National accounts also often contain labour market information ...... Note: In the rst model calibration the informal sector accounts for 57%. ..... Public sector. Note: ...
Macro-Labour Lecture:
Understanding labour market dynamics Ekkehard Ernst Macroeconomic Policies and Jobs Unit Research Department International Labour Organization (ILO)
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November 2018
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How do long-term averages compare?
USA vs. Germany
A little quiz Long-term average performance (1973-2016) USA
Germany
Unemployment rate
6.4
6.4
Employment growth
1.4
0.6
Total hours worked
1.3
-0.1
(in % of the labour force) (in % p.a.)
(change in % p.a.)
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ILO
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Overview
Purpose and learning objective Purpose of this lecture
I
Introduction into main labour market concepts
I
How concepts relate to each other
I
How to measure labour market concepts
I
Carry out a country analysis
What you will learn in this lecture
I
Main building blocks of labour market analysis
I
How they relate to macro-economic models
I
How to identify key labour market obstacles
I
How to carry out a country scan
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Overview
Overview 1
Theoretical considerations: Making sense of the labour market
I I I 2
...and its extensions Mobility, barriers and segmentation
Empirical applications: Sources and trends
I I I I I 3
The standard model...
Assessing real-world labour markets : Labour market information Margins of adjustment: Measuring wages, ows and hours worked Institutions and regulation Employment projections How to do a country scan
Country diagnostics: Where are the key barriers?
I I
Introduction to country scans Preparing group work sessions
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ILO
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Labour market concepts, indicators and models
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ILO
November 2018
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Part I - Overview
Overview: Labour market concepts and theory 1
Key indicators of the labour market
2
Sources of labour market information: Labour market surveys, National accounts, and Big Data
3
Search, matching and mismatch: The standard case
4
...with endogenous search
5
...with monopolistic competition
6
...with endogenous job destruction
7
...with dual labour markets
8
Okun's law, the Phillips curve and natural unemployment
9
Growth and unemployment
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ILO
November 2018
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Key labour market concepts and information sources
Key indicators of the labour market
Decomposing the labour force: Decent work indicators
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ILO
November 2018
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Key labour market concepts and information sources
Sources of labour market information
Labour market information: Sources I
Surveys of households (`persons')
I I I
I
Population census Income and expenditure survey
Surveys of establishments (`companies')
I I I
I
Labour force survey
Establishment survey of production Employment and earnings survey Occupational employment and vacancy survey
Administrative data (`records')
I I I
Educational enrolment data Migration records Employment services records
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ILO
November 2018
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Key labour market concepts and information sources
Sources of labour market information
Labour market information: Comparison I Household surveys
Strengths
I
Comprehensive coverage
Weaknesses
I
of population
Sampling prevents reliable estimates for small groups
I
Detailed questioning
I
Lower quality of data on
permits precise
income, sensitive and
measurement of
employer-related topics
statistical concepts for short reference periods
I
Ekkehard Ernst
Labour ows can be
I
Cannot provide estimates
estimated when panel
of vacancies, training
structure
needs, etc
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November 2018
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Key labour market concepts and information sources
Sources of labour market information
Labour market information: Comparison II Strengths
Establishment surveys
Ekkehard Ernst
Weaknesses
I
Comprehensive coverage of larger businesses
I
Poor coverage of very small and unregistered businesses
I
Payroll records provide consistent and reliable data for income and employment by industry
I
Requires constant updating of registers (births and deaths)
I
Only source for data on vacancies, training needs, etc
I
High non-response rates
I
Sampling prevents reliable estimates for small groups
I
Data items are limited by the information in establishment's registers
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Key labour market concepts and information sources
Sources of labour market information
Labour market information: Comparison III Administrative records
Strengths
I
Total count allows
Weaknesses
I
Often poor coverage
I
Often not up to date
I
Data quality may be
maximum detail
I
Inexpensive to compile statistics
questionable
I
Series breaks when adm. denition changes (e.g. to receive unemployment benets)
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ILO
November 2018
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Key labour market concepts and information sources
Sources of labour market information
Labour market information: Processing
How to best exploit household or labour force surveys:
I
Pre-process data to t
I
Cross-tabulates and generates labour market indicators using ILO
ADePT
denitions
I
Extensive documentation of tool and labour market concepts: ADePT documentation
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ILO
November 2018
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Key labour market concepts and information sources
National accounts
National accounts information National accounts also often contain labour market information
I
Auxiliary variables to allow to calculation of ratios, e.g. output per employee
I
Can contain more detailed information than LFS:
I
I I
Hours worked, wages
Are based on the establishement principle Beware of the production concept:
I
Production is a domestic concept, i.e. all production taking place in a particular economy
I
Labour force is a national concept, i.e. all residents that are part of the labour force
I
Large discrepancies in small open economies with cross-border workers (e.g. Luxembourg, parts of Switzerland).
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Key labour market concepts and information sources
Other sources, big data
Other sources of labour market information I
ILO October Inquiry:
I
I
Meta survey request pre-processed data
School-to-work transition surveys:
I
Tailor-made surveys on 30 countries (2 waves) on education and labour market status of 15-29 years old
I
Child-labour surveys:
I
Tailor-made surveys on labour market status using 75 household surveys of less than 18/15 years old
I
ILO's Key Indicators of the labour market (KILM):
I I
18 key indicators collected from national sources Overview of denitions and concepts, including limitations:
KILM
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Key labour market concepts and information sources
Other sources, big data
Unstructured data
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ILO
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Key labour market concepts and information sources
Overview of labour markets around the world
A snapshot on global labour markets
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ILO
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Labour market models
The standard Beveridge curve
How to think about labour markets Beveridge curve
V
Lower job rent (p − w) #
V1 V0 Rising mismatch
U0
U1
U
The Beveridge curve links vacancies to job seekers via the matching function:
m (V , U).
m =
In equilibrium, matching equals job destruction:
m (V , U) = σL = σ (1 − U) I
Rising wages, lower productivity, higher costs of opening vacancies lowers job creation ray;
I
Rising mismatch shifts Beveridge curve outward.
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1. Labour supply is xed; job destruction happens at exogenous rate σ 2. Changes in unemployment are determined by the rate at which job seekers match with open vacancies, Vt ∆Ut = σ · Lt − m (Vt , Ut ) · Ut
where m (·)displays constant returns to scale. 3. In equilibrium when ∆Ut = 0 and normalizing the labour force to unity, i.e. unemployment rate is: U¯ =
Lt =
1 − Ut the
σ
¯ 1 σ + m θ,
where θ = UVtt represents the tightness of the labour market. 4. Firms open a new vacancy when they expects its net prots prior to the match to equal the cost of opening a vacancy: (p + w ) · m (θ, 1) · Vt
=
⇒p−w
=
(r + σ) · p · ζ (r + σ) · p · ζ m (1, 1/θ)
where p: sales price, ζ : instantaneous vacancy costs 5. The quasi rent of a match is shared through (Nash) wage bargaining: w = (1 − β) R + β · p (1 + θζ)
where β : workers' bargaining power and R : the reservation wage. 6. The job creation equation is determined through combining the wage equation and the labour demand schedule: (r + σ) + βm (θ, 1) (1 − β) (p − R) = p·ζ m (1, 1/θ) Source: Pissarides (2000), ch. 1
Labour market models
The standard Beveridge curve
The Beveridge curve: Country examples
3000
3500
4000
4500
4000
5000
2015 2007 2006 2008
5000
6000
8000
10000
12000
14000
16000
350
Unemployment
400
450
2007
2001 2002 2003
2006 2011 2000 2005 2012 2010 2004 1999 1998
200
2013 2014 2015
1997 1996 1995
150
Vacancies 2010
2008
2009
100
2009 2006 2004 2005
250
300
80000 60000 20000
Vacancies
40000
2014 2012 2013 2011
20082007
300
2010
France
2015
250
2011
Unemployment
Sweden
200
2013 2012 2009
Unemployment
2001 20022003
2014
2003 2002 2005 2004
3000
Vacancies
2001
2016
2000
600 500 400 200
300
Vacancies
2015 2015 2012 2014 2012 2011 2001 2014 2013 2000 2013 2001 2000 2007 2007 2011 20082008 2002 2010 2002 2006 2009 2003 2010 2006 2009 2005 2003 2004 2005 2004 2500
United States
6000
Germany 2016
1990 1989 1992 1991 2000
1994 1993 2500
3000
Unemployment
Source: Germany - Bundesbank; USA - FRED; Sweden, France - OECD Main Economic Indicators Ekkehard Ernst ILO November 2018
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Labour market models
The standard Beveridge curve
What explains labour market mismatch? I
Outward movements of the Beveridge curve indicate rising mismatch:
I I
I
More open vacancies per number of job-seekers More job-seekers for each individual vacancy
Reasons?
I
Geographical mismatch:
Job-seekers don't move to locations where
jobs are
I
Skill mismatch:
Job-seekers don't have the right skills (horizontal,
vertical, quantitative)
I
Wage increases and sectoral reallocation (Mehrotra & Sergeyev, 2012): High wage increases lower demand for specic sectors
I
Institutions (Bonthuis et al., 2015):
Employment protection,
occupational licensing prevent quick restructuring
I
Demographic shifts (Bova et al., 2016):
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ILO
Strong labour force growth
November 2018
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1. Skill mismatch is also known as occupational mismatch. 2. Three dierent forms can be distinguished: Quantitative: The most general form: supply of skills does not correspond to demand (either too high or too low) Horizontal: Field of studies in supply and demand do not match (e.g. there is a high demand for engineers but only psychologists are available) Vertical: The level of education does not match demand (e.g. strong demand for low-skilled workers is matched only by tertiary educated graduates) 3. In the case of vertical mismatch, two problems arise: When demand for skills is higher than supply, productivity growth suers. When supply for skills is higher than demand, reservation wages and unemployment (among graduates) is high.
Labour market models
The standard Beveridge curve
Alternative matching theories... Traditional explanation: Random matching between jobseekers and rms with open vacancies:
I
Pissarides (2000); Mortensen & Pissarides (1994)
Convex adjustment costs of labour and capital: Productivity shocks have persistent employment eects:
I
Den Haan et al. (2000); Merz & Yashiv (2007)
On-the-job search and heterogeneity: Degree of mismatch depends on state of the macro-economy:
I
Albrecht & Vroman (2002); Pissarides (1994); Mortensen & Nagypál (2007); Nagypál (2008)
Directed search and queueing lead to endogenous matching function with asymmetric reactions to gov' interventions:
I
Kohlbrecher & Merkl (2016); Lagos (2000); Sattinger (2005)
Endogenous search intensity and job quality changes with workers' outside options:
I
Acemoglu (2001)
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Labour market models
The standard Beveridge curve
...and implications for employment dynamics Dierence between traditional and search-and-matching framework:
I
Asymmetric reactions to business cycle upswings and downswings (job-less recoveries)
I
Search-and-matching allows to distinguish between job creation and destruction dynamics (see, e.g., Davis et al., 1998)
I
Skills mismatch (e.g. skill-biased technological change) increases in upswings
I
Persistence of unemployment dynamics with respect to shocks
I I
Sluggish labour productivity adjustment following a shock Common framework to understand ows between unemployment, employment and inactivity
I
Accounting for job ows in driving employment (for the UK: Elsby et al., 2011; for the US:
I
Shimer, 2012)
Fluctuations of participation over the business cycle (Krusell et al., 2017)
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Labour market models
Extensions of the Beveridge curve
Extensions of the Beveridge curve 1
Endogenous search
I
Depending on the state of the labour market, workers will search more intensively
2
Monopolistic competition
I 3
Endogenous separation
I 4
Firms are price-setters, workers price-takers
Productivity shocks will endogenously destroy jobs
Labour market segmentation
I
Distinguishing between dierent types of workers (skilled vs unskilled)
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Labour market models
Extensions of the Beveridge curve
The Beveridge curve with endogenous search Beveridge curve: Endogenous search
V
Lower cost of filling a vacancy (p − w) "
V1 V0
Higher search effort
U1
U0
U
I
When search eort goes up, matching rates go up and less unemployed are roaming for vacancies
I
Employers cut time in nding workers, the job rent goes up and more vacancies are being created
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ILO
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Labour market models
Extensions of the Beveridge curve
The Beveridge curve with monopsonistic competition V
Beveridge curve: Monopsonistic competition
Lower wages (p − w) " V1
V0 Lower search effort
U0 U1
U
I
Employers set wages unilaterally; maximise share of matching rent that goes to capital owners
I
Workers reduce search eort, employers increase vacancy posting: Ambiguous eect on unemployment
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What is monopsony?
