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Monthly Unemployment Estimates through GREG vs STM Statistics Netherlands  Martijn Souren  Boukje Janssen  Jan van den Brakel  Sabine Krieg.

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Presentation on theme: "Monthly Unemployment Estimates through GREG vs STM Statistics Netherlands  Martijn Souren  Boukje Janssen  Jan van den Brakel  Sabine Krieg."— Presentation transcript:

1 Monthly Unemployment Estimates through GREG vs STM Statistics Netherlands  Martijn Souren  Boukje Janssen  Jan van den Brakel  Sabine Krieg

2 Monthly Unemployment Estimates through GREG vs STM Statistics Netherlands  What we do  What we cannot do  What we could do!  What we should do?

3 Monthly Unemployment Estimates through Three months GREG (What we do) Statistics Netherlands

4 Monthly Unemployment Estimates through Three months GREG (What we do) Disadvantages:  Real monthly seasonal patterns are smoothed out and thus biased  Structural changes appear delayed  Rigid RGB correction Advantages:  Large sample size Statistics Netherlands

5 Monthly Unemployment Estimates through Three months GREG (What we do) Statistics Netherlands

6 Monthly Unemployment Estimates through Monthly GREG (What we cannot do) Statistics Netherlands

7 Disadvantages:  Rigid RGB correction  Large standard errors Advantages:  Real monthly figures Monthly Unemployment Estimates through Monthly GREG (What we cannot do) Statistics Netherlands

8 Monthly Unemployment Estimates through Monthly GREG (What we cannot do) Statistics Netherlands

9 Monthly Unemployment Estimates through Monthly GREG (What we cannot do) Statistics Netherlands

10 Monthly Unemployment Estimates through Monthly GREG (What we cannot do) Statistics Netherlands

11 Monthly Unemployment Estimates through Monthly STM (What we could do!) Statistics Netherlands

12 Structural Time Series Modelling: The population parameter can be decomposed in a trend component, a seasonal component and an irregular component. Monthly Unemployment Estimates through Monthly STM (What we could do!)

13 Statistics Netherlands Monthly Unemployment Estimates through Monthly STM (What we could do!) Structural Time Series Modelling: Each component can be seperately modelled and interpreted.

14 Monthly Unemployment Estimates through Monthly STM (What we could do!) Statistics Netherlands

15 Monthly Unemployment Estimates through Monthly STM (What we could do!) Statistics Netherlands

16 Monthly Unemployment Estimates through Monthly STM (What we could do!)

17 Statistics Netherlands Monthly Unemployment Estimates through Monthly STM (What we should do?)

18 Monthly Unemployment Estimates through Monthly STM (What we should do?) Advantages:  Real monthly figures  Real monthly seasonal patterns  Better RGB correction Disadvantages:... Statistics Netherlands

19 Monthly Unemployment Estimates through Monthly STM (What we should do?) Implementation:  (Un)employed- and Total Labour Force  7 Domains: Age(3) x Sex(2) and total  Consistency with Lagrange-method  (Un)employment rates calculated afterwards Statistics Netherlands

20 Monthly Unemployment Estimates through Monthly STM (What we should do?) Thank you for your attention Statistics Netherlands

21 Box-Jenkins ARIMA modelling: Eliminating trend + seasonal effects by taking differences. Assumed is that local statistical properties of the time series is constant over time Statistics Netherlands Monthly Unemployment Estimates through Monthly STM (What we should do?)

22 Real series are never stationary, time varying regression coefficients and multivariate extensions are easily handled Aparantly different methods, but historically quite similar Statistics Netherlands Monthly Unemployment Estimates through Monthly STM (What we should do?)


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