There’s been renewed attention to trade policy, tariff measures, and bilateral agreements, including trade agreements between the United States and India. Our FRED graph above shows monthly US exports and imports to and from India over the past four decades. Both imports (orange line) and exports (blue line) have gradually risen since the 1990s.

Yet, they are a small share of total US imports and exports, as shown by our second FRED graph, below. As of January 2026, exports to India accounted for about 2.5% of total US exports, and imports from India accounted for 3% of total US imports.

Data in FRED also allow us to see the geographic distribution of trade with India across US states. Our FRED map below illustrates the value of exports to India as of 2022. States shaded in dark green were the top exporters, with export values between $776.8 million and $5.72 billion. Most of these states lie along the East and West coasts, with some high-exporting states in the Midwest (Illinois) and the South (Louisiana, Florida, and Georgia).

How these graphs and maps were created: First graph: Search FRED for “EXP5330” and select “U.S. Exports of Goods by F.A.S. Basis to India.” In the “Edit Graph” panel, open the “Add Line” tab to search for “IMP5330” and select “U.S. Imports of Goods by Customs Basis from India.” Click “Add data series.” Open the “Format” tab to change the color of the second line to orange and the line style to solid. Second graph: Search FRED for “EXP0015” and select “U.S. Exports of Goods by F.A.S. Basis to World.” In the “Edit Graph” panel, open the “Edit Lines” tab. Scroll down to “Customize data” to search for “EXP5330” and add “U.S. Exports of Goods by F.A.S. Basis to India.” In the “Formula” tab, apply formula b/a to get the share of exports to India in total U.S. exports. To calculate the share of imports from India in total U.S. imports, open the “Add Line” tab and search for “IMP0015” and select “U.S. Imports of Goods by Customs Basis from World.” In the “Edit Graph” panel, open the “Edit Lines” tab. Scroll down to “Customize data” to search for “IMP5330” and select “U.S. Imports of Goods by Customs Basis from India.” Apply the same formula as line 1. Then open the “Format” tab and change the color of the second line to orange and the line style to solid. Ensure that all four datasets are of the same format. Map: Search FRED for “Value of exports to India from” and click on the first option. Click “View Map” and, in the “Edit Map” section, change the number of color groups to 5 and choose the fractile method.

Suggested by Revathy Ramchandran and B. Ravikumar.

On the first Friday of the month, the Bureau of Labor Statistics releases data on the prior month’s job growth and the unemployment rate. It’s one of the most anticipated data releases. Financial market participants pay close attention to see whether the change in jobs is consistent with forecasters’ expectations. For example, the February 2026 report showed the economy shed 92,000 jobs, while forecasters anticipated modest gains of around 50,000 jobs, a difference of 142,000 jobs.

At first glance that may seem like a huge discrepancy, but putting these numbers in a broader context paints a slightly different picture.

First, the data are from a sample of businesses.

These economic statistics are derived from a sample of about 120,000 businesses. Because it is a sample, these statistics have what are known as confidence intervals.* The BLS reported that, for the recent 92,000 jobs lost, the 90% confidence interval ranged from a possible loss of -214,000 jobs to a possible gain of 30,300 jobs.

Second, the labor market is dynamic.

Underlying these headline statistics is a very dynamic labor market where millions of people are changing jobs every month. The FRED graph above plots total nonfarm hires and separations over the past 5 years. The values range from a low of around 5,000,000 to high of around 7,000,000. These statistics come from another BLS report called the Job Openings and Labor Turnover survey, which surveys around 20,000 establishments and is released toward the end of the month.

The second graph shows the difference between hires and separations along with changes in nonfarm payroll employment (i.e., the headline job growth number). For example, the “strong” January jobs report showed the economy adding 126,000 jobs, while the JOLTS data above indicate 5,105,000 people left their employer and 5,294,000 were hired by a new employer, for a net difference of 189,000. Given the confidence intervals of these two surveys, these numbers are not statistically different from one another.

So, when reading the headlines about changes in employment in the thousands, it’s useful to keep in mind a few facts about the millions of jobs in the labor market.

