United States 

Department of 

Agriculture 

Forest Service 

A Regional Analysis 

Northeastern Forest 

Experiment Station 

of Pallet Supply 

Research Paper 

N E-580 and Demand 

William G. Luppold 

R. Bruce Anderson 
The Authors 

I William G. Luppold attended the University of Florida where he received 

his B.S.A. and M.S.A. in food and resource economics in 1974 and 1977, 

respectively. After receiving a Ph.D. in agricultural economics from Virginia 

Polytechnic Institute in 1981, he joined the Northeastern Forest Experiment 

Station, Forestry Sciences Laboratory, Princeton, West Virginia. He is currently Project Leader of a Forest Service economics research unit. 

R. Bruce Anderson received a B.S. degree in forest science from The 

Pennsylvania State University in 1965 and an MS. degree in wood science 

1 from the same institution in 1970. For the past 15 years, he has been 

engaged in research on improved marketing and economic utilization of 

low-grade hardwood in various forest products industries at the Northeastern Forest Experiment Station, Forestry Sciences Laboratory, Princeton, 

West Virginia. He is currently working as an economist on problems associ- t ated with the economic analysis of the production and di~tribution~of hardwood products. 

Manuscript received for publication 29 August 1985 

Abstract 

Eight regional demand and supply equations for pallets were developed 

in this study. Demand for pallets is affected by the price pallet users 

receive for their products, the price pallet users pay for labor, and past 

price of labor versus the cost of new capital equipment as approximated by 

interest rates. Pallet production is affected by pallet price, past lumber 

price, past wage rates in the pallet industry, and an index of labor productivity. Results indicate that forces outside of the pallet market tend to influence pallet demand, while forces inside of the pallet market greatly 

influence pallet supply. However, since the level. of demand has a great deal 

of influence on pallet price, it is concluded that the pallet market is 

strongly influenced by overall general economic activity, while it is only 

weakly influenced by activity within the forest products markets. 
Introduction 

The pallet industry has grown rapidly since 1935, 

with major growth periods in the early and late 1970's 

(Fig. 1). Both of these strong growth periods were 

marked by increasing industrial output coupled with 

escalating labor costs. The only major downturn in 

pallet production occurred during the 1974-75 and 

1981-82 economic recessions. 

In 1982, the pallet industry consumed more than 3 

billion board feet of hardwood lumber and more than 

600 million board feet of softwood lumber. These quantities represent a minimum of 36 percent of the hardwood lumber and 9 percent of all lumber consumed in 

PALLETS PRODUCED (millions) 

the United States during 1982. This level of consumption makes the pallet industry the largest user of hardwood lumber and the second largest user of all lumber 

in the United States. 

If present pallet use and pallet construction methods are continued, the resulting demand for hardwood 

lumber for pallets has the potential to cause regional 

problems in the supply of hardwood raw material. In 

order to assess the impact that the pallet industry will 

have on the regional distribution of our hardwood 

resource in the future, information on the regional 

demand, supply, and price of pallets is needed. 

YEAR 

Figure 1.-Pallet production 1935-83. 
The Pallet Market 

Pallets are produced nationwide at approximately 

1,800 plants employing more than 23,000 workers (U.S. 

Department of Labor 1984'). Pallets are an inexpensive 

product produced from low-grade lumber at relatively 

small plants that employ unskilled or semi-skilled labor. 

However, the cost of transporting pallets is high relative to the cost of pallet production. Therefore, pallets 

are normally produced in close proximity to the 

purchaser. 

Pallet firms tend to produce for local or regional , markets, depending in part on the size of the firm. Very 

small firms tend to compete solely in local markets, 

while the larger firms tend to compete in larger geographic areas. In a study of pallet firms in the Northeast by Bond and Sendak (1970), nearly 50 percent of 

the firms employed fewer than 10 persons and competed entirely in local markets. 

Factors Affecting the Supply and 

Demand of Pallets 

The major factors that affect pallet demand and 

supply-along with the variables that represent these 

factors, the influence of these factors on demand or 

supply, and the time it takes for a change in these 

factors to affect the pallet market-are listed in Tables 

1 and 2, respectively. 

Because pallets are low-value products with relatively high transportation costs, it is assumed that 

regional pallet demand equals regional pallet supply. 

This assumption implies a separate set of demand and 

supply equations for each region. Therefore, quarterly 

equations were estimated for each of eight census 

regions of the United States. These regions as defined 

by the U.S. Department of Commerce are: 

Region 

New England 

Middle Atlantic 

East North-Central 

West North-Central 

South Atlantic 

East South-Central 

West South-Central 

Pacific 

State 

ME, NH, VT, MA, RI, CT 

NJ, NY, PA 

OH, IL, IN, MI, WI 

MN, IA, MO, ND, SD, NB, 

K,S 

DE, MD, VA, WV, NC, SC, 

GA, FL 

AL, KY, TN, MS 

AR, LA, OK, TX 

CA, OR, WA 

'U.S. Department of Labor, Bureau of Labor Statistics. 

ES-202 program, employment and wages, SIC 2448, quarterly 

data for period 1975 through 1983. Unpublished report. Wash-. 

ington, DC: U.S. Department of Labor, Bureau of Labor Statistics; 1984. 58 p. 

The factors affecting the demand and supply of 

pallets are derived from economic theory and observation of the pallet market. Using economic theory, we 

ascertain that pallet demand is positively affected by 

the price pallet users receive for their product (output 

price) and negatively affected by the price of pallets 

and the price of labor. The ratio of wage rates to capital 

is included in the demand equation to account for the 

trade-off between a labor-intense system employing 

manpower and a capital-intense system employing 

pallets. 

Economic theory also indicates that the supply of 

pallets is positively affected by the price of pallets and 

negatively affected by the price pallet producers pay 

for labor and lumber. Pallet supply is also affected by 

changes in production processes leading to greater 

labor productivity. To account for this change, a labor 

productivity index has been included in the supply 

equations. 

A mathematical representation of the demand and 

supply equations, along with a full description of the 

variables in these equations, is presented in Appendix 

A. The weight scheme used to develop the regional 

output price and demanders' wage rates is in Appendix 

B. The species used to calculate regional lumber price 

are in Appendix C. 

The impact time periods associated with the different variables in the demand and supply equations represent the time it takes pallet users or producers to 

react to changes in the variables listed in Tables 1 and 

2. The choice of the length of the impact times was 

based on observation of the pallet production and 

purchasing decisions and empirical evidence gained 

through statistical estimation of the demand and supply equations. These impact times may or may not be 

representative of the behavior of any particular pallet 

producer or user, but are representative of the aggregate or total demand and supply forces at work in the 

pallet market. 

The impact period of 4 to 6 quarters associated 

with pallet price in the demand equation (Table 1) indicates that after a change in pallet price, it takes pallet 

users about a year to start to react and another 4 quarters to fully react to this change. The length of time it 

takes pallet users to react to changes in pallet prices is 

affected by the way in which pallets are purchased. 

Because pallets are a minor input in the manufacturing 

and distribution costs for pallet-using industries, the 

decision to purchase pallets is made on an annual or 

semi-annual basis and is, therefore, probably based on 

expected future pallet price. The expected price is, in 

turn, probably based on past pallet prices. The reaction 

time between changes in pallet price and pallet 

demand is further retarded by the 1- to &month time 

period between the decision to purchase pallets and 

the actual ordering of pallets. 
Table 1.-Major factors affecting pallet demand, the impact of these 

factors on pallet demand and the length of time it takes 

these factors to impact demand. The names of variables 

used to represent the factors are in parentheses 

Factor Impact of Impact 

factor time 

Regional price index of products Positive Immediate 

produced by industries that use 

pallets (output price) 

Price of pallets (pallet price) Negative 4 to 6 quarters 

Regional wage rates in industries Negative Immediate 

that use pallets (demanders' wage 

rate) 

Ratio of wage rates to interest rates Positive 9 to 12 quarters 

(wage interest ratio) 

Table 2.-Major factors affecting pallet supply, the impact of these 

factors on pallet supply, and the length of time it takes 

these factors to impact supply. The names of variables 

used to represent the factors are in parentheses 

Factor Impact of Impact 

factor time 

Price of pallets (pallet price) Positive Immediate 

Regional price of low-grade lumber Negative 3 to 6 quarters 

(lumber price) 

Wage rates in the pallet industry Negative 3 to 6 quarters 

(suppliers' wage rates) 

Index of labor productivity in the Positive 3 to 6 quarters 

pallet industry (index of productivity) 
The impact time associated with a change in wage 

rates relative to interest rates (the wage ratelinterest 

rate ratio) is lengthy because of the time it takes to 

recognize the potential of palletizing, develop a palletized handling system, and implement such a system. 

We assume that it takes potential pallet users 1 year to 

recognize the need for a pallet system, another year to 

plan for a materials handling system that uses pallets, 

and a third year to implement the system. 

The impact time period associated with lumber 

price, wage rates, and labor productivity variables in 

the supply equation is 3 to 6 quarters. Work by Schuler 

and Wallin (1983) and Luppold (1984) has indicated that 

past input prices affect current pallet production. The 

length of time it takes pallet producers to react to 

changes in prices results from a number of factors, 

including the tendency of pallet firms to stockpile 

materials and price inventories on a first-inlfirst-out 

basis. Because many pallet producers tend to inventory 

lumber, past lumber price affects current pallet supply. 

Another factor that causes delayed responses in pallet 

production after a change in,production costs is the 

lack of precise day-to-day data on the cost of production and net revenue. 

Statistical Results 

The statistically estimated regional demand and 

supply equations are shown in Tables 3 and 4, respectively. All dependent and independent variables were 

transformed by taking the natural logarithm, resulting 

in equations of multiplicative form. 

The estimated demand equation fitted the data 

well; the multiple correlation coefficients (R2's) ranged 

between 0.79 and 0.94. The signs of all coefficients in 

all regional equations were as expected-coefficients 

associated with output price and the laborlcapital ratio 

were positive and the coefficients associated with 

pallet price and wage rates were negative. The coefficients associated with pallet price, output price, wage 

rates, and the ratio of wage rates to interest rates were 

significant across all regions at the 0.05 alpha level or 

higher. 

The estimated supply equation also fitted the data 

well; the R2 ranged between 0.86 and 0.97. Again, the 

signs of all supply equation coefficients were as 

expected-the coefficients associated with pallet price 

and the labor productivity index were positive and the 

coefficients associated with lumber price and wage 

rates were negative. The coefficients associated with 

all variables in the eight supply equations were significant at the 0.05 alpha level or higher, except for the 

coefficient associated with lumber price in the Pacific 

Region. The insignificant coefficient associated with 

lumber price in the Pacific Region probably resulted 

from the fact that no satisfactory lumber price series 

could be found to reflect the type of lumber used by 

western pallet manufacturers. 

The Durbin Watson (DW) statistics indicate some 

degree of first-order autocorrelation in the South Atlantic supply regions. All other DW statistics fell within 

the indeterminate area of the DW table. Because 

autocorrelation is an efficiency problem and the individual coefficients of the South Atlantic supply equation 

are statistically significant, no adjustment for 

autocorrelation was completed. 

Analysis of Results 

The coefficients in Tables 3 and 4 were estimated 

to allow direct interpretation. The technical name for 

these coefficients is elasticities. An elasticity represents the percentage impact on a dependent variable 

(in this instance, pallet usage or production) caused by 

a 1-percent change in an independent variable (the 

variables outlined in Tables 1 and 2). Elasticities are 

useful because they provide information on the relative 

importance of a particular factor on demand or supply. 

For example, if the price of pallets were increased by 1 

percent, the demand for pallets in the New England 

Region would decrease by 1.23 percent. Likewise, if the 

price of output increased by 1 percent in the New 

England Region, pallet demand would increase by 5.26 

percent. 

In Table 3, the size of the output price elasticity 

compared to the other price elasticities indicates that 

output price tends to heavily influence pallet demand. 

A strong gain in pallet demand tends to be linked to 

periods of high economic activity, while slumps in the 

pallet market correspond to low economic activity. 

The second most influential variable affecting 

pallet demand, as indicated by the coefficients in Table 

3, is wage rates in the industries demanding pallets. 

The wage-rate elasticity of demand is higher than the 

pallet-price elasticity of demand in every region where 

the coefficient associated with wage rates is statistically significant (valid). 

The coefficient associated with the ratio of wage 

rates to interest rates is difficult to interpret. However, 

this variable indicates that capital is substituted for 

labor as the relative cost of capital decreases in relation to the relative cost of labor. The rather small coefficient and length of the. reaction time associated with 

this variable indicate that this substitution occurs 

slowly. 
Table 3.-Results of the demand equation estimation, by region 

Price Pallet Wage Wagelinterest 

Reaion out~ut rice rates ratio R2 DW w 

New 5.26 -1.23 -3.90 0.50 0.82 1.56 

England (3.85) (-4.86) (-3.50) (9.93) 

Mid-Atlantic 

East 

North-Central 

West 

North-Cent ral 

South 

Atlantic 

East 

South-Central 

West 

South-Central 

Pacific 

(3.32) (-3.64) (-2.96) (9.49) 

t values are in parentheses. 

t = 2.479 at 0.01 level of significance. 

t = 1.706 at 0.05 level of significance. 

Table 4.-Results of the supply equation estimation, by region 

Pallet Lumber Wage Productivity 

Region price price rates index R2 DW 

New England 1.98 -0.80 -0.85 1.62 0.89 1.19 

(1 2.0) (-4.46) (-2.91) (4.36) 

Mid-Atlantic 

East 

Nort h-Central 

West 

North-Central 

South Atlantic 

East 

South-Central 

West 

South-Cent'ral 

Pacific 

(4.96) (0.005) (-3.1 1) (4.08) 

t values are in parentheses. 

t = 2.462 at the 0.01 level of significance. 

t = 1.699 at the 0.05 level of significance. 
Summary and Conclusions 

Pallet price elasticity of demand is near or below 1 

in every region, indicating that the demand for pallets 

is relatively insensitive to changes in pallet price. The 

fact that the demand elasticities of factors that are 

determined outside of the pallet market-output price 

and wage rates-are larger than pallet price elasticity 

indicates that general economic forces influence pallet 

demand more so than forces within the pallet market. 

The information in Table 4 indicates that pallet 

price is the single most influential factor affecting 

pallet supply. The relative value of pallet-price elasticity 

to lumber-price elasticity and wage-rate elasticity indicates that, unlike pallet demand, pallet supply is very 

much affected by forces within the pallet market. In 

fact, in all but the East South-Central Region, the 

pallet-price elasticity of supply exceeded the sum of 

the lumber-price and wage-rate elasticities of supply. 

Wage-rate elasticity of supply and lumber-price 

elasticity of supply are very similar for half of the 

regional supply equations. There seems to be a marked 

difference between the central regions and eastern 

regions. The one exception to this rule is the West 

South-Central Region, which is primarily the state of 

Texas. Since the central regions are associated with 

heavy industry and a large degree of unionization, it is 

expected that the larger wage-rate elasticity of supply 

is a result of the degree of unionization in the central 

regions. 

The index representing changes in labor productivity on the supply of pallets indicates that a great deal 

of labor-saving capital investments occurred in the 

pallet industry during the last 10 years. This degree of 

labor productivity is indicated by the fact that employmeilt in the pallet industry increased by 42 percent 

between 1975 and 1983, while pallet production has 

increased by 62 percent. 

Regional differences were observed in the magnitude of some of the estimated elasticities. For example, pallet users in the industrialized regions of the 

North (New England, Mid-Atlantic, and West NorthCentral) were more sensitive to changes in output price 

than pallet users in other regions. In the industrial 

North, the pallet-using industries are concentrated in 

the primary and fabricated metal manufacturing and 

machinery manufacturing areas. These industries may 

be sensitive to the general economic climate and 

adjust their pallet purchases with each change in the 

economy. 

Price elasticity of supply for pallets is relatively 

large in all regions. Pallet producers are expected to 

adjust levels of production rather quickly in response 

to changes in the market price of pallets. To be competitive, some pallet producers must adjust their levels 

of production by entering or leaving the market. 

Eight regional demand and supply equations were 

developed in this study. In these equations, pallet 

demand is developed as a function of the prices of the 

demander's inputs used with pallets and the price of 

the pallet demander's output, and pallet supply was 

developed as a function of the prices of inputs used in 

the pallet production process and the price of pallets. 

The results of these equations indicate that significant variation exists in pallet demand and supply in the 

eight different regions. Regional equations can be 

considered as opposed to a national equation that 

would ignore regional variation. The estimated demand 

and supply equations fitted the data well-the R2 

ranged from 0.76 to 0.97. Estimates of output-price 

elasticity, wage-rate elasticity of demand, and palletprice elasticity of supply indicate that these are major 

factors influencing the quantities of pallets in each of 

the regional markets. 

In the demand equations, output-price elasticity is 

always larger than either of the input elasticities, that 

is, the wage-rate or pallet-price elasticities. In six of the 

eight regions, output-price elasticity is also larger than 

the sum of these two input-price elasticities. Additionally, the wage-rate elasticity of demand is generally 

higher than pallet-price elasticity. As noted before, 

output price and pallet demanders' wage rates are 

determined outside the pallet market. Thus, general 

economic forces that determine the level of these variables have a greater effectd on the pallet demand than 

the effect of forces within the pallet market. 

In the.supply equations, the relative magnitude of 

the pallet-price elasticity in comparison to input-price 

elasticities for lumber price and wage rates indicates 

that, unlike pallet demand, pallet supply is very much 

affected by forces within the pallet market. As noted 

earlier, in all but one region, pallet price elasticity is 

larger than the sum of lumber-price and wage-rate 

elasticities. Thus, pallet price exerts a greater influence 

on the quantity of pallets supplied than the other 

forces within the pallet market. 

The analysis shows that differences exist among 

regions with respect to pallet demand and supply. 

Factors that influence these differences include pallet 

price, price of outputs, and wage rates of pallet 

demanders. This analysis should provide a sound basis 

for future assessments of regional pallet demand, supply, and price. 
Literature Cited 

Bond, R. S.; Sendak, P. E. The structure of the wood. 

platform industry of the Northeast. Bull. No. 586. 

Amherst, MA: University of Massachusetts, College 

of Agriculture; 1970. 70 p. 

Lemsky, Abe, ed. Hardwood market report. Memphis, 

TN: Abe Lemsky; 1972-84. 

Luppold, William G. An econometric study of the U. S. 

hardwood lumber market. Forest Science 

30(4): 1027-1038; 1984. 

Schuler, A. T.; Wallin; W. B. A revised econometric 

model of the domestic pallet market. Res. Pap. 

NE-522. Broomall, PA: U.S. Department of Agriculture, Forest Service, Northeastern Forest Experiment 

Station; 1983. 5 p. 

Appendix A 

Demand and Supply Equations 

Demand Qd = f(P0, PPID3, ED3, EID4) 

Supply Qs = g(PP1, PLUD2, PLSD2, ILPRD2) 

where: 

Qd = 

Qs = 

PO = 

PPID3 = 

ED3 = 

EID4 = 

PPI = 

PLUD2 = 

PLSD2 = 

ILPRD2 = 

Regional quantity of pallets 

demanded in quarter t. 

Regional quantity of pallets supplied in quarter t. 

Weighted regional producer price 

indexes for industries that use 

pallets. Source of price 

indexes: Bureau of Labor Statistics. Weights used to calculate 

regional indexes are in Appendix B. 

Pallet price index specified as a 

polynomial distributed lag t-4 to 

t-7. Source of price index: Bureau 

of Labor Statistics. 

Weighted regional wage rates for 

industries that use pallets, specified as a polynomial distributed lag 

t-4 to t-7. Source of wage 

rates: Bureau of Labor Statistics. 

Weights used to calculate regional 

wage rates are in Appendix B. 

Ratio of regional wage rates in 

industries that use pallets to the 

interest rate on 90-day commercial 

paper, specified as a polynomial 

distributed lag t-9 to t-12. Source 

of interest rates: Survey of Current 

Business. 

Price index of pallets. 

Source: Bureau of Labor Statistics. 

Regional price of lumber specified 

as a polynomial distributed lag t-3 

to t-6. Source of lumber 

prices: Hardwood Market Report. 

Specific species used in calcutating regional lumber prices are in 

Appendix C. 

Wage rates in the pallet and wood 

container industry, specified as a 

polynomial distributed lag t-3 to 

t-6. 

Index of labor productivity in the 

pallet industry measured as the 

value of shipments per man-hour, 

specified as a polynomial distributed lag t-3 to t-6. 
Appendix B 

Weights Used to Calculate Regional Indexes for Pallet-Using Industries 

Region 

East West East West 

Industry New Mid- North- North- South South- South- Pacific 

England Atlantic Central Central Atlantic Central Central 

Food 0.07 0.1 2 0.09 0.21 0.1 3 0.14 0.17 0.17 

Textiles 0.09 0.06 0.00 0.01 0.31 0.11 0.01 0.01 

Paper 0.09 0.06 0.04 0.05 0.06 0.06 0.05 0.05 

Chemicals 0.04 0.10 0.05 0.04 0.09 0.12 0.12 0.05 

Rubber, plastics 0.08 0.06 0.07 0.06 0.03 0.06 0.06 0.06 

Stone, clay, glass 0.02 0.05 0.03 0.06 0.06 0.05 0.06 0.05 

Primary metal 0.06 0.14 0.13 0.04 0.06 0.10 0.07 0.06 

Fabricated metal 0.16 0.13 0.17 0.12 0.07 0.12 0.15 0.13 

Machinery 0.24 0.19 0.22 0.27 0.09 0.12 0.19 0.16 

Transportat ion 

equipment 0.15 0.09 0.20 0.14 0.10 0.12 0.12 0.26 

Appendix C 

Specific Species Used in Calculating Regional Lumber Prices 

Region Speciesa 

New England 

Mid-Atlantic 

East 

North-Central 

West NorthCentral 

South Atlantic 

East SouthCentral 

West SouthCentral 

Pacific 

Northern red oak (Grades 2C and 3A) and Northern hard 

maple (Grade 2C) 

Northern red oak (Grades 2C and 3A) 

Northern red oak (Grades 2C and 3A) 

Northern red oak (Grades 2C and 3A) 

Southern red oak (Grades 2C and 3A) 

Southern red oak (Grades 2C and 3A) 

Southern red oak (Grades 2C and 3A) 

Softwood lumber price index, from Fingertip Facts and 

Figures, published by NFPA, Washington, D.C. 

aPrices for individual species taken from Hardwood Market Report (Lemsky 

1972-84), first week in each quarter. 
Luppold, William G.; Anderson, R. Bruce. A regional analysis 

of pallet supply and demand. Res. Pap. NE-580. Broomall, 

PA: US. Department of Agriculture, Forest Service, Northeastern Forest Experiment Station; 1986. 8 p. 

This paper examines the factors that affect regional pallet 

supply and demand by developing, estimating, and interpreting models for the eight major census regions with viable 

pallet markets. 

ODC 721 

Keywords: Econometric; production; usage 
Headquarters of the Northeastern Forest Exgeriment Station are in 

Broomall, Pa. Field laboratories are maintained at: 

Amherst, Massachusetts, in cooperation with the University of 

Massachusetts. 

Berea, Kentucky, in cooperation with Berea College. 

Burlington, Vermont, in cooperation with the University of 

Vermont. 

Delaware, Ohio. 

Durham, New Hampshire, in cooperation with the University of 

New Hamphire. 

Hamden, Connecticut, in cooperation with Yale University. 

Morgantown, West Virginia, in cooperation with West Virginia 

University, Morgantown. 

Orono, Maine, in cooperation with the University of Maine, 

Orono. 

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, Syracuse. 

University Park, Pennsylvania, in cooperation with the 

Pennsylvania State University. 

Warren, Pennsylvania. 

I *U.S. GOVERNMENT PRINTING OFFICE: 1986-605-026:20047