Forecasting Immigration in Official Population Projections Using an Econometric Model

Abstract

Although substantial research has been conducted to quantify the determinants of international migration, most official population projections do not include such determinants in a formal migration model. Statistics Norway forecasts gross immigration to Norway using an econometric model based on standard migration theories. The main variables include income level, unemployment, and population size in Norway and the sending countries, and the number of immigrants already living in Norway. Projections of exogenous variables are drawn from international and Norwegian sources. Three different alternatives are specified for the income variables, leading to three different forecasts for gross immigration until 2100.

Assessing time series models for forecasting international migration: Lessons from the United Kingdom

“…This illustrates the importance of treating migration as a non-stationary process where systemic 'shocks' are expected. An alternative approach for modelling such shocks relies on including dummy variables for such past events (Cappellen et al, 2015;de Beer, 1993), but even then the key issue with unpredictability of such shocks remainsand the approach can be argued to suppress the predictive uncertainty as a result.…”

“…There are many social, economic, political and environmental drivers which impact migration flows (Massey et al, 1993), yet there is no single, robust migration theory that can be used for forecasting purposes (Arango, 2000). Besides, even if credible explanations of past migration flows existed, their tenets would be difficult to extrapolate into the futurefor that reason, most of the formal forecasting models rely on time series analysis, be it frequentist or Bayesian (Azose & Raftery, 2015;Bijak, 2010;Bijak & Wiśniowski, 2010;Cappellen, Skjerpen, & Tønnessen, 2015;de Beer, 1993de Beer, , 2008Wiśniowski, Smith, Bijak, Raymer, & Forster, 2015). Besides, even if credible explanations of past migration flows existed, their tenets would be difficult to extrapolate into the futurefor that reason, most of the formal forecasting models rely on time series analysis, be it frequentist or Bayesian (Azose & Raftery, 2015;Bijak, 2010;Bijak & Wiśniowski, 2010;Cappellen, Skjerpen, & Tønnessen, 2015;de Beer, 1993de Beer, , 2008Wiśniowski, Smith, Bijak, Raymer, & Forster, 2015).…”

“…Migration is also susceptible to events that are difficult to predict in terms of timing and impact, such as changes in the economic cycle, policies or political circumstances. Besides, even if credible explanations of past migration flows existed, their tenets would be difficult to extrapolate into the futurefor that reason, most of the formal forecasting models rely on time series analysis, be it frequentist or Bayesian (Azose & Raftery, 2015;Bijak, 2010;Bijak & Wiśniowski, 2010;Cappellen, Skjerpen, & Tønnessen, 2015;de Beer, 1993de Beer, , 2008Wiśniowski, Smith, Bijak, Raymer, & Forster, 2015).…”

Differences in all-cause mortality

“…It is expected to continue to increase quite substantially over the coming years (Cappelen, Skjerpen, and Tønnessen 2015). Norway's immigration policy was fairly liberal post-World War II.…”

A Bayesian Semiparametric Approach for Trend–Seasonal Interaction: an Application to Migration Forecasts

“…However, a common belief around its non-repeatability and nontraceability left most migration projections dependent on deterministic methods until the mid-1990s. Nevertheless, as it is unquestionable that forecasting is not only about modelling, but also about quantifying uncertainty, these naive approaches have been progressively abandoned and substituted by standard probabilistic techniques like time series analysis (Lee and Tuljapurkar, 1994;De Beer, 1997;Keilman et al, 2002;Wilson and Bell, 2004;Raymer et al, 2012) and generalized linear regressions (Schmidt and Fertig, 2000;Alvarez-Plata et al, 2003;Cohen et al, 2008;Cappelen et al, 2015).…”