Insightsfrom the data - Europa€¦ · Managers Professionals Technicians and associate...

transcript

Insights from the data

Emilio Colombo, Catholic University of Milano and CRISP

AO/DSL/VKVET-GRUSSO/Real–time LMI 2/009/16 1

Compare OJV…with what?• How OJV stand within the realm of labour

market data?• Can they be compared with other official

statistics?• What is the benchmark?• What are the limits and the constraints of our

The problem of the population of ref.• JV surveys are often targeted to a narrow

population• Firms >10 employees• Little detail on sectors• Often no detail on occupations

Thus there is no clear benchmark to compare our data with, especially if we are interested in details

Can we use LFS?• Can we compare OJV with LFS?• No!!! The former are stocks the latter flows• …but• Think of where the demand comes from

• Expansion demand • Replacement demand (this derives directly

from the stock)We looked at the distribution of OJV and of LFS in early release countries in IV qtr 2018

OJV vs LFS

0% 5% 10% 15% 20% 25% 30% 35%

Czechia

Germany

Ireland

United Kingdom

France

Share of total (7 countries)

% employment % web

OJV vs LFS: occupations

0% 5% 10% 15% 20% 25%

Managers

Professionals

Technicians and associate professionals

Clerical support workers

Service and sales workers

Skilled agricultural, forestry and fishery…

Craft and related trades workers

Plant and machine operators and assemblers

Elementary occupations

FR FR - web

0% 5% 10% 15% 20% 25% 30%

Managers

Professionals

DE DE - web

0% 5% 10% 15% 20%

Managers

Professionals

IT IT - web

OJV vs LFS: skill level

HIGH LEVEL MEDIUM LEVEL LOW LEVEL

FR - web

40% 39%

IT - web

DE - web

ES - web

44%41%

IE - web

UK - web

CZ CZ -web

OJV vs LFS: sector

CZ DE IE ES IT UK FR

Information and communication

Web LFS

Professional and technical services

Web LFS

OJV vs LFS: sector

Administrative and support service

Web LFS

Retail trade

Web LFS

Web vs official JVSCan we compare web vacancies with official vacancy statistics?Difficult

• Different sampling method• Different time frame• Different population

Time series analysis. ItalyWe have implemented a time series analysis on Italian data comparing web with official statistics• Quarterly time series for different sectors• Disentangle trend from cycle• Perform a cointegration analysis

Time series analysis. Italy

Time series analysis. Trend

Time series analysis. Cycle

Cointegration analysis. SectorsNace (Sector) Series I(d)

Cointe-gration

Coeff.Long run

R2 Unit root t-test

B,C,D,E - Industry NSO I(1) Y 0.561(0.010)*** 0.993 -4.195WEB I(1)

G - Wholesale and retail trade; repair of motor vehicles/motor

NSO I(1) Y 0.573(0.025)*** 0.963 -4.922

WEB I(1)H - Transportation and storage NSO I(1) Y 0.709(0.038)*** 0.945 -5.321

WEB I(1)I - Accommodation and food service activities

NSO I(0) N

WEB I(1)J - Information and communication NSO I(1) Y 0.482(0.024)*** 0.952 -3.246

WEB I(1)K - Financial and insurance activities

NSO I(0) N

WEB I(1)M - Professional, scientific and technical activities

NSO I(1) Y 0.408(0.021)***0.949

-3.863

WEB I(1)All Sectors NSO I(1) Y 0.616(0.026)*** 0.963 -3.447

WEB I(1)

Representativeness• OJV are not representative of the whole population• Some sectors/occupations are over-represented, others

are under-represented• Can we correct OJV in order to be representative?• What is the benckmark to use?• What variables should be included?

Web vs official statistics• On Official data of Italian LFS we created

population profiles cells determined by combinations of occupation (130), sector of activity (12) and region (20), partitioning the data-set into 31,200 cells.

• Jwv data (truncated sample) has been classified in a similar way with combinations of the same variables.

Logit for missingness

First run a logistic model to identify the factors that affect the missingness

P(zjt=1) =logit-1(b0 +b1j NUTS2j + b2jISCOj + b3jNACEj +b4jQuarterjt +Interactions)

Multilevel for correction

Then we run a multilevel poisson model

Yjt /µjt ~ Poisson(µjt)

with the standard log link function as a function of level-1 (time) predictor:

log(µjt) = g0j + g1j Quarter jt

with a random effect only for the intercept that depends also on fixed level-2 predictors:

g0j = (g00 + u0j) + g01 NUTS2j + g02 ISCOj + g03 NACEj

Correcting for lack of representativeness

AO/DSL/VKVET-GRUSSO/Real–time LMI 2/009/16 250 5 10 15 20 25 30 35

Agriculture, Forestry and Fishing

Industry; Manufacturing;

Construction

Wholesale Retail Trade; Repair of Motor Vehicles/Motorcycles

Accommodation and Food Service activities (act.)

Transportation and Storage

Information and Communication

Financial and Insurance Act.

Real Estate Activities; Professional, Scientific and Technical

Administrative and Support Service Act.; Public Administration and Defense;Compulsory Social Security

Education; Human Health and Social Work Act. + Arts, Entertainment and Recreation

Other Service activities (Act); Act. Households as Employers; Undifferentiated goodsand Services Producing Act.of Households for own use; Act. of Extraterritorial…

% JV Observed

% Model predicted

% JWRate

Insightsfrom the data - Europa€¦ · Managers Professionals Technicians and associate...

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