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Data Mining Techniques Used to Study Impact of Immigration on the US Economy

Mining data relating to patents helped researchers determine that immigrants were not stealing the thunder from ethnic Americans.

For decades, immigrants have played a vital role in the U.S. labor force and economy at large. Most arrive on H1-B visas that US firms use to employ highly skilled specialized workers for a period of three years, after which these recruits can apply for green cards to acquire permanent residency status. Whether the H-1B visa program is promoting innovation or affecting job prospects for Americans is one of the most hotly debated subjects today. Another ongoing controversy is about whether outsourcing is good or bad for the US economy. Let’s look at the debates around these two pressing issues.

Innovative Data Mining Help Researchers reach Important Conclusions

In his research report The Supply Side of Innovation: H-1B Visa Reforms and US Ethnic Innovation coauthored with William F. Lincoln of the University of Michigan, Harvard Business School professor William Kerr indicates that immigration is good for innovation and has a limited overall effect on non-immigrant workers.

This research study, which relied extensively on data mining techniques, reports that

  • The growth of H-1B program is linked to the increase in the number of immigrants working in science and engineering
  • The H-1B program did not displace native Americans from their jobs

However, it also ruled out the opposing idea that the program created greater job opportunities for Americans.

The study also looked at whether H-1B visas promoted innovation. The researchers examined data on patent applications and grants from the United States Patent and Trademark Office through May 2009. However, as these records did not have precise information about inventors’ immigration status or ethnicities, they decided to mine the data. Using data mining software, the researchers examined the names in the patent applications and grants through May 2009. Though the patent records did not contain any information regarding the inventors’ immigration status or ethnicity, the name-matching software helped them infer the ethnicity of inventors at any given firm.

Name matching plays a key role in database and data mining applications concerning people. By mining the patent data, the researchers were able to identify the number of inventions by foreign ethnicities, especially Indians and Chinese. They found that a 10 percent increase in the H-1B population is correlated with a 1 percent increase of total patented inventions.

Mining the data also helped them demonstrate that the H-1B program did not notably impact the number of patents that carried Anglo-Saxon names. This indicated that immigrants were not stealing the glory from ethnic American inventors.

The Challenges of Big Data Management

The rate at which the world is generating data is mind-boggling. Along with the growth in information, businesses are learning that analyzing their databases as well as large and complex forms of data across industries or ‘big data’ can prove lucrative. A professional data mining services are available for industries such as healthcare, engineering, banking, and education. Data from websites can be collected and fed into an Excel database. Contact information can be gleaned from websites and e-newspapers mined for specific information. Data mining is also helping fleet managers manage their trucking fleets more efficiently. Given the sophistication of data mining software and computerized systems, public and private organizations are now making use of the mountain of information on hundreds of variables to boost their bottom line.

About MOS Team

MOS Team

Managed Outsource Solutions (MOS) is a leading BPO company committed to providing business process outsourcing solutions for a wide range of industries such as Medical, Legal, Information Technology and Online Media.