The Atlanta Fed's macroblog provides commentary on economic topics including monetary policy, macroeconomic developments, financial issues and Southeast regional trends.
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March 05, 2015
Could Reduced Drilling Also Reduce GDP Growth?
Five or six times each month, the Atlanta Fed posts a "nowcast" of real gross domestic product (GDP) growth from the Atlanta Fed's GDPNow model. The most recent model nowcast for first-quarter real GDP growth is provided in table 1 below alongside alternative forecasts from the Philadelphia Fed's quarterly Survey of Professional Forecasters (SPF) and the CNBC/Moody's Analytics Rapid Update survey. The Atlanta Fed's nowcast of 1.2 percent growth is considerably lower than both the SPF forecast (2.7 percent) and the Rapid Update forecast (2.6 percent).
Why the discrepancy? The less frequently updated SPF forecast (now nearly a month old) has the advantage of including forecasts of major subcomponents of GDP. Comparing the subcomponent forecasts from the SPF with those from the GDPNow model reveals that no single factor explains the difference between the two GDP forecasts. The GDPNow model forecasts of the real growth rates of consumer spending, residential investment, and government spending are all somewhat weaker than the SPF forecasts. Together these subcomponents account for just under 1.0 percentage point of the 1.5 percentage point difference between the GDP growth forecasts.
Most of the remaining difference in the GDP forecasts is the result of the different forecasts for real business fixed investment (BFI) growth. The GDPNow model projects a sharp 13.5 percent falloff in nonresidential structures investment that largely offsets the reasonably strong increases in the other two subcomponents of BFI. Much of this decline is due to petroleum and natural gas well exploration; a component which accounts for almost 30 percent of nonresidential structures investment and looks like it will fall sharply this quarter. The remainder of this blog entry "drills" down into this portion of the nonresidential structures forecast (pun intended). (A related recent analysis using the GDPNow model has been done here).
A December macroblog post I coauthored with Atlanta Fed research director Dave Altig presented some statistical evidence that in the past, large declines in oil prices have had a pronounced negative effect on oil and mining investment. Chart 1 below shows that history appears to be repeating itself.
The Baker Hughes weekly series on active rotary rigs for oil and natural gas wells has plummeted from 1,929 for the week ending November 21 to 1,267 for the week ending February 27. The Baker Hughes data are the monthly source series for drilling oil and gas wells industrial production (IP) and one of the two quarterly source series for the U.S. Bureau of Economic Analysis's (BEA) estimate of drilling investment (for example, petroleum and natural gas exploration and wells). The other source series for drilling investment is footage drilled completions from the American Petroleum Institute, released about a week before the BEA publishes its initial estimate of GDP.
Chart 2 displays three of these indicators of drilling activity. The data are plotted in logarithms so that one-quarter changes approximate quarterly growth rates. The chart makes clear that the changes in each of the three series are highly correlated, suggesting that the Baker Hughes rig count can be used to forecast the other series. The Baker Hughes data end on February 27, and we can (perhaps conservatively) extrapolate it forward by assuming it remains at its last reading of 1,267 active rigs through the end of the quarter. We can then use a simple regression to forecast the February and March readings of drilling oil and gas wells IP. Another simple regression with the IP drilling series and its first-quarter forecast allows us to project first-quarter real drilling investment. The forecasts, shown as dashed lines in chart 2, imply real drilling investment will decline at an annual rate of 52 percent in the first quarter. This decline is steeper than the current GDPNow model forecast of a 36 percent decline as the latter does not account for the decline in active rotary rigs in February.
A 52 percent decline in real nonresidential investment in drilling would likely subtract about 0.5 percentage point off of first-quarter real GDP growth. However, it's important to keep in mind that a lot of first quarter source data for GDP are not yet available. In particular, almost none of the source data for the volatile net exports and inventory investment GDP subcomponents have been released. So considerable uncertainty still surrounds real GDP growth this quarter.
February 26, 2015
Are Shifts in Industry Composition Holding Back Wage Growth?
The last payroll employment report from the U.S. Bureau of Labor Statistics (BLS) included some relatively good news on wages. Private average hourly earnings rose an estimated 12 cents in January, the largest increase since June 2007. Even so, earnings were up only 2.2 percent over the last year versus average growth of 3.4 percent in 2007.
