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https://github.com/urbananalyst/us-hardship-index

National hardship index from US census data
https://github.com/urbananalyst/us-hardship-index

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National hardship index from US census data

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README 

        
---

title: "US Hardship Index"

output:

  md_document:

    variant: markdown_github



  rmarkdown::html_vignette:

    self_contained: no

---



```{r opts, echo = FALSE}

knitr::opts_chunk$set (

    collapse = TRUE,

    warning = TRUE,

    message = TRUE,

    width = 120,

    comment = "#>",

    fig.retina = 2,

    fig.path = "README-"

)

```



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status](https://github.com/UrbanAnalyst/us-hardship-index/workflows/R-CMD-check/badge.svg)](https://github.com/UrbanAnalyst/us-hardship-index/actions?query=workflow%3AR-CMD-check)

[![Project Status: Active](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)



# US Hardship Index



`us-hardship-index` is an R package for calculating a hardship index for

specified US states, using data from the US Census Bureau's *American Community

Survey*. It includes the single primary function `hs_hardship_index()`, which

accepts the two parameters of:



- "state" for the desired US state; and

- "year" for the desired year (with values available since 2010).



The index itself is calculated from the methodology of "*An Update on Urban

Hardship*," by Lisa M. Monteil, Richard P. Nathan, and David J. Wright (2004),

*The Nelson A. Rockefeller Institute of Goverment*. It is formed as a multiple

of the following six measures, each standardised to unit (or percentage)

scales:



- *occupancy*: Proportion of rooms with > 1 occupant per room;

- *poverty*: Proportion of households below poverty line;

- *unemployment*: Proportion of unemployed adults;

- *no_hs*: Proportion of population without highschool diploma

- *deps*:  Proportion of population who may be considered dependent; that is

  either under 18 or over 65

- *income*: Per-capita income



All variables are quantified such that lower values are better, except for

income. The hardship index is then simply the product of those six metrics,

again standardised to a unit (or percentage) scale. An example of the index in

action is provided by [the city of Chicago](

https://data.cityofchicago.org/Health-Human-Services/Census-Data-Selected-socioeconomic-indicators-in-C/kn9c-c2s2/data),

as a table of the six metrics plus their conversion to a composite hardship

index.



Note that those Chicago data are ultimately transformed into a single rank for

each measured area, and so manifest a perfectly uniform distribution. In

contrast, the values returned by the `hs_hardship_index()` function are not

transformed, and so generally manifest highly skewed distributions. The

logarithm of these values will nevertheless generally be approximately normally

distributed. Accordingly, any statistical analyses of hardship values should

generally be applied to log-transformed versions of the values derived here.



## Access to Census Bureau Data



This package requires an API key for census.gov, which can be obtained from

[the Census Bureau's website](https://api.census.gov/data/key_signup.html).

This key should be stored as an environment variable named `CENSUS_API_KEY`,

generally by specifying its value in the `~/.Renviron` file. Alternatively, the

key can be set with the [`tidycensus` function,

`census_api_key()`](https://walker-data.com/tidycensus/reference/census_api_key.html).