1. Knowledge spillover from
multinational firms:
Channel of labor mobility
Avichai Chasid
Under the supervision of Prof. Saul Lach
December 2015
The Hebrew University of Jerusalem
2. Outline
• Motivation
• Research question
• Literature
• Data
• Empirical Work
• Preliminary findings
Avichai Chasid - HUJI2 December 15
3. Motivation
• Israel known as “Startup Nation”:
The Hi-Tech takes relatively large share of the economy (17% of privet sector GDP).
The highest R&D/GDP ratio (4.5%) in the world.
• During the last decade - massive entry of multinational foreign firms:
Establishing new R&D center (Green field).
Acquired/merged local startups or R&D firms.
• For continuation of the R&D activities.
• Only for IP (Intelligence-Properties) acquisition, so the firm is closed.
• The main focus of MNE is – producing inventions and new knowledge
(not specific product), and transferring them to parent company (global
MNE).
Avichai Chasid - HUJI3 December 15
4. Share of MNEs in the Israeli Hi-tech sector: 2009
• High productivity (output per employee) of the foreign firm in the Israeli
hi-tech.
December 15Avichai Chasid - HUJI4
In
(Foreign owend firms)
Out
(Large local firms)
Hi-tech
Manufacturing
30%59%Employment
42%61%Output
In
(Foreign owend firms)
Out
(Large local firms)
Software & RD
(72-73)
33%23%Employment
54%25%Output
5. R&D expenditures by ownership
• Growth in R&D expenditures of foreign owned firms
• Stagnation in R&D expenditures of Local firms
Avichai Chasid - HUJI5 December 15
Foreign RD centersForeign – Total
Foreign
Local
Local
6. December 15Avichai Chasid - HUJI6
Source: OECD, Gross domestic expenditure on R&D of foreign affiliates,
CBS, globalization survey.
7.4
21
63.3
0 10 20 30 40 50 60 70
Korea
Russian Federation
Turkey
Portugal
Slovenia
Mexico
Poland
Spain
Romania
Finland
Estonia
France
Belgium
Singapore
Denmark
Italy
Norway
Czech Republic
Sweden
Hungary
Slovak Republic
Austria
United Kingdom
Israel
Multinational foreign firms in the Israeli Hi-Tech
Share of foreign firms in R&D expenditures - 2009
7. Multinational foreign firms in the Israeli Hi-Tech
• Wage gaps in 2009 :
yearly wage per R&D employee ($)
Avichai Chasid - HUJI7 December 15
DifferenceIn
(Foreign owend firms)
Out
(Large local firms)Branch
22%82,36567,264
Hitech
Manufacturing
23%103,44084,306Software
(72)
17%114,64197,661R&D
(73)
8. Research question
• The big question:
What is the effect of multinational foreign firms
on the local Hi-Tech activity?
• My question try to open the black box of potential labor mobility spillover
channel, More specific:
Is productivity of local firm increased when hiring
workers with previous experience from MNEs?
The findings will help us understand:
Is the knowledge of foreign firms spillover despite the strong protection on IP?
Avichai Chasid - HUJI8 December 15
9. Literature
• Knowledge as public good with positive externalities. Arrow, 1962; Romer,
1990.
• FDI - Forign Direct Investment: Why companies invest globally? Helpman,
1984; ..
• Spillover of knowledge between firms – part of production function.
Griliches, 1979; Coe & Helpman, 1995.
• Spillover in worker mobility channel:
Theory: Caves, 1999; Fosfuri et al, 2001.
Empirical: Gorg & strobel, 2005; Balsvik, 2011; Poole, 2013.
• Spinoff and entry - empirical:
Klepper & Sleeper, 2005; Muendler et al, 2012.
Avichai Chasid - HUJI9 December 15
10. Data
• Employer-employee database from National Insurance Institute
8~ million observations over 12 years (2000-2011)
Hi-Tech, Med-Tech, Hi-tech services & Academy
• Panel data of firms and workers:
Firm specific: Employer, Economic branch
Worker specific: Month of work, Salaries, Age, Gender, Children
• Additional Data on firms:
R&D centers (IVC)
MNEs (manual)
Exit : Mergers/acquiation/IPO (IVC)
Avichai Chasid - HUJI10 December 15
11. Data
• Using data manipulation we achieved important variables:
Labor mobility between employers
Changes in wages
Size of firms
Opening/closures firms
Avichai Chasid - HUJI11 December 15
12. Mobility from MNE to Local - wage change
• 9,236 high salaries workers (25K+ NIS) moved from foreign to Local
• 2,033 of them move to small companies (marked)
December 15Avichai Chasid - HUJI12
to
local foreign
Local 1-
4
Local 5-
19
Local 20-
99
Local
100-249
Local
250-499
Local
500+
Local
100M+
Foreign
1-249
Foreign
250+
RD
Center
Green 1-
249
RD
Center
Green
250+
RD
Center 1-
249
RD
Center
250+
from
local
Local 1-4 -17% 29% 36% 67% -9% 12% 94% 67% 94% 32% 104% 0% 9%
Local 5-19 -38% -6% -3% 1% 6% -18% 6% 28% 28% -2% 18% -1% 22%
Local 20-99 -45% -14% -5% -4% -13% -22% 0% 7% -17% 0% 12% -5% -2%
Local 100-249 -66% -25% -19% -8% -50% -9% -7% 14% 12% 18% 15% -3% 2%
Local 250-499 -51% -18% -13% 123% -9% -25% -5% 8% -29% 8% -6% -1% -4%
Local 500+ -47% 8% -3% -10% -39% -17% -4% 19% 58% 32% 109% 17% 23%
Local 100M+ -64% -41% -11% -27% -10% -17% -16% -5% 12% 20% 11% 2% 11%
foreign
Foreign 1-249 -64% -25% -61% -28% -22% -68% -1% 5% -5% 10% -20% 8% -17%
Foreign 250+ -81% -40% -34% -40% 46% -63% -63% 16% -32% -36% -18% 34% -33%
RD Center Green 1-249 -69% -44% -24% -11% -31% -46% -23% -12% -61% -31% 11% -30% -4%
RD Center Green 250+ -87% -50% -33% -56% 2% -60% -47% 23% 8% 0% 1% -20% -17%
RD Center 1-249 -49% -24% -27% -25% -23% -36% -22% -18% -10% -27% -14% -18% -3%
RD Center 250+ -76% -50% -38% -35% -32% -51% -23% -50% -17% -14% -10% -32% -35%
13. Local firms - hired from MNEs
December 15Avichai Chasid - HUJI13
• Size in the first year the company hired high-salary (25K+) worker.
Hired from
Local only
Hired from
ForeignSize (workers)
1,0907361-4
3704315-9
61489110-49
28150850+
2,3352,566Total
14. Empirical work
• Compare outcomes between firms that hired from MNEs to “similar”
companies that didn’t hired such type of workers:
Treatment group: Firms that hired high-salary workers from foreign MNEs.
Control group: firms that hired high-salary workers from local MNEs.
Additional controls: year, branch, firm size, salaries level
• Outcomes (available success indicators in the data):
Number of employers, Level of wages, Merge/IPO, Survival.
• Not pure identification strategy :
Selection problem: not random assignment - the worker examines the startup ideas and
choose the better one.
But, not crucial:
1. The characteristics of treatment & control groups are close.
2. The best possible way to research such an interesting phenomena.
Avichai Chasid - HUJI14 December 15
15. Mobility from MNE to Local
December 15Avichai Chasid - HUJI15
to
local foreign
Local 1-
4
Local 5-
19
Local 20-
99
Local
100-249
Local
250-499
Local
500+
Local
100M+
Foreign
1-249
Foreign
250+
RD
Center
Green 1-
249
RD
Center
Green
250+
RD
Center 1-
249
RD
Center
250+
from
local
Local 1-4 -17% 29% 36% 67% -9% 12% 94% 67% 94% 32% 104% 0% 9%
Local 5-19 -38% -6% -3% 1% 6% -18% 6% 28% 28% -2% 18% -1% 22%
Local 20-99 -45% -14% -5% -4% -13% -22% 0% 7% -17% 0% 12% -5% -2%
Local 100-249 -66% -25% -19% -8% -50% -9% -7% 14% 12% 18% 15% -3% 2%
Local 250-499 -51% -18% -13% 123% -9% -25% -5% 8% -29% 8% -6% -1% -4%
Local 500+ -47% 8% -3% -10% -39% -17% -4% 19% 58% 32% 109% 17% 23%
Local 100M+ -64% -41% -11% -27% -10% -17% -16% -5% 12% 20% 11% 2% 11%
foreign
Foreign 1-249 -64% -25% -61% -28% -22% -68% -1% 5% -5% 10% -20% 8% -17%
Foreign 250+ -81% -40% -34% -40% 46% -63% -63% 16% -32% -36% -18% 34% -33%
RD Center Green 1-249 -69% -44% -24% -11% -31% -46% -23% -12% -61% -31% 11% -30% -4%
RD Center Green 250+ -87% -50% -33% -56% 2% -60% -47% 23% 8% 0% 1% -20% -17%
RD Center 1-249 -49% -24% -27% -25% -23% -36% -22% -18% -10% -27% -14% -18% -3%
RD Center 250+ -76% -50% -38% -35% -32% -51% -23% -50% -17% -14% -10% -32% -35%
treatment
control
Treatment: 2,000~ workers 1,000~ firms
Control : 1,700~ workers 1,500~ firms
16. Difference in Differnce:
The effect of labor mobility from multinational firms
December 15Avichai Chasid - HUJI16
ATE2= (Tafter- Tbefore) - (Cafter- Cbefore)
17. Preliminary finding:
The effect of labor mobility from multinational firms
December 15Avichai Chasid - HUJI17
Size in
first year
(workers)
Hired
workers
from
Number
of firms
employees wage
Survival
rate
Avg.
workers
before
Avg.
workers
after
Growth
rate
Avg.
wage
before
Avg.
wage
after
Growth
rate
1-4
Foreign 736 2 6 181% 17,325 18,340 6% 76%
Local only 1,090 2 4 88% 16,716 14,908 -11% 73%
Difference 93% 17% 3%
5-9
Foreign 431 7 19 183% 17,859 19,523 9% 76%
Local only 370 7 11 69% 13,951 13,842 -1% 72%
Difference 114% 10% 4%
18. ?DDD – why to match in growth rate
December 15Avichai Chasid - HUJI18
• Maybe the control firm already has a product and don’t expect to growth.
ATE2= (Tafter- Tbefore) - (Cafter- Cbefore)
19. ?DDD – why to match in growth rate
• Same types of firms
December 15Avichai Chasid - HUJI19
ATE3 = (ΔTafter- ΔTbefore) - (ΔCafter- ΔCbefore)
זליגת ידע – ספרות כלכלית נרחבת שמתארת את התופעה של זליגת ידע בין פירמות. אנו טוענים כי בפונקציית הייצור של הפירמה ישנם מרכיבים אותם היא קובעת כמו עובדים , הון, מחקר ופיתוח וישנם מרכיבים שהיא נהנת מהם בגלל שהם בעלי תועלת חיצונית חיובית כמו מאגר הידע שפירמות אחרות השקיעו בו. זליגת הידע מתרחשת בערוצים רבים – שיתוף מידע בין עובדים, פרוייקטים משותפים לפירמות שונות, מעבר של עובד, הנדסה לאחור ועוד. הספרות האמפירית שחוקרת את התופעה מצאה עדויות מוצקות לקיומה של זליגת ידע, אך השיטה המקובלת היא אומדן כללי של תוספת מכירות/תוצר של פירמה אחת כתוצאה מתוספת מו"פ של פירמה שכנה. לא נעשו הרבה עבודות שניסו לפתוח את הקופסה השחורה של ערוצי הזליגה ולנסות לבחון איך הם מתרחשים ובאיזו עוצמה.
בהקשר של העבודה שלי אני מעוניין להראות כי לנוכחות של חברות זרות ישנה השפעה חיובית על השוק המקומי שכן עובדים שמתחילים את דרכם בפירמות הרב-לאומיות רוכשים יכולות כלים ואף קשרים בתחומי הידע הרלוונטיים וכאשר הם עוזבים את החברה בה עבדו הם לוקחים איתם רבים מכלים אלו ומועילילם לפירמות שהם מצטרפים אליהם או מקימים בעצמם.