Firms are price-setters as they dominate the (local) labour market
Workers are price-takers and cannot negotiate their wages
The monopsonistic rm maximises:
max π = p · y m (L) − w (L) · L L
with the rst-order condition:
∂π = 0 ⇔ p · yLm − w − w 0 · L = 0 ∂L Let
εLw ≡
w L
·
∂L . Then, the rst-order condition writes as: ∂w
yLm − w 1 = ⇔ yLm = w w εLw
1
+
1
εLw
.
1 > 0, y m > w and hence y m < y 0 . In other words, both production As ε L L Lw and employment will be in the monopsonistic case, compared to the full competition case.
smaller
Labour market models
Extensions of the Beveridge curve
Beveridge curve: Endogenous job destruction Beveridge curve: Endogenous separation
V
Negative productivity shock lowers matching rent
(p − w) #
V1 V0 Negative productivity shock shifts Beveridge curve up
U0
U1
U
I
A (permenant) negative productivity shock reduces the job rent, decreases job vacancy positing
I
If only certain sectors or occupations are aected, mismatch goes up and the Beveridge curve moves outward
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ILO
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Labour market models
Extensions of the Beveridge curve
Labour market duality Tightness for high-skilled labour higher than for low-skilled A: Arbitrage condition of vacancies between high- and low-skilled labour, with jobseeker arrival probability:
θH
A B
¯ θ:
Maximum arrival rate for low-skilled labour VL ! 0
U
θH ∼ V H H
Steepness of A determined by productivity differential between H and L workers
U
θL ∼ VL L
B: Flow equilibrium locus (Beveridge curve): ¯ = LH + LL L
45◦ θ¯
θL
Source: Saint-Paul (1996); Zenou (2008)
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ILO
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Labour market duality with matching frictions
Both labour market segments have type-specic, constant-returns-to-scale matching functions: i i i m = m V ,U ,
where i
∈ {H, L}
The arrival rate at which jobseekers match with vacancies is the slack in the labour market and dened as: i
m V i , Ui
θ =
=m
Vi
1,
Ui
Vi
!
(1)
Curve A:
Value of a vacancy, V , is determined by an asset equation and depends on the value of a matched job, J , and the expected future change in value, V˙ . Hence, the value of H-vacancy writes as: (r + θH ) V
H
H H
=θ J
+ V˙H
(2)
with r : the discount rate (interest rate) and θH : the labour market tightness of the H -labour market. Similarly, the value of L-vacancies are determined as: (r + θL ) V
L
L L = θ J + V˙L
where θL : the labour market tightness of the L-labour market.
(3)
The (ow) value of a job, J , depends on the productivity of L- versus H -jobs. (r + σ) J
H
(r + σ) J
L
=
ρ + σV
H
=
1 + σV
L
+ J˙H + J˙L
(4) (5)
where ρ > 1, the productivity of H−jobs (i.e. the productivity dierential with respect to L-jobs) and σ: the exogenous rate of job destruction. In equilibrium, we have: V
and
L
=V
H
V˙H = V˙L = J˙H = J˙L =
0
Combining equations (2)-(5) and rearranging terms, we obtain: θ
H
=
θL ρ − θ L (1 − ρ) / (r + σ)
which is represented in the chart by the curve A. The curve A is upward-sloping and lies above the 45°-line. The larger the productivity dierential, ρ, is, the steeper is the curve. Curve B:
Curve B describes the ow equilibrium locus. The number of jobseekers can be recovered from equation (1) as: i i i U =V h θ
Assume a labour force normalised to unity, L = 1, and, total employment, E , and employment in H - and L-jobs as E H and E L . Then, the number of available jobs must equal the number of vacancies:
Let's assume x : the share of H -type workers, then: U
H
=x −E
H
and U L
=L−x −E
(7)
L
Change in employment is determined by hirings and job separations. In steady state where have: i i i E˙ i = m V , U − σE =
0 ⇔ Ei
E˙ i =
m V i , Ui
=
σ
0 we (8)
Using (7) and (8), we obtain the market-specic Beveridge curves: h θi
i
u =
where uH
H = Ux
, uL
θ i/σ
H H = 1V−x , v H = Vx
U V
+ h θi
, vL = =
and v i
L = 1V−x
=
1 θ i/σ
+ h θi
(9)
and the accounting equations:
x ·u
H
+ (1 − x) · u
L
x ·v
H
+ (1 − x) · v
L
Plugging in (9) into (8) and (6), we can determine the ow equilibrium locus B in the chart as: 1 + θH/σ 1 + θL/σ x H + (1 − x) L =E θ /σ + h θ H θ /σ + h θ L which is downward-sloping in the
θ H , θ L -quadrant.
(10)
Labour market models
Extensions of the Beveridge curve
Rise in the skill premium More jobs lost for low-skilled than created for high-skilled Increase in the demand for highly skilled:
I I I
θH
A
A0 B
Decreases vacancy creation for low-skilled Increases vacancy creation for high-skilled
θ¯0 < θ¯ Maximum tightness for low-skilled labour declines
Increase in the skill premium
Rise in aggregate unemployment A rise in H-productivity makes vacancy creation for L-workers over-proportionally more costly θ¯0
θ¯
θL
Source: Saint-Paul (1996)
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ILO
November 2018
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Using (9), the aggregate unemployment rate is given by: U = xu
H
h θH h θL L + (1 − x) u = x H + (1 − x) L . H θ /σ + h θ θ /σ + h θ L
Full dierentiation yields the change in the unemployment rate as a function of changing labour market tightness on H - and L-labour markets: H H L L dU = xµ θ dθ + (1 − x) µ θ dθ (11) where µ
θi =
θ i h0 θ i −h θ i /σ 2 θ i /σ+h θ i
>
0 as h (·) is convex, i.e.
h0 > 0, h00 >
0.
Changes along the B -curve are determined by dierentiating (10): 0 = xϕ where ϕ
θi =
H H L L θ dθ + (1 − x) ϕ θ θ
h θ i −θ i h0 θ i /σ− h0 θ i +1/σ 2 θ i /σ+h θ i
Plugging (12) into (11) yields:
(12)
.
µ θL · ϕ θH H H dU = xµ θ 1− dθ µ θH · ϕ θL
The impact of a change in H -tightness, θH , on the unemployment rate will depend on: µ θL · ϕ θH < H µ θ · ϕ θL
Given the convexity of
h θi ,
1⇔
θ L h0 θ L − h θ L θ H h0 θ H − h θ H < . 0 L 0 H σh θ + 1 σh θ +1
this condition will be satised as long as
lies above the 45°-line. Given that µ
θi >
0 and
dθ H dρ
>
θH < θL ,
0, this establishes that
which is the case as the A-curve dU dρ
>
0.
Labour market models
Extensions of the Beveridge curve
Rise in the supply of college graduates Increased labour supply makes both segments more uid θH
I
B
B0
A0
A
Further increase in vacancy creation for high-skilled
I
But also more vacancies for low-skilled
θ¯0
θ¯
θL
Source: Saint-Paul (1996)
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ILO
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Labour market models
Wages and rigidities
Theories on wages Wage bargaining
Sharing
Ecient
matching rents
bargaining
Benchmark theory:
Internal
Fully exible wages
labour market
Tournament
Wage
Eciency wages
posting
Prevent
Limit
Worker
Gift
Wage
shirking
turnover
selection
exchange
dispersion
Ekkehard Ernst
ILO
Monopsony
November 2018
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Labour market models
Wages and rigidities
Why do wages not adjust during downturns? I
Administered wages and prices:
I I
I
Unemployment benets
Wage bargaining:
I I
I
Minimum wages
Wages adjust only partially to shocks Wages react to nation-wide, sectoral shocks
(Downward) wage rigidities (see Bewley, 1999):
I
Nominal wage rigidities:
I I I
I
Menu costs: xed costs of changing price tags Information rigidities: xed costs of acquiring information Social norms; fairness considerations
Real wage rigidities:
I I
Employment protection Eciency wages
Matching labour demand and supply is costly, not instantaneous! Ekkehard Ernst
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November 2018
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Labour market models
Labour supply: Extensions
When wages fall too much: The reserve army eect w LD
LS
wC
wI
LC
LI
L
Source: Dasgupta & Goldar (2006)
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ILO
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Labour market models
Labour supply: Extensions
Household income and labour supply decisions w wH wH , LH : High-income households Satiation level wC , LC : Competitive equilibrium wI , LI : Informal employment
wC
Reservation wage
LS
wI
LD LH LC
LI
L
Source: Sharif (2000)
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ILO
November 2018
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Labour market models
Skills and technology
Skills and education Human capital an essential investment for economic development and labour market success:
I
General education increases access to new technologies, enhances productivity
I
Job-relevant skills are needed to access particular labour market
Skills can be:
I
general (reading, writing, math);
I
occupation-specic (e.g. how to assemble a car) or
I
company-specic (company procedures, production techniques)
Returns to schooling,
α,
typically measured using Mincer equations:
Yit = Y0 +α·YearsOfSchoolingit +β·ObservedIndividualCharacteristicit +εit
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ILO
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Labour market models
Skills and technology
Skill premia in historical perspective
1.0
Wage premium: Craftsmen to labourers 1.2 1.4 1.6 1.8
2.0
Wage premium in England: 1220−2000
1200
1400
1600
1800
Source: https://ourworldindata.org/skill-premium-income-by-education/; Clark (2005) Ekkehard Ernst ILO
2000
November 2018
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Labour market models
Skills and technology
Returns to schooling across the world Returns to schooling by educational level and region (latest available year between 2000-2011) Region
Primary
Secondary
Tertiary
GDP per capita
World
10.3
6.9
16.8
6,719
Middle East and North Africa
9.4
3.5
8.9
3,645
South Asia
9.6
6.3
18.4
2,626
Eastern and Central Europe
8.3
4.0
10.1
6,630
High-income economies
4.8
5.3
11.0
31,748
(2005 PPP)
East Asia and the Pacic Latin America and the Caribbean Sub-Saharan Africa
11.0
6.3
15.4
5,980
9.3
6.6
17.6
7,269
13.4
10.8
21.9
2,531
Source: Montenegro & Patrinos (2014)
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ILO
November 2018
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Labour market models
Skills and technology
20000
GDP per person employed (in US$) 25000 30000 35000
40000
Skills and economic development
2019
2015 2011 2007
2003 1999 1995 1991 12
14
16 High−skilled workforce (in %)
18
20
Note: Data after 2014 are forecasts.
