Whatever Happened to the Recovery in Southern Pine Sawtimber Stumpage Prices?

When a year draws to a close, it is customary to look back and take stock of what has transpired. If that is done with U.S. Southwide pine sawtimber (i.e., DBH ≥ 12.0 inches) stumpage prices, someone might legitimately wonder if an economic recovery has ever really arrived. Between August 2011 and November 2015, stumpage prices have increased by 10.5% on a trend-line basis; that corresponds to a compound annual growth rate (CAGR) of 2.5%. Yet, the 2015 year-to-date (through November) average of total U.S. housing starts (1.102 million units SAAR) is over 130% higher than the April 2009 low point (478,000 units). In addition, the trended CAGR of Random Lengths' southern yellow pine lumber composite price is up 7.7% since January 2009. So, why has the post-Great Recession stumpage price increase been so muted?

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One reason is the Canadian dollar (CAD). A weaker CAD encourages Canadian lumber exports to the United States, in the process capturing market share from U.S. solid wood manufacturers and -- in turn -- reducing demand for U.S. softwood sawtimber. U.S. imports of Canadian softwood lumber have risen at a trend CAGR of 8.3% since January 2009. 

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In the chart below, we divided total U.S. housing starts by the CAD/USD exchange rate (HS/CAD) to suggest the degree to which the exchange rate affects perceptions that U.S. solid wood manufacturers have regarding housing starts. For those producers the “HS/CAD” line is a more realistic portrayal of domestic lumber demand derived from housing starts than the reported “TotalHS” line. Thus, while total reported housing starts have increased at a trend CAGR of 14.4% since April 2009, HS/CAD have risen by only 11.0% -- a difference of nearly one-quarter. The increase in Canadian softwood lumber imports has largely kept pace with the CAD-adjusted rise in U.S. housing demand.

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A second reason is that, although total housing starts have been rising, the share of total starts claimed by multi-family structures -- which, on average, use roughly one-third the volume of softwood lumber per start compared to single-family homes -- has been expanding (from an annual average of 19.5% in 2010 to 35.8% YTD through November 2015). That larger share of multi-family units also helps explain why total housing starts were up 81% on an annual basis between 2009 and 2014, but U.S. lumber production rose by only 34% (+37% for Southern production) during the same period.

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Another reason is that tree growth continues to outpace the volume harvested. With more supply "on the stump" -- particularly in pine sawtimber, as shown in the following table -- price pressure is reduced.

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This situation has been further exacerbated by the Great Recession’s impact on installed sawmill manufacturing capacity. As noted above, southern lumber prices have increased at a trend CAGR of nearly 8% since January 2009; this is because -- and despite a muted recovery in lumber demand -- roughly 20% of U.S. solid wood capacity (the losses for lumber were even greater) was shuttered as a result of the industrial downturn experienced during/since the Great Recession. Thus, there was insufficient capacity to meet even the comparatively anemic increase in demand as the recovery occurred, prompting lumber prices to rise and capacity utilization rates to climb. That explains the lumber price response, but what about stumpage prices? 

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The loss of manufacturing capacity hindered the sector’s ability to expand lumber supply in response to rising consumer market demand. It also reduced localized geographic demand for stumpage -- both in terms of the quantity of stumpage demanded and the number of mills competing for that stumpage. Coupling the stumpage market situation of fewer mills and lower localized demand with increasing log supply “on the stump” explains why the stumpage price recovery has been muted despite steady trend improvement in lumber prices since 2009.

Taking all of these influences together, and given our expectations of how present trends are likely to “play out,” we see little reason to believe a dramatic change may be coming over the horizon.

The foregoing comments represent the general economic views and analysis of Delphi Advisors, and are provided solely for the purpose of information, instruction and discourse. They do not constitute a solicitation or recommendation regarding any investment.

Whither Home Prices?

With June’s median existing home price rising to a record-high $236,400 and the median new-home price at $281,900 (just $20,900 off the November 2014 record of $302,700), what direction are home prices likely to take going forward? To hazard a guess we used a metric -- inspired by an Agora Financial 5 Min. Forecast published on 23 July -- wherein median home price (MP) is divided by median household income (MHI) to derive a price/income multiple (PIM).

Each month the U.S. Census Bureau reports the median price of new homes sold; likewise, the National Association of Realtors (NAR) reports the median price of existing homes sold. The Census Bureau reports median household income on only an annual basis, however, and the latest data is for 2013. We first converted the monthly median new and existing home prices to annual observations by calculating averages for each year (the green and purple lines, respectively, in the first graph below). To estimate median household income for 2014 and 2015, we developed an ordinary least squares regression equation (R² = 0.91) wherein the Census Bureau’s MHI is a function of NAR’s annualized MHI (reported as part of NAR’s housing affordability index data series). The derived MHI estimates are shown as the red segment of the income line in the first graph below.

Several items are noteworthy: Growth in MHI broke off its long-term trend in the wake of the Great Recession (i.e., since 2007) and -- although having regained its pre-recession level in 2012 -- has yet to fully recover its former trajectory. New-home MPs peaked in 2007, bottomed in 2009, essentially regained their pre-recession level by 2012, and have continued higher since then. Existing-home MPs, by contrast, peaked in 2006, bottomed in 2011, and have yet to regain their pre-recession level.

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The Census Bureau’s median home price data extends back to 1984 whereas NAR’s data begins in 2003. For the available years, we divided annualized median home price by annualized median household income to estimate new and existing home price/income multiples. Prices and PIMs are shown in the second graph below. PIMs for new homes have ranged from 3.57 to 5.34, for an average of 4.31; existing-home PIMs have ranged from 3.29 to 4.71, for an average of 3.86. I.e., on average new home prices have been equivalent to 4.31 times MHI, and existing home prices 3.86 times MHI.

