# LOAD_PNADC

The `load_pnadc` function is a wrapper for `get_pnadc` from the package `PNADcIBGE`, with added identification algorithms for panel construction. For details on the identification algorithms, see `vignette("BUILD_PNADC_PANEL")`.

Panel Structure:

The table below shows the first and last quarter (`ANOtrimestre`, e.g. `20121` = 2012 Q1) covered by each PNADC rotating panel:

Panel | Start | End
--- | --- | ---
1 | 20121 | 20124
2 | 20121 | 20141
3 | 20132 | 20152
4 | 20143 | 20163
5 | 20154 | 20174
6 | 20171 | 20191
7 | 20182 | 20202
8 | 20193 | 20213
9 | 20204 | 20224
10 | 20221 | 20241
11 | 20232 | 20252
12 | 20243 | 20263
13 | 20254 | 20274
14 | 20271 | 20291

Usage:

Default:

    load_pnadc(
      save_to = getwd(),
      years,
      quarters = 1:4,
      panel = "advanced_3",
      raw_data = FALSE,
      save_options = c(TRUE, TRUE),
      vars = NULL
    )

To download PNADC data for all quarters of 2022 and 2023, with advanced fuzzy identification (Stage 3), simply run:

    load_pnadc(
      save_to = "Directory/You/Would/like/to/save/the/files",
      years = 2022:2023,
      panel = "advanced_3"
    )

To download PNADC data for all of 2022, but only the first quarter of 2023, run:

    load_pnadc(
      save_to = "Directory/You/Would/like/to/save/the/files",
      years = 2022:2023,
      quarters = list(1:4, 1)
    )

To download PNADC data without any variables treatment or identification (e.g., for all quarters of 2021), run:

    load_pnadc(
      save_to = "Directory/You/Would/like/to/save/the/files",
      years = 2021,
      panel = "none",
      raw_data = TRUE
    )

To download PNADC data, save quarters on disk, and save panels as Parquet, run:

    load_pnadc(
      save_to = "Directory/You/Would/like/to/save/the/files",
      years = 2022,
      save_options = c(TRUE, FALSE)
    )

To download PNADC data and save panels as RDS but discard the quarterly files, run:

    load_pnadc(
      save_to = "Directory/You/Would/like/to/save/the/files",
      years = 2022,
      save_options = c(FALSE, TRUE)
    )

To download only a specific subset of variables — for example, age (`V2009`) and habitual income (`VD4019`) — alongside the structural columns that `PNADcIBGE` always returns, run:

    load_pnadc(
      save_to = "Directory/You/Would/like/to/save/the/files",
      years = 2022,
      vars = c("V2009", "VD4019")
    )

> Note: `PNADcIBGE::get_pnadc()` always downloads a set of ~210 structural columns regardless of the `vars` argument. These include survey design weights (`V1027`, `V1028`, `V1028001`–`V1028200`, `posest`, `posest_sxi`), deflator variables (`Habitual`, `Efetivo`), and identifiers such as `UF`, `Estrato`, `V1029`, `V1033`, and `ID_DOMICILIO`. The `vars` argument adds columns on top of those; it does not restrict them. Use `vars = NULL` (the default) to download all available microdata columns.

If you specify `vars` and also request panel identification, any columns required by the identification algorithm that are absent from `vars` will be added automatically and a warning will tell you which ones were added. For example, when using `panel = "advanced_3"`, the columns `V2007`, `V20082`, `V20081`, `V2008`, and `V2003` must be present. If you omit them from `vars`, the function adds them for you:

    # Only V2009 requested, but panel = "advanced_3" needs
    # V2007, V20082, V20081, V2008 and V2003 — these are added automatically
    # with a warning.
    load_pnadc(
      save_to = "Directory/You/Would/like/to/save/the/files",
      years = 2022,
      panel = "advanced_3",
      vars = c("V2009", "VD4019")
    )

Options:

1. save_to: The directory in which the user desires to save the downloaded files.

2. years: picks the years for which the data will be downloaded

3. quarters: The quarters within those years to be downloaded. Can be either a vector such as `1:4` for consistent quarters across years, or a list of vectors, if quarters are different for each year (e.g. `list(1:4, 1:2)` for four quarters in the first year and two in the second).

4. panel: Which panel algorithm to apply to this data. There are five options:

   - `none`: No panel is built. If `raw_data = TRUE`, returns the original data. Otherwise, creates some extra treated variables. Quarterly files are saved depending on `save_options`.
   - `basic`: Performs basic identification steps using household IDs, sex, and exact dates of birth.
   - `advanced_1`: Performs Stage 1 advanced identification, imputing missing birth dates using within-household donors.
   - `advanced_2`: Performs Stage 2 advanced identification, relaxing the year of birth constraint.
   - `advanced_3` (Recommended): Performs Stage 3 advanced identification, utilizing Graph Theory for fuzzy matching of fragmented interviews to account for typographical errors.

5. raw_data: A command to define if the user would like to download the raw or treated data. There are two options:

   - `TRUE`: if you want the PNADC variables as they come.
   - `FALSE`: if you want the treated version of the PNADC variables.

6. save_options: A logical vector of length 2 controlling file saving behavior:

   - `c(TRUE, TRUE)` (default): saves quarterly and panel files as `.rds`.
   - `c(FALSE, TRUE)`: does not save quarterly files; saves panel files as `.rds`.
   - `c(TRUE, FALSE)`: saves quarterly and panel files as `.parquet` datasets.
   - `c(FALSE, FALSE)`: does not save quarterly files; saves panel files as a `.parquet` dataset.

7. vars: A character vector of additional variable names to download, following the same convention as `vars` in `PNADcIBGE::get_pnadc()`. Use `NULL` (the default) to download all available microdata columns. See the note above regarding the ~210 structural columns that are always returned by `PNADcIBGE::get_pnadc()` regardless of this argument

Details:

The function performs the following steps:

1. Loop over years and quarters using `PNADcIBGE::get_pnadc` to download the data. All quarters are collected in memory and saved depending on `save_options`.
2. Split the data into panels by the panel variable `V1014`.
3. Apply the identification algorithms defined in `build_pnadc_panel`.
4. Save the panel files as `.rds` or `.parquet`, depending on `save_options`.

- The base identification logic in `build_pnadc_panel` was originally drawn from Ribas, Rafael Perez, and Sergei Suarez Dillon Soares (2008): “Sobre o painel da Pesquisa Mensal de Emprego (PME) do IBGE”, with extensive modernizations, missing-data imputation, and graph-based fuzzy matching introduced by the Data Zoom team.