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ILO
November 2018
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Labour market models
Skills and technology
Skill-biased technological change
Note: TFP = total factor productivity. Source: De Michelis
Ekkehard Ernst
et al.
(2013)
ILO
November 2018
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Labour market models
Skills and technology
Job polarization
Source: ILO (2015)
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ILO
November 2018
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Labour market models
Skills and technology
Explaining job polarization Skill complementarity Ease of automation
High
Low
High
Routine-cognitive tasks
Routine manual tasks
Low
Non-routine-cognitive tasks
Non-routine manual tasks
What explains job polarization? (see, e.g., Goos et al., 2014)
I
Routine tasks will be automized
I
Non-routine tasks at both ends of the income distribution
But: I
Rogo (2011): Can skill premia persistent in a world with labour mobility?
I
Absolute vs. comparative advantages
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ILO
November 2018
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Labour market models
Macro-labour dynamics
Macro-economic owchart
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ILO
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Labour market models
Macro-labour dynamics
Okun's law I I
Arthur Okun (1962) discovered an empirical relationship:
I
A negative correlation between the rate of unemployment and the real output
I
Okun's Law is a simple equation in which it has been used as rules of thumbs
I
Many studies have been done on conrming this relationship⇒Okun's Law has become a feature in standard macroeconomic models
I
To produce more goods and services in an economy more labour input is required. Examples:
I I
I
Hiring more workers making employees work longer hours.
Arthur Okun presumed that the rate of unemployment reected the amount of labour used in the economy
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Okun's law describes the demand side and is a reduced form relationship between aggregate demand and labour demand: 1. Shifts in aggregate demand will cause output to uctuate around potential causes rms to hire or re workers which changes the employment level. 2. It describes deviations of employment and output from their potential when the economy is working under full employment. 3. Potential output is determined by the economy's productive capacity and increases over time as a result of technological change and factor accumulation. 4. The level of employment over the long run (the natural rate of unemployment) is determined by the size of the labour force and by frictions in the labour market 5. When output is at its long run, both employment and unemployment are at their long run levels. Moreover, in the log-run (without demand shocks), unemployment and output will be unrelated.
Labour market models
Macro-labour dynamics
Okun's law II Okun's law can be formulated as an empirical relationship between changes in unemployment,
∆u ,
and GDP growth,
g
(see Okun, 1962; Ball et al., 2013;
Cazes et al., 2013):
g = A − c · ∆u When labour market ows are in equilibrium:
∆u = 0 ⇒ ⇒
m (V , U) = σE = σ (1 − U) U = f (1/V ) , ∆u = f (1/∆V )
Growth and vacancy creation are therefore positively linked as
f 0 < 0:
g = A − c · ∆u = A − c · f (1/∆V ) In order to understand the impact on prices and wages, we need to link growth to ination. This is done with the
Phillips curve via the Modied output gap
(see Sell (2016)):
e e MOG : π = π+ 1 + βg = π+1 + β [A − c · f (1/∆V )]
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Empirical estimates of Okun's coecients Estimated Okun's coecients vary across countries and over time:
country Australia Austria Belgium Canada Denmark Finland France Germany Ireland Italy Japan Netherlands New Zealand Norway Portugal Spain Sweden Switzerland United Kingdom United States
Estimates pre 1995 post 1995 -0.552 -0.433 -0.134 -0.137 -0.634 -0.310 -0.500 -0.287 -0.490 -0.369 -0.610 -0.297 -0.400 -0.335 -0.427 -0.270 -0.462 -0.382 -0.142 -0.358 -0.109 -0.209 -0.713 -0.336 -0.317 -0.426 -0.319 -0.247 -0.221 -0.463 -0.793 -0.923 -0.648 -0.362 -0.211 -0.274 -0.419 -0.215 -0.447 -0.464
Source: Ball et al. (2013)
Labour market models
Macro-labour dynamics
The Phillips curve I π PC
π0
U
U0
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Labour market models
Macro-labour dynamics
The Phillips curve II: Demand shock π PC
π1
π0
U1
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1. Phillips (1958) documented for UK data from 1861 to 1957 a downward-sloping relationship between the growth rate of nominal wages and unemployment. 2. This became an integral part of policy making in the 1960s:
πt =
X
γi πt−1 − β · ut
i≥1 where
γi
the autoregressive terms of past ination rates and
slope of the trade-o between unemployment and ination. 3. Policy makers expected to be able to exploit this trade-o permanently.
Increase in the money wage via a monetary stimulus... ... would lead to an increase in aggregate demand... ...which would decrease unemployment.
β
the
Labour market models
Macro-labour dynamics
The Phillips curve III: The NAIRU π PC
NAIRU
π1
π0
U1
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U0
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Labour market models
Macro-labour dynamics
The Phillips curve IV: Rational expectations π PC
NAIRU
π1
π0
U
U0
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1. Both Friedman (1968) and Phelps (1968) noted - independently - that with adaptive expectations, the Phillips curve trade-o breaks down, once ination is constant:
πt = πte − β · ut Whenever
πt = πte = πt−i
then necessarily
β = 0.
2. This creates a ratcheting eect:
Increase in money wages leads to an increase in prices
⇒Purchasing
power and the real wage are not increasing
Production has not increased, consumption will fall back to initial level. Unemployment will return to previous level, i.e. the NAIRU
But:
Ination is permanently higher now.
This became the majority view after the hyperination episode in the 1970s. 3. With rational expectations, agents do not make any mistakes on average: πte = πt . There will be no trade-o, even in the short-run (Sargent & Wallace, 1975). 4. Expansionary policy without money illusion: Purchasing power is kept constant. Ination will jump immediately to higher level without aecting unemployment.
Labour market models
Macro-labour dynamics
Linking Beveridge and Phillips curves I
U
PC , and curve, BC ,
Phillips curve, Beveridge
P C1
BC0
BC1
P C0
are connected through the Modied Output Gap,
I
MOG ; N AIRU1
Move along the (short-term) Phillips curve aects job creation,
I
N AIRU0 JC0
JC ;
Shift of the Phillips
JC1
curve shifts the Beveridge curve, 0
I NAIRU
→ 1;
π
π1
V0
π0
V1
V
is the angle of
the job creation line compatible with stable ination
I
An increase in labour market mismatch (dashed lines), increases M OG0
th NAIRU M OG1
See Dickens (2009); Sell (2016)
π
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Labour market models
Macro-labour dynamics
Growth and unemplomyent: Overview Disembodied technological change I
Productivity increases for all jobs
I
No replacement of capital needed
I
Ex.: Economies of scale from trade
Embodied technological change I
Productivity increases only for new jobs
I
Capital investment needed
I
Old jobs become obsolete
I
Ex.: Robotization
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Labour market models
Macro-labour dynamics
Growth and unemployment: The capitalization eect I Introducing growth in the previous framework requires to consider capital accumulation (e.g. 1.
Eriksson, 1997):
Firms choose investment,
I,
desired employment,
L
and vacancies,
V,
to maximize their prots:
ˆ
∞
max
I ,L,V
[F (K , p · L) − w · L − pcV − I ] e −rt dt
0
K˙ = I − δ · K where p : labour-augmenting productivity, c : vacancy creation cost, σ : exogenous job destruction, and δ : capital depreciation.
subject to
2.
L˙ = q (θ) V − σ · L
and
Workers reap part of the quasi rent of the match through wage bargaining:
ζ w = βp f (k) − (r + δ) k + cθ 1−ζ where
f (k) =
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Labour market models
Macro-labour dynamics
Growth and unemployment: The capitalization eect II 3.
Labour market equilibrium using standard optimization procedures:
(1 − β) f (k) − kf 0 (k) − 4.
Labour market tightness,
⇒Unemployment
5.
The
θ,
r +σ−g ζ βcθ − c =0 1−ζ q (θ)
increases with (exogenous) growth,
g.
and growth are negatively related.
capitalization eect:
Firms that expect higher growth have an
interest to bring forward vacancy creation as the opportunity cost of an open vacancy falls with higher growth.
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Labour market models
Macro-labour dynamics
Growth and unemployment: Endogenous tenure Tenure T JD
I
JC
With endogenous separation rms chose both vacancy creation and tenure
I
T0
Higher growth and higher wages lead to lower tenure
θ
θ0
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Labour market models
Macro-labour dynamics
Growth and unemployment: Creative job destruction I
With technological progress, endogenous separation increases:
Tenure T JD0
JC1
JC0
JD1
JD0 → JD1 T0
I
Technological progress also raises wages, which lowers vacancy creation
T1
JC0 → JC1 θ1
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The discussion follows closely Merz (1995) and Ernst (2016). 1.
Households acccumulate wealth through deposits D = Y − c with income generated from asset returns and gainful employment Y = rW W + w · N , with rW the average ex post return on wealth and N the level of employment: W˙
D = rW W + w · N − c
=
(13)
In addition, households face an employment constraint, which depends on the number of jobs created by rms and determines the evolution of their disposable income: N˙
(14)
L
m (θ) − σ · N
=
where σ: the rate of job destruction assumed to be exogenously given. Households, then, maximise their interetemporal utility by determining their optimal path of consumption, c , subject to the job dynamics N according to the optimal household program: ˆ∞ max c
u (c, N) e
−ρt
dt
t=0
s.t. (13) and (14) 1−η c·N −γ
with the contemporaneous utility function u (c) = where η: the (constant) relative 1−η risk aversion, ρ: the intertemporal time preference rate and −γ (1 − η): the disutility from labour. 2.
In steady state, households optimal consumption evolve according to: g =
c˙ c
=
1 η
(rW − ρ)
(15)
3.
Firms post vacancies on the labour market and invest in new capital. They transform inputs according to a constant-returns-to-scale production function with labour-saving technological progress, A: F = F (K , AN) , FK > 0, FN > 0, FKK < 0, FNN < 0. Keeping a vacancy open is costly and proportional to wage costs ζ · w V . Existing jobs are destroyed at an exogenous rate σ. Installed capital depreciates at rate δ. The rm then maximises prots selecting vacancies, V ≥ 0, and its capital stock according to the following optimal program: ˆ ∞
max
N,K ,V
0
ν1 (t) (F (K , AN) − wN − rK K − ζ · w V − rK K ) e
−ρt
(16)
dt
where ρ stands for the intertemporal preference rate and ν1 (t) for the household's shadow variable related to its accumulation constraint, which rms maximise against the constraints of employment and capital accumulation:
4.
N˙
=
q (θ) V − σ · N
K˙
=
I − δ · K.
(17) (18)
Following Eriksson (1997), bargaining power, β , describes the bounds between which wages and interest rates have to fall: Workers have a fall-back option provided by the social security system, which guarantees a replacement income in form of unemployment benets, R0 . Hence, wages will be determined as a weighted average of the sum of marginal productivity, FN , the gain of lling a vacancy, θζ0 , and unemployment benets, R0 : w = β (FN + θζ0 ) + (1 − β) R0
Both unemployment benets and vacancy costs are assumed to be adjusted in line with real wages in order to capture increases in productivity:R0 = R · w (0 ≤ R < 1), ζ0 = ζ · w . Hence: w = β (FN + θζ · w ) + (1 − β) R · w
⇔
w =
β
1 − βθζ − (1 − β) R
FN
(19)
5.
