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The FRED® Blog

The economics of greeting cards Can Valentine's Day dashes to the store help the industry?

Tomorrow is Valentine’s Day, a great opportunity to spread some love…of economics…and study the greeting card industry. A search for greeting cards yields 90 results! One of the more interesting is shown in the graph. Unfortunately, we have only annual data; a higher frequency could have helped us see how much the industry depends specifically on Valentine’s Day. But we can see that the revenue of this industry appears to be trending down. So, is the reason for the decline the rise of the Internet and mobile apps? Maybe. FRED data can’t reveal all the mysteries of the universe, so we leave it to the reader to explore. Yours truly, FRED.

How this graph was created: As mentioned, a search for “greeting cards” yields quite a few results. Click on the series you want to graph.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: REVEF511191ALLEST

Can businesses get loans these days? A look at the state of commercial lending by banks

Businesses often need money and one way they get it is through commercial loans from banks. We gauge this environment by graphing the total mass of loans banks have made to commercial entities. Of course, the fact that the current mass of loans is the highest it’s ever been is hardly surprising: The economy is growing and loan levels aren’t adjusted for inflation, so this measure is bound to keep increasing. For this reason, we’ll deflate this indicator with a proxy for the size of the economy: nominal GDP (i.e., not real GDP).

Now we have a better way to compare commercial lending conditions over time. Things are still looking rather good right now, but consider these two caveats: 1. Businesses have other ways to finance—say, through private loans or issuing bonds or stock in equity markets. These options may change over time, which probably explains why there was an upward trend in the early decades, when this sort of financing was building up. 2. This reported loan mass shows only the results of supply and demand, but not how difficult it is to get a loan (actual supply) or how much businesses want these loans (actual demand).

To evaluate loan supply conditions, the Federal Reserve conducts a survey of loan officers, asking them whether they tightened loans conditions and for whom. The graph below shows this, with higher values indicating tighter lending conditions. It’s very clear how recessions have led bank officers to be more careful with their lending. But right now, conditions seem to be pretty good.

How these graphs were created: Top graph: Search for “commercial loans.” Middle graph: First, use the top graph. Then go to the “Edit Graph” panel to add “GDP” to the first line, making sure to use the nominal measure. Then apply formula a/b. Bottom graph: Start afresh and search for “loan standards”; select the two series you want and click on “Add to Graph.”

Suggested by Christian Zimmermann.

View on FRED, series used in this post: BUSLOANS, DRTSCILM, DRTSCIS, GDP

Two tales of federal debt Why people disagree on the level of the federal debt

There’s much disagreement on whether the federal government’s debt is too high. Here are two ways of looking at this perfectly understandable question.

The top graph shows the federal debt as a share of GDP. You want to compute such a share because the federal debt over long horizons depends on the size of the economy. There’s been a marked increase in debt in response to the past recession, and it has leveled off at about 100% of annual GDP. Some consider that high. Some consider that too high.

The bottom graph multiplies the series above by the 10-year Treasury rate. This represents how much the debt costs, as a share of GDP. Here we see the cost is remarkably low—of course, thanks to low interest rates. Note that this is an approximation, as not all debt is in 10-year Treasuries and the issue dates vary greatly in the portfolio. But including other interest rates gives the same general picture. Looking from this angle, some consider the debt to be too low.

How these graphs were created: For the top graph, search for “federal debt” and the series of it as a share of GDP should be among the top choices. For the bottom graph, use the first graph and go to the “Edit Graph” section: Add a series to the first line by searching for “10-year treasury rate” and applying formula a*b/100.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: GFDEGDQ188S, GS10

They say nothing beats a home-cooked meal Comparing price inflation of food at home and away from home

The graph shows the evolution of two price indexes: food consumed at home and food served in a restaurant. It’s striking how the price of food served to you has kept increasing, while the price of food you prepare yourself has either increased more slowly or even decreased. In fact, the difference between these prices has increased by 61% over the sample period, meaning that the ratio of restaurant food prices to home food prices is 61% higher now than it was in 1953. What do we make of this? After all, the basic ingredient for both is the same: agricultural products. The difference is that restaurant meals also include a substantial service component: Other people prepare the food and serve it to you. While agriculture has benefited from big-time productivity enhancements, the same cannot be said for the manual labor provided in a restaurant. As real wages increase, the kitchen and wait staff become more expensive more quickly than the goods they prepare and serve, which is why our restaurant bills grow more quickly than our grocery bills. To be fair, we don’t usually pay ourselves to do our own grocery shopping, cooking, serving, and dishwashing. Or, for that matter, give ourselves a 20% tip.

How this graph was created: From the CPI release table, select the two series and click “Add to Graph.”

Suggested by Christian Zimmermann.

View on FRED, series used in this post: CUSR0000SAF11, CUSR0000SEFV

Interest rates for future centenarians Discount rates for evaluation of future values

FRED recently added high quality market bond yield curve data from the U.S. Treasury. These are interest rates computed from high-quality commercial bonds to reflect the market’s thinking about how much it’s discounting future incomes with minimal risk. The U.S. Treasury needs these measures to evaluate the current value of liabilities in pension funds. You do this properly by using various maturities—from 6 months to 100 years in 6-month intervals. This produces an interesting yield curve. We focus here on the 100-year example. Obviously, there’s no commercial bond out there with a 100-year maturity right now. The calculation intrapolates for the various maturities and in this case likely extrapolates. We’re wondering, though, how a 100-year discount rate rate could be useful for pension liability pricing, as no employee alive today would reasonably expect to receive a pension distribution a century from now. However, this can be useful for other purposes, such as evaluating the usefulness of infrastructure with long lifespans or the impact of climate change. Note also that this 100-year rate has been decreasing significantly, just as all the others have, showing that the current interest rate environment has an effect far into the future.

How this graph was created: Search for “HQM bond” and, surprisingly, the 100-year rate is among the top choices.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: HQMCB100YR


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