An Analysis of the Japanese Demand For Wood Productsby

Type, Species and Source

Working Paper 97.02

By

Christopher W. Gaston

Project Director

Bill WilsonCanadian Forest ServicePacific Forestry Centre

Victoria, BC

April 1997

Funding Support

Completion of this report was supported by the Canadian Forest Service, the OpportunityIdentification Program (Program 5) of the Canada-British Columbia Partnership Agreement onForest Resource Development: FRDA II, and the Forest Economics and Policy AnalysisResearch Unit (FEPA) at UBC.

Acknowledgments

The author wishes to thank Bill Wilson and Gregg Delcourt for their suggestions and reviewcomments in the design and completion of this report.

Author

Gaston was a Ph.D. student at the University of British Columbia during the completion of thisproject. He is currently working at FORINTEK in Vancouver.

Disclaimer

The views expressed in this report do not necessarily represent those of the Canadian ForestService or the BC Forest Service.

This report is available from:PublicationsPacific Forestry CentreCanadian Forest Service506 West Burnside RoadVictoria, BC V8Z 1M5

fax: 250 363 0797

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EXECUTIVE SUMMARY

There has been a surprisingly small amount of research done on the investigation of wood

product demand beyond very broad classifications, such as “softwood lumber” or “softwood logs”.It is hypothesised that hiding wood characteristics through such data aggregation risks obscuring

important dimensions of both forest product trade and forest policy.

This study was motivated by the recognition that the willingness-to-pay for softwood lumber,for example, varies considerably by grade category, both in relative prices and in their individual

price trends. Figure 1.2 illustrates, showing the real (inflation adjusted) prices of three gradecategories of Douglas fir lumber from the Pacific Northwest from 1972 to 1993. While the structural

and merchantable grades showed zero to moderate price growth, respectively, the clear gradeshowed an average real price growth of 3.5% per year.

When one considers the changing resource base in British Columbia (BC), and the

corresponding increase in the forest industry’s cost structure, the changing patterns of global woodsupply toward fast-growing plantations, increased emphasis on engineered products, and the

globalization of trade, the importance of delineating unique wood product demands increases. Forexample, where have BC’s competitive advantages lain in the past, and where are they likely to lie

in the future? What will be the economic consequence of BC’s transition to a second growthresource? Who (source) and what (type of wood and non-wood building materials) represents

existing competition for BC wood products in end-use, and how is this likely to change?

To address such questions, this study has focussed on quantifying the degree of woodproduct substitution in a single market, being Japan. This market was chosen because: 1) it

represents the largest importer of forest products today (Sedjo, 1994); 2) it is the second mostimportant market for BC (after the US); 3) it has an interesting history of evolving from a reliance

on domestic production, then importation of whole logs, then importation of lumber and otherfurther processed products (creating a good case study for quantifying the substitution between

these and alternative inputs); and 4) it has been a significant buyer of both construction grade andappearance grade wood products. While existing data sources did not allow for an investigation

by grades, this study disaggregated Japanese wood product imports by product type, species andcountry of origin, over the period of 1965 to 1993.

This paper is presented in four sections, including the background and scope of the study

(Section 1), the description of the Japanese wood products market (Section 2), the results of thequantitative analysis on wood product substitution in Japan (Section 3), and a discussion of the

0

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1972 1976 1980 1984 1988 1992

Clear Merchantable Structural

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Figure 1.2 PNW Douglas Fir Lumber Prices ($US per thousand board-feet, real ,PPI adjusted, 1992 = 100)

Source: Complied from Random Lengths, Various Yearbooks.

Grade Definitions:

� Clear Douglas-Fir, green, #2 Clear, 15% #3; 2½ X 6 and wider; export price,f.o.b. dock, Or. and Wash. (prior to 1985 prices f.a.s.).

� Merch. Douglas-Fir, Merchantable, #1, 15% #2; 6 X 12 and wider; export price, asabove (prior to 1985 prices f.a.s., based on #1, 25% #2).

� Struct. Douglas-Fir, green, #1 and better, random 10/20; 2 X 4; domestic price,f.o.b. mill.

marketing and policy implications, as well as recommendations for further research (Section 4). Sections 2 through 4 are summarized below.

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Figure 2.7 Japanese Industrial Wood Supply(Japan Forestry Agency Data, Provided by Dr. Y. Mori,Kyoto University, Japan)

The Market for Wood Products in Japan

@ Japan has a significant domestic forest resource (37 million hectares), with forested landas a percentage of the total land base being very similar to that of BC, and growingconditions which allow for significantly greater annual increments in their volume of timber.The mean annual increment on Japanese plantations averages 7.5 cubic metres perhectare.

@ In spite of this large resource base, the population is large and the per capita resource basesmall. Over time, Japan has moved from almost total self-sufficiency in log inputs to aheavy reliance on log imports. Although Japan has undertaken considerable reforestation,this was mostly done after the war. Given Japan’s forest rotations of roughly 30 years,these plantings are now nearing harvest age.

@ At present, roughly 60% of Japan’s domestic log production is harvested from man-madeforests. Given the lower quality and higher cost of this source, compared to domestic oldgrowth, this again encourages log imports.

@ Although the harvest from Forest Agency land has remained rather constant over thisperiod, it has shown a gradual decline as a percent of total harvests; the significance of thislies in the fact that it is these lands that contain the largest percentages of old growth, albeiton less accessible lands than the private forests.

1-15 Yrs 16-30 Yrs 31-45 Yrs 46-60 Yrs 60 + Yrs0

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Figure 2.1 Distribution of Man-made Forest by Age Class, 1986(Japan Forestry Agency, 1991)

@ Domestic softwood log production dropped roughly 40% over the past three decades whiledomestic hardwood log production dropped more than 65%. Softwood log importsincreased 400% while hardwood log imports stayed relatively constant.

@ While log imports have shown the noted overall increase over this period, imports actuallypeaked in 1973 and have been dropping ever since. Against this trend, lumber importshave been increasing throughout. As was the case with logs, Japan has shifted its lumberimports away from hardwoods in favour of softwoods.

@ Over time, Japan substitutes the import of logs with the import of lumber and furtherprocessed products. The primary reason for the drop in log imports seems to be less afunction of Japanese demand and more a function of the declining availability of logs on theworld market (due to growing export restrictions and declining old growth supplies world-wide). The former Soviet Union may offer major potential for added future supply.

@ While the sources of softwood log and lumber imports have not changed significantly overthis time period, total log and lumber market shares held bu suppliers have.

@ North America and the former Soviet Union are the only significant suppliers of importedlogs for housing in Japan. Logs from these two countries are used almost exclusively forlumber production. Only 20% of South Sea logs are used for lumber production, and NewZealand logs have been used almost exclusively for packaging material.

@ Japan has not shown a great acceptance of either softwood plywood or other panelproducts as substitutes for its traditional hardwood plywood (of which Japan is a significantproducer). Instead, Japan initially shifted to using domestic hardwood logs and later shiftedto imported hardwood logs and veneer.

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Figure 2.5 Japanese Housing Starts by Number(Japanese Ministry of Construction Data, Provided by Y. Mori,Kyoto University, Japan; 2x4 Data from INTEREX)

@ Annual housing starts in Japan have exceeded 1.5 million many years over the past twodecades. Given that this is comparable to that of the US, and less than half the population,this illustrates a pent up demand for replacements of low quality housing built since theSecond World War. Of total starts, wooden houses represent roughly 50% today, ascompared to roughly 80% in 1965.

Analysis of the Japanese Demand for Wood Products

The objective of the analysis was to quantify the nature of wood product demand with asmuch attention to product detail as possible. More specifically, estimates of “own-price” and “cross-price elasticities of demand” were desired, telling us the anticipated reaction in Japan to a changein the price of a specific product, and a change in the price of a substitute product, respectively.For example, if the price of SPF lumber from Canada increases by 10%, what is the likely percentdecrease in the quantity demand for this product (own-price)? Further, if the price of US dimensionlumber of a particular species increases by 10%, what is the likely percent increase in the demandfor Canadian SPF (cross-price)?.

The data used to address these questions was the Japan Tariff Association’s Import ofCommodity by Country, annual values from 1965 to 1993. These data report the Japanese importsof all wood products, broken down by type (soft and hardwood logs, soft and hardwood lumber,particle board, fibreboard, plywood, veneer sheets, and other further processed items), by country

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of origin (which, for the purpose of this study, was aggregated into Canada, the US, Chile/NewZealand, the former Soviet Union, the South Seas, and “rest of world”), and, for logs and lumber,by species. An extensive search of published data sources revealed that breaking these data intofurther detail, such as grades or categories of grades, was not possible. However, this could beinferred to some degree by the species (for example, knowing that SPF is primarily used asconstruction grade dimension lumber) and by source (for example, knowing that New ZealandRadiata pine has historically been used in low grade applications).

Given the noted lack of trade research reported in the literature that disaggregates woodproducts beyond very broad categories such as “softwood lumber”, the analysis reported in thispaper was necessarily prefaced by a literature review on appropriate methodologies. Estimationof elasticities of demand when a large number of potentially unique, yet related, products is notwithout its problems, partially explaining the tendency for researchers to utilize aggregations tobegin with. Two methodologies were discovered, both being applications of a paper published byArmington in the 1960's. The first was reported in a paper by Chou and Buongiorno (1983).Unfortunately, the direct application of Armington’s theory, while theoretically sound, suffers fromoverly restrictive assumptions, yielding questionable results. In a second paper, Hseu andBuongirno (1992) attempt to relax these restrictive assumptions. While their model is more robust,closer investigation reveals theoretical inconsistencies with Armington’s original work. (Refer toAppendix “A” for detail.)

This study employs direct estimates of own-price elasticities on individual wood productsin addition to the Armington-type models. While this does not allow for the estimation of cross-price effects, it does serve to illustrate the strengths and weaknesses of Armington’s followers.

The main conclusions which come out of this analysis are:

@ Individual wood products, whether aggregated by product type, origin, or species, behaveas distinct economic units. This was quantitatively extended to include quality insofar astrade detail was available for planed versus non-planed lumber (What the Japan TariffAssociation refers to as “planed lumber” is construction grade dimension lumber, includingCanadian SPF). This was qualitatively extended to quality through the knowledge andinformal judgements about the nature of wood products typical of individual sources.Interestingly, almost without exception, wood imports had lower real Yen prices in 1993than in 1965. Appendix “B” contains graphical representations of import volumes and realprice over the 1965-1993 study period; this is presented for the main product aggregateson the following page.

@ In terms of product type, the own-price elasticity of demand was found to be the smallestfor softwood logs, largest for panel products, with lumber’s elasticity lying somewhere inbetween. Said another way, softwood logs displayed the fewest number of substitutes, andpanel products displayed the greatest number of substitutes.

@ In terms of the origin for softwood lumber, the own-price elasticity of demand was found tobe the smallest for Canada (not including the former Soviet Union, which represented asmall proportion of softwood lumber imports), largest for NZ/Chile, with softwood lumberfrom other sources lying somewhere in between.

@ In terms of the species of softwood lumber, S-P-F (and other “planed lumber”) was shownto have by far the highest own-price elasticity, while red cedar from the US and yellow

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cedar from Canada showed the smallest own-price elasticities.

@ In the case of softwood logs, the lowest own-price elasticity was for US logs, and thehighest was for NZ/Chile logs. The own-price elasticity for the former Soviet Union has apositive sign, a non-intuitive result which may be explained by the presence of long-termcontracts. Compared to lumber, there was little difference by species shown for the own-price elasticities for US logs.

@ The cross-price elasticities, while generally found to be quite inelastic, mostly demonstratea willingness to substitute one wood product for another to some degree (imperfectsubstitutes). This includes substituting one product type for another, such as softwoodlumber for softwood logs, logs from one location for logs from another, or one species oflogs for another. With many individual products comparisons, however, there are cross-price elasticities which are not significantly different from zero. This reflects a smallelasticity of substitution, with the two products acting as complements rather thansubstitutes. Finally, Japanese buyers appear to be more willing to substitute moreprocessed products in response to price increases for less processed products than theother way around. This may reflect changes in the product mix of domestically processedlogs.

@ Increases in the price of Japan’s domestic logs cause the Japanese to substitute importedwood products, with a near unit cross-price elasticity. Given the significance of theJapanese domestic log supply over the course of the study period, symmetry would suggestthat increases in the prices of imported wood products lead to significant substitution withdomestic logs.

@ In spite of the increasing purchasing power of the Yen over the period covered by thisstudy, it was determined that Japanese buyers have remained price sensitive, yet havebeen willing to pay considerable price premiums for certain products.

@ There was no evidence of structural change in the Japanese market for aggregated woodimports. This shows that the substitution of one product for another (such as lumber forlogs) has been gradual over the 1965 to 1993 study period.

@ In Japanese markets, iron/steel and wood inputs appear to be complimentary, likely dueto the importance of both non-wood housing starts and non-residential construction.

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Implications of the Results

@ The conclusions offered above indicate that the Japanese buyer views different wood

products, down to the level of species of lumber and logs, as having different levels ofsubstitutability. In spite of the noted wealth due to the strength of the yen over the past

three decades, the Japanese buyer has exhibited a strong sensitivity to price. This begsthe question of how Japan’s purchase patterns and export prices enjoyed here at home

might change if the Yen were to decline relative to the Canadian dollar. Is the incidenceof low price elasticities (a less than 10% drop in quantity demanded against a 10% increase

in price) for selected wood products likely to hold given a trend of higher real prices inJapan?

@ Japan has a significant forest resource which must not be overlooked in the future,

especially in the advent of higher real imported wood prices.

@ Canadian shipments to Japan are at average unit prices which are considerably higher thanshipments to the US. While this is due in part to the mix of product being sold and in part

to an “export premium” (for example, the Japanese valuing certain attributes that the USmarket does not), the point is that this market has allowed the Canadian producer to

differentiate its products. Given the growing importance of such differentiation to thecontinued profitability, increased knowledge of Japan’s buying habits is critical, leading to

the identification of areas of competitive advantage. (See implications for further researchbelow.)

@ From a forest policy perspective, it must be recognized that some of the unique demands

for wood product imports in Japan are likely linked to the attributes of “old growth” timber.The diversity of products, complementing the diversity of markets, has been a strong area

of competitive advantage in Canada. At the same time, the incentive to maintain thisproduct diversity, be it through intensive silviculture and/or longer forest rotations, does not

presently exist.

Implications for further research:

@ Given that the literature search on methodologies to estimate substitution effects on a large

number of related products proved inadequate, further methodological research is clearlyneeded. It may be concluded that a “parametric” approach such as that reported here is

not practical, in which case a “hedonic” approach may be more appropriate. A hedonicapproach focuses on the demand for the attributes of a product, rather than on the product

itself.

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@ This study has focussed on demand descriptors in the interest of maintaining a reasonablescope. However, it will be equally important to investigate supply responses to price with

a similar level of wood product detail. Only then will it be possible to utilize more powerfultools for trade flow analysis and price forecasting beyond broad product aggregates.

