This document discusses shifts in the Beveridge curve since the 2007 recession. It begins by providing background on the Beveridge curve and how it has shifted outward since 2007, with unemployment falling more slowly as job openings rose. Previous explanations for this shift, like skills mismatches or extended unemployment benefits, are deemed insufficient. The document then presents an economic model of the labor market to derive an expression for the Beveridge curve. It suggests a rise in policy uncertainty may help explain the curve's outward shift since 2007.
這是BILL在第四屆簡球會「為自己出征」所分享的簡報!
首先BILL分享了TED及Slide Share這兩個平台,
說明視覺劃時代的來臨,
接著和觀眾分享簡報設計的「三個禮物」,
分別是表達視覺化、訊息圖像化、選色系統化
最後鼓勵大家:"To start, you don't have to be good; to be good, you have to start!"只要開始練習與揣摩,可以學會簡報的視覺設計!
這是BILL在第四屆簡球會「為自己出征」所分享的簡報!
首先BILL分享了TED及Slide Share這兩個平台,
說明視覺劃時代的來臨,
接著和觀眾分享簡報設計的「三個禮物」,
分別是表達視覺化、訊息圖像化、選色系統化
最後鼓勵大家:"To start, you don't have to be good; to be good, you have to start!"只要開始練習與揣摩,可以學會簡報的視覺設計!
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Uncertainty and the slow labor market recovery
1. Uncertainty
and the Slow Labor
Market Recovery
Yi-Hung Peng, Tou-Te Tsai, Yu-Chieh Chiang
2013.11.1
2. Reporting Process
1
The Beveridge curve: Past and present
2
Measuring shifts in the Beveridge curve
3
Effects of policy uncertainty on shifts in the Beveridge curve
4
Conclusion
3
4. The Beveridge curve: Past and present
The history of Beveridge curve
The Beveridge curve, or UV-curve, was developed in 1958 by
Christopher Dow and Leslie Arthur Dicks-Mireaux.
The Beveridge curve enabled economists to employ an
analytical method for the decomposition of unemployment:
deficient-demand (or cyclical) unemployment
and structural unemployment.
5
5. The Beveridge curve: Past and present
Likely because the Beveridgecurve enabled economists to
analyze the problems Beveridge
addressed,
the curve was named in the
1980s after William Beveridge.
6
6. al
y
t is
yed
his
nt
nty
me
e
Figure 1
Figure 1: Actual and fitted Beveridge
Actual and fitted Beveridge curve
curve
Job openings rate (%)
5
Fitted
4
3
Since 2007
recession
Before 2007
recession
2
1
3
5
7
Unemployment rate (%)
9
Sources: Job Openings and Labor Turnover Survey (JOLTS), Daly et al.
11
7
7. Actual and fitted Beveridge curve
Job openings rate (%)
5
Fitted
4
3
Since 2007
recession
Before 2007
recession
2
1
3
5
7
Unemployment rate (%)
9
Sources: Job Openings and Labor Turnover Survey (JOLTS), Daly et al.
11
8
8. Actual and fitted Beveridge curve
Job openings rate (%)
5
v
Fitted
4
3
Since 2007
recession
Before 2007
recession
2
1
3
5
7
Unemployment rate (%)
9
Sources: Job Openings and Labor Turnover Survey (JOLTS), Daly et al.
11
8
9. Actual and fitted Beveridge curve
Job openings rate (%)
5
v
Fitted
4
3
Since 2007
recession
Before 2007
recession
2
1
3
5
7
Unemployment rate (%)
9
u
Sources: Job Openings and Labor Turnover Survey (JOLTS), Daly et al.
11
8
10. Actual and fitted Beveridge curve
Job openings rate (%)
5
v
Fitted Beveridge curve
4
3
Since 2007
recession
Before 2007
recession
2
1
3
5
7
Unemployment rate (%)
9
u
Sources: Job Openings and Labor Turnover Survey (JOLTS), Daly et al.
11
8
11. Actual and fitted Beveridge curve
Job openings rate (%)
5
v
Fitted Beveridge curve
4
Data
3
Since 2007
recession
Before 2007
recession
2
1
3
5
7
Unemployment rate (%)
9
u
Sources: Job Openings and Labor Turnover Survey (JOLTS), Daly et al.
