Transcript Local job multipliers in Turkey  Altan Aldan William Maloney Josefina Posadas Temel Taskin (Central Bank of Turkey) (World Bank) (World Bank) (World Bank) The views expressed here belong to.

Local job multipliers in Turkey

Altan Aldan
William Maloney
Josefina Posadas
Temel Taskin
(Central Bank of Turkey)
(World Bank)
(World Bank)
(World Bank)
The views expressed here belong to the authors and should not be interpreted as the official views of the World Bank or Central Bank of Turkey.
Posadas, World Bank, 1818 H Street NW, Washington DC, USA;
[1] Corresponding author: Josefina
Tel: +1 202 458 7279; [email protected]
Motivation
• Job multiplier: Every time a local economy generates a new job by
attracting a new business/growing firms in the tradable sector, a
significant number of additional jobs are created in the non-tradable
(service) sector.
• Job multiplier is larger for high productivity jobs: high levels of human
capital, high-tech industries.
• New non-tradable jobs created in local labor markets with
agglomerations tend to have higher wages than similar non-tradable
jobs in local labor markets without agglomeration economies.
• Thus, new high-skilled jobs benefit the whole population of the local
labor market (through multiplier effect) and not only those in highskilled jobs.
• Governments devote significant effort and resources to attract new
businesses and job creation.
• Estimating multiplier effects is important to use resources efficiently
and to understand effects of these policies.
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Turkish context (1)
Important regional variation in the growth of tradable and non-tradable
employment
tradable
1990-2000
non-tradable
1990-2000
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Turkish context (2)
Important regional variation over time in the ratio of change in nontradable to tradable employment
Ratio NT/T 1990-2000
Ratio NT/T 2000-2011
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This paper
• Measures job multiplier effect in Turkey and compares it to USA and
Sweden
• Based on Moretti and Thulin (2013) methodology
• Results are divided in 2 parts due to data limitations
• 1985-2000
• 1985-2011
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Methodology (1)
• Estimation problem:
• Job creation in the tradable and non-tradable sector responds to
common unobserved factors  cofounding effects.
• Might be reverse causality from non-tradable sector to tradable
sector under full-employment and no labor mobility across labor
markets
• Solution:
Instrument: predicted employment growth at the level of the district and
industry based on
• Industry distribution in the local labor market at the beginning of
the period,
• National industry growth that isolates the district-specific effect.
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Methodology (2)
Econometric model:
∆𝐸𝑐,𝑡 𝑁𝑇 = 𝛼 + 𝛽∆𝐸𝑐,𝑡 𝑇 + 𝛾𝑑𝑡 + 𝜀𝑐,𝑡
where
•
•
•
∆𝐸𝑐,𝑡 𝑁𝑇 is change in employment in the non-tradable sector in city c and
time t and t-s
∆𝐸𝑐,𝑡 𝑇 is change in employment in the tradable sector in city c and time t
and t-s
𝑑𝑡 is a dummy variable for the second period
Instrument:
∆𝐸𝑐,𝑡 𝑇 =
𝑇
𝑇
𝑗 𝐸𝑐,𝑗,𝑡−𝑠 ∆ln(𝐸𝑗,𝑡
− 𝐸𝑐,𝑗,𝑡 𝑇 )
where
•
•
𝑇
𝐸𝑐,𝑗,𝑡−𝑠
is the number of jobs in industry j in city c at time t-s
∆ln(𝐸𝑗,𝑡 𝑇 − 𝐸𝑐,𝑗,𝑡 𝑇 ) is the change in national (excluding city c) employment
in industry j between year t and t-s.
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Data (1)
• Ideal data:
• Long time series to capture the structure of the economy (as
opposed to the cyclical variation)  20 years,
• Good regional disaggregation to define local markets precisely 
NUTS3 or lower,
• Good sector/industry disaggregation  NACE3,
• Employment by education  level of education,
• Type of employment  wage vs. self-employment,
• Wages (by the categories of above),
• Public expenditure in industry promotion.
• Population census:
• At least 3 periods and a long time coverage (1985;1990;2000; 2011),
• Good regional disaggregation (district),
• Poor sector disaggregation (only 8 tradable sectors),
• Good education and employment type.
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Variable definitions
Based on Census data:
• Jobs: any person that reports being employed
• Counts formal and informal; full-time and part-time; wage work
and self-employment,
• Skilled job: if the worker has secondary or higher level of education,
• Industry classification:
• Excludes agriculture, mining, military and government,
• Includes 8 tradable sectors,
• Includes 16 non-tradable sectors.
• Geographic unit:
• District including metropolitan areas,
• Small districts (less than 5000 workers) are merged with the
closest large district.
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Results (1)
Population Census Data: 1985, 1990, 2000
Effect of tradable on non-tradable
(T-NT)
Effect of tradable on tradable
(T-T)
0.27
3.01
1.97
OLS
IV (Excluding
Istanbul)
2.07
0.18
IV(Including
Istanbul)
OLS
Each tradable job generates 3
non-tradable jobs in Turkey.
0.19
IV (Excluding
Istanbul)
IV(Including
Istanbul)
Each tradable job generates 0.27
tradable jobs in Turkey.
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Results (2)
Population Census Data: 1985, 1990, 2000
Effect of tradable on non-tradable
Effect of tradable on tradable
0.36
3.90
0.32
3.25
0.19
0.87
0.75
1.08
0.06
-0.18
Total Non-tradable Skilled Non-tradable
Jobs
Jobs
Skilled Tradable Jobs
0.18
-0.03
Unskilled Nontradable Jobs
Unskilled Tradable Jobs
Each skilled tradable job generates 3.90
non-tradable jobs.
Total Tradable Jobs Skilled Tradable Jobs
Skilled Tradable Jobs
Unskilled Tradable
Jobs
Unskilled Tradable Jobs
Each skilled tradable job generates 0.32
tradable jobs,
Of which, 3.25 are skilled non-tradable jobs, And each unskilled tradable job generates
0.18 tradable jobs.
and 0.75 are non-skilled tradable jobs.
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Results (3)
Population Census Data: 1985, 1990, 2000, 2011
3.1
Drop due to
aggregation
Constant over time*
2.81
2.74
district
province
1985-2000
province
1990-2011
*No statistically significant variation of the job multiplier over time
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Comparison
Multipliers
USA
Sweden
Turkey
Average, tradable on non-tradable
1.6
0.5
3.01
High Skill, tradable on non-tradable
2.5
2.8
3.90
High Tech, tradable on non-tradable
4.9
1.1
-
Average, tradable on tradable
0.26
0.33
0.18
Potential factors limiting the multiplier effects of Sweden:
•
•
•
Lower labor mobility,
Lower wage differentials between high- and low-skilled workers,
Generous social assistance and unemployment insurance.
Potential factors limiting the multiplier effects of Turkey:
•
•
Lower labor mobility for high-skilled workers, maybe due to amenities in large
cities?
Large hiring and firing costs, maybe mitigated through sizable informal sector.
Potential factors strengthening the multiplier effects of Turkey:
•
•
High income inequality and skill premium,
Low social expenditures relative to GDP.
Notes: Turkey: results based on censuses 1985-2000; USA: results from Moretti (2010); Sweden: results from Moretti and Thulin(2013)
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Job multiplier for evidence-based policy
Use the multiplier effect for policy-making
• Tax incentives for new businesses, especially if
geographically concentrated;
• Design stimulus or counter-cyclical policies;
• Promotion of innovation and high-value added industries;
• Understand future demand of jobs and infrastructure
resulting from industry growth in specific geographic
areas;
• Understand future internal migration as some districts
grow and others fizzle.
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