The program set up by (16) subject to (17) yields an equilibrium on capital and labour markets summarised in the following proposition. Firms select the optimal stream of jobs and investment according to: LL ≡ (1 − β) (1 − R) − βθζ −
ζβ
q (θ)
b+η σ+ρ−w
c˙ c
=
0
(20)
Fully dierentiating (20) allows to assess that: dθ dg
=−
∂LL/∂g ∂LL/∂θ
(
< >
0 if η > 1 0 if η < 1.
Hence, whether unemployment rises or falls with growth depends on the relative risk aversion, η, which is an empirical question. The table on the next slide provides an overview of existing estimates.
Relative risk aversion - Country estimates
Zimbabwe 0.04 Sri Lanka Belarus 0.09 Bosnia and Herzegovina Netherlands 0.1 Madagascar Albania 0.14 Germany Bolivia 0.16 Mexico Panama 0.18 Cameroon Benin 0.21 Canada Korea 0.27 Slovenia Serbia 0.27 Georgia Croatia 0.31 Uruguay Dominican Republic 0.32 Honduras Ireland 0.35 India Poland 0.38 Botswana Lao PDR 0.39 Myanmar Japan 0.44 United Kingdom Ukraine 0.44 Kosovo Paraguay 0.47 Bulgaria Estonia 0.51 Portugal El Slavador 0.54 Austria Finland 0.57 Greece Armenia 0.57 Mozambique Brazil 0.63 Chile Ghana 0.63 New Zeland Russia 0.65 Vietnam Uganda 0.67 Norway Source: Gandelman & Hernandez-Murillo (2014)
0.68 0.72 0.72 0.77 0.78 0.82 0.83 0.83 0.88 0.9 0.91 0.92 0.94 1.01 1.03 1.03 1.06 1.07 1.08 1.08 1.11 1.13 1.15 1.15 1.16
Australia Moldova Tajikistan Argentina Switzerland Lithuania Indonesia Tanzania South Africa Bangladesh Macedonia, FYR United States Ecuador France Peru Belgium Kyrgyz Republic Azerbaijan Senegal Malaysia Venezuela, Rep Bol Montenegro Burundi Taiwan Uzbekistan
1.17 1.19 1.19 1.2 1.21 1.23 1.24 1.26 1.29 1.3 1.34 1.39 1.39 1.43 1.44 1.55 1.81 1.85 1.89 1.93 2.08 2.1 2.17 2.45 2.96
Labour market models
Labour market segmentation and macro dynamics
Informality and business cycles Cyclical properties: Model comparisons with and without informality
Real business
Search and
Informality I
Informality II
cycles
matching
(high switching costs)
(low switching costs)
σ (y ) = 0.5
σ (y ) = 0.41
σ (y ) = 0.21
σ (y ) = 2.59
σ (x)
σ(x) σ(y )
corr (x, y )
σ (x)
σ(x) σ(y )
corr (x, y )
σ (x)
σ(x) σ(y )
corr (x, y )
σ (x)
σ(x) σ(y )
Consumption
0.32
0.63
0.96
0.22
0.55
0.96
0.13
0.58
0.96
1.11
0.43
0.92
Investment
0.21
0.43
0.91
0.16
0.38
0.92
0.08
0.39
0.91
1.58
0.61
0.96
Formal employment
0.03
0.06
0.71
0.05
0.13
0.97
0.05
0.24
0.96
0.03
0.01
0.56
-
-
-
0.05
0.13
-0.97
0.01
0.07
-0.01
0.02
0.01
-0.40 -0.34
Unemployment Informal employment Formal wages Informal wages
corr (x, y )
-
-
-
-
-
-
0.05
0.23
-0.99
0.04
0.01
0.35
0.70
0.99
0.22
0.54
0.99
0.13
0.62
0.96
1.10
0.43
0.97
-
-
-
-
-
-
0.09
0.44
0.99
1.15
0.45
0.98
Note: In the rst model calibration the informal sector accounts for 57%. We assume a capital elasticity in the production function of 0.26; the unemployment rate is 13%. In the second calibration, the informal sector is smaller at 50% as switching costs are smaller. Unemployment is now only 5% and the capital elasticity is calibrated at 0.54. For comparison, the results of a Real Business Cycle model and a standard Search and Matching model have also been displayed. Source: Bridji & Charpe (2011)
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Labour market models
Information and expectations
Why are networks important to understand? Production networks I
Input-output linkages between sectors: Firms in dierent sectors buy from and sell to each other
I
A shock to a rm in one sector can impact rms in other sectors (I-O analysis)
I
Depending on the strength of sectoral linkages the shocks will be felt more or less in dierent sectors
Labour market networks I
Jobseekers receive information about vacancies from friends and relatives
I I
Pockets of unemployment become persistent Information about labour market success eects one's education decision (e.g. gang violence)
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Labour market models
Information and expectations
Why are networks important to understand?
Financial market networks I
Banks are related to each other through credit linkages
I
If one bank goes bankrupt, these risks can spread from one bank to another
I
Are some banks systemic? Could they trigger a banking crisis?
I
This has become a major eld of research since the global nancial crisis!
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Labour market models
Information and expectations
Labour market networks and information Micro-structure of (labour) markets Unemployment duration depends on network structure:
I
Calvò-Armengol & Jackson (2004)
Emergence of social institutions can be fostered in tightly-knit interactions:
I
Social interactions are segmented, not fully random: Ernst (2004)
Shock transmission in production networks, use sectoral data:
I
Acemoglu et al. (2012); Castagna et al. (2017)
Social networks and labour market outcomes
I
Montgomery (1991, 1992, 1994)
Social-network structure and information contagion:
I
Jackson et al. (2017); Shiller (2017)
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Labour market models
Information and expectations
Shock transmission in networks I Understanding the employment impact of a nancial market shock: The Italian case:
I
Li,j
Employment
j = 1, .., n = 18 I
for
i = 1, ..., N = 8091
municipalities in
sectors
Construct a minimum-spanning tree (MST; connected graph) using sectoral similarities
I
The distance
δij
between two sectors
i
and
j
is calculated as:
δi,j = αi + βi · Li,j where
αi =
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and
βi =
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Labour market models
Information and expectations
Shock transmission in networks II Panel A: Network structure
Panel B: Shock transmission 10.0
R 4.4
6
A
5.1
B
4.7
D
5.6
E
Variation in employment (in percent) 4.0 6.0 8.0
P 4
L 4.7
N
Q
4.6 9.2
S
8.9 12.9
10
5.5
J
K
H
M
F
G 40.9
0.0
I 28.1 29.4
2.0
22.1
C
A
B
C
D
E
F
G
H
I
J
K
L
M N
P
Q
R
S
Note: Letters designate the 18 dierent sectors as follows: A: Agriculture, forestry and shing; B: Mining and quarrying; C: Manufacturing; D: Electricity, gas, steam and air conditioning supply; E: Water supply sewerage, waste management and remediation activities; F: Construction; G: Wholesale and retail trade repair of motor vehicles and motorcycles; H: Transportation and storage; I: Accommodation and food service activities; J: Information and communication activities; K: Financial and insurance activities; L: Real estate activities; M: Professional, scientic and tech. activities; N: Administrative and support service activities; P: Education; Q: Human health and social work act.; R: Arts, entertainment and recreation; S: Other service activities. Source: Castagna et al. (2017) Ekkehard Ernst
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Labour market models
Information and expectations
How do networks evolve?
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Labour market models
Information and expectations
How do expectations aect labour markets? I
Employers' perspectives:
I
Asset prices, investment and jobs: Phelps curves (Zoega, 2009; Hall, 2014; Kilic & Wachter, 2015)
I
I
Hiring uncertainty and nancial market turbulence
Workers' expectations:
I
Earnings prospects and investment in skills (e.g. Popov & Laeven, 2016; Wiswall & Zafar, 2016)
I I
I
Taxes, trade and informal employment Income ows and labour market participation
Social consequences of labour market outcomes:
I
Labour prospects and social unrest (see, e.g., ILO, 2015)
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Labour market models
Information and expectations
Asset prices, investment and unemployment Share price index deflated by wage index) 60 80 100 120
Canada
2007 1999 2000 2006 1998 2001 2005 1997 2004 2002 2003 1996
20
1995 1994 1993 1991 1992 1989 1972 1990 1987 1971 1973 1970 1988 1986 19851976 1984 1974 1977 1980 1981 1975 1978 1979
2
4
6 Unemployment rate
1983 1982
8
2007 2006 2000 2005
1973 1972 19701971 1974
40
Share price index deflated by wage index) 40 60 80 100 120
United States
10
4
6
2004 2001 1999 1998 1997 2003 2002 1996 1987 1989 1995 1994 1980 1986 1988 1981 1990 1985 1993 1983 1991 1979 1992 1984 1975 1976 1978 1982 1977
8 Unemployment rate
1970 1971 1974
1988 1987
1991
1992
1
Ekkehard Ernst
1986 1993 1994 1996 19951997 1985
20072006
1984 1983 1981 1982 1979 1980 1978 1976 1975 1977
2
3 4 Unemployment rate
2000 20051999 2004 2001 1998 2002 2003
2007 2006
1970
2005 1972
2000 2001 1999 1987 2004 2002 1998 1997 2003 1996 1995 1989 1988 1986 1990 1980 1985 1981
1971 1973
1974
1979 1976 1975 19771978 1982
40
1990
12
Australia
1989
Share price index deflated by wage index) 60 80 100 120 140
Share price index deflated by wage index) 100 150 200
1973 1972
50
Japan
10
5
2
ILO
4
6 8 Unemployment rate
1994 1993 1991
1984
1992
1983
10
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Labour market diagnosis
Overview
Overview of empirical methodologies Objectives of growth and employment diagnostics Diagnose the bottlenecks to job creation and growth Propose solutions
Empirical tools:
I
Presentation of basic trends
I
Principal component analysis (PCA)
I
Regression analysis; establish the relationship between dierent variables of interest
I
Forecasting and modelling - Policy scenarios
I
Input-output matrices: Sectoral and occupational breakdown of policy scenarios
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Labour market diagnosis
Growth diagnostics
A selection tree for growth analysis Low levels of private investment and entrepreneurship High cost of nance
Low return to economic activity
Low social returns
Low appropriability Balance of payments constraints Government failures
Market failures Lack of domestic nance
Low human capital Isolation/Lack of access to markets
Macro risks; nancial, monetary, scal instability
Low domestic savings
Poor intermediation
Micro risks: Property rights, corruption, taxes
Bad infrastructure Information externalities Coordination failures
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Labour market diagnosis
Labour market diagnostics
Where are barriers for labour markets?
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Labour market diagnosis
Labour market diagnostics
Linking macro- and labour-analysis I I
Linking the labour market decomposition:
Lt = Ntf + Ut + NtI1 + NtI2 I
...with the production function...
