Federal Reserve Economic Data

FRED recently added 7 data series about the business conditions and outlook of upstream oil and gas energy firms headquartered in the 11th Federal Reserve District.

In industry lingo, upstream refers to oil and gas exploration and production and the related services that support those activities. Geographically, the 11th District of the Federal Reserve consists of Texas, northern Louisiana, and southern New Mexico. The regional Reserve Bank in the 11th District is in Dallas, Texas, so the dataset itself is called the Dallas Fed Energy Survey.

The FRED graph above shows the three broadest indicators of business conditions captured by the survey:

• level of business activity (solid blue line)
• company outlook (dashed green line)
• uncertainty (dashed orange line)

The data are reported as diffusion indexes. You can read about another example of this type of index here. In short: The direction of change in the value of the index indicates rising or falling values of the underlying concept being assessed.

What do the indexes show?

The indexes of company outlook and level of business activity generally move in the same direction and at the same time. Between Q3 2024 and Q3 2025 (the last four observations available at the time of this writing), those indexes ranged between 7.1 and -17.6. That suggests relatively stable outlook and activity conditions. However, the index measuring uncertainty was above 40 during most of that time. This is noteworthy because, since 2016, when data are first available, the uncertainty index generally moved in the opposite direction of the indexes of business activity and company outlook. Perhaps that could be expected because oil and gas exploration and production activities are large scale and expensive operations that take many years to plan and execute. In short: Uncertainty undermines this industry.

How this graph was created: Search FRED for and select “Dallas Fed Energy Survey – Level of Business Activity.” Click on the “Edit Graph” button and select the “Add Line” tab to search for “Dallas Fed Energy Survey – Company Outlook.” Don’t forget to click on “Add data series.” Repeat the last two steps to search for and add “Dallas Fed Energy Survey – Uncertainty.”

Suggested by Diego Mendez-Carbajo.

In a recent FRED Blog post, we discussed how confidence intervals show the level of certainty about the accuracy of an estimate. In short: Wider confidence intervals signal more uncertainty.

Also, larger survey sample sizes increase the statistical accuracy of the data collected and allow data users to confidently compare apples to apples. Today’s post offers a bite-size example.

Our FRED graph above shows US Census estimates for median household income in three US counties:

• Pitkin, CO (solid blue line), home to the town of Aspen.
• New York, NY (dashed red line), the borough of Manhattan in New York City.
• Teton, WY (solid green line), home to the town of Jackson in the Jackson Hole valley.

Between 1989 and 2023, estimated median household income was frequently very similar for all three locations listed above: the coastal urban center and the two mountainous rural areas. But the number of residents was vastly different.

Population size influences the number of households sampled to collect income data: The more populous the county, the more households are sampled. So the estimated data are relatively more precise in more populous counties (e.g., New York County) than in less populous counties (e.g., Pitkin and Teton counties).

FRED also has data that capture the confidence intervals reported along with the estimated income data. The relative confidence interval for New York, NY, data can be as much as five times smaller than those for the Pitkin, CO, and Teton, WY, data, as seen in the graph below. That means far less uncertainty about the accuracy of the reported figures.

So, clearly, it’s best to be cautious when you try to make fair apples-to-apples data comparisons, including data from the Big Apple itself.

How these graphs were created: Search FRED for and select “Estimate of Median Household Income for Pitkin County, CO.” Click on the “Edit Graph” button and select the “Add Line” tab to search for “Estimate of Median Household Income for New York County, NY.” Don’t forget to click on “Add data series.” Repeat the last two steps to add the third series: “Estimate of Median Household Income for Teton County, WY.” Lastly, use the “Format” tab to customize the line styles. For the second graph, follow the same general procedure, except that each line is now composed of three series: Search first for “90% Confidence Interval Upper Bound…,” then “90% Confidence Interval Lower Bound…,” and finally the above mentioned estimate. Then apply the formula (a-b)/c on each line.

Suggested by Diego Mendez-Carbajo.

The US Census Bureau collects data and reports on the poverty level each year. Their statistical definition of poverty has to do with the affordability of food. As they describe, the Office of Management and Budget’s Directive 14 sets a money income threshold related to the after-tax spending by families on a food plan defined by the Department of Agriculture. At the time of this writing, the poverty income threshold for a family of four is $32,130.

The solid orange line in our FRED graph above shows the number of people, measured in millions, who lived in poverty between 1989 and 2023. In 2023, that number was estimated to be 40,763,043 persons. The dashed lines above and below the solid line show the boundaries (or range) of the 90% confidence interval associated with the poverty estimate.

Why does the Census provide a range for its poverty measure?

The Census Bureau estimates poverty rates using data from several different surveys. The regional sample size of the surveys impacts their reliability: In statistics, data obtained from small samples tend to be less reliable than data obtained from larger samples. The Census estimates take all this into account and include a 90% confidence interval for the reported figures.

What’s a 90% confidence interval?

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 this graph was created: Search FRED for and select “90% Confidence Interval Upper Bound of Estimate of People of All Ages in Poverty for United States.” Click on the “Edit Graph” button and select the “Add Line” tab to search for “Estimate of People of All Ages in Poverty for United States.” Don’t forget to click on “Add data series.” Use the “Add Line” tab again to search for and add “90% Confidence Interval Lower Bound of Estimate of People of All Ages in Poverty for United States.” Lastly, use the “Format” tab to customize the line styles.

Suggested by Diego Mendez-Carbajo.