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Spooked by prices this Halloween? FRED shines a light on consumer and producer prices of candy and costumes

If you’ve been in any grocery stores, pharmacies, toy stores, or supermarkets recently, you’ve seen Halloween in all its glory. According to the National Retail Federation, Americans are expected to spend $9 billion on Halloween fun. How does the spike in consumption of candy and costumes affect prices for consumers and producers? As it turns out, the consumer price index appears to be more volatile than the producer price index.

The graph shows the consumer price index (CPI) in purple and the producer price indexes (PPI) in orange and black for candy and costumes. (Sadly, CPI for costumes isn’t available.) The PPIs don’t vary much, but the CPI does. After all, the prices of sugar, cloth, and other inputs exhibit less holiday-related seasonal variation than the prices producers can charge around those holidays. The PPI for costumes and vestments varies the least, which isn’t surprising: Fewer seasonal factors such as weather or harvest schedules impact the prices of inputs for costume production. The PPI for candy shows slightly more variation, yet displays less of a seasonal pattern than the CPI for candy, which tends to spike each March and September.

Candy prices are expected to rise in the spring and fall, as demand rises to fill Easter baskets and trick-or-treat bags. But savvy shoppers who consult FRED can see that the worst of the Halloween price hikes seem to end by October. It’s the early candy shoppers who often take the hit every September when prices are at their scariest.

How this graph was created: Search for “CPI Candy” and select the monthly, not seasonally adjusted series. From the “Edit Graph” panel, change the units to “Index,” selecting the date 2011-12-01 (to align with the next series). Then click “Add Line” and search for “PPI Chocolate” and select the relevant series. Click “Add Line” again and search for “PPI Vestments and Costumes” and select the relevant series. Change the start date to 2011-12-01.

Suggested by Maria Hyrc and Christian Zimmermann.

View on FRED, series used in this post: CUUR0000SEFR02, PCU3113531135, WPU0381044115

The business behind the trade balance Why trade deficits decrease in recessions and increase in booms

How does the trade balance relate to economic activity? The graph above shows the U.S. trade balance for goods and services as a percentage of GDP. Obviously, there was a surplus initially and now there’s a persistent deficit. Beyond that, it looks like every time there’s a recession, the trade deficit tends to decrease. (Or, if we go farther back in the past, the trade surplus tends to increase.) Obviously, many things affect the trade balance, but let’s see what FRED can show us about this relationship.

A good way to reveal how series may be correlated is to look at scatter plots. Instead of relating economic data to dates, scatter plots relate two data series to each other, one on each axis. The graph above does this with changes to the trade balance ratio on one axis and percent changes to real GDP on the other axis. What may look like a random assortment of dots actually has some information. Imagine the graph is divided into four quadrants and then consider where the dots are located. The upper right and lower left quadrants have fewer data points than the other two, highlighting that there is indeed a negative correlation: That is, when real GDP tends to increase, the trade balance tends to decline—that is, trade surpluses decrease or trade deficits increase.

Why is that? First, consider that the trade balance is net exports—that is, exports minus imports. Imports are highly correlated with GDP, while exports are less so. We see this in the graph above, which plots imports. This time, the upper left and lower right quadrants are the most populated. This highlights the positive correlation: That is, when real GDP tends to increase, imports do as well. Thus, over the business cycle, it is really imports that drive the trade balance: When the economy is doing well, producers need more intermediate goods, and imports are mostly intermediate goods. Also households consume more, and a share of those consumption goods are imports. If you graph exports, the correlation is much harder to see. Exports depend much more on what happens abroad, which isn’t that well correlated with domestic activity.

How these graphs were created: First graph: Search for “net exports” and select the quarterly series. From the “Edit Graph” panle, add GDP and apply formula a/b*100. Second graph: Use the first graph and change the sample period to start in 1954. From the “Edit Graph” panel, change the units to “Change.” Add a line by searching for “real GDP,” change its units to “Percent change,” open the “Format” tab, and switch the type to “Scatter.” Third graph: Use the second graph but with real imports in percent change.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: GDP, GDPC1, IMPGS, NETEXP

What a wonderful world Tracking global GDP

Here at the FRED Blog, we often describe the economies of individual countries, but what about the world as a whole? That calculation is more complicated than you may think. It’s not sufficient to just add up all the economies’ GDPs. First, they’re all denominated in different currencies, so you need to convert them into a common currency. Second, determining what exchange rate to use isn’t straightforward: Some are set at levels that don’t correspond to market forces, and even market forces may deviate significantly from purchasing power parity across countries. Thank goodness for the World Bank, which does all these calculations for us. Now, they do make some assumptions that people may or may not agree with; but if you’re looking for the long-run picture, these assumptions shouldn’t matter much.

We offer such a picture in the FRED graph above. We still had to modify it a bit, as the World Bank series is in current U.S. dollars. To remove the impact of inflation, we divided the figures by the implicit deflator for U.S. GDP. (This is also a debatable choice, as one would ideally use a deflator for world GDP. But no such deflator is available.)

The graph shows several phases: We see steady growth until about 2002. Then we see a stronger growth spurt. And then, since 2011, we see noticeably slower growth. While this data series is based on every economy in the world, it’s most influenced by the large developed economies. Some of the larger but less-developed economies, such as China and India, have grown a lot. The growth of the latter has slowed down a bit recently, and there’s talk of secular stagnation for the former, stemming from slower productivity growth and declines in the working-age population. Return to FRED in, say, ten years to see how things have evolved, in particular whether the other developing countries have become more significant forces in driving world economic growth.

How this graph was created: Search for “world GDP,” select the series with the longest sample period, and click “Add to Graph.” From the “Edit Graph” panel, add a series by searching for “GDP deflator” and selecting the implicit GDP deflator for the U.S. Apply formula a/b.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: GDPDEF, NYGDPMKTPCDWLD

Employer contributions The steep climb of supplemental wage benefits

Employees get paid, and their compensation can be divided into (a) wages and salaries and (b) supplements to wages and salaries. The Bureau of Economic Analysis defines supplements to wages and salaries as “employer contributions for employee pension and insurance funds and employer contributions for government social insurance.” This FRED graph shows the fraction of supplements to wages and salaries in total employee compensation from 1950 to 2017. (Note: A past FRED Blog post also discusses compensation, including non-wage benefits.)

We can see a clear trend here: The fraction of these supplements has increased consistently, from less than 8% of total compensation in 1950 to 18% in 1990. Since 1990, though, the series seems fairly stable, hovering between 17% and 20%. The Social Security tax rate exhibits a similar pattern and, thus, may be one of the causes behind this phenomenon. (Specifically, the Social Security tax rate was 1.5% in 1950, was about 5% in the mid-1970s, and has been 6.2% since 1990.)

How this graph was created: Search for and select “Gross Domestic Income: Compensation of Employees Paid: Wages and Salaries.” From the “Edit Graph” panel’s “Modify Frequency” option, choose “Annual.” Next, select the time frame option and change the start date to “1950-01-01.” From the “Edit Graph” panel’s “Customize Data” section, type “Compensation of Employees: Supplements to Wages and Salaries” and select this option to add a second series. In the formula box, enter b/(a+b) and click “Apply” to divide supplemental compensation by total compensation.

Suggested by Makenzie Peake and Guillaume Vandenbroucke.

Want to learn more about employee compensation?

  • Income for the top 1% has risen mainly because of higher executive compensation, esp. in the form of stocks, options, and bonuses.
  • Remember the 2018 teacher strikes in West Virginia, Oklahoma, Kentucky, Arizona, and Colorado? Wages there are lower than average, but so is the cost of living.
View on FRED, series used in this post: A038RC1Q027SBEA, A4102C1Q027SBEA

The usual suspects (behind U.S. trade deficits): China, Canada, Mexico, Japan, and Germany A long-term lineup of U.S. trading partners

According to economic theory, countries should export goods in which they have a comparative advantage in production and import those in which they don’t. For several years, the U.S. has been the number 1 importer and the number 2 exporter in the world. But the U.S. has recently imposed tariffs on imports from several foreign nations, citing the growing U.S. trade deficit as a main reason. So let’s use FRED to examine the overall picture of the U.S. trade deficit and the trade balance with its largest trading partners.

The first graph shows net U.S. exports, defined as the difference between total exports and total imports, divided by GDP. This net exports-to-GDP ratio has been negative since the late 1970s, when the U.S. started running a continual trade deficit. One explanation involves important sources of income the U.S. receives from abroad, as explained in a past FRED Blog post. This flow of foreign income allows the U.S. economy to consume more than it produces.

Exploring this and other theories in detail is beyond the scope of this post, but this persistent trade deficit over the past 40 or so years does lead to interesting questions involving the U.S.’s trading partners. For instance, is the trade deficit driven mostly by trade with one particular country?

The second graph plots the difference between exports and imports as a share of GDP with respect to the U.S.’s five largest trading partners: China, Canada, Mexico, Japan, and Germany. We can see right away that there’s a significant difference between the U.S. trade deficit with China and the U.S. trade deficits with the other countries. It’s also interesting to note that, in the 1990s, the largest share of the trade deficit originated from trade with Japan. But since China’s entry to the WTO in late 2001, the largest share is China’s. We also see that the U.S. had roughly balanced trade with Mexico in the early 1990s; but around 1994, coinciding with the implementation of NAFTA, the trade pattern changed and a noticeable deficit with Mexico emerged.

Now, is having persistently large trade deficits a bad thing? The answer to this question is not straightforward. There are several forces affecting the direction of trade with different countries, and a substantial amount of research in economics is dedicated to answering this question.

How these graphs were created: For the first graph, search for and select “Net Exports of Goods and Services, Billions of Dollars.” From the “Edit Graph” panel, add a second series to the graph: “Gross Domestic Product, Billions of Dollars.” In the formula box, type a*100/b. For the second graph, search for and select “U.S. Exports of Goods by F.A.S. Basis to China, Mainland (EXPCH).” From the “Edit Graph” panel, add a second series to the graph: “U.S. Imports of Goods by Customs Basis from Germany.” Then add the “Gross Domestic Product, Billions of Dollars” series again. In the formula box, type (a-b)*100/(c*1000). Then use the “Add Line” feature to repeat the above steps for the other countries (Canada, Mexico, Japan, and Germany).

Suggested by Asha Bharadwaj and Maximiliano Dvorkin.


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