Ytf = F At , Kt , Ntf , NtI1 I
...to determine employment in the informal economy:
MPLIt1 = wtI I
...and the formal economy:
f Ntf = (1 − σ) Nt− 1 + m (Vt , Ut )
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Labour market diagnosis
Labour market diagnostics
Linking macro- and labour-analysis II I
Switching from formal to informal status and back is possible but costly:
Vtu = I
wtI + ce rt
...and depends on the average growth of national income:
gt = (1 − nt ) {σ [rt (1 − τ ) − ρ]} + nt · gtw I
...and the rate at which vacancies are created in the formal economy: 1
g LP 1+rt t
n
Ekkehard Ernst
1 βζ(1+τw )
h io + w (Rt+1 ) (1 − x) f (θt+1 ) − ζ1 = w (Rt ) · f (θt )
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Labour market policies and institutions
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Part II - Overview
Overview: Labour market policies and institutions
1
International labour standards
2
Employment protection legislation
3
Minimum wages
4
Public employment
5
Trade unions
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Labour market policies and institutions
Labour standards and employment protection legisation
International labour standards
0
Per cent of all ILO conventions 50
100
Ratification index (2016)
Central and Western Asia
East Europe+CIS
OECD
World
Source: ILO calculations
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Labour market policies and institutions
Labour standards and employment protection legisation
Employment protection legislation: Elements 1
Permanent contracts
I I I 2
Advance notice periods Unfair dismissal: Possibility of re-instatement
Temporary contracts
I I 3
Severance payments: linked to seniority, capped?
Maximum length of temporary contract Renewability, waiting periods
Collective dismissals
I
Additional costs and procedures when more than one individual is being dismissed
4
Enforcement
I
How strictly are regulations enforced? (Number of labour inspectors, quality of legal system)
I
Currently no indicator available for this dimensions
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Labour market policies and institutions
Labour standards and employment protection legisation
0
1
2
3
4
Employment protection legislation: Evolution
1985
1990
1995
2000
OECD average Australia Germany
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2010
2015
Legislative bandwidth United Kingdom France
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Labour market policies and institutions
Labour standards and employment protection legisation
Employment protection legislation: Mechanisms V
Beveridge curve: Employment protection
EPL lowers matching rent
(p − w) # V0
V1 EPL lowers job destruction
U0 U1 Impact on vacancies: Unambiguously
I
Impact on unemployment:
Ekkehard Ernst
U
negative Ambiguous; positive only if job creation declines faster than job destruction
I
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Labour market policies and institutions
Labour standards and employment protection legisation
Employment protection legislation: Issues Empirically mixed outcomes:
I
Employment protection legislation does reduce labour market ows...
I
...and aects the job-content of growth (see discussion above)
Little evidence for its eect on aggregate outcomes:
I
Aggregate unemployment barely aected
I
Some studies suggests that marginal groups are particularly aected (youth, women)....
I
...but study results are context-specic
I
More robust results on its eects on reallocation and productivity growth
Kicking the can down the road: States impose upon rms what they cannot or do not want to regulate themselves
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Labour market policies and institutions
Minimum wages and administered prices
Minimum wages: International comparison Minimum wage
0
KGZ UZB
KAZ RUS AZE
Per cent 50
UKR CZE USA TJK EST HRV MDA ROM ESP ARM HUN BGR SVK MKD LTV CAN POL SRB GBR FRA SVN DEU ALB
100
(in % of average wage)
Note: Data refers to 2013 or earlier, except for Germany: 2015. North America and Western Europe: red bars; Eastern Europe: green bars; Central Asia: blue bars Source: Global Wage Report
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Labour market policies and institutions
Minimum wages and administered prices
Minimum wages: Standard case V
Beveridge curve: Minimum wages
Lower profits with MW (p − w) #
V0
V MW
Higher search effort with a minimum wage
U0
U MW
U
In fully competitive markets, minimum wages:
I I I
Lower job creation rates; Increase search eorts by job seekers; Lower open vacancies and raise unemployment. Ekkehard Ernst
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November 2018
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Labour market policies and institutions
Minimum wages and administered prices
Minimum wages: Monopsonistic competition I Beveridge curve: Minimum wages with monopsony
V
V0
1 U0 Let's start with the competitive equilibrium
I
Firms create vacancies
I
...to match with
Ekkehard Ernst
U0
U
1 :
V0 ...
job-seekers.
ILO
November 2018
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Labour market policies and institutions
Minimum wages and administered prices
Minimum wages: Monopsonistic competition II Beveridge curve: Minimum wages with monopsony
V
Lower search effort
Lower wages (p − w) "
V1
V0
2
1 U0 In a monopsony we move from
1
to
U1
U
2 :
I
Firms have the power to set lower wages, which helps create more vacancies
I
...but job-seekers will lower search eort, leading to more unemployed
Ekkehard Ernst
ILO
V1 ...
U1 .
November 2018
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Labour market policies and institutions
Minimum wages and administered prices
Minimum wages: Monopsonistic competition III V
Beveridge curve: Minimum wages with monopsony Lower search effort
Lower wages (p − w) "
Lower profits with MW (p − w) #
V1
V MW 3
V0
2 Higher search effort with a minimum wage
1 U0 Compared to the competitive equilibrium
U
1 , in a monopsony:
higher but search eort lower, increasing both open vacancies and unemployment
I
Job creation is
I
A minimum wage will
I
A minimum wage can therefore
Ekkehard Ernst
U1 U MW
reduce vacancy creation but enhance search eort reduce unemployment: ILO
U MW < U1
2
3
November 2018
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Labour market policies and institutions
Minimum wages and administered prices
0
Public employment (in per cent of total employment) 2 4 6 8 10
Public employment around the world
D frica frica Asia Asia bean acific OEC rth A ntral ran A Carib South t Asia & P & No & Ce Saha ca & Eas East rope meri Sub− A le d n rn Eu Mid te Lati s a E SOE
General government
Public sector
Note: Partial country coverage per region. Sub-Saharan Africa: 9 countries; East Asia & Pacic: 7 countries; Eastern Europe & Central Asia: 18 countries; Latin America & Caribbean: 15 countries; Middle East & North Africa: 8 countries; OECD: 29 countries; South Asia: 3 countries. Source: ILO Stat; Rodrik (2000) Ekkehard Ernst
ILO
November 2018
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Labour market policies and institutions
Trade unions and wage bargaining
Trade unions: Monopoly unions w
LD
Union bargaining curve
LS
wU nion
wcomp
LU nion
Lcomp
LS;max
L
Source: McDonald & Solow (1981)
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ILO
November 2018
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Labour market policies and institutions
Trade unions and wage bargaining
Trade unions: Ecient bargaining w
LD
LS
π min
wU nion Efficient bargaining curve π U nion wcomp π∗
LU nion
Ekkehard Ernst
Lcomp
ILO
LS;max
L
November 2018
81 / 184
Labour market policies and institutions
Labour market segmentation
Segmented labour markets wage LdN
LdU
LdU 0
E w∗ E0 wN 0 OU
L∗U
L∗U 0
ON
Separate labour markets but full sectoral mobility:
I
Similar wages on formal and informal labour markets
I
Relative size of formal employment depends on the strength of labour demand in the formal economy.
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ILO
November 2018
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Labour market policies and institutions
Labour market segmentation
Labour market segmentation with rigid wages wage LdN
LdU
LdU 0
A
C wU
EN
wN wN 0
0 EN
OU
LC U0
LC U
ON
Labour market rigidity (e.g. unionized wages):
I
Some part of the labour market receives a wage premium
I
Shocks to the unionized sector will increase the wage premium
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ILO
November 2018
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Labour market policies and institutions
Labour market segmentation
Trade unions and an (informal) minimum wage wage LdN
LdU
LdU 0
A
C wU
EN M inimum wN wN Unemployment
OU
LC U0
LC U
¯U L
ON
Rigid wages in the non-unionised lead to unemployment:
I
Example: Minimum wages, administered prices
I
Shocks to the unionized sector will increase both the wage premium and unemployment
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ILO
November 2018
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Labour market policies and institutions
Labour market segmentation
Minimum wage in the monopsonistic formal sector wage M CL
LdF
LdN
A
wFM inimum wFM onop
OF
C 0 wN wN
B
onop M inimum LF LM F
ON
Minimum wage when the formal sector is monopsonistic:
I
Monopsonistic wage is below equilibrium wage, welfare loss
I
An increase in the (formal sector) minimum wage, lowers informality and increases welfare.
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ILO
November 2018
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Wages and labour market activity
Ekkehard Ernst
ILO
November 2018
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Part III - Overview
Overview: Wage dynamics
1
Wage trends
2
Evolution of bargaining power
3
Demographic changes
4
Wages, employment and activity
5
An activity indicator
6
Determinants of wage growth
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ILO
November 2018
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Wages, employment and hours
Wages and rigidities
Theories on wages Wage bargaining
Sharing
Ecient
matching rents
bargaining
Benchmark theory:
Internal
Fully exible wages
labour market
Tournament
Wage
Eciency wages
posting
Prevent
Limit
Worker
Gift
Wage
shirking
turnover
selection
exchange
dispersion
Ekkehard Ernst
ILO
Monopsony
November 2018
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Wages, employment and hours
Wages and rigidities
Why do wages not adjust during downturns? I
Administered wages and prices:
I I
I
Unemployment benets
Wage bargaining:
I I
I
Minimum wages
Wages adjust only partially to shocks Wages react to nation-wide, sectoral shocks
(Downward) wage rigidities (see Bewley, 1999):
I
Nominal wage rigidities:
I I I
I
Menu costs: xed costs of changing price tags Information rigidities: xed costs of acquiring information Social norms; fairness considerations
Real wage rigidities:
I I
Employment protection Eciency wages
Matching labour demand and supply is costly, not instantaneous! Ekkehard Ernst
ILO
November 2018
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Wages, employment and hours
Wage trends
Exploring wages and trends Existing cross-country predictions:
I
PriceWaterhouseCoopers (PwC) produced Global Wage Projections to 2030
I
(Hawksworth & Lambe, 2013)
The Conference Board provides labour cost projections for OECD countries (Levanon et al., 2016)
I
ILO Inwork, Global Wage Database (ILO, 2014)
Wages and macro conditions:
I
The Wage-Phillips curve: Wage growth as a function of unemployment
I
Wage curve: Level of wages as a function of unemployment (Blanchower & Oswald, 1994)
I
Dierence: Shocks to unemployment have permanent level eects with wage curve, compatible with empirical evidence
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ILO
November 2018
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Sources of incomes and their breakdown
Three major categories can be distinguished in household earnings: 1.
Wages remunerate labour and are related to formal or informal (dependent) employment relationships.
2.
Mixed incomes are generated by self-employed or employers of un-incorporated entreprises where a distinction between capital and labour remuneration is dicult.
Components of labour costs
Depending on the tax-benet system, a signicant dierence exist between total labour costs and net take-home pay: 1.
Gross wages include taxes and workers' contributions to social security.
2.
In addtion, employers also have to contribute their part to social security, adding to total labour costs.
3.
Together this creates a signicant tax wedge between net wages and gross labour costs (more than 50% in some countries).
Wages, employment and hours
Wage trends
What explains slow wage growth? Wages have developed slowly, even in those countries where unemployment is low. Why?
I
Unemployment higher than actually measured?
I
Labour market slack is still large but hidden: part-time, temporary employment, lower participation rates
I
Fall in worker's bargaining power
I I I
I
Trade unions less powerful (globalization, service sector employment) Reduction in public sector wages Rising labour market concentration
Political and hiring uncertainty?
