https://github.com/hendersontrent/qldyjcost

Simple R package for costs and calculations of youth offending in Queensland, Australia
https://github.com/hendersontrent/qldyjcost

cost-benefit cost-benefit-analysis econometrics economics evaluation statistics

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Simple R package for costs and calculations of youth offending in Queensland, Australia

• Host: GitHub
• URL: https://github.com/hendersontrent/qldyjcost
• Owner: hendersontrent
• License: other
• Created: 2024-06-06T03:46:39.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-08-13T11:11:47.000Z (3 months ago)
• Last Synced: 2024-10-11T18:48:22.739Z (27 days ago)
• Topics: cost-benefit, cost-benefit-analysis, econometrics, economics, evaluation, statistics
• Language: R
• Homepage:
• Size: 42 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.Rmd
  • License: LICENSE

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README

        
---

output: rmarkdown::github_document

---

# qldyjcost

Cost of Offending Tools for Youth Justice in Queensland

```{r, include = FALSE}

knitr::opts_chunk$set(

comment = NA, fig.width = 12, fig.height = 8, cache = FALSE)

```

```{r set-options, echo=FALSE, cache=FALSE}

options(width = 400)

```

## Purpose

This is a simple, lightweight R package purely for convenience for my day job as a Senior Data Scientist at the consulting firm [Nous Group](https://nousgroup.com/) where I frequently conduct evaluations for Queensland Youth Justice.

## Installation

You can install the development version of `qldyjcost` from GitHub using the following:

```{r eval = FALSE}

devtools::install_github("hendersontrent/qldyjcost")

```

## Usage

The core of `qldyjcost` is a data frame of historical costs from peer-reviewed sources called `yjcosts`. It can be accessed easily via:

```{r, message = FALSE, warning = FALSE}

library(qldyjcost)

head(yjcosts)

```

`yjcosts` contains historical offending costs broken down by offence seriousness for court costs, police costs, wider social costs, and custody costs.

`qldyjcost` also contains functionality for adjusting the historical offending costs to values for a given financial year using inflation. The `get_cpi` function webscrapes inflation rates from the [Australian Bureau of Statistics](https://www.abs.gov.au/statistics/economy/price-indexes-and-inflation/consumer-price-index-australia/) and automatically cleans it up ready for use:

```{r, message = FALSE, warning = FALSE}

cpi <- get_cpi(location = "Australia")

head(cpi)

```

Instead of grabbing CPI for the country, we can instead get it for any capital city:

```{r, message = FALSE, warning = FALSE}

cpi_bris <- get_cpi(location = "Brisbane")

head(cpi_bris)

```

While this function is useful in isolation, it forms a key component of the workhorse function of `yjcosts` which is `adjust_costs`. `adjust_costs` applies inflation adjustments to the offending cost data to any given financial year. Specifically, it does this by averaging CPI values for each FY associated with the baseline costs in `yjcosts` as well as the user-specified FY to adjust to. The interface is incredible simple. Here is how to adjust costs to FY 2023-24 dollars:

```{r, message = FALSE, warning = FALSE}

adj <- adjust_costs(fy = "2023-24", location = "Australia")

head(adj)

```