Collective Agreements
Rubén Pérez Sanz
2023-06-27
Descriptives of Collective Agreements in Spain
The main purpose of this document is to have an idea of how collective agreements work in Spain.
Setting
Load
The libraries that I will need:
library(dplyr)
library(ggplot2)
library(statsr)
library(readxl)
library(expss)
library(stringr)
library(zoo)Define Theme
mytheme <- theme_gray
theme_update(
plot.title = element_text(
family = 'serif',
face = 'bold.italic',
colour = 'grey25',
size = '18'
),
axis.title = element_text(
family = 'serif',
face = 'bold',
colour = 'grey25',
size = '12'
),
axis.text = element_text(
family = 'serif',
colour = 'grey35',
size = '10'
),
legend.title = element_text(
family = 'serif',
colour = 'grey25',
face = 'bold',
size = '12'
),
legend.text = element_text(
family = 'serif',
colour = 'grey35',
size = '10'
)
)Define the paths
dell <- 0
if (dell == 1) {
computer <- "C:/Users/jj22684/"
} else {
computer <- "C:/Users/lenovo/"
}
setwd(paste0(computer,"Dropbox/WORK/data/REGCON/Codes/FIRM/3.descr"))
Main_path <- paste(computer, "Dropbox/WORK/data/REGCON", sep = "")
raw_path <- paste(computer, "Dropbox/WORK/data/REGCON/RAW files", sep = "")Load the database
load(paste(Main_path, "/Files/FIRM/built/regconfirm_built.R", sep = ""))Descriptives
Duplicates by codca and firmid
The firs table shows the number of repeated CBA, usually they are duplicated because they are renegotiated (new text).
The second table shows the number of CBA that a firm has signed, it may be the case that it has signed CBA’s in different provinces, towns or establishments.
## # A tibble: 8 × 3
## ndups n_codca excess
## <int> <int> <dbl>
## 1 1 4812 0
## 2 2 1748 1748
## 3 3 651 1302
## 4 4 180 540
## 5 5 52 208
## 6 6 23 115
## 7 7 6 36
## 8 8 6 42## # A tibble: 33 × 3
## ndups n_firms excess
## <int> <int> <dbl>
## 1 1 3678 0
## 2 2 1408 1408
## 3 3 549 1098
## 4 4 189 567
## 5 5 92 368
## 6 6 56 280
## 7 7 23 138
## 8 8 19 133
## 9 9 9 72
## 10 10 6 54
## 11 11 4 40
## 12 12 4 44
## 13 13 2 24
## 14 14 3 39
## 15 15 1 14
## 16 16 1 15
## 17 17 2 32
## 18 18 3 51
## 19 19 1 18
## 20 20 2 38
## 21 23 1 22
## 22 24 1 23
## 23 25 1 24
## 24 27 2 52
## 25 29 1 28
## 26 32 1 31
## 27 33 1 32
## 28 35 2 68
## 29 36 1 35
## 30 88 1 87
## 31 100 1 99
## 32 209 1 208
## 33 261 1 260Duplicates by province, economic activity and firm size.
The firs table shows the number of firms by province, eco act at 4 digit level and firms size in bins
The second table shows the number of firms by province, eco act at 2 digit level and firms size in bins
Procedure type
The graph below shows how many CAs have been negotiated, depending on:
- New agreement: the firm didn’t have a CA and now it has
- New text: the firm had a CA in place, and it has been renegotiated
Looking at the first graphs, many agreements are brand new agreements.
The second graph divides the type of procedure into the agreement nature.
Functional Scope: level of coverage of CA within the firm
Most CA apply to the entire firm
## # A tibble: 4 × 2
## funcscope n
## <chr> <int>
## 1 "Band Agreements" 397
## 2 "Enterprise Group/Linked Enterprises" 305
## 3 "Firm or all the Establishments of\nthe Firm" 7979
## 4 "One or Several Firm Establishments" 2788Date of publication
## Warning: The `trans` argument of `continuous_scale()` is deprecated as of ggplot2 3.5.0.
## ℹ Please use the `transform` argument instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## `summarise()` has grouped output by 'dtpublim'. You can override using the
## `.groups` argument.
State of validity
Firm size
In the first graph we see the distribution of firm size up to 500 employees, otherwise the histograme would be too distorted.
In the second graph, it is the same but for up to 100 employees to advert the spike at 6.
## The following objects are masked from REGCON_FIRM2 (pos = 5):
##
## codca, firmid, idca## Warning: Removed 490 rows containing non-finite outside the scale range (`stat_bin()`).
## Removed 490 rows containing non-finite outside the scale range (`stat_bin()`).## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`geom_bar()`).
## Removed 2 rows containing missing values or values outside the scale range
## (`geom_bar()`).
## Warning: Removed 2307 rows containing non-finite outside the scale range (`stat_bin()`).
## Removed 2 rows containing missing values or values outside the scale range
## (`geom_bar()`).
## # A tibble: 1 × 6
## `mean(size)` `var(size)` `min(size)` `median(size)` `max(size)` `sum(size)`
## <dbl> <dbl> <int> <dbl> <int> <int>
## 1 231. 1930977. 1 49 73838 1728081## # A tibble: 863 × 2
## size n
## <labelled> <int>
## 1 1 11
## 2 2 9
## 3 3 12
## 4 4 14
## 5 5 32
## 6 6 142
## 7 7 110
## 8 8 115
## 9 9 98
## 10 10 151
## # ℹ 853 more rowsFirm size by procedure type
## The following objects are masked from REGCON_FIRM2 (pos = 3):
##
## codca, firmid, idca, size, sizem, sizew## The following objects are masked from REGCON_FIRM2 (pos = 6):
##
## codca, firmid, idca## Warning: A numeric `legend.position` argument in `theme()` was deprecated in ggplot2
## 3.5.0.
## ℹ Please use the `legend.position.inside` argument of `theme()` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.## Warning: The dot-dot notation (`..density..`) was deprecated in ggplot2 3.4.0.
## ℹ Please use `after_stat(density)` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.## Warning: Removed 490 rows containing non-finite outside the scale range
## (`stat_bin()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_bar()`).
## Warning: Removed 2307 rows containing non-finite outside the scale range (`stat_bin()`).
## Removed 4 rows containing missing values or values outside the scale range
## (`geom_bar()`).
## # A tibble: 2 × 6
## proctype `mean(size)` `var(size)` `median(size)` `max(size)` `sum(size)`
## <fct> <dbl> <dbl> <dbl> <int> <int>
## 1 New Agreement 151. 1785511. 34 73838 603328
## 2 New Text 323. 2082533. 79 34793 1124753Firm size and delegates
## The following objects are masked from REGCON_FIRM2 (pos = 3):
##
## codca, firmid, idca, proctype, size, sizem, sizew## The following objects are masked from REGCON_FIRM2 (pos = 4):
##
## codca, firmid, idca, size, sizem, sizew## The following objects are masked from REGCON_FIRM2 (pos = 7):
##
## codca, firmid, idca## Warning: Removed 490 rows containing non-finite outside the scale range
## (`stat_bin()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_bar()`).
## Warning: Removed 2307 rows containing non-finite outside the scale range (`stat_bin()`).
## Removed 4 rows containing missing values or values outside the scale range
## (`geom_bar()`).
## # A tibble: 2 × 6
## proctype `mean(size)` `var(size)` `median(size)` `max(size)` `sum(size)`
## <fct> <dbl> <dbl> <dbl> <int> <int>
## 1 New Agreement 151. 1785511. 34 73838 603328
## 2 New Text 323. 2082533. 79 34793 1124753