11
8
14. Figure 1
Actual and fitted Beveridge curve
Job openings rate (%)
5
Fitted
Since late 2007, the Beveridge
curve has gradually shifted outward
4
3
Since 2007
recession
Before 2007
recession
2
1
3
5
7
Unemployment rate (%)
9
11
11
15. Job openings rate (%)
5
Fitted
Since late 2007, the Beveridge
curve has gradually shifted outward
4
3
Since 2007
recession
Before 2007
recession
2
What has caused this shift
1
3
5
7
Unemployment rate (%)
9
11
12
16. The Beveridge curve: Past and present
What has caused this shift Previous Explanation
13
17. The Beveridge curve: Past and present
What has caused this shift Previous Explanation
1
“Beveridge curve may reflect a mismatch between the
skills unemployed workers have and what employers
are looking for.”
13
18. The Beveridge curve: Past and present
What has caused this shift Previous Explanation
1
“Beveridge curve may reflect a mismatch between the
skills unemployed workers have and what employers
are looking for.”
Recent research suggests that skill mismatch is
probably not a main driving force
13
19. The Beveridge curve: Past and present
What has caused this shift Previous Explanation
1
“Beveridge curve may reflect a mismatch between the
skills unemployed workers have and what employers
are looking for.”
Recent research suggests that skill mismatch is
probably not a main driving force
2
“The expansion of unemployment insurance benefits”
EX:the 2008 extension of unemployment compensation.
13
20. The Beveridge curve: Past and present
What has caused this shift Previous Explanation
1
“Beveridge curve may reflect a mismatch between the
skills unemployed workers have and what employers
are looking for.”
Recent research suggests that skill mismatch is
probably not a main driving force
2
“The expansion of unemployment insurance benefits”
EX:the 2008 extension of unemployment compensation.
Unemployment insurance benefits have been
reduced over the past two years.
13
21. The Beveridge curve: Past and present
1
“Beveridge curve may reflect a mismatch between the
skills unemployed workers have and what employers
are looking for.”
2
“The expansion of unemployment insurance benefits”
EX:the 2008 extension of unemployment compensation.
Policy Uncertainty
14
23. Measuring shifts in the Beveridge curve
A rise in the level of uncertainty about fiscal and monetary
policy is a third possible explanation for the shift in the
Beveridge curve.
16
24. Measuring shifts in the Beveridge curve
A rise in the level of uncertainty about fiscal and monetary
policy is a third possible explanation for the shift in the
Beveridge curve.
“
”
We need an economic model of the labor market.
16
26. Measuring shifts in the Beveridge curve
!! = ! !! !!
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!
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t
!=
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!!
−
!
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!
!
17
27. Measuring shifts in the Beveridge curve
!! = ! !! !!
!
!! !!
!!!
!
! m denotes new matches (hires) being formed
t
unemployment (u)
!=
!
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!
!!
−
!
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!
!
17
28. Measuring shifts in the Beveridge curve
!! = ! !! !!
!
!! !!
!!!
!
! m denotes new matches (hires) being formed
t
unemployment (u)
!
Ω!!!
job vacancy rate (v)
!=
!
!!
−
!
!!! !!!
!
!
17
29. Measuring shifts in the Beveridge curve
!! = ! !! !!
!
!! !!
!!!
!
! m denotes new matches (hires) being formed
t
unemployment (u)
!
!
μ is= Ω!!! capturing (true) match!!! !!! !
a scale parameter ! !! − ! efficiency
!
job vacancy rate (v)
17
30. Measuring shifts in the Beveridge curve
!! = ! !! !!
!
!! !!
!!!
!
! m denotes new matches (hires) being formed
t
unemployment (u)
!
!
μ is= Ω!!! capturing (true) match!!! !!! !
a scale parameter ! !! − ! efficiency
!
job vacancy rate (v)
at denotes firms’ recruiting intensity (for example, advertising)
17
31. Measuring shifts in the Beveridge curve
!! = ! !! !!
!
!! !!
!!!
!
! m denotes new matches (hires) being formed
t
unemployment (u)
!
!
μ is= Ω!!! capturing (true) match!!! !!! !
a scale parameter ! !! − ! efficiency
!
job vacancy rate (v)
at denotes firms’ recruiting intensity (for example, advertising)
st denotes the search intensity of unemployed workers
17
32. Measuring shifts in the Beveridge curve
!! = ! !! !!
!
!! !!
!!!
!
! m denotes new matches (hires) being formed
t
unemployment (u)
!
!
