Dag van de Lokale Rekenkamer “Weighting the consequences” Martijn Souren Consistent LFS weighting Statistics Netherlands LFS workshop, Paris 2010

Dag van de Lokale Rekenkamer  Internal consistency  Monthly  Quarterly data  Annual data  Longitudinal data  External consistency  Register data  National accounts Consistent LFS weighting Statistics Netherlands LFS workshop, Paris 2010

 Monthly estimates  Working force in three categories:  Unemployed, employed and non-working population  Crossed by sex and age:  Totals and 6 domains Monthly and quarterly data Introduction Statistics Netherlands LFS workshop, Paris 2010 Internal consistency

 Three month moving averages:  Generalized regression (GREG) estimator  One set of weights  Rigid correction for Rotation Group Bias (RGB)  Equal to quarterly estimates Monthly and quarterly data Introduction Statistics Netherlands LFS workshop, Paris 2010 Internal consistency

Dag van de Lokale Rekenkamer Monthly and quarterly data Montht-4 t-3 t-2 t-1 t Wave 1t-4 t-3 t-2 t-1 t 2t-7 t-6 t-5 t-4 t-3 3t-10 t-9 t-8 t-7 t-6 4t-13 t-12 t-11 t-10 t-9 5t-16 t-15 t-14 t-13 t-12 Statistics Netherlands LFS workshop, Paris 2010 Internal consistency

 Three month moving averages (GREG)  Rigid correction for Rotation Group Bias (RGB)  Equal to quarterly estimates  Structural time series estimates (STM)  Real Monthly estimates  Model based RGB correction  Averages should equal quarterly estimates  Internally consistent by adding table:  Average (un)employed working population crossed by sex and age Monthly and quarterly data Introduction Statistics Netherlands LFS workshop, Paris 2010 Internal consistency

Dag van de Lokale Rekenkamer Monthly and quarterly data Montht-4 t-3 t-2 t-1 t Wave 1t-4 t-3 t-2 t-1 t 2t-7 t-6 t-5 t-4 t-3 3t-10 t-9 t-8 t-7 t-6 4t-13 t-12 t-11 t-10 t-9 5t-16 t-15 t-14 t-13 t-12 Statistics Netherlands LFS workshop, Paris 2010 Internal consistency

 Structural time series estimates into GREG  Internally consistent by adding table with averages  However, by adding monthly estimates divided by three:  Multiplying the quarterly weights by three, yields exact monthly estimates from quarterly data as well Quarterly data Introduction Statistics Netherlands LFS workshop, Paris 2010 Internal consistency

 Quarterly GREG into annual estimates  Adding quarterly data  Dividing Quarterly weights by four:  Fully consistent  Responses not in all waves, different set of weights:  Partly consistent by adding table:  (Un)employed working population crossed by sex and age Annual data Introduction Statistics Netherlands LFS workshop, Paris 2010 Internal consistency

 Quarterly or anual flow statistics  Only responses in subsequent quarters of years  Different set of weights  Partly consistent by adding tables:  Beginning period  Ending period Longitudinal data Introduction Statistics Netherlands LFS workshop, Paris 2010 Internal consistency

Dag van de Lokale Rekenkamer  Internal consistency  Monthly  Quarterly data  Annual data  Longitudinal data  External consistency  Register data  National accounts Consistent LFS weighting Statistics Netherlands LFS workshop, Paris 2010

 Improving the weighting scheme  Reducing bias  Different statistics becoming more consistent:  Unemployment register  Income register  Demographic register Register data Introduction Statistics Netherlands LFS workshop, Paris 2010 External consistency

 Adjusting the estimates  Forcing consistency, or  Reducing and explaining inconsistency:  Income register National accounts Introduction Statistics Netherlands LFS workshop, Paris 2010 External consistency

Dag van de Lokale Rekenkamer  To what extent is consistency necessary?  (Un)employment crossed by sex and age?  How to deal with panel designs?  More subsets, more inconsistency?  More Rotation group bias, more inconsistency?  How to handle inconsistencies with national accounts?  Forcing or explaining? Discussion Statistics Netherlands LFS workshop, Paris 2010