er 

Forest Service tumpage Pric 

ortheastern Forest 

Experiment Station 

Research Paper NE-683 
Abstract 

State and regional weighted averages were calculated for timber stumpage prices 

for the northeastern region. The weighting factor was the timber volume harvested. 

The regional price series for hardwood sawtimber, softwood sawtimber, hardwood 

pulpwood, and softwood pulpwood are reported for the 31 -year period, 1961 to 

1991. Hardwood sawtimber prices increased at the average annual rate of 10.3 

percent (nominal), softwood sawtimber at 6.4 percent, hardwood pulpwood at 6.5 

percent, and softwood pulpwood at 5.3 percent. Inflation, as measured by the 

All-commodity, Producer Price Index, averaged 5.7 percent per year over the 

31 -year period. 

The Author 

PAUL E. SENDAK, forest economist, received a B. S. degree in forestry from 

Rutgers University in 1965, and an MS. degree in forestry in 1968 and Ph.D. 

degree in forest economics in 1972 from the University of Massachusetts. He joined 

the Northeastern Forest Experiment Station in 1969 and since 1993 has been 

engaged in research on ecology and management of northern hardwoods and 

associated ecosystems at the Northeastern Station's Forestry Sciences Laboratory, 

Durham, New Hampshire. This paper resulted from research conducted while he 

was forest economist and Project Leader of the research unit on economic potential 

of forest production in the North at the Northeastern Station's Forestry Sciences 

Laboratory in South Burlington, Vermont. 

Acknowledgment 

I thank R. Charlotte Jasko and James Bove for collecting, organizing, and computer 

entering of the timber stumpage price data from various states that we used in this 

study. 

Manuscript received for publication 9 September 1993 

USDA FOREST SERVICE 

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January 1994 

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Introduction 

Economic models are important tools in planning natural 

resource programs and in managing natural resources. The 

U.S. Department of Agriculture, Forest Service uses the 

Timber Assessment Market Model (TAMM) to model timber 

markets for the Resource Planning Act (RPA) Assessment 

(Adams and Haynes 1980, Haynes 1990). 

Although relatively good stumpage or mill-delivered. timber 

prices exist for softwood timber in the West and South, such 

is not true for hardwood and softwood timber in the North. 

This has been a problem in modeiing timber markets in this 

region. Analysts are forced to develop their own price series 

from published data, or in some cases, to choose a long 

running series such as that published in New Hampshire, and 

let that represent a multi-state region. 

On investigation, the problem isn't a lack of data. There are 

some relatively long price series in the Northeast covering 30 

or more years. Now, oowever, almost all of the 12 

Northeastern States publish some type of stumpage price 

report (Lutz et al. 1992). In particular, hardwood lumber 

production has been increasing in the North relative to the 

South (Luppold and Dempsey 1989). As a result, many 

states began collecting and publishing stumpage prices 

during the 1980's. The problem is one of aggregating the 

data in a meaningful way to capture market trends for the 

region or multi-state sub-region. 

Cardellichio and Binkley in 1983 set forth four criteria for a 

stumpage price series1: 

.sufficient historical data should be available for each price 

series to facilitate econometric estimation of ... timber supply 

functions. ..; 

.the price series should be representative of the 

geographical regions within the model ...; 

....the price series should measure a large volume of sales 

within that region; and 

.data from a single source are preferable to data derived 

from combining several sources to ensure comparability 

across regions and over time. 

They found that there is no one data source in the Northern 

States that satisfies these criteria. The next best choice is to 

find a series or aggregate of two or more series to satisfy as 

many of the first three criteria as possible. 

The specific objective of this study, recognizing the new 

sources of data that have become available, was to create a 

price series for timber stumpage that reflects the trends in 

Cardellichio, Peter A.; Binkley, Clark S. 1983. Stumpage 

prices in the hardwood assessment market model. 

[Unpublished.] On file with: School of Forestry, Yale 

University, New Haven, CT. 

regional prices over time. The four price series of interest are 

hardwood sawtimber and pulpwood and softwood sawtimber 

and pulpwood. 