What accounts for the sluggish growth in average earnings? The average hourly earnings data for all workers is essentially the sum of the average earnings per hour within an industry weighted by that industry's share of employment. In this piece, Ed Lazear argues that a shift of the U.S. economy away from some high-paying industries to lower-paying industries may have contributed to dampened wage growth. Lazear specifically calls out the reduced share of employment in the relatively high-paying finance industry, at hospitals, and in the information sector as potential culprits. A shift in employment away from relatively high-wage jobs will put downward pressure on the growth in average wages.
To get some idea of the effect of industry composition on wages, I took the 2014 calendar year average wage for each industry group at the two-digit NAICS level and multiplied it by the share of employment in that industry in 2014 (admittedly, two-digit NAICS level of disaggregation is very coarse and masks a lot of potential shifts in job-types within industries). Summing across the industries gives an estimate of total average private hourly earnings in 2014. I then repeated the exercise, but using the 2007 industry shares of employment instead (see the chart).
Would average wages have been higher if we had the same mix of employment across industries as we had before the recession? The answer seems to be yes, but not much higher. If nothing had changed in the economy's industry employment mix since 2007, then average wages would have been about 12 cents higher.
This translates into a 16.8 percent increase in nominal wages between 2007 and 2014 versus a 16.2 percent increase if the actual industry employment shares where used, because the decline in the shares of employment in the relatively high paying industries Lazear cites has not been very large, and some higher-paying industries have seen growth. Moreover, some industries with below-average wages, such as retail trade, have experienced a decline in their share of employment as well.
February 23, 2015
Are Oil Prices "Passing Through"?
In a July 2013 macroblog post, we discussed a couple of questions we had posed to our panel of Southeast businesses to try and gauge how they respond to changes in commodity prices. At the time, we were struck by how differently firms tend to react to commodity price decreases versus increases. When materials costs jumped, respondents said they were likely to pass them on to their customers in the form of price increases. However, when raw materials prices fell, the modal response was to increase profit margins.
Now, what firms say they would do and what the market will allow aren't necessarily the same thing. But since mid-November, oil prices have plummeted by roughly 30 percent. And, as the charts below reveal, our panelists have reported sharply lower unit cost observations and much more favorable margin positions over the past three months...coincidence?
February 20, 2015
Business as Usual?
Each month, we ask a large panel of firms to compare their current sales with "normal times." In our February survey, the firms in our panel reported their sales were approaching normal. Indeed, on average, larger firms (those with 100 or more employees) tell us sales levels this month were right at normal. But smaller firms, although improving, are still lagging their larger counterparts (see the chart).
These qualitative assessments suggest a continuation of the trend we've seen in our quarterly quantitative data (these data are compiled at the end of each quarter). In December, our panel of firms reported sales levels about 2.7 percent below normal—virtually identical to the Congressional Budget Office's estimate of the output gap. Here, too, our survey data show that on average, sales of the larger firms in our panel were essentially back to normal, but smaller firms were still reporting ample slack (see the chart).
Our next quantitative assessment of slack in U.S. business is due for release on March 20.
February 17, 2015
What's (Not) Up with Wage Growth?
In recent months, there's been plenty of discussion of the surprisingly sluggish growth in hourly wages. It certainly has the attention of our boss, Atlanta Fed President Dennis Lockhart, who in a speech on February 6 noted that
The behavior of wages and prices, in contrast, remains less encouraging, and, frankly, somewhat puzzling in light of recent growth and jobs numbers.
So what's up—or not up—with wage growth? Using samples of matched worker-level wage data from the U.S. Bureau of Labor Statistics' Current Population Survey, chart 1 plots the annual time series of median 12-month growth rates in per-hour wages. Like most wage growth measures, this chart indicates that wage growth has been gradually increasing since the end of the recession, but growth remains quite a bit lower than before the recession began. Prior to the recession, the median growth rate of wages was around 4 percent a year. This growth rate declined to 1.7 percent in 2010 (as the incidence of wage freezes become much more prevalent, as shown in this research) and increased to 2.5 percent in 2014. For comparison, the chart also shows the annual growth in the Employment Cost Index's measure of wages. The trends in the two measures are broadly similar.
A previous macroblog post discussed details about the method of constructing the median wage growth data.