For new homes, the PIM peaked at 5.06 in 2005 -- the height of the housing boom. It slid to its low point of 4.31 by 2009 and has since trended to an all-time high of 5.34 in 2015. For existing homes, the PIM peaked at 4.71 in 2005 (despite the MP peaking in 2006), but two additional years were required to hit the bottom of 3.29 (in 2011); as with its corresponding MP, the existing-home PIM has not yet returned to its pre-recession high.

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Particularly in light of the new-home PIM presently at an estimated all-time high and incomes posting only slow growth compared to home prices (especially on an inflation-adjusted basis), we think there is greater downside than upside risk to home prices. The table below shows the implications for prices if the PIMs return to selected historical levels.

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For new homes, the best scenario shown involves the PIM returning to its 2005 level; that would result in a price reversion to $273,334 -- a decline of $15,590. A more dire scenario would have the current PIM retreating by an amount equivalent to that seen between the 2005 peak and 2009 trough; in that case, the PIM would drop to 4.60 with the new-home MP falling to $248,576 (a decline of $40,358).

Because the existing-home PIM has not returned to its pre-recession peak, there is perhaps more upside potential. For example, were that PIM to once again hit the 2005 peak, the existing-home MP could increase by $38,922 to $254,622. The most pessimistic scenario involves the existing-home PIM retreating from its current level by the amount seen between 2005 and 2011; in that case the multiple would slump to 2.57, resulting in the existing-home MP dropping by $76,888 to $138,812.

For housing starts (new homes) and sales (existing homes) to continue climbing higher, we believe it will be necessary for home prices -- particularly new home prices -- to fall so coherence is maintained with households' ability to pay (i.e., MHI). Until that occurs we believe it will be difficult for housing starts to make more substantial progress toward regaining the long-term average level of 1.5 million units per year.

Unfortunately, as the table above shows, home-price reductions will choke off the ability of some current homeowners to refinance or trade up/down, thereby reducing access to potential home equity that might provide additional economic stimulus. On balance, however, lower home prices would likely provide the greater economic boon because the Echo Boom demographic cohort would be able to flex more economic muscle through greater household formations. Regardless, the path forward in housing’s march back toward “normal” is likely to encounter several twists and turns. There will be a variety of counterbalancing impacts to the general economy in the process that, on net, could prove positive.

The foregoing comments represent the general economic views and analysis of Delphi Advisors, and are provided solely for the purpose of information, instruction and discourse. They do not constitute a solicitation or recommendation regarding any investment. 

Zombie Trees

Halloween seems an appropriate time to highlight a national horror story.  Although this post looks at it through the prism of Idaho, sadly the tale is unfolding in many places throughout the U.S. West.

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We start the tale innocently enough: comparing the number of standing trees per acre on forest land across Idaho.  But first, a bit of background.  In USFS nomenclature “forest land” is the broadest classification of land with trees growing on it, including lands that have at least 10 percent forest cover; timberland refers to forest land that surpasses a productivity threshold and is not legislatively reserved from being actively managed. 

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According to the USFS's Forest Inventory and Analysis ("FIA") unit, there are nearly 21.5 million acres of forest land across the state.  Eighty percent of the forest land in the state is managed by the federal government, with the vast majority (76 percent of the state’s forest land) managed by the United States Forest Service (“USFS” or “NFS”).  The State of Idaho manages six percent of the forest land in Idaho with the remaining 14 percent managed by private land owners.  These lands are interspersed with one another across the state.

With that is background, let’s plunge ahead with our tale.  For the three primary forest managers/owners in Idaho, the USFS, the State of Idaho (“IDL”, for Idaho Department of Lands), and private land owners, the average forest land acre carries roughly the same number of live trees (122 per acre for USFS, 119 per acre for IDL, and 108 per acre for private).  However, the number of standing dead trees per acre on the USFS (43) is roughly double the number of standing dead trees per acre on State (20) and Private lands (14).  Why would this be?  Remember, the USFS doesn’t represent an isolated pocket of property but rather is by far the most significant land manager in terms of geography within the state.

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IDL and private land is generally more actively managed, including higher harvest activity, than forest land managed by the USFS.  For instance, as can be seen in the graph below, although USFS managed lands represent 76 percent of all forest land, it currently accounts for less than 15 percent of the annual timber harvest in the state.   On the other hand, the state, comprising six percent of the forest land acreage, accounts for nearly 30 percent of the harvest.  In the case of private land owners, 60 percent of the annual harvest is sourced from their acreage, representing 14 percent of the forest land in the state.

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To further examine the link between active management and tree mortality, the next chart focuses on USFS land only.  As can be seen there are 10 columns in all, comprising five sets of two columns each.  Each set of two columns shows the number of living trees and the number of standing dead trees per acre.

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The far right set of two columns on the chart above corresponds to the USFS graph shown in the prior trees per acre by ownership chart.  The other four sets of two columns segregate USFS forest land into four different categories.  The first two sets look at more productive forest land  while the second two sets of columns look at less productive forest lands.  The more productive forest land area is further sub-divided between acres that are not reserved, i.e. that are open to active management, and acres that are reserved, or legislatively withdrawn from any active management occurring on them.  Designated wilderness areas are an example, the most common in fact, of acreage that is reserved from active management.  Similarly, the less productive acres are sub-divided between not reserved and reserved.

