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Policy Hub: Macroblog provides concise commentary and analysis on economic topics including monetary policy, macroeconomic developments, inflation, labor economics, and financial issues for a broad audience.

Authors for Policy Hub: Macroblog are Dave Altig, John Robertson, and other Atlanta Fed economists and researchers.

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February 25, 2019

Tariff Worries and U.S. Business Investment, Take Two

Last summer, we reported that one fifth of firms in the July Survey of Business Uncertainty (SBU) were reassessing capital expenditure plans in light of then-recent tariff hikes and retaliation concerns. Roughly 6 percent had already cut or deferred capital spending as a result of tariff worries.

Since then, tariff hikes and trade policy tensions have continued to mount, as recounted in the Peterson Institute's Trade War Timeline. U.S. stock market volatility also rose sharply in the last four months of 2018, partly in reaction to trade policy concerns. These developments led us to pose another round of questions about trade policy and investment in the January 2019 SBU.

We first asked each firm if tariff hikes and trade policy tensions caused it to alter its capital expenditures in 2018 and, if so, in which direction and by how much. We use the responses to estimate the net impact of tariff hikes and trade policy tensions on U.S. business investment in 2018.

Exhibit 1: Estimated Impact of Tariff Hikes and Trade Policy Tensions on Gross Capital Investment Expenditures by U.S. Businesses in 2018

We estimate that tariff hikes and trade policy tensions lowered gross investment in 2018 by 1.2 percent in the U.S. private sector and by 4.2 percent in the manufacturing sector. The larger response for manufacturing makes sense, given its relatively high exposure to international trade. In constructing these estimates, we consider firms that raised and lowered investment due to trade policy, and we weight each firm by its size.

To estimate the dollar impact of trade policy developments, we multiply the percentage amounts by aggregate investment values. The resulting amounts for U.S. business investment in 2018—minus $32.5 billion for the private sector and minus $22 billion for manufacturing—are modest in magnitude, in line with our forward-looking assessment last summer.

In January, we also asked forward-looking questions about the potential impact of trade policy worries on business investment. As reported in Exhibit 2 below, 20 percent of firms said they are reassessing their capital expenditure plans in 2019 because of tariff hikes and trade policy tensions, a share very similar to what we obtained in our forward-looking question last July. As before, manufacturing firms were more likely to reassess their capital spending plans due to trade policy concerns.

Exhibit 2: Share of Firms Reassessing Capital Expenditure Plans due to Tariff Hikes and Trade Policy Tensions

Exhibit 3 below speaks to the question of how firms have reassessed their capital expenditure plans. Here, too, results are similar to what we reported last summer, with one important exception. Among firms reassessing, more than half have either postponed or dropped some portion of their capital spending for 2019, compared to just 31 percent in July 2018. Thus, it appears that firms anticipate somewhat larger negative effects of trade policy developments on capital expenditures in 2019 than they did in 2018.

Exhibit 3: How Firms Are Reassessing Capital Expenditure Plans

All told, our results continue to suggest that tariff hikes and trade policy tensions have had a rather modest impact on U.S. business investment. Of course, tariffs and other trade barriers affect U.S. and foreign economies through multiple channels. Even if the near-term business investment effects of trade policy developments are modest in magnitude, trade barriers can disrupt supply chains, raise input prices, and lead to higher prices for consumer goods. That's important to keep in mind as the trade policy outlook remains murky.

January 17, 2018

What Businesses Said about Tax Reform

Many folks are wondering what impact the Tax Cuts and Jobs Act—which was introduced in the House on November 2, 2017, and signed into law a few days before Christmas—will have on the U.S. economy. Well, in a recent speech, Atlanta Fed president Raphael Bostic had this to say: "I'm marking in a positive, but modest, boost to my near-term GDP [gross domestic product] growth profile for the coming year."

Why the measured approach? That might be our fault. As part of President Bostic's research team, we've been curious about the potential impact of this legislation for a while now, especially on how firms were responding to expected policy changes. Back in November 2016 (the week of the election, actually), we started asking firms in our Sixth District Business Inflation Expectations (BIE) survey how optimistic they were (on a 0–100 scale) about the prospects for the U.S. economy and their own firm's financial prospects. We've repeated this special question in three subsequent surveys. For a cleaner, apples-to-apples approach, the charts below show only the results for firms that responded in each survey (though the overall picture is very similar).

As the charts show, firms have become more optimistic about the prospects for the U.S. economy since November 2016, but not since February 2017, and we didn't detect much of a difference in December 2017, after the details of the tax plan became clearer. But optimism is a vague concept and may not necessarily translate into actions that firms could take that would boost overall GDP—namely, increasing capital investment and hiring.

In November, we had two surveys in the field—our BIE survey (undertaken at the beginning of the month) and a national survey conducted jointly by the Atlanta Fed, Nick Bloom of Stanford University, and Steven Davis of the University of Chicago. (That survey was in the field November 13–24.) In both of these surveys, we asked firms how the pending legislation would affect their capital expenditure plans for 2018. In the BIE survey, we also asked how tax reform would affect hiring plans.

The upshot? The typical firm isn't planning on a whole lot of additional capital spending or hiring.

In our national survey, roughly two-thirds of respondents indicated that the tax reform hasn't enticed them into changing their investment plans for 2018, as the following chart shows.

The chart below also makes apparent that small firms (fewer than 100 employees) are more likely to significantly ramp up capital investment in 2018 than midsize and larger firms.

For our regional BIE survey, the capital investment results were similar (you can see them here). And as for hiring, the typical firm doesn't appear to be changing its plans. Interestingly, here too, smaller firms were more likely to say they'd ramp up hiring. Among larger firms (more than 100 employees), nearly 70 percent indicated that they'd leave their hiring plans unchanged.

One interpretation of these survey results is that the potential for a sharp acceleration in GDP growth is limited. And that's also how President Bostic described things in his January 8 speech: "For now, I am treating a more substantial breakout of tax-reform-related growth as an upside risk to my outlook."



November 6, 2017

Building a Better Model: Introducing Changes to GDPNow

Among the frequently asked questions on GDPNow's web page is this one:

Is any judgment used to adjust the forecasts? Our answer:

No. Once the GDPNow model begins forecasting GDP growth for a particular quarter, the code will not be adjusted until after the "advance" estimate. If we improve the model over time, we will roll out changes right after the "advance" estimate so that forecasts for the subsequent quarter use a fixed methodology for their entire evolution.

This macroblog post enumerates a number of minor changes to GDPNow that were implemented on October 30, when it began forecasting fourth-quarter real gross domestic product (GDP) growth. Here is a summary of the changes, intended to improve the accuracy of the GDP subcomponent forecasts:

  1. Services personal consumption expenditures (PCE). Use industrial production of electric and gas utilities to nowcast real PCE on electricity and natural gas. Use international trade data on travel services to forecast revisions to related PCE travel data.
  2. Real business equipment investment. Use/forecast data from the advance U.S. Census Bureau reports on durable manufacturing  and international trade in goods  that, previously, hadn't been utilized until the full reports on manufacturing  and/or international trade .
  3. Real nonresidential structures investment. Replace a discontinued seasonally adjusted producer price index for "Steel mill products: Steel pipe and tube" with a nonseasonally adjusted version. The index is used to construct a price deflator for private monthly nonresidential construction spending.
  4. Real residential investment. Use employment data for production and nonsupervisory employees of residential remodelers to help forecast real investment in residential improvements.
  5. Real change in private inventories. Use published monthly inventory levels in the U.S. Bureau of Economic Analysis's underlying detail tables 1BU and 1BUC after the third-release GDP estimate from the prior quarter to estimate inventory levels for a number of industries in the first month of the quarter forecasted by GDPNow.
  6. Federal, state, and local government spending. Forecast investment in intellectual property products for these subcomponents using autoregression models.

The first three columns of the following table decompose the official estimate of the third-quarter real GDP growth rate, and forecasts of the growth rate from the discontinued and modified versions of GDPNow, into percentage point contributions from the subcomponents of GDP.

As the table shows, the methodological changes did not have much of an impact on the final third-quarter subcomponent forecasts—apart from inventory investment, where the modifications lowered the contribution to growth from 0.80 percentage points to 0.60 percentage points—or on their accuracy. Nevertheless, the topline GDP forecast of the modified model (2.3 percent) was less accurate than the previous version (2.5 percent). In the discontinued version of GDPNow, an overestimate of the inventory investment contribution to growth partly canceled out underestimated contributions from each of net exports, government spending, and nonresidential fixed investment.

In the modified version, the inventory contribution was also underestimated and did not cancel out these other errors. The last two columns of the table show that all of the subcomponent errors of the modified model were at least as small as their historical average for the discontinued version. However, the topline GDP forecast was less accurate than average because of less cancellation of the subcomponent errors than usual. We hope that the cancellation of subcomponent errors in the modified model will be more similar to the historical average in the discontinued version in the future.

Although the methodological changes could have more of an impact than the table suggests, we do not expect them to have a substantial impact in general. For example, on October 30, the discontinued version of GDPNow projected 3.0 percent GDP growth in the fourth quarter, which was little different from the modified model forecast of 2.9 percent growth. We provide a more detailed explanation of the changes to GDPNow here . Going forward, this same document will document any further changes to the model and when we made them.

October 19, 2017

How Ill a Wind? Hurricanes' Impacts on Employment and Earnings

According to the Current Employment Statistics payroll survey, seasonally adjusted nonfarm payroll employment declined 33,000 in September. This decline was the first drop in employment since 2010 and followed a 169,000 gain in August. At the same time, seasonally adjusted average hourly earnings in the private sector increased 2.9 percent year over year in September. This increase in average wages was the largest since the end of the Great Recession in 2009. However, it seems likely that the decline in employment contributed to the rise in average hourly earnings. Why would a decline in employment contribute to an increase in average hourly earnings? We're glad you asked!

As noted by the U.S. Bureau of Labor Statistics, Hurricanes Harvey and Irma reduced employment in the payroll survey, whose reference period is the pay period that includes the 12th of the month. Hurricane Harvey first made landfall in east Texas on August 25 and again in Louisiana on August 30, and Hurricane Irma made landfall in south Florida on September 10. The storms forced large-scale evacuations and severely damaged many homes and businesses. For workers who are not paid when they miss work, being unable to work during the surveyed pay period means they are not counted in September payrolls.

To measure the size of Harvey and Irma's effect on payroll employment, we first looked at data from the Current Population Survey (CPS). We found that the bad weather forced about 1.5 million nonfarm workers who had a job during the September reference week to miss work. Of those, about 1.2 million were wage and salary earners, and about 760,000 of those were unpaid during their absence from work.

Our analysis indicates that September saw a shortfall in seasonally adjusted payroll employment between 200,000 and 300,000 jobs, suggesting that workers returning to work could result in a large rebound in payroll employment. (Not to get too far into the weeds, but our analysis involved regressing payroll employment growth on its lagged values as well as current and lagged seasonally adjusted changes in shares of workers who were not at work because of bad weather.)

What about average hourly earnings? Changes in average hourly earnings over time reflect both the effect of people getting pay raises and changes in who is working this month versus last month or last year. This latter effect can be large during recessions, when workers in lower-wage jobs are disproportionately more likely to be laid off. The absence of these workers from payrolls increases the average wage among the remaining employed workers, even if those remaining workers are not getting much of a pay increase (see this macroblog post for more discussion).

The September payroll survey depicted a particularly large decline in employment in the leisure and hospitality sector, which is significant because average hourly earnings in that sector are typically about 40 percent lower than overall average hourly earnings. In addition, from the CPS we see that the usual hourly earnings of workers not at work because of bad weather is much lower than for other workers. These data suggest that temporary absences from work because of bad weather likely put upward pressure on average hourly earnings, and some of that upward pressure could reverse itself as these workers return to their jobs. If the pace of average hourly earnings doesn't relax, however, then that would suggest more workers getting larger pay raises due to a tightening labor market.