The currency seems to have a negative effect…
There are two sides to every story, even for US-China foreign trade. Ever since China emerged to the world economy as a major manufacturing powerhouse, United States started to lose jobs in the manufacturing sector. Once upon the time firms of manufactured goods such as shoes, clothes even electronics, begun to move their production plants to China’s populous cities looking for an edge in low salaries. However, that trade story with China is oversimplified and misleading. Given that Donald Trump points to currency manipulation for blaming China for U.S.’ losses, I took data on Renminbi’s “depreciation” from January 2009 up to the end of 2015, and regressed it against the value of shipments of the American manufacturing sector. Yes, it does, the currency seems to have a negative effect on the value of shipments in the aggregate. Nonetheless, there are also gains on the U.S.’ side.
I wanted to see quickly to what extent a mere variation of the China’s currency would have an effect on U.S.’ manufacturing production. Then, the stats that I chose for analyzing this phenomenon were the value of shipments (see below for definition) made by U.S. manufacturing firm’s facilities . Then, I took the variation of the Renminbi as recorded by the U.S. Federal Reserve Bank. That is a ratio between nominal measures of the U.S. Dollar and the Yuan. The initial date is January of 2009 for all the time series. The final month is December of 2015.

By Catherine De Las Salas
During this period, China’s currency has been allegedly devaluated down to at least 5 percent. The results bolster Trump’s idea that China’s currency takes a toll in American manufacturing. Though, I do not aim at proving that for these reasons jobs have moved from U.S. to China. Nevertheless, there are also gains for some of the industries within the United States.
Finding statistical significance in these time series is hard:
Finding statistical significance in these time series is difficult. Just for the sake of the debate, I lowered the statistical threshold by amplifying the confidence intervals even down to 80 percent. That way I could achieve a bit of evidence of the trade impact of China’s currency on American manufacturing sector. Twelve items stood out of the rest. Positive coefficients could be found in Wood Products, Metal Machinery, Turbines and power transmission equipment, and Pharmaceutical goods. Note that statistical significance in these cases is down to 80 percent. So, if anyone ever would like to make a case out it, one has to be cautious with any assertion. Nevertheless, those coefficients are still positive and deserve some attention whenever generalizations come to drive the debate about U.S.-China’s trade.
On the other hand, negative coefficients showed up in eight items. The most important line, total manufacturing, registered a negative coefficient (-.42) with statistically significant at the 80 percent level. Total manufacturing excluding defense also classified with a negative coefficient of -.47. Nondurable goods revealed a negative coefficient of -.60 percent.
Below is the list of items and their correspondent coefficients alongside the confidence levels. Remarked in red cells are items with negative coefficients, whereas items with positive coefficients are noted in green cells. Here I also attached the database (Renmimbi US Manufacturing).
Results:
“Value of shipments covers the received or receivable net selling values, f.o.b. plant (exclusive of freight and taxes), of all products shipped, both primary and secondary, as well as all miscellaneous receipts, such as receipts for contract work performed for others, installation and repair, sales of scrap, and sales of products bought and resold without further processing. Included are all items made by or for the establishments from materials owned by it, whether sold, transferred to other plants of the same company, or shipped on consignment. The net selling value of products made in one plant on a contract basis from materials owned by another was reported by the plant providing the materials”.
Categories: Macroeconomics, Statistics and Time Series.
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