Inflation reflects how prices of goods and services in the economy are changing. One measure of inflation is the consumer price index (CPI), which is the common headline number reported in the media.

The numbers for the CPI are released monthly, so it can be hard to tell what the CPI is doing on a daily or weekly basis. But what if there were prices you could observe directly that would serve as a closely related proxy for the CPI?

The FRED graph above shows that the CPI for all items and the CPI for sugar and sweets move similarly. Another way to say this is that these two price indices are highly correlated. Since 1947 the correlation is 0.99, and since the middle of 2020 the correlation is 0.97. Having a positive correlation that’s this close to 1 means that, as the CPI for sugar and sweets increases, so does the CPI for all items.

So, are price changes for sugary treats an indication of price changes overall? Well, this correlation between the two indices might be spurious. As an earlier FRED Blog post described it, “because time series can exhibit a common trend, it becomes difficult to interpret whether there is a relationship between them beyond that common trend.”

One way to investigate potential spurious correlation is to see if there is also a correlation in the growth rates of the two variables. We do this in our second graph by plotting the growth rate from the month prior for both price indices.

The correlation between the growth rates is 0.97 since 2020, which suggests this correlation is sound and not spurious. So, you could track the prices of candy or cookies on a daily or weekly basis at the grocery store to gauge what’s going on with the CPI for all items.

How these graphs were created: First graph: Search FRED for and select the “CPI for All items” series. In the “Edit Graph” panel, use the “Add Line” tab to search for and select “CPI Sugar and Sweets.” To normalize the data, selecte the last option in the the “Units” dropdown menu: “Index (Scale value to 100 for chosen date)”; choose 1990-01-01 and click “Copy to All.” Display the graph since 1947-01-01, which is the common start of the two series. Second graph: From the first graph, choose Units “Percent Change,” click “Copy to All,” and display the graph since 2000-01-01.

Suggested by B. Ravikumar and Amy Smaldone.

Different interest rates are involved in the monetary policy process: The federal funds rate (FFR) gets most of the news headlines, but deeper reporting refers to the interest rate on reserve balances (IORB) and the discount rate, as well as something called the overnight reverse repurchase agreement (ON RRP) rate. At first glance, the relationship among these rates might be difficult to parse; so let’s take a moment to sort it out.

The target range for the effective FFR is set by the FOMC, while other rates tend to be determined by market forces. Rather than set an exact number, the FOMC sets a range and aims to keep the effective FFR in that range.

To help maintain the rate in this target range, the Board of Governors sets the IORB rate and the FOMC sets the ON RRP Rate to nudge the FFR up or down within the range. More information on these rates can be found in this FRED Blog post by Jane Ihrig and Scott Wolla.

The Discount Window is a facility through which banks can borrow directly from the Fed—typically as a last resort for banks that weren’t able to borrow from other banks or had insufficient cash on hand. The primary credit rate (often referred to as the discount rate) is the rate banks pay for borrowing from the Fed, a rate set by each Bank’s board of directors. It’s unlikely banks would borrow at higher market rates if they could borrow from their Federal Reserve Bank, which makes the discount rate an effective ceiling on the FFR target range.

The ON RRP rate, on the other hand, serves as a floor for the FFR as financial institutions (theoretically) wouldn’t lend funds for a rate below the ON RRP rate, since they would be able to earn a higher and risk-free interest by putting their money at the Federal Reserve instead of loaning it out. The above FRED shows that the FFR stays between the discount rate and the ON RRP.

Find more information on the relationship between these tools in this Page One Economics essay also by Jane Ihrig and Scott Wolla.

How this graph was created: Search FRED for federal funds rate and select the daily federal funds effective rate series. From the “Edit Graph” panel, search for and select “IORB.” Repeat for “Overnight Reverse Repurchase Agreements Award Rate” and “Discount Window Primary Credit Rate.” Restrict the date range to the past year.

Suggested by Jack Fuller and Nathan Jefferson.

Economics studies what is produced, how, and for whom, but always under the assumption that the desire to consume goods and services motivates work and trade. Real, per capita consumption is often the most informative consumption measure because it adjusts for inflation and population growth. Total nominal consumption would tend to rise as the price level or population rises, even if individuals aren’t consuming more.

The FRED graph above shows that real, per capita consumption and each of its components—durable goods, nondurable goods, and services— have risen consistently over the long run, except for short retrenchments during recessions. It shows that average American consumption is more than 4.5 times as great at the end of 2023 than in 1950.*

In addition to these long-run trends and retrenchments during recessions, the first graph shows that consumption was unusually volatile during the COVID-19 pandemic. Total consumption and service consumption declined substantially, but there were seemingly less-pronounced movements in consumption of durable and nondurable goods. Unfortunately, the differences in scale among the four measures of consumption make it difficult to see relative changes in consumption expenditures.

The second FRED graph helps us see relative changes in real expenditures in these three components of consumption, which are normalized by dividing each by total consumption. There’s a definite decline in the share of nondurable goods consumption over the whole sample, as well as a large increase in the share of durable goods consumption. The share of service consumption is more complex: It rises from the 1940s to the early 1990s and then declines. Service consumption is also unusual in that the share of service consumption has often risen during recessions.

Consumption patterns change according to consumer preferences, technology, income changes, and credit availability. Chien (2015) shows that using nominal shares of service consumption, rather than real service consumption, indicates a fairly pronounced and steady rise in service consumption. In other words, a rise in the relative price of services drove much of the rise in service consumption. The reason service prices rose relative to nondurables or (especially) durables is that productivity increases were faster for manufactured goods (durables and nondurables) than for services. That is, technological advances improved our ability to make televisions, computers, and cars much more than they improved our ability to provide medical exams, give college lectures, or babysit children.

Finally, to better see the behavior of relative consumption around the COVID recession of 2020, our last FRED graph illustrates real, per capita expenditures from the first quarter of 2019 through the first quarter of 2021, with each series normalized to take the value 100 in the first quarter of 2020. During this episode, service consumption declined substantially, while consumption of nondurables declined modestly, and consumption of durables stayed steady. It’s easy to understand that consumers’ desires to avoid services (i.e., human contact for restaurant meals or massages) would reduce service consumption during COVID. If people aren’t going out, they might also postpone purchases of some nondurables, such as clothing and footwear. Finally, people stuck at home will still want entertainment, so purchases of computers, televisions, and durable exercise equipment remained fairly steady.

*Examples of durable goods are vehicles, furniture, computers, and software. Some non-durables are paper and plastic products, clothing, footwear, and food. Services include entertainment, healthcare, auto repairs, landscaping, and babysitting.

How these graphs were created:
First graph: Search FRED for and select “Real personal consumption expenditures per capita.” From the “Edit Graph” panel, open the “Add Line” tab to search for and select “Real personal consumption expenditures per capita: Goods: Nondurable goods.” Repeat for “Real personal consumption expenditures per capita: Goods: Durable goods” and “Real personal consumption expenditures per capita: Services.”
Second graph: From the first graph, use the “Edit Graph” panel’s “Edit line 2”: Under “Customize data” search for and select “Real personal consumption expenditures per capita” and apply formula a/b. Repeat for lines 3 and 4. Finally, click on “Edit line 1” and delete it.
Third graph: Start from the first. From the “Edit Graph” panel and then “Edit line 2,” select “Index (Scale value to 100 for chosen date or recession)” In the “units” box and select “US recession” with “2020-02-01 Start.” Select “Copy to all” to the right of the units selection. Click on “Edit line 1” and delete it. Above the graph, select “2019-01-01” and “2021-01-01″ as the sample dates.

Suggested by Christopher Neely.