Several patterns emerge when the data is analyzed in this way.  First, the more productive lands carry more lives trees per acre than less productive lands.  Second, the ratio of the number of dead trees per acre compared to the number of live trees per acres is higher on less productive lands.  But, third, and most important here, is regardless of productivity, there are more dead trees per acre on lands where no active management is possible.  Fourth, on the most productive areas that are open to be actively managed, the number of standing dead trees per acre is still nearly double that seen on IDL and private ownership.  Thus, on the USFS even acres where ostensibly active management can be practiced, not enough is being done and trees are dying.

Beyond, the charts and numbers, the reality is all too obvious to anyone who looks at Idaho’s national forests.  Suppression of fire and significant reduction harvesting, both for regeneration and thinning, have allowed forest managed by the USFS to become overcrowded and old.  In the relatively dry climates of the Inland West, the old, overcrowded conditions weaken trees, making them more susceptible to insects, disease, and death.

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Trees per acre are one thing and seem bad enough but when the number of dead trees per acre are multiplied across the size of the USFS holdings in the state the magnitude of the losses becomes even more sobering.  The next chart compares the volume represented in standing dead trees on the USFS compared to volume in live trees on other ownerships in Idaho.  As can be seen, the volume represented in the standing dead trees on USFS timberland (not reserved and productive lands) exceeds the live volume on any other single ownership class in the state.  Total standing dead volume on all USFS forest land is nearly equal to the total live volume on all other ownerships combined in the state.

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For those concerned about global climate change and green house gases, there is an additional element of this carnage that is often overlooked.  As is well known, trees grow by utilizing atmospheric elements, including carbon dioxide, other nutrients from the soil, sunlight energy, and water.  One result of this growth process is a reduction in carbon dioxide, fixing carbon within the tree's cellular structure and producing oxygen as a by-product  When a tree dies and begins a slow process of decay, the fixed carbon within the tree is released.  However, this process will take a long time in the dry Inland West so a significant amount of carbon remains ‘stored’ in the dead trunk for an extended period of time.  However, no new tree can take its place while it stands, and so that portion of the forest is no longer in effect exchanging carbon dioxide for oxygen as it once did while carbon that had been stored within the tree during decades of growth slowly leaks away.

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But standing dead trees and standing dead volume speaks to what has been --- not what is happening.  The chart below begins to look at what is happening now, not what has been.  It compares the volume in trees that die annually to the volume of trees harvested annually by ownership.

 

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The first two stacked columns on the chart compare mortality on non-reserved forest land acres – acres that are open to active management – to 2012’s harvest.  Each column is sub-divided by ownership to depict the contribution of each ownership category to the state total.  The comparison is made on non-reserved acres because those are the only acres on which active management, including timber harvest, can occur.  The last column on the chart depicts the annual mortality occurring on forest land acreage reserved from active management.

 

Total mortality, on both non-reserved and reserved forest land, is nearly 4 times the amount of volume being harvested annually state-wide.  The annual mortality on the USFS acres that are open to active management is over 18 times the volume of the annual harvest from those same acres.  Finally, the annual mortality on the 3.8 million acres of reserved – Wilderness – acres in the state exceeds the annual harvest on the 16.4 million acres of forest land in the state open to active management across all ownerships.  In a word, the Idaho Wilderness is being slaughtered.

The chart below shows net annual growth and annual harvest on Idaho forest lands.  The ratio of net annual growth to annual harvest ("growth/drain ratio") is a common, sometimes overused, metric used to test harvest intensity.  Net annual growth is the amount of growth occurring in a year minus the amount of annual mortality.    As can be readily seen, not only does state-wide net annual growth exceed state-wide harvest, the net annual growth on each ownership exceeds the annual harvest for each individual ownership class in the state.  Notably, the "growth/drain" on private ownerships (1.33) exceeds the same ratios on USFS (1.17) and IDL (1.12).

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Looking at those results on the USFS one might be tempted to conclude harvest levels could be increased only slightly before harvest exceeds net annual growth, prompting forest inventory to fall.  However, this is one example where the growth-drain ratio alone doesn't provide an adequate picture of forest conditions; in this case, the high level of mortality distorting what is occurring on USFS lands.

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The chart above separates the components of net annual growth apart and further separates them by non-reserved (i.e. open to active management) and reserved forest lands for each ownership class.  As can be seen on this chart, on most ownerships annual mortality is a fairly small relative to annual growth (16 percent on IDL and private forest land in Idaho).  Unfortunately, this is not the case for the USFS.  On USFS non-reserved forest lands annual mortality is a whopping 76 percent of annual growth.  However, on reserved forest land the picture is even more dire; annual mortality is 206 percent of annual growth.  Idaho’s spectacular wilderness and back-country areas are slowly dying.  Dying by starvation, dying by thirst, dying by strangulation.  Combining the non-reserved and reserved acreage results in a slightly positive net annual growth where annual growth exceeds annual mortality by four percent.

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The next chart (see above) now completes the picture, pitting harvest against net annual growth on the acres open to active management.  On USFS it’s clear the net annual growth on acres open to active management exceeds harvest by over 500 percent.  This is a radically different picture than when comparing the annual USFS harvest to the USFS property total where net annual growth is much lower due to the annual mortality occurring in Idaho’s wilderness areas.  However, the extremely positive net annual growth to harvest on USFS lands needs to be understood in the context of other clear trends on USFS lands: rampaging mortality on reserved forest lands and mortality that is rapidly increasing on non-reserved forest lands.

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Will Zombie Trees overrun the national forests in Idaho?  And remember, Idaho is simply a snapshot of the dynamic underway in many public forest lands across the U.S. West.  As bad as it is, unfortunately, the story does not end with a moonscape of standing dead trees.  Ultimately a lightning strike will cremate the standing and tilting remains of zombie trees, polluting expansive air sheds, further ravaging wildlife habitat, exposing streams and rivers to significant sediment loads and reduced shade, and sometimes sterilizing soils for a generation.

