The Return to Knowledge of English in Non-English Speaking Country

We use a unique data set to examine the return to English knowledge. Our primary focus is on

Russian immigrants to Israel, but we study native Israelis as well. Understanding the role of English

in this setting is important for at least three reasons.

First, globalization and the ensuing growth in the importance of foreign language knowledge has

become an important theme in the popular press. The San Francisco Chronicle reports that families

seek nannies who speak a language other than English because “They want to give their children a

head start in business in 20 years.” (Helen Riley-Collins, president of Aunt Ann's In-House Staffing

in San Francisco, quoted in Hua, 2005). It is also commonly argued that the success of Canada, the

United States and other countries with large immigrant populations reflects, in part, access to world

markets fostered by the immigrant population’s knowledge of foreign languages and cultures

(Farooqui, 2005)

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th
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Dustmann, Christian and Arthur van Soest, “Language and the Earnings of Immigrants,” Industrial
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Farooqui, Noreen, “Immigrants Are Assets in the Global Economy,” Toronto Sun, July 6, 2005, C3.
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of Economics, 116 (4), 1373–1408.
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Industrial and Labor Relations Review,” 57 (2003): 128–140.
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2001): 65-78.
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Tutor Their Tots,” San Francisco Chronicle , November 28, 2005, B1.
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Assimilation and Distributional Effects,” American Economic Review, 81 (1991): 297-302.
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Earnings Differences,” American Economic Review, 75 (1985): 818–827.
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Years, 1970-1990,” Canadian Public Policy/Analyse de Politiques, 23 (1997): 115-140.
Tainer, E., “English Language Proficiency and the Determination of Earnings Among Foreign
Men,” Journal of Human Resources, 23 (1988): 108–121.
19
TABLE 1
Basic Data for Workplace Occupation Survey and Comparison with Income Survey
Income Survey WOS Survey 
(Russian Immigrants only) Immigrants Israelis
Age 39.4(11.8)
35.7
(10.3)
33.6
(10.3)
Years of education 13.7(3.1)
14.2
(2.9)
13.6
(3.1)
Labor force 
Experience 
19.8
(11.5)
15.5
(9.8)
13.9
(10.4)
Years since
Migration
5.4
(2.1)
5.2
(2.1) -
Currently married 0.80(0.40)
0.72
(0.45)
0.62
(0.49)
Male 0.61(.49)
0.56
(0.50)
0.59
(0.49)
Job Tenure - 3.17(2.03)
5.91
(6.27)
Current Hebrew - 2.41(0.68) *
Entry Hebrew - 1.60(0.72) *
Current English - 1.94(0.71)
2.47
(0.59)
Entry English - 1.66(0.66)
2.16
(0.66)
Monthly Earnings 3689(1700)
3861
(1900)
5280
(3283)
Unskilled Worker 12% 11% 14%
Skilled Worker 36% 39% 46%
Physicians/Nurses - 8% 10%
High-tech - 42% 30%
*Assumed to speak Hebrew very well. Coded 0 for natives.
- Not available.
20
TABLE 2
Basic Data for Workplace Occupation Survey by Occupation and Immigrant Status
Nurses & Doctors High-Tech Skilled Unskilled Nurses & Doctors High-Tech Skilled Unskilled
Immigrants Natives
Age 34.4
(7.7)
38.2
(10.3)
34.6
(10.5)
31.5
(9.6)
35.7
(8.6)
32.6
(9.6)
33.4
(10.7)
34.6
(11.2)
Years of
education
16.5
(2.1)
15.3
(2.5)
13.1
(2.8)
12.6
(2.3)
17.8
(2.1)
14.7
(2.4)
12.6
(2.8)
11.6
(2.3)
Experience 11.9
(7.4)
16.9
(9.7)
15.5
(10.1)
12.9
(9.58)
11.9
(8.1)
11.9
(8.9)
14.8
(11.0)
17.0
(11.8)
Years since
Migration
4.63
(1.99)
5.7
(1.9)
5.14
(2.24)
4.76
(1.81)
- - - -
Currently
Married
0.74
(0.44)
0.74
(0.44)
0.69
(0.46)
0.70
(0.46)
0.73
(0.45)
0.57
(0.50)
0.60
(0.49)
0.69
(0.46)
Male 0.41
(0.49)
0.52
(0.50)
0.60
(0.49)
0.69
(0.46)
0.43
(0.50)
0.57
(0.50)
0.62
(0.49)
0.66
(0.47)
Job Tenure 3.33
(2.12)
3.16
(2.00)
3.20
(2.15)
3.04
(1.73)
9.25
(7.44)
4.94
(5.95)
5.46
(5.32)
7.10
(7.82)
Current
Hebrew
2.59
(0.60)
2.40
(0.67)
2.37
(0.71)
2.45
(0.62)
- - - -
Entry
Hebrew 
1.72
(0.73)
1.66
(0.70)
1.59
(0.70)
1.35
(0.57)
- - - -
Current
English
1.86
(0.66)
2.01
(0.71)
1.91
(0.72)
1.79
(0.76)
2.79
(0.45)
2.61
(0.50)
2.38
(0.57)
2.21
(0.72)
Entry
English
1.50
(0.55)
1.70
(0.67)
1.65
(0.67)
1.61
(0.70)
2.44
(0.58)
2.22
(0.63)
2.13
(0.62)
1.93
(0.79)
Monthly
Earnings
4827
(2231)
4255
(2211)
3469
(1197)
3041
(1600)
7561
(3827)
6333
(4049)
4320
(2003)
4589
(2983)
TABLE 3
CROSS -SECTION EARNINGS ESTIMATES
1
IS
2
WOS
3
WOS
4
WOS
5
WOS
6
WOS*
Immigrant -0.62(0.02)
-0.50
(0.03)
-0.39
(0.03)
-0.51
(0.04)
-0.46
(0.04)
-0.60
(0.06)
Years since
Migration/10
0.24
(0.01)
0.33
(.05)
0.26
(0.05)
0.20
(0.05)
0.20
(0.05)
0.22
(0.05)
Hebrew - * * 0.06(0.02)
0.06
(0.02)
0.10
(0.02)
English (very
well) - * * *
0.13
(0.02)
0.14
(0.02)
Male 0.51(0.01)
0.16
(0.02)
0.17
(0.02)
0.17
(0.02)
0.18
(0.02)
0.17
(0.01)
Married 0.34(0.07)
0.02
(0.02)
0.01
(0.02)
0.01
(0.02)
0.01
(0.02)
0.02
(0.02)
Education 0.08(.002)
0.07
(.003)
0.06
(.003)
0.06
(.003)
0.06
(.003)
0.04
(.003)
Experience 0.05(.001)
0.02
(.003)
0.02
(.003)
0.02
(.003)
0.02
(.003)
0.02
(.002)
Exp /1002 -0.09(.003)
-0.05
(0.01)
-0.05
(0.01)
-0.05
(0.01)
-0.05
(0.01)
-0.05
(0.01)
Seniority - * 0.02(.002)
0.02
(.002)
0.02
(0.002)
0.02
(0.002)
Intercept 6.14
(0.05)
7.25
(0.02)
7.22
(0.04)
7.23
(0.04)
7.24
(0.04)
7.49
(0.04)
R - 0.32 0.35 0.36 0.37 0.482
N 16171 2726 2726 2726 2726 2726
 *Column 6 also controls for occupation and establishment fixed effects.
22
TABLE 4
CROSS -SECTION EARNINGS ESTIMATES
by Education
13 or More Years Education 12 or Fewer Years Education
Immigrant -0.35(0.04)
-0.77
(0.06)
-0.68
(0.03)
-0.25
(0.04)
-0.23
(0.06)
-0.22
(0.06)
Years since
Migration/10
0.34
(0.07)
0.24
(0.07)
0.23
(0.07)
0.19
(0.08)
0.20
(0.08)
0.20
(0.08)
Hebrew * 0.12(0.02)
0.11
(0.02) *
-0.01
(0.02)
-0.01
(0.02)
English (very
well) * *
0.14
(0.02) * *
 0.07
(0.03)
Male 0.19(0.02)
0.19
(0.02)
0.19
(0.02)
0.13
(0.02)
0.13
(0.02)
0.13
(0.02)
Married 0.01(0.02)
0.01
(0.02)
0.01
(0.02)
-.01
(0.03)
-.005
(0.03)
-0.01
(0.03)
Education 0.06(.005)
0.06
(.005)
0.06
(.005)
0.04
(0.01)
0.04
(0.01)
0.03
(0.01)
Experience 0.03(.004)
0.03
(.004)
0.03
(.004)
0.01
(.003)
0.01
(.003)
0.01
(.003)
Exp /1002 -0.08(0.01)
-0.08
(0.01)
-0.07
(0.01)
-0.03
(0.01)
-0.03
(0.01)
-0.03
(0.01)
Seniority 0.02(.003)
0.02
(.003)
0.02
(.003)
0.03
(.003)
0.03
(.003)
0.03
(.003)
Intercept 7.20
(0.08)
7.21
(0.08)
7.19
(0.08)
7.51
(0.09)
7.51
(0.09)
7.52
(0.09)
R 0.36 0.37 0.39 0.23 0.23 0.242
N 1648 1648 1648 1078 1078 1078
23
TABLE 4A
CROSS-SECTION ESTIMATES OF THE RETURN TO LANGUAGE KNOWLEDGE
by Immigrant Status
Hebrew English Very Well
Immigrants
All 0.06
(0.02)
0.11
(0.02)
High Education 0.11
(0.02)
0.13
(0.03)
Low Education .000
(0.02)
0.03
(0.04)
Natives
All * 0.10
(0.03)
High Education * 0.11
(0.04)
Low Education * 0.08
(0.03)
24
TABLE 5
CROSS -SECTION EARNINGS ESTIMATES
by Occupation
Nurses & Doctors High-Tech Skilled Unskilled
Immigrant -0.78(0.17)
-0.71
(0.08)
-0.30
(0.06)
-0.29
(0.12)
Years since
Migration/10
0.35
(0.20)
0.29
(0.09)
0.17
(0.07)
0.03
(0.16)
Hebrew 0.19(0.06)
0.10
(0.03)
0.02
(0.02)
0.04
(0.05)
English (very
well)
0.27
(0.06)
0.18
(0.03)
 0.09
(0.02)
 0.05
(0.04)
R 0.56 0.40 0.24 0.542
N 244 993 1141 348
Other controls: male, married, education, experience and experience squared, seniority.
25
TABLE 6
LONGITUDINAL EARNINGS ESTIMATES
(1) (2) (3) (4) (5)
Immigrant -0.01(0.02)
-0.06
(0.02)
-0.05
(0.02)
-0.05
(0.02)
-0.06
(0.02)
Seniority/10 0.24(0.01)
0.24
(0.01)
0.22
(0.01)
0.21
(0.02)
0.21
(0.02)
Seniority/10*
Immigrant
0.24
(0.04)
0.20
(0.04)
0.20
(0.04)
0.16
(0.04)
0.19
(0.04)
Change in Hebrew
fluency *
0.07
(0.01)
 0.06
(0.01)
 0.06
(0.01)
 0.05
(0.01)
Change in knowing
English very well * *
0.12
(0.02)
0.10
(0.02)
0.09
(0.02)
Additional controls No No No Yes Yes
Fixed occupation and
establishment effects No No No No Yes
R 0.13 0.14 0.15 0.18 0.292
N 2726 2726 2726 2726 2726
Dependent variable: Change in log wage
Additional controls: Experience, male, education, married
TABLE 7
LONGITUDINAL EARNINGS ESTIMATES
by Education and Occupation
and Their Relation to Cross-Section Estimates of the Return to Language Knowledge
13 or More Years
Education
12 or Fewer Years
Education
Doctors and
Nurses High-Tech Skilled Unskilled
Immigrant -0.04(0.03)
-0.03
(0.03)
-0.08
(0.08)
-.003
(0.03)
-0.08
(0.03)
-0.10
(0.06)
Seniority/10 0.28(0.02)
0.14
(0.02)
0.27
(0.05)
0.33
(0.03)
0.14
(0.03)
0.08
(0.03)
Seniority/10*
Immigrant
0.16
(0.06)
0.09
(0.07)
0.57
(0.16)
0.17
(0.07)
0.09
(0.06)
0.28
(0.13)
Change in Hebrew Fluency 0.08(0.01)
0.03
(0.02)
 -0.02
(0.05)
0.09
(0.02)
0.07
((0.02)
 0.01
(0.03)
Change in Knowing English Very Well 0.12(0.02)
0.03
(0.03)
0.14
(0.05)
0.11
(0.03)
0.06
(0.03)
0.04
(0.05)
R 0.21 0.08 0.37 0.26 0.09 0.072
Cross-Section Estimates (from tables 4 and 5)
Hebrew 0.11 -0.01 0.19 0.10 0.02 0.05
English 0.14 0.07 0.27 0.18 0.09 0.05
Difference Between Cross-Section and Longitudinal Estimates
Hebrew 0.03 -0.04 0.21 0.01 -0.05 0.04
English 0.02 0.04 0.13 0.07 0.03 0.01
N 1648 1078 244 993 1141 348
Dependent variable: Change in log wage
Additional controls: Experience, male, education, married
27
TABLE 8
LONGITUDINAL ESTIMATES OF THE RETURN TO LANGUAGE KNOWLEDGE
by Immigrant Status
Hebrew English Very Well
Immigrants
All 0.07
(0.01)
0.08
(0.03)
High Education 0.08
(0.02)
0.11
(0.03)
Low Education 0.03
(0.02)
.001
(0.04)
Natives
All * 0.12
(0.02)
High Education * 0.13
(0.03)
Low Education * 0.06
(0.04)
Additional controls: Experience, male, education, married, seniority

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