μ is= Ω!!! capturing (true) match!!! !!! !
a scale parameter ! !! − ! efficiency
!
job vacancy rate (v)
(variables for the beveridge curve shifter)
at denotes firms’ recruiting intensity (for example, advertising)
st denotes the search intensity of unemployed workers
17
33. mple, advertising).
Measuring shifts in the Beveridge curve
Imposing the steady-state relation:
hat
where deno
he Beveridge curve
mt denotes new matches (hires) being formed
unemployment (u)
18
34. mple, advertising).
Measuring shifts in the Beveridge curve
Imposing the steady-state relation:
hat
where deno
he Beveridge curve
δ denotes the job separation rate
mt denotes new matches (hires) being formed
unemployment (u)
18
35. ensity (for example, advertising).
Measuring shifts in the Beveridge curve
-state relation that
where denotes
xpression for the Beveridge curve
!
!!!
!! = ! !! !! !! !!
!
!
1−α
a
).
!=
!
Ω!!!
!
!!
−
!
!!! !!!
!
!
uced-form representation of all factors that can shift
19
36. ensity (for example, advertising).
Measuring shifts in the Beveridge curve
-state relation that
where denotes
xpression for the Beveridge curve
!
!!!
!! = ! !! !! !! !!
!
!
1−α
a
).
!=
!
Ω!!!
!
!!
−
!
!!! !!!
!
!
uced-form representation of all factors that can shift
19
37. ensity (for example, advertising).
Measuring shifts in the Beveridge curve
-state relation that
where denotes
xpression for the Beveridge curve
!
!!!
!! =! ! !! ! ! !! !! !!! !
! !!
!
!
! =
!
!
1−α
a
).
!
!
! !
! !
The expression for the Beveridge curve
!
!
!=
!=
Ω!!!
!
Ω!!!
!
!
!!
!!
−
!!! !!!
!
!
!
−
!!! !!!
!
!
uced-form representation of all factors that can shift
19
38. ensity (for example, advertising).
Measuring shifts in the Beveridge curve
-state relation that
where denotes
xpression for the Beveridge curve
!
!!!
!! =! ! !! ! ! !! !! !!! !
! !!
!
!
! =
!
!
1−α
a
).
!
!
! !
! !
The expression for the Beveridge curve
!
!
!=
!=
Ω!!!
!
Ω!!!
!
!
!!
!!
−
!!! !!!
!
!
!
−
!!! !!!
!
!
uced-form representation of all factors that can shift
19
39. ensity (for example, advertising).
Measuring shifts in the Beveridge curve
-state relation that
where denotes
xpression for the Beveridge curve
!
!!!
!! =! ! !! ! ! !! !! !!! !
! !!
!
!
! =
!
!
1−α
a
).
!
!
! !
! !
The expression for the Beveridge curve
!
!
!=
!=
Ω!!!
!
Ω!!!
!
!
!!
!!
−
!!! !!!
!
!
!
−
!!! !!!
!
!
uced-form representation of all factors that can shift
19
40. ensity (for example, advertising).
Measuring shifts in the Beveridge curve
-state relation that
where denotes
xpression for the Beveridge curve
!
!!!
!! =! ! !! ! ! !! !! !!! !
! !!
!
!
! =
!
!
1−α
a
).
!
!
! !
! !
The expression for the Beveridge curve
!
!
!=
!=
Ω!!!
!
Ω!!!
!
!
!!
!!
−
!!! !!!
!
!
!
−
!!! !!!
!
!
uced-form representation of all factors that can shift
19
41. ensity (for example, advertising).
(1)
Measuring shifts in the Beveridge curve
where mt denotes new matches (hires) being formed,
-state relation that
denotes
match efficiency, st denotes the whereintensity of un
search
xpressionfirms’the Beveridge curveexample, advertising)
for recruiting intensity (for
!
!!!
!! =! ! !! ! ! !! !! !!! !
! !!
!
!
!! =
!! !
! !
Imposing the steady-state relation that
!
1−α
a
).
!rate, The expression forexpression for the Beveridge curv
we obtain the the Beveridge curve!
!
!=
!=
(2)
Ω!!!
!
Ω!!!
!
!
!!
!!
−
!!! !!!
!
!
!
−
!!! !!!
!
!
( of all. factors curve shifter shift
) Beveridge that can
uced-form representation
α 1−α
where Ω ≡ δ / µ s a
19
42. (2)
Measuring shifts in the Beveridge curve
(
α 1−α
where Ω ≡ δ / µ s a
).
