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Longitudinal Analysis and the Scottish Economy

David Bell

Scotecon

University of Stirling

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Key Issues in Scottish Economic Performance

• Economic Growth– Entrepreneurship– Population Decline– Skills– Economic Inactivity

• Widening role for economic analysis in policies under control of Scottish Parliament

• Can longitudinal data enhance the evidence base for policy?

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Longitudinal Data and the Scottish Economy

• At present role is limited because ….– Relatively few longitudinal data sources– Scottish sample often small– Not much expertise in the use of such data

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Key Longitudinal Datasets

• Individual/Household Based– BHPS– Cohort Studies– NES– Census

• But what about firms?– Futureskills Scotland Skills Surveys– IDBR

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Don’t put all your eggs in the longitudinal basket!

• Reliance on longitudinal data should be limited• Has some advantages

– Controls for unobserved heterogeneity – Permits event modelling

• But also disadvantages– More susceptible to measurement error

– It does not answer the “evaluation problem”– Small samples may limit modelling approach and

hence usefulness– The past not necessarily a good guide to the future

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Use a Variety of Data Sources and Methods(in the Scottish context)

• Reconciling different results from different datasets is a useful means of understanding the datasets

• Replication in other datasets suggests results are more robust

• As does confirmation by other methods

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Two Examples

• Public Sector Wages

• Relative Returns to Education in Scotland and Rest of Great Britain

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Public Sector Wages - The Context

• Public sector pay accounts for the majority of spending under the Barnett formula

• Pay plays an important role in attracting, retaining and motivating public sector staff

• Public sector rewards influence private sector labour markets

• Growing pressure for reform

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The Public Sector Premium

• Why do public sector employees earn more?– Compensating differentials– Efficiency wages– Bargaining structures

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The Public Sector Premiumin Great Britain

WageSectorPrivateMean

WageSectorPublicMean

Source: Labour Force Survey

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“Explained” and “Unexplained” Components of the Public-Sector Premium

• Differences in mean pay may simply reflect differences in skill levels, education, experience etc.

• Use regression to “net out” these effects – these are the “explained” components of the public sector premium

• What remains is the “unexplained” component

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Explained and Unexplained Components of Public Sector Premium

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

Males England

Males Scotland

FemalesEngland

FemalesScotland

Diff

ere

nce

in (

Ln

) W

ag

es

Unexplained

Explained

Source: Labour Force Survey

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Spatial Sensitivity by Public Sector Bargaining GroupRelative to Private Sector Comparator

0 0.1 0.2 0.3 0.4 0.5 0.6

Civil Service (Inland Revenue)

Local Authority Single status

Teachers

Nurses

Royal Mail manual

NHS Professionals Whitely B

NHS Ambulance

Police

NHS Admin & clerical

University manual*

Prison Officers*

NHS Ancillaries

Fire Service

NHS Doctors & Dentists

Source: New Earnings Survey

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Does the Premium Vary by Location in the Wage Distribution?

-10% -5% 0% 5% 10% 15% 20%

malesEngland

malesScotland

femalesEngland

femalesScotland

malesEngland

malesScotland

femalesEngland

femalesScotland

25

th p

erc

en

tile

75

th p

erc

en

tile

Source: Labour Force Survey

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But What About Individual Experiences in Moving Between Sectors?

• Model based on Holtz-Eakin & Rosen analysis of the impact of self employment on earnings

),,(21 ttttttt PublicPXfPublicPPP

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Moving between sectors(compared with staying in the private sector)

UK

-2

0

2

4

6

8

10

12

public/public public/private private/public

10th percentile

25th percentile

50th percentile

75th percentile

90th percentile

Source: New Earnings Survey

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Moving between sectors(compared with staying in the private sector)

Greater London

-5

0

5

10

15

20

public/public public/private private/public

10th percentile

25th percentile

50th percentile

75th percentile

90th percentile

Source: New Earnings Survey

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Moving between sectors(compared with staying in the private sector)

Scotland

-2

0

2

4

6

8

10

12

public/public public/private private/public

10th percentile

25th percentile

50th percentile

75th percentile

90th percentile

Source: New Earnings Survey

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Returns to Qualifications

• Are the returns to Scottish qualifications different from returns to English qualifications?

• Does the Scottish educations system as a whole perform better than the English system?

• Sources: Labour Force Survey, NCDS

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Coefficient t statisticOther Higher Education -0.19 -40.6A Level -0.37 -87.6GCSE, O Levels -0.46 -103.4Other Quals -0.57 -87.5

(omitted category is degree qualification)Quals in Scotland 0.14 8.1

Higher Education in Scotland -0.08 -5.7Highers in Scotland -0.08 -6.3O Levels in Scotland -0.11 -7.8Other Quals in Scotland -0.08 -3.4

Works in London 0.29 80.0Works in Scotland -0.01 -1.4

(omitted category is works in Rest of England)

Quals in Scotland, Works in London -0.05 -1.4Quals in Scotland, Works in Scotland -0.14 -7.7

(omitted category is works in Rest of England)

n = 162204F = 1784.32R2 = 0.3813

Other controls, gender tenure tenure2, age left education,Industry, marital status, number of children, size of workforce, year dummies

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Returns to Qualification by Region of Work(Relative to Lowest Quals working in Rest of England)

-20%

0%

20%

40%

60%

80%

100%

120%

Rest ofEngland

London Scotland Rest ofEngland

London Scotland

Quals in England Quals in Scotland

Per

cent

Degree

Other Higher Education

A Level

GCSE, O Levels

Other Quals

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Using NCDS to Estimate Returns to Education

• Not a large enough sample to construct separate Scottish estimates

• Not many movements between Scotland and England to separate out labour market from qualification effects

• But much better controls for ability and family background etc.

• Dummy for whether educated in Scotland or not is insignificant

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Returns to Qualification by NVQ Level(relative to the unqualified)

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

1 2 3 4 5

Source: NCDS

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Conclusions

• Longitudinal analysis can aid our understanding of key processes in the Scottish economy

• Absence of longitudinal data on firms is an important omission

• Relevant sample sizes tend to be small

• Can play a useful supporting role.