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Trends in capacity utilization around the world

The capacity utilization rate of a country is constructed as the percentage of resources (i.e., labor and capital) used by corporations and factories to produce enough finished goods to meet demand. In normal times, factories tend to use around 80% of their available productive resources. (Want to learn more?)

The graph above shows the evolution of capacity utilization in the U.S. (light blue), Brazil (red), the U.K. (green), and Germany (purple) from 2000:Q1 to 2017:Q3 at a quarterly frequency. During this period, the average capacity utilization in the U.S. was the lowest in our sample, and it was below 80% most of the time. The average capacity utilization was highest in Germany, with an average of 85% (outside of recessions).

During the Great Recession, all countries experienced a sharp decrease in their capacity utilization. Brazil experienced the shortest decline, which occurred later than in the developed economies. This has often been referred to as “decoupling” of developing countries, which, despite being integrated in the global economy, have been more resilient to the crisis. In the case of Brazil, capacity utilization decreased from 85.1% in 2008:Q3 to 77.4% in 2009:Q1. In the U.S., it decreased from 80.4% in 2008:Q1 to 67.3% in 2009:Q2. After the crisis, capacity utilization in all countries except the U.S. went back to normal. Indeed, for the last two and a half years of the sample, capacity utilization has been declining in the U.S. This is also the case in Brazil. This trend contrasts with the one observed in Germany and the U.K., where capacity utilization has been increasing over much of the same period.

Low capacity utilization usually implies that shortages, bottlenecks, and inflation are not issues in most industries. This allows industries to increase manufacturing production without incurring significantly higher production costs. The data suggest that this is the case in the U.S. In the U.K. and Germany, however, demand seems to have picked up in the past two years, which could lead to an increase in prices in the European countries.

How this graph was created: Go to FRED and search for “Business Tendency Surveys for Manufacturing: Capacity Utilization: Rate of Capacity Utilization: European Commission and National Indicators for Brazil.” Go to “Edit Graph,” select “Add Line,” and add “Business Tendency Surveys for Manufacturing: Capacity Utilization: Rate of Capacity Utilization: European Commission and National Indicators for the United Kingdom.” Repeat to add Germany and the U.S. Go to “Edit Graph,” select “Format,” and choose “Recession shading” to be “On.”

Suggested by Ana Maria Santacreu and Heting Zhu.

View on FRED, series used in this post: BSCURT02BRM160S, BSCURT02DEQ160S, BSCURT02GBQ160S, BSCURT02USQ160S

Money makes the world go round…and goes round the world The impact of migration and remittances

According to the World Bank, 3.4% of the world’s population lives outside their nation of birth. For many, migration serves as a means of improving economic well-being, escaping violence and persecution, or finding education and employment. Although immigrants frequently separate from friends and family who remain in their place of origin, they often stay connected. In fact, those living abroad sent over $570 billion to their home countries in 2016, which is more than triple the amount of official worldwide development aid, according to the Pew Research Center.

The map above shows the proportion of remittance inflows to GDP for nations around the world in 2015. Several factors affect the data, which are based on two variables: the size of the economy and the magnitude of remittance inflows. Thus, smaller, poorer nations with large populations living abroad are likely to have larger remittance inflows-to-GDP ratios.

The size of a nation’s migrant population depends in part on the policies of other nations. Given that the U.S. is the largest destination for immigrants worldwide, U.S. policies, such as offering temporary protected status (TPS) to migrants from certain nations, can substantially affect the magnitude of remittance inflows. TPS is given to migrants from nations experiencing natural disaster or violent conflict and grants the right to work and remain in the U.S. until the status expires.

Ten countries currently have TPS, and FRED data are available for 7 of them. For Nepal, Haiti, Honduras, and El Salvador, remittances amount to more than 16% of GDP. Of the 40 nations with the highest remittance inflow-to-GDP ratios, 12 are, have been, or are requesting to be covered by TPS. Of the 40 nations with the lowest remittance inflow-to-GDP ratios, only 2 are or were covered by TPS.

The impact of migration policy and remittance inflows may seem small, but a study found that a 10% increase in per capita remittance inflows leads to an average decrease of 3.5% in the number of people living in poverty in the home country. The same study found that “a 10% increase in the share of international [e]migrants in a country’s population will lead to a 2.1% decline in the share of people living on less than $1.00 per person per day.” Through entrepreneurship, cultural exchange, and employment, emigrants can prove beneficial to the economies of their home countries. Look for future posts that examine the effects on the host country.

How this map was created: From GeoFRED, select “Nation” as the region type, then look for data on “Remittances.”

Suggested by Maria Hyrc and Christian Zimmermann.

View on FRED, series used in this post: DDOI11ALA156NWDB, DDOI11USA156NWDB, DDOI11ZWA156NWDB

Despite the recovery, paying the mortgage can still be a hurdle Comparing mortgage, credit card, and commercial real estate delinquency rates

It’s widely believed that the burst of the housing bubble triggered the Great Recession in 2007. That recession has been over for almost a decade, but the delinquency rate for single-family residential mortgages remains higher than it was before the recession. The blue line plots this mortgage delinquency rate on a quarterly basis since 2002. The delinquency rate was 3.7 percent in the fourth quarter of 2017, which is nearly 2 percentage points higher than its average 2002-2007 value of 1.9 percent. This isn’t necessarily what we’d expect, given current conditions: The S&P/Case-Shiller U.S. National Home Price Index reached its all-time peak in December 2017, and the average mortgage rate reached its all-time low in 2013 and has remained relatively low since. In addition, the economy is booming and the current unemployment rate is only 4.1 percent.

Moreover, this elevated mortgage delinquency rate is a bit puzzling if you consider the recovery made by the delinquency rates for credit card debt and commercial real estate loans. These are plotted using the red and green lines, respectively. The credit card delinquency rate in the fourth quarter of 2017 (2.6 percent) is lower than it was before the recession, and the delinquency rate of commercial real estate loans (0.7 percent) is at an all-time low. Given that these rates have recovered and dropped below their pre-recession levels, there must be some underlying factors preventing a similar recovery in residential mortgage loans.

How this graph was created: Search for “delinquency” and select the three (not seasonally adusted) series. Click on “Add to Graph.” Then change the starting date to “2002-01-01.”

Suggested by YiLi Chien.

View on FRED, series used in this post: DRBLACBN, DRCCLACBN, DRSFRMACBN

There’s electricity in the air! But it’s not for sale The production of electricity is outpacing sales

If you follow the energy sector, you know we’re living through interesting times. Energy sources are going through a slow but steady transformation: from traditional fossil fuels such as oil and coal to natural gas, wind, and sun. Given these changes, new companies are entering the energy production industry.

The graph above shows that electricity production in the United States has steadily grown; and, about 10 years ago, it plateaued. Electricity sales, however, have barely increased in the past decades. What’s happening? The divergence between the two measures is, to a large extent, due to more and more electricity production never hitting the market. Many firms and even households produce their own energy for their own use. This could be energy extraction from byproducts of production such as biogas or burning waste or running one’s own wind or solar farm. The recent flattening of electricity production reflects the fact that electricity demand is not increasing as it has in the past, thanks to improved energy efficiency all around. A major reason is also that the U.S. economy continues its natural evolution from energy-intensive heavy industry toward more specialized energy-efficient manufacturing and services.

How this graph was created: Search for “industrial production electricity,” select the two series, and click “Add to Graph.” From the “Edit Graph” menu, choose units “Index,” which should default to the starting date of 1972-01-01. Then click on “Apply to all.”

Suggested by Christian Zimmermann.

View on FRED, series used in this post: IPG22111S, IPN22112MS

The cost of owing How rising interest rates can affect the federal government's debt payments

Rising interest rates mean higher interest rates on debt payments, which means it becomes more expensive to buy a home, buy a car, or even go to college. It also becomes more expensive for the federal government to finance its debt.

As interest rates rise, payments on federal government debt also increase. The FRED graph above shows federal government expenditures with interest payments since January 1990: As federal debt has risen, expenditures on interest payments have also risen. These expenditures also depend on interest rate movements: When interest rates fall, payments decrease for the same level of federal debt. The Federal Reserve tends to lower interest rates during recessions, and this translates to lower payments, as seen in 2001 and 2008. (The gray shaded bars represent recession periods.)

Conversely, when economic conditions improve, the Federal Reserve tends to raise interest rates and this leads to higher interest payments. The second graph illustrates these two forces behind the movements in federal interest payments: The blue line is the secondary market rate on the 3-month Treasury bill, a measure of the federal government cost of borrowing that tracks very closely the interest rate set by the Federal Reserve (the federal funds rate). The red line is a measure of total public debt.

In principle, these two series can help us disentangle the main driving forces behind increasing interest payments. But doing this is more complicated than it sounds: The reason is that the federal government issues debt at different maturities, and the Fed typically sets only short-term rates. The behavior of interest rates at longer maturities depends on market forces and expectations of future inflation, among other factors.

How these graphs were created: For the first graph, search for and select “federal government expenditures: interest payments”; set the starting date to 1990-01-01. For the second graph, search for and select “3-month treasury bill: secondary market rate” (the monthly series); set the starting date to 1990-01-01. From the “Edit Graph” menu, select “Add Line.” Search for “federal debt: total public debt” and click on “Add data series.” From the “Edit Lines” tab, under “Units,” select “Index (Scale value 100 for chosen date)” and set that date to 1990-01-01. Then, under “Customize data” in the “Formula” field, type “a/100” and click “Apply.”

Suggested by Miguel Faria-e-Castro.

View on FRED, series used in this post: A091RC1Q027SBEA, GFDEBTN, TB3MS


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