Data and Methods 

Table 1 is a summary of the stumpage price information 

available for the 12 northeastern states (Lutz et al. 1992). It 

shows major attributes of the reports by state. All were 

entered into computer files. Information on annual timber cut, 

by state, was not available for all the states. Since timber-cut 

volume was used as a weighting factor in computing regional 

aggregates, Forest Inventory and Analysis (FIA) reports on 

timber cut, by state, were used to provide these estimates. 

An advantage of using the FIA reports is that the information 

is collected for all states using the same methods. A 

disadvantage is that the period covered by the report is 

different for almost all the states and the information for any 

one state is collected and reported approximately once every 

10 years. The latest quantity information for each state was 

used as the weighting factor. 

The rule applied was to include the fewest number of species 

that accounted for at least 85 percent of the total cut as 

reported by the most recent forest inventory. If the 85-percent 

level was reached, additional species were included if they 

accounted for at least 5 percent of the total cut. In most 

cases, the rule was applied successfully. But there were 

exceptions due to poor correspondence between reporting 

categories among the various reports. Within a state and 

product group, such as hardwood sawtimber in New York, a 

volume-weighted average price for species in that group was 

calculated. These averages then were weighted by total 

timber volume cut for each product group to calculate 

region-wide averages. A weighted average was used 

because a simple average of prices would fail to account for 

the relative importance of different species and different 

states in determining an average price. Through weighting, 

those species cut in the greatest quantities and those states 

that harvested the greatest quantities were assigned more 

importance in calculating an average price. 

The method used here is analogous to the calculation of a 

general price index, such as the Consumer Price Index. The 

fixed quantity assumption was necessary because the annual 

quantity of timber cut by state was not available. However, 

the requirement of a base-year quantity was not met fully 

because the timber-cut data were not reported for the same 

year. If the different species within states and the states in 

the region retain the same relative position from year to year, 

the aggregate regional prices will provide a reliable measure 

of stumpage price change over time. This is a reasonable 

assumption, because relative quantity cut by species tends to 

change slowly over time. Of more concern are changes in 

average timber quality and size and local scaling practices. 

The qualitysize factor also changes slowly over time but 

could be significant if sales reported were biased toward very 

poor or very good quai* timber. The local scaling factor can 

change more quickly with changes in demand for consumer 

goods that use wood in their manufacture. As prices for sawn 

wood products decrease, sawmills may not only decrease 
Table 1.--Summary sf important characteristics of timber stumpage price reports published in the Northeasta 

State Type of data Year reporting 

collected initiated 

CT All stumpage 1988 

DEC All stumpage 1985 

ME All stumpage 1959 

MA All stumpage 1988 

NH Private stumpage 1948 

NY All stumpage 1972 

PA All stumpage 1983 

RI All stumpage ' 1988 

VT All stumpage 1981 

Reporting 

frequency 

Reporting region Price statistic(s) Reporting units 

b reported 

Number 

d Median, high, low Mbf lnt-1/4", cords 

1 Weighted average Mbf unspecified 

scale, cords 

8 Average of "most Mbf lnt-1/4", cords, 

common" prices, tons 

high, low 

d Median, high, low Mbf lnt-1/4", cords 

10 High, low Mbf lnt-1/4", cords 

14 "Most common," Mbf lnt-1/4", 

high, low Scribner, Doyle; 

cords 

4 Average, standard Mbf lnt-1/4", tons 

deviation 

d Median, high, low Mbf lnt-I/@, cords 

3 Median, high, low Mbf lnt-I/@, cords 

WV All stumpage 1986 1 5 Median, high, low Mbf Doyle, cords 

aMaryland and New Jersey do not publicly report timber stumpage prices. 

bReporting regions are adjusted occasionally; these represent the regions in 1988. 