It's well known that wage growth varies across job characteristics such as occupation, industry, and hours worked as well as across worker characteristics such as education and age. For example, younger workers tend to experience higher hourly wage growth than older workers (even though their hourly wage tends to be lower), and part-time workers tend to have lower wage growth than full-time workers. We thought it might be interesting to look at wage growth for various job and worker characteristics. Are there any bright spots where the median growth in wages has approached prerecession levels?
The answer seems to be no, at least not for the set of characteristics we examined.
The following charts plot the annual time series of the median 12-month growth rate in the wages of workers with a given characteristic (occupation, age, etc.). Chart 2 depicts workers across three broad occupation groups: general-services jobs, production-oriented occupations discussed in our last macroblog post, and a category encompassing managerial, professional, and technical occupations (labeled “professional” in the chart).
Chart 3 shows the median year-over-year wage growth of workers employed in goods-producing versus service-producing industries.
Chart 4 shows the median growth in the wages of individuals working full-time versus those working part-time.
Chart 5 shows the median wage growth of workers with less than an associate degree and those with at least an associate degree.
Chart 6 shows the median growth in the wages of individuals between 16 and 35 years of age, those 36 to 55 years of age, and those over 55 years of age.
We can sum up our findings by saying that median wage growth is higher for some characteristics than others, and the recent trend in wage growth is generally positive across characteristics. But none of the characteristic-specific median growth rates we looked at are close to returning to prerecession levels. Lower-than-normal wage growth appears to be a very widespread feature of the labor market since the end of the recession.
February 12, 2015
Are We Becoming a Part-Time Economy?
Compared with 2007, the U.S. labor market now has about 2.5 million more people working part-time and about 2.2 million fewer people working full-time. In this sense, U.S. businesses are more reliant on part-time workers now than in the past.
But that doesn't necessarily imply we are moving toward a permanently higher share of the workforce engaged in part-time employment. As our colleague Julie Hotchkiss pointed out, almost all jobs created on net from 2010 to 2014 have been full-time. As a result, from 2009 to 2014, the part-time share of employment has declined from 21 percent to 19 percent and is about halfway back to its prerecession level.
But the decline in part-time utilization is not uniform across industries and occupations. In particular, the decline is much slower for occupations that tend to have an above-average share of people working part-time. This portion of the workforce includes general-service jobs such as food preparation, office and administrative support, janitorial services, personal care services, and sales.
The following chart compares the share of part-time employment for these general-service occupations with the share for production-type occupations (such as machine operators, fabricators, construction workers, and truck drivers).
The above chart suggests that if you talk to retailers or restaurateurs, they will say that they always relied pretty heavily on part-time workers. Their utilization increased during the recession, and it really hasn't changed much since then. But manufacturers or construction firms are more likely to say that part-time work is not that common, and although they did increase their utilization of part-time workers during the recession by quite a lot, things have been gradually returning to normal.
Why is the part-time share of employment declining more slowly in general-service occupations? The economy has been generating full-time general-service jobs at a much slower pace than in the past. Of the approximately 7.6 million full-time jobs created between 2010 and 2014, only about 17 percent have been in general-service occupations, versus about 32 percent of the 7.8 million full-time jobs created between 2003 and 2007. At the current rate of full-time job creation in general-service occupations, it would take more than 10 years for the part-time share of employment in general-service occupations to return to its prerecession average.
From the workers' perspective, a relevant question is whether these part-time utilization rates are desirable. Some people work part-time and do not currently want or are not available for full-time work (so-called part-time for noneconomic reasons, PTNER). Others are available and want full-time work but are working part-time because of slack business conditions or the unavailability of full-time jobs (so-called part-time for economic reasons, PTER). The following chart shows the share of employment in the general-service and production occupation groupings that is PTER and PTNER.
The chart indicates that most of the movement in the part-time share of employment is coming from people who want full-time work. In both cases, the share of involuntary part-time employment rose during the recession, but for general-service occupations it has been more persistent than for production jobs.
Why has the demand for full-time workers in general-service occupations been more subdued than for other jobs? As the following chart shows, wage growth for these occupations has been quite weak in the past few years, suggesting that employers have not been experiencing much tightness in the supply of workers to fill vacancies for these occupations. Presumably, then, the firms generally find it acceptable to have a greater share of part-time workers than in the past.
The overall share of the workforce employed in part-time jobs is declining and is likely to continue to decline. But the decline is not uniform across industries and occupations. Working part-time has become much more likely in general-service occupations than in the past—and a greater share of those workers are not happy about it.