 

While popular science and belief stretch to accommodate and explain such ravages as part of the “natural order”, the fuel loads fanning today’s wildfires are not natural and the results rarely orderly.  Yes, thankfully there is a kind of rejuvenation in the aftermath of wildfire’s annihilation.  But in light of the destruction it seems the question is could such rejuvenation be achieved in a manner with less apocalyptic fury and lower societal cost.  Earthquakes, hurricanes, and pestilence are all natural as well.  Yet, we try to operate in a manner to mitigate their damaging effects on society, not amplify them.  As a society will we find the will to halt the advancing scourge of zombie trees?

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QFR Paper Manufacturing – 2014 First Quarter

With this post we are initiating coverage of the Census Bureau’s Quarterly Financial Review data for the U.S. paper manufacturing industry. Each quarter the Census Bureau samples a broad array of U.S. corporations to gather a snapshot of business sector health and activity. The program, known as the Quarterly Financial Report, or QFR, survey has been collected and published for over sixty years by various Federal agencies, the Census Bureau being the current administrator of the program. These data provide a standardized and comprehensive look at the financial condition of the industry.

Results from sampled businesses are aggregated and reported by the North American Industry Classification System (NAICS) and by asset size category. There are separate NAICS codes for wood product manufacturing (“321”) and paper manufacturing (“322”). Based upon returned sample surveys, the QFR presents estimated statements of income and retained earnings, balance sheets, and related financial and operating ratios by industry sector and asset size category. What’s reported in this blog is only a snapshot of the other data reported by the QFR survey.

The paper manufacturing data is categorized by asset size: firms with less than 25 million dollars in assets (“small firms”), firms with more than 25 million in assets (“large firms”), and all firms regardless of size. While the data is somewhat dated, it provides a useful perspective on business direction and momentum with respect to the current cycle as well as providing benchmarks for individuals firm’s performance.

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Viewing the 2014Q1 data, the picture that emerges is a gradually improving industry sector that was hampered by adverse 2014Q1 weather conditions, which have been widely reported by the financial media as the principal cause behind 2014Q1's negative real GDP print. Comparisons to the prior quarter (2013Q4) are further complicated by significant non-operating income and a significant federal tax credit received in 2013Q4. Granting these complications to in-depth interpretation of 2014Q1 industry results, probably the most significant observation is although year-over-year industry net sales increased by 5.5%, operating margins fell, dropping from 5.74% in 2013Q1 to 3.49% in 2014Q1. However, despite loss of operating margin, the industry’s focus on asset rationalization has maintained both ROE and ROA in the solidly within the upper quartile of performance relative to the past 10 years.

Selected financial results of paper manufacturers’ first quarter 2014 is summarized in the table shown below. Notable highlights (see table below) include:

• Net Sales – 2014Q1 net sales ($32.9 billion) retreated by 3.2 percent compared to 2013Q4’s net sales, a reduction approximately three times larger (more negative) than the median reduction seen between Q4 and Q1 over the past ten years. Despite dropping from 2013Q4’s sales, 2014Q1’s net sales increased by 5.5% compared to 2013Q1’s net sales level.
• EBITDA – 2014Q1 operating cash-flow, or Earnings Before Interest, Taxes, Depreciation, and Amortization (EBITDA), posted 10-year lows for both large firms and the industry.
• Operating Income – 2014Q1 operating income was in lower quartile of last 10 years for industry and both large and small firms.
• Pre-tax Income – 2014Q1 pre-tax income posted significant declines to 2013Q4, dropping nearly 52 percent compared to a 10 year average percentage change between Q4 and Q1 of nearly 12%.
• Net Income – 2014Q1 net income posted significant declines on both a quarter-over-quarter basis as well as on a year-over-year basis. As noted earlier, quarter-over-quarter comparisons are complicated by large non-operating income received in 2013Q4. However, year-over-year comparisons don’t suffer from this issue and point to significant cost structure increases in 2014Q1 vs. 2013Q1: year-over-year sales improved by $1.7 billion while net income fell by $0.9 billion, a combined implied cost delta of $2.6 billion, or 8.3% on 2013Q1 sales of $31.2 billion.
• Operating Margins – 2014Q1 operating margins showed significant erosion across the board on both quarter-over-quarter and year-over-year comparisons.
• ROE and ROA – Despite apparently increasing operating costs both Return on Equity (ROE) and Return on Assets (ROA) posted year-over-year increases and were in the upper quartile of performance relative to the past 10 years.

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The key unknown for the industry sector is how much of the increase in 2014Q1 operating costs was attributable to the adverse weather conditions that were blamed for the negative GDP change. The fact 2014Q1 sales contracted from 2013Q4’s net sales level by more than the median percentage between Q4 and Q1 over the past 10 years is consistent with adverse weather impacts. However, 2014Q1’s net sales increase relative to 2013Q1’s net sales potentially challenges weather as the principle explanation for 2014Q1’s EBITDA, operating income, pre-tax income, and net income declines. The second quarter data, due to be released mid-September, will provide additional insights into the industry’s trajectory this business cycle.

QFR Wood Products Manufacturing – 2014 First Quarter

With this post we are initiating coverage of the Census Bureau’s Quarterly Financial Review (QFR) data for the U.S. wood products industry. Each quarter the Census Bureau samples a broad array of U.S. corporations to gather a snapshot of business sector health and activity. The program, known as the Quarterly Financial Report, or QFR, survey has been collected and published for over sixty years by various Federal agencies, the Census Bureau being the current administrator of the program. These data provide a standardized and comprehensive look at the financial condition of the industry.

