1. Background

In the Labour Force Survey (LFS) respondents are interviewed for five consecutive quarters over a 12 month period, with 20 per cent of the sample being replaced at each quarter. This allows for a longitudinal dataset to be created over a limited time interval, where respondents’ characteristics can be tracked over their time in the survey.

The ONS publishes population-weighted longitudinal datasets for each calendar quarter. These are available for each quarter since 1997 and can be used to analyse changes in labour market characteristics over two or five quarters. The datasets include "flow" variables, which estimate the size of the movements between the three main labour market statuses of employment, unemployment and economic inactivity.

Monitoring changes in the labour market status of respondents to the LFS aids the understanding of the quarterly changes in the levels of employment, unemployment and economic inactivity. These indicators are published as stocks for a given period, with changes expressed as the difference between successive quarters. These quarterly comparisons represent the net changes between the three labour market statuses. The underlying gross flows are usually considerably larger and may not correspond with those implied by the net changes. Estimates of the gross flows between the statuses can be derived from the LFS Longitudinal Datasets and are summarised in this note.

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2. Method

There are two types of LFS longitudinal datasets: two-quarter and five-quarter. These are weighted using the same population estimates as those used in the main quarterly LFS datasets, although the weighting methodology differs (see technical note). Consequently the estimates are broadly consistent with the published aggregates, but not entirely. Also, the datasets are limited to people aged 16-64.

Both types of dataset contain a flow variable with eleven categories, with all combinations of employment, unemployment and economic inactivity accounted for, plus two categories for those entering and leaving the 16-64 population over the quarter. For the purpose of this analysis, those entering or leaving this population are excluded from the measured sample. The stock of the employed, unemployed and inactive at each quarter can therefore be estimated by summing the corresponding flow categories.

For this analysis, the two-quarter datasets have been used in order to gain some insight into the quarterly changes in the headline published aggregates.

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3. The charts in this article

Estimates of flows between labour market statuses are available at data table X02 (81.5 Kb Excel sheet).

The charts in this article show the estimated gross flows, that is the total inflow or outflow for 16 to 64 employment, unemployment and inactivity from one calendar quarter to the next. They are seasonally adjusted. Analysis of the net flows, that is the difference between the total inflow and outflow, are also included and these are compared with the quarterly changes in the published aggregates, partly to give an indication of the robustness of the flows analysis.

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4. Key messages for quarter 1 2015

  • The gross inflow to unemployment was virtually unchanged in the latest quarter, after having decreased to near its pre-recession low the previous quarter.

  • The gross inflow to employment has increased, driven primarily by the flow from outside the labour force.

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5. Quarterly gross flows

The diagram below shows the gross flow between each economic status between October - December 2014 and January to March 2015. The stocks for each status represent the latter period and are the seasonally adjusted aggregates for people aged 16-64.

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6. Unemployment

The inflow to unemployment (Figure 1) shows little change in the latest quarter after having been on a decreasing trend for most of the last three years.

The gross flow out of unemployment (Figure 2) has continued the downward trend of the last year with the outflow to inactivity at its lowest for seven years.

Figure 3 shows that the net quarterly flow has remained negative, although it is the smallest it has been for over a year. This is consistent with the quarterly change in stock.

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7. Employment

The total inflow to employment (Figure 4) increased in the latest quarter, driven by an increase in the flow from inactivity.

The trend in the gross outflow from employment (Figure 5) has remained flat at just under 900,000. The outflow to inactivity has remained significantly higher than the outflow to unemployment.

Figure 6 shows that the net flow and change in stock have both increased.

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8. Inactivity

The difference between the flows into inactivity from employment and unemployment has increased although the gross flow remains flat (Figure 7).

The gross outflow from inactivity (Figure 8) has increased for the first time in 4 quarters, driven by the flow to employment, which is at its highest since 2004.

Figure 9 indicates that the net flow for inactivity and the quarterly change in stock have moved below zero in the latest quarter

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9. Technical note

There are differences between the data used for the published LFS aggregate estimates and the longitudinal data used to estimate the gross flows:

  1. Flows are currently adjusted for non-response bias through special calibration weights in the longitudinal datasets. These aim to account for the propensity of certain types of people to drop out of the LFS between one quarter and the next. For example, housing tenure features in the weighting of the longitudinal data because, historically, households in rented accommodation have been more likely to drop out of the survey than owner-occupiers.

  2. There is some evidence that the longitudinal datasets are affected slightly by response error which causes a slight upward bias in the estimates of the gross flows. For example, if it was erroneously reported that someone had moved from unemployment to employment then, in addition to the outflow from unemployment being overestimated, so would the inflow to employment. In the main quarterly LFS dataset, any such misreporting errors tend to cancel each other out.

  3. The differences in the net flows for inactivity shown in Chart 9 are mainly the result of excluding the entrants to, and leavers from, the population in the flows estimates contained in this piece of analysis. This effect is normally one that increases the number of people who enter inactivity. This is because the increase in inactivity from those people turning 16 is greater than those leaving inactivity due to becoming 65.

  4. The stocks derived from the longitudinal datasets differ from those obtained from the quarterly LFS datasets due to their being based on a subset of the main LFS sample. The restriction to measuring only those who are commonly aged 16-64 across successive quarters discounts those entering or leaving the population and also those over 64. All such people are accounted for in the headline LFS aggregates.

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Jenkins J and Chandler M (2010) ‘Labour market gross flows data from the Labour Force Survey’ (145.4 Kb Pdf) Economic & Labour Market Review, February 2010.

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.Background notes

  1. Details of the policy governing the release of new data are available by visiting www.statisticsauthority.gov.uk/assessment/code-of-practice/index.html or from the Media Relations Office email: media.relations@ons.gov.uk
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Contact details for this Article

Richard Clegg
Telephone: +44 (0)1633 455400