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TABLE OF CONTENTS

ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i

TABLE OF CONTENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x

LIST OF FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi

LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xii

1.0 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 Scope of the Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

The Research Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6Organization of the Paper . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2.0 THE MARKET FOR WOOD PRODUCTS IN JAPAN . . . . . . . . . . . . . . . . . . . . . . . . . . 7

2.1 The Japanese Domestic Timber Resource . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72.2 The Use of Japanese Domestic Timber Production . . . . . . . . . . . . . . . . . . . . . . . . 92.3 Imports of Wood Products into Japan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132.4 Japanese Processing of Domestic and Imported Logs . . . . . . . . . . . . . . . . . . . . . 172.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

3.0 THE ANALYSIS OF THE JAPANESE DEMAND FOR WOOD PRODUCTS . . . . . . . . 24

3.1 The Japanese Wood Product Import Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243.2 Individual Estimates of Own-Price Elasticities of Demand . . . . . . . . . . . . . . . . . . 333.3 Armington Two-Stage Estimates of Own- and

Cross-Price Elasticities of Demand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 413.4 Summary of Research Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

4.0 CONTRIBUTIONS, LIMITATIONS, AND IMPLICATIONS FOR FURTHER RESEARCH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

4.1 Implications of the Research for BC Wood Product Marketing . . . . . . . . . . . . . . 494.2 Implications of the Research for BC Forest Policy . . . . . . . . . . . . . . . . . . . . . . . . 524.3 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 534.4 Implications for Further Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

BIBLIOGRAPHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

APPENDIX A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

APPENDIX B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

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LIST OF FIGURES

Figure 1.1 Random Lengths S-P-F Lumber Futures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3Figure 1.2 PNW Douglas Fir Lumber Prices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5Figure 2.1 Distribution of Man-Made Forest by Age Class (Japan) . . . . . . . . . . . . . . . . . . . 8Figure 2.2 Japanese Domestic Log Production by Species . . . . . . . . . . . . . . . . . . . . . . . 9Figure 2.3 Japanese Domestic Log Production by Ownership . . . . . . . . . . . . . . . . . . . . . 10Figure 2.4 Japanese Domestic Log Supply by Utilization . . . . . . . . . . . . . . . . . . . . . . . . . 11Figure 2.5 Japanese Housing Starts by Number . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12Figure 2.6 Japanese Housing Starts by Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12Figure 2.7 Japanese Industrial Wood Supply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14Figure 2.8 Japanese Self-Sufficiency in Logs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14Figure 2.9 Japanese Self-Sufficiency in Lumber . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16Figure 2.10 Japanese Self-Sufficiency in Panel Products . . . . . . . . . . . . . . . . . . . . . . . . . . 16Figure 2.11 Japanese Imports of Softwood Lumber and Logs, 1993 . . . . . . . . . . . . . . . . . 18Figure 2.12 Japanese Imports of Softwood Lumber and Logs, 1965 . . . . . . . . . . . . . . . . . 18Figure 2.13 Japanese Imports of Hardwood Lumber and Logs, 1993 . . . . . . . . . . . . . . . . . 19Figure 2.14 Japanese Imports of Hardwood Lumber and Logs, 1965 . . . . . . . . . . . . . . . . . 19Figure 2.15 Japanese Lumber Shipments by Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20Figure 3.1 Nominal Price of Japanese Imports of Canadian Sitka Spruce

Lumber, By Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30Figure 3.2 Nominal Price of Japanese Imports of Canadian Yellow Cedar

Lumber, By Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30Figure 3.3 Observed Versus Predicted Values of the Quantity Demanded of

Aggregate Softwood Lumber Imports by Japan . . . . . . . . . . . . . . . . . . 36

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LIST OF TABLES

Table 3.1 Japan Tariff Association Data, Converted Codes . . . . . . . . . . . . . . . . . . . . . . . 25Table 3.2 B.C. Offshore Lumber Exports Relative to the Whole of Canada . . . . . . . . . . . 32Table 3.3 Estimates of the Japanese Demand for Aggregated Wood Imports . . . . . . . . . 35Table 3.4 Estimates of the Japanese Demand for Selected

Disaggregated Wood Products. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37Table 3.5 Cochrane-Orcutt Estimates of the Japanese Demand for Aggregated

Wood Imports, With the Inclusion of a Non-Wood Regressor. . . . . . . . 40Table 3.6 Calculated Own- and Cross-Price Elasticities of Demand for

Japanese Imports of all Wood Products by Type . . . . . . . . . . . . . . . . . 43Table 3.7 Calculated Own- and Cross-Price Elasticities of Demand for

Japanese Imports of Softwood Lumber by Country of Origin . . . . . . . . 44Table 3.8 Calculated Own- and Cross-Price Elasticities of Demand for

Japanese Imports of Canadian Softwood Lumber by Species . . . . . . . 44Table 3.9 Calculated Own- and Cross-Price Elasticities of Demand for

Japanese Imports of all Wood Products by Type, II . . . . . . . . . . . . . . 46Table 3.10 Calculated Own-Price Elasticities of Demand of Selected Wood

Product Imports by Japan not Shown in Table 3.9 . . . . . . . . . . . . . . . 46Table 4.1 Destination of Canadian Softwood Lumber and Log Exports, 1992 . . . . . . . . . 50

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1.0 INTRODUCTION

This paper reports an investigation of an aspect of Pacific Rim log and lumber trade which

has received surprisingly little attention to date: factor demand estimation with recognition thatwood inputs are imperfect substitutes in production. While there have been many studies which

have estimated demand parameters for wood inputs, virtually all of them have used highlyaggregated trade data (such as "softwood lumber"). By contrast, this study investigates demand

substitution by product, by region, and by species.

1.1 BackgroundHiding wood characteristics through data aggregation tends to obscure important

dimensions of both forest product trade and forest policy.

A good example of this problem is illustrated by US allegations that BC export restraints onsoftwood logs constitute a subsidy for BC sawmills. By aggregating all softwood logs, there is a

danger of obscuring the log export pattern which might exist in the absence of export restrictions.Kalt’s (1994) submission to the US Department of Commerce in the Canada/US softwood lumber

countervail case offers a good example of how to improve trade analysis with less aggregated data.He argues that British Columbia (BC) export restraints, which primarily affect coastal logs

containing a significant proportion of logs from which clear and merchantable grade lumber can beextracted, do not constitute a subsidy for interior sawmills producing mostly lower grade

construction lumber.

Another example is offered by the determination of allowable annual cuts within the contextof BC's sustained yield policy. Haley and Luckert (1994) and van Kooten (1993), for example,

argue that meeting the objectives of sustained yield does not simultaneously meet the objectivesof sustainable development. In short, choosing forest rotations and/or silvicultural regimes which

maximize volume, without any reference to value, does not necessarily promote a strong forest-based economy. If one adds goals to incorporate non-timber values in forest management, the

inherent problems in focusing on physical volume alone become further amplified.

There are a number of important questions which require an investigation of trade relatedto wood species and sources of origin. For example, will BC’s second growth Douglas-fir

(Pseudotsuga menziesii (Mirb.) Franco) be able to compete with New Zealand’s plantationproduced clear radiata pine (Pinus radiata D. Don)? More generally, where have BC's competitive

advantages lain in the past, and where are they likely to lie in the future? What will be theeconomic consequence of BC's transition to a second growth resource, particularly in light of

increased environmental pressures to reduce the forest land base? To what degree will non-woodmaterials substitute for existing forest products produced in BC, and what will be the economic and

environmental consequences of such substitutions? How does the emergence of engineeredwood products affect demand substitution for BC timber resources?

There is no standard definition of wood quality. For example, one definition of quality might be the1

presence of attributes in wood that are related to appearance. In the case of softwood lumber, this wouldinclude such characteristics as clear grain, large dimensions, and narrow ring width. Another definition ofquality might be structural strength. In other words, quality must be related to the intended purpose of thelumber. Constantino gets around defining quality in terms of specific wood characteristics by using a priceindex, where quality is related to the buyer’s aggregate willingness to pay.

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There are two potential occurrences which will have to be faced as BC makes the transition

toward a forest industry increasingly dependent on second-growth and subsequent forest crops:

1) according to the most recent BC Ministry of Forests timber supply reviews, BC isgoing to witness a significant reduction in the volume of available timber over thenext couple of decades;

2) according to Constantino (1986) and Constantino and Haley (1988), withoutappropriate changes in BC forest policy, the quality of timber is going to be1

significantly lower.

If the forest industry in BC is to minimize these potentially negative impacts on the provincial

economy, it will be necessary to examine marketing opportunities for the future, and translate theseinto appropriate land use plans, levels of silvicultural activities, and forest rotations. In other words,

it is time for forestry to make the transition from a production orientated to a market orientatedindustry. This can only be accomplished by a detailed analysis of which BC wood products have

historically contributed most to net revenues, and which are most likely to do so in the future. Thisneed will become increasingly important as old-growth timber becomes scarcer and price increases

lead to accelerated substitution.

As can be seen in Figure 1.1, cash prices for lumber more than doubled in the first coupleof months of 1993 (following decades of zero real price growth). Since then, prices have been

extremely volatile, making any forecast of future price trends difficult.

There is some debate as to the significance of this price spike. While some believe that thisoccurrence was not all that unusual (see Sohngen and Haynes, 1994), others suggest that the

market is displaying a structural change (see Sutton, 1994; Michaelis, 1994; and Mather, 1994).The latter opinion would suggest that prices will either stabilize at a new plateau at some point in

the future or even continue to demonstrate real price growth.

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1989 1990 1991 1992 1993 1994

When the percent change in the quantity of demand for a wood product is smaller than the percent2

change in its price, the demand for this product is termed inelastic. A review of the literature which reportshistorical lumber elasticities is offered in Appendix A.

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Figure 1.1 Random Lengths S-P-F Lumber Futures, Chicago Mercantile Exchange, Spot Contract*.Compiled from various issues of The Financial Post.

* As this chart always tracks the nearest delivery month, prices are analogous to the cash

market.

Historically, the demand for construction lumber has been price inelastic . This can be2

explained by one or more of the following: there have been few substitutes (this has not likely been

the case); price has not been an issue (e.g., lumber has represented a small portion of the cost ofa home); or, there have historically been no inexpensive available substitutes relative to the price

of lumber. However, demand for construction lumber may become price elastic (i.e. a structuralchange) if an increased price level leads to reduced wood consumption through the building of

smaller homes and/or lumber substitution. The economic implications of the potential for suchwood product substitutes translates into the central theme of this paper.

Substitutes for logs, lumber or further processed wood products can take many forms. The

most obvious is substitution with the same basic product, but from a different location. Analysishas shown that such cross-price elasticities of demand for lumber are significantly higher (even

elastic) as compared to the own-price elasticities (see Appendix A). In other words, while thequantity of local lumber demanded is not very price responsive (such as the demand for US

Midwest lumber given the price of Midwest lumber), the quantity demanded is responsive to theprice of similar wood from a different area, such as imports from Canada. For example, a 1%

decrease in the price of Canadian lumber may cause the quantity of US Midwest lumber demandedto decrease by more than 1%. Estimates suggest that cross-price elasticities may be high even

for dissimilar types of wood, such as imports of hardwood from Indonesia to replace USconsumption of local softwood. Some studies also show that non-wood materials may substitute

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for logs and lumber.

While the apparent willingness to substitute seems rather straight forward, it must be noted

that no mention has been made of the specific characteristics of “similar” products. Due to anapparent lack of trade data broken down by grade, little can be found in the literature to document

this potentially important aspect of substitution. Figure 1.2, showing the prices of three grades ofPNW Douglas-fir lumber over the past two decades, illustrates the danger of describing lumber (or

logs) as a single homogeneous commodity.

Note that the lumber prices in Figure 1.2 are in real terms, not nominal. Over the timeperiod indicated, clear grade Douglas-fir export prices rose roughly 3.5% per annum, the

merchantable grade price trend was virtually flat, and the structural grade had a negative pricegrowth. Given these distinct differences in price trends, it is obviously not rational to expect that

construction grade lumber, for example, can fully substitute for clear grades. Prices can also varytremendously within a grade. For example, prices for clear grade coastal BC lumber exports to

Japan from one firm in 1994 was reported to exceed $ 2,400 CDN per thousand board feet,averaged over all dimensions; the price for the largest dimensions would be considerably higher.

1.2 Scope of the StudyAnalysis of silvicultural regimes, forest practices, land-use and trade policies are all

negatively affected by the lack of information on wood product demand by some measure of

disaggregation. However, before research can be carried out which addresses the policy and traderamifications of using aggregated wood product data, significant background research is needed.

This must begin with a quantification of the uniqueness of individual product types (logs, lumberand further processed products), species and origin as distinct economic goods.

As the central theme of this study is to quantify the degree of substitution of wood products,

the sole focus will be on demand determinants. Further, to keep the analysis manageable, thestudy focuses on a single market—Japan. The Japanese market was chosen because: 1) it

represents the largest importer of forest products today (Sedjo, 1994); 2) it has an interestinghistory of evolving from reliance on domestic production, then importation of whole logs, and most

recently importation of lumber (which allows for quantification of the substitution between thesealternative inputs); and 3) it has been a significant buyer of both construction grade and

appearance grade wood products.

The Research ProblemFigure 1.2 helps put the research problem into perspective. By comparing the three grades

of Douglas-fir lumber over the past two decades, the growing market premium for the clear grade(and, to a lesser extent, the merchantable grade) is obvious. Although international trade data do

0

500

1000

1500

2000

2500

$US

per

MF

B

1972 1976 1980 1984 1988 1992

Clear Merchantable Structural

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Figure 1.2 PNW Douglas Fir Lumber Prices ($US per thousand board-feet, real ,PPI adjusted, 1992 = 100)

Source: Complied from Random Lengths, Various Yearbooks.

Grade Definitions:

� Clear Douglas-Fir, green, #2 Clear, 15% #3; 2½ X 6 and wider; export price,f.o.b. dock, Or. and Wash. (prior to 1985 prices f.a.s.).

� Merch. Douglas-Fir, Merchantable, #1, 15% #2; 6 X 12 and wider; export price, asabove (prior to 1985 prices f.a.s., based on #1, 25% #2).

� Struct. Douglas-Fir, green, #1 and better, random 10/20; 2 X 4; domestic price,f.o.b. mill.

not offer such grade detail, they do offer species detail, from which grade measures can often bededuced. For example, the species mix spruce-pine-fir (S-P-F) lumber, which is exported primarily

from North America, is known as a construction or structural grade commodity. North Americanlumber exports to Japan of such species as yellow cedar (Chamaecyparis nootkatensis (D. Don)

Spach) and Sitka spruce (Picea sitchensis (Bong.) Carr.), on the other hand, are primarily of clearand merchantable grades. Further, the origin also offers an association with grade. New Zealand

log and lumber exports, for example, have historically been known to provide sub-structural grades,which have been used in Japan primarily as packaging materials.

The research problem is best addressed through a number of questions. For instance, how

do the own-price elasticities of demand differ in Japan by product type, origin and by species? How

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do the cross-price elasticities for these wood products differ, both with other wood (type, species

and origin) and non-wood substitutes? Will scarcity in North American S-P-F lumber lead to realprice growth as evidenced in higher grade lumber, or will price rises be met with reduced demand

through substitution—both wood and non-wood (Perez-Garcia, 1993; Prins, 1993a and 1993b).Will there be less substitution in the future in species and/or origin typical of clear grades as

compared to structural?

The second ramification of the price trend distinctions shown in the figure is that coastal BCrelies on old-growth timber stands for the vast majority of its present lumber production. Timber

yielding clear grades is exploited In such stands. Given existing silvicultural efforts and harvestrotations, the supply of clear timber will be significantly reduced as old-growth availability declines.

This leads to the question of whether it is possible to generate this high grade economically fromsecond growth stands (although this will largely be an implication for further study). Related to the

substitution questions above, it must be asked to what extent clear lumber from second growth cancompete with clear lumber from old-growth timber. Also, to what extent will engineered wood

products such as laminated posts alleviate the scarcity of old-growth supplies. Finally, will therebe alternative sources of old-growth?

ObjectivesThe research problem described in the previous section can be translated into the following

three objectives:

1. To determine own-price and cross-price demand elasticities in Japan for logs,lumber and other wood products by exporting region and species. Cross-pricedemand elasticities include substitution with Japanese domestic logs, differentspecies, source of export (both with same and different species), and substitutionwith non-wood products.

