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Labour market performance of surviving relatives in the Netherlands: applying sequence analysis on SSD data Katja Chkalova (CBS) 16 May 2013.

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Presentation on theme: "Labour market performance of surviving relatives in the Netherlands: applying sequence analysis on SSD data Katja Chkalova (CBS) 16 May 2013."— Presentation transcript:

1 Labour market performance of surviving relatives in the Netherlands: applying sequence analysis on SSD data Katja Chkalova (CBS) 16 May 2013

2 Summary 1. Introduction 2. Data & analysis methods 3. Results

3 Introduction  Changes in social security policy  National Survivors Benefits Act (Anw) and recent research  Research questions  What routes and trajectories do survivors of bereavement adopt on the labour market after the event (typology)?  What routes and trajectories lead to withdrawal from the labour market and Anw - dependence  Discriminating effects

4 Sequence analysis in a nutshell Sequence properties and general statistics  Most analysis methods focus on only one state or transition/event  The average labour market career often contains multitudes of states and transitions (E/UB/U)  Sequence analysis offers the possibility to examine labour market careers as a whole of states, transitions and events # distinct states, events and transitions Length / duration of distinct states (mean / total duration / duration of separate spells) Most common patterns / searching for particular patterns Entropy, turbulence, complexity Timing of events

5 Edit-distances Hamming distance (substitution costs) Optimal Matching (indel costs) Quantified Common Attribute Longest Common Prefix Longest Common Suffix Longest Common Sub-sequence # of Distinct Sub-sequences # Matching Sub-sequences Sequence analysis in a nutshell Pairs of sequences: distances, similarities and dissimilarities

6 Results Operationalising and alphabet -Research population: persons who have lost their partner in Sequences of the same length of 61 months: 12 months before the event (death of the partner), the month of the event and 48 months after the event

7 -Emphasising Anw- benefits as a separate state -Three integrated tracks of sequences -Job -Benefits (AO/WW/WWB) -Anw benefits -65 years and older as a separate category for labour market state Results Operationalising and alphabet

8 Starting position: working inactive receiving benefits working with benefits Other Results Operationalising and alphabet

9 -Construct sequence strings -Distinguish between the starting positions -Determine general statistics of sequence strings -Calculate distances between sequence strings separately for every starting position -Find clusters of distances within every group with a distinct starting position -Do a regression analysis with typology as dependent variable Results Steps in the analysis

10 Visualisation of the sequence data: The state distribution plot of the labour market states of the survivors during 61 months Results General statistics

11 Working InactiveBenefits Working with benefits Results General statistics

12 # transitions per period Results General statistics

13 Starting position: working Longest common subsequence X 1.000% cluster Working without any interruptions11.247% Work > work and Anw4.117% Work > inactive later in the research period4.318% Work > inactive within 2 years after the event1.56% Work > Anw1.15% Work > % Work > other benefits0.83% Remaining0.31% Results Typology

14 Work > Anw Work > work with Anw Results Typology Starting position: working

15 There is an evident impact of the event on the labour market performance of the surviving relatives Gender differences in types of trajectories adopted Significant differences in behaviour between survivors in different life course phases The starting position is of great importance for outcomes (typology) Anw is being used by different groups of survivors: - Long-term Anw assistance with little chance of reconnecting with the labour market - Complementary Anw-assistance Results Important conclusions

16 Labour market performance of surviving relatives in the Netherlands: applying sequence analysis on SSD data Questions? Katja Chkalova (CBS) 16 May 2013


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