1. These are estimates with confidence intervals, which imply a wide range of possible outcomes.
2. The employment base is almost 160,000,000 nonfarm employees.
3. There are about 5,000,0000 separations and hires each month, and the headline jobs number is the difference between these numbers.

*A note about confidence intervals: A recent On the Economy blog post discusses the confidence intervals and statistical framework related to the unemployment rate. A recent FRED Blog post discusses confidence intervals related to US poverty estimates: “In short, a confidence interval is the level of certainty about the accuracy of the estimate. The Census Bureau routinely employs a 90% confidence interval for its estimates. As they explain, a 90% confidence interval provides a level of certainty that, if you measure poverty using the same procedure multiple times, the estimated value will be within the range 90 out of 100 times.”

How these graphs were created: Search FRED for and select “Total Separations: Total Nonfarm.” Click on the “Edit Graph” button in the top right corner and open the “Add Line” tab. Search for “JTSHIL” and choose “Hires: Total Nonfarm.” Adjust the date range to start January 1, 2021, to see the past 5 years. For the second graph, again search for and select “JTSHIL.” Click on “Edit Graph,” search for “JTSTSL” in the Customize data portion, and choose “Total Separations: Total Nonfarm.” Apply formula a-b. Open the “Add Line” tab and search for “All Employees, Total Nonfarm.” Change units to “Change, Thousands of Persons.” Edit the timeframe to start January 1, 2021, to see the past 5 years.

Suggested by John Fuller and Charles Gascon.

Every quarter, FOMC meeting participants submit their projections of key economic indicators. The committee releases the Summary of Economic Projections (SEP) containing the median, central tendency, and range of their projections for the civilian unemployment rate, headline and core personal consumption expenditures (PCE) inflation rates, real GDP growth, and the federal funds rate. Projections are generally provided for the current year, the next two years, and the “longer run.” In this blog post, we use ALFRED to look at several recent projections for the unemployment rate, core PCE inflation, and the federal funds rate through 2028.

The first ALFRED graph above presents the unemployment rate projections for the fourth quarters of 2026, 2027, and 2028, according to the SEPs released in March 2026, December 2025, and September 2025. Most recently, as shown by the red bar, the median FOMC participant projects that the unemployment rate will average 4.4% in Q4 2026 and drop to 4.3% over 2027 and to 4.2% in 2028. How does this stack up against previous projections for the same period? The December projections still had unemployment at 4.4% this year, while it ticked down to 4.2% in 2027 and stayed there in 2028. The September projections are the same as the current ones. In other words, there haven’t been any developments over the past six months that would suggest a materially stronger or weaker labor market in the near term than the median participant previously expected.

The second graph below contains the core inflation rate projections for the same years, and it has some more variation. While the median FOMC participant still expects inflation to return to target by 2028, projections of the inflation rate have been revised upward a bit for 2026 and 2027. In September, the median participant had projected core inflation to measure only 2.6% by the end of this year. However, over the past six months, that projection has shifted up by 0.1 percentage point to 2.7%. Similarly, the 2027 projections for March also shifted up 0.1 percentage point to 2.2%. This partially reflects stubborn inflation observed in 2025.

The final graph shows the median participant’s projections of the federal funds rate. The most recent federal funds rate projections are unchanged from what they were in September 2025 for each year from 2026 through 2028. You may notice that there is no green bar for the December release (or “vintage”). This is because the SEP projections for the federal funds rate were the exact same as the September vintage. We are able to see the March vintage, despite being the same, because the 2025 vintages also included end-of-year values for 2025. This means there was a change as we drop the 2025 observations for the March 2026 vintage.

How these graphs were created: Search ALFRED for “FOMC unemployment” and take the median projection. Click on “Edit Graph,” choose a bar graph, and add two bars with the same series again. Finally, select the proper vintage for each bar. Change the dates to 2026-01-01 to 2028-01-01. For the other two graphs, proceed similarly with “FOMC Consumption” and “FOMC Fed Funds Rate.”

Suggested by John Fuller and Charles Gascon.