Forest Finance: Common Errors and Suggested Solutions

23 01 2013

News flash: we all make errors when analyzing forestry investments.  Which are the most common and how can we avoid them?

At the end of the day, most analytic errors in forestry relate to the data used – the inputs – or the math in a spreadsheet.  Errors associated with inputs affect the cash flows in the analysis and how it impacts value when discounted back to the present.  When reviewing models for clients, we commonly find errors associated with the assumed costs, the estimated revenues, the timing of cash flows and the expectations associated with inflation and asset appreciation.  Specifically, in our work and the work of others, we focus on and observe three major categories of errors in Excel models and spreadsheets.

First, we find that analytic errors in Excel are common.  Of all of the spreadsheet models we review, approximately one-third have an error in a formula (that we find). Most often, these are associated with “relative” and “absolute” referencing, where a formula is pulling in data from the wrong cell or worksheet.  Professor Ray Panko at the University of Hawaii, who actually conducts spreadsheet research (, noted in a 2006 interview with the Wall Street Journal that “you’re going to have undetected errors in about 1% of all spreadsheet formulas.”

Second, we observe application errors, which basically reference issues with the thinking behind the spreadsheet, the formula chosen, the use of a formula, or a comparison made.  For example, analysts commonly make mistakes with inflation by mixing real and nominal discount rates and cash flows.  Also, spreadsheet models of forestry investments may inappropriately compare before and after-tax results and investments of differing duration (time periods). Finally, using the incorrect metric can be problematic, such as misapplying cash-on-cash return, pay back analysis and internal rate of return (IRR).  We typically find errors of this type when analysts are comparing timberland and forestry investments with alternative asset classes, such as stocks, bonds, agricultural commodities and commercial real estate.  Historically, the day-to-day metrics for forestry differed in application, so a bit of time spent checking assumptions and thinking through the communication of results can be helpful.

Third, errors of omission are especially problematic (and embarrassing).  We work hard to avoid the situation of being asked “did you check _____?” and, if relevant, having to answer “No, we didn’t think of that.”  Ugh.  Unfortunately, we find that third-party spreadsheets often omit key facts or considerations, including relevant costs and potential revenues.  Just as important can be confirming that the assumed costs and revenues are current and reflect the best available, accessible information.  In short, know what’s knowable.

We observe a few key practices in our work with clients to minimize the chance and occurrence of errors.  First, we label tabs and worksheets, and date all files. That way, if we revisit a model several weeks or months later, we can retrace our steps and know what we’re working with.  Also, if we correct an error or make another improvement, we know which version is the most current.  Second, we try to set aside time to check each other’s work before sending results “out the door.”  Admittedly, this is also the most challenging.  We find that imposing and embracing milestones – midpoints for deliverables or reviewing work – throughout a project institutionalize a level of quality control.  Finally, at the end of the day, we ask ourselves the question “where could we have blown this?” Some level of paranoia and self-awareness is required for quality analysis of forestry, or any other, investments.

Click here to register for “Applied Forest Finance” on February 7th in Atlanta.  The course details skills and common errors associated with the financial and risk analysis of timberland and other forestry-related investments.


Timber REITs Accelerate Past the S&P 500 YTD for 2012

5 07 2012

As we hit midfield for 2012 and closed out the second quarter, the timber REIT sector as measured by the Forisk Timber REIT (FTR) Index posted a 12.09% gain relative to 8.31% for the S&P 500 (click here for the free FTR Weekly Summary).  While the year-to-date results vary by firm (see table), the sector benefited from (1) strong exposure to improving markets for homes and construction in key US regions and (2) attractive dividend yields relative to other industries and REIT subsectors.

For investors and analysts tracking wood and timber REIT markets, Forisk offers “Timber Market Analysis” on August 15th in Atlanta, a one-day course detailing a step-by-step process to understand, track, and analyze the price, demand, supply, and competitive dynamics of timber markets and wood baskets. For more information, click here

Forecasting Stumpage Prices and Timberland Investment Performance Requires Local Knowledge of Wood Demand

16 10 2011

Last week, I met with the CEO of one of world’s largest forest management and consulting firms.  We ended up discussing a mutually perplexing question, “why do some timberland investors prioritize macro issues like housing at the expense of understanding market-specific issues such as local wood demand, mill risk and actual forest inventories?”  While housing market forecasters have, once again, delayed expectations of the anticipated home building recovery, Forisk analysis of local timber markets affirms the primacy of micro-market, investment specific factors over regional and national trends.

Shifts in forest supplies and wood demand influence regional timber markets. The extent to which sub-regional markets, such as mill-specific wood baskets or property-specific timber markets, are influenced by regional or macroeconomic changes remains unclear.  Previous analyses by USDA Forest Service and University researchers such as Bob Abt, Fred Cubbage, Tom Holmes, David Newman, Jeff Prestemon, and Runsheng Yin, estimate a price elasticity of demand for softwood stumpage ranging from -0.50 to -0.57 and a price elasticity of supply ranging from 0.29 to 0.50.

This implies that for every 1% change in price, changes in demand or supply will be considerably less than 1%. [This also implies that for every 1% change in demand, price changes would exceed 1%.]

In 2005, Forisk Consulting began collecting mill-specific wood demand data on a quarterly basis throughout the US South.  In 2008, we expanded this coverage to the continental United States.  Today, our team manages an ongoing research program that collects and confirms data on 3,196 announced and operating wood-using forest industry and wood bioenergy mills throughout the US.  We believe this to be the most comprehensive and current tracking of US forest industry health and demand available in the world.

How has this research helped the forest industry and timberland investors?  We have found that local market performances have wide ranges of price-to-demand elasticities and mill risk profiles, beyond those established in regional or national analyses.  The differences across markets are statistically significant and provide a rigorous basis to adjust market-specific discount rates, stumpage price forecasts and expected rates of recovery.

For example, the expected price effect from a demand shock (i.e. a new mill) in a sub-regional market depends heavily on:

  1. Available forest inventories and growing conditions; and
  2. The competitiveness and distribution of wood-using mills in the local market.

Competitive markets with multiple mills can aggravate and prolong the impact of a demand shock on prices.  Alternately, competitive markets provide the best uses of new capital for timber and forest industry investments when benchmarked against ranges of wood baskets and timber markets across multiple performance criteria.

Despite Wet Weather, Pine Grade Markets Recover; Use of Woods-Direct Chips Increasing

23 04 2010

Southern demand for pine grade timber raw materials rebounded 6.1% during the 1st quarter of 2010, according to the Wood Demand Report, after reaching five-year lows the previous quarter.  Data providers reported that “markets have turned around” while others confirmed restarting production during the past few quarters.   Several mill managers expressed concern that, while markets improved, they feared that mills may overproduce in the near-term, thereby suppressing potential price recovery for end products such as lumber and plywood.

Pine pulpwood demand increased 1.1% South-wide during the quarter at both pulp and OSB mills.  In addition, the 1st quarter produced the highest reported consumption of in-woods chips for both pine and hardwood since 2006.  Consumption of both products has increased gradually over the past few years.

Looking ahead, we expect increasing consumption to continue.  Pulpwood demand in the US South is projected to recover in two years and reach pre-decline highs by 2013, according to the ForiskForecast.  Demand by pulp and paper users will be modest, and OSB producers will “consume more as the housing market recovers,” according to Dr. Tim Sydor, Forisk’s Forest Economist.  The primary growth in pulpwood demand will be from wood bioenergy customers.  We project wood bioenergy producers in the South will consume a pulpwood equivalent on par with OSB producers by 2015.