About Investing in America

About Investing in America

Initially launched in 2017, this product has been revamped and updated to provide a detailed and layered view of the current reality of Chinese foreign direct investments (FDI) in America.

With the interactive map, users can view the distribution of Chinese FDI in America at three levels: national, state, and county. For example, users can easily compare one US state or county to another in terms of the volume of Chinese investments, as well as those investments’ local economic impacts across diverse American geographies.

We hope this feature is useful to both local and national policymakers, businesses, and potential investors, as well as anyone seeking a more comprehensive and granular picture of Chinese investments in America.

How Is This Product Different?

Several attributes set this product apart from other offerings on Chinese investment. First, it offers a level of granularity that is not publicly available. Second, it uses proprietary data to construct a bottom-up picture of the current reality of Chinese investments rather than one based on announced investments that may or may not happen. Third, the latest edition includes a breakdown of greenfield investments at all levels (see more below on data and methodology).

Foreign investments are very difficult to execute under any circumstance. Many deals begin with major announcements or groundbreaking ceremonies but then ultimately fail, providing no added value to the local economy. In some cases, greenfield investments, such as Tianjin Pipe‘s investment in Gregory, Texas, take a long time to complete.

This is all the more difficult for Chinese investments in a highly charged environment. What were considered acceptable, job-creating investments just a few years ago are now invariably politicized—for example, the latest brouhaha over a Chinese-invested battery plant in Michigan.

This is why we launched the new iteration to see whether Chinese FDI between 2017 and 2021 plummeted as bilateral tensions rose. To our surprise, it has not. In fact, some states have even seen significant increases in jobs related to Chinese investment.

How It Works

The map should be intuitive to navigate, but here are some pointers just in case:

  • Clicking on a single state will display all counties that have Chinese-owned entities and corresponding state-level data in the dashboard. Similarly, hovering on a county will show the same set of corresponding data as the dashboard menu;
  • To view another state, click on the “zoom out” button in the upper left to return to the default national view.
  • The best viewing experience will be on desktop or laptop, because the map has been optimized for those screen sizes. While the product is functional on mobile, it will be a less optimal viewing experience.

Dashboard Terms

You’ll notice that we use the term “entities” instead of “companies.” Because of the bottom-up construction of Chinese FDI, the headline figures are based on the total number of “entities” instead of “companies.” Numerous companies are multi-entity operations across the United States, and each entity has employees that should be generating revenue in theory. For example, Fuyao Glass America has four operating entities. While using entities risks projecting an inflated volume of Chinese FDI, we made this compromise in order to tabulate jobs and sales from all entities.

  • Chinese FDI = total number of entities in which mainland Chinese companies or investors have a majority stake (>50%).
  • Jobs from Chinese FDI = total number of employees across all Chinese-owned entities.
  • Total Sales = sales value by Chinese-owned entities within a particular jurisdiction.
  • Greenfields = investments in new facilities and operations from the ground up, such as plants and factories, as opposed to direct acquisition of physical assets or passive capital injections to acquire stakes in companies.
  • Top Industries by Greenfields = sectors with the highest concentration of Chinese-owned greenfield entities (sectors are based on SIC codes).

Data and Methodology

The underlying data used in this product is called the National Establishment Time-Series (NETS), a database of establishment information from commercial data provider Dun & Bradstreet (D&B).

For almost 30 years, D&B has taken regular snapshots of the US economy at the firm level by collecting information, such as job creation and destruction, sales, change in primary markets, and corporate affiliation, among other data. According to D&B, the collection of data is largely based on the compilation of regulatory records, filings, and telephonic surveys. The company claims it conducts over 100 million calls per year to verify and update its database. The dataset is up to date as of 2021.

With the NETS data as our foundation, we conducted rigorous due diligence, data cleaning, and re-coding. During this process, we identified, verified, and at times corrected the base data. This process required collecting and leveraging information from a wide array of sources that include, but are not limited to, regulatory filings, corporate information, media coverage, Bureau of Economic Analysis, and US Census Bureau.

In addition, because the 2021 dataset had notable discrepancies from the 2017 dataset, we conformed the two datasets to the best of our ability to ensure there wasn’t over or undercounting of investments and purged investments that are no longer valid. Any errors in the dataset are either due to our inability to verify based on open sources or our oversight.

For employment figures, we relied exclusively on the D&B dataset, even though we are aware of some discrepancies between the employment data and public employment figures on companies’ websites. As a result, we did a random sampling of companies to compare job figures and did not detect a pattern of jobs inflation in the D&B data. We believe the job figure variances likely end up averaging out reasonably close to reality.

For the sales of multi-entity companies, D&B only provides data for the parent company and not for each individual entity. Therefore, we allocated the company’s sales revenue based on the proportion of employees in each entity to the total employees of the parent company.

Throughout our data verification process, we took a conservative approach to maintain baseline data accuracy and worked to avoid inflating the figures to the extent possible. Of course, some deviation from the economy in real time is inevitable as this set of data is very granular and the American economy is dynamic and constantly changing.

We also have to accept some margins of error—for instance in the job figures—because the underlying data cannot be entirely free of error. The dataset is partly compiled from millions of human responses and interactions and constantly being updated in real time, and human errors are inevitable. Beyond these necessary caveats on data integrity, the final dataset we used is, to our knowledge, the best micro-level data we can get to provide an accurate representation of total Chinese FDI in the United States as of 2021.

We hope to receive feedback from users, especially if errors or omissions are noticed. Because this data is highly specific in terms of entity and location, users in local communities are well suited to “double check” the accuracy of elements in the product. A user may well live on the same block as a Chinese-owned entity featured in our product, so we strongly encourage the user to treat this product as a team effort between MacroPolo and you.

To provide feedback, please reach out to our product manager Ruihan Huang (rhuang@paulsoninstitute.org). This feedback loop will be important as we work to improve the product and make it as useful and accurate a representation of Chinese investment in America as possible.

Credits
Product Manager: Ruihan Huang
Research Assistance: Xuerong Shang, Miao (Irene) Qi, Lelan Hu
Design and Development: Annie Inacker, Yna Mataya, Chris Roche