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The Federal Reserve Bank of St. Louis is the center of the Eighth District of the Federal Reserve System. This District includes Arkansas, eastern Missouri, southern Illinois and Indiana, western Kentucky and Tennessee, and northern Mississippi.

Articles by FRED Blog

Currency arbitrage in the precious metals market: A gold rush?

4 days ago

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FRED’s as good as gold, and the FRED Blog has used London Bullion Market Association data to prove it. In fact, our previous post tracks gold prices and appraises the new gold bar at the St. Louis Fed. Now these gold prices are quoted in three different currencies—U.S. dollars, British pounds, and euros—which is a golden opportunity to discuss arbitrage.
Arbitrage is the risk-free purchase and sale of an asset to profit from a difference in price across markets. Because the gold fixing price is quoted in three different currencies at once, it’s possible that one could make a profit by buying and selling gold in different currencies and then selling the currencies. For example: buy gold in U.S. dollars, sell the gold right away in British pounds, and then convert

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The price and weight of a bar of gold : Raise the bar at the St. Louis Fed’s Economy Museum

11 days ago

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The U.S. Mint is missing one gold bar.
No. This isn’t the plot of a National Treasure sequel. It’s the latest addition to the St. Louis Fed’s Economy Museum: a 9.75” long, 1.5” tall bar of gold on loan from the Mint. Because the bar is 99.999% pure gold, it weighs 28 pounds! So, how much does a 28-pound gold bar cost?
Let’s use FRED data to figure out the price of this bar, which is on display, coincidentally, right across from the museum’s FRED exhibit.
Although some people see gold as a hedge against inflation, the graph above shows just how volatile the price of gold can be. Here, we have the “fixing price” of a troy ounce of gold in U.S. dollars in the London bullion market. London is the largest trading center for precious metals, and gold prices are reported

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What’s the state of your air quality? : State-level CO2 emissions

14 days ago

View on GeoFRED®
Many data series in FRED are versatile enough to be viewed in different ways. We’ve offered two perspectives so far on CO2 emissions at the national level. Today, we offer another perspective—emissions at the state level—thanks to GeoFRED. The map above shows total emissions for each continental U.S. state. These numbers depend on the number of residents, types of economic activity, and types of fuel used. So it’s no surprise that the most populous states are the ones emitting the most carbon dioxide, with the possible exception of Louisiana.
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Emissions from coal show something different. For example, the largest state, California, actually has one of the lowest coal-related emission levels. The relatively smaller states of Michigan, Missouri, and

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Data fluctuations from Manic Monday to Freaky Friday : FRED tracks weekdays per month, quarter, and year

18 days ago

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High-frequency data can include seasonal factors that affect economic activity. The timing of federal and local holidays changes each year, and weekends can fall all over the place in any given month. So not every period has the same number of business days. FRED now has data to help you sort that out.
Although it doesn’t account for holidays, the graph above shows the number of weekdays in a month. The data come from a release on domestic auto and truck production from the Board of Governors, which helps in cleaning the data of seasonal and predictable factors. The variation in weekdays is actually quite important, as it fluctuates between 20 and 23 days per month, which is a difference of over 10%.
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The second graph shows the number of weekdays

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Central banking since 1701 : Three centuries of Bank of England asset data

21 days ago

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The British have a history of recording excellent historical data, and we’ve already written a few related posts. Today we look at central bank assets for the Bank of England, founded in 1694. The graph above shows the assets as a share of GDP since 1701, which is a remarkable timeline, especially because it requires estimates of GDP from before the American Revolutionary War not to mention the Battle of Culloden!
This FRED graph shows us that assets in the 18th century reached a fifth of GDP before slowly receding. There were run-ups during the turmoil of the Great Depression, World War II, and the Great Recession and its financial crisis. For comparison, we added the (much shorter) corresponding series for the United States in red. It’s pretty amazing how well

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CO2 in the air: How does it get there? : CO2 emissions by fuel type and sector

25 days ago

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In a previous post, we looked at carbon emissions by fuel type broken down by different economic sectors. Today, we slice the data another way: We look at each economic sector and break down their emissions by fuel type. The first graph shows that the big emitters are transportation, electric power generation, and industry. Overall emissions have tended to decline, mostly thanks to a decline from power generation.
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The next graph shows the commercial sector. Overall, it emits relatively little CO2 and all fuel types seem to be on the decline. The recent surge in gasoline is most likely due to a reclassification of some sub-sectors into the commercial sector.
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The next graph, which shows emissions from the industrial sector, isn’t

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Have you heard the news? News can affect markets : The effects of economic news on expectations of future financial performance

28 days ago

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FRED’s all about data, which economists often use to conduct or test their research. So let’s look at some of that research…
In a recent St. Louis Fed working paper, economists Maximiliano Dvorkin, Juan M. Sanchez, Horacio Sapriza, and Emircan Yurdagul study how the arrival of news affects emerging markets. They use a logic from a 2006 paper by Beaudry and Portier to identify news events—aka “shocks.” The idea is to compare a financial index that captures the expected future performance of the economy with a measure of current performance. They identify “good news” when the expected performance variable improves without any proportional improvement in the current performance variable. On the flip side, they identify “bad news” when the expected performance variable

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Do government dollars drive recovery? : The conventional wisdom and data behind government spending during recessions

January 23, 2020

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Conventional wisdom suggests that, once you determine the appropriate level of government spending on goods and services, this level should grow more or less in line with the growth of the broader economy. Keeping the growth rate of government spending stable over the business cycle helps stabilize the business cycle.
But let’s see what the data show: The FRED graph above plots (1) the percentage change year-to-year of total government spending on goods and services and (2) the employment-to-population ratio. The three shaded regions in the graph represent periods of recession, each characterized by a rapid decline in employment followed by a gradual recovery. But the growth in nominal government spending wasn’t the same across these three recessions: It

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Working 9 to 5: Women make up more of the workforce : A look at women in the workforce by sector

January 16, 2020

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“Tumble out of bed and I stumble to the kitchen. Pour myself a cup of ambition…”  —Dolly Parton
The song and the movie 9 to 5 were released in 1980, back when women made up only 41% of employed workers in the U.S.
The Bureau of Labor Statistics has continued to collect the data and recently announced that women have broken through the 50/50 threshold in the U.S. workforce: That is, more women are employed than men. As the FRED graph above shows, this is the second time in U.S. history this threshold has been crossed. (Note that the December 2019 number is 50.0% in this graph, but a more exact value is 50.04%.)
FRED has more-specific data to help illuminate this event. To begin with, there have been more employed women than employed men in the private

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What fuels air pollution? : A look at CO2 emissions by fuel type

January 13, 2020

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The U.S. Energy Information Administration collects data on CO2 emissions, and FRED has recently added these data to its catalog. The graph above stacks the amount of CO2 emitted from the three main energy sources: coal, natural gas, and petroleum. Given the recent shift in energy sources, it shouldn’t be surprising the coal-related share of emissions has declined as the natural gas-related share of emissions has grown. Now let’s look at the picture across different economic sectors.
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Our second graph shows the sources of CO2 emissions from coal. Clearly, electric power generation creates the bulk of emissions. Industrial uses—the creation of steel, for example—contribute some emissions as well. The other sectors are negligible, with

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Native Americans in the U.S. : A look at county-level Native American population data

January 9, 2020

View on GeoFRED®
FRED has added a great deal of county-level data recently, including population estimates, which include various race and ethnicity categories. These new data are especially well-suited for viewing on a map. So, of course, we look to GeoFRED: The map above shows non-Hispanic Native Americans. Note that the color scheme relates to the total number of Native Americans in each county, not in proportion to the county’s overall population.
Clearly, large numbers of Native Americans live in the West, especially the Southwest, and in Oklahoma—for obvious historical reasons that involve displacement of Native peoples. There are also quite a few counties where hardly any Native Americans live: For example, there are none in the Kansas counties of Comanche and Cheyenne. On the

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Globalization affects India, too : A look at trade openness and the labor income share in India

January 6, 2020

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A previous post discussed the recent decrease in the labor share and increase in the capital share in GDP for many nations. Reasons for this decline in payments to labor include capital-augmenting technology growth, globalization, and changing skill composition of the labor force. In this post, we focus solely on India’s story.
In the 1990s, India began to implement a series of economic reforms that, among other things, helped open up the economy to trade and foreign investment. These policy changes reduced import tariffs and regulations, with the aim of making the economy more market-oriented. As a result, the labor share of India’s income decreased significantly.
The graph above shows that India’s trade openness, measured as the ratio of the sum of India’s

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A New Year’s resolution: More homemade food : Food prices for dining out vs. staying home

January 2, 2020

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Here at the FRED Blog we’re continuously looking for self-improvement opportunities, and our New Year’s resolution is to focus on home-cooked foods. Food at home is often fresher and healthier, but it’s also less expensive: The graph above shows that the cost of food away from home has been increasing much faster than the average of all foods. We’ll try to pepper the FRED Blog with healthier and tastier posts all through the year.
How this graph was created: Search for “CPI food,” check the two series, and click “Add to Graph.”
Suggested by Christian Zimmermann.

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Is the decline in manufacturing economically “normal”? : Deciphering the phases of economic development

December 30, 2019

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The FRED graph above tracks the proportions of employees working in three industries—construction, mining and logging, and manufacturing—since 1939. Construction (the blue line) has remained roughly horizontal. Mining and logging (the green line) has steadily declined. And manufacturing (the red line) has noticeably declined as well. This trend may look like weakness for the U.S. economy, but is it something to worry about?
Let’s take a step back: Historically, economic development has led to a declining share of workers in goods-producing sectors. The first sector to decline is agriculture,* whose workers moved to manufacturing and mining during the Industrial Revolution (which pre-dates our graph by a century or so). In the 19th century and beyond, the U.S.

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Move along. Nothing to see here. (Seriously.) : Searching for financial stress

December 26, 2019

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You may be relaxing over the holidays, but Team FRED Blog feels a little contrarian, like that uncle you can never agree with. So let’s talk about stress.
FRED offers three series from different regional Federal Reserve Banks that are intended to alert us to financial stress. All three indices use available data from the financial sector to try to establish an aggregate that highlights the level of risk in that sector, with higher values showing more stress.
The good news? Today, things are looking pretty steady. You could even say that there’s nothing to see here. At least as far as financial stress goes.
But the data overall show a couple of things quite clearly: The Great Recession was definitely financial in nature, with great financial stress, whereas the

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Shop till your drop…your credit score : Credit card delinquency rates

December 23, 2019

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You may be out buying last-minute presents, but the elves here at the FRED Blog are still at work contemplating credit card delinquency rates. It’s not the most festive topic, but there are at least a few interesting observations.
The graph above shows delinquency rates that range from slightly below 2% to slightly below 7%. This range could seem high, given these are unsecured loans: that is, without any collateral, such as a house to back up a mortgage loan. Or this range could seem low, given the relatively high interest rates that credit cards typically carry.
Beyond the obvious increase in delinquencies during recessions, we notice that smaller banks now have noticeably higher delinquency rates than the largest 100 banks. This is a new development. Have the

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How has the U.K stock market fared lo these past 300 years? : An historical data literacy lesson on U.K. stock prices

December 19, 2019

[embedded content]FRED offers some historical time series that the Bank of England has compiled, including the series shown above that tracks the price of stock market shares. The series starts way back in 1709 with the shares of the South Sea Company and the British East India Company. Other companies have been added and subtracted as they’ve entered and left the U.K. stock market. Just glancing at the graph reveals two things: First, the series is close to zero most of the time and then explodes. Second, there are wild fluctuations in recent decades.
For both these “observations,” though, there’s a mirage at work. Don’t worry: This optical illusion is common in very long time series. But let’s clear it up. Back in the 18th century, all prices, including share prices, were much

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An economic encomium for Sub-Saharan Africa : Good news from Ethiopia, Ghana, and Rwanda

December 16, 2019

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Sub-Saharan Africa has long been hindered by economic development traps: National economies have not been able to sustain significant growth for various reasons—such as high poverty leading to low savings, which  leads to low or negative economic growth. These days, there are some good reasons for optimism, as several countries have shown robust growth for a couple of decades. The FRED data in the graph above focus on three of these countries: Ethiopia, Ghana, and Rwanda, which have all more than doubled their per capita GDP in less than two decades.
Of course, not all African countries follow this pattern. But the example of the “Asian Tigers” (Hong Kong, Singapore, South Korea, and Taiwan) has shown that a few leading countries can help propel other countries

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Whither the workers? : How the working-age population affects productive capacity

December 12, 2019

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One way to measure the productive capacity of a country is to look at its working-age population. Members of this group are most likely to be available for productive employment that can sustain a country’s economic growth. The age range is generally considered to be 15 to 64, although some statistics start later. The graph above shows this population for the United States, Canada, and Japan.
Japan stands out in this trio: Its working-age population has been declining as a result of declining fertility and little immigration. These conditions make it difficult for Japan’s economy to grow. If sustained positive growth is the objective, Japan would need to improve the productivity of its smaller workforce much more than other countries with larger workforces would

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A lesson in measuring the federal debt : The many ways to calculate how much the U.S. federal government owes

December 9, 2019

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What’s the debt level of the U.S. federal government? The answer isn’t as straightforward as it may seem. A quick search on FRED for “federal debt” delivers the graph above, which shows the total level of the federal debt, in millions of dollars, at a quarterly frequency since first quarter 1966. The latest figure, as of the writing of this post, corresponds to second quarter 2019 and amounts to over $22 trillion. We can also express the federal debt as a percentage of GDP, like so:
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The federal debt reached 103% of GDP in second quarter 2019. These numbers, however, don’t properly reflect the amount owed by the federal government to private bondholders, since certain federal agencies (primarily, the Social Security trust funds) also hold federal

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Back and forth between buying and building houses : What’s behind two different responses in the housing market?

December 5, 2019

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Monetary policy affects interest rates, which affect mortgages, which affect decisions in the housing market. That may be easy to understand, but the housing data may not have such clear-cut patterns. Let’s see what FRED has to show us.
The red line in the graph is the average 30-year fixed-rate mortgage (right axis) from the early 1970s to 2019. The blue line in the graph is the ratio of housing starts built by contractors over housing starts built by owners (left axis) for the same period.
From 1985 to 2007, this ratio was generally flat, around 1.5, implying contractors built approximately 60% of housing starts. But during episodes of macroeconomic turbulence, the ratio has diverged from its historical average. But not in a consistent way… In the late 1970s and

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Take note: FRED has updated some series names

December 2, 2019

The FRED Team has just automated the process of how it names many of its data series. Because FRED aggregates data from 89 different sources, choosing the right name for any of the 627,000 data series is no small matter. Yes, the Bard wrote “A rose by any other name would smell as sweet.” But in the world of data, a confounding name can be a thorny problem.
Let’s choose a common example. The data series for the unemployment rate in the U.S. is collected by the Bureau of Labor Statistics (BLS). But the media can choose to report the data with a variety of names: national unemployment rate, civilian unemployment rate, official unemployment rate, harmonized unemployment rate, or U3.
The FRED graph below shows two series: the unemployment rate (from the BLS) and the harmonized

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Where is the U.S. growing? : Population growth in metropolitan statistical areas

November 25, 2019

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If you’ve looked at FRED data, you’ve probably seen the term MSA, which is “metropolitan statistical area,” which the Census defines as “a core area containing a substantial population nucleus, together with adjacent communities having a high degree of economic and social integration with that core.” It’s that high degree of economic integration that can make MSAs more comprehensive and relevant than just the specific governmental boundaries of cities and counties. In fact, MSAs often span several counties and sometimes straddle state borders. Think of it as a commuting basin… Or create your own metaphor!
The GeoFRED map here shows population growth for MSAs: Red is at the strong end of the growth spectrum and dark blue is at the weak end. What’s behind these changes

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Living in an uncertain world : More uncertainty data in FRED

November 21, 2019

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We’ve recently looked at different ways to measure uncertainty in the U.S. economy. Today, we look at international data on economic and policy uncertainty. While U.S.-level data were measured by looking at what newspapers report, the international data are based on quarterly reports from the Economist Intelligence Unit in each country. Having a single source for each country means one must be careful in interpreting the data: It contains quite a bit of noise, and there may be some idiosyncrasies for each country that make cross-country comparisons difficult: A report may focus on one particular aspect of a country, or it may be related to uncertainties in other locations that may affect that country.
The GeoFRED map above covers the third quarter of 2019. The

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The national growth quilt : GDP growth for each U.S. county

November 18, 2019

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What’s new from the Bureau of Economic Analysis? Real GDP data at the county level, which is now part of FRED’s ever-growing database. The data shown here are for 2015 and are still considered “beta”; but visit FRED in December and the data will be even more definitive.
The map above shows GDP growth for each county across the U.S. It looks like a patchwork quilt. Clearly, high and low and middle-ground growth rates are sprinkled across the nation, with very little uniformity within each state. (Though you could make a case that Nevada and Illinois have much more homogeneous growth across the state.)
View on GeoFRED®
The data are even more detailed than just overall county growth: They’re also divided into the government, services, and goods sectors. The second map

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The economics behind the motivation to migrate : Income gaps and inequality in the U.S. and Central America’s Northern Triangle

November 14, 2019

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In the past two years, the surge in undocumented immigrants from Central America’s Northern Triangle has been covered extensively by most news outlets. The stories of these migrants from El Salvador, Guatemala, and Honduras involve compelling and often perilous human experiences and intense reactions to the issues involved.
Apart from the political and social views about immigration, there are fundamental questions to ask that may have some economic answers: What is the main motivation for these migrations? And why are people willing to put themselves and their families at great risk to migrate to the U.S.?*
The graph above shows the ratio of per capita income in the U.S., the intended destination for many of these migrants, to per capita income in the three

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Chile’s been hot, politically and economically : Comparing growth and equality in South America

November 7, 2019

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If you’ve followed the evolution of Latin America for the past 25 or 30 years, you might be shocked by the recent unrest in Chile: The country’s economic growth has been stunning and widely seen as a harbinger of growth and development for all of Latin America, a region that has underperformed for many years. Chile’s growth is also touted as a confirmation that the openness and liberalization advocated by the “Washington Consensus” was the right prescription for the country and, by extension, for all of Latin America. Of course, this view has had dissenters. But regardless of ideological alliances or inclinations, most were surprised by the depth, pervasiveness, and persistence of the recent violent protests and demonstrations in Chile.
We hope FRED can add

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The rich borrow, too : Liability distribution across rich and poor households

November 4, 2019

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Over the past  few  weeks, we’ve used data from a dataset compiled by the Federal Reserve Board specifically to analyze the distribution of data across households. While our target so far has been assets, today we look at liabilities. How do rich and poor households borrow?
The graph above shows the total liabilities of four wealth classes: the top 1%, the next 9%, the next 40%, and the bottom 50%. At first glance, it appears that richer households hold less in liabilities. But if you hover over the graph, you see the actual percentages: the top 1% hold 4.6% of all liabilities, the bottom half 36%. One might assume the rich borrow less and the poor borrow more. But to better understand this, let’s take a look at the major categories on the liability side of

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It’s the great pumpkin FRED graph, Charlie Brown : Producer price index data for pumpkins and other treats

October 31, 2019

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Happy Halloween from the FRED Team!
Economic data can be scary and full of tricks…but it also includes some treats, like this fun FRED series on the price of pumpkins. And we couldn’t help ourselves: We used FRED’s frighteningly awesome graphing tools to “seasonally adjust” this graph in all the right colors.
This data series, by the way, is a recent addition to FRED: goods-level producer price index (PPI) data used in the consumer price index (CPI). The graph obviously looks deserted in places. That is, data points are missing pretty much throughout the year, except in September and October. But if you think about it, that’s when pumpkins are MUCH more popular on the market, right? One simple observation is that the price of pumpkins has been remarkably stable for

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Who holds what wealth? : More from the Survey of Consumer Finances

October 28, 2019

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A week ago, we reported on the evolution of wealth for different classes of households, divided by wealth quantiles: top 1%, next 9%, next 40%, and bottom 50%. This time we look at what their wealth consists of—again, leveraging the Federal Reserve Board’s Survey of Consumer Finances. The first graph shows the distribution of total assets across the four groups. As mentioned in the earlier post, the first three groups have a similar share of assets, despite having vastly different population sizes, with the bottom 50% having much less.
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The second graph shows the same distribution, but this time restricted to real estate assets. Now it looks quite different, with the top 1% holding significantly less (as a share) while the bottom 50% are doing

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