The March year-over-year import/export container count growth rate improved from last month, but the year-to-date growth remains in contraction.

Analyst Opinion of Container Movements

Simply looking at this month versus last month - this was a stronger month. The three-month rolling average declined and is in contraction.

Imports container counts give an indication of the U.S. economy's state and the soft data continues to indicate a weak economy. Exports are saying the global economy is weak as well.

Container data is consistent with other transport data indicating a weak economy.

This data set is based on the Ports of LA and Long Beach which account for much (approximately 40%) of the container movement into and out of the United States - and these two ports report their data significantly earlier than other USA ports. Most of the manufactured goods move between countries in sea containers (except larger rolling items such as automobiles). This pulse point is an early indicator of the health of the economy.

Consider that imports final sales are added to GDP usually several months after import - while the import cost itself is subtracted from GDP in the month of import. Export final sales occur around the date of export. Container counts do not include bulk commodities such as oil or autos which are not shipped in containers. For this month:

As the data is very noisy - the best way to look at this data normally is the 3-month rolling averages. There is a direct linkage between imports and USA economic activity - and the change in growth in imports foretells a real change in economic growth. Export growth is an indicator of competitiveness and global economic growth.

There is reasonable correlation between the container counts and the US Census trade data also being analyzed by Econintersect. But trade data lags several months after the more timely container counts.

Econintersect considers import and exports significant elements in determining economic health (please see caveats below). recession levels.

Containers come in many sizes so a uniform method involves expressing the volume of containers in TEU, the volume of a standard 20-foot long sea container. Thus a standard 40-foot container would be 2 TEU.

There is a good correlation between container counts and trade data (the US Census trade data is shown on the graph below). Using container counts gives a two-month advance window on trade data.

Inflation-Adjusted Year-over-Year Change Imports (blue line) and Exports (red line)

Caveats on the Use of Container Counts

These are extraordinary times with historical data confused by a massive depression and significant monetary and fiscal intervention by government. Further containers are a relatively new technology and had a 14 year continuous growth streak from 1993 to 2006. There is not enough history to make any associations with economic growth - and we must assume a correlation exists.

Further, it is impossible from this data to understand commodity or goods breakdown (e.g. what is the contents in the containers). Any expansion or contraction cannot be analyzed to understand causation.

Imports are a particularly good tool to view the Main Street economy. Imports overreact to economic changes much like a double ETF making movements easy to see.

Contracting imports historically is a recession marker, as consumers and businesses start to hunker down. Main Street and Wall Street are not necessarily in phase and imports can reflect the direction for Main Street when Wall Street may be saying something different. During some recessions, consumers and businesses hunkered down before the Wall Street recession hit - and in the 2007 recession the contraction began 10 months into the recession.

Econintersect determines the month-over-month change by subtracting the current month's year-over-year change from the previous month's year-over-year change. This is the best of the bad options available to determine month-over-month trends - as the preferred methodology would be to use multi-year data (but the New Normal effects and the Great Recession distort historical data).