-booklet.pdf)

states/nd
2022

[Reference](https://casetext.com/regulation/oklahoma-administrative-code/title-710-oklahoma-tax-commission/chapter-50-income/subchapter-15-oklahoma-taxable-income/part-7-credits-against-tax/section-71050-15-118-credit-for-nonrecurring-adoption-expenses)

states/ok
2023

[Reference](https://dor.sc.gov/forms-site/Forms/I360_2022.pdf)

states/sc
2022

![NE military retirement income](https://github.com/user-attachments/assets/5bc37aa3-ca17-4592-98c0-a6270f2ee68f) [Reference](https://revenue.nebraska.gov/sites/revenue.nebraska.gov/files/doc/2022_Ne_Individual_Income_Tax_Booklet_8-307-2022_final_8.pdf)

states/ne
2022

Currently Census applies a model when calculating it in the ASEC. Based on income and other factors. We can replicate it. https://www2.census.gov/programs-surveys/supplemental-poverty-measure/technical-documentation/spm_techdoc.pdf#page=17 >When reporting medical expenses, respondents are asked not...

The [ASEC codebook](https://www2.census.gov/programs-surveys/cps/techdocs/cpsmar23.pdf) suggests that `SPM_MEDXPNS` equals the sum of these: ```python cps["health_insurance_premiums_without_medicare_part_b"] = person.PHIP_VAL cps["over_the_counter_health_expenses"] = person.POTC_VAL cps["other_medical_expenses"] = person.PMED_VAL cps["medicare_part_b_premiums"] = person.PEMCPREM ``` @PavelMakarchuk and I compared them...