I I
Hiring uncertainty still higher than before the crisis Despite the low increase in living standards only limited social movements
I
Demographic eects?
I
Older workers have typically less rapid wage growth, composition eects
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ILO
November 2018
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Wages, employment and hours
Wage trends
Fall in bargaining power I: Trade unionization Evolution of trade unionisation (in %) mid 2010s 100 Iceland
80 Denmark Sweden Finland
60 Belgium Norway Malta Cyprus
40
Bolivia Italy Luxembourg Russian Federation Argentina Canada Austria Ireland Romania Hong Kong, UnitedChina Kingdom Singapore Greece New Zealand Brazil Netherlands Chile Germany Namibia Japan Portugal SpainSwitzerland Australia Latvia Poland Czech Republic Slovakia UnitedRepublic States of Korea, Ethiopia Hungary Malaysia Philippines Lithuania France
20
Malawi
Estonia Guatemala
0 0
Source: ILOStat, Industrial Relations Data. Ekkehard Ernst
20
40
ILO
60 mid 2000s
80
100
November 2018
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Wages, employment and hours
Wage trends
Fall in bargaining power II: Bargaining coverage Evolution of bargaining coverage(in %) mid 2010s 100
France Austria Belgium Finland Sweden Denmark Netherlands Italy Spain
80
Portugal Norway
60
Germany Luxembourg Switzerland Australia Czech Republic Cyprus
40
China Romania
Ireland Canada UnitedSlovakia Kingdom Hungary
20
Greece
Malawi Estonia Japan Latvia Korea, UnitedRepublic States of Lithuania Philippines
0 0
Source: ILOStat, Industrial Relations Data. Ekkehard Ernst
20
40
ILO
60 mid 2000s
80
100
November 2018
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Wages, employment and hours
Wage trends
Fall in bargaining power III: Public sector wages
Ekkehard Ernst
ILO
November 2018
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Wages, employment and hours
Wage trends
Demographic decomposition of wages
Wage growth tracker Ekkehard Ernst
ILO
November 2018
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Wages, employment and hours
Wages, employment and activity
Should wages have been growing faster? Wage elasticity with respect to unemployment
−1.0
−0.5
0.0
G20 countries average
Pre−crisis
Ekkehard Ernst
Post crisis
ILO
November 2018
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Wages, employment and hours
Wages, employment and activity
How to measure labour market slack
Labour market slack
Inactives
Adults > 15 years not in the labour force
Ekkehard Ernst
Unemployed
Out of a job and looking for one
ILO
Short hours
Maximum annual hours minus actual hours worked
November 2018
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Wages, employment and hours
Wages, employment and activity
An activity indicator How to measure all margins on the labour market together?
I
A jobs activity index:
JAt = Hourst × (1 − Unemploymentt ) × LabourForcet I
Dene a Maximum Potential Activity Level of:
Potentialt = 3000 × WorkingAgePopulationt , I
i.e. an absence of unemployment where all people at working age (aged 15 and over) are working 3000 hours a year
I
This corresponds to the maximum amount of hours worked observed in the database.
I
The inactivity rate calculates then as (measured in per cent):
JAt InactivityRatet = 100 × 1 − Potentialt Ekkehard Ernst
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.
November 2018
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Wages, employment and hours
Wages, employment and activity
Inactivity versus unemployment: USA United States Contribution 100 to inactivity
10 66 Inactivity/ Unemployment rate
80
6 64
60
40 3 62 20
0
0 60 1960
Ekkehard Ernst
1980
2000
Hours
Employment
Unemployment rate (RHS)
Inactivity rate (RHS)
ILO
2020 Participation
November 2018
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Wages, employment and hours
Wages, employment and activity
Inactivity versus unemployment: France France Contribution 100 to inactivity
75 Inactivity/ Unemployment rate 12 74
80
60
73
40
7 72
20
71 2 70
0 1980
Ekkehard Ernst
1990
2000
2010
Hours
Employment
Unemployment rate (RHS)
Inactivity rate (RHS)
ILO
2020 Participation
November 2018
100 / 184
Wages, employment and hours
Wages, employment and activity
Wage growth: Unemployment vs. total hours
−0.5 −1.0
−1.0
−0.5
0.0
Panel B: OECD countries Wage elasticity with respect to unemployment
0.0
Panel A: G20 countries Wage elasticity with respect to unemployment
Pre−crisis
Post crisis
Pre−crisis
Post crisis
−0.5 −1.0
−1.0
−0.5
0.0
Panel D: OECD countries Wage elasticity with respect to inactivity
0.0
Panel C: G20 countries Wage elasticity with respect to inactivity
Pre−crisis
Post crisis
Pre−crisis
Post crisis
Note: Nominal wage inflation regressions include controls for GDP deflator, old−age employment and year trend. Inactivity is measured as the difference between total hours worked and a hypothetical maxi− mum number of potential hours worked. Crisis year=2008 Source: OECD, ILO Global Wage Database, own calculations
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ILO
November 2018
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Understanding labour market dynamics
Ekkehard Ernst
ILO
November 2018
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Part IV - Overview
Overview: Understanding labour market dynamics
1
Measuring labour market ows
2
Labour market mobility
3
The term structure of unemployment
4
Job-to-job transitions
5
Gross unemployment risk
6
Trade and jobs
7
Remittances and labour markets
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ILO
November 2018
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Labour market dynamics
Measuring labour market ows
Labour market ows I Most labour market information is on stocks only: I
Labour force
I
Employment
I
Unemployment
I
Informal jobs
Information on labour market ows is lacking: I
Job creation, destruction and transitions
I
Worker dis- and encouragement, retirement
I
Labour market turnover:
I
Gross risk of unemployment
Ekkehard Ernst
ILO
Job Creation + Job Destruction Total employment
November 2018
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Labour market dynamics
Measuring labour market ows
Labour market ows II EI: Retirement, maternity, sickness, disability IE: Job return after inactivity
Job stayers
Inactives
EI
E
I IE UI
EU
IU UE
UE: Unemployment outows EU: Unemployment inows
U
IU: Job search after inactivity UI: Discouragement
Long-term unemployed
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ILO
November 2018
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Labour market dynamics
Measuring labour market ows
Labour market ows III I
Labour force surveys only oer observations at one point in time:
I I
Typically, individuals cannot be followed from one survey to another Few countries have panel surveys where individuals are followed over at least two consecutive surves
I
I
Some surves have recall questions, which are often unreliable
But: I I I
Reported information can be used to construct proxies:
Unemployment by duration Average tenure for current employees A growing literature has made use of these procedures, including for forecasting: Barnichon & Nekarda (2012); Shimer (2012); Elsby et al. (2013)
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ILO
November 2018
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Labour market dynamics
Measuring labour market ows
Measuring unemployment ows I I
Measuring the gross dynamics on the labour market:
∆Ut = ∆Lt − ∆Et = Inflowst − Outflowst I
Changes in employment can be broken down:
∆Et = JobCreationt − JobDestructiont I
Assuming constant labour force, in- and outows of unemployment serve as proxies for job matching and job destruction:
∆Ut = st (1 − Ut ) − ft · Ut where:
Ekkehard Ernst
st
:
Job destruction rate
ft
:
Job creation rate
ILO
November 2018
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Labour market dynamics
Measuring labour market ows
Measuring unemployment ows II I
Outows are inversely correlated to unemployment duration (see Shimer, 2012):
ft ∼ I
1
UDt
Consider the change in unemployment from month
t −d
to month
t:
ut − ut−d = utNew − Ft · ut−d where
utNew :
new job-seekers between
t −d
and
t
unemployment duration of less than 1 month. I
Hence:
Ft = 1 − Ekkehard Ernst
ut − utNew ut−d ILO
and ft
=
with an
− ln (1 − Ft ) d November 2018
108 / 184
Labour market dynamics
Measuring labour market ows
Measuring unemployment ows III: Examples Inflows (right scale)
−3
2.0
Outflows (left scale)
1980
1990
2000
2010
−6
−5
−4
1.0 −4.0 −3.0 −2.0 −1.0 0.0
−6
−5
−4.0 −3.0 −2.0 −1.0 0.0
1.0
−3
Italy Inflows (right scale)
−4
2.0
Canada Outflows (left scale)
1985
1990
2000
2005
2010
−3
2.0
1980
1990
2000
2010
Outflows (left scale)
1970
1980
Inflows (right scale)
1990
2000
−6
−5
−4
1.0 −4.0 −3.0 −2.0 −1.0 0.0
−6
−5
−4.0 −3.0 −2.0 −1.0 0.0
1.0
−3
United States Inflows (right scale)
−4
2.0
Japan Outflows (left scale)
1995
2010
Source: ILO (2013) Ekkehard Ernst
ILO
November 2018
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Labour market dynamics
Measuring labour market ows
Measuring unemployment ows IV: More examples Germany
France
UR
350
14
United Kingdom
UR
350
14
UR
350
14
GFC 12
12
12
300 10
250
300
10
8
6
300
10
8
250
6
8
250
6
200 4
150
2 2004
2006
2008
2010
2012
2014
2016
United States
4
200
2018
2 2002
2004
2006
2008
2012
2014
2016
Japan
UR
3000
2010
4
200
2018
2 2000
2002
2004
2006
2008
2012
2014
2016
Italy
UR 14
14
2010
2018
UR 14
200 500 12
2800
12
12 180
450 10
10
10 160
2600 400 8
8
8 140
2400
350 6
6
6 120
2200 4
300
4
4 100
2000
2 2000
2002
2004
2006
2008
2010
2012
2014
2016
2018
250
2 2002
Total unemployment rate (right axis)
2004
2006
2008
2010
2012
2014
2016
Inflows in excess of outflows
2018
2 2000
2002
2004
2006
2008
2010
2012
2014
2016
2018
Outflows in excess of inflows
Note: Labour market flows (in 1000s) for selected countries - outflows from and inflows into unemployment vs. the unemployment rate. UR : Unemployment Rate. GFC : Global Financial Crisis Source: ILO Labour Flow Estimates 2018, Key Labour Market Indicators
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ILO
November 2018
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Labour market dynamics
Measuring labour market ows
Measuring labour market mobility I Shorrocks Mobility Index Et−1 Ut−1 It−1
Et ptEE
Ut
It
.
.
.
ptUU
.
.
.
M Shorrocks =
P n− ni p i n−1
ptII
Mobility is measured by all those that change labour market status within one year.
I ptEE : I ptUU : I
Job stayers Long-term unemployed
ptII : Discouraged workers
Source: Formby
Ekkehard Ernst
et al.
(2004)
ILO
November 2018
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0.0 un ga Po ry rt G uga er m l a Be ny lg iu G m re ec C ze F e ch ra R nce ep ub li Sp c ai Lu Ire n xe lan m d bo ur N Po g e l a U ni the nd te rla d Ki nds ng do Au m st U Fi ria ni nl te an d St d D ate en s m ar k
H
Shorrocks mobility index 0.2 0.4 0.6
Labour market dynamics
Ekkehard Ernst
Measuring labour market ows
Measuring labour market mobility II Shorrocks mobility index, 2009 Scale: 0 − no mobility; 1 − full mobility
ILO November 2018 112 / 184
Labour market dynamics
Measuring labour market ows
Measuring labour market mobility III How to measure mobility costs? I
Assume costly labour mobility across
Cij > 0 I
for
Wi Pi
= Marginal
productivity in sector
Flow utility of being employed in sector
Vi = RealWage I
sectors at cost
Each sector is assumed to be fully competitive, so that Real Wages
I
i ∈ {1, . . . , N}
i 6= j .
