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# Construction Economics – An Eye on Forecasts

5-5-21

How can you tell if your preferred construction economic forecast is on track to finish the year as predicted?

For comparison, in the following link I’ve collected initial 2021 construction spending forecasts from nine different sources. Measuring Forecasting Methodology & Accuracy

As of 5-3-21, three months of actual data are in. The first step is to compare that current actual data to the predictions. The next step is to use a bit of math to answer the question, Can we get there from here?

Here’s examples:

First let’s look at Lodging. In the AIA initial 2021 Outlook, ABC forecast -13% and Moody’s forecast -52%. Current spending year to date through March is -25%. Are either of these forecasts achievable?

Lodging construction starts dropped 11% in 2019 and dropped another 50% in 2020. The seasonally adjusted annual rate (SAAR) of spending fell from \$33bil in Q1 2020 to \$24bil in Q1 2021, down 27%. The current rate of spending is coming in between 25%-30% below same month last year (yoy).

Now do the math.

Look at the ABC forecast for lodging. To finish the year down -13%, monthly spending needs to average -13% for all 12 months of 2021. 12 months x -13% = -157. But 3 months, down cumulatively 25%, are already known. 3 months x -25% = -75. What would need to occur for the last 9 months to reach a total 2021 spending down -13%?

12 x -13% = -157 minus 3 x -25% = -75, therefore -157 minus -75 = -82. In the remaining nine months, Lodging would need to fall a cumulative 82%, or 82/9 = an average of 9%/month.

Well, the current rate of spending is down 25% yoy and construction starts the previous two years are down 60%. Cash flows seem to indicate spending will not increase this year. There is little hope of seeing an increase in monthly spending in 2021. Since new starts are less than half of only two years ago, spending is unlikely to increase from a monthly rate down 25% to a monthly rate down only 9% for the next nine consecutive months. Therefore this forecast is unlikely to play out. The ABC forecast is too optimistic.

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Now let’s look at the Moody’s forecast for lodging. To finish the year down -52%, monthly spending needs to average -52% for all 12 months of 2021. 12 months x -52% = -624. But 3 months, down cumulatively 25%, are already known. 3 months x -25% = -75. What would need to occur for the last 9 months to reach a total 2021 spending down -52%?

12 x -52% = -624 minus 3 x -25% = -75, therefore -624 minus -75 = -549. In the remaining nine months, Lodging would need to fall a cumulative 549%, or 549/9 = an average of 61%/month.

Well, the current rate of spending is down 25% yoy and construction starts the previous two years are down 60%. Cash flows are indicating monthly spending will drop 3% to 4% per month this year. Spending would need to decline 61-25=36% in one month and stay at that rate for the remainder of the year, OR, spending would need to start falling at a rate of 12%/month and continue 12% lower every month for the remainder of the year. By December, spending would be down over 100%, so this is not even feasible. Therefore this forecast cannot play out. The Moody’s forecast is far too pesimistic.

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Second, let’s look at Manufacturing. In the AIA initial 2021 Outlook, ABC forecast +6.5% and Moody’s forecast -3.4%. Current spending year to date through March is -9%. Are either of these forecasts achievable?

Manufacturing construction starts dropped 10% in 2019 and dropped another 57% in 2020. The seasonally adjusted annual rate (SAAR) of spending fell from \$78bil in Q1 2020 to \$71bil in Q1 2021, down 10%. The current rate of spending is coming in between 7%-11% below same month last year (yoy).

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Look at the ABC forecast for manufacturing. To finish the year up +6.5%, monthly spending needs to average +6.5% for all 12 months of 2021. 12 months x +6.5% = +78. But 3 months, down cumulatively 9%, are already known. 3 months x -9% = -27. What would need to occur for the last 9 months to reach a total 2021 spending up+6.5%?

12 x +6.5% = +78 minus 3 x -9% = -27, therefore +78 minus -27 = +105. In the remaining nine months, Manufacturing would need to gain a cumulative 105%, or 105/9 = an average of +12%/month.

Well, the current rate of spending is down 9% yoy and construction starts the previous two years are down 67%. Cash flows seem to indicate spending will continue to drop at a rate of 2% to 3% per month this year. There is little hope of seeing an increase in monthly spending in 2021. Since new starts are down 67% from two years ago, spending is unlikely to increase from a monthly rate down 9% to a monthly rate up 12%, a swing of 21%, for the next nine consecutive months. Therefore this forecast is highly unlikely to play out. The ABC forecast is far to optimistic.

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Now let’s look at the Moody’s forecast for manufacturing. To finish the year down -3.4%, monthly spending needs to average -3.4% for all 12 months of 2021. 12 months x -3.4% = -41. But 3 months, down cumulatively 9%, are already known. 3 months x -9% = -27. What would need to occur for the last 9 months to reach a total 2021 spending down +3.4%?

12 x -3.4% = -41 minus 3 x -9% = -27, therefore -41 minus -27 = -14. In the remaining nine months, Manufacturing would need to fall a cumulative -14%, or -14/9 = an average of -1.5%/month.

Well, the current rate of spending is down 9% yoy and construction starts the previous two years are down 67%. Cash flows are indicating monthly spending will drop 2% to 3% per month, every month this year. Spending would need to begin falling at a rate of only -1.5%/month and continue -1.5% lower every month for the remainder of the year. A decline of 67% in starts over the previous two years solidifies a rate of decline beyond that at near 3%/month. This scenario would depend on cutting the rate of decline in half for the remainder of the year, but the lack of starts in previous years provides no help to achieve that goal. The Moody’s forecast is too optimistic.

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It’s in your best interest to know how to assess the plausibility of forecast components before you question an analysis that varies widely from your preferred forecast. It may be your preferred forecast that is way off.