Gender Equality in Denmark - using BigQuery

Equality in Denmark - difference in what men and women earn


According to Danmarks Statistik, pay gap in 2017 was 13%

Pay gap is the average difference between the remuneration for men and women who are working
Pay gap was 13% in Denmark according to data that is publicly available in Statistikbanken at https://www.statistikbanken.dk/LIGELI2

Data contains job roles and age. Here are the top 15 job roles where pay gap is over 20%


Top 15

Row	Work	Age31to39	Age41to49
1	22 Work in the field of health	21.7	31.0
2	3311 Work on securities and currency trading	19.8	27.4
3	331 Work with finance, accounting and mathematics	20.1	26.2
4	3313 Accounting	20.8	25.1
5	1211 Management in finance functions	16.8	24.2
6	815 Operator work in the manufacture of textile, fur and leather products	17.0	24.0
7	1420 Management of the main activity in retail and wholesale trade	15.3	23.9
8	142 Management of the main activity in retail and wholesale trade	15.3	23.9
9	3321 Insurance work	18.6	23.8
10	3331 Freight Forwarders Work	17.3	23.7
11	33 Work in business services, finance, administration and sales	19.6	22.7
12	7511 Butchery, fish trade and related work in food production	14.4	22.5

13	52 Sales	15.4	22.5
14	3334 Real estate agency and property management work	22.2	22.2
15	226 Other Health work	13.7	21.9

Pay gap doubles with age 
The numbers increase consistently for all work functions. Men apparently get better at their jobs. Women get worse?

Working functions with negative pay gap

I found work functions with negative pay gap - where women in the 40's earn more than men.

Row	Work	Age31to39	Age41to49
1	2353 Other language teaching	-1.2	-6.5
2	9411 Cooking fastfood	-10.9	-5.5
3	2263 Work in the field of work and hygiene	0.0	-3.5
4	1324 Management of the main activity in supply, distribution and the like	-7.3	-3.3
5	941 Manual work in cooking the food	-6.8	-3.2
6	94 Manual work in cooking the food	-6.8	-3.2
7	5329 Other care work in the field of health	-2.1	-2.9
8	4224 Hotel receptionist work	-3.0	-2.3
9	1321 Management in production	10.6	-2.0
10	5321 Care work at institutions and hospitals (excluding nursing homes)	-1.2	-2.0
11	2636 Work in religion	-1.1	-1.6

Teaching and manual work. Hm, exciting. Age is also a crucial factor here. It appears that women in the 40's are worse at cooking and teaching than women in the 30's.


How did I do this?

I have worked with BI before and I can remember it as something very difficult. Firstly, my laptop should be big enough to install additional Tools in Excel.

It may seem strange - yes, Sonja you are a developer, you have a big laptop. No, no when you sit with customers, you get the same laptop as the customer's employees. Employees working with BI do not otherwise need "developer" laptops and Windows and Office Pro versions and licenses.

Other thing that irritates me that BI work ends up many times being a work on installing SQL or fixing the SQL installation.

In addition, ordinary employees are not allowed to install software so even though their laptops are big enough they can not get anything but "standard" Windows and Office.

So, how did I do this?

I used Google BigQuery that runs completely in browser.

1. I found a page about equality her and data in .csv format at https://www.statistikbanken.dk/

2. I chose all the columns at https://www.statistikbanken.dk/LIGELI2

3. Saved everything as a .csv file
4. I opened https://bigquery.cloud.google.com/
5. I selected "Create new data set" and called it "loengab"

6. I added new table "PayGap" and used the .csv file as source

7. "Automatically detect" is very smart, but I chose to add my own columns

8. I clicked on "Compose query" button in top left corner of the page

9. A page where I can write SQL queries opened. Cool...

10. The result is a table, data that can be saved or exported to sheets.

Query to get job roles where women earn more: