Pew Research Center Study on Which Cities had the Most H-1B Visas

On March 29, 2018, the San Jose Mercury News published a story titled "H-1B: Silicon Valley doesn’t get majority of controversial visas, report says". It begins:

The controversial H-1B work visa used heavily by Silicon Valley tech firms to acquire talent is much more widely used by companies based in New York and Texas, according to new research.

From 2010 to 2016, almost a third of the visas, which are intended for workers in jobs requiring specialized knowledge and a bachelor’s degree or higher, went to businesses in the New York City area, the Pew Research Center reported Thursday.

The referenced Pew Research Center Study is titled "East Coast and Texas metros had the most H-1B visas for skilled workers from 2010 to 2016" and begins as follows:

The employment of high-skilled foreign workers with H-1B visas centered in large East Coast metropolitan areas from fiscal years 2010 to 2016. These foreign workers also made up a significant part of the workforces in several Texas metro areas, according to a Pew Research Center analysis of previously unpublished metro-level government data of H-1B visa approvals obtained through a public records request.

The H-1B visa program is the nation’s largest temporary employment visa program. About 247,900 H-1B visa approvals – 29% of the nation’s total – went to employers in the New York City metro area from fiscal 2010 to 2016 (the most recent years for which data are available at the metropolitan level). The Dallas and Washington metro areas (74,000 and 64,800 approvals, respectively) had the next-highest totals, with Boston (38,300 approvals) also among the top metro areas by this measure. The data, obtained from U.S. Citizenship and Immigration Services, include details of those approved for an H-1B visa.

In the next paragraph, the article states a remarkable finding that College Station, Texas "stands far above the rest, with about 32 H-1B approvals per 100 workers". It also mentions that "more than 99% of the metro area’s H-1B approvals went to employees of Cognizant Technology Solutions Corp., whose U.S. headquarters is in College Station".

This last finding especially seemed to merit addition investigation. There are links to PDF and CSV files showing the number of approved H-1B petitions by employer for 2015 through 2017 on the U.S. Citizenship and Immigration Services website but the data does not contain the location of the employers or the H-1B workers. The following code outputs the first 20 employers in the file:

In [2]:
import pandas as pd
csvfile = 'https://www.uscis.gov/sites/default/files/USCIS/Resources/Reports%20and%20Studies/Immigration%20Forms%20Data/BAHA/Approved_H1B_2017_Employers_3.2.18.csv'
aa = pd.read_csv(csvfile, skiprows = 4)
aa.columns = ['TaxID','Employer','Approved','Salary','Degree','Subcount','Misc']
aa = aa.iloc[:, 0:4]
print(aa[aa.Employer.str.strip() != ""].head(20))
   TaxID                        Employer  Approved     Salary
0   4155    COGNIZANT TECH SOLNS US CORP   28,908     85,429 
4   9806       TATA CONSULTANCY SVCS LTD   14,697     73,505 
12  0235                     INFOSYS LTD   13,408     85,717 
18  4401                   WIPRO LIMITED    6,529     75,082 
23  4513         DELOITTE CONSULTING LLP    6,027    106,797 
28  2904                   ACCENTURE LLP    5,070     83,573 
32  2696      TECH MAHINDRA AMERICAS INC    4,931     78,443 
40  6545            AMAZON CORPORATE LLC    4,767    118,637 
45  5035                 HCL AMERICA INC    4,392     87,978 
50  4442           MICROSOFT CORPORATION    4,069    130,259 
56  5929           CAPGEMINI AMERICA INC    3,580     84,667 
60  1430       IBM INDIA PRIVATE LIMITED    3,000     79,916 
64  5596            ERNST & YOUNG US LLP    2,986    105,794 
69  3581                      GOOGLE INC    2,758    134,419 
74  2743               INTEL CORPORATION    2,625    104,691 
79  3900           SYNTEL CONSULTING INC    2,119     70,258 
82  4110                       APPLE INC    2,055    142,974 
88  4303  LARSEN & TOUBRO INFOTECH LIMIT    1,864     78,737 
90  9951               CISCO SYSTEMS INC    1,587    128,389 
94  5019                    FACEBOOK INC    1,566    144,812 

As can be seen, the employers appear to be listed in descending number of approvals. Also, Cognizant did have the top number of approved H-1B visas in 2017.

In any event, the location for both the employer and the H-1B workers is contained in disclosure files for the LCA programs. LCA stands for Labor Condition Application and is a form employers must file with the U.S. Department of Labor for H-1B, H-1B1 (Singapore and Chile) and E-3 (Australia) work visas.

The Pew study gives more information about the LCA program. If you click on "About this analysis" in the study, you'll see a section that begins:

The H-1B visa program allows U.S. employers to hire foreigners to work for up to six years in jobs that require highly specialized knowledge, and workers’ employment may be extended if they have green card applications pending. To participate, employers first submit applications to the U.S. Department of Labor attesting that no U.S. worker would be displaced by the prospective foreign worker. The application is then reviewed by U.S. Citizenship and Immigration Services (USCIS) before the State Department interviews the foreign worker and issues the visa.

This section goes on to describe the source for this data used in the study. It states:

The data on H-1B visa approvals were obtained from USCIS through a Freedom of Information Act request and were received in November 2017. Approvals that are subject to the annual cap account for nearly all (99.9%) approvals in this analysis. The FOIA data does not distinguish between approvals for initial and continuing employment. It includes employer names and employer location (city and state) but excludes worker location, which could be at the employer location or another location. This analysis assumes H-1B visa approvals are for foreigners who will work at the employer location.

Hence, the study looks at the employer names and location, not the worker location. It states that it "assumes H-1B visa approvals are for foreigners who will work at the employer location". The analysis below will show that this is a very flawed assumption. It will look at the LCA files to obtain information about the worker location. These files can be found on the U.S. Department of Labor website under the Disclosure Data tab. The following python code loads the LCA file for 2017 in order to look at the location data.

UPDATE: Problem with "About this analysis" in current Pew posting

At some point between November 9, 2018 and January 13, 2019, the "About this analysis" functionality in the Pew Study appears to have stopped working. Clicking on "ABOUT THIS ANALYSIS" (where it's capitalized) in a November 9, 2018 archive of the page causes text that includes the excerpts listed in the prior section to be displayed. On the other hand, clicking on it in a January 13, 2019 archive of the page has no effect. However, the excerpts listed in the prior section can be seen in the January 13th archive via the following steps:

  1. View the page in Google Chrome and highlight "About this analysis".
  2. Right-click and select Inspect.
  3. The first of the following lines should be highlighted:

    > <h4 class="collapsible-title">...</h4>
       </div>
     > <div class="content" style="display:none;">...</div>
    
  4. Click the arrow on the left of the last line. That should display the following lines.

    > <p>...</p>
     > <p>...</p>
     > <p>...</p>
     > <p>...</p>
     > <p>...</p>
     > <p>...</p>
    
  5. Click on the arrow on the left of the first and fourth lines to display the excerpts listed in the prior section.

Repeating the above steps for the November 9, 2018 archive of the page will reveal similar but slightly different code. I'm not a javascript expert so I would appreciate the opinion of anyone who can look at the code and judge the precise purpose of the change that was made. However, I did find that, if you change the "display:none;" to "display:block;" in the third line above (this can be done via right-click and selecting "Edit as HTML"), the hidden text will permanently appear.

Load 2017 Labor Condition Application (LCA) Data

The H-1B LCA Data is from https://www.foreignlaborcert.doleta.gov/pdf/PerformanceData/2017/H-1B_Disclosure_Data_FY17.xlsx and is linked to at https://www.foreignlaborcert.doleta.gov/performancedata.cfm (under the Disclosure Data tab). This data needs to be copied to the local directory initially. It can take several minutes to load this XLSX file the first time so the code writes the needed subset of the data out to a CSV file which loads quickly in subsequent runs.

In [3]:
import pandas as pd
import os.path
import time
csv_file = 'H-1B_FY17.csv'
xlsx_file = 'H-1B_Disclosure_Data_FY17.xlsx'
if (os.path.isfile(csv_file)):
    start = time.time()
    yy = pd.read_csv(csv_file)
    end = time.time()
    print('Seconds to load: ' + str(end - start))
else:
    start = time.time()
    zz = pd.read_excel(xlsx_file)
    end = time.time()
    print('Seconds to load: ' + str(end - start))
    zz.info()
    yy = zz.loc[:, ['CASE_STATUS','VISA_CLASS','EMPLOYER_NAME','EMPLOYER_CITY','EMPLOYER_STATE','EMPLOYER_POSTAL_CODE',
                    'SOC_NAME','TOTAL_WORKERS','WORKSITE_CITY','WORKSITE_COUNTY','WORKSITE_STATE','WORKSITE_POSTAL_CODE']]
    yy.to_csv(csv_file)
Seconds to load: 1.502570390701294

Look at just certified applications

The following code limits the applications to just those that have been certified and outputs the first five rows of the data.

In [4]:
xx = yy[yy['CASE_STATUS'] == 'CERTIFIED']
xx.head()
Out[4]:
Unnamed: 0 CASE_STATUS VISA_CLASS EMPLOYER_NAME EMPLOYER_CITY EMPLOYER_STATE EMPLOYER_POSTAL_CODE SOC_NAME TOTAL_WORKERS WORKSITE_CITY WORKSITE_COUNTY WORKSITE_STATE WORKSITE_POSTAL_CODE
194 194 CERTIFIED H-1B CLOUDWICK TECHNOLOGIES INC. NEWARK CA 94560 SOFTWARE DEVELOPERS, APPLICATIONS 1 MOUNTAIN VIEW SANTA CLARA CA 94040
195 195 CERTIFIED H-1B TATA CONSULTANCY SERVICES LIMITED ROCKVILLE MD 20850 WEB DEVELOPERS 1 HUDSON SUMMIT OH 44236
196 196 CERTIFIED H-1B HEALTH MANAGEMENT SYSTEMS, INC. IRVING TX 75038 SOFTWARE DEVELOPERS, APPLICATIONS 1 IRVING DALLAS TX 75038
197 197 CERTIFIED H-1B BLACKROCK INVESTMENT MANAGEMENT, LLC NEW YORK NY 10022 SOFTWARE DEVELOPERS, APPLICATIONS 1 SAN FRANCISCO SAN FRANCISCO CA 94105
198 198 CERTIFIED H-1B UNIVERSITY OF CALIFORNIA, BERKELEY BERKELEY CA 94720 SOIL AND PLANT SCIENTISTS 1 BERKELEY ALAMEDA CA 94720

Description of LCA fields

The following code describes the fields in the current data.

In [5]:
xx.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 545694 entries, 194 to 624649
Data columns (total 13 columns):
Unnamed: 0              545694 non-null int64
CASE_STATUS             545694 non-null object
VISA_CLASS              545694 non-null object
EMPLOYER_NAME           545662 non-null object
EMPLOYER_CITY           545685 non-null object
EMPLOYER_STATE          545682 non-null object
EMPLOYER_POSTAL_CODE    545683 non-null object
SOC_NAME                545694 non-null object
TOTAL_WORKERS           545694 non-null int64
WORKSITE_CITY           545690 non-null object
WORKSITE_COUNTY         544783 non-null object
WORKSITE_STATE          545694 non-null object
WORKSITE_POSTAL_CODE    545686 non-null object
dtypes: int64(2), object(11)
memory usage: 58.3+ MB

Worksite Counties which requested the most H-1B workers in 2017

The following code shows the countries which requested the most H-1B workers in 2017:

In [6]:
def checkCounty(county, state):
    ee = xx[xx['WORKSITE_COUNTY'].str.contains(county, na=False)]
    ff = ee[ee['WORKSITE_STATE'].str.contains(state, na=False)]
    gg = ff.groupby(['WORKSITE_COUNTY','WORKSITE_STATE']).agg({'TOTAL_WORKERS':'sum'})
    ss = gg.sort_values(by='TOTAL_WORKERS',ascending=False)
    print(ss[ss['TOTAL_WORKERS'] > 9].head(10))
    
checkCounty('','')
                                TOTAL_WORKERS
WORKSITE_COUNTY WORKSITE_STATE               
SANTA CLARA     CA                     113039
NEW YORK        NY                      55774
KING            WA                      43466
DALLAS          TX                      32756
COOK            IL                      31924
SAN FRANCISCO   CA                      28720
LOS ANGELES     CA                      25870
FULTON          GA                      22022
HARRIS          TX                      21623
SAN DIEGO       CA                      19868

As can be seen, Santa Clara County, the key county in Silicon Valley, requested the most H-1B workers. In fact, it requested more than double the number requested by New York County. This does not necessarily mean that they got the most approved but it certainly calls for further investigation.