Gross labour ows from sector
i
+Cij
i : Fi0 (Li )
i:
× SectoralShock
to sector
j:
Vj mij ∼ PN
k=1 Vk
I
From the empirical observation of gross labour ows one can then deduct that (implicit) mobility costs (see Artuc et al., 2010, 2015).
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ILO
November 2018
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Labour market dynamics
Measuring labour market ows
Measuring labour market mobility IV Labour mobility costs across the world
Note: Estimates of labour mobility costs based on UNIDO data. Source: Artuc
et al.
Ekkehard Ernst
(2015)
ILO
November 2018
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Labour market dynamics
Measuring labour market ows
The term structure of unemployment How does the length of unemployment duration evolve over time?
I
Most labour force surveys only have duration data at specic period lengths:
I
I
e.g. 3, 6, 12, 24 months
Often no cross-country comparability, interval length depends on country surveys
I
But: similar distribution patterns:
I I
I
High incidence at low unemployment duration Incidence declines with duration
Estimate a
I
β -distribution
on the support [0, 1]:
Continuous distribution function characterised by two parameters,
α > 0, β > 0 I
Mean and variance:
α α+β Ekkehard Ernst
and
αβ 2
(α + β) (α + β + 1)
ILO
November 2018
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Labour market dynamics
Measuring labour market ows
The term structure of unemployment: France
Term structure of unemployment
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ILO
November 2018
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Labour market dynamics
Gross unemployment risk
Job tenure and job-to-job transitions I I
How to measure job-to-job transition rates? Available information:
I I I I
I
Incidence of tenure rates for 7 tenure brackets:
Incidencet Lengtht
Average tenure (in years) for these tenure brackets: Unemployment out- and in-ows: Employment:
UEt , EUt
Et
Calculate average tenure rates (in months):
AverageTenuret = where
i
i
12 100
·
X
Incidencei,t · Lengthi,t
i
are dierent tenure categories:
= {LessThan1Month,
1MonthTo6Months, 6MonthsTo12Months,
12MonthsTo3years, 3YearsTo5Years, 5YearsTo10Years, MoreThan10Years}
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ILO
November 2018
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Labour market dynamics
Gross unemployment risk
Gross unemployment risk I
Employment survival rates:
ct = e I
1 − AverageTenure
t
Surviving jobs:
EEt = ct · Et I
Job-to-job transitions:
JJt = Et − EEt − UEt
Gross unemployment risk GURt
= EUt + LTUt + UEt =
Ekkehard Ernst
Job loss + Long-term U + Short-term U
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November 2018
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Labour market dynamics
Gross unemployment risk
Gross unemployment risk: Germany vs United States Germany − August 2018
United States − September 2018
At risk: Not at risk: 90.7%
At risk:
Not at risk: 84.4%
Job loss
Job loss
Short−term U
Short−term U
Long−term U
Long−term U
Unemployment rates: Germany - 3.4%, USA: 3.7% Gross unemployment risk: USA = 66% higher than in Germany
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ILO
November 2018
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Growth and jobs
Job transitions and policies
17.4
14.1
11.8
10.9
−3.6
−19.0
I I I
Total
Real disposable income growth
External demand
Growth of real share prices
Capital stock growth
Employment rate (lagged)
Real wage growth
−23.1
User cost of capital
Contributions to unemployment outflows (in %) −40 −20 0 20 40
60
What aects unemployment ows? - Outows
Demand components play an important role (>40%) Indication for some nancial accelerator eect (>30%) Relative prices (wages) more moderate role ( 0, UL < 0
0
p·c =w ·L L = U (c, L) − λ [p · c − w · L]
yields the rst-order conditions: ∂L = ∂c ∂L = ∂L
0 ⇔ Uc0
0⇔
UL0
=λ·p = −λ · w
) ⇒
Uc0 UL0
3. The competitive labour market equilibrium therefore writes as: U0 0 y =− c UL0
=
p w
The standard labour market model
Monopsonistic competition
When employers are in charge w
M CL
LD
LS
M P Lmonopson
wcomp
wmonopson
Lmonopson
Lcomp
LS;max
L
Source: Manning (2003)
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ILO
November 2018
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The monopsonistic rm maximises:
max π = p · y m (L) − w (L) · L L
with the rst-order condition:
∂π = 0 ⇔ p · yLm − w − w 0 · L = 0 ∂L Let
εLw ≡
w L
·
∂L . Then, the rst-order condition writes as: ∂w
yLm − w 1 = ⇔ yLm = w w εLw
1
+
1
εLw
.
1 > 0, y m > w and hence y m < y 0 . In other words, both production As ε L L Lw and employment will be in the monopsonistic case, compared to the full competition case.
smaller
The standard labour market model
Monopsonistic competition
When employers are in charge: Welfare loss w
M CL
LD
LS
Harberger triangle: Welfare loss
M P Lmonopson
wcomp
wmonopson
Lmonopson
Lcomp
LS;max
L
Source: Manning (2003)
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ILO
November 2018
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The standard labour market model
Monopsonistic competition
When employers are in charge: A minimum wage w
M CL
LD
LS
Harberger triangle: Welfare loss
M P Lmonopson
wcomp wM inimum wmonopson
Lcomp
Lmonopson L
LS;max
L
M inimum
Source: Manning (2003)
Ekkehard Ernst
ILO
November 2018
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When rms can set wages unilaterally, the introduction of a minimum wage can increase both wages and employment as long as
w Minimum < w Comp .
Some essential reading on minimum wages:
Recent overview: Neumark & Wascher (2008)
The 2015-16 Seattle minimum wage increase: Jardim et al. (2017)
Minimum wages and rm employment in China: Huang et al. (2014)
Minimum wages in Latin America: Maloney & Mendez (2003)
Earlier evidence in low-wage services: Card & Krüger (1995)
Annex 2: Further reading
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Further reading
Bibliography I Acemoglu, D. 2001. Good jobs vs. bad jobs.
Journal of Labor Economics, 19(1),
121.
Acemoglu, D., Carvalho, V. M., Ozdaglar, A., & Tahbaz-Salehi, A. 2012. The network origins of aggregate uctuations.
Econometrica, 80(5),
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Albrecht, J. W., & Vroman, S. 2002. A matching model with endogenous skill requirements.
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283305.
Artuc, E., Chaudhuri, S.., & McLaren, J. 2010. Trade shocks and labor adjustment: A structural empirical approach.
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Artuc, E., Lederman, D., & Porto, G. 2015. A mapping of labor mobility costs in the developing world.
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Ball, L.B., Leigh, D., & Loungani, P. 2013.
Barnichon, R., & Nekarda, C. J. 2012. The ins and outs of forecasting unemployment: Using labor force ows to forecast the labor market.
Brookings Papers on Economic Activity, Fall,
83117. Bewley, T. F. 1999.
Why wages don't fall during a recession.
Cambridge, MA.: Harvard
University Press. Blanchower, D. G., & Oswald, A. J. 1994. Bonthuis, B., Jarvis, V., & Valhala, J. 2015.
determinants.
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The wage curve. Cambridge, MA.: MIT Press. Shifts in euro area Beveridge curves and their ILO
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Further reading
Bibliography II Shifting the Beveridge Curve. Dual labour markets with search costs.
Bova, E., Jalles, J. T., & Kolerus, C. 2016. Bridji, S., & Charpe, M. 2011.
Calvò-Armengol, A., & Jackson, M. O. 2004. The eects of social networks on employment and inequality.
American Economic Reivew, 94(3), 426454. Myth and measurement: The new economics of the minimum
Card, D., & Krüger, A. 1995.
wage.
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Economic vulnerabilities in Italy: A network analysis using similarities in sectoral employment.
Castagna, A., Chentouf, L., & Ernst, E. 2017.
Cazes, S., Verick, S., & Al Hussami, F. 2013. Why did unemployment respond so dierently to the global nancial crisis across countries? Insights from Okun's Law.
Policy, 2(1),
IZA Journal of Labor
118.
Chami, R., Ernst, E., Fullenkamp, C., & Oeking, A. Forthcoming. Do remittances benet workers in poor countries? Evidence from cross-country data.
IMF Working Paper. Journal of Political
Clark, G. 2005. The condition of the working class in England, 1209-2004.
Economy, 113(6),
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Dasgupta, P., & Goldar, B. 2006. Female labour supply in rural India: An econometric analysis.
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Further reading
Bibliography III Davis, S. J., Schuh, S., & Haltiwanger, J. C. 1998.
Job creation and destruction.
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MA.: MIT Press. De Michelis, A., ao, Estev & Wilson, B. A. 2013. Productivity and employment: Is it a choice?
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4160.
Den Haan, W. J., Ramey, G., & Watson, J. 2000. Job destruction and propagation of shocks.
American Economic Reivew, 90(3).
Pages 205242 of: Fuhrer, J., & Kodrzycki, Y. K. (eds), Understanding ination and the implications for monetary policy: A Phillips curve perspective. MIT Press.
Dickens, W. T. 2009. A new method for estimating time variation in the NAIRU.
Elsby, M., Smith, J. C., & Wadsworth, J. 2011. The role of worker ows in the dynamics and distribution of UK unemployment.
Oxford Review of Economic Policy, 27(2),
Elsby, M., Hobijn, B., & Sahin, A. 2013. Unemployment dynamics in the OECD.
Economics and Statistics, 95(2),
Ernst, E. 2004.
Review of
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Eriksson, C. 1997. Is there a trade-o between employment and growth?
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338363.
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The evolution of time horizons for economic develpoment.
Ernst, E. 2015. Supporting jobseekers. How benets can help unemploymed workers and strengthen job creation?
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Bibliography IV Ernst, E. 2016. Might Tobin be right? The role of market frictions in policy-induced portfolio
Pages 261287 of: Bernard, L., & Nyambuu, U. (eds), Dynamic modeling, empirical macroeconomics, and nance. New York: Springer. Ernst, E., & Rani, U. 2011. Understanding unemployment ows. Oxford Review of Economic Policy, 27(2), 268294. Ernst, E., & Viegelahn, C. 2014. Hiring uncertainty: A new labour market indicator. shifts for growth.
Formby, J. P., Smith, W. J., & Zheng, B. 2004. Mobility measurement, transition matrices and
Journal of Econometrics, 120, 181205. American Economic Reivew, 68(1), Hernandez-Murillo, R. 2014. Risk aversion at the country level.
statistical inference.
Friedman, M. 1968. The role of monetary policy. Gandelman, N., &
117.
Goos, M., Manning, A., & Salomons, A. 2014. Explaining job polarization: Routine-biased
American Economic Reivew, 104(8), 25092526. High discounts and high unemployment. Tech. rept. 19871. National Bureau
technological change and oshoring. Hall, R. E. 2014.
of Economic Research, Cambridge, MA. Hawksworth, J., & Lambe, C. 2013.
Global wage projections to 2030.
Lnodon:
PriceWaterhouseCoopers. Huang, Y., Loungani, P., & Wang, G. 2014.
from China.
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Minimum wages and rm employment: Evidence ILO
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Further reading
Bibliography V ILO. 2013. The ILO Estimates on Unemployment Flows: Introducing Flows to Assess the Variations in Unemployment.
In: Key Indicators of the Labour Market, 8th edition.
Geneva:
International Labour Oce. ILO. 2014.
Global wage report. Wages and income inequality.
Geneva: International Labour
Organization (ILO). ILO. 2015.
World employment and social outlook. Trends.
Geneva: International Labour
Organization (ILO). ILO, & WTO. 2009.
Globalization and informal employment.
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Jackson, M. O., Rogers, B., & Zenou, Y. 2017. The economic consequences of social-network structure.
Journal of Economic Literature, 55(1),
147.
Jardim, E., Long, M. C., Plotnick, R., van Inwegen, E., Vigdor, J., & Wething, H. 2017.
Minimum wage iincrease, wages, and low-wage employment: Evidence from Seattle. The Impact of Globalization on the Informal Economy - A macro-level cross country study. Kilic, M., & Wachter, J. A. 2015. Risk, unemployment, and the stock market: A rare-event-based explanation of labor market volatility. Kohlbrecher, B., & Merkl, C. 2016. Business cycle asymmetries and the labor market. Kapoor, Rakesh. 2005.
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Further reading
Bibliography VI Krusell, P., Mukoyama, T., Rogerson, R., & Sahin, A. 2017. Gross worker ows over the business cycle.
American Economic Reivew, 107(11),
34473476.
Lagos, R. 2000. An alternative approach to search frictions.
108(5), 851873.
Levanon, G., Colijn, B., Paterra, M., & Rust, E. 2016.
Journal of Political Economy,
Labor Cost Projections.
Maloney, William F., & Mendez, Jairo Nunez. 2003. Measuring the Impact of Minimum Wages: Evidence from Latin America.
No. 9800, .
National Bureau of Economic Research Working Paper Series,
Monopsony in motion. Imperfect competition in labor markets.
Manning, A. 2003.
Princeton
University Press. McDonald, I. M., & Solow, R. M. 1981. Wage bargaining and employment.
Reivew, 71(5),
McDonald, R., & Siegel, D. 1986. The Value of Waiting to Invest.
Economics, 101(4),
Quarterly Journal of
707728.
Mehrotra, N. R., & Sergeyev, D. 2012.
Policy.
Sectoral Shocks, The Beveridge Curve and Monetary
Merz, M. 1995. Search in the labor market and the real business cycle.
Economics, 36,
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896908.
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269300.
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Further reading
Bibliography VII Merz, M., & Yashiv, E. 2007. Labor and the market value of the rm.
Reivew, 97(4),
Montenegro, C. E., & Patrinos, H. A. 2014.
around the world.
Comparable estimates of returns to schooling
Montgomery, J. D. 1991. Social networks and labor market outcomes.
Review, 81(5),
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Montgomery, J. D. 1992. Job search and network composition: Implications of the strength-of-weak-ties hypothesis.
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586596.
Montgomery, J. D. 1994. Weak ties, employment and inequality: An equilibrium analysis.
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12121236.
Mortensen, D., & Pissarides, C. 1994. Job creation and job destruction in the theory of unemployment.
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Mortensen, D. T., & Nagypál, E. 2007. More on unemployment and vacancy uctuations.
Review of Economic Dynamics, 10, 327347. Labor-market uctuations and on-the-job search. Neumark, D., & Wascher, W. L. 2008. Minimum wages. Cambridge, MA.: MIT Press. Okun, A. M. 1962. Potential GNP, its measurement and signicance. Tech. rept. Cowles Nagypál, E. 2008.
Foundation.
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Bibliography VIII Phelps, E. S. 1968. Money-wage dynamics and labor-market equilibrium.
Economy, 76(4),
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678711.
Phillips, A. W. 1958. The relationship between unemployment and the rate of change of money wages in the United Kingdom 1861-1957.
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283299.
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Equilibrium unemployment theory. Cambridge, MA: The MIT Press. A lost generation? Education decisions and employment outcomes during the U.S. housing boom-bust cycle of the 2000s. Rodrik, D. 2000. What drives public employment in developing countries? Review of Development Economics, 4(3), 229243. Rogo, K. 2011. Technology and inequality. Saint-Paul, G. 1996. Dual labour markets. A macroeconomic perspective. Cambridge, MA.: Pissarides, C. 2000.
Popov, A., & Laeven, L. 2016.
MIT Press. Sargent, T., & Wallace, N. 1975. 'Rational' expectations, the optimal monetary instrument, and
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the optimal money supply rule. Sattinger, M. 2005.
241254.
http://www.albany.edu/economics/research/workingp/2005/queues.pdf.
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Further reading
Bibliography IX
Sell, F. L. 2016. Combining the Beveridge and the Phillips Curve into an integrative model: The Modied Output Gap.
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112.
Sharif, M. 2000. Inverted "S"-The complete neoclassical labour-supply function.
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Shiller, R. J. 2017. Narrative economics.
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Shimer, R. 2012. Reassessing the ins and outs of unemployment.
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Zenou, Y. 2008. Job search and mobility in developing countries: Theory and policy implications. Zoega, G. 2009.
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336355.
Employment and asset prices.
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List of slides
Understanding labour market dynamics
List of slides I 2
A quiz: Comparing long-term averages
3
Purpose and learning objective
4
Overview
6
Overview: Labour market concepts and theory
7
Decomposing the labour force: Decent work indicators
8
Labour market information: Sources
9
Labour market information: Comparison I
10
Labour market information: Comparison II
11
Labour market information: Comparison III
12
Labour market information: Processing
13
National accounts information
14
Other sources of labour market information
15
Unstructured data
16
A snapshot on global labour markets
17
How to think about labour markets
18
The Beveridge curve: Country examples
19
What explains labour market mismatch?
20
Alternative matching theories...
21
...and implications for employment dynamics
22
Extensions of the Beveridge curve
Labour market concepts and theories
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List of slides
Understanding labour market dynamics
List of slides II 23
The Beveridge curve with endogenous search
24
The Beveridge curve with monopsonistic competition
25
Beveridge curve: Endogenous job destruction
26
Labour market duality
27
Rise in the skill premium
28
Rise in the supply of college graduates
29
Theories on wages
30
Why do wages not adjust during downturns?
31
When wages fall too much: The reserve army eect
32
Household income and labour supply decisions
33
Skills and education
34
Skill premia in historical perspective
35
Returns to schooling across the world
36
Skills and economic development
37
Skill-biased technological change
38
Job polarization
39
Explaining job polarization
40
Macro-economic owchart
41
Okun's law I
42
Okun's law II
43
The Phillips curve I
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List of slides
Understanding labour market dynamics
List of slides III 44
The Phillips curve II: Demand shock
45
The Phillips curve III: The NAIRU
46
The Phillips curve IV: Rational expectations
47
Linking Beveridge and Phillips curves
48
Growth and unemplomyent: Overview
49
Growth and unemployment: The capitalization eect I
50
Growth and unemployment: The capitalization eect II
51
Growth and unemployment: Endogenous tenure
52
Growth and unemployment: Creative job destruction
53
Informality and business cycles
54
Why are networks important to understand?
55
Why are networks important to understand?
56
Labour market networks and information
57
Shock transmission in networks I
58
Shock transmission in networks II
59
How do networks evolve?
60
How do expectations aect labour markets?
61
Asset prices, investment and unemployment
62
Overview of empirical methodologies
63
A selection tree for growth analysis
64
Where are barriers for labour markets?
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List of slides
Understanding labour market dynamics
List of slides IV 65
Linking macro- and labour-analysis I
66
Linking macro- and labour-analysis II
68
Overview: Labour market policies and institutions
69
International labour standards
70
Employment protection legislation: Elements
71
Employment protection legislation: Evolution
72
Employment protection legislation: Mechanisms
73
Employment protection legislation: Issues
74
Minimum wages: International comparison
75
Minimum wages: Standard case
76
Minimum wages: Monopsonistic competition I
77
Minimum wages: Monopsonistic competition II
78
Minimum wages: Monopsonistic competition III
79
Public employment around the world
80
Trade unions: Monopoly unions
81
Trade unions: Ecient bargaining
82
Segmented labour markets
83
Labour market segmentation with rigid wages
84
Trade unions and an (informal) minimum wage
85
Minimum wage in the monopsonistic formal sector
Labour market policies and institutions
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List of slides
Understanding labour market dynamics
List of slides V Wages and employment 87
Overview: Wage dynamics
88
Theories on wages
89
Why do wages not adjust during downturns?
90
Exploring wages and trends
91
What explains slow wage growth?
92
Fall in bargaining power I: Trade unionization
93
Fall in bargaining power II: Bargaining coverage
94
Fall in bargaining power III: Public sector wages
95
Demographic decomposition of wages
96
Should wages have been growing faster?
97
How to measure labour market slack
98
An activity indicator
99
Inactivity versus unemployment: USA
100 Inactivity versus unemployment: France 101 Wage growth: Unemployment vs. total hours
Labour market ows
103 Overview: Understanding labour market dynamics 104 Labour market ows I 105 Labour market ows II 106 Labour market ows III
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List of slides
Understanding labour market dynamics
List of slides VI 107 Measuring unemployment ows I 108 Measuring unemployment ows II 109 Measuring unemployment ows III: Examples 110 Measuring unemployment ows IV: More examples 111 Measuring labour market mobility I 112 Measuring labour market mobility II 113 Measuring labour market mobility III 114 Measuring labour market mobility IV 115 The term structure of unemployment 116 The term structure of unemployment: France 117 Job tenure and job-to-job transitions 118 Gross unemployment risk 119 Gross unemployment risk: Germany vs United States 120 What aects unemployment ows? - Outows 121 What aects unemployment ows? - Inows 122 Labour ows and Okun's law I 123 Labour ows and Okun's law II 124 Labour ows and Okun's law III 125 Labour ows and Okun's law IV 126 Determinants of outow elasticities 127 Determinants of inow elasticities
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List of slides
Understanding labour market dynamics
List of slides VII 128 Alternative measures of uncertainty 129 Stochastic labour demand I 130 Stochastic labour demand II 131 Stochastic labour demand III 132 Stochastic labour demand IV 133 Hiring uncertainty: Example USA 134 Labour market outcomes under hiring uncertainty 135 Financial stress, hiring uncertainty and job creation 136 The New-Keynesian Phillips curve 137 An overview of the model ows I 138 An overview of the model ows II 139 Putting the pieces together 140 Modelling methodology I 141 Modelling methodology II 142 A double (hybrid) Phillips curve 143 A word on the data and methodology 144 Estimation results: Labour block 145 Estimation results: Macro block 146 Estimation results: Fiscal block 147 Long-term vs. short-term eects: Job creation 148 Long-term vs. short-term eects: Job destruction
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List of slides
Understanding labour market dynamics
List of slides VIII 149 Exit scenarios from the crisis: Government decit 150 Exit scenarios from the crisis: Job growth 151 Trade and informal employment 152 Trade and informal employment: Determinants 153 Remittances and labour markets I 154 Remittances and labour markets II 155 Remittances and labour markets III 156 Capital/income ows and labour markets
Group-work: Country study
158 Going forward: Exercise this week 159 A checklist for the country scan
Annex
161 Some useful labour market concepts I 162 Some useful labour market concepts II 163 Many workers and rms 164 When employers are in charge 165 When employers are in charge: Welfare loss 166 When employers are in charge: A minimum wage 167 Bibliography
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