2. To qualitatively extend objective one to explore Japan’s demand for broad gradecategories (construction versus appearance).

3. To explore the implications of the above for BC forest industry strategy and publicforest policy.

Organization of the PaperThe above objectives are addressed and presented in this paper as follows. Section 2

describes the Japanese wood products market. Section 3 describes the data used in this study,the empirical models used, and a summary of the results. Finally, Section 4 offers the

contributions, limitations and implications for further research.

2.0 THE MARKET FOR WOOD PRODUCTS IN JAPAN

This section investigates the market for wood products in Japan, including its evolution over

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the past several decades. This investigation starts with a synopsis of Japan's timber resources and

log production, followed by a description of the demand for this production along with the demandfor imports. Finally, a discussion of Japan's lumber and panel production, comparing domestic

with imported timber inputs, as well as competition with lumber and panel imports is presented.This is an important lead-in to Section 3, which describes the empirical model developed in this

study to represent the derived Japanese demand for logs, lumber and other wood products.

2.1 The Japanese Domestic Timber ResourceAlthough approximately 70 percent of Japan’s 37 million hectares is covered by forests, the

population is high (approximately 125 million, Canadian Global Almanac, 1995), resulting in a percapita forest area which, at less than a fifth of a hectare, is less than half the world average (Japan

Forestry Agency, 1991).

Of the total forest land in Japan, there are 13.67 million hectares of natural forests (54%),10.22 million hectares of man-made forests (40%), with the balance being either unstocked land

or bamboo groves (1.37 million hectares, or 6%). The natural forest area consists of 75%deciduous species, 13% coniferous species and 12% mixed forests. The deciduous species

include oak (Quercus mongolica and Quercus dentata), elm (Ulmus davidiana), ash (Fraxinusmandshuica), and beech (Fagus crenata). The coniferous species include fir (Abies veitchii, Abiesmariesii, and Abies sachalinensis), spruce (Picea hondoensis and Picea jezoensis), hemlock(Tsuga diversifolia), larch (Larix leptolepis), pine (Pinus densiflora, or red pine; Pinus pentapphylla,

or white pine; Pinus Thunbergii, or black pine), Hinoki (Chamaecyparis obtusa), and Sugi(Cryptomeria japonica).

In contrast, 98% of the man-made forest is coniferous. Ten percent of the area is larch,

11% is pine, 24% is Hinoki, 45% Sugi, 9% is spruce and fir, and 1% miscellaneous.

The growing stock of the natural forests is roughly 1.5 billion cubic metres compared toroughly 1.4 billion cubic metres in the man-made forests (Japan Forestry Agency, 1991). The man-

made forests are primarily a product of extensive planting which took place in two decadesfollowing World War II. Annual growth of the plantations is roughly 76 million cubic metres, or a

mean annual increment (MAI) of 7.5 cubic metres per hectare. Figure 2.1 shows the agedistribution of these trees.

In spite of this impressive growth rate on their man-made forests, it has been suggested

that the quality of the timber from these stands is not high, particularly in terms of inadequate logdiameters due to a noted lack of tree spacing (Iwai, 1986). This point will be returned to later.

Japan’s annual harvest from 1990 to 1993 ranged from about 27 million cubic metres to 30million cubic metres, with roughly 60% being harvested from the man-made forests. As can be

seen from Figure 2.2, which shows log production by species, this has dropped considerably sincethe 1960s. However, as made evident by Figure 2.1, the volume harvested can be expected to

1-15 Yrs 16-30 Yrs 31-45 Yrs 46-60 Yrs 60 + Yrs0

1000

2000

3000

4000

5000

6000

Given the reforestation effort in Japan post-World War II, and given that forest rotations in Japan are3

typically 40 to 60 years, depending on species, site quality, etc. (Iwai, 1986), this would suggest a significantincrease in the potential availability of domestic supplies early in the next century. However, these rotationswill also depend on desired log quality.

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Figure 2.1 Distribution of Man-made Forest by Age Class, 1986(Japan Forestry Agency, 1991)

increase significantly over the comingdecades .3

In terms of forest land ownership, as of 1986 58% was private, 31% national and the

remaining 11% was under prefecture and community control (Japan Forestry Agency, 1991). Theprivate forests (14.68 million hectares) are owned by nearly 3 million entities (individuals,

corporations and other organizations). Approximately 90% is owned by individuals, with anaverage holding of only 2.6 hectares (60% of the private owners own less than 1 hectare of land).

The national forest land base (7.89 million hectares) is under the jurisdiction of the ForestryAgency. The national forests tend to be located in the steep mountainous areas, unlike the private,

prefecture and community forests, which tend to be located in more economically accessible areas(Japan Forestry Agency, 1991). Roughly 33% of the national forests are replanted by area (as

of 1989), the vast majority of which is in softwood (Otsuka, 1992).

Of the total annual log production in Japan in 1990, 20.5 million cubic metres came fromprivate lands, 1.9 million cubic metres from the prefecture and community lands, and 8.6 million

It is noted that this is only true for traditional post and beam construction. Personal communication4

with Bob Holm, Executive Director of the BC Wood Specialties Group, reveals that this is changing. Mr. Holmsuggests that post and beam construction in Japan today is sometimes similar to North American platform-frame construction in-so-far as the posts are hidden from sight with panelling.

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Figure 2.2 Japanese Domestic Log Production by Species(Japan Forestry Agency Data, Provided by Dr. Y. Mori, Kyoto University, Japan)

Note: The volume scale on Figures 2.2, 2.3, 2.4, and 2.7 are identical for ease ofcomparison.

cubic metres from national forests. Figure 2.3 shows how this relationship has varied since 1960.Over 40% by area of the private lands are replanted (as of 1989) (Otsuka, 1992).

2.2 The Use of Japanese Domestic Timber ProductionJapan has a very long history of using wood, particularly for housing. The country's familiar

post and beam construction has created a demand for wood which has both structural strength and

appearance qualities. The importance of this combination lies in the visually exposed vertical pillarsjoined to exposed horizontal beams and girders .4

The domestic timber of choice for the pillars, due to their combined strength and high

appearance characteristics are Hinoki (Japanese cypress) and Sugi (Japanese cedar, orCryptomeria). For beams, Akamatsu (Japanese red pine) is often used for its ability to handle large

shearing stress. Foundations are often made from Hinoki due to natural rot-resistant properties.Sugi heartwood is often used for panelling due to its decorative colour. Sugi is also used for ceiling

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Figure 2.3 Japanese Domestic Log Production by Ownership(Japan Forest Agency Data, Provided by Dr. Y. Mori, Kyoto University, Japan)

boards due to its light weight. Overall, it is the Hinoki that has been the species most valued by

the Japanese, even in ancient times (Japan Forestry Agency, 1991).

Aside from the Japanese demand for wood used in post and beam construction, there hasbeen a growing demand for wood suitable for platform-frame (PFC) and prefabricated housing

construction. The wood imports most suitable for these housing types include North American S-P-F and other dried, planed, dimension softwood lumber, as well as panel products. Largely due to

the marketing efforts of the Canadian government an the Canadian Council of Forest Industriesin the mid 1970s, PFC starts rose from zero in 1975 to 56,299 in 1993, representing 4.8% of all

housing starts, or just over 8% of wood housing starts (INTEREX, 1995). Prefabricated housingconstruction was introduced in the 1950s, and by 1993 represented just over 20% (246,108 starts)

of total housing starts. However, most of the prefabricated homes are made from steel andconcrete, with wooden starts being roughly 30,000 in 1991 (Pesonen, 1993). Small amounts of

wood are required in steel prefabricated houses. Once again, planed, dimension lumber and panelproducts are demanded for this housing type.

Interestingly, hardwoods in Japan do not typically get used for decorative purposes. In fact,

hardwoods are primarily used as pulp furnish or other woodchip products, followed by their use inplywood manufacture. An estimated 35% of Japan’s plywood consumption is for the manufacture

of concrete forms, with most of the balance being used as sheathing in construction for walls, floors

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Figure 2.4 Japanese Domestic Log Supply by Utilization(Japan Forest Agency Data, Provided by Y. Mori,Kyoto University, Japan)

and roofing (Sedjo, et al., 1994).

Combined with softwood, over 60% of the domestic industrial timber in Japan hashistorically been used for lumber, followed by roughly 30% for pulp and wood chips combined, and

a small percentage for veneer sheets for plywood and other miscellaneous products (JapanForestry Agency, 1991). The historical context is presented in Figure 2.4.

One of the distinctive features of lumber demand in Japan is that in addition to the quality

of the wood, dimensions are critical. Not only are the dimensions demanded inconsistent withNorth American standards, but they can change from one region in Japan to the next, or even from

one building project to the next (Sedjo, et al., 1994; Japan Forestry Agency, 1991). This partiallyexplains the existence of thousands of local mills producing to meet highly localized demand

conditions (to be discussed in Section 2.4).

In 1992, 79% of domestic lumber shipments went into housing construction (Japan ForestryAgency). For this reason, a look at housing starts over time can be quite instructive; Figures 2.5

and 2.6 show both wood and non-wood housing starts since 1965, by number and by arearespectively.

The rapid growth in housing starts throughout the 1960s and early 1970s reflects the rapid

economic growth Japan was enjoying over this period. Referring back to either Figure 2.2 or 2.3,

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Figure 2.6 Japanese Housing Starts by Area(Japanese Ministry of Construction Data, Provided by Y. Mori,Kyoto University, Japan)

Figure 2.5 Japanese Housing Starts by Number(Japanese Ministry of Construction Data, Provided by Y. Mori,Kyoto University, Japan; 2x4 Data from INTEREX)

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domestic wood production also increased through much of this time, peaking at 53 million cubic

metres in 1967, and remaining over 40 million cubic metres through the early 1970s. (As will bemade clear in the next section, this domestic production was, of course, supplemented by growing

levels of imports.)

From the mid-1970s to the early 1980s this economic growth slowed and ultimatelydeclined, spurred by the "oil crisis" of 1973. After 1986, economic activity stabilized and began to

show modest growth (as did housing starts).

It is interesting to note that the population in Japan has not changed significantly over thepast several decades. During the 1960s, population increased by an average of 1% per year,

peaking at roughly 2% in 1970. Ever since then the rate of population growth declined, beingroughly 0.5% per year in 1989 (Yu, et al., 1990). This suggests that economic activity (or per

capita GNP) is a better indicator of housing starts than is population growth.

Before turning to a description of the Japanese lumber processing sector, imports of woodproducts are summarized in the following.

2.3 Imports of Wood Products into JapanAs can be seen in Figure 2.7, Japan has moved from a situation of almost total self-

sufficiency in wood products (95% of Japan's total industrial wood supply in 1955 came from

domestic production) to a very strong reliance on imports (only 25% of Japan's total industrial woodsupply in 1992 came from domestic production).

Figure 2.8 shows that Japan's self-sufficiency in logs alone has declined by a similar

magnitude for both softwood and hardwood. Domestic softwood sawlog production declined fromroughly 26 million cubic metres in the early 1960s to less than 16 million cubic metres over the

same period. The drop in domestic hardwood sawlog production is even more dramatic, movingfrom over 6 million cubic metres to less than 2 million cubic metres over these three decades.

Unlike softwood, imports have been an important component of hardwood log supply over thewhole period, ranging around the 10 million cubic metre mark both in the 1960s and early 1990s.

In fact, in the early 1960s, Japan imported almost twice as much hardwood logs by volume thansoftwood. By the 1990s this turned around, with imports of softwood logs being almost twice that

of hardwood logs (1962 and 1993 percentages of softwood log imports were 32% and 62%,respectively, with the total volume of log imports almost tripling).

It is also obvious from Figure 2.7 that Japan has shown a strong preference for importing

logs rather than lumber, although lumber imports increased throughout this period. Lumber importsincreased from 112,000 cubic metres in 1955 to 12,424,000 cubic metres in 1992, in roundwood

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Figure 2.8 Japanese Self-Sufficiency in Logs(FAO Yearbook, Various Years)

Figure 2.7 Japanese Industrial Wood Supply(Japan Forestry Agency Data, Provided by Dr. Y. Mori,Kyoto University, Japan)

-15-

equivalents. Log imports increased only up to 1973, and have been decreasing ever since. It is

widely accepted that this decline in log imports, relative to lumber and other wood product imports,is less a function of Japanese demand and more a function of world supply (Cartwright, 1995;

Pesonen, 1993; Sedjo, et al, 1994; Robertson and Waggener, 1995). Indonesia, for example,traditionally a major hardwood log supplier to Japan, adopted log export restrictions in the early

1980s, and by 1985 banned log exports all together. Presently, parts of Malaysia are consideringsimilar policies (Sedjo, et al., 1994). This trend toward log export restrictions is due in part to the

producing countries’ desire to develop their own wood processing industry, and in part to growinglocal economies (particularly Malaysia and Indonesia), which have increased domestic demand for

their wood products. US log supplies have also decreased, particularly logs cut from old growthtimber. The drop in the availability of such logs has become most pronounced over the past few

years, exacerbated by land withdrawals from the public forests for non-timber uses. As oneJapanese forest economist concludes, it is difficult for second growth PNW logs or domestic

Japanese logs to compete with lumber imported from BC, which has been produced from oldgrowth timber (Kato, 1982).

As a result of decreasing log supplies, Japan has, however unwillingly, been substituting

lumber for log imports. In 1965, 84% of all solid wood imports by value (logs, lumber, panel andother further manufactured products) were in the form of logs. By 1993, log imports as a

percentage of total solid wood products had decreased to 44% (Japan Tariff Association). Lumberimports increased from 15% to 33% of the value of total imports over the same period, while panel

product imports increased from 1% to 23% of the total.

Figures 2.9 and 2.10 illustrate how Japanese self-sufficiency in lumber and other panelproducts changed from 1962 to 1992. Keeping in mind that the domestic lumber or panel product

production in these figures includes production from imported logs, the fact that Japan's self-sufficiency in lumber and veneer has dropped significantly since the 1960s confirms its gradual

substitution away from logs.

Lumber imports, like logs, have also seen a shift away from hardwoods in favour ofsoftwoods. In 1962, only 11% of lumber imports were softwood, as compared to 85% in 1993, and

with roughly 15 times the volume of lumber imports in 1993 as compared to 1962.

Although Japan exports insignificant amounts of logs and lumber, the country hashistorically been a major exporter of hardwood plywood. In the 1950s, Japan was the second

largest plywood producer (after the US) and the largest exporter (primarily to the US and Europe).Due to increased domestic demands, export volumes became insignificant by the 1970s.

Indonesia replaced Japan in this market, exporting large volumes of tropical plywood by the early1980s. By 1988, Indonesia was the largest tropical plywood exporter in the world (FAO). Japan,

however, is still the second largest tropical plywood producer in the world, utilizing mostly imported

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Figure 2.9 Japanese Self-Sufficiency in Lumber(FAO Yearbook, Various Years)

Figure 2.10 Japanese Self-Sufficiency in Selected Panel Products(FAO Yearbook, Various Years)

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logs and veneer (primarily from Malaysia). In spite of this, Japan’s plywood imports have increased

from negligible amounts in the early 1960s to over 4 million cubic metres in 1993. Indonesiaprovides about 95% of these imports. Finally, Japan has also been producing softwood plywood

in increasing quantities in recent years (Sedjo, et al.,1994), although imports have remainedsluggish (less than 220,000 cubic metres in 1993; Japan Tariff Association).

To date, both domestic production and imports of other panel products have been minor

compared to plywood. In 1992, Japanese production of particle board was estimated at just over1 million cubic metres (roundwood equivalent; FAO) compared to imports of only 125,000 cubic

metres. Equivalent values for fibreboard are 929,000 cubic metres and 155,000 cubic metres,respectively. In neither case are Japanese exports significant.

Figures 2.11 through 2.14 illustrates the rather consistent sources of Japanese imports,

especially for softwood logs and lumber. In the case of hardwood logs, the major imports haveshifted away from the Philippines, first to Indonesia and then to Malaysia. This has not, however,

been the case for further processed products, particularly wood panels. In 1965, the major panelimports into Japan (primarily plywood) came from North America and Europe, whereas in 1993,

the biggest plywood imports came from Indonesia; this was also supplemented with fibreboardimports (with New Zealand being the largest supplier), and particle board (with Canada being the

largest supplier).

While the sources of Japanese wood product imports have been rather consistent, themarket share that each exporting country enjoys has not. The biggest change over the 1965-1993

period is the change from imports of hardwood to softwood, followed by the less pronouncedchange in imports from logs to lumber. This largely translates into an increase in Japanese market

share enjoyed by North America (mostly the PNW for logs and BC for lumber).

2.4 Japanese Processing of Domestic and Imported LogsAs made evident in the previous section, Japan has shown a strong preference for the

import of unprocessed logs over lumber and other products. This section explores the processingof logs in Japan, both domestic and imported, with the hope of shedding some light on input

preferences.

It was shown in Figure 2.4 that approximately 60-70% of Japan's domestic logs are usedfor lumber, with the balance being used primarily for pulp and wood chips, and small amounts for

veneer, fibreboard, scaffolding, and other miscellaneous uses. It was also shown that this roughbreakdown has remained relatively consistent over the 1965-1993 period. Virtually 100% of the

imported logs from North America, the former Soviet Union and New Zealand, by contrast, areused for lumber production. On the other hand, imported logs from the South Sea countries are

primarily used for veneer, with less than 20% being used for lumber (Japan Forest Agency).

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Figure 2.11 Japanese Imports of Softwood Lumber and Logs, 1993(Japan Tariff Association)

Figure 2.12 Japanese Imports of Softwood Lumber and Logs, 1965(Japan Tariff Association)

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Figure 2.13 Japanese Imports of Hardwood Lumber and Logs, 1993(Japan Tariff Association)

Figure 2.14 Japanese Imports of Hardwood Lumber and Logs, 1965(Japan Tariff Association)

It must be kept in mind that in 1989, New Zealand had not begun shipping significant quantities of5

its pruned pine. The percentage of their wood products going into Japanese housing can, therefore, beexpected to have changed quite dramatically.

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Figure 2.15 Japanese Lumber Shipments by Use(Japan Forestry Agency Data, Provided by Y. Mori,Kyoto University, Japan)

Figure 2.15 shows the total breakdown of Japanese lumber production, from combineddomestic and imported logs, over time. An average of 70-75% of the lumber production over the

period of this graph was used in construction, with the remainder being used primarily forpackaging and furniture.

As of 1989, roughly 80% of lumber made from domestic logs went into housing

construction, as was the case for lumber processed from North American and the former SovietUnion log imports. In the case of lumber produced from South Sea logs, however, only 45% went

into housing, while an additional 20% went into packaging and the remaining 35% into furniture andother miscellaneous uses. The vast majority (over 80%) of the lumber made from New Zealand

logs went into packaging (Otsuka, 1992).5

As of 1989, there where over 17,000 sawmills in Japan. Given lumber shipments ofapproximately 30 million cubic metres at that time, this gives an overall average output of only

1,750 cubic metres (roundwood equivalent) per mill. Of these sawmills, approximately 40%process domestic logs only, approximately 15% process imported logs only, and the balance

This higher price is likely due to the lower level of competing log imports.6

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process both (Otsuka, 1992).

Although the average sawmill size is small, especially by BC standards, they range

significantly in size. Those mills that utilize predominantly (or only) domestic logs are generallysmall family operations employing less than 10 people. These tend to be inland mills located close

to the timber source. While this makes up the majority of sawmills by number in Japan, those thatprocess predominately imported logs tend to be considerably larger. These are usually either

coastal mills, or mills located close to large urban centres.

Logging and sawmilling typically are not integrated in Japan. Sawmills purchase domesticlogs directly from the landowners, independent log producers, forestry cooperatives or sawlog

markets (which number in the hundreds). Imported logs are mostly purchased from tradingcompanies and wholesalers. Logs from the national forests in Japan are sold by competitive bid

(Kato, 1982).

There are many sources in the literature which state that Japan’s domestic log suppliershave difficulty competing with imports on price (see, for example, Sedjo, et al., 1994; Otsuka, 1992;

Iwai, 1986). In the case of Japanese cypress, for example, the stumpage cost alone averaged over40,000 Yen/m in 1990 (approximately $325 US), or a total cost of producing a domestic log of3

roughly 55,000 Yen (approximately $425 US) (Otsuka, 1992). This compared to the averageimport price for US hemlock logs (a competing species) of less than 27,000 Yen in 1990 (or less

than $210 US) (Japan Tariff Association). Reporting Japanese cypress log costs a decade earlier,Mochida (1984) quotes an even higher price of over 53,000 Yen/m stumpage and a total log cost3

of over 65,000 Yen/m .3 6

While it appears that imported lumber is also less expensive than domestically producedlumber, the higher cost of shipping lumber reduces the price differential. Otsuka (1992), quotes

three price comparisons for lumber from a study done by the Forest Products Research Institutein Japan. These comparisons are for the production of posts in 1990. The final cost of these posts

in Japan when domestic cedar logs were used was 54,800 Yen/m ; when North American hemlock3

logs were used, 48,400 Yen/m ; and finally, the cost of imported North American hemlock lumber3

was 43,000 Yen/m . In terms of US dollars, these values are approximately $420, $375 and3

$330/m , respectively.3

When looking at the price of lumber produced in Japan relative to imports, however, it is

not clear, due to inconsistencies in dimension and other measures of quality, that the two are ascomparable as is the case with logs.

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2.5 SummaryThis section has highlighted the significant trends in Japan’s demand for domestic and

imported wood products over the past three decades:

1) Japan has moved from almost total self-sufficiency in log inputs to a heavy reliance on logimports. Although Japan has undertaken considerable reforestation, this was mostly doneafter the war, leaving little opportunity to change this trend before the turn of the century.

2) At present, roughly 60% of Japan’s domestic log production is harvested from man-madeforests. Given the lower quality and higher cost of this source, compared to domestic oldgrowth, this again encourages log imports.

3) Although the harvest from Forest Agency land has remained rather constant over thisperiod, it has shown a gradual decline as a percent of total harvests; the significance of thislies in the fact that it is these lands that contain the largest percentages of old growth, albeiton less accessible lands than the private forests.

4) Domestic softwood log production dropped roughly 40% over this period while domestichardwood log production dropped more than 65%. Softwood log imports increased 400%while hardwood log imports stayed relatively constant.

5) While log imports have shown the noted overall increase over this period, imports actuallypeaked in 1973 and have been dropping ever since. Against this trend, lumber importshave been increasing throughout. As was the case with logs, Japan has shifted its lumberimports away from hardwoods in favour of softwoods.

6) The primary reason for the drop in log imports seems to be less a function of Japanesedemand and more a function of the declining availability of logs on the world market (dueto growing export restrictions and declining old growth supplies world-wide). The formerSoviet Union may offer major potential for added future supply.

7) While the sources of softwood log and lumber imports have not changed significantly overthis time period, total log and lumber market shares have.

8) North America and the former Soviet Union are the only significant suppliers of importedlogs for housing in Japan. Logs from these two countries are used almost exclusively forlumber production. Only 20% of South Sea logs are used for lumber production, and NewZealand logs have been used almost exclusively for packaging material.

9) Japan has not shown a great acceptance of either softwood plywood or other panelproducts as substitutes for its traditional hardwood plywood (of which Japan is a significantproducer). Instead, Japan initially shifted to using domestic hardwood logs and later shiftedto imported hardwood logs and veneer.

Japan has a significant domestic forest resource, with forested land as a percentage of the

total land base being very similar to that of BC, and growing conditions which allow for significantlygreater annual increments in their volume of timber. Given the high population density, however,

it is likely that domestic supply will continue to fall far short of demand. Further, given that Japanhas already exploited most of its accessible old growth stocks, coupled with a heavy reliance on

-23-

relatively inexpensive imports, much of Japan’s timber resources lie outside of the country’s

extensive margin (the existence of the imports putting downward pressure on domestic prices).It could be argued that much of Japan’s man-made timber stocks are also outside of the extensive

margin, due to the lower cost of imports relative to the cost of intensive silviculture and harvesting.

The question now, however, is will the Japanese substitute lower quality logs, importedlumber and other wood products for the high quality logs, which currently comprise a major

proportion of their total imports? Or, will Japan increasingly rely on domestic wood supplies?

In terms of BC, as a past and potential future supplier of wood products, Japan has showna strong demand for high quality lumber from BC’s old growth, in spite of its preference for logs.

Given the higher cost of log production in Japan, it is likely that this demand will continue for aslong as BC has old-growth stocks to mill; this could last for several decades if the expansion of

BC’s extensive margin outpaces that of Japan’s. At some point, however, it is possible (or evenlikely given BC’s present level of silvicultural efforts), that Japan’s domestic stocks will be more

valuable (revenue minus cost) than BC imports. In addition, of course, is the possibility ofincreased lumber imports from sources other than BC.

-24-

3.0 THE ANALYSIS OF THE JAPANESE DEMAND FOR WOOD PRODUCTS

This section reports the estimation of demand elasticities for wood products in Japan, by

type of product (logs, lumber and panel products, both soft and hardwood), species and source(domestic production and imported products). This begins with a discussion of the data used in

the analysis (Section 3.1), then moves into a brief discussion of the methodology used and theresults. Three separate methodologies are employed for comparison, reported in Sections 3.2 and

3.3. Added detail regarding the latter two methodologies can be found in Appendix A. Finally, asummary of the results is offered in Section 3.4.

3.1 The Japanese Wood Product Import DataThe main source of data for the quantity and price relationships is the Japan Tariff

Association, Imports of Commodity by Country. This publication offers data on the annual import

of all commodities in considerable detail, giving volume and value by country of origin. The dataset used in this study covers the period 1965 to 1993, with the recognition that the level of detail

diminishes as one goes further back in time. The reason that the study does not utilize data priorto 1965 is that the level of detail was considered to be inadequate.

In 1965, this publication reported imports from over 50 countries, broken down into a total

of 80 categories of wood products. This included 10 categories of softwood logs, 14 categoriesof hardwood logs, 16 categories of softwood lumber, 10 categories of hardwood lumber, 14

categories of panel products, and 16 categories of further manufactured products. Unlike lateryears, the wood product detail is primarily in the form of species. At the other extreme, 1993

showed considerably more detail. The total number of wood product categories increased to 145,broken down to 10, 20, 21, 23, 41, and 30, respectively, as above. The detail on country of origin

also increased, exceeding 80.

In order to run time series regressions over the entire 29 year period, it was necessary toaggregate much of the detail offered by these data in the later years in order to obtain consistent

product categories through all years. While this task was considerable in itself, it was furthercomplicated by the fact that the Japan Tariff Association utilized three different commodity

classification systems over this time period. This meant that the data had to once again beaggregated to the common denominator found over the three commodity classification systems.

As this requires a degree of subjective judgement, the end result of the aggregations used in thisstudy is reported in detail in Table 3.1.

As seen in the table, in spite of the need for aggregation due to changes in the data series

over time, considerable detail was retained. There are 10 categories of softwood logs (SLG-X) and10 categories of hardwood logs (HLG-X), the breakdown being purely by species. The first

-25-

Table 3.1: Japan Tariff Association Data, Converted CodesNew 65-75 76-87 88-93 Description

SLG-1 242-299 44.04-310 4403.20-010 Coniferous Logs, roughly squared or half squared

SLG-2 242-210 44.03-321 4403.20-091 Sawlogs & veneer logs, Pinus

SLG-3 242-221 44.03-322 4403.20-092 Sawlogs & veneer logs, Sitka spruce

SLG-4 242-229 44.03-323 4403.20-093 Sawlogs & veneer logs, Abies and Picea, excluding

Sitka spruce

SLG-5 242-230 44.03-324 4403.20-094 Sawlogs & veneer logs, Larix

SLG-6 242-240 44.03-325 4403.20-095 Sawlogs & veneer logs, white cedar, yellow cedar,

& other Chamaecyparis

SLG-7 242-250 44.03-326 4403.20-096 Sawlogs & veneer logs, hemlock & other Tsuga

SLG-8 242-260 44.03-327 4403.20-097 Sawlogs & veneer logs, red cedar & other Thuja

SLG-9 242-270 44.03-328 4403.20-098 Sawlogs & veneer logs, Douglas-fir & other Pseudotsuga

SLG-10 Sawlogs & veneer logs, conifer, n.e.s.242-298 44.03-329 4403.20-099

HLG-1 Non-coniferous logs, roughly squared or half squared242-391 + 44.04-100 + 4403.99-210 +

242-399 44.04-390 4403.99-311 +

4403.32-010 +

4403.33-011

HLG-2 242-310 + 44.03-331 + 4403.31-090 + Sawlogs & veneer logs, lauans and apitons to '75; lauan,

242-381 44.03-336 4403.32-090 + kruimg mersawa and other Dipterocarpaceae family '76-'87;

4403.33-019 + All Meranti, Keruing, and kapur, '88 onward, plus mahogany

4403.99-290

HLG-3 242-320 44.03-100 4403.99-319 + Sawlogs & veneer logs, Kwarin, Tsuge or boxwood, Tagayasan

4403.99-310 + (Cassia siamea Lam.), red sandal wood, rosewood, or

4403.33-099 ebonywood (excl. ebony w/ white streaks)

HLG-4 242-340 44.03-333 4403.99-391 Sawlogs & veneer logs, cottonwood and aspens

HLG-5 242-350 44.03-200 4403.99-190 Sawlogs & veneer logs, kiri (Paulownia)

HLG-6 242-360 44.03-334 Sawlogs & veneer logs, lignum vitae

HLG-7 242-370 44.03-335 4403.33-091 Sawlogs & veneer logs, teak

HLG-8 342-382 44.03-337 4403.99-392 Sawlogs & veneer logs, American black walnut

HLG-9 242-383 + 44.03-338 Sawlogs & veneer logs, sandalwood

242-384

HLG-10 242-389 + 44.03-339 + 4403.99-399 + Sawlogs & veneer logs, non-coniferous, n.e.s. (incl. oak

242-330 44.03-390 + 4403.91-000 + and beech post 1987)

44.03-332 4403.92-000 +

4403.34-000 +

4403.35-000

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Table 3.1: ContinuedNew 65-75 76-87 88-93 Description

SLM-0a 4407.10-330 Lumber, SPF, not more than 160 mm in thickness

SLM-0b 4407.10-320 Lumber, planed or sanded, n.e.s.

SLM-1a 243-211 44.05-310 4407.10-121 + Lumber, Pinus, not exceeding 160 mm in thickness

4407.10-330

SLM-1b 243-212 44.05-510/511 Lumber, Pinus, exceeding 160 mm in thickness

SLM-2a 243-221 44.05-512/521 4407.10-341 Lumber, Sitka spruce (combined; post 1977, not

exceeding 160 mm)

SLM-2b 44.05-522 4407.10-349 Lumber, Sitka spruce exceeding 160 mm (after 1977)

SLM-3a 243-222 44.05-320 4407.10-129 + Lumber, Abies (excluding Calif. red fir, grand fir, noble

4407.10-350 fir, etc.) & Picea, not exceeding 160 mm

SLM-3b 243-223 44.05-513/530 Lumber, Abies (excluding Calif. red fir, grand fir, noble fir,

etc.) & Picea, exceeding 160 mm

SLM-4a 243-231 44.05-330 4407.10-210 + Lumber, Larix, not exceeding 160 mm

4407.10-290

SLM-4b 243-232 44.05-540 Lumber, Larix, exceeding 160 mm

SLM-5a 243-240 44.05-515/551 4407.10-361 Lumber, white and yellow cedar and other Chamaecyparis

(post 1977, not exceeding 160 mm)

SLM-5b 44.05-552 4407.10-369 Lumber, white and yellow cedar and other Chamaecyparis,

exceeding 160 mm (post 1977)

SLM-6a 243-250/251 44.05-516/561 4407.10-371 Lumber, hemlock and other Tsuga (post 1974, not

exceeding 160 mm)

SLM-6b 243-252 44.05-517/562 4407.10-379 Lumber, hemlock and other Tsuga, exceeding 160 mm

(post 1974)

SLM-7a 243-260 44.05-518/571 4407.10-381 Lumber, Douglas-fir and other Pseudotsuga (post 1977, not

exceeding 160 mm)

SLM-7b 44.05-572 4407.10-389 Lumber, Douglas-fir and other Pseudotsuga, exceeding

160 mm (post 1977)

SLM-8 243-271 + 44.05-521/581+ 4407.10-310 Lumber, incense cedar

243-279 44.05-522/589

SLM-9a 243-280 44.05-529/591 4407.10-391 Lumber, conifer, n.e.s. (post 1977, not exceeding 160 mm)

SLM-9b 44.05-592 4407.10-399 Lumber, conifer, n.e.s., exceeding 160 mm (post 1977)

SLM-10 243-291 44.13-300 4409.10-310 Planed, grooved or tongued; Pinus, Abies, Picea and Larix

SLM-11 Planed, grooved or tongued, conifer, n.e.s.243-299 44.13-510 4409.10-320

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Table 3.1: ContinuedNew 65-75 76-87 88-93 Description

HLM-1 Lumber, Kwarin, Tsuge or boxwood, Tagayasan (Cassia243-310 44.05-100 4407.99-110 +

4407.99-190 siamea Lam.), red sandal wood, rosewood, or ebonywood

HLM-2 243-320 44.05-200 4407.99-210 + Lumber, Kiri

4407.99-290

HLM-3 243-330 44.05-531/593 4407.21-110 + Lumber, teak

4407.21-190

HLM-4 243-340 44.05-532/594 4407.99-410 + Lumber, lignum vitae

4407.99-490

HLM-5 243-350 44.05-400 4407.21-210 + Lumber, lauan, kruing, mersawa and other Dipterocarpacea

4407.21-290 +

4407.21-300 +

4407.99-310 +

4407.99-390 +

4407.23-000

HLM-6 243-360 44.05-539/599 4407.99-500 + Lumber, non-conifer, n.e.s.

4407.91-000 + (oak)

4407.92-000 + (beech)

4407.22-000

HLM-7 243-393 44.13-400 4409.20-330 Lumber, planed, grooved or tongued, lauan, kruing, mersawa

and other Dipterocarpaceae

HLM-8 243-399 + 44.13-590 + 4409.20-350 + Lumber, planed, grooved or tongued, non-conifer, n.e.s.

243-391 + 44.13-100 + 4409.20-310 +

4409.20-340

243-392 44.13-200 4409.20-320

VS-1 631-111 44.14-100 4408.90-100 Veneer sheets, Kwarin, Tsuge or boxwood, Tagcyasan, red

sandalwood, rosewood and ebony wood.

VS-2 631-112 + 44.14-220 4408.90-200 Veneer sheets, Teak

631-113

VS-3 631-119 + 44.14-210 + 4408.10-010 + Veneer sheets, n.e.s.

631-120 44.14-230 + 4408.10-021 +

44.14-290 4408.10-029 +

4408.20-010 +

4408.20-090 +

4408.90-300 +

4408-90-410 +

4408.90-490

Table 3.1: Continued

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New 65-75 76-87 88-93 Description

PLY Plywood; "cellular"; "blockboard"631-210 + 44.15-191 + 4412.19-011 +

631-211 + 44.15-111 + 4412.19-019 +

631-212 + 44.15-119 + 4412.19-021 +

631-213 + 44.15-192 + 4412.19-022 +

631-214 + 44.15-193 + 4412.11-011 +

631-219 + 44.15-194 + 4412.11-019 +

631-220 44.15-195 + 4412.11-021 +

44.15-196 + 4412.11-022 +

44.15-300 + 4412.11-023 +

44.16-000 4412.11-024 +

4412.11-029 +

4412.12-011 +

4412.12-019 +

4412.12-021 +

4412.12-022 +

4412.21-010 +

4412.21-090 +

4412.29-010 +

4412.91-090 +

4412.99-010 +

4412.99-090 +

4418.90-100

PB 631-420 44.18-100 + 4410.10-010 + Particle board; "reconstituted"; "densified"

44.18-200 4413.00-000 +

4410.90-010

FB 44.11-100 + 4411.11-000 -> Fibreboard; "hardboard"; "building board"

44.11-900 4411.99-000

LAM 631-410 44.15-200 + 4412.29-010 + Laminated; "improved"

44.17-000 4412.99-010 +

4412.21-010 +

4418.90-222

MISC 631-870 ---> 44.19-000 ---> 4409.10-200 + Misc.; incl. wood beading/moulding, boxes, casks,

632-899 44.28-290 4409.20-200 + barrels, wood for decorative use, etc.

4414-00-000 ->

4421.90-099

category in each, which is treated as lumber in this study, is logs which are roughly squared or half

squared (cants). Although it might have been expected that prices within this category would be

-29-

significantly higher than prices of dimension lumber, such is not the case; further, the reported

volumes in this category are very low. For this reason, SLG-1 and HLG-1 were aggregated withSLM-9 and HLM-9, respectively, these latter categories being softwood and hardwood lumber, not

elsewhere specified (n.e.s.), respectively. (For definitions of SLG-1, etc., see Table 3.1.)

There are 20 final categories of softwood lumber (SLM-X), along with 8 categories ofhardwood lumber (HLM-X). In the case of softwood lumber the categories include detail on size

breakdown (greater or less than 160 mm) as well as species. Unfortunately, this breakdown wasnot consistently offered throughout the entire period, starting only in 1974 and 1977 in most cases.

It is possible that there was no lumber imported by Japan less than 160 mm previous to theseyears. Further, just as was the case with cants, although there is a price spread between the two

size categories for most species, this spread is not as dramatic as one might expect. This isillustrated in Figures 3.1 and 3.2, which show size comparisons for Japanese imports of selected

Canadian lumber species. As a result, the size detail was not maintained in the regressionsreported in this study; volumes and total values were summed within each category.

It can also be noted in Table 3.1 that spruce-pine-fir (S-P-F) lumber and “planed or sanded”,

n.e.s. imports were not reported individually until 1988. It is assumed that previous to this datesuch imports were reported in the category of “planed, grooved or tongued”; the regressions

reported in this study, therefore, aggregate SLM-0, SLM-10 and SLM-11 into a single category.In the case of hardwood, the two categories of planed, grooved or tongued lumber, HLM-7 and

HLM-8, are aggregated into one category for the regressions.

It is with the panel products that the Japan Tariff Association data loses the greatest levelof detail in the earlier years. While the data from 1988 onward includes breakdown by species (or

at least hardwood versus softwood), and often other characteristics such as density and thickness,previous years lose detail progressively. For the regressions reported in this study, a single

category is used for each of the following: veneer sheets (VS-1 through VS-3 are aggregated),plywood, particle board, fibreboard, and laminated lumber. Other assumptions regarding panel

descriptions found in the data series are noted in Table 3.1 (for example, including “cellular” and“blockboard” in the plywood category).

Finally, the Japan Tariff Association data include considerable detail under the category of

miscellaneous, such as mouldings, wood beadings, and other further manufactured wood products.Imports in this category were not included in the present analysis due to their comparatively

insignificant volumes, and the problems associated with converting volumes to a common unit.

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Given the similarity of wood products imported from Canada and the United States, it7

would have been reasonable to combine these two into “North America”. However, thisdisaggregation was desired due to the emphasis on Canada in the results and discussion inChapters 5 through 7.

-31-

All log and lumber volumes are reported in cubic metres, roundwood equivalent. In the

aggregate regressions, where log imports are included with lumber and/or wood panel imports,consideration was given to using a lumber recovery factor. However, this was not done for two

main reasons. First, lumber recovery can vary widely, not only due to processing differencesamong sawmills, but also because of differences in the fibre source, species, log characteristics

and product being produced. Secondly, one might just as rightly state that the lumber imports byJapan should also include a “lumber recovery factor” insofar as Japan remanufactures a significant

quantity of its raw imports. This is, of course, particularly true for cants or other large dimensions.As assigning a value to this recovery would be highly arbitrary, it was decided to leave all volumes

as reported.

Panel products are reported in a number of different units, which makes conversions moredifficult. While 1000 square metres of panel products which are 1 mm thick equal one cubic metre,

the product categories used in this study span a great variety of thicknesses, not all of which arereported. To get around this problem, it was noticed that the value of panel imports reported by

the Japan Tariff Association very closely parallel those quoted by the FAO over the same timeperiod (once converted to a common currency)(Forest Products Yearbook, various issues). As a

result, the panel product volumes in this study were converted using the average values suggestedby the FAO data.

As particle board and laminated lumber are quoted in cubic metres (solid wood equivalent),

they required no conversions for the present study. Plywood and veneer sheets are quoted insquare metres and were converted to cubic metres by dividing by 135 (FAO). Fibreboard is quoted

in kilograms and was converted to cubic metres by dividing by 300 (FAO).

As the country of origin detail was much too high for the purposes of this study, six countrygroups were created and data aggregated accordingly: Canada, the United States , the former7

Soviet Union, the combined imports from New Zealand and Chile (representing the major plantationproducers of radiata pine), the combined imports from the South Seas, and the combined imports

from the “rest-of-world” (all other countries exporting wood products to Japan). While The JapanTariff Association does not break down Canadian imports by province, as Table 3.2 demonstrates

for lumber, the vast majority of Canadian off-shore solid wood product exports originate from BritishColumbia.

A number of additional time-series data were needed for the present study. As noted in

Center for International Trade in Forest Products (CINTRAFOR).8

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Section 2, domestic log and lumber production were obtained from the Japan Forestry Agency,

Table 3.2 B.C. Offshore Lumber Exports Relative to the Whole of Canada(000s m )3

Year B.C. Canada B.C./Canada

1982 4377 5025 87.1%

1985 3810 4004 95.2%

1986 3822 4153 92.0%

1987 5739 6181 92.8%

1988 6141 6854 89.6%

1989 6039 6951 86.9%

1990 6093 7406 82.3%

Source: Selected Forestry Statistics Canada, Information Report E-X-47, Natural Resources Canada,1993.

Table of Demand and Supply. Prices for domestic logs and lumber were obtained from the JapanWood Products Information & Research Centre; from 1984 on these prices were received directly

from their in-house publication (various issues), while prices before this date were obtained fromthe Global Trade Model data bank at the University of Washington .8

To convert the price series used in the estimation of aggregate imports to real values, the

deflator employed was the Japanese producer price index for imported “wood, lumber & relatedproducts” (Bank of Japan).

For the “cost of everything else”, noted as P later on in this section, a monthly wageE

earnings index for Japan was used, obtained from FAO’s International Financial StatisticsYearbook (1994). In those regressions where it was desirable to investigate cross-price elasticities

between the quantity of a wood product demanded and a non-wood import, individual wholesaleprice indices for iron & steel products, ceramics, stone & clay products, and for plastic products

were used, obtained from the Bank of Japan.

Finally, the per-capita GNP values were obtained from FAO’s International FinancialStatistics Yearbook (1994).

GNP 1Q �1D Q �2

I Q �3E

C PDQD � PIQI � PEQE

In this discussion, output is taken to be gross national product (GNP). In much of the9

literature which investigates the derived demand for wood inputs, housing starts is used. In thepresent study, however, which is looking at various forms of the wood input (logs as well aslumber), a more general measure of output is considered appropriate.

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3.2 Individual Estimates of Own-Price Elasticities of DemandThe literature review offered in Appendix A reveals that the estimation of own-price and

cross-elasticities for a number of potentially unique, yet related, price series is problematic. The

estimation of the Japanese import of wood products down to the level of detail desired here offeredno exception. The potential solution discussed in the review was an Armington-type model which

estimates demand in a two-step process, essentially measuring the demand of aggregated wooddemand in the first step, then breaking up this demand into its component parts in the second step.

However, it is shown in the appendix that putting this procedure into practice is not without its ownproblems. For this reason, it is desirable to first estimate individual own-price elasticities by more

conventional methods, allowing for subsequent comparisons to the two-stage approach.

The most straight-forward method of estimating the demand for wood products in Japanis through derived demand. Japanese home builders, being the primary end users of wood

products, have a number of choices among possible material inputs. They can use domesticlumber milled from domestic logs, domestic lumber milled from imported logs, or imported lumber.

Builders can also choose between hardwood and softwood, and between domestic and importedfurther processed wood products (such as wood panels). Finally, the builders can change the

proportion of wood to non-wood materials used. It must also be noted that the builders’ choice ofinput is dependent on the type of housing construction, such as post and beam versus platform-

frame, with the former requiring larger dimensions, higher quality, and different species (seeSection 2).

In making these decisions, economic theory suggests that the builders (or the building

industry) will combine these alternative wood products with other inputs needed in the productionof houses (such as labour, energy, machinery and capital) in such a way as to maximize profits or,

equivalently, to minimize costs subject to the production function. To illustrate, consider a Cobb-Douglas production function as follows :9

(3.1)

where: GNP = gross national product in Japan;Q = the quantities of domestic wood, imported wood, and the quantity ofk

“everything else” that goes into building a house;1,� = parameters.i

The costs of building these homes can be represented as:(3.2)

QI 5P�1

I P�2

D P�3

E GNP �4

ln(QIt) �0 �1 ln(PIt) � �2 ln(PDt) � �3 ln(PEt) ��4 ln(GNPt) � µt

-34-

where: P = the price of Qk k

If builders are assumed to adjust their input mix in such a way as to minimize costs subjectto the technology described by Equation 3.1, this will yield the derived demand for input materials,

as a function of only input prices and output quantity:

(3.3)

where: Q = the quantity demanded of a specific imported wood product;I

P = the price of this product;I

P = the Japanese domestic price;D

P = the price of “everything else” that is used along with this product toE

produce the output;

GNP = Per-capita gross national product as a proxy for production output.

By empirically estimating Equation 3.3 when Q , for example, is the quantity of all importedI

lumber by Japan, the value of � would represent the own-price demand elasticity of imported1

lumber (thus the expected minus sign), � and � the cross-price elasticities for changes in the2 3

quantity of imported lumber demanded given changes in the prices of Japanese domestic lumber

and “everything else”, respectively, and � the change in quantity of imported lumber demanded4

given a change in production output.

The individual regressions reported in this section vary Q and P over various levels ofI I

aggregations individually, ranging from highly aggregated (all wood product imports by Japan,including logs lumber and panels) to highly disaggregated (for example the Japanese import of

yellow cedar lumber from Canada). In the case of total aggregation, P in Equation 3.3 representsD

the domestic price of logs in Japan. In all other case of less aggregated products (say softwood

lumber imports), P is the average of both the domestic Japanese log price and the price of allD

imports other than that being estimated (all imports except softwood lumber).

In all of the regressions, a Cobb-Douglas form was used, translating Equation 3.3 to:

(3.4)

Table 3.3 shows the ordinary least square (OLS) and the Cochrane-Orcutt estimates of theJapanese demand for aggregated wood product imports (including logs, lumber and panel

products, both softwood and hardwood). In log-log form, the quantity of import demand isregressed on the real unit price of the aggregate wood products import (P ), the domestic price ofI

logs in Japan (P ), an index of wage rates in Japan (P ) and the per capita gross national productD E

in Japan (GNP).

Durbin-Watson critical values are quoted from Judge, et al. (1988), reproduced from10

Savin and White (1977).

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Table 3.3 Estimates of the Japanese demand for aggregated wood imports.

Constant P P P GNP R -Adj. DWi D E2

Ordinary Least Square

12.741 -0.1607 1.208 -0.802 0.842 0.646 0.590(11.630) (-0.642) (3.366) (-5.347) (6.935)

Cochrane-Orcutt Durbin’s h

13.625 -0.0373 0.862 -0.719 0.8253 0.816 0.233(12.280) (-0.194) (2.324) (-3.341) (4.919)

Note: P , P , P , and GNP, are the logarithms of the price of aggregate wood imports (logs,i D E

lumber and panels), the price of Japanese domestic logs, the monthly average wageindex in Japan, and per capita GNP in Japan, respectively. Numbers in parentheses aret-values.

The reason for including the Cochrane-Orcutt estimate is apparent from the investigation

of the Durbin-Watson (DW) statistic in the OLS regression. The lower and upper bound criticalvalues for the DW test for five parameters and 29 observations are 1.124 and 1.743, respectively .10

As the DW statistic from the OLS regression lies below the lower bound, suggesting that thisregression is potentially serially correlated, a Cochrane-Orcutt regression is used.

The value of Durbin’s h statistic on the Cochrane-Orcutt regression is 0.233, indicating that

there is no evidence of higher order autocorrelation. Under the null hypothesis of no higher orderautocorrelation, Durbin’s h is asymptotically normal with zero mean and unit variance. This null

hypothesis is rejected if the statistic is greater than 1.645 at the 5 percent level of significance(1.645 being the t-value at 5 percent significance with � degrees of freedom) (see Judge, et al.,1988; and Whit, 1993).

The direct factor demand regression reported in Table 3.3 was tested for evidence ofstructural change in two ways. First, a sequential Chow test was performed. Second, the

regression was re-run with the inclusion of dummy variables, both on the intercept and on theimport price. The dummy variable was defined as being zero for the first x years and one

otherwise. This was done with two different values of x. The first period is defined as being from1965 to 1973 due to the rapid growth in Japanese housing starts as compared to 1974 to 1993.

Further, Japan utilized fixed exchange rates based on the gold standard until the early 1970s. Thesecond period is defined as being 1965 to 1980, due to the introduction of log export controls by

10,000,000

20,000,000

30,000,000

40,000,000

50,000,000

60,000,000 C

ubic

Met

res

1965 1968 1971 1974 1977 1980 1983 1986 1989 1992

Observed Predicted

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Figure 3.3 Observed versus predicted values of quantity demanded of aggregate softwood lumberimports by Japan when regressed on the average import price, possible wood substituteprice (other wood imports and domestic logs), the Japanese wage index, and per capitaGNP.

two major South Sea hardwood log producers in the early 1980s.

The Chow test rejects structural change, and there are insignificant t-values on the interceptand import price dummy variables.

More generally, Table 3.3 demonstrates that this regression offers a reasonably good fit,

with an adjusted correlation coefficient of 0.816. This is graphically illustrated in Figure 3.3.Further, all of the parameter values meet a priori expectations in terms of sign, and all parameter

values are significant with the exception of that on the imported wood price. That this parameteris insignificant comes as no great surprise; one would expect the own-price elasticity of aggregate

imports of all wood products to be highly inelastic (few available substitutes). The parametershown can be interpreted as not being significantly different from zero.

Table 3.4 shows the results of estimating the derived demand for selected disaggregations

of Japanese wood product imports. Cochrane-Orcutt regressions are again employed due toevidence of serial correlation. Each row in the table represents an individual regression, changing

the dependent variable Q and independent variable P in each case, with the i representing thei i

specific product indicated. The individual regressions also include a second price variable, being

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Table 3.4 Estimates of the Japanese demand for selected disaggregated wood imports.

Constant P P P GNP R -Adj. Durbin’s hi O E2

Softwood lumber from all sources

11.109 -0.650 1.469 -0.710 1.562 0.940 0.499 (9.313) (-2.340) (3.351) (-4.105) (8.839)

Softwood lumber from Canada

9.897 -0.951 2.104 -0.547 1.639 0.880 0.290(5.371) (-2.473) (2.965) (-1.855) (5.561)

Yellow cedar lumber from Canada

3.743 -0.398 0.599 -0.308 1.415 0.835 0.776(1.415) (-3.300) (3.833) (-0.961) (4.223)

Sitka spruce from Canada

8.124 -1.109 1.553 -0.366 1.222 0.676 0.119(2.222) (-2.287) (2.543) (-1.259) (3.111)

Douglas fir lumber from Canada

5.197 -1.255 1.993 -0.993 1.422 0.911 0.259(8.814) (-3.012) (2.265) (-0.831) (6.619)

Hemlock lumber from Canada

4.593 -0.209 0.439 -0.577 1.198 0.618 0.926(3.770) (-0.255) (0.630) (-3.169) (2.999)

Other lumber from Canada

12.282 -1.536 2.003 -0.387 1.500 0.809 0.456(6.991) (-2.558) (2.931) (-1.553) (8.803)

“Planed” lumber from Canada

3.730 -3.591 3.596 -0.470 1.338 0.956 0.188(0.694) (-3.216) (2.302) (-0.446) (6.172)

Softwood lumber from the US

3.619 -1.329 2.531 -0.891 1.626 0.788 0.557(1.922) (-1.529) (2.013) (-0.809) (4.233)

Red cedar lumber from the US

8.808 -0.040 0.983 -1.202 1.577 0.713 0.707(6.811) (-1.893) (1.689) (-1.098) (2.633)

Note: P, P , P , and GNP, are the logarithms of the price of the indicated wood product, thei O E

average price of other imported wood products and Japanese domestic logs combined,the monthly average wage index in Japan, and per capita GNP in Japan, respectively.Numbers in parentheses are t-values.

Table 3.4 (Cont.) Estimates of the Japanese demand for selected disaggregatedwood imports.

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Constant P P P GNP R -Adj. Durbin’s hi O E2

“Planed” lumber from the US

9.331 -5.309 4.863 -0.239 1.207 0.866 0.122(3.167) (-2.981) (2.887) (-0.883) (4.454)

Softwood lumber from New Zealand

6.118 -3.217 2.881 -0.408 0.967 0.777 0.142(4.298) (-2.009) (2.514) (-1.255) (4.833)

Softwood lumber from the former Soviet Union

1.181 0.045 0.454 -0.611 0.983 0.606 0.983(2.645) (0.893) (1.563) (-0.607) (3.398)

Softwood lumber from Other

9.910 -1.417 2.691 -0.436 1.262 0.903 0.188(4.111) (-4.253) (3.109) (-3.162) (5.331)

Hemlock lumber from Other

14.232 -3.417 3.139 -0.228 1.403 0.897 0.558(7.319) (-2.999) (3.222) (-1.936) (8.278)

“Planed” lumber from Other

6.689 -0.517 1.404 -0.655 1.239 0.770 0.812(5.557) (-1.807) (2.300) (-2.300) (5.309)

Softwood logs from all sources

15.609 -0.0901 0.174 -0.372 0.651 0.752 0.774(20.99) (-0.294) (0.703) (-1.345) (2.475)

Softwood logs from the US

11.712 -0.209 1.146 -0.653 0.777 0.634 0.0387(6.843) (-1.660) (1.943) (-2.318) (3.653)

Sitka spruce logs from the US

5.177 -0.104 0.399 -0.481 1.293 0.701 0.836(4.008) (-1.809) (2.166) (-1.563) (2.599)

Abies/picea logs from the US

3.696 -0.339 1.190 -0.936 0.880 0.793 0.254(1.990) (-1.458) (2.203) (-0.816) (3.636)

Yellow cedar logs from the US

8.294 -0.400 0.525 -0.267 1.193 0.660 0.779(5.073) (-1.826) (1.927) (1.193) (3.101)

Note: P, P , P , and GNP, are the logarithms of the price of the indicated wood product, thei O E

average price of other imported wood products and Japanese domestic logs combined,the monthly average wage index in Japan, and per capita GNP in Japan, respectively.Numbers in parentheses are t-values.

Table 3.4 (Cont.) Estimates of the Japanese demand for selected disaggregatedwood imports.

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Constant P P P GNP R -Adj. Durbin’s hi O E2

Hemlock logs from the US

10.363 -0.388 1.121 -0.622 0.655 0.819 0.903(4.468) (-2.473) (2.301) (-2.456) (2.709)

Douglas fir logs from the US

3.290 -0.554 0.906 -0.355 0.773 0.791 0.127(6.309) (-2.936) (2.631) (-1.853) (1.985)

Softwood logs from Canada

2.333 -2.318 1.939 -0.800 1.283 0.613 0.505(8.300) (-1.709) (1.881) (-2.067) (3.929)

Softwood logs from the NZ/Chile

11.255 -3.015 3.093 -0.553 1.098 0.788 0.816(3.901) (-2.190) (2.361) (-1.637) (1.986)

Softwood logs from the former Soviet Union

5.100 -0.109 0.666 -0.839 1.459 0.512 1.233(1.994) (-0.029) (1.101) (-0.934) (2.069)

Softwood logs from “Other”

9.112 -1.747 2.447 -1.143 0.769 0.876 0.311(4.373) (-7.419) (4.938) (-5.046) (2.349)

Hardwood lumber from all sources

13.989 -1.158 1.685 -0.672 1.693 0.954 0.421(9.526) (-4.477) (3.685) (-1.632) (5.519)

Hardwood logs from all sources

12.875 -0.0827 0.675 -0.604 0.723 0.820 0.808(9.709) (-0.631) (1.913) (-2.310) (2.419)

Panel products from all sources

14.139 -2.531 2.334 -0.887 1.481 0.883 0.866(-3.400) (-3.965) (2.360) (-0.632) (1.195)

Note: P, P , P , and GNP, are the logarithms of the price of the indicated wood product, thei O E

average price of other imported wood products and Japanese domestic logs combined,the monthly average wage index in Japan, and per capita GNP in Japan, respectively.Numbers in parentheses are t-values.

the average real unit price of all other possible wood substitutes. This includes the price ofimported products other than Q and the price of domestic logs in Japan. The average real pricei

per unit of these two substitution possibilities is indicted as P in the table. The other independentO

variables, being the wage rate index in Japan (P ) and the Japanese per capita gross nationalE

product (GNP) are common to all of the regressions.

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Over all, the regressions offer reasonably good fits, with adjusted correlation coefficients

typically over 0.8. Further, almost all of the parameter values meet a priori expectations in termsof sign, and the majority of the parameter values are significant. Finally, tests for structural change

were again rejected in each case.

It is interesting to note the differences in own-price elasticities based on product (withimported log demand being highly inelastic, panels being rather elastic and lumber lying

somewhere in-between), source (for example, demand for US softwood logs being highly inelasticand softwood logs from “other” being elastic), and species (for example, the demand for yellow

cedar lumber from Canada being highly inelastic and “planned” lumber being quite elastic).

Before proceeding to the results of the two-stage estimations of own-price and cross-priceelasticities, the results of the regression which estimates the degree of non-wood substitution is

offered.

Table 3.5 shows the same regression reported in Table 3.3, but with the addition of a priceindex for iron/steel. The parameter on this non-wood “substitute” comes as somewhat of a

surprise, as it has a negative sign (although the parameter is not significant). This suggests thatiron/steel acts as a complement to wood in the Japanese output of products (as measured by the

per capita GNP), rather than as a substitute. Aside from the possibility of multicollinearity amongthese regressors (i.e., that the iron/steel parameter is not meaningful due to very high variances),

one would have to conclude that for the Japanese output which requires wood as an input (whichis primarily housing construction in Japan), iron/steel is also desired in combination.

Table 3.5 Cochrane-Orcutt estimates of the Japanese demand for aggregated wood imports, with theinclusion of a non-wood regressor.

Constant P P P P GNP R -Adj. Durbin’s hi D E steel2

13.305 -0.0062 0.879 -0.621 -0.312 0.923 0.815 0.172(11.500) (-0.0313) (2.364) (-2.590) (-0.958) (4.719)

Note: P , P , P , P and GNP, are the logarithms of the price of aggregate wood imports (logs, lumber andi D E steel

panels), the price of Japanese domestic logs, the monthly average wage index in Japan, the price indexof iron/steel in Japan, and per capita GNP in Japan, respectively. Numbers in parentheses are t-values.

3.3 Armington Two-Stage Estimates of Own- and Cross-Price Elasticities ofDemand

The shortcoming of the methodology reported in the previous section is that it does not

ln(QIt) �0 �1 ln(PIt) � �2 ln(PDt) � �3 ln(PEt) ��4 ln(GNPt) � µt

lnQi

Qj t

Q0i ) lnPi

Pj t

� �t

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allow for cross-price elasticities of demand to be estimated. For example, it would be useful to

estimate the change in the Japanese quantity demanded of S-P-F lumber imports from Canadain response to a price increase of Radiata pine from New Zealand.

Theoretically, this could have been estimated by using Equation 3.4 and including the prices

of a number of additional products, thereby offering chosen cross-price elasticities directly.Unfortunately, this is not practical for two reasons. First, the prices of, say, softwood lumber

imports from Canada by species will likely have similar trends even if they display differences inmagnitude. This invariably leads to problems of multicollinearity, which tends to exaggerate the

variance of the price variable. This may lead to the elimination of an important price variable fromthe regression, leading to potential biases. The second practical problem of including a high

number of prices as regressors is the loss of degrees of freedom. Given that there are a greatnumber of wood products when broken down by type, species and source, and annual data that

spans 1965 to 1993, the degrees of freedom would easily be diminished to unacceptably low levels.

From the discussion offered in Appendix A, Armington (1969) offers a potential solution.The approach, illustrated empirically by Chou and Buongiorno (1983), allows for a highly

aggregated form of Equation 3.4 to be used, such as the quantity of all lumber imports by Japan,yet still leads to highly disaggregated price elasticity information. This is accomplished by a two

step process. First, the demand for total imports of a kind (such as softwood lumber) is estimated,derived from the demand for some measure of output (such as GNP or housing starts). Second,

the demand for individual sources of the product, derived from the demand for the product inaggregate is estimated.

The two-stage approach essentially estimates the following two equations independently:

(3.5)

(3.6)

Equation 3.5 is identical to Equation 3.4 estimated earlier, Q in this case representing someaggregate, such as all softwood lumber imports. In Equation 3.6, a constant elasticity of

substitution, ), is estimated by specifying all combinations of the components of the aggregateimport measured in Equation 3.5, such as softwood lumber from different sources or different

species (the Q/Q ’s). These combinations are estimated as a system of equations, and restrictingi j

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the estimated elasticity of substitution to be constant. To ensure that the quantity and price

variables in Equations 3.5 and 3.6 are related, Equation 3.5 is estimated with constant elasticityof substitution price and quantity indices, calculated from the value of ).

As shown in Appendix A, the own- and cross-price elasticities of demand can now be

calculated from knowledge of the market shares of the disaggregated products (for example, theshare of Canadian softwood lumber imports to all softwood lumber imports), the value of �1 and

the value of ). The results are displayed in Tables 3.6 through 3.8 for three different levels ofproduct aggregation: all Japanese wood product imports by type, softwood lumber imports by

source, and softwood lumber imports from Canada by species.

Beginning with the highest level of aggregation in Table 3.6, note that all of the own-priceelasticities (the diagonal from upper left to lower right) have the expected minus sign, with both

softwood and hardwood logs reflecting slightly inelastic demand and softwood lumber, hardwoodlumber and panels reflecting elastic demands. The cross-price elasticities also have the expected

signs, and are less than unitary in all cases. Note that the cross-price elasticities indicate a greaterwillingness to substitute lumber and panels in response to increases in the price of logs than the

other way around.

Table 3.6 also breaks out the substitution and market expansion effects of the calculatedelasticities (see Appendix A). As the own-price elasticity of the aggregate demand of all wood

product imports (the � ) is insignificantly different from zero, however, the market expansion effect1

is always zero.

Table 3.7 shows the calculated own- and cross-price elasticities of demand when imports

are defined as softwood lumber by country of origin. The own-price elasticities are represented bythe sum of the two values in each cell (the addition of the substitution and market expansion

effects), and are again of the expected sign. All values reflect inelastic demand, with little variationby source of the softwood lumber.

The signs of the cross-price elasticities, on the other hand, are not what one might initially

expect. In all cases, the sum of the two values (again, the substitution and market expansioneffects) is negative; without investigation of the component parts one comes to the conclusion that

softwood lumber from different sources are complements rather than substitutes. This is shown

Table 3.6 Calculated own- and cross-price elasticities of demand for the Japaneseimports of all wood products by type.

SLG HLG SLM HLM PANSLG -0.888 Sub 0.552 0.213 0.063 0.061

X 0 0 0 0 0

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HLG -0.904Sub 0.568 0.213 0.063 0.061X 0 0 0 0 0

SLM -1.243Sub 0.568 0.552 0.063 0.061X 0 0 0 0 0

HLM -1.393Sub 0.568 0.552 0.213 0.061X 0 0 0 0 0

PAN -1.395Sub 0.568 0.552 0.213 0.063X 0 0 0 0 0

Shares 0.390 0.379 0.146 0.043 0.042

* SLG, HLG, SLM, HLM, PAN refer to softwood logs, hardwood logs, softwood lumber,hardwood lumber, and aggregate wood-based panels, respectively,

* The elasticity of substitution ()) = 1.456* The elasticity of the Japanese demand for aggregate imports (�) = 0* Shares (S ) are calculated by value at the mean.i

* Own-price elasticity of each product type is calculated as (1-S )) + S �i i

* Cross-price elasticity between product types is calculated as S ) - S �j j

* Sub = substitution effect; X = market expansion effect

by the positive substitution effects not to be the case, however. The negative net effect occursbecause the market expansion effect counteracts the substitution effect in all cases, as the

constant elasticity of substitution is smaller in value than the elasticity of demand of the aggregateimport of softwood lumber from all sources. The result of this “cancelling” effect is that the cross-

price elasticities are very low in all cases.

Finally, Table 3.8 shows the calculated own- and cross-price elasticities of demand whenfocussing on the Japanese imports of Canadian softwood lumber by species. The signs are again

as expected, being negative for both the own- and cross-price elasticities, noting once again thatthe market expansion effect in the latter is more than offsetting the substitution effect.

When comparing the own-price elasticity estimates from Tables 3.6 through 3.8 with the

direct estimates offered earlier, it can be noted that they are far from being similar. Most notably,the range in the own-price elasticities, whether by product type, softwood lumber by source, or

Canadian softwood lumber by species is considerably narrower with the two-stage estimations.The reason for this is undoubtably the restrictive nature of the constant elasticity of substitution

assumption. In fact, appropriate tests on the simultaneous equations reject the hypothesis of aconstant elasticity of substitution. This should not really come as too big of a surprise. After

Table 3.7 Calculated own- and cross-price elasticities of demand for the Japaneseimports of softwood lumber by country of origin.

SLM SLM SLM SLM SLMCan US NZ RU OTH

SLM -0.318Can Sub 0.208 0.023 0.016 0.071X -0.252 -0.028 -0.020 -0.086 -0.382

SLM -0.425US Sub 0.315 0.023 0.016 0.071X -0.382 -0.028 -0.020 -0.086 -0.252

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SLM -0.610NZ Sub 0.315 0.208 0.016 0.071X -0.382 -0.252 -0.020 -0.086 -0.028

SLM -0.617RU Sub 0.315 0.208 0.023 0.071X -0.382 -0.252 -0.028 -0.086 -0.020

SLM -0.562OTH Sub 0.315 0.208 0.023 0.016X -0.382 -0.252 -0.028 -0.020 -0.086

Shares 0.498 0.328 0.036 0.026 0.112

* SLM , SLM , SLM , SLM , and SLM refer to softwood lumber from Canada,Can US NZ RU OTH

the US, New Zealand, the former Soviet Union, and “other” countries, respectively* The elasticity of substitution ()) = 0.6331* The elasticity of the Japanese demand for imports of all softwood lumber (�) = 0.768* Shares (S ) are calculated by value at the mean.i

* Own-price elasticity of each product type is calculated as (1-S )) + S �i i

* Cross-price elasticity between product types is calculated as S ) - S �j j

* Sub = substitution effect; X = market expansion effect

Table 3.8 Calculated own- and cross-price elasticities of demand for the Japanese imports ofCanadian softwood lumber by species.

SLM SLM SLM SLM SLM SLMC2 C5 C6 C7 C9 C0

SLM -0.424 C2 Sub 0.075 0.229 0.022 0.015 0.083X -0.203 -0.623 -0.061 -0.039 -0.227-0.145

SLM -0.403C5 Sub 0.053 0.229 0.022 0.015 0.083X -0.145 -0.623 -0.061 -0.039 -0.227-0.203

SLM -0.248C6 Sub 0.053 0.075 0.022 0.015 0.083X -0.145 -0.203 -0.061 -0.039 -0.227-0.623

SLM -0.455C7 Sub 0.053 0.075 0.229 0.015 0.083X -0.145 -0.203 -0.623 -0.039 -0.227-0.061

SLM -0.463C9 Sub 0.053 0.075 0.229 0.022 0.083X -0.145 -0.203 -0.623 -0.061 -0.227-0.039

SLM -0.394C0 Sub 0.053 0.075 0.229 0.022 0.015X -0.145 -0.203 -0.623 -0.061 -0.039 -0.227

Shares 0.112 0.157 0.480 0.047 0.030 0.175

* SLM , SLM , SLM , SLM , SLM , and SLM refer to Canadian Sitka spruce lumber, yellowC2 C5 C6 C7 C9 C0

cedar, hemlock, Douglas fir, “other” species, and “planed”, respectively.* The elasticity of substitution ()) = 0.477* The elasticity of the Japanese demand for imports of softwood lumber from Canada (�) = 1.299* Shares (S ) are calculated by value at the mean.i

* Own-price elasticity of each product type is calculated as (1-S )) + S �i i

* Cross-price elasticity between product types is calculated as S ) - S �j j

* Sub = substitution effect; X = market expansion effectall, the assumption states that the Japanese wood buyer views the substitution of softwood lumberfrom New Zealand for softwood lumber from the US, for example, exactly the same as substituting

Canadian softwood lumber for US lumber.

Ironically, this means that the procedure suggested by Armington (1969), and laterforwarded by Chou and Buongirno (1983), largely negates what Armington set out to accomplish

to begin with. This was to show that the assumption of homogeneous “commodity” demand is

The results obtained by Chou and Buongirno (1983) for the US imports of hardwood11

plywood support this finding, with little variation found in the own-price elasticities by countryof origin.

As discussed in Appendix A, there are also problems with the derivation of the elasticity12

calculations when the constant elasticity of substitution assumption is dropped.

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potentially over-restrictive. It would appear from the results presented here that what is being

suggested by Armington for dealing with this restriction ends up being self-defeating .11

This is undoubtably what prompted Hseu and Buongirno (1992), who also found that theirdata rejected the equality restriction on the elasticity of substitution, to pursue their research. As

discussed in some detail in Appendix A, however, their findings can only be considered empirical;that is, it is not supported by theoretical foundations. The reason for this is primarily the inability

to link Equations 3.5 and 3.6 without the constant elasticity of substitution assumption .12

With the clear understanding that the results of the analysis can only be consideredempirical, Tables 3.9 and 3.10 show selected results from applying Hseu and Buongirno’s

methodology to the data used in this study. Noting the improved correlation with the directestimates for the own-price elasticities offered earlier, the case for further research on dealing with

Armington’s restrictive assumption is clear.

Table 3.9 Calculated Own- and Cross-price Elasticities of Demand for the JapaneseImports of Wood Products by Type.

Softwood Hardwood Softwood Hardwood Veneer Plywood Fibreboard ParticleLogs Logs Lumber Lumber Sheets Board

SoftwoodLogs

-0.109* 0.067* 0.026* 0.008* 0.001* 0.006* 0.000* 0.000*

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HardwoodLogs

0.043* 0.016* 0.005* 0.001* 0.004* 0.000* 0.000*-0.068*

SoftwoodLumber

0.169 0.165 0.019 0.003 0.015 0.001 0.001-0.371

HardwoodLumber

0.332 0.323 0.124 0.005 0.030 0.001 0.001-0.815

VeneerSheets

0.488 0.475 0.183 0.054 0.044 0.002 0.002-1.244

Plywood 1.097* 1.066* 0.411* 0.121* 0.017* 0.004* 0.004*-2.715*

Fibreboard 2.585 2.512 0.968 0.285 0.040 0.232 0.009-6.620

ParticleBoard

1.051 1.021 0.393 0.116 0.016 0.094 0.004 -2.690

* Sigma i used in the calculation is insignificant at 90% confidence.

Table 3.10 Calculated Own-price Elasticities Of Selected Wood Product Imports byJapan Not Shown in Table 3.9.

Canadian SW Logs Former USSR SW Lumber US Douglas-fir Lumber-2.079 0.039 -1.079

US SW Logs “Other” SW Lumber US Red Cedar Lumber-0.304 -0.936 -0.269

NZ Logs Can. Sitka Spruce Lumber US “Planed” Lumber-2.698 -1.328 -6.512

Former USSR SW Logs Can. Y/W Cedar Lumber US “Other” Lumber0.120 * -0.245 -1.885

“Other” SW Logs Can. Hemlock Lumber US Sitka Spruce Logs-2.044 -0.226 * -0.173 *

South Sea HW Logs Can. Douglas-fir Lumber US Abies/Picea Logs-0.032 * -1.094 -0.109 *

“Other” HW Logs Can. “Planed” Lumber US W/Y Cedar Logs-1.812 -3.894 -0.551 *

Canadian SW Lumber Can. “Other” Lumber US Hemlock Logs-0.457 -1.480 -0.101

US SW Lumber US Sitka Spruce Lumber US Doug. Fir Logs-0.905 * -0.965 -0.246

NZ SW Lumber US Hemlock Lumber-2.347 -0.010 *

* Sigma I used in the calculation is insignificant at 90% confidence.

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3.4 Summary of Research Findings

The following offers a brief summary of the major research findings of the analysis of the

Japanese demand for imported wood products by type, country of origin and species. To facilitatethe understanding of these findings, Appendix B offers a graphical representation of all imports

categories for both volume and real unit values.

1. Japanese importers were paying less (real Yen per unit) for all wood product aggregatesin 1993 than they were in 1965. This has largely been because of strong increases in the

value of the Yen over this period relative to her trading partners. For example, in 1965,the aggregate real price of softwood lumber was roughly 55 thousand Yen per m , as3

compared to 40 thousand Yen per m in 1993. In terms of Canadian dollars, these two3

values are roughly $170 per m and $500 per m , respectively.3 3

2. Individual wood products, whether aggregated by product type, source, or species,

behave as distinct economic units. This was quantitatively extended to include qualityinsofar as trade detail was available for planed versus non-planed lumber. This was

qualitatively extended to quality through the knowledge and informal judgements aboutthe nature of wood products typical of individual sources.

3. In terms of product type, the own-price elasticity of demand was found to be the smallest

for softwood logs, largest for panel products, with lumber’s elasticity lying somewhere inbetween. Said another way, softwood logs displayed the fewest number of substitutes,

and panel products displayed the greatest number of substitutes.

4. In terms of the country of origin for softwood lumber, the own-price elasticity of demandwas found to be the smallest for Canada (not including the former Soviet Union, which

represented a small proportion of softwood lumber imports), largest for NZ/Chile, withsoftwood lumber from other sources lying somewhere in between.

5. In terms of the species of softwood lumber, S-P-F (planed lumber) was shown to have

by far the highest own-price elasticity, while red cedar from the US and yellow cedar fromCanada showed the smallest own-price elasticities.

6. In the case of softwood logs, the lowest own-price elasticity was for US logs, and the

highest was for NZ/Chile logs. The own-price elasticity for the former Soviet Union hasa positive sign, a non-intuitive result which may be explained by the presence of long-term

contracts. Compared to lumber, there was little difference by species shown for the own-price elasticities for US logs.

7. The cross-price elasticities, while generally found to be quite inelastic, mostly

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demonstrate a willingness to substitute one wood product for another to some degree(imperfect substitutes). This includes substituting one product type for another, such assoftwood lumber for softwood logs, logs from one location for logs from another, or one

species of logs for another. With many individual products comparisons, however, thereare cross-price elasticities which are not significantly different from zero. This reflects a

small elasticity of substitution, with the two products acting as compliments rather thansubstitutes. Finally, Japanese buyers appear to be more willing to substitute more

processed products in response to price increases for less processed products than theother way around. This may reflect changes in the product mix of domestically processed

logs.

8. Increases in the price of Japan’s domestic logs cause the Japanese to substituteimported wood products. Given the significance of the Japanese domestic log supply

over the course of the study period, symmetry would suggest that increases in the pricesof imported wood products lead to significant substitution with domestic logs.

9. In spite of the increasing purchasing power of the Yen over the period covered by this

study, it was determined that Japanese buyers have remained price sensitive, yet havebeen willing to pay considerable price premiums for certain products.

10. There was no evidence of structural change in the Japanese market for aggregated wood

imports. This shows that the substitutions of one product for anther (such as lumber forlogs) has been gradual over the 1965 to 1993 study period.

11. In Japanese markets, iron/steel and wood inputs appear to be complimentary, possibly

due to the importance of both non-wood housing starts and non-residential construction.

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4.0 Contributions, Limitations and Implications for Further Research

By investigating the Japanese demand for wood imports disaggregated by product, regionand species, this research has shown that wood inputs are imperfect substitutes in production.

This important finding suggests that hiding wood characteristics through data aggregationpotentially obscures important dimensions of both forest product trade and forest policy.

The primary contribution of this study is to offer some of the needed background

information to develop a more detailed understanding of international wood product trade. To date,there have been very few studies which have investigated the factor demand for wood beyond very

broad product categories, such as “softwood logs”, or “softwood lumber”. It is hoped that this studyhas succeeded in demonstrating the need to move beyond such limiting product aggregations.

As a background study, no hard conclusions nor recommendations can be made. This

task is left for future extensions and additions to the present research. However, there are anumber of implications of this study for the BC forest industry which can be discussed, particularly

those which relate to the marketing of BC solid wood products. This discussion is offered below.

4.1 Implications of the Research for BC Wood Product MarketingAn obvious application of the results of this study is in BC's choice of markets. While BC

has been a significant source of softwood lumber for the Japanese market over the entire periodof this study, a little over a decade ago Canadian softwood lumber exports to Japan as a percent

of all markets was only 8% by value, or less than 4% by volume (Canadian Forestry Service, 1984).At this time, lumber produced from old growth coastal timber largely found its way to the mix of

dimension lumber destined for the US housing market. Further, high grades of lumber from theBC Interior were not commonly separated from the S-P-F mix destined for this same US market.

This US market has remained a "commodity" market where it is difficult to differentiate the productto price advantage. It is for this reason that the coastal forest industry, fuelled by the recession

of the early 1980s and falling timber supplies, realized the need to diversify its customer base. Thisrealization materialized in the BC Interior industry shortly thereafter. Over the past decade, the

forest industry has indeed become more market oriented. Scarcity induced price premiums forcertain grades or attributes of lumber have led to better log sorting, cutting to customer demanded

sizes, the adoption of kiln drying and international quality certification, etc. Recognizing thedifficulties in employing a diversification strategy in the US, Canada (primarily BC) increased its

share of softwood lumber exports to Japan to 21% by value in 1992 (Natural Resources Canada,1993), as well as increasing exports to Europe.

The overall market mix in 1992 is shown in Table 4.1. The difference in the nature of the

lumber product shipped to the US versus Japan is supported by examining the average price per

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Table 4.1 Destination of Canadian Softwood Lumber and Log Exports, 1992. Softwood Lumber

000 $ m $ per m3 3

US 4,195,276 65.76% 30,848,622 78.42% 136

Africa 15,846 0.25% 89,766 0.23% 177

Algeria 11,942 0.19% 51,975 0.13% 230

Europe 629,209 9.86% 2,549,763 6.48% 247

Belgium 69,548 1.09% 206,774 0.53% 336

France 26,517 0.42% 78,263 0.20% 339

Germany 67,736 1.06% 114,996 0.29% 589

Italy 77,537 1.22% 146,458 0.37% 529

UK 349,393 5.48% 1,847,858 4.70% 189

Asia 1,464,601 22.96% 5,598,317 14.23% 262

Japan 1,325,474 20.78% 4,732,838 12.03% 280

Australia 62,164 0.97% 201,218 0.51% 309

Other 12,533 0.20% 51,446 0.13% 244

World 6,379,629 100.00% 39,339,132 100.00% 162

Softwood Logs

US 20,951 14.04% 151,000 13.64% 139

Asia 128,082 85.83% 956,000 86.36% 134

Japan 124,148 83.19% 915,000 82.66% 136

Other 203 0.14% 0 0.00%

World 149,236 186.10% 1,107,000 100.00% 135

Source: Natural Resources Canada, “Selected Forestry Statistics”, 1993.

cubic metre, with shipments to Japan being worth more than twice per cubic metre than those tothe US. While this is not shown to be true in the case of softwood logs, any comparison here is

likely to be obscured by Canada's log export restrictions.

Note that Canada exported only 22% of its lumber, by volume, to non-US destinations.Of this 22%, it can also be seen that roughly 60% of these exports went to Japan, with the balance

destined mostly to Europe. It is this emphasis on the Japanese market that this section will nowaddress.

First of all, it should be made clear that Japan is not Canada’s only potential market for

differentiated lumber products. As shown in Table 7.1, exports to most off-shore destinations in1992 were at higher average prices than for sales to Japan (in the case of Germany, in fact, more

than twice as high as the average export price to Japan). Further, growing Asian economies hold

The Canadian-Japanese exchange rate is not the only rate BC exporters should be worried about. It has13

been estimated that a 1 cent increase in the Canadian dollar relative to the US dollar, maintained for one year,translates into a loss in revenues to the Canadian forest industry of $450 million (Price Waterhouse, 1995).

There is some doubt, however, as to Japan’s ability to harvest significant quantities of14

appearance grade timber, at least in the short- to medium-run. As there has been little financial

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promise for adding to the list of potential markets for BC's wood products. Given the advantages

of trading in non-commodity markets, the advantages of further diversification seems justified.When one introduces the uncertainty of future prices in Japan, to which the discussion now turns,

the potential advantages become even more clear.

From a BC marketing point of view, perhaps the single most important element in tryingto predict what the future holds in terms of wood product prices sold to Japan (vis-a-vis premiums

over the other BC markets) is the Japanese/Canadian exchange rate . As has been noted, Japan13

has actually been paying less each year, on average, for even high quality products such as

softwood logs from the PNW and softwood lumber from the BC Coast. The question that cannothelp but come to mind is whether they would be willing to pay more? What is likely to happen if

the Japanese Yen stabilizes or weakens in the future?

There are three possible scenarios which could unfold given this eventuality. The first isthat Japan will start paying higher real prices for at least the higher quality commodities which are,

after all, becoming more and more scarce, technological advances notwithstanding. From theCanadian or American point of view, there would be little change in the Canadian or US dollar price

trends that have been seen all along (down for low quality, up for high quality).

The second possibility is that Japan will resist higher Yen prices by substituting othercommodities. Unless the Yen does not depreciate equally over all currencies, this could mean

substituting appearance quality wood with structural quality wood and/or non-wood substitutes. Aswas suggested in the previous chapter, this would also include continued substitution of lumber and

panel products against rising log prices. The growing acceptance of platform-frame constructionwould support this possibility.

The third possibility is that Japan reverses its growing dependence on wood imports, and

invests in its domestic forest resource. In fact, it has been proposed in this study that the onlyreason that Japan imports as much wood as it does is because the vast majority of its domestic

supply lies outside the extensive margin. But this tight extensive margin is a direct result of "cheapimports" (in Yen terms), with which domestic sources have difficulty in competing. Remembering

the resource description offered in Chapter 3, including the extensive post war plantings whichwould become merchantable in light of rising prices, it is possible that BC's biggest futurecompetitor for the Japanese market will be Japan itself . This observation should, however, be14

incentive to do so, it has been suggested that Japan’s forest plantations have not been managed tomaximize value (personal communication, John Powles, Director for Asia, Council of ForestIndustry).

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tempered with Japan’s growing non-timber valuation of its forest resource.

The results of the present study suggest that all three possibilities could come into play.

Given the very small own-price elasticities shown for many of the wood products imported byJapan, the scenario of higher real Yen prices is certainly possible for these wood products. The

second and third possibility are best supported when taken together. The present study suggeststhat price rises for those wood products with high own-price elasticities lead to substitution with

domestically produced lumber and panel products (from imported and domestic log supplies).Given that all three possibilities are supported, depending on the wood product under

consideration, this suggests that the existence of a price premium for some wood products overothers is likely to persist.

However, it must be cautioned that the elasticity values offered in this study were

estimated over a fairly narrow range of real Yen prices, with an overall down trend. Is the incidenceof low own-price elasticities for selected wood products likely to hold at higher real prices than

Japan has historically paid? It is possible that the only reason the PNW and BC have enjoyed pricepremiums for high grade logs and lumber is because of the strength of the Japanese Yen. In spite

of the fact that BC has sold similar products for even higher prices to European buyers (Table 7.1),there is some validity to the argument that the Japanese have driven up the world price as a direct

result of their strong currency, and would drive down this world price in the advent of a falling Yen.Even the preliminary evidence offered in this study, however, casts considerable doubt on this

hypothesis. It is more likely that Japan has made every effort to pay as little as necessary tosecure these fibre supplies. This was confirmed by the range of own-price elasticities presented

in this study. Had Japan been willing to "pay anything" as a result of its strong purchasing power(in the income sense, leading to "cheap" imports), own-price elasticities would have all been low,

regardless of species or origin. To the contrary, wood products such as planed lumber from theUS and Canada, and logs from NZ/Chile display highly elastic demands. If the price goes up even

a little (due to a falling Yen) the quantity demanded goes down considerably. In short, Japan hasbeen shown to be price conscious in spite of its “wealth”.

4.2 Implications of the Research for BC Forest PolicyWhen describing the motivation for this research in the introductory section, it was pointed

out that over the next couple of decades, BC is going to witness a significant reduction in thevolume of available timber. Given the selected forest rotations for BC’s second growth stands and

the existing silvicultural efforts, it was also pointed out that the quality of timber is also going to be

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lower.

These facts contribute to the market implications discussed in Section 7.1.2 insofar as

they describe the nature of the future product. Given that the BC Crown controls the vast majorityof the forest land base, it is primarily forest policy, not industry market strategies, that will impact

on the future ability to adopt a market orientation.

It was argued in the previous section that there is no reason to expect that the marketpremium for certain wood products will disappear. While there may be no way to predict what

attributes of the wood in the future will command such price premiums, one fact does remain: if thelevel of silviculture and/or length of forest rotations does not change from present practices, there

will be no old growth quality timber available at some point in the future. In addition to this study’simplications for a more diversified BC forest product market, then, the related implication is for a

continued diversity in the product itself. Even if there is not a premium market for productsproduced from clear, slowly grown, large timber in the long-run, this timber can always be used for

alternative purposes (including the potential of the forests for the production of non-timber values).Without provision for these products, however, the option will be lost.

While there are a number of government initiatives which could help facilitate the

preservation of future product diversity, discussion of such initiatives is clearly beyond the scopeof this study. There is a need for considerably more research in this area, which will be briefly

summarized following a discussion of the limitations of the present study.

4.3 Limitations

The most obvious limitation comes from the quantification of the degree and nature ofimport substitution as a result of a price increase in a specific product. Due to reasons of

multicolliniar data, determining such cross-price effects requires a unique methodology, one whichArmington (1969) provided and which has largely been accepted in the literature. However, it has

been shown here that this methodology is not without its own limitations, centred around overlyrestrictive assumptions, and that these translate directly into limitations for the present study. While

Hseu and Buongiorno (1993) attempted to deal with the problem of the restrictive assumptionsused by Armington, it has been shown that the results should only be considered empirical.

The second limitation of this study is the lack of adequate secondary data on the quality

of wood products traded in the Pacific Rim market. This fact limited quality aspects of thediscussion to planed versus non-planed lumber, with further comparisons by species or source

being largely a matter of judgment.

Limitations resulting from the lack of data can be broken down into two components: thetreatment of wood input supply, and the use of a single output production function.

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In the estimation of the Japanese wood factor demands, it was assumed that the market

supply was completely elastic, with Japanese buyers behaving as a “price takers”. In other words,Japan cannot affect the price of its wood purchases by varying the amount purchased. The “price

taker” assumption was justified in this study as it was felt that there was little evidence in theliterature to support the hypothesis that Japanese buyers have monopsony power in their wood

purchases, especially for lumber. However, this may be more problematic when dealing withgreater product detail.

Unfortunately, potential limitations created by the supply assumption can not be

addressed without data which allows for the estimation of supply functions by area, by product, andby species.

The second methodological limitation of this study involves the underlying production

function from which the derived demand equations for the factor demands were obtained. It wasproposed that the Japanese demand for wood products is derived from the per capita GNP in

Japan, regardless of the differing species and implied quality. This assumption was supported bythe recognition that Japanese housing construction, being the largest single end use for wood

imports, requires a range of qualities. Appearance grades are required for posts and beams,panelling, and so on; structural grades are required for the non-visible house components of post

and beam construction, and for a growing percentage of platform frame and prefabricated housingconstruction; and “utility” grades are required for sub-flooring, filler for laminated posts, concrete

moulds, and so on. It is possible, however, that this single output production function is overlysimplistic to adequately deal with quality issues, particularly when quantifying substitutions (cross-

price elasticities). For example, the buyer of structural or utility grades, which are “capital” or“producer” goods, will likely treat the demand for fibre in the true “derived” sense. That is, if the

sale price of a house goes up, all else being equal, the house builder would be willing to pay thatmuch more for the inputs. Appearance grades, however, may more closely resemble “consumer”

goods, insofar as consumer income, tastes, education, tradition, etc., are all capable of shifting thequantity demanded independent of price. The buyers of this fibre would be exhibiting direct

willingness to pay for specific characteristics.

It was shown in Section 2 that the growing percentage of platform-frame andprefabricated housing relies on construction grade imports, and could largely explain the demand

for Japan’s imports of S-P-F and other planed, dimension lumber. In the context of the presentstudy, it could be suggested that in response to higher softwood log prices, Japan has shown a

willingness to substitute one form of housing construction for another. The limitations of this study,however, do not allow this to be quantified. Aside from the requirement of more detailed trade

As a reminder, there exists a wide range of quality within both appearance and structural15

classifications of lumber.

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data , it must be recognized that all three construction types use both appearance and structural15

grades of lumber.

A further limitation to the production function employed in this study, is that wood inputswere expressed in their cubic metre equivalents, regardless of the product type. This fails to

recognize the range of costs associated with the Japanese processing of logs versus lumberversus further processed inputs. Although this treatment can be justified by using a general output

indicator such as GNP as opposed to housing starts, and by noting Japan’s preference for re-manufacturing even processed imports, added detail on the Japanese cost structure could prove

insightful.

The choice of Japan as the demand focus could be considered a further limitation to thisstudy. Although there were good reasons for making this choice, as discussed in the introductory

section, it may limit the overall applicability of the results.

The first potential limitation is that real prices for almost all of Japan’s wood productimports dropped over the course of the study period, corresponding to a fairly consistent increase

in the purchasing power of the Japanese Yen. This suggests that it was not possible to definemore than a fairly narrow price range within the demand functions characterising Japanese wood

purchases. In other words, it is possible that the estimated demand elasticities would have beensignificantly different in the absence of a strong Yen.

A second, and related limitation, is that in light of Japan’s growing purchasing power, this

country may not be representative of other markets. Further, given that Japan is rather unique inits post and beam construction preferences, the nature of the demand for appearance grade wood

products outside of this country has not been identified.

4.4 Implications for Further Research

Given what has been learned about the negative effect of Armington’s neededassumptions for his two-stage approach to product demand within a market, there is a strong need

to continue to challenge its application. This is particularly important in light of the wide acceptanceof his approach, and the potentially misleading published results. The difficulty in dealing with

multicolliniar data problems has more than likely contributed to the lack of research dealing withheterogeneous product trade to be found in the literature. This is obviously not a trivial problem,

and its solution is well beyond the scope of the present research. Yet the importance of developingmethodologies that better address the unique nature of products must be stressed.

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In addition to the methodological problems associated with modelling heterogenousproducts, it must be pointed out that the underlying limitation discussed in the previous section,

being the lack of disaggregated wood product trade data, is likely to limit potential extensions ofthis study. As a qualifying recommendation for further research, then, it is suggested that the place

to start is in overcoming these data obstacles. It is hoped that a continued recognition of theimportance of these data will expose primary sources and/or the future availability of better

secondary sources.

As stated, most of the limitations of this study could be addressed in the absence of thesedata restrictions. Given the noted limitation of not recognizing the different demand characteristics

of structural lumber, for example, as compared to appearance grade lumber, more detailed datawould allow for a more sophisticated, multiple output production function. Due to its importance,

this point deserves additional consideration in the context of its implications for further research.

There exists a considerable range in prices within the definition of “appearance” or“structural” lumber, or even within detailed grade classifications. In other words, the necessity to

describe “quality” as planed versus non-planed lumber in this study, for example, can bemisleading. It must be recognized that planed and non-planed lumber alike can be of high or low

quality, and that the implications for BC’s marketing strategy must take these quality ranges intoaccount. It is possible, for example, that the higher quality S-P-F lumber from the BC Interior is

demanded for post and beam construction in Japan, while the lower quality green squares fromthe BC Coast are not.

Aside from the quality of the resource, future studies should also include attention to the

quality of the product. By this it is meant that there has been a growth in the production of, and thedemand for, further processed products, such as panels and engineered products. While the

present study has included an analysis of veneer and panel products, data were not available todocument the demand for further value-added products such as engineered wood products, wood

“systems”, and other further manufactured products such as door and window frames. In fact, itis also an important implication for further research that the present study was not able to

differentiate between, for example, S-P-F lumber from the BC interior cut to metric sizes, comparedto S-P-F lumber from the US which, if destined for the Japanese market, likely requires a higher

degree of remanufacture. In short, “value-added” may evolve in small, rather than dramatic, steps(Cohen, 1992).

More generally, as the present study has focