If so it may well be that the government has already achieved this without noticing it or indeed doing anything much to immigration policy - other than have a Brexit vote.
To see why this may be so, it is important to note that there are at least 2 different data sources, both based on surveys, with which to estimate changes in the numbers of immigrants coming to and leaving the UK. Neither source is perfect, but the government (and the ONS) refer to the net changes as estimated by the International Passenger Survey (IPS). This estimates the number of non-British nationals arriving minus the number of non-British nationals leaving in any year to get an estimate of net-immigration.
There is however an alternative source, the Labour Force Survey, (LFS), which can estimate the numbers of immigrants living in the UK at any time. The LFS is used by the ONS to estimate the numbers of employed and unemployed in the UK and as such is deemed to be a reliable and timely source for population numbers. The difference between the LFS immigrant estimates at two points in time is also an estimate of the net change in immigration. Figure 1 tracks the LFS estimates of the total immigrant population (based on self-reported country of birth) from 2010 to the present.
|Figure 1: LFS Estimates of UK Immigrant Population|
On the LFS measure therefore the government has met its target of getting net immigration into the tens of thousands for more than a year now (a falling population means net immigration is in the minuses)
To see how this conflicts with the estimates regularly published and commented on by government and the media, use the fact that any change in a population (be it people with freckles, goldfish etc) equals the number of arrivals minus the number of leavers. In the case of the immigrant population this means
Inflows into UK – Outflows from UK + Births - Deaths = Net Change in Immigration
The left hand panel of Figure 2 tracks the LFS estimate of net immigration - as measured by the 12-month change in the immigrant population numbers at a point in time - along with a (generous) allowance for sampling error. This again makes it clear that net immigration - according to the LFS - has been falling for over a year. More people are leaving than arriving (or dying than being born). The government's target has been reached - and more.
In contrast the IPS measure of immigration in the right hand panel shows net immigration happily growing at around 300,000 a year - and so way above the 100,000 target, with little change since the Brexit vote.
So how can we reconcile these two patterns? The IPS just measures inflows and outflows not births and deaths, so it is just possible that the LFS numbers are in negative territory because more immigrants are dying than being born - though this seems highly unlikely given the age profile of immigrants (immigrants are typically younger than the rest of the population and so less likely to be at risk of death). The IPS counts immigrants as "Non-British nationals" who are expecting to stay in the UK for more than 12 months, while the LFS estimates above estimate immigrants based on country of birth. So it is conceivable that the two different measures will produce different trends (though they didn't in the run-up to the Brexit vote - see forthcoming Blog post). So do we just surrender to the fact that surveys measure different things and give up? Or should we worry more about the different signals coming from the different surveys and the consequent uncertainty for policy making.
This is important because immigration is likely to remain an issue at centre of public/political/academic debate for the foreseeable future. As such would seem important to try to get good estimates of the level as well as the change in the immigrant population in order to inform policy. The two principal UK data sets that measure aspects of immigration currently seem to be saying different things.
We probably need more regular open discussion/dialogue between users and providers of the data about what can be done. And some recognition from policy makers that there is a discrepancy in the signals from data sources that may be worth thinking about.