Function to find Employer Cities and Worksite Cities with the largest worker requests

For any specific company, the following function will list the locations that request the most H-1B workers by both the EMPLOYER_CITY (typically, the location of the company headquarters) and the WORKSITE_CITY (the location where the workers are to actually work).

In [7]:
def checkEmployer(empname):
    ee = xx[xx['EMPLOYER_NAME'].str.contains(empname, na=False)]
    gg = ee.groupby(['EMPLOYER_NAME','EMPLOYER_CITY','EMPLOYER_STATE']).agg({'TOTAL_WORKERS':'sum'})
    ss = gg.sort_values(by='TOTAL_WORKERS',ascending=False)
    print(ss[ss['TOTAL_WORKERS'] > 9].head(10))
    gg = ee.groupby(['EMPLOYER_NAME','WORKSITE_CITY','WORKSITE_STATE']).agg({'TOTAL_WORKERS':'sum'})
    ss = gg.sort_values(by='TOTAL_WORKERS',ascending=False)
    print(ss[ss['TOTAL_WORKERS'] > 9].head(10))

Employer Cities and Worksite Cities with the largest worker requests for all Employers

If the function is called with an empty string, the function will look at all employers as shown below.

In [8]:
checkEmployer("")
                                                                                TOTAL_WORKERS
EMPLOYER_NAME                                   EMPLOYER_CITY   EMPLOYER_STATE               
DELOITTE CONSULTING LLP                         PHILADELPHIA    PA                      93598
COGNIZANT TECHNOLOGY SOLUTIONS U.S. CORPORATION COLLEGE STATION TX                      50755
HCL AMERICA, INC.                               SUNNYVALE       CA                      39667
APPLE INC.                                      CUPERTINO       CA                      27223
MPHASIS CORPORATION                             NEW YORK        NY                      21803
DELOITTE & TOUCHE LLP                           PHILADELPHIA    PA                      20940
INFOSYS LIMITED                                 PLANO           TX                      20565
TATA CONSULTANCY SERVICES LIMITED               ROCKVILLE       MD                      18912
CAPGEMINI AMERICA INC                           CHICAGO         IL                      16196
ERNST & YOUNG U.S. LLP                          SECAUCUS        NJ                      12272
                                                          TOTAL_WORKERS
EMPLOYER_NAME               WORKSITE_CITY WORKSITE_STATE               
APPLE INC.                  CUPERTINO     CA                      19412
DELOITTE CONSULTING LLP     PHILADELPHIA  PA                      10672
AMAZON CORPORATE LLC        SEATTLE       WA                       8747
NVIDIA CORPORATION          SANTA CLARA   CA                       7847
APPLE INC.                  AUSTIN        TX                       7723
DELOITTE CONSULTING LLP     LAKE MARY     FL                       6766
QUALCOMM TECHNOLOGIES, INC. SAN DIEGO     CA                       6335
MICROSOFT CORPORATION       REDMOND       WA                       5554
DELOITTE CONSULTING LLP     NEW YORK      NY                       4513
QUALCOMM ATHEROS, INC.      SAN JOSE      CA                       4324

As can be seen, Cognizant did request the second highest number of H-1B workers when the requests are grouped by EMPLOYER_CITY. However, the second list shows that Apple in Cupertino is the employer which requested the most workers when the requests are grouped by WORKSITE_CITY. In addition, Nvidia and Qualcomm Atheros also are in the top ten for worksite cities in Santa Clara County. In any case, this function is used to focus in on Cognizant below.

Employer Cities and Worksite Cities with the largest worker requests for Cognizant Technology

Following is the result of running the function for Cognizant:

In [9]:
checkEmployer("COGNIZANT TECH")
                                                                                TOTAL_WORKERS
EMPLOYER_NAME                                   EMPLOYER_CITY   EMPLOYER_STATE               
COGNIZANT TECHNOLOGY SOLUTIONS U.S. CORPORATION COLLEGE STATION TX                      50755
                                                                              TOTAL_WORKERS
EMPLOYER_NAME                                   WORKSITE_CITY WORKSITE_STATE               
COGNIZANT TECHNOLOGY SOLUTIONS U.S. CORPORATION TEANECK       NJ                       3570
                                                CHICAGO       IL                       1919
                                                HARTFORD      CT                       1791
                                                LOS ANGELES   CA                       1613
                                                SAN RAMON     CA                       1559
                                                IRVING        TX                       1469
                                                ATLANTA       GA                       1132
                                                BRIDGEWATER   NJ                       1028
                                                PHOENIX       AZ                        950
                                                CHARLOTTE     NC                        941

