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How a year of NAFTA news affected exchange rates Markets overshoot in the short term

Exchange rates are among the most volatile macro series. When allowed to float, exchange rates are much more responsive to news and shocks than interest rates or the prices of goods and services. They are volatile at lower frequencies (e.g., monthly and quarterly) but especially volatile at higher frequencies (e.g., hourly, daily, or weekly). Moreover, exchange rates tend to “overshoot,” with much stronger responses to news and shocks in the short term than in the medium and long terms. This behavior, which is the opposite of Paul Samuelson’s Le Chatelier’s principle, was first formalized by Rudiger Dornbusch more than forty years ago.

A relevant example is the recent exchange rate behavior for Mexico and Canada, two of the U.S.’s main trading partners. The graph shows the daily exchange rate of the Mexican peso (left axis) and the Canadian dollar (right axis) in terms of U.S. dollars. And the three vertical lines identify three recent U.S. events: election day (Nov. 8, 2016) in green, inauguration day (Jan. 20, 2017) in purple, and the day the president announced his intention to renegotiate NAFTA (April 27, 2017) in blue.

During the recent presidential campaign, the Republican candidate clearly and ardently advocated restraining some international trade in general and terminating NAFTA specifically. However, the dominant view (both within the U.S. and worldwide) was that the Democratic candidate would win the election. The 2016 election result was a surprise for most observers and, as argued here, for investors as well. Between Tuesday, Nov. 8, and Thursday, Nov. 10, there’s a clear and significant jump in the peso-to-dollar exchange rate: from 18.435 pesos per U.S. dollar to 20.493. That’s more than 10% in just a few hours. The Canadian dollar also depreciated, but only about 1.3%, from 1.333 to 1.347. The responses of these exchange rates seem to suggest that, on Nov. 8, investors took seriously the prospect that NAFTA would be terminated or renegotiated and that such a change could reduce the value of investments in Mexico.

After the election, both exchange rates stabilized and even moved downward. However, the Mexican peso began a bumpy ride: It depreciated significantly, peaking on Jan. 20, 2017, the date the new administration took office. The peso then appreciated continuously but only until April, when the president used Twitter to announce his inclinations to terminate NAFTA. This position was reinforced by the fact that the U.S. also imposed preliminary countervailing duties on Canadian imports of softwood. Both the peso and the Canadian dollar depreciated with respect to the U.S. dollar. On April 27, 2017, the president announced his intention to renegotiate NAFTA. Eventually, both currencies appreciated.

Since September, though, both currencies have depreciated: 5% for the Canadian dollar and 9% for the Mexican peso. Two factors may be at work: a potential increase in U.S. interest rates and the news that renegotiating NAFTA has proven to be very difficult for all three countries.

How to make this graph: Search for the daily series of the Mexican peso exchange rate: DEXMXUS. From the “Edit Graph” menu, choose “Add Series” and search for the similar Canadian dollar exchange rate: DEXCAUS. From the “Format” menu, select the right axis for the Canadian exchange rate. In both series, select 3 for the line width. To create the vertical lines, open the “Add Line” tab and select “user-defined line”: Enter the date you want for both the start and end dates, and use values to fill most of the vertical space. (By the way, the exchange rates aren’t tracked on holidays or weekends, so there are some blank segments in the series.)

Suggested by Alexander Monge-Naranjo.

View on FRED, series used in this post: DEXCAUS, DEXMXUS

Employment Data: The Story Continues As with unemployment, there's more to employment than meets the eye

A recent FRED Blog post looked beyond the headline unemployment numbers and revealed how much more goes on behind the scenes. But unemployment isn’t the only complex economic indicator; payroll employment also has some intricate layers to it.

Payroll employment is a broad term that encompasses many kinds of employment in the U.S., one of which is the number of wage and salary workers paid an hourly rate. These workers are at least 16 years old, working either full- or part-time, and paid an hourly rate for their principal form of employment but are not self-employed. They comprised 58.7% of all wage and salary workers in 2016, according to a BLS Report. Workers paid by the hour are typically younger and about 26% of them are part-time workers, compared with only about 18% for all employed U.S. adults.

The graph tracks the number of these wage and salary workers receiving hourly pay according to their level of educational attainment. The purple areas at the top show those who didn’t finish high school, the pink shows those with a high school diploma, the green shows those with some college or an associate’s degree, and the blue shows those with a bachelor’s degree and higher. The largest proportion of workers have completed high school but no other schooling; a close second is those who have finished some college but don’t have a degree. A part of this trend may be explained by the fact that those with college degrees typically go on to salaried positions, while many high school graduates remain in jobs that pay by the hour. The pink and green areas also include students working while attaining degrees.

For those seeking employment during high school or college, a position that pays an hourly wage is simply more practical than a salary job, which often requires a commitment of several years. Frequently, those with less education are more likely to be considering returning to school to complete a degree, so they may prefer a job paid at an hourly rate for the flexibility it offers.

How this graph was created: From the list of releases in FRED, select “Characteristics of Minimum Wage Workers”; then select the first release table, “Number of Workers Paid Hourly Rates by Educational Attainment, Annual, Not Seasonally Adjusted.” Check the boxes next to the relevant series and click “Add to Graph.” In the “Edit Graph” section under the “Format” tab,  change the graph type to “Area” and stacking to “Normal.” Adjust the graph height to 800 and click “Apply.” Play with the colors.

Suggested by Maria Hyrc and Christian Zimmermann.

View on FRED, series used in this post: ACPRC1, ASDEC1, BADEC1, DCDEC1, HDNCC1, HS13C1, HS4NC1, L1HSC1, MADEC1, OCPRC1, PRDEC1, SCNDC1

Eat, drink, and be thankful Tracking prices of the Thanksgiving meal

Turkey, cornbread, sweets, and more. It’s no wonder 27% of Americans say their favorite holiday is Thanksgiving, according to a 2004 Gallup Poll. And the National Retail Foundation estimates that shoppers spend an average of about $300 per person during the long weekend. Some of that spending is on gifts and holiday sales. Here, we’ll focus on a costs specific to the Thanksgiving Day meal.

The International Monetary Fund tracks the global prices of a number of food items, and FRED has those data. The graph shows the change in price from one year ago for the four series most relevant to Thanksgiving: sugar, corn, poultry, and beverages. Sugar and corn are certainly the most volatile, with prices rising over 100% in a year on several occasions. However, prospects are good this year for a second helping of creamed corn: Prices in June were about 12% lower than they were a year ago (if you are sourcing on world markets), and the trend looks likely to continue.

Turkey, on the other hand, hasn’t fared so well this year. Before March 2017, prices hadn’t fluctuated by more than 20%; however, the change in poultry prices from June 2016 to June 2017 was over 32%. But don’t put away the baster and roasting pan just yet. The index measures the prices of poultry around the globe, not just turkey in the United States. Turkey is still comparatively cheaper than most other U.S. meats and alternatives. According to the USDA, turkey was $1.54 per pound in September, compared with $4.13 per pound for ham and $5.79 for beef roasts. So, although your turkey may be comparatively more expensive than last year’s, sticking to this meat dish may save you a substantial amount.

Those with a sweet tooth can also take a deep breath. June prices for sugar were almost 30% lower than a year prior. While damage done to sugar farms by recent hurricanes could limit future sugar production, recent USDA data show that the price continued to drop in September 2017. Sugar is consistently less volatile than other foods, so your traditional pies and cobblers will likely still find their way to the table.

How this graph was created: Search for “global price” and select “International Monetary Fund” as the source in the sidebar. This should give you all the relevant series on one page. (Otherwise, add them to the graph later.) Select the series you want and click on “Add to Graph.” From the “Edit Graph” tab, select units “Percent change from year ago” and click on “Apply to all.”

Suggested by Maria Hyrc and Christian Zimmermann.

View on FRED, series used in this post: PFANDBINDEXM, PMAIZMTUSDM, PPOULTUSDM, PSUGAISAUSDM

Where is subprime? Mapping the distribution of subprime borrowers by county

The “subprime credit population”—those with credit scores below 650—received much attention during and after the Great Recession of 2007-2009. Are these borrowers concentrated in certain areas or evenly distributed across the country? FRED’s county-level data from Equifax maps out the percentage of each county’s population that’s classified as subprime. The geographic disparities are quite large. At the high end, in Kenedy County, Texas, almost 56% of the population has a subprime credit score. At the low end, in Hooker County, Nebraska, only 3% of the population has a subprime credit score. Overall, the subprime population is more common in Southern states, but there are exceptions. Big Horn County, Montana, is 35% subprime, resembling Hardin County, Texas, and Marshall County, Tennessee. But some of Big Horn’s neighboring counties in Montana—for example, Carbon County (16%) and Yellowstone County (23%)—have much smaller subprime populations.

How this map was created: From GeoFRED, select county-level data and choose “Equifax Subprime Credit Population” in the drop-down menu.

Suggested by Guillaume Vandenbroucke.

The full banana of the labor market An update on the Beveridge curve

Three and a half years ago, we published a blog post about the Beveridge curve featuring the graph above, which shows how job vacancies and unemployment relate to each other. Each dot represents their values at a particular date. Beveridge’s theory is that these two measures don’t form a kinked line along the axes in a scatter plot, but rather a banana shape. This shape occurs because of delays and frictions in the job market: Vacancies and job seekers take time to intersect, as there may be mismatches in terms of job location and qualifications, for example. The graph above doesn’t show the expected full banana because the available sample period just wasn’t long enough. So, we revisit this idea by updating the graph, shown below. The banana, although not very smooth, is now complete.

How this graph was created: Search for “job openings” and add the series to the graph. From the “Edit Graph” section, add the second series by searching for and adding “civilian unemployment.” From the “Format” tab, choose “Scatter” for graph type. To connect the dots, choose a non-zero line width in the settings of the first series, which is where you can also adjust the size of the dots.

Suggested by Charley Kyd and Christian Zimmermann.

View on FRED, series used in this post: JTSJOR, UNRATE


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