inflation.Rmd

---
title: "Inflation Data"
author: "Aaron Peikert"
date: "`r Sys.Date()`"
output: pdf_document
repro:
  packages:
    - here
    - tidyverse
    - lubridate
    - aaronpeikert/repro@fc7e884
  scripts:
    - R/prepare_inflation.R
  data:
    - data/raw/inflation.rds
---

```{r setup, include=FALSE}
repro::automate_load_packages()
repro::automate_load_scripts()
knitr::opts_chunk$set(echo = FALSE)
```

The dataset we use stems from the [Bank of England Research datasets](https://www.bankofengland.co.uk/statistics/research-datasets).

I quote:

> This dataset contains the individual responses to our Inflation Attitudes Survey, a quarterly survey of people’s feelings about inflation and other economic variables like the interest rate. 

```{r load-inflation}
# code chunks can come from other scripts, this one is loaded from:
# `R/prepare_inflation.R`
```

```{r transform-inflation}
# this chunk is also loaded from the same script
# note that they must be empty and the names must correspond
```

For this dataset the **Bank of England** asked `r prettyNum(nrow(inflation), big.mark = ".", decimal.mark = ",")` people for their *opinion* on the perceived and expected inflation.
The survey has run quarterly since `r min(inflation$year)`.

```{r}
inflation %>% 
  group_by(date) %>% 
  summarise(across(c(perception, expectation),
                   ~ mean(., na.rm = TRUE)),
            .groups = "drop") %>% 
  pivot_longer(c(expectation, perception)) %>% 
  ungroup() %>% 
  ggplot() +
  geom_line(aes(date, value, color = name)) + theme_minimal() +
  ylab("subjective inflation in %-points") +
  labs(color = "") +
  theme(legend.position = c(.1, .9)) +
  NULL
```

```{r}
with(mtcars, plot(hp, mpg))
```