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Annotated by Zenko Takayama, Ph.D
Olney, William W. (2017) English Proficiency and Labor Market Performance: Evidence from the Economics Profession. Economic Inquiry, 55(1), 0-44.
Ronride Ai
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Table
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References
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Images
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Note
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2.1
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Rankings Data
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2.2
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Biographical Information
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2.3
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Descriptive Statistics
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4.1
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Baseline
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4.2
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Components
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5.1
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English Definition
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5.2
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Country Controls and Results
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5.3
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Alternate Rankings
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5.4
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Cohorts
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5.5
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Individual Controls
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5.6
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Sample
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A.1
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Data Gathering Process
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A.2
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Missing Values
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A.3
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Country of Birth of Top Economists
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A.4
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- Biographical information for each of the top economists in the sample was individually gathered
- from a variety of sources. This proved to be the most daunting aspect of this project but also the
- most important. Great care was taken to ensure that each piece of information was correct, which
- often entailed confirming it across multiple sources. The specific data collection process for each
- individual took the following form.First, the curriculum vitae (CV) of the individual was used which proved to be the most
- important source of biographical information. Almost all economists publicly post their CVs and
- the information is deemed highly accurate, since the economist creates the document themselves.
- The CV almost always includes current employment, undergraduate institution, undergraduate
- graduation year, Ph.D. institution, and Ph.D. graduation year. Often the economist’s CV also
- includes information on the country of birth, year of birth, citizenship, and languages (including
- "mother tongue"). Since citizenship can change, it was not used to identify country of birth unless
- it could be independently confirmed with other information from different sources. Furthermore,
- the "mother tongue" and country of birth were almost always consistent. However, country of birth
- had far better coverage. For economists that provided all of this biographical information, the data
- gathering process was complete. However, even for these individuals, the data provided in the CV
- was cross-checked against information provided by other sources. Unfortunately, many economists
- do not provide for instance country and year of birth in their CVs and so I turned to other sources.Economists with missing or incomplete CVs, were looked up in Who’s Who in Economics (Blaug
- and Vane 2003). This book provides biographical information, including name, education, country
- of birth, date of birth, and current and past employment, for the most noteworthy economists of
- the twentieth century. Numerous older and more prominent economists are listed in the book, and
- thus Who’s Who in Economics proved to be a valuable source of information. When applicable,
- rarely did an entry in Who’s Who in Economics conflict with the information provided on the
- economist’s CV.The short autobiographies written by Nobel Prize winning economists also proved to be a useful
- source of information. This was a first hand account of the economists past, although obviously it is37
- only available for a select group of economists. For economists that unfortunately passed away, there
- are often obituaries that include extensive biographical information. In addition, economists often
- grant interviews which are available online and contain information about their past. Numerous
- economists also provide a short biography on their website. This often has information such as
- country of birth, date of birth, or the place that they grew up which was not readily available on
- their CV.Many economists have entries in Wikipedia that contain biographical information. However,
- given the open source nature of Wikipedia, I used this information sparingly and would cross-
- check it with data from other sources before using it. Finally, background check websites (such
- as Radaris) contain information on the age of an individual which can be used to infer the year
- of birth.This information was only utilized if the full name (including middle initial) matched
- the economist, if the place of residence was consistent with the economist’s current employer, and
- if past locations were consistent with past employers of the economist. Finally, before using this
- information, the date of birth was cross checked against the year of undergraduate degree to ensure
- that the implied age at graduation was plausible. For economists with common names it was not
- possible to conclusively identify them on these websites and thus the observation was left missing.
