As we move past the first anniversary of the COVID-19 outbreak (and the associated recession and deflationary pressures), data watchers will no doubt need to incorporate stimulus checks, the unprecedented speed of economic normalization that we've witnessed, pockets of virus surges, and, of course, historic base effects into their forecasts. This will, indeed, be one of the most complicated periods of economic data we’ve seen in years. To help navigate these challenges, here are four broad rules to consider while assessing the increasingly complicated data in the coming months:
1 Limit your reliance on conventional growth metrics
2 Throw precision out the window—timeframes will matter more
3 Get granular on data releases
4 Remember that factors that supported the rebound in 2020 will also unwind, reducing support
1 Limit your reliance on conventional growth metrics
We’re probably several quarters (likely more outside of the United States) away from being able to return to the pre-coronavirus approach to analyzing economic data with basis point-level precision. The sheer magnitude of the pandemic’s impact on economies the world over effectively decimated any traditional concept of what an acceptable margin for error around estimates would look like: Recent economic prints such as March’s U.S. retail sales and employment data exceeded consensus expectations by a huge margin but drew only minimal market reaction. In the next couple of months, we believe traditional year-over-year (YoY) growth metrics will be rendered meaningless; for instance, U.S. retail sales could conservatively post a ~36% growth rate in April, while housing, inflation, and production are all expected to surge so aggressively that they’ll almost certainly distort any signal investors will typically receive by simply looking at growth rates.
It isn’t just base effects currently complicating the data. There are other distortions hampering visibility, including the complicating effects of volatile weather patterns, stimulus checks, delayed refunds, and regional differences in vaccine distributions and reopenings. In short, headline data isn’t producing a clean signal on growth and shouldn’t be interpreted that way.
2 Throw precision out the window—timeframes will matter more
If precise estimates don’t matter as much in the months ahead, what does? The simple answer is timeframes and the necessity for data to confirm that the Great Reopening is indeed sizable and has gained momentum. This is especially true for employment and inflation.
- Employment—The United States must see meaningful job gains over the summer or risk market disappointment for two reasons. First, given the composition of job losses during the pandemic, meaningful gains that coincide with the reopening have to corroborate improved activity in key discretionary services sectors and that the reopening heals the labor market quite quickly. Second, there are important ramifications for Q4: While U.S. policymakers could opt to extend unemployment benefits, our belief is that getting sufficient support for such a measure could prove to be more difficult than it was during the three prior relief packages, especially with the current push toward infrastructure spending already poised to add to expenditures. Consequently, the more meaningful the jobs recovery in Q4, the lower the likelihood that the type of permanent employment scarring that we’ve been concerned about will transpire. Key U.S. metrics to watch over the coming weeks include initial and continuing claims, as well as gains in the leisure and hospitality space.
- Inflation—We don’t think there’s much risk of market volatility related to upside surprises in the coming months: This development has been well telegraphed by global economists and policymakers, including the potential for upside surprises; however, problems may arise if inflationary pressures persist into the late summer, even at levels modestly above expectations. This will likely spark a repricing of sticky inflation risks and, correspondingly, markets could become increasingly tempted to test the U.S. Federal Reserve’s (Fed’s) stated resolve to tolerate an overshoot of price pressures, but, unfortunately, we won’t know this until we enter Q3.
Timeline for normalization
Source: Manulife Investment Management, as of April 9, 2021. For illustrative purposes only. Individual portfolio management teams may have different views and opinions that are subject to change without notice. Actual results could differ materially from those anticipated in forward-looking statements.
3 Get granular on data releases
As the economy reopens and new data sets arrive, make it a point to look beyond the headline figures—data components will, in some cases, matter more than the headline indicator.
For instance, we believe jobs gains in the leisure and hospitality spaces, a component of the monthly U.S. nonfarm payrolls, will be more critical than the headline number—in the current environment, it serves as a gauge of sector-level demand as economic activity picks up. Also, more important than headline jobs gains, a pickup in labor force participation rates during the Great Reopening would signal that labor supply is coming back online, thereby limiting wage growth—a key input into the inflation outlook.
Unsurprisingly, jobs in hospitality have followed activity
U.S. jobs, rebased, January = 100
Similarly, in U.S. housing, one area of focus would be months’ supply for existing home sales, or the number of months it would take for existing homes that are already on the market to sell under the current sales environment. Part of the recent surge in home prices can be attributed to plummeting supply, which is intuitive given most people are reluctant to move during a pandemic. The increasing inventory of homes available for sale should act as a pressure-release for home prices. By paying attention to months’ supply, we’re likely to have a better read of the overall picture for future prices and be well positioned to contextualize what we expect to be a temporary pause in rising house prices.
U.S. housing months' supply is at unsustainable lows
4 Remember that factors that supported the rebound in 2020 will likely also unwind, reducing support
A lot of focus on the U.S. economic outlook has been dedicated to what the reopening/normalization might look like, and here the glass is generally looked at as being half full—in other words, through the lens of a normalization in services and abating inflationary concerns. There is, however, a flip side to this coin: It's likely that those areas that had been supercharged by the pandemic will eventually normalize, at least on a relative basis, and this time, to the downside. Here’s our noncomprehensive list of items that supported the recovery so far that are likely to become less supportive over time.
- Housing activity has, counterintuitively, significantly contributed to growth in 2020. During the COVID-19 recession, falling yields, supply shortages, and a trend toward de-urbanization all contributed to a surge in real estate activity, with new construction and renovations being beneficiaries. As a result, residential construction’s contribution to U.S. growth hit highs not seen in four decades. Consequently, we expect to see a marked (albeit temporary) deceleration in the space as higher rates, improved mobility, and increased supply come back online. This implies that housing activity is likely to slow, and while we remain long-term believers in real assets and U.S. housing, it isn’t realistic to expect to see the space grow at the pace it did in 2020. Similarly, sales of goods are likely to take a breather as consumers spend more on services. As mentioned earlier, we expect retail sales to chalk up huge gains in the next month or two and to surpass pre-pandemic spending by June, with the caveat that a sharp YoY drop-off could occur over the summer.
Residential construction's contribution to GDP growth (%)
- The pandemic also distorted wage growth, a key input into the inflation outlook. The increase in average hourly earnings in the past year can be traced to the fact that a substantial number of job losses during the period had been primarily concentrated in lower-paid positions in the services sector. As a result, the statistical gain that we saw merely reflected the change in the composition of the data pool, which now comprises more higher-salaried workers as a share of the overall workforce than before the pandemic. As more lower-paying positions come back online, we’re likely to see marked declines in average hourly earnings. Crucially, just as the upside in wages had to be discounted, so too will the unwind (although we’d note that lack of wage growth is supportive of our view that we’re not going to see runaway inflation).
U.S. average hourly earnings may unwind
Average hourly earnings, YoY change (%)
- More broadly, our view is that the policy support that aided the recovery so far is also likely to see an unwind; consequently, measures of policy support such as YoY liquidity injections will also deteriorate. This will be true for the Fed, which has already unwound many of its liquidity and emergency lending facilities, including the 13(3) emergency lending facilities and SLR facilities. It will also be true for fiscal policy and the fiscal impulse, which has likely already peaked, and while government money remains a major support for U.S. growth, its impact will likely lessen in the coming year.
We’re entering an interesting period in which expected data distortion requires economists and data watchers to temporarily set aside analytical habits that they’ve traditionally relied on. Base effects and other one-off factors are likely to make the goal of getting a good read of the economy even tougher. In our view, we’ll need to dig deeper into the data set and, even then, prepare to wave goodbye to the idea of precision forecasting until normality returns.
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