The term is a reduced-form repre
δ denotes the job separation rate
μ a scale
Weis callparameter capturing (true) match efficiency
the “Beveridge curve sh
a denotes firms’ recruiting intensity (for example, advertising)
Beveridge curve. unemployed workers
s denotes the search intensity of
t
t
20
43. (2)
Measuring shifts in the Beveridge curve
(
α 1−α
where Ω ≡ δ / µ s a
).
Ω is the “Beveridge curve shifter”, the reduced-form
representation of all factors that can shift the Beveridge curve
The term is a reduced-form repre
δ denotes the job separation rate
μ a scale
Weis callparameter capturing (true) match efficiency
the “Beveridge curve sh
a denotes firms’ recruiting intensity (for example, advertising)
Beveridge curve. unemployed workers
s denotes the search intensity of
t
t
20
44. (2)
Measuring shifts in the Beveridge curve
(
α 1−α
where Ω ≡ δ / µ s a
).
Ω is the “Beveridge curve shifter”, the reduced-form
representation of all factors that can shift the Beveridge curve
Increased Ω leads to an outward shift in the curve.
The term is a reduced-form repre
δ denotes the job separation rate
μ a scale
Weis callparameter capturing (true) match efficiency
the “Beveridge curve sh
a denotes firms’ recruiting intensity (for example, advertising)
Beveridge curve. unemployed workers
s denotes the search intensity of
t
t
20
45. al
y
t is
yed
his
nt
nty
me
e
Figure 1
Figure 1: Actual and fitted Beveridge
Actual and fitted Beveridge curve
curve
Job openings rate (%)
5
Fitted
4
3
Since 2007
recession
Before 2007
recession
2
1
3
5
7
Unemployment rate (%)
9
Sources: Job Openings and Labor Turnover Survey (JOLTS), Daly et al.
11
21
46. Imposing the steady-state relation tha
rate, we obtain the expression for the
(2)
Since 200
recessio
Beveridge curve shifter:
Original State
(
α 1−α
where Ω ≡ δ / µ s a
).
The term is a reduced-form repres
We call the “Beveridge curve shift
Beveridge curve.
We construct a time series for usin
Beveridge curve relation in equation
job separation rate is taken from th
the U.S. Bureau of Labor Statistics.
22
47. Imposing the steady-state relation tha
rate, we obtain the expression for the
(2)
Beveridge curve shifter:
Increase Ω→Outward shift
(
α 1−α
where Ω ≡ δ / µ s a
).
Since 2
recess
The term is a reduced-form repres
We call the “Beveridge curve shift
Beveridge curve.
We construct a time series for usin
Beveridge curve relation in equation
job separation rate is taken from th
the U.S. Bureau of Labor Statistics.
23
48. (2)
(
α 1−α
where Ω ≡ δ / µ s a
).
Increased Ω leads to an
outward shift in the curve.
The term is a reduced-form representat
We call the “Beveridge Since 2007
curve shifter.”
recession
Beveridge curve.
We construct a time series for using da
Beveridge curve relation in equation (2),
job separation rate is taken from the 24
Job
50. Measuring shifts in the Beveridge curve
Policy Uncertainty
Newspaper articles discussing economic policy uncertainty
25
51. Measuring shifts in the Beveridge curve
Policy Uncertainty
Newspaper articles discussing economic policy uncertainty
Tax code provisions scheduled to expire
25
52. Measuring shifts in the Beveridge curve
Policy Uncertainty
Newspaper articles discussing economic policy uncertainty
Tax code provisions scheduled to expire
The extent of disagreements among economic forecasters
about such variables as future levels of inflation and
government spending
25
53. ve
s
on
he
Figure 2
Figure 2: Beveridge curve shifter and policy uncertainty
Beveridge curve shifter and policy uncertainty
Index
3.0
2.5
Percent
7.0
Recruiting intensity
(left axis)
6.5
6.0
2.0
1.5
5.5
Policy uncertainty
(left axis)
5.0
4.5
1.0
0.5
Beveridge curve shifter
(right axis)
0.0
00 01 02 03 04 05 06
Note: Three-month moving average.
4.0
3.5
3.0
07
08
09
10
11
12
26
54. 2.5
2.0
and the job vacancy rate (v), can be derived from a general matc
Recruiting intensity
following form(left axis)
(see Pissarides 2000, chapter 5):
6.5
6.0
(1)
5.5
where mt denotes uncertainty (hires) being formed, µ is a scale
Policy new matches
5.0
1.5 match efficiency, s denotes the search intensity of unemployed
(left axis)
t
firms’ recruiting intensity (for example, advertising).
4.5
1.0
4.0
Beveridge curve shifter
relation that (right axis)
where
3.5
0.5 Imposing
the steady-state
rate, we obtain the expression for the Beveridge curve
0.0
3.0
00 01 02 03 04 05 06
(2)
Note: Three-month moving average.
07
08
09
10
11
12
Beveridge curve shifter
(
α 1−α
)
where Ω ≡ δ / µ s a
.
to a higher unemployment rate for a given number of job
27
d
55. efficiency is a broad concept that encompasses a range of variables,
from filling vacancies, thereby raising unemployment. An estimate indicates that, without policy
ecruit new employees. If the process of matching workers and jobs
uncertainty, the unemployment rate in late 2012 would have been close to 6.5%, 1.3
curve shifts to the right, meaning that, for a given job vacancy rate,
percentage points lower than the actual rate.
her.
Measuring shifts in the Beveridge curve
loyment rate and the vacancy rate to quantify changes in job match
The U.S. labor market has recovered more slowly following the Great Recession than after previous
t we call the “Beveridge curve shifter.” In Figure 2, the blue line
recessions. Historically, the unemployment rate tends to fall as job openings increase, a relationship
Beveridge curve shifter has increased substantially, consistent with
urve displayed in Figure 1.represented graphically by the Beveridge curve. However, even though the number of job openings in the
economy has been rising during the recovery, the unemployment rate has remained stubbornly high. As
onomic policy uncertaintya result, asby Baker, Bloom, and Davis
developed Figure 1 shows, the Beveridge curve has shifted away from its historical pattern. There are
now more jobless workers for a given number of job openings than in the decade before the downturn.
lume of newspaper articles discussing economic policy uncertainty,
heduled to expire, and the extent of disagreements among economic
Researchers have suggested several
Figure 1
Figure 2
reasons for this shift. Workers may
Actual and fitted Beveridge curve
Beveridge curve shifter and policy uncertainty what is
not have the skills that match
Index
Percent Job openings rate (%)
needed for current job openings. 7.0 5
3.0
Recruiting intensity
Alternatively, more generous
Fitted
(left axis)
6.5
2.5
unemployment benefits may have
n
4
6.0
reduced the pressure on unemployed
2.0
5.5
individuals to search for jobs. In this
Policy uncertainty
Economic Letter, we propose an 5.0 3
1.5
(left axis)
Since 2007
alternative explanation. We present
recession
4.5
1.0
evidence that heightened uncertainty
Before 2007
recession
about economic policy during the 4.0 2
Beveridge curve shifter
0.5
e
(right axis)
recovery made businesses more
3.5
reluctant to hire workers. When
0.0
3.0
1
businesses become
00 01 02 03 uncertainty rises,08 09 10 11 12
04 05 06 07
3
5
7
9
11
Unemployment rate (%)
Note: Three-month moving average.
more hesitant to hire. They reduce
Sources: Job Openings and Labor Turnover Survey (JOLTS), Daly et al.
recruiting efforts by raising hiring
(2012), and authors’ calculations.
ads to a higher unemployment rate for a given number of job
standards, increasing the number of
ge curve outward. The green dashed line in Figure 2 indicates that,
interviews, or simply not filling vacancies. For instance, some businesses may interview candidates
28
56. efficiency is a broad concept that encompasses a range of variables,
from filling vacancies, thereby raising unemployment. An estimate indicates that, without policy
ecruit new employees. If the process of matching workers and jobs
uncertainty, the unemployment rate in late 2012 would have been close to 6.5%, 1.3
curve shifts to the right, meaning that, for a given job vacancy rate,
percentage points lower than the actual rate.
her.
Measuring shifts in the Beveridge curve
loyment rate and the vacancy rate to quantify changes in job match
The U.S. labor market has recovered more slowly following the Great Recession than after previous
t we call the “Beveridge curve shifter.” In Figure 2, the blue line
recessions. Historically, the unemployment rate tends to fall as job openings increase, a relationship
Beveridge curve shifter has increased substantially, consistent with
urve displayed in Figure 1.represented graphically by the Beveridge curve. However, even though the number of job openings in the
economy has been rising during the recovery, the unemployment rate has remained stubbornly high. As
onomic policy uncertaintya result, asby Baker, Bloom, and Davis
developed Figure 1 shows, the Beveridge curve has shifted away from its historical pattern. There are
now more jobless workers for a given number of job openings than in the decade before the downturn.
lume of newspaper articles discussing economic policy uncertainty,
Policy Uncertainty & Beveridge curve shifter
heduled to expire, and the extent of disagreements among economic
Researchers have suggested several
Figure 1
Figure 2
reasons for this shift. Workers may
Actual and fitted Beveridge curve
Beveridge curve shifter and policy uncertainty what is
not have the skills that match
Index
Percent Job openings rate (%)
needed for current job openings. 7.0 5
3.0
Recruiting intensity
Alternatively, more generous
Fitted
(left axis)
6.5
2.5
unemployment benefits may have
n
4
6.0
reduced the pressure on unemployed
2.0
5.5
individuals to search for jobs. In this
Policy uncertainty
Economic Letter, we propose an 5.0 3
1.5
(left axis)
Since 2007
alternative explanation. We present
recession
4.5
1.0
evidence that heightened uncertainty
Before 2007
recession
about economic policy during the 4.0 2
Beveridge curve shifter
0.5
e
(right axis)
recovery made businesses more
3.5
reluctant to hire workers. When
0.0
3.0
1
businesses become
00 01 02 03 uncertainty rises,08 09 10 11 12
04 05 06 07
3
5
7
9
11
Unemployment rate (%)
Note: Three-month moving average.
more hesitant to hire. They reduce
Sources: Job Openings and Labor Turnover Survey (JOLTS), Daly et al.
recruiting efforts by raising hiring
(2012), and authors’ calculations.
ads to a higher unemployment rate for a given number of job
standards, increasing the number of
ge curve outward. The green dashed line in Figure 2 indicates that,
interviews, or simply not filling vacancies. For instance, some businesses may interview candidates
28
58. Effects of policy uncertainty on shifts in the Beveridge curve
“
How much heightened policy uncertainty may
have contributed to this shift?
”
V
U
Ω
Job vacancy rate
Unemployment rate
Beveridge curve shifter
Policy uncertainty
30
59. s of uncertainty on the unemployment rate in our theoretical model,
ge
cy
e
he
id
ly
n
ty
the
Figure 3
Figure 3: Policy uncertainty and shifts in the Beveridge
Policy uncertainty and shifts in the Beveridge curve
curve
Job openings rate (%)
5
Fitted
4
Since 2007 recession
implied by policy uncertainty
3
Since 2007
recession
Before 2007
recession
2
1
3
5
7
9
Unemployment rate (%)
Sources: JOLTS, Daly et al. (2012), and authors’ calculations.
11
31
60. 7
Part of the Beveridge curve
that has been driven by policy
uncertainty, based on
estimates we put into our
statistical model.
Since 2007 recession
implied by policy uncertainty
Since
rece
32
61. Part of the Beveridge curve
that has been driven by policy
uncertainty, based on
estimates we put into our
statistical model.
However, beginning in autumn
2009, policy uncertainty
became an increasingly
important factor behind the
shift in the Beveridge curve.
Since 2007 recession
implied by policy uncertainty
Since 2007
recession
33
62. Effects of policy uncertainty on shifts in the Beveridge curve
Heighted uncertainty may have contributed to the shift
Our results suggests that, in late 2012, if there had been no
policy uncertainty shocks, The unemployment rate would have
been close to 6.5% instead of the reported 7.8%.
34
63. Effects of policy uncertainty on shifts in the Beveridge curve
Conclusion
35
64. Effects of policy uncertainty on shifts in the Beveridge curve
Conclusion
All else equal
35
65. Effects of policy uncertainty on shifts in the Beveridge curve
Conclusion
All else equal
Increase in
policy
uncertainty
35
66. Effects of policy uncertainty on shifts in the Beveridge curve
Conclusion
All else equal
Increase in
policy
uncertainty
Significant
decline in
recruiting
intensity
35
68. Conclusion
In an uncertain economic environment, businesses reduce
their recruiting intensity.
As the economy recovers and uncertainty recedes, the
Beveridge curve should return to its pre-recession position and
the pace of job recovery should accelerate.
37