The aim of this study is to analyse the data of migration between Germany and other EU countries in the time frame between 1974 to 2014. We will explore the data analyse change in time, and relative to countries, use the data to forecast mogration in years 2015 and 2016.
To summarize the result, we see a incresing pattern in the number of migrations both to and from Germany, specially from 2000’s. The highest total number of departure from Germany to another country took place in 2014 to Poland with 138 thousand migrants. And the greatest number of people came to Germnay from another cuntry were also from Poland in 2014 with around 197 thousand. Finally we concluded a meanigful difference between the number of Female and Male migrants from Germany both in the years 2013 and 2014.
The dataset contains the number of people arrived to or departed from Germany for living from 1947 to 2014. It also gives these data based on the gender of migrants.
To have an understanding of the pattern here you can see the total number of arrivals and departures based on gender.
It can be seen that the trend in both arrivals and departures is roughly increasing specially from mid 2000’s. Also till mid 2000’s the number of departures is roughly equal and sometimes more that the number of arrivals. But from then the number of arrivals started increasing faster and gets higher than departures.
We want to explore how many people came and left when and where the most. These can be seen the best in the plots below
Based on the plots, in the yeras 2008 and 2014 respectively 132 and 138 thousand people have left Germany to Poland which are the most number of departures to a single country. Also in each of years 2013 and 2014, 197 thousand people came to Germany from again Poland.
As no seasonal pattern could be seen in the data , I decided to use the random walk method for forecasting. The results of forecasting including 95 percent confidence intervals can be seen in the following charts.
To test the significance of difference I tested the null hypothesis that the average number of male and female immigrants are equal acroos all countries against the alternative hyphothesis that they are different. As the data does not appear to show a distribution, I use the Wilcoxon Rank test.
Looking at the charts of immigrants in years 2013 and 2014 it seems that there are more male immigrants than female.
To be precise. respectively in 2013 and 2014 there where in average 5446 and 6552 more male imigrants that female. The P-value of the test for both years are almost zero. So the null hypothesis is rejected and the number of male and female migrants are significantly different.
Statistisches Bundesamt, Wiesbaden 2016