Results from sampled businesses are aggregated and reported by the North American Industry Classification System (NAICS) and by asset size category. There are separate NAICS codes for wood product manufacturing (“321”) and paper manufacturing (“322”). Based upon returned sample surveys, the QFR presents estimated statements of income and retained earnings, balance sheets, and related financial and operating ratios by industry sector and asset size category. What’s reported in this blog is only a snapshot of the other data reported by the QFR survey.

The wood products manufacturing data is categorized by asset size: firms with less than 25 million dollars in assets (“small firms”), firms with more than 25 million in assets (“large firms”), and all firms regardless of size. While the data is somewhat dated, it provides a useful perspective on business direction and momentum with respect to the current cycle as well as providing benchmarks for individuals firm’s performance.

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Viewing the 2014Q1 data, the picture that emerges is an industry that may have already peaked for this cycle in terms of financial performance. Yet caution is in order: the very tentative housing recovery following the Great Recession could well offer surprises in terms of shape and trajectory of this business cycle. Further, as has been well publicized in the financial media, weather effects were notable in 2014Q1 and these too could be impacting financial results. However, as the graph below shows, net sales have been declining since 2013Q2. Likewise, on trend over the past 12 quarters EBITDA, operating income, and net income increased through 2013Q2 but since then have traced a downward trend. Note net income, operating income, and EBITDA for the weather-affected 2014Q1 is greater than 2013Q4’s (prior quarter) results and roughly on par with 2013Q1’s (prior year) results.

Selected financial results of wood products manufacturers’ first quarter 2014 is summarized in the table shown below. Notable highlights (see table below) include:

• Net Sales - 2014Q1 net sales ($19.3 billion) fell by 4.2% relative to 2013Q4 net sales. Because the wood products industry is highly cyclical, the median Q4 to Q1 change over the past 10 years is computed and shown in the tenth column of the table for the entire industry to facilitate quarter over quarter comparisons. The 2014Q1 drop in net sales from 2013Q4 is greater than the median Q4 to Q1 drop over the past 10 years (-4.2% vs. -3.6%). On a year-over-year basis, the industry showed a slight increase (+0.5%). The increase in net sales was concentrated on firms with assets less than $25 million (+3.4%) while net sales contracted in aggregate for firms with assets greater than $25 million (-1.2%). 
• EBITDA – 2014Q1 operating cash-flow was in the upper quartile of 10-year quarterly performance for all firms, regardless of size. Despite relatively high financial performance compared to the prior 10 years, EBITDA still fell on a year-over-year basis.
• Operating Income –2014Q1 operating income for small firms more than doubled (+115.8%) from 2014Q4’s level while large firms’ operating income increased by 12.3%. Despite the explosive quarter-over-quarter change for small firms, year-over-year operating income expanded by less than 1%. Large firms’ operating income fell by over 8% on a year-over-year basis. The composite results for the industry showed a decline of nearly 5% on a year-over-year basis.
• Pre-tax Income – 2014Q1 pre-tax income increased by over 140% compared to 2013Q4 for all firms and sizes, nearly three times the median quarter-over-quarter increase between Q4 and Q1 over the past 10 years.
• Net Income – Despite small firms’ 2014Q1 net income more than quadrupling 2013Q4’s level, year over year net income still fell by nearly 9 percent. Large firms’ quarter-over-quarter performance, a more than 50 percent increase, registered solid positive year-over-year results as well, pulling industry-wide net income high enough to post a year-over-year expansion of 4.4% in net income.
• Operating Margins – Improved for all firms on a quarter-over-quarter basis but declined for all firms on a year-over-year basis. Despite year-over-year declines, margins were still in the upper 30 percentile compared to the past 10 years, posting an industry average over 8%.
• ROE and ROA – Despite Return on Equity (ROE) and Return on Assets (ROA) for small firms falling on a quarter-over-quarter their levels remain in upper 15 percentile of the past 10 years of financial performance. Year-over-year performance for the industry as a whole showed improvement, posting 15.42% and 5.76% for ROE and ROA, respectively.

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Second quarter data, which is released the middle of September, will provide important information on either dispelling concerns the peak for this cycle has already been achieved or that recent performance was simply the market grabbing a breath before launching higher still.

And we have a new “WAHT” Award Winner*…

*for more about the WAHT Award, click here

Take a deep breath, pour yourself a fresh cup of coffee, or whatever is your beverage of choice to relax with, start the song (right click and select open in a new tab or window to avoid navigating away from this page), and read the article, “A few reasons to be optimistic about the U.S. economy.”  I’m sure you’ll begin to feel much better.

Then, when you’re ready to stop basking in fairytales and return to the real world, ask yourself:

1) If U.S. Healthcare cost increases are slowing due to something other than the economy, how does one explain a global slowdown in healthcare costs?  Is the global slowdown also slowing due to the prospect of implementing ObamaCare in 2014?  The proposition seems dubious.  Further, even if the slowdown is for a reason other than the weak economy, does it really provide a boost to the broader economy when the pace of spending increase is still greater than the pace of increase in U.S. private worker pay?

