# AMECO Dataset

#### Eric Persson

#### 2017-02-15

## Introduction

This package contains the entire European Commission Annual macro-economic (AMECO) database in a format amenable to analysis in R.

The AMECO database was last updated: 13 February 2017.

## Simple example

The dataset is in a clean, long format:

    library(dplyr)

    ##
    ## Attaching package: 'dplyr'

    ## The following objects are masked from 'package:stats':
    ##
    ##     filter, lag

    ## The following objects are masked from 'package:base':
    ##
    ##     intersect, setdiff, setequal, union

    library(ameco)
    head(ameco)

    ## # A tibble: 6 × 8
    ##                code                           country   sub.chapter
    ##               <chr>                             <chr>         <chr>
    ## 1 EU28.1.0.0.0.NPTD                    European Union 01 Population
    ## 2 EU15.1.0.0.0.NPTD     European Union (15 countries) 01 Population
    ## 3 EA19.1.0.0.0.NPTD                         Euro area 01 Population
    ## 4 EA12.1.0.0.0.NPTD          Euro area (12 countries) 01 Population
    ## 5 DU15.1.0.0.0.NPTD EU15 (including D_W West-Germany) 01 Population
    ## 6 DA12.1.0.0.0.NPTD EA12 (including D_W West-Germany) 01 Population
    ## # ... with 5 more variables: title <chr>, unit <chr>, cntry <chr>,
    ## #   year <dbl>, value <dbl>

Filtering with the `sub.chapter` variable allows you to easily find the variable of interest:

    ameco %>%
      filter(sub.chapter == "01 Population") %>%
      .$title %>%
      unique()

    ## [1] "Total population (National accounts)"
    ## [2] "Total population"
    ## [3] "Population: 0 to 14 years"
    ## [4] "Population: 15 to 64 years"
    ## [5] "Population: 65 years and over"

Being interested in the total population of a few countries, we can easily subset the data and plot the results:

    library(ggplot2)

    ameco %>%
      dplyr::filter(title == "Total population",
             year == 2015,
             cntry %in% c("USA", "JPN", "DEU", "FRA", "ESP", "ITA")) %>%
      ggplot(aes(x = reorder(country, -value), y = value / 1000)) +
      geom_bar(stat = "identity") +
      theme_bw() +
      labs(x = NULL, y = "Population (millions)", title = "Total population")

## Disclaimer

This package is not affiliated with, nor endorsed by, the European Commission. I aim to update it whenever the AMECO database is updated. If you ever see that it is out-of-date, don’t hesitate to send a pull request and/or remind me to update it.