=All states but Delaware publish stumpage prices by species. dConnecticut. Massachusetts. and Rhode Island ~ublish acombined report for Southern New England with two reporting regions--east, or west of the Connecticut River. 

their log prices, which are reflected in stumpage prices, but 

they may tighten their log grading rules or lower their 

estimate of volume contained in a log. This latter action is not 

reflected in the stumpage price. All these effects can be 

gradual or sudden, operate in the same or different direction, 

but are not measurable by any of the stumpage price sources 

used in this study. 

Maine 

The source of stumpage prices was Maine Forest Service 

(1 963-91) and for timber volume cut, Nevel et al. (1 985). 

Three species--spruce, white pine, and balsam fir--accounted 

for 89 percent of the softwood sawtimber cut. Five 

species-hard maple, yellow birch, beech, ash, and 

aspen-accounted for 58 percent of the hardwood sawtimber 

cut. The "Other hardwoods" category accounted for 42 

percent of the hardwood sawtimber cut, but no corresponding 

category existed in the Stumpage Price Report, so the 

category was eliminated. For the pulpwood groups, all 

hardwoods and all softwoods accounted for 100 percent of 

the pulpwood cut. 

New Hampshire 

The source of stumpage prices was Engalichev (1 961 -91) 

and for timber volume cut, Nevel et al. (1986). New 

Hampshire reports price ranges by timber quality class for 

most species. When quality was reported, the medium quality 

class was used. The average price was assumed to be the 

center of the reported range. Three species--white pine, 

spruce-fir, and hemlock--accounted for 99 percent of the 

softwood sawtimber volume cut. Six species-oaks, hard 

maple, white birch, yellow birch, ash, and beech-accounted 

for 91 percent of the hardwood sawtimber cut. For softwood 

pulpwood, prices for spruce-fir in the north and central 

regions of New Hampshire were used. Hardwood pulpwood 

prices also were from the north and central regions. For the 

pulpwood groups, all hardwoods and all soft~oods 

accounted for most of the pulpwood cut. 

New York 

The source of stumpage prices was New York State 

Department of Environmental Conservation (1974-91) and for 

timber volume cut, Nevel et al. (1 982). Three species--white 

pine, hemlock, and red pine--accounted for 97 percent of the 

softwood sawtimber volume cut. Eight species-hard maple, 

red oak, soft maple, black cherry, beech, ash, basswood, and 

white oak--accounted for 92 percent of the hardwood 

sawtimber cut. For the pulpwood groups, all hardwoods and 

all softwoods accounted for 100 percent of the pulpwood cut. 

Pennsylvania 

The source of stumpage prices was Pennsylvania State 

University (1987-91) and for timber volume cut, Bones and 

Shewood (1 979). Two species--hemlock and white 

pine--accounted for 96 percent of the softwood sawtimber 

cut. Nine species--red-black oak, black cherry, white oak, soft 

maple, hard maple, chestnut oak, yellow-poplar, scarlet-pin 

oak, and ash--accounted for 91 percent of the hardwood 
Table 2.--Average nominal and reala stumpage prices, by product group, in the Northeast, 1961-91 

Year Hardwood sawtim ber Softwood sawtimber Hardwood pulpwood Softwood pulpwood 

Nominal Real Nominal Real Nominal Real Nominal Real 

aAdjusted for inflation by the Producer Price Index, All-commodity (1982 = 100). 
sawtimber cut. Chestnut oak was grouped with white oak and 

scarlet-pin oak was grouped with red-black oak to match the 

price-reporting categories. For the pulpwood groups, a11 

hardwoods and all softwoods accounted for 100 percent of 

the pulpwood cut. 

Southern New England (Connecticut, Massachusetts, 

and Rhode Island) 

The source of stumpage prices was University of 

Massachusetts (1 988-91) and for timber volume cut, 

and Wharton (1 988). Two species--white-red pine and other 

softwood--accounted for 100 percent of the so~ood 

sawtimber cut. Three species--oaks, beech-birch-maple, 

other hardwoods--accounted for 100 percent of the hardwood 

sawtimber cut. No pulpwood prices are reported for southern 

New England. 

Vermont 

The source of stumpage rices was McEvoy (1982-94) and 

for timber volume cut, Nevel et al. (1 986). Three 

species--white pine, spruce-fir, and hemlock--accounted for 

96 percent of the softwood sawtimber cut. Four species--hard 

maple, oaks, yellow-birch, and ash--accounted for 71 percent 

of the hardwood sawtimber cut. For the pulpwood groups, all 

hardwoods and all softwoods accounted for 100 percent of 

the pulpwood cut. 

est Virginia 

The source of stumpage prices was Murriner (1989-91) and 

for timber volume cut, Bones and Glover (1977). Two 

species--yelow pine and white pine-accounted for 46 

percent of the softwood sawtimber cut. There was poor 

correspondence among categories in the price and timber cut 

reports, resulting in a small percentage of the total softwood 

cut included here. Eleven species--northern red oak, yellowpoplar, other red oak, chestnut oak, white oak, hard maple, 

hickory, soft maple, basswood, black cherry, and 

ash-accounted for 90 percent of the hardwood sawtimber 

cut. Northern red oak and other red oak were combined to 

match the price-reporting category of red oak. All hardwood 

pulpwood accounted for 100 percent of the pulpwood cut. No 

prices were reported for softwood pulpwood. 

In general, simple averages of prices reported by regions 

within states were calculated to obtain statewide averages 

and annual averages from quarterly or semi- annual reports. 

Adjustments were made when data anomalies were 

encountered due to changes in reporting format or missing 

observations. Sawtimber prices reported in Doyle or Scribner 

log-rule volume were converted to International 114-inch-rule 

volume (Pennsylvania State University 1987-91). Pulpwood 

prices reported by weight were converted to standard cord 

(Nevel et al. 1986). 

Results 

Table 2 shows the average timber stumpage prices for the 

four product groups for the Northeast from 1961 -91. Along 

with the nominal prices are the real prices, in 1982 dollars. 

Inflation, as measured by the All-commodity, Producer Price 

Index, averaged 5.7 percent per year over the time period. 

The nominal regional prices are plotted over time in Figures 1 

through 4. The individual state ,price series also are plotted in 

the same figures. These plots show at a glance the inclusion 

of states in the regional average and their tracking with the 

regional average and with the other states. The regional 

average includes Maine and New Hampshire from 1961 to 

1974 when New York was added. Vermont was included 

starting in 1982, Pennsylvania in 1985, southern New 

England in 1988, and West Virginia in 1989. Earlier 

stumpage prices exist for some of these states, but some of 

the data were reported in substantially different format or 

sporadically. 

For hardwood sawtimber (Fig, I), the single state that comes 

closest to tracking the regional series is New York. For 

softwood sawtimber (Fig. 2), New Hampshire comes closest 

to tracking the regional series. For hardwood and especially 

softwood pulpwood (Figs. 3 and 41, the regional series 

follows the Maine series closely, due to the large pulpwood 

volume harvested in the state. 

Finally, Table 3 presents the annual percentage rate of 

change in the regional stumpage price series for the 1961 to 

1991 period, for both nominal and real prices. The rates were 

estimated using the regression procedure in Sendak (I 991). 

Generalized least squares (GLS) was used to estimate the 

real rates of change because the regression residuals were 

serially correlated (see, for example, Johnston 1972). The 

result of serially correlated residuals in ordinary least squares 

regression is an unbiased estimate of the rate of change, but 

its standard error is underestimated leading to a higher 

t-value. Because the real rates of change were close to zero, 

GLS was used to obtain efficient estimates, decreasing the 

chance of making a Type I error. 

Hardwood sawtimber, for both nominal and real prices, had 

the greatest rate of increase over the 31 years. Real prices 

increased at an average rate of 4.5 percent per year. 

Softwood sawtimber prices kept ahead of inflation; real prices 

increased at an average rate of almost 1 percent per year. 

Pulpwood, both hardwood and softwood, increased at about 

the rate of inflation, with real prices showing no increase over 

the 31 -year period. 

Table 3.--Nominal and real annual percentage rate (APR) 

of change in Northeast stumpage prices, by product 

group, 1961 -91 

Species and product group Nominal Real 

------------- Percent --..-------- 

Sawtimber 

Hardwood 

Softwood 6.4 0.7 

Pulpwood 

Hardwood 

Softwood 

aNot significantly different from zero (p 4 0.05). 
61 63 65 67 69 71 73 75 77 79 81 83 85 87 69 91 YEAR 

HARDWOOD SAWTIMBER 

Figure 1 .--Hardwood sawtimber stumpage price in dollars per 

Mbf (International 114-inch rule) for the Northeast and by 

state, 1961 -91. 

'REGIONAL 

61 63 65 67 69 71 73 7LR77 70 81 83 85 87 89 91 

HARDWOOD PULPWOOD 

Figure 3.--Hardwood pulpwood stumpage price in dollars per 

cord for the Northeast and by state, 1961 -91. 

61 63 65 67 69 71 73 Th77 79 81 83 85 87 89 91 

SOFTWOOD SAWTIMBER 

Figure 2.--SoWood sawtimber stumpage price in dollars per 

Mbf (International 114-inch rule) for the Northeast and by 

state, 1961 -91. 

oIIII,lI,IIIIIIl,IIIIIIIIIIIIII1 

61 63 65 67 69 71 73 7:u!7 74 81 83 85 87 89 91 

SOFTWOOD PULPWOOD 

Figure 4.--SoWood pulpwood stumpage price in dollars per 

cord for the Northeast and by state, 1961 -91. 
Summary 

Timber stumpage prices have been estimated for the 

Northeast. State reported stumpage prices were weighted by 

timber cut within states and within the region. Species or 

species groups that represent large volumes of the timber 

cut, both within states and within the region, have a greater 

influence on the regional stumpage prices than do the 

relatively minor species. The regional prices meet some of 

the criteria listed by Cardellichio and Binkley cited in the 

Introduction. A series consisting of 31 years is of sufficient 

length for econometric estimation of timber supply functions. 

Prices are included for up to 9 states in the 1 2-state region 

for good geographical representation. Although the coverage 

of sales probably differs from state to state, the weighting by 

volume harvested somewhat addresses this issue by placing 

emphasis on commercially important species. 

Literature Cited 

Adams, Darius M.; Haynes, Richard W. 1980. The 1980 

softwood timber assessment market model: structure, 

projections, and policy simulations. Forest Science 

Monograph 22 [Suppl. to Forest Science. 26(3)]. 64 p. 

Bones, James T.; Glover, Ralph P., Jr. 1977. The timber 

industries of West Virginia. Resour. Bull. NE-47. Upper 

Darby, PA: US. Department of Agriculture, Forest Service, 

Northeastern Forest Experiment Station. 16 p. 

Bones, J. T.; Sherwood, J. K. 1979. Pennsylvania timber 

industries-a periodic assessment of timber output. 

Resour. Bull. NE-59. Broomall, PA: U.S. Department of 

Agriculture, Forest Service, Northeastern Forest 

Experiment Station. 26 p. 

Engalichev, Nicolas. 1961 -91. New Hampshire forest 

market report: 1961-91. Durham, NH: University of New 

Hampshire Cooperative Extension Service. In cooperation 

with: New Hampshire Department of Resources and 

Economic Development. 

Haynes, R. W. 1990. An analysls of the timber situation In 

the United States: 1989-2040. Gen. Tech. Rep. RM-199. 

Fort Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Forest and Range Experiment 

Station. 286 p. 

Johnston, J. 1972. Econometric methods. 2nd ed. New 

York: McGraw Hill. 437 p. 

Luppold, William; Dempsey, Gilbert P. 1989. New estimates 

of Central and Eastern US. hardwood lumber 

production. Northern Journal of Applied Forestry. 6: 

120-1 23. 

Lutz, Jack; Howard, Theodore E.; Sendak, Paul E. 1992. 

Stumpage price reporting In the northern United 

States. Northern Journal of Applied Forestry. 9(2): 69-73. 

McEvoy, Thomas J., ed. 1982-91. Vermont forest 

quarterly: 1982-91. Burlington, VI: University of Vermont 

School of Natural Resources. In cooperation with: U.S. 

Department of Agriculture, Forest Service and Vermont 

Department of Forests, Parks and Recreation. 

Maine Forest Service, Department of Conservation. 1963-91. 

Stumpage prices: 1963-91. Augusta, ME: Management 

and Utilization Division. 

Murriner, Edward C. 1989-91. West Virginia timber price 

report: 1989-91. Charleston, W: West Virginia Division of 

Forestry. 

Nevel, Robert L., Jr.; Engalichev, Nicolas; Gove, William G. 

1986. The timber industries of New Hampshire and 

Vermont--a periodic assessment of timber output. 

Resour. Bull. NE-89. Broomall, PA: U.S. Department of 

Agriculture, Forest Service, Northeastern Forest 

Experiment Station. 56 p. 

Nevel, Robert L., Jr.; Lammert, Peter R.; Widmann, Richard 

H. 1985. Maine timber output. Resour. Bull. NE-83. 

Broomall, PA: U.S. Department of Agriculture, Forest 

Service, Northeastern Forest Experiment Station. 42 p. 

Nevel, Robert L., Jr.; Sochia, Everett L.; Wahl, Thomas H. 

1982. New York timber industries-a periodic 

assessment of timber output. Resour. Bull. NE-73. 

Broomall, PA: U.S. Department of Agriculture, Forest 

Service. 30 p. 

Nevel, Robert L., Jr.; Wharton, Eric H. 1988. The timber 

Industries of southern New England-a periodic 

assessment of timber output. Resow. Bull. NE-101. 

Broomall, PA: U.S. Department of Agriculture, Forest 

Service, Northeastern Forest Experiment Station. 28 p. 

New York State Department of Environmental Conservation. 

1974-91. Stumpage price report: 197491. Albany, NY: 

Bureau of Land Resources, Division of Lands and Forests. 

Sendak, Paul E. 1991. Re-expressing interest rates 

estimated from the exponential model. Northern Journal 

of Applied Forestry. 8: 172-1 73. 

Pennsylvania State University. 1987-91. Pennsylvania 

woodlands timber market report: 1987-91. University 

Park, PA: School of Forest Resources, Cooperative 

Extension Service. 

University of Massachusetts. 1988-91. Forest products 

market trends in southern New England: 1988-91. 

Amherst, MA: University of Massachusetts, Cooperative 

Extension System. In cooperation with: Connecticut 

Extension Service and Rhode Island, Connecticut and 

Massachusetts State Forestry Agencies. 

*U. S. GOVERNMENT PRINTING OFFICE: 1993-550- 1 12/80007 
Sendak, Paul E. 1994. Northeastern regional timber stumpage prices: 

1961-91. Res. Pap. NE-683. Radnor, PA: U.S. Department of Agriculture, 

Forest Service, Northeastern Forest Experiment Station. 6 p. 

State and regional weighted averages were calculated for timber stumpage 

prices for the northeastern region. The weighting factor was the timber volume 

harvested. 

Keywords: Price analysis; regression analysis; price series 
Headquarters of the Northeastern Forest Experlment Station is in Radnor, Pennsylvania. Field laboratories are maintained at: 

-- - 

Amherst, Massachusetts, in cooperation with the University of Massachusetts 

Burlington, Vermont, in cooperation with the University of Vermont 

Delaware, Ohio 

Durham, New Hampshire, in cooperation with the University of New Hampshire 

Hamden, Connecticut, in cooperation with Yale University 

Morgantown, West Virginia, in cooperation with West Virginia University 

Orono, Maine, in cooperation with the University of Maine 

Parsons, West Virginia 

Princeton, West Virginia 

Syracuse, New York, in cooperation with the State University of New York, 

College of Environmental Sciences and Forestry at Syracuse University 

University Park, Pennsylvania, in cooperation with The Pennsylvania State University 

Warren, Pennsylvania 

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