2) It certainly appears that after six long years the U.S. Housing sector is definitely getting better (fingers crossed; registration required to view link).  However, in the “WAHT award-winning” article there seems to be a view the Federal Reserve’s interest rate policy is separate from what the economy does.  Said another way, if the housing improvement translates into what is described as “really turns around,” won’t the Federal Reserve raise its “super-low interest rates” to avoid overheating the economy?  And why are interest rates still so low?  Is it for housing, or for another reason?  Concern has already been expressed over maintaining low interest rates in the present economic environment by some Federal Reserve presidents, although those sharing this view are in a minority among voting members this year

Recent comments from Chairman Bernanke address these issues (emphasis added).  The first issue is why interest rates are still low:

“If, as the FOMC anticipates, the economic recovery continues at a moderate pace, with unemployment slowly declining and inflation expectations remaining near 2 percent, then long-term interest rates would be expected to rise gradually toward more normal levels over the next several years. This rise would occur as the market's view of the expected date at which the Federal Reserve will begin the removal of policy accommodation draws nearer and then as accommodation is removed. Some normalization of the term premium might also contribute to a rise in long-term rates.”

The key to note here is not a word about the housing market.  The Fed’s accommodative policy is principally due to high unemployment levels and, secondarily, a fear of deflation. So, by keeping rates low and policy lax, the Fed hopes to maintain some inflation in the face of significant economic slack. 

The second issue is: What happens if the economy begins to strengthen if, say, an improving housing market provides added spark:

“If, as the FOMC anticipates, the economic recovery continues at a moderate pace, with unemployment slowly declining and inflation expectations remaining near 2 percent, then long-term interest rates would be expected to rise gradually toward more normal levels over the next several years. This rise would occur as the market's view of the expected date at which the Federal Reserve will begin the removal of policy accommodation draws nearer and then as accommodation is removed. Some normalization of the term premium might also contribute to a rise in long-term rates.”

Two observations on the quote above:  1) The reason rates are low is because the economy is weak. When the economy isn’t weak interest rates won’t remain low, they’ll increase.  Why?  Because 2) central banks need to meet their price stability mandates and leaving rates low won’t allow that to happen.  So, when interest rates finally begin to increase again, what happens to interest payments on the U.S. debt?  I suspect a new crisis unfolds.

3) The WAHT award winner hypothesizes our recent episodes of "genuine malgovernance" were caused by the “extraordinary stresses the recession put on the political system”…. how quaint.  I turn to Mark Twain’s (1836 to 1910, RIP) quote:  “Suppose you were an idiot, and suppose you were a member of Congress; but I repeat myself.”  I’m guessing Mark Twain wasn’t prophesying about today’s federal government but instead lamenting the one of his day.  I’m not holding out much hope we’re seeing a sea change on this one.

4) U.S. Corporate profits are strong -- and that’s a good thing -- but it appears one of the reasons they’re strong is due to corporations paying lower wages.  This isn’t a shocking result given labor slack.  However, U.S. consumers need disposable income if they’re going to buy the things that drive corporate sales that result in corporate profits.  But U.S. households have been losing ground on that score for some time; real disposable income is down as well, both in aggregate as well as on a per capita basis.  Thus, the current situation doesn’t seem particularly sustainable.

5) Neither Europe nor China appears to be tumbling off an economic cliff...Cómo?   While China may not be falling off an economic cliff, it certainly isn’t roaring and substantial risks remain as it navigates from an investment- and export-led economy to a consumer-driven economy.  However, characterizing that Europe isn’t falling off an economic cliff makes me wonder what our WAHT award winner is reading about the European economy because it clearly isn’t what I’m reading.  While much of the mainstream media likes to proclaim the crisis is over, it seems it doesn’t take long for the crisis pop right back up again, which makes me suspect it never really left in the first place.  Informed opinion seems to agree the Euro crisis is far from over too;  unemployment conditions,  economic data, and recent political events seem to indicate there is little prospect of resolution any time soon.

6) Two other suggestions, that technology will deliver job and wage growth and the U.S. is on the threshold of an "insourcing boom" seem speculative at present.

In fact, one of the mechanisms providing the aforementioned record corporate profits is productivity-enhancing technology -- resulting in lower wages being paid.  Frequently the direct pay-off for such technology is worker displacement.  I don’t argue against this because such creative destruction (i.e., innovation) is needed for American enterprise to remain globally competitive.  I simply highlight that these two points of optimism are somewhat contradictory.

As far as being on the threshold of an “insourcing boom,” I appreciate the quip: “anecdotes aren’t data.”  I'm glad for the people of Louisville, Kentucky who are benefiting from General Electric's decision to bring manufacturing jobs back to their Appliance Park facility.  But a company making some decisions, even one as big as GE, doesn't mean a new era is upon us.  The "tale of the tape" for either technology or insourcing will be if job growth accelerates; so far the jury is out on that score despite February’s favorable employment job growth print.

7) The point about natural gas prices is definitely a positive for U.S. growth prospects going forward.  I’ll spare readers the pessimism of “malgoverance” finding a way to turn a positive into a negative.  After all, this post is about feeling optimistic and earlier it was posited by the WHAT award-winning article the period of “genuine malgoverance” may indeed be behind us.  I will, however, point out the inevitable -- but positive, assuming no added regulatory burden -- that natural gas prices will increase.  That is because given the recent divergence between crude oil and natural gas prices, consumption will shift away from crude oil and toward natural gas.  On a net basis that will result in lower energy costs -- a good thing for the U.S. economy.

8) The final point, that U.S. consumer confidence as measured by Gallup is up from where it was during the recession, is definitely true.  But saying that is a bit like (to use a basketball analogy since March Madness is nearly upon us) commenting at 3 minutes into the second half your team is staging a comeback because they’ve narrowed the opponent’s lead by 8 points since halftime.  But the lead at halftime was 35 points -- still a long way to go.

The great enemy of the truth is very often not the lie, deliberate, contrived and dishonest, but the myth, persistent, persuasive and unrealistic.
                                                                    John F. Kennedy

The result of this deception Is very strange to tell,

For when I fool the people I fear, I fool myself as well!
                              Selected lyrics from “Whistle a Happy Tune”
                              Oscar Hammerstein II, lyrist

Levitating

Levitating. Lev-i-tat-ing. To rise or cause to rise into the air and float in apparent defiance of gravity.

On December 20, 2012 the Bureau of Economic Analysis (BEA) announced the third (“final”) estimate of 2012.Q3 real change in GDP at 3.1 percent, up from the advance/first estimate of 2.0 percent announced the end of October and from the second estimate of 2.7 percent announced the end of November.

Our general view of the U.S. economy is that it has been on a glide path towards another recession – in fact, our forecasts called for the recession to potentially have started by now. As can be seen in the graph below, until these latest revisions, the data of since 2011.Q4 has certainly been consistent with our forecast perspective.



Click on Image to Enlarge

But, as can also be seen, we have been on a similar glide path once before during the current business cycle. Between 2009.Q4 to 2010.Q3 the economy’s momentum was stalling even with over $800 billion of Federal ARRA stimulus (shaded region on the graph above) being fed into its veins. The scheduled reduction in Federal stimulus spending, combined with slowing growth in real disposal income starting in 2010.Q2, seemed to indicate a nearly unavoidable recession was on the near horizon.

In fact, a recession seemed so unavoidable the Economic Cycles Research Institute (ECRI) famously asserted as much in September 2011, “…the U.S. economy is indeed tipping into a new recession. And there’s nothing that policy makers can do to head it off.” As the months passed and “the recession” didn’t arrive ECRI continued to say they ultimately would be proven correct, despite many doubters.

A quick aside: Finally in July 2012 ECRI stated the US economy had already entered recession (and thus “coincidentally” self-confirming their original recession call) and that the National Bureau of Economic Research (NBER), which officially declares the start and end of recessions for the U.S. economy, would ultimately vindicate ECRI’s reading of the economic tea leaves. As ECRI continued to double-down on their recession call a cottage industry sprang up analyzing, and sometimes ridiculing, their proprietary methodology.

Whether ECRI ultimately is proved right or wrong about the U.S. economy being in recession, at least one question screams for an answer: what happened during the latter portion of 2011 so that the economy avoided what seemed to be an almost certain contraction? Perhaps more importantly, could it happen again at this time in 2012 and was the most recent upward revision in 2012.Q3 real GDP change the first sign of the economy gaining altitude?

While there are definitely some parallels between late 2011 and late 2012, we don’t think there are enough to say that lightning strikes twice and the upward revision in 2012.Q3 is the start of a new growth spurt. But let’s briefly examine what happened in late 2011 to see if there are any lessons for today.

There was a VERY significant private inventory buildup from 2011.Q2 to 2011.Q4 (see chart below); over this period private domestic investment ("PDInv") accounted for 77 percent of real GDP change while a more typical proportion is closer to 40 percent (see third chart in this post). Some of this increase in PDInv may have been to rebuild inventories from prior quarters during the business cycle.

Click on Image to Enlarge

As can be seen in the chart above, the quarterly average for personal consumption expenditures ("PCE") between 2009.Q2 to 2011.Q1 was $51.6 billion, 75 percent of the net change in the quarterly average real GDP change during that period (51.6 + 36.5 – 13.5 – 5.7, or $68.9 billion). That’s running pretty hot and no doubt some inventories were thin and some restocking was in order.

Further, some inventory building may have occurred purposely in anticipation of future sales increasing. However, with the benefit of 20/20 hindsight, any business betting on improving future sales was probably disappointed given how events unfolded. As can be seen on the first chart, real disposable personal income (“DPInc”) was actually contracting from 2011.Q2 to 2011.Q4 (negative real change). As a result, as the chart below shows, PCE fell from a quarterly average of $51.6 to $34.1 billion during the period 2011.Q2 to 2011.Q4.

Which leads to the third reason business inventories were increasing during this period: business inventory was piling up because consumers weren’t buying, creating an overhang in inventory. Thus, even though real GDP lurched higher over the last half of 2011, giving off signs that it had pivoted away from contraction, in actuality the economy was choking.

Click Image to Enlarge

By early 2012 the inventory overhang became clear and so domestic investment sharply contracted during 2012.Q1 to 2012.Q3; as can be seen in the chart above, PDInv on an average quarter basis plummeted from $65.6 billion to $20.2 billion.



So, to wrap up learning from what happened in late 2011, increases in PDInv were the principal forces pushing real GDP changes higher. Those increases were likely exacerbated by contractions in real DPInc.



Our observation is that despite the correction in PDInv over the past three quarters, the degree of real GDP growth attributable to PDInv is still high for the entire cycle when compared to the two most recent cycles’ first 13 quarters of growth. As can be seen in the chart below, PDInv has accounted for about 40 percent of real GDP change while, to date in the current business cycle, it accounts for 54 percent.

This suggests to us there will need to be yet more reductions in private investment over the coming quarters or a significant ramp-up in PCE to bring the rates back into balance with each other compared to other business cycles for the economy to truly move into a sustainable growth path.



The best outcome for the economy would be an increase in DPInc that translates into an increase in PCE. However, as the first graph of this post shows, during 2012.Q2 and 2012.Q3 the pace of real DPInc growth was slowing, not expanding. This makes a significant increase in PCE unlikely.

In fact, we would say the chance of this improving soon recently took another hit; the day after the second estimate for 2012.Q3 GDP release the BEA reported the latest statistics on DPInc in the November 30th Personal Income and Outlays release. The new data indicates that in real terms October’s DPInc fell by 0.1 percent (a drop of $12.2 billion) from September’s level while real PCE decreased by 0.3 percent (a drop of $29.5 billion).