- Despite my best efforts to construct a comprehensive dataset using this data collection process,
- some biographical information for certain economists remains unavailable. Furthermore, if there
- was any ambiguity or inconsistencies across sources, I erred on the side of caution and left the
- observation missing. Thus, a portion of economists within my sample have missing biographical
- information. For this paper, the country of birth and date of birth missing values are potentially
- problematic since they are used to construct the English, age, and age squared variables utilized in
- the empirical analysis. Information on gender, the first letter of the economists last name, and the
- year of death (when applicable) were never missing.In the sample of the top 2.5% of economists, 9% of the year of birth observations are missing
- and 20% of the country of birth observations are missing. It is unclear whether to leave these38
- observations missing or rely on other biographical information to make inferences about these
- missing values. In the baseline specification, I chose the latter option to ensure, to the extent
- possible, that the full sample of top economists was maintained. Thus, specifically it is assumed
- that individuals graduated from their undergraduate institution at the age of 22.In addition,
- it is assumed that the economist obtained an undergraduate degree from an institution in their
- country of birth. Since information on the undergraduate institution is seldom missing, this proved
- to be a useful way of identifying both missing values.How reasonable is it to assume that the economist graduated from their undergraduate institu-
- tion at the age of 22? Figure A1 provides information on the age at graduation, for those economists
- that have non-missing data on year of birth and year of graduation. 43% of these individuals grad-
- uated at the age of 22 and 79% graduated between the ages of 21-23. Thus, approximating the
- date of birth by subtracting 22 from the economist’s graduation year appears to be remarkably
- accurate.Next it is worth asking how reasonable it is to assume that the economist graduated from an
- undergraduate institution in their country of birth. Among those economists with non-missing
- values, Figure A2 shows the share of individuals whose country of birth matches the country of39
- their undergraduate degrees. The first column shows that 89% of economists graduated college in
- the country in which they were born. Column 2 shows that the share is 98% for those born in
- the six English speaking countries and 75% for non-English speaking countries. Overall, Figure A2
- demonstrates that it is surprisingly common for economists to attend an undergraduate institution
- in their country of birth.Despite the fact that the assumptions used to approximate the age and country of birth of
- the economist seem remarkably accurate, it is worth investigating what would happen if these
- observations were left missing. Table A1 replicates Table 5 but leaves these values missing. Despite
- the drop in the number of observations, the results remain very similar. Specifically, English remains
- positive and significant in all three specifications. Furthermore, the magnitude of the coefficients, if
- anything, becomes larger in Table A1. Thus, the treatment of these missing values has no significant
- bearing on the results.404142
- The baseline analysis uses the rank of an economist as the dependent variable of interest. However,
- perhaps the mapping of papers and citations data into rankings is affecting the distribution of
- economists and thus the results. Fortunately, in addition to the rank data, IDEAS/RePEc also
- provides the underlying "score" data which in this case refers to the weighted (i.e. quality adjusted)
- number of papers and citations. This section examines whether the results are sensitive to whether
- the rank or score variables are used.Column 1-3 of Table A3 reports the results using total average score, papers score, and citations
- score as the dependent variables. The coefficients on English remain significant and positive in all
- of these specifications. However, unlike the rank data, the magnitude of the coefficients now vary
- due to the different underlying distributions of the dependent variables. This makes comparisons
- across these specifications difficult.For comparison purposes, columns 5-6 standardize the paper and citation scores to have a
- mean zero and a standard deviation of one (the total score in column 4 is then the average of these
- two standardized variables). The coefficients on English in columns 4-6 are all still positive and
- significant but now the magnitude of the coefficients are also similar. We see that being a native
- English speaker increases the economists total score, papers score, and citations score by about 0.2
- standard deviations.Finally, columns 7-9 take the natural log of the total average score, the paper score, and the
- citation score.The results indicate that native English speakers have approximately 9% more
- quality adjusted papers and approximately 22% more quality adjusted citations. Overall, Table A3
- indicates that the results are similar across a variety of different score measures and all of these
- findings are consistent with the baseline rank results.4344
p. 24
The fact that such strong results are found in a math and written based discipline like economics suggests that the impact of being a native English speaker is likely even larger in other fields and professions
(Olney 2017, p. 24)
translation
経済学のような数学と文章をベースとする学問でこれほど強い結果が出たということは、英語を母国語とすることが他の分野や職業でさらに大きな影響を与える可能性があることを示しています。
memo
+ note
p. 24
they indicate that some individuals have an advantage at publishing within economics simply due to their country of birth and native language
(Olney 2017, p. 24)
translation
経済学の世界では、生まれた国や母国語によって、出版が有利になる人がいることを示すものです。
memo
+ note
p. 24
English proficiency leads to approximately a 9% increase in the quality adjusted number of papers and a 22% increase in the quality adjusted number of citations.
(Olney 2017, p. 24)
translation
英語力があると、品質調整後の論文数が約9％、品質調整後の被引用回数が約22％増加することになります。
memo
+ note