How to Estimate Market Value

There are too many variables to create a simple formula, but this data-based method can help you estimate residual equipment values

Construction Equipment - June 1, 2004

Mike Vorster
Contributing Editor

Many equipment managers circumvent market value by being overly conservative and assuming a zero residual value in the owning-cost calculation. Yet a simple, efficient method of estimating residual values will produce rate calculations that are more accurate, more competitive, and closer to reality.

The true residual value of a machine when sold at any point in its life is an unknown that depends on many factors. Make, model, type and age when sold are the underlying determinants with other factors such as the condition of the machine and the amount of life left on major wear items affecting individual transactions. (See "How to Reduce Loss in Value," December 2003, p. 75.) The state of the economy, the amount of work in the area, and the machine's ability to meet current environmental standards also have a major impact. It is impossible to develop a formula for use under all conditions.

But if we have sufficient historical data, we can make accurate estimates of residual value by setting up a system to turn the data into information. Here's how:

Define a category by identifying a type, size or make of machine for which you would like to determine residual values. The more closely defined the category the better. It is important to distinguish between makes and models, but defining the category too closely makes it difficult to obtain necessary data.

Obtain market data that gives the residual value and age for the defined machines that have been sold in your area in the recent past. The best data come from machines that you have sold, because you know the terms of the transaction and the age of the machine. Published auction results also provide excellent data, although age is normally expressed in years and calculated as the difference between the date of manufacture and the date of sale. The availability of the data and the ability to sort by make, model, region and date of sale make auction data easy to use. You can create a very good database by combining your own data with published auction results. Ten to 20 pairs of data points giving age and residual value will be sufficient to provide a good basis for analyzing a particular category.

Determine Residual Value Percentage by dividing the recorded residual value by the standard purchase price (or manufacturer's list price). Residual value percentage helps normalize the data so that you can use the results to estimate the residual value for similar machines with different purchase prices.

Plot the data and insert a trend line. Use a large piece of graph paper or a spreadsheet program to plot the residual value percentages on the vertical axis and age on the horizontal axis. Draw a trend line to give an average or "best fit" representation of the plotted data points. Some points will be above the line and some points will be below the line. The objective is to find the average value of the data.

Use the trend line to estimate how the residual value percentage varies with age. The fact that the data were collected for sales made in your area in the recent past should eliminate many of the variations caused by location and economic conditions and give you confidence in the results. Select the age along the horizontal axis, go up to the trend line, and read the expected residual value percentage on the vertical axis. Multiply the purchase price of the new machine by the residual value percentage to arrive at your best estimate for the residual value of the machine at that particular age.

The table shows seven of the 16 data points collected to estimate the residual value percentage for Group II excavators operated at a quarry. All 16 data points are plotted in the accompanying chart, and the trend line has been added. The estimated residual value percentage for this class of excavator in the given market is approximately 35 percent after three years and approximately 25 percent after four.

The impact of utilization or total hours worked on the residual value percentage is a contentious issue that is difficult to resolve. Auction companies wisely steer clear of publishing hours worked due to the fact that it is difficult to confirm the data with confidence. If reliable data giving both age in hours and residual value are available, then it is possible to use this method with hours worked rather than age in years on the horizontal axis.

Most experts agree that residual value percentages based on age in years and age in hours will yield similar results as long as the average hours worked per year remains close to the norm for the particular category of machine. Varying either above or below this norm seems to impact the residual value percentage adversely as under-utilization leads to suspicion that the recorded hours worked are not reliable and over-utilization leads to the assumption that the machine has been overworked and, perhaps, under-maintained.

This method is a simplified version of one developed for an extensive study into the residual value of certain classes of construction equipment recently completed here at Virginia Tech. For a description of this study and access to the tool developed to estimate residual values.

Sample Data
Date of Manufacture	Date of Sale	List Price	Residual Value	Age at Sales (years)	Residual Value Percentage
For our example, we used data for 16 excavators (seven are shown), plotting age at sale and residual value percentages. Data on 10 to 20 machines is sufficient to provide a good basis for analyzing a particular category.
August '97	Nov-03	$105,000	$21,000	6.3	20%
December '97	Dec-03	$110,000	$26,500	6.0	24%
January '98	Dec-03	$110,000	$22,000	5.9	20%
April '98	Jan-04	$105,000	$24,200	5.8	23%
October '98	Jan-04	$110,000	$23,100	5.3	21%
February '00	Jan-04	$114,000	$31,000	3.9	27%
January '99	Feb-04	$110,000	$28,600	5.1	26%