Just to keep things in perspective, the average QUARTERLY GAIN in real PCE during the current recovery has been $45.2 billion (see second graph in this post) while the initial estimate for the MONTH of October was a DROP of $29.5 billion). Not exactly a great way to start 2012.Q4 if what is needed is a significant ramp-up in PCE.

In addition, buried down in the November 30 Personal Income and Outlays release, the BEA noted it had revised DPInc back through April 2012 and PCE back through July 2012. The BEA release provided revision details only for the months of August and September, not for all the months revised. For August and September, DPInc was revised $4.9 billion HIGHER in real dollars (-28.6 to -28.2 in August and -2.3 to +2.2 in September) and real PCE was revised $14.4 billion LOWER (+12.8 to -3.2 in August and +38.9 to +40.5 in September).

These revisions were incorporated into the second 2012.Q3 GDP estimate released on November 29.  The revisions explain the downward revision in consumer spending between the advance and second estimate that sent newswires buzzing with the seemingly contradictory messages of upwardly revised third quarter 2012 GDP growth but weaker fundamentals when internal details were examined. This, by way of example, from Reuters:

“It was the fastest growth since late 2011 and much quicker than the 2 percent rate the government estimated last month…Growth in consumer spending, which accounts for about 70 percent of U.S. economic activity, was cut by more than half a percentage point….”

And the full-tale may not yet be told. The blogsite Zerohedge compared October’s revised real DPInc series published on the St. Louis Federal Reserve site to the same data set they had downloaded the prior month and noted the BEA’s revisions resulted in reducing cumulative DPInc between April and September by $40 billion.

Even though these revisions were included as part of 2012.Q3’s second GDP estimate, BEA indicated the DPInc extend back into the second quarter as well. This suggests that 2012.Q2 GDP reported growth could be reduced in subsequent revisions (probably next year). But even though the revised statistics may not be known until next year, the reality they reflect is felt now.

Focusing in on 2012.Q3’s “final” estimate of real GDP change, while the estimate was revised higher, the increase relative to the advance/first estimate was mostly due to more spending on PDInv while PCE was revised lower than originally reported in the advance estimate (see our MacroPulse post on the second estimate for details).  The third 2012.Q3 estimate returned some of what was originally trimmed in PCE between the first and second estimates but only marginally while PDInv essentially unchanged between the second and third estimates (see our MacroPulse post on the third/final estimate for details).

While the increase in PDInv was not as out of balance with PCE as during the latter half of 2011, recall that through the course of this business cycle PDInv is higher than would be considered healthy compared to PCE. Thus, based on the final GDP estimate during 2012.Q3 no material progress was being made on bringing those back into balance.

Further, as was stated earlier, October’s PCE has turned down in real terms, potentially making the situation worse, not better. This is certainly not a good way to start 2012.Q4. While some of the reduction in PCE may be due to the impact of Hurricane Sandy, it is unclear to what extent the storm is affecting the numbers.

Some argue rebuilding and restoration activity in the aftermath of Hurricane Sandy will spur economic activity. However, to make such an argument means the deployment of economic resources to redress the hurricane’s damage is better than the deployment that would have occurred with those same resources if the economy hadn’t experienced hurricane damage. Our view is that, at best, such expenditures are simply redirected and a “push” in terms of the national economy, but not a source of economic stimulus resulting in increased economic activity.

Net exports were revised higher in both the second and third revisions of 2012.Q3’s GDP. Net exports contributed 0.38 percentage points of the 3.1 percent of real GDP growth in the latest 2012.Q3 GDP estimate, an increase from the 0.23 percentage point contribution in 2012.Q2.

Despite the net increase in the contribution between 2012.Q2 and 2012.Q3 we believe the underlying details point to a less positive fundamental: slowing global economic growth. First, U.S. exports fell from a contribution of 0.72 percent in 2012.Q2 to 0.27 percent in 2012.Q3 as trading partners’ economies slowed. However, the reduction in this case was mitigated by declining crude oil prices that caused the value of U.S. imports to fall. The cheaper price of crude oil imports was also due to shrinking global economic growth, the common denominator in this case.

Government spending, which has been mostly retreating throughout this business cycle, was revised higher in the third estimate from the advance estimate. However, the fact that government spending provided a positive contribution to 2012.Q3 real growth is significant when analyzing what lies ahead; a significant share of the government spending during 2012.Q3 was in defense spending.

We suspect the increase in government spending came about from three factors:

1. The end of the third quarter also marked the end of the Federal, and many state and local governments’, fiscal year, when frequently the “use it or lose it” mentality kicks into high gear.
2. With the fiscal cliff looming the potential for significant budget cuts are a real possibility for federal departments, particularly the Defense Department, spurring expenditures in advance of the calendar year deadline.
3. 2012.Q3 was also the homestretch of a presidential election, so any restraint that may have otherwise been imposed on federal spending was probably softened because government spending would serve to lift reported GDP, which could only help the incumbent.

So collecting the pieces together, in terms of government spending, none of these factors are replicable going forward in the near term and so government spending will likely subtract rather than add to GDP moving forward. Slowing global economic activity places any further near-term positive contribution to U.S. GDP in doubt as well. Finally, at some point the economy cannot continue to increase PDInv without consumers buying goods and services. And, consumers will have difficulty ramping up purchases if – as seems to be happening – DPInc growth stalls.

Our conclusion is that 2012.Q3’s rate of increase in GDP change relative to 2012.Q2’s rate of change is not the first step towards a repeat of what unfolded over the last half of 2011 when GDP churned higher. Instead, it is more a matter of levitation, the unlikely convergence of either unrepeatable or unsustainable events, than improvement based on economic fundamentals.