As can be seen, College Station, Texas was listed as the EMPLOYER_CITY for all of the H-1B workers requested by Cognizant in 2017. However, the WORKSITE_CITY appears to be distributed all throughout the country. The only Texas location in the top 10 was Irving which is in the Dallas-Fort Worth metropolitan area. Following is what the Pew study said about College Station:

When looking at the footprint of high-skilled foreign workers by metro area, College Station, Texas, stands far above the rest, with about 32 H-1B approvals per 100 workers. (More than 99% of the metro area’s H-1B approvals went to employees of Cognizant Technology Solutions Corp., whose U.S. headquarters is in College Station.) By comparison, no other metro area had more than five H-1B approvals per 100 workers.

From the wide distribution of worksite cities shown above, the 32 H-1B approvals per 100 workers for College Station is totally mistaken. Nearly all of the workers appear to have been working in other locations. It is the working population of those other locations that the Cognizant workers should have been compared against.

Employer Cities and Worksite Cities with the largest worker requests for other Employers

Is Cognizant the only such miscalculation? To answer this, it's useful to look at the other employers with the most H-1B approvals in 2017. Following are the results for Tata Consultancy, the second on the list:

In [10]:
checkEmployer("TATA CONSULT")
                                                                TOTAL_WORKERS
EMPLOYER_NAME                     EMPLOYER_CITY EMPLOYER_STATE               
TATA CONSULTANCY SERVICES LIMITED ROCKVILLE     MD                      18912
                                  DUVAL         FL                         62
                                                                TOTAL_WORKERS
EMPLOYER_NAME                     WORKSITE_CITY WORKSITE_STATE               
TATA CONSULTANCY SERVICES LIMITED IRVING        TX                        648
                                  ATLANTA       GA                        612
                                  CHICAGO       IL                        585
                                  NEW YORK      NY                        474
                                  SAN ANTONIO   TX                        426
                                  BELLEVUE      WA                        379
                                  SUNNYVALE     CA                        371
                                  PHOENIX       AZ                        358
                                  CHARLOTTE     NC                        310
                                  PLANO         TX                        308

As can be seen, the EMPLOYER_CITY for Tata Consultancy is Rockville, Maryland. According to the Wikipedia entry for the Washington metropolitan area, Rockville is a part of that area. As can be seen in the interactive table in the Pew study, the Washington metropolitan area is the area with the third largest number of approvals. Note that the table can be sorted by approvals using the arrow above that column. In any case, once again the actual worksites of the H-1B workers appear to be spread throughout the country, at least according to the original LCA requests.

Following are the results for Infosys Limited, the employer with the third most H-1B approvals in 2017:

In [11]:
checkEmployer("INFOSYS LIMITED")
                                              TOTAL_WORKERS
EMPLOYER_NAME   EMPLOYER_CITY EMPLOYER_STATE               
INFOSYS LIMITED PLANO         TX                      20565
                                              TOTAL_WORKERS
EMPLOYER_NAME   WORKSITE_CITY WORKSITE_STATE               
INFOSYS LIMITED SUNNYVALE     CA                        803
                PHOENIX       AZ                        708
                ATLANTA       GA                        675
                HOUSTON       TX                        616
                CHARLOTTE     NC                        607
                PLANO         TX                        591
                HARTFORD      CT                        444
                TAMPA         FL                        422
                IRVINE        CA                        391
                RICHARDSON    TX                        390

As can be seen, the EMPLOYER_CITY for Infosys Limited is Plano, Texas. According to the Wikipedia entry for the Dallas–Fort Worth–Arlington metropolitan area, Plano is a part of that area. As can be seen in the interactive table in the Pew study, this metropolitan area is the area with the second largest number of approvals. Once again the actual worksites of the H-1B workers appear to be spread throughout the country.

Following are the results for Wipro Limited, the employer with the forth most H-1B approvals in 2017:

In [12]:
checkEmployer("WIPRO")
                                             TOTAL_WORKERS
EMPLOYER_NAME EMPLOYER_CITY  EMPLOYER_STATE               
WIPRO LIMITED EAST BRUNSWICK NJ                       9815
WIPRO LLC     EAST BRUNSWICK NJ                       1252
                                              TOTAL_WORKERS
EMPLOYER_NAME WORKSITE_CITY   WORKSITE_STATE               
WIPRO LIMITED SUNNYVALE       CA                        530
              AUSTIN          TX                        346
              RICHMOND        VA                        279
              RICHFIELD       MN                        271
              HOUSTON         TX                        256
              SAN JOSE        CA                        240
              LONE TREE       CO                        194
              MENOMONEE FALLS WI                        176
              IRVING          TX                        163
              SAN FRANCISCO   CA                        138

As can be seen, the EMPLOYER_CITY for Wipro Limited is East Brunswick, New Jersey. According to the Wikipedia entry for East Brunswick, it's a part of the New York-Newark-Jersey City metropolitan area. As can be seen in the interactive table in the Pew study, this metropolitan area is the area with the largest number of approvals. Once again the actual worksites of the H-1B workers appear to be spread throughout the country.

Following are the results for Deloitte Consulting, the employer with the fifth most H-1B approvals in 2017:

In [13]:
checkEmployer("DELOITTE CONSULT")
                                                      TOTAL_WORKERS
EMPLOYER_NAME           EMPLOYER_CITY EMPLOYER_STATE               
DELOITTE CONSULTING LLP PHILADELPHIA  PA                      93598
                        PHILADELPIA   PA                         60
                                                      TOTAL_WORKERS
EMPLOYER_NAME           WORKSITE_CITY WORKSITE_STATE               
DELOITTE CONSULTING LLP PHILADELPHIA  PA                      10672
                        LAKE MARY     FL                       6766
                        NEW YORK      NY                       4513
                        ATLANTA       GA                       3675
                        CHICAGO       IL                       3646
                        DALLAS        TX                       3138
                        SAN FRANCISCO CA                       2333
                        HOUSTON       TX                       2226
                        MECHANICSBURG PA                       2034
                        BOSTON        MA                       1495

As can be seen, the EMPLOYER_CITY for Deloitte Consulting is Philadelphia, Pennsylvania. As can be seen in the interactive table in the Pew study, the Philadelphia-Camden-Wilmington metropolitan area is the area with the sixth largest number of approvals. Once again the actual worksites of the H-1B workers appear to be spread throughout the country.

Following are the results for Accenture LLP, the employer with the sixth most H-1B approvals in 2017:

In [14]:
checkEmployer("ACCENTURE")
                                            TOTAL_WORKERS
EMPLOYER_NAME EMPLOYER_CITY EMPLOYER_STATE               
ACCENTURE LLP CHICAGO       IL                       7548
                                             TOTAL_WORKERS
EMPLOYER_NAME WORKSITE_CITY  WORKSITE_STATE               
ACCENTURE LLP ATLANTA        GA                        318
              HOUSTON        TX                        298
              CHICAGO        IL                        239
              RICHFIELD      MN                        235
              HARTFORD       CT                        187
              CHARLOTTE      NC                        185
              PHILADELPHIA   PA                        176
              SAN JOSE       CA                        148
              REDMOND        WA                        138
              WOODLAND HILLS CA                        138

As can be seen, the EMPLOYER_CITY for Accenture LLP is Chicago, Illinois. As can be seen in the interactive table in the Pew study, the Chicago-Naperville-Elgin metropolitan area is the area with the seventh largest number of approvals. Once again the actual worksites of the H-1B workers appear to be spread throughout the country.

The following table shows the employers who made the 6 largest requests for H-1B workers in 2017 and their ranking for H-1B visa approvals in the Pew study. The last column shows the rank of metropolitan area by population as shown in the Wikipedia entry for U.S. metropolitan areas.

                                                                                                       Pew   Population
                    Employer  Approved   Salary  Employer_City        Metropolitan Area                Rank  Rank
----------------------------  --------  -------  -------------------  -------------------------------  ----  ----------
COGNIZANT TECH SOLNS US CORP   28,908    85,429  COLLEGE STATION, TX  College Station-Bryan, TX          5   187  
   TATA CONSULTANCY SVCS LTD   14,697    73,505  ROCKVILLE, MD        Washington-Arlington-Alexandria    3     6
                 INFOSYS LTD   13,408    85,717  PLANO, TX            Dallas-Fort Worth-Arlington        2     4
               WIPRO LIMITED    6,529    75,082  EAST BRUNSWICK, NJ   New York-Newark-Jersey City        1     1
     DELOITTE CONSULTING LLP    6,027   106,797  PHILADELPHIA, PA     Philadelphia-Camden-Wilmington     6     7
               ACCENTURE LLP    5,070    83,573  CHICAGO, IL          Chicago-Naperville-Elgin           7     3
                                                                      San Jose-Sunnyvale-Santa Clara    10    35

Hence, those six companies appear to play a major role in the results in the Pew Study. As shown above, however, the H-1B workers in all six were spread among numerous metropolitan areas. For this reason, it would seem that the Pew study's conclusions on what metropolitan areas had the most H-1B visas for skilled workers form 2010 to 2016 is largely unfounded. As stated in the study inself, it is based on the locations where the company headquarters are located, not the location where the H-1B workers are actually working. It is the worksite locations that the number of approvals should be compared against.

All six of the companies listed above are IT consulting firms. The study's assumption that "H-1B visa approvals are for foreigners who will work at the employer location" may be less unreasonable for companies whose chief product is not consulting and/or services. Of those companies listed in the first table above, Amazon, Microsoft, Google, Apple, and Facebook had the majority of their requested workers slated to work at the employer location. The percentages ranged from 67% for Google to 86% for Amazon. The largest exception was Intel which had only 17% (1110 of 6586 requested workers) slated to work in the employer city of Santa Clara with 2666 slated for Hillsboro, OR and 1218 slated for Folsom, CA. Cisco had just 47% (3531 of 7583) slated to work in the employer city of San Jose, CA. Hence, the assumption is better for non-consulting companies but still has problems. In any event, companies whose main business is consulting obtain the great majority of H-1B workers and the assumption that their H-1B workers will work in the employer city appears to be totally wrong for them.

Employer Cities, Worksite Cities, and Worksite Counties with the largest worker requests

The above analysis looks at the difference between the Employer City and the Worksite City for specific employers. This helps show the effect of companies whose main business is consulting on the metropolitan areas listed in the Pew study. This section looks at the employer cities, worksite cities, and worksite counties with the largest H-1B worker requests since the Pew study likewise gives numbers by metropolitan area, ignoring specific employers.

Following is Python code that looks at the Employer Cities requesting the most H-1B workers in 2017, followed by the resulting table and bar chart:

In [41]:
import matplotlib.pyplot as plt
%matplotlib inline

gg = xx.groupby(['EMPLOYER_CITY','EMPLOYER_STATE']).agg({'TOTAL_WORKERS':'sum'})
ss = gg.sort_values(by='TOTAL_WORKERS',ascending=False)
ss.to_csv('EMPCITY'+'.csv', sep=',')
ss['1000s_OF_WORKERS'] = ss['TOTAL_WORKERS'] / 1000
print(ss.iloc[:,[1]].head(10))
ss.index = ss.index.get_level_values(0)+", "+ss.index.get_level_values(1)
plt.grid(zorder=0)
plt.barh(range(10),ss['1000s_OF_WORKERS'].head(10),zorder=3)
plt.yticks(range(10), ss.index)
plt.gca().invert_yaxis()
plt.xlabel('Thousands of H-1B Workers Requested')
plt.title("Employer Cities Requesting the Most H-1B Workers")
                                1000s_OF_WORKERS
EMPLOYER_CITY   EMPLOYER_STATE                  
PHILADELPHIA    PA                       131.266
NEW YORK        NY                        53.282
COLLEGE STATION TX                        51.026
SUNNYVALE       CA                        46.649
PLANO           TX                        35.859
CHICAGO         IL                        35.352
SAN JOSE        CA                        34.811
SANTA CLARA     CA                        30.043
CUPERTINO       CA                        27.843
ROCKVILLE       MD                        19.830
Out[41]:
Text(0.5,1,'Employer Cities Requesting the Most H-1B Workers')

Following is Python code that looks at the Worksite Cities (instead of the Employer Cities) requesting the most H-1B workers in 2017, followed by the resulting table and bar chart:

In [46]:
gg = xx.groupby(['WORKSITE_CITY','WORKSITE_STATE']).agg({'TOTAL_WORKERS':'sum'})
ss = gg.sort_values(by='TOTAL_WORKERS',ascending=False)
ss.to_csv('WORKCITY'+'.csv', sep=',')
ss['1000s_OF_WORKERS'] = ss['TOTAL_WORKERS'] / 1000
print(ss.iloc[:,[1]].head(10))
ss.index = ss.index.get_level_values(0)+", "+ss.index.get_level_values(1)
plt.grid(zorder=0)
plt.barh(range(10),ss['1000s_OF_WORKERS'].head(10),zorder=3)
plt.yticks(range(10), ss.index)
plt.gca().invert_yaxis()
plt.xlabel('Thousands of H-1B Workers Requested')
plt.title("Worksite Cities Requesting the Most H-1B Workers")
                              1000s_OF_WORKERS
WORKSITE_CITY WORKSITE_STATE                  
NEW YORK      NY                        55.409
SAN JOSE      CA                        34.263
SAN FRANCISCO CA                        29.286
CHICAGO       IL                        24.694
SANTA CLARA   CA                        21.415
HOUSTON       TX                        20.745
CUPERTINO     CA                        20.155
ATLANTA       GA                        20.110
AUSTIN        TX                        20.054
PHILADELPHIA  PA                        18.648
Out[46]:
Text(0.5,1,'Worksite Cities Requesting the Most H-1B Workers')

As can be seen above, looking at worksite instead of employer cities causes Philadelphia to drop from first with 131,266 requests to tenth with 18,648 requests. Philadelphia is the location of the headquarters for Deloitte Consulting. Also, College Station (TX), Sunnyvale (CA), Plano (TX), and Rockville (MD) drop out of the top ten. These are the locations of the headquarters for Cognizant Technology, HCL America, Infosys Limited, and Tata Concultancy Services Limited, respectively.

Also notable is that three of the worksite cities (San Jose, Santa Clara, and Cupertino) are in Santa Clara County, California. This is the location of Silicon Valley. The following Python code looks at the worksite counties requesting the most H-1B workers in 2017, followed by the resulting table and bar chart:

In [48]:
gg = xx.groupby(['WORKSITE_COUNTY','WORKSITE_STATE']).agg({'TOTAL_WORKERS':'sum'})
ss = gg.sort_values(by='TOTAL_WORKERS',ascending=False)
ss.to_csv('WORKCOUNTY'+'.csv', sep=',')
ss['1000s_OF_WORKERS'] = ss['TOTAL_WORKERS'] / 1000
print(ss.iloc[:,[1]].head(10))
ss.index = ss.index.get_level_values(0)+", "+ss.index.get_level_values(1)
plt.grid(zorder=0)
plt.barh(range(10),ss['1000s_OF_WORKERS'].head(10),zorder=3)
plt.yticks(range(10), ss.index)
plt.gca().invert_yaxis()
plt.xlabel('Thousands of H-1B Workers Requested')
plt.title("Worksite Counties Requesting the Most H-1B Workers")
                                1000s_OF_WORKERS
WORKSITE_COUNTY WORKSITE_STATE                  
SANTA CLARA     CA                       113.039
NEW YORK        NY                        55.774
KING            WA                        43.466
DALLAS          TX                        32.756
COOK            IL                        31.924
SAN FRANCISCO   CA                        28.720
LOS ANGELES     CA                        25.870
FULTON          GA                        22.022
HARRIS          TX                        21.623
SAN DIEGO       CA                        19.868
Out[48]:
Text(0.5,1,'Worksite Counties Requesting the Most H-1B Workers')

As can be seen, Santa Clara County had over twice as many requests as the number two worksite county, New York County. Santa Clara County is the location of Silicon Valley. Hence, Silicon Valley did have the most requests for H-1B workers by worksite county despite the San Jose-Sunnyvale-Santa Clara, CA area being ranked tenth in the Pew's table of employer metropolitan areas. In fact, the H-1B visa approvals per 100 workers shown in the table appears to be largely meaningless. This is especially the case for the 32 H-1B visa approvals per 100 workers listed for College Station, Texas. This is because the Pew study is comparing the H-1B workers who are working in the Worksite Cities (where they are actually working) to the population of workers in the Employer City (where the company headquarters is located). As shown above, these are often very different cities, especially in the case of [IT consulting firms]https://en.wikipedia.org/wiki/List_of_IT_consulting_firms).