By John Robertson, vice president and senior economist, and
Ellie Terry, an economic policy analysis specialist, both of the Atlanta Fed's research department
January 15, 2015
Contrasting the Financing Needs of Different Types of Firms: Evidence From a New Small Business Survey
The National Federation of Independent Business's (NFIB) small business optimism index surpassed 100 in December, a sign that small business' outlook on the economy has now reached "normal" long-run average levels. But that doesn't mean that everything is moonlight and roses for small firms. One question from the NFIB's survey (one that is not used in its overall optimism index) concerns a firm's ability to obtain credit. The survey asks, "During the last three months, was your firm able to satisfy its borrowing needs?" The chart below shows the net percent (those responding "yes" minus those saying "no") of firms reporting improving credit access.
The chart suggests that credit access has improved significantly since the end of the recession but that conditions still appear to be tougher than typical. Given the importance of small firms to employment growth, we at the Atlanta Fed have been particularly interested in monitoring financing conditions for small businesses. For this reason, we've conducted a regular survey of small businesses in the Southeast since 2010. In the fall of 2014, we joined forces with the New York, Philadelphia, and Cleveland Feds to expand and refine the small business data collection effort. The results of that survey are now available on our website and include downloadable data tabulations by different types of firms. Specifically, data are available by criteria including states, industries, firm size (in terms of revenue), and firm development stage.
Our previous small business surveys have focused on the experiences of young firms, so I found the new survey's tabulation by firm development stage of particular interest. For example, here's a summary of the experience of startups' ability to access financing markets versus that of mature firms.
First, what constitutes a startup? For comparison purposes, we draw the line (somewhat arbitrarily) at less than five years old. For mature firms, they not only have to be at least five years old, but they also must have at least 10 employees and hold some debt. When I picture a startup, I imagine a new restaurant owner purchasing tables and chairs, or a tech company manufacturing a prototype to market to potential investors. These types of firms are unproven and risky and tend to need relatively small amounts of money. Which begs the question: where are they going to get funds they need to grow? Before answering that question, let's examine the recent business performance of startups in the survey. About half of startups operated at a loss during the previous 12 months, but only about 20 percent had shrinking revenues. Most were either increasing the size of their workforce or had the same number of employees as a year ago. The top challenge reported by these young businesses was nearly tied between "difficulty attracting customers" (reported by 27 percent of firms) and "lack of credit availability" (reported by 26 percent of firms).
So how do those behind startups fund their businesses? In 2013, nearly half relied primarily on personal savings, whereas about 18 percent primarily used retained business earnings. Without a solid revenue history to prove their creditworthiness, financing was understandably difficult to come by. Only about 38 percent of startups received at least some financing, compared with 93 percent of mature firms. Many startups assumed it would be a fruitless endeavor—about one-fifth of them assumed they would be turned down, the cost would be too high, or the search would be too time consuming. The number of people who sought financing was about equal to those who were discouraged, and most were seeking less than $250,000.
Where did they apply? Their search was much broader than used by their counterparts at mature firms. Although both types of firms sought mostly loans and lines of credit, applications for products backed by the Small Business Administration, credit cards, and equity investments were notably higher for younger firms compared to mature firms. When it came to loans and lines of credit, there were large differences not only in what types of insitutions they submitted applications to, but also where they were most successful. Startups were mostly likely to apply at large regional and large national banks, but their approval rates were higher with smaller banks and online lenders (see the table).
The differences between young firms and mature ones is only one way to look at the data. The full report details variations by firm size, industry, and state. For more on general business and finance conditions of small firms, visit the small business trends dashboard.
January 09, 2015
Gauging Inflation Expectations with Surveys, Part 3: Do Firms Know What They Don’t Know?
In the previous two macroblog posts, we introduced you to the inflation expectations of firms and argued that the question you ask matters a lot. In this week's final post, we examine another important dimension of our data: inflation uncertainty, a topic of some deliberation at the last Federal Open Market Committee meeting (according to the recently released minutes).
Survey data typically measure only the inflation expectation of a respondent, not the certainty surrounding that prediction. As a result, survey-based measures often use the disagreement among respondents as a proxy for uncertainty, but as Rob Rich, Joe Tracy, and Matt Ploenzke at the New York Fed caution in this recent blog post, you probably shouldn't do this.
Because we derive business inflation expectations from the probabilities that each firm assigns to various unit cost outcomes, we can measure the inflation uncertainty of a respondent directly. And that allows us to investigate whether uncertainty plays a role in the accuracy of firm inflation predictions. We wanted to know: Do firms know what they don't know?The following table, adapted from our recent working paper, reports the accuracy of a business inflation forecast relative to the firm's inflation uncertainty at the time the forecast was made. We first compare the prediction accuracy of firms who have a larger-than-average degree of prediction uncertainty against those with less-than-average uncertainty. We also compare the most uncertain firms with the least uncertain firms.
On average, firms provide relatively accurate, unbiased assessments of their future unit cost changes. But the results also clearly support the conclusion that more uncertain respondents tend to be significantly less accurate inflation forecasters.Maybe this result doesn't strike you as mind-blowing. Wouldn't you expect firms with the greatest inflation uncertainty to make the least accurate inflation predictions? We would, too. But isn't it refreshing to know that business decision-makers know when they are making decisions under uncertainty? And we also think that monitoring how certain respondents are about their inflation expectation, in addition to whether the average expectation for the group has changed, should prove useful when evaluating how well inflation expectations are anchored. If you think so too, you can monitor both on our website's Inflation Project page.
January 07, 2015
Gauging Inflation Expectations with Surveys, Part 2: The Question You Ask Matters—A Lot
In our previous macroblog post, we discussed the inflation expectations of firms and observed that—while on average these expectations look similar to that of professional forecasters—they reveal considerably more variation of opinion. Further, the inflation expectations of firms look very different from what we see in the household survey of inflation expectations.
The usual focal point when trying to explain measurement differences among surveys of inflation expectations is the respondent, or who is taking the survey. In the previous macroblog post, we noted that some researchers have indicated that not all households are equally informed about inflation trends and that their expectations are somehow biased by this ignorance. For example, Christopher Carroll over at Johns Hopkins suggests that households update their inflation expectations through the news, and some may only infrequently read the press. Another example comes from a group of researchers at the New York Fed and Carnegie Mellon They've suggested that less financially literate households tend to persistently have the highest inflation expectations.
But what these and related research assume is that whom you ask the question of is of primary significance. Could it be that it's the question being asked that accounts for such disagreement among the surveys?
We know, for example, that professional forecasters are asked to predict a particular inflation statistic, while households are simply asked about the behavior of "prices in general" and prices "on the average." To an economist, these amount to pretty much the same thing. But are they the same thing in the minds of non-economists?You may be surprised, but the answer is no (as a recent Atlanta Fed working paper discussed). When we asked our panel of firms to predict by how much "prices will change overall in the economy"—essentially the same question the University of Michigan asks households—business leaders make the same prediction we see in the survey of households: Their predictions seem high relative to the trend in the inflation data, and the range of opinion among businesses on where prices "overall in the economy" are headed is really, really wide (see the table).
But what if we ask businesses to predict a particular inflation statistic, as the Philly Fed asks professional forecasters to do? We did that, too. And you know what? Not only did a majority of our panelists (about two-thirds) say they were "familiar" with the inflation statistic, but their predictions looked remarkably similar to that of professional forecasters (see the table).
So when we ask firms to answer the same question asked of professional forecasters, we got back something that was very comparable to responses given by professional forecasters. But when you ask firms the same question typically asked of households, we got back responses that looked very much like what households report.
Moreover, we dug through the office file cabinets, remembering a related table adapted from a joint project between the Cleveland Fed and the Ohio State University that was highlighted in a 2001 Cleveland Fed Economic Commentary. In August 2001, a group of Ohio households were asked to provide their perception of how much the Consumer Price Index (CPI) had increased over the last 12 months, and we compared it with how much they thought "prices" had risen over the past 12 months.The households reported that the CPI had risen 3 percent—nearly identical to what the CPI actually rose over the period (2.7 percent). However, in responding to the vaguely worded notion of "prices," the average response was nearly 7 percent (see the table). So again, it seems that the loosely defined concept of "prices" is eliciting a response that looks nothing like what economists would call inflation.
