Federal Reserve Economic Data

The scale of US international trade as a share of the entire US economy peaked around 2011. Since then, US international trade has moderated.

In this post, we look at how this moderation affected international goods exports from the top goods exporting US states.

We rank US states by their cumulative exports since 1997, the first year of availability of state GDP data in FRED, where state GDP is necessary to compute a state’s exports to GDP ratio. The largest exporting states over the past three decades are

• Texas
• California
• New York
• Washington*
• Illinois

To see how important exports have been for these states, relative to the size of the state’s economy, we create ratios of state exports to state GDP. And that is what our FRED graph above shows. We also do the same for the national export-to-GDP ratio.

California, New York, and Illinois largely follow the national pattern, although California exhibits a somewhat more significant drop in recent years compared with the years immediately after the Great Recession.

Washington, however, experienced a much sharper drop in its exports-to-GDP ratio in recent years: It was just under 7% in 2024 compared with a peak of almost 21% in 2014. The trade dispute with China between 2017 and 2019 and loss of market share in top export categories, such as transportation equipment and agricultural products, contributed to this decline.

Texas is at the other end of the spectrum: Its export-to-GDP ratio peaked at about 20% in 2022, defying the national trend. The last decade’s strong oil and gas exports performance for Texas was a major factor driving this peak.

Although the national picture shows a gradual moderation in the export-to-GDP ratio since 2011-12, the picture for some individual states is considerably different.

*If you don’t measure cumulative exports since 1997, and look only at recent exports, then Washington is replaced by Louisiana.

How this graph was created: Search FRED for and select the annual series of “Exports of Goods for Texas.” From the “Edit Graph” panel, take the annual frequency aggregated as a sum, add “Gross Domestic Product: All Industry Total in Texas,” and apply the formula (a*100)/(b) to get percentages. Repeat these steps for other states. For the United States, use the same method and apply the formula (a*100)/(b*1000).

Suggested by Subhayu Bandyopadhyay and Hoang Le.

Mortgage loans allow households to buy a home or to borrow money against the value of a home they already own. With mortgage loans, the real estate is offered as collateral, a payback guarantee for the lender.

Our FRED graph above shows the billions of dollars lent by large US banks to consumers in newly issued mortgage loans. Data are available between the third quarter of 2013 and the second quarter of 2025. Each of the three lines represents a separate purpose for borrowing these funds:

• Purchasing a home (solid blue line)
• Refinancing the mortgage to secure more affordable repayment terms, including the interest rate on the loan (dashed green line)
• Refinancing the mortgage to receive a cashout for the difference between the new mortgage loan and the original loan (dashed orange line)

The relative importance of each purpose has changed over time.

Between 2013 and 2016, for every new dollar borrowed to purchase a home, another dollar was borrowed to refinance a mortgage loan. Between mid-2017 and mid-2019, new borrowing for home purchases outpaced refinancing. Between 2019 and  2021, during the COVID-19 pandemic, refinancings rose above new mortgages as homeowners took advantage of lower interest rates, despite many homeowners changing locations and moving into new homes.

Starting in 2022, when interest rates began to rise, mortgage refinancing quickly declined. Soon after, borrowing to purchase a home also declined, but not as much. As of mid-2025, the latest data available at the time of this writing, new borrowing to purchase a home was 2.7 times larger than borrowing to refinance a mortgage loan.

How this graph was created: Search FRED for and select “Large Bank Consumer Mortgage Originations: Purpose Type: Purchase.” Click on the “Edit Graph” button and select the “Add Line” tab to search for and select “Large Bank Consumer Mortgage Originations: Purpose Type: Refinance – Rate / Term & Other Refinance.” Don’t forget to click on “Add data series.” Repeat the last two steps to search for and add the third series: “Large Bank Consumer Mortgage Originations: Purpose Type: Refinance – Cashout.”

Suggested by Diego Mendez-Carbajo.

When the US Census conducts the monthly Current Population Survey on behalf of the Bureau of Labor Statistics (BLS), it asks households more than 200 questions about their employment status. One of those questions is “Do you currently want a job, either full or part time?”

As the BLS explains it: “People who want a job now are a subset of those not in the labor force.” The labor force is made up of (1) persons who are employed and (2) persons who are not employed but who had actively looked for employment in the four weeks prior to being asked about it.

Let’s put these concepts in the context of data available in FRED.

Our FRED graph above shows the percentage of persons who want a job out of the total pool of those who aren’t in the labor force. The blue line represents men, and the green line represents women.

The data, available since 1994, show very similar proportions for men and women. The rates ebb and flow with the business cycle, noticeably increasing during recessions (shaded areas in the graph). Over the past decade, an average of 6.6% of men and 5.1% of women who weren’t in the labor force would have liked to have gotten a job. Aside from the large spikes during the COVID-19 pandemic, these values have been fairly constant, suggesting the size of the pool of people interested in joining the labor market is relatively stable.

How this graph was created: Search FRED for and select “Not in Labor Force – Want a Job Now, Men.” Click on “Edit Graph” and use the “Edit Line” tab to customize the data by searching for “Not in Labor Force, Men.” Don’t forget to click on “Add.” Next, type in the formula (a/b)*100 and click on “Apply Formula.” Next, use the “Add Line” tab to search for and add “Not in Labor Force – Want a Job Now, Women.” Lastly, customize those data by adding “Not in Labor Force, Women” and applying the formula described earlier.

Suggested by Diego Mendez-Carbajo.