Fig. 1.

Fig. 2.

Fig. 3.

Fig. 4.

Ethnic composition and its changes in Latvia, 2000–2019 (Central Statistical Bureau of Latvia)_
| Ethnic group | Total population 2019 | Population change 2000–2019 | Mean age | ||||
|---|---|---|---|---|---|---|---|
| number | % of total | % of ethnic minorities | number | % | 2000 | 2019 | |
| Latvians | 1,196,251 | 62.3 | – | −174,305 | −12.7 | 36.8 | 40.4 |
| Russians | 478,578 | 24.9 | 66.2 | −224,539 | −31.9 | 39.5 | 47.4 |
| Belarusians | 61,418 | 3.2 | 8.5 | −35,719 | −36.8 | 44.7 | 55.4 |
| Ukrainians | 43,062 | 2.2 | 6.0 | −20,572 | −32.3 | 41.9 | 52.5 |
| Poles | 38,818 | 2.0 | 5.4 | −20,680 | −34.8 | 42.0 | 50.9 |
| Lithuanians | 22,340 | 1.2 | 3.1 | −11,085 | −33.1 | 42.3 | 51.0 |
| Other | 79,040 | 4.1 | 10.9 | +29,345 | +59.0 | 36.2 | 24.0 |
| Total | 1,919,507 | −457,555 | −19.2 | 38.2 | 42.5 | ||
Binary logistic regression model variables_
| Type | Variable | Group | Regression model no. |
|---|---|---|---|
| Filter variables | Ethnicity | Latvians | all |
| Ethnic minorities | |||
| Dependent variable | Migration status | In-migrants | all |
| Non-migrants | |||
| Covariates (predictor variables) | Age group | 15–19 | all |
| 20–24 | |||
| 25–29 | |||
| 30–34 | |||
| 35–39 | |||
| 40+ | |||
| Urban system | Capital city of Riga | 1; 2; 3; 4 | |
| Suburbs of Riga | |||
| Other largest cities | |||
| Regional & small towns | |||
| Rural areas | |||
| Region | Riga & suburbs | 5; 6; 7; 8 | |
| Zemgale | |||
| Vidzeme Kurzeme | |||
| Latgale |
Logistic regression of the likelihood of internal migration, predicted by age group and region of destination (ref_ non-migrants Latvians)_
| β – internal migrants among Latvians (ref. non-migrants) | |||||
|---|---|---|---|---|---|
| Model 5 (2011) | Model 6 (2019) | ||||
| β coefficient | P | β coefficient | P | ||
| Age | 15–19 | −0.167 | 0.000 | 0.220 | 0.000 |
| 20–24 | 0.895 | 0.000 | 0.762 | 0.000 | |
| 25–29 | 1.000 | (ref.) | 1.000 | (ref.) | |
| 30–34 | 0.544 | 0.000 | 0.853 | 0.000 | |
| 35–39 | 0.096 | 0.000 | 0.556 | 0.000 | |
| 40+ | −0.638 | 0.000 | −0.243 | 0.000 | |
| Regions | Riga & suburbs | 1.000 | (ref.) | 1.000 | (ref.) |
| Zemgale | 0.739 | 0.000 | 0.869 | 0.000 | |
| Kurzeme | 0.807 | 0.000 | 0.930 | 0.000 | |
| Vidzeme | 0.782 | 0.000 | 0.777 | 0.000 | |
| Latgale | 0.515 | 0.000 | 0.624 | 0.000 | |
| −2 Log likelihood | 280,393.782 | 277,992.085 | |||
| Nagelkerke R2 | 0.062 | 0.037 | |||
Logistic regression of the likelihood of internal migration, predicted by age group and destination within the urban system (ref_ non-migrants ethnic minorities)_
| β – internal migrants among ethnic minorities (ref. non-migrants) | |||||
|---|---|---|---|---|---|
| Model 3 (2011) | Model 4 (2019) | ||||
| β coefficient | P | β coefficient | P | ||
| Age | 15–19 | −0.183 | 0.000 | 0.180 | 0.000 |
| 20–24 | 0.904 | 0.001 | 0.816 | 0.000 | |
| 25–29 | 1.000 | (ref.) | 1.000 | (ref.) | |
| 30–34 | 0.636 | 0.000 | 0.913 | 0.020 | |
| 35–39 | 0.194 | 0.000 | 0.680 | 0.000 | |
| 40+ | −0.693 | 0.000 | −0.123 | 0.000 | |
| Urban system | Capital city of Riga | 1.000 | (ref.) | 1.000 | (ref.) |
| Suburbs of Riga | 1.090 | 0.000 | 1.428 | 0.000 | |
| Large cities | 0.953 | 0.286 | 1.414 | 0.000 | |
| Regional & small towns | 0.956 | 0.512 | 1.851 | 0.000 | |
| Rural areas | 0.928 | 0.011 | 1.828 | 0.000 | |
| −2 Log likelihood | 129,068.467 | 114,064.836 | |||
| Nagelkerke R2 | 0.059 | 0.052 | |||
In-migrants and non-migrants by ethnicity (age group 0–14 excluded)_
| 2010–2011 | 2018–2019 | |||||||
|---|---|---|---|---|---|---|---|---|
| In-migrants | Non-migrants | In-migrants | Non-migrants | |||||
| Count (k) | % | Count (k) | % | Count (k) | % | Count (k) | % | |
| Latvians | 33.6 | 3.3 | 999.9 | 96.7 | 32.8 | 3.4 | 943.7 | 96.6 |
| Ethnic minorities | 14.0 | 2.0 | 668.4 | 98.0 | 12.2 | 2.0 | 600.7 | 98.0 |
| Total | 47.6 | 2.8 | 1668.3 | 97.2 | 45.0 | 2.8 | 1544.4 | 97.2 |
Logistic regression of the likelihood of internal migration, predicted by age group and region of destination (ref_ non-migrants ethnic minorities)_
| β – internal migrants among minorities (ref. non-migrants) | |||||
|---|---|---|---|---|---|
| Model 7 (2011) | Model 8 (2019) | ||||
| β coefficient | P | β coefficient | P | ||
| Age | 15–19 | −0.174 | 0.000 | 0.227 | 0.000 |
| 20–24 | 0.906 | 0.001 | 0.851 | 0.001 | |
| 25–29 | 1.000 | (ref.) | 1.000 | (ref.) | |
| 30–34 | 0.639 | 0.000 | 0.908 | 0.013 | |
| 35–39 | 0.201 | 0.000 | 0.704 | 0.000 | |
| 40+ | −0.698 | 0.000 | −0.088 | 0.000 | |
| Regions | Riga & suburbs | 1.000 | (ref.) | 1.000 | (ref.) |
| Zemgale | 0.975 | 0.402 | 1.222 | 0.000 | |
| Kurzeme | 1.275 | 0.000 | 1.254 | 0.000 | |
| Vidzeme | 0.858 | 0.000 | 0.695 | 0.000 | |
| Latgale | 0.861 | 0.000 | 0.852 | 0.000 | |
| −2 Log likelihood | 129,127.080 | 117,087.907 | |||
| Nagelkerke R2 | 0.058 | 0.025 | |||
Logistic regression of the likelihood of internal migration, predicted by age group and destination within the urban system (ref_ non-migrants Latvians)_
| β – internal migrants among Latvians (ref. non-migrants) | |||||
|---|---|---|---|---|---|
| Model 1 (2011) | Model 2 (2019) | ||||
| β coefficient | P | β coefficient | P | ||
| Age | 15–19 | −0.139 | 0.000 | 0.194 | 0.000 |
| 20–24 | 0.914 | 0.000 | 0.754 | 0.000 | |
| 25–29 | 1.000 | (ref.) | 1.000 | (ref.) | |
| 30–34 | 0.543 | 0.000 | 0.845 | 0.000 | |
| 35–39 | 0.102 | 0.000 | 0.531 | 0.000 | |
| 40+ | −0.620 | 0.000 | −0.254 | 0.000 | |
| Urban system | Capital city of Riga | 1.000 | (ref.) | 1.000 | (ref.) |
| Suburbs of Riga | 0.872 | 0.000 | 1.178 | 0.000 | |
| Large cities | 0.807 | 0.000 | 0.940 | 0.007 | |
| Regional & small towns | 0.758 | 0.000 | 1.064 | 0.025 | |
| Rural areas | 0.471 | 0.000 | 0.976 | 0.127 | |
| −2 Log likelihood | 279,745.547 | 276,813.279 | |||
| Nagelkerke R2 | 0.065 | 0.041 | |||