So it turns out that the question you ask matters—a lot—more so, evidently, than to whom you ask the question. What's the right question to ask? We think it's the question most relevant to the decisions facing the person you are asking. In the case of firms (and others, we suspect), what's most relevant are the costs they think they are likely to face in the coming year. What is unlikely to be top-of-mind for business decision makers is the future behavior of an official inflation statistic or their thoughts on some ambiguous concept of general prices.
In the next macroblog post, we'll dig even deeper into the data.
January 05, 2015
Gauging Inflation Expectations with Surveys, Part 1: The Perspective of Firms
Central bankers measure inflation expectations in more than a few ways, which is another way of saying no measure of inflation expectations is entirely persuasive.
Survey data on inflation expectations are especially hard to interpret. Surveys of professional economists, such as the Federal Reserve Bank of Philadelphia's Survey of Professional Forecasters, reveal inflation expectations that, over time, track fairly close to the trend in the officially reported inflation data. But the inflation predictions by professional forecasters are extraordinarily similar and call into question whether they represent the broader population.
The inflation surveys of households, however, reveal a remarkably wide range of opinion on future inflation compared to those of professional forecasters. Really, really wide. For example, in any particular month, 13 percent of the University of Michigan's survey of households predicts year-ahead inflation to be more than 10 percent, an annual inflation rate not seen since October 1981. Even in the aggregate, the inflation predictions of households persistently track much higher than the officially reported inflation data (see the chart). These and other curious patterns in the household survey data call into question whether these data really represent the inflation predictions on which households act.
Even if you're unfamiliar with the literature on this subject, the above observations may not strike you as particularly hard to believe. Economists are, presumably, expert on inflation, while households experience inflation from their own unique—some would suggest even uninformed—perspectives.
We have yet another survey of inflation expectations, one from the perspective of businesses leaders. We think this may be an especially useful perspective on future inflation since business leaders, after all, are the price setters. Our survey has been in the field for a little more than three years now—just long enough, we think, to step back and take stock of what business inflation expectations look like, especially in comparison to the other survey data.
Our initial impressions are reported in a recent Atlanta Fed working paper, and the next few macroblog posts will share some of our favorite observations from this research.
We have been asking firms to assign probabilities to possible changes in their unit costs over the year ahead. From these probabilities, we compute how much firms think their costs are going to change in the coming year and how certain they are of that change (see the table). What we find is that the inflation expectations of firms, on average, look something like the inflation predictions of professional forecasters, but not so much like the predictions of households.
But we also find that there is a significant range of opinion among firms, more so than the range of opinions that forecasting professionals express. Some of the variation among firms appears to be related to their particular industries and are broadly correlated with the uneven cost pressures shown in similar industrial breakdowns of the Producer Price Index from the U.S. Bureau of Labor Statistics (see the table).
So what we have now are three surveys of inflation expectations, each yielding very different inflation predictions. What accounts for the variation we see across the surveys? Our survey allows us to experiment a bit, which was one of the motivations for conducting it. We didn't just want to measure the inflation expectations of firms; we wanted to learn about those expectations. In the next few macroblog posts, we'll tell you a few of the things we've learned. And we think some of our initial findings will surprise you.
- New Atlanta Fed Series Shows Wage Growth Held Steady in May
- Approaching the Promised Land? Yes and No
- Will the Elevated Share of Part-Time Workers Last?
- Falling Job Tenure: It's Not Just about Millennials
- Atlanta Fed's Wage Growth Measure Increased Again in April
- myCPI: Getting More Personal with Inflation
- Sales Flexing Muscle at More Firms
- All Eyes on the Consumer
- Signs of Strengthening Wage Growth?
- What the Weather Wrought
- June 2015
- May 2015
- April 2015
- March 2015
- February 2015
- January 2015
- December 2014
- November 2014
- October 2014
- September 2014
- Business Cycles
- Business Inflation Expectations
- Capital and Investment
- Capital Markets
- Data Releases
- Economic conditions
- Economic Growth and Development
- Exchange Rates and the Dollar
- Fed Funds Futures
- Federal Debt and Deficits
- Federal Reserve and Monetary Policy
- Financial System
- Fiscal Policy
- Health Care
- Inflation Expectations
- Interest Rates
- Labor Markets
- Latin America/South America
- Monetary Policy
- Money Markets
- Real Estate
- Saving, Capital, and Investment
- Small Business
- Social Security
- This, That, and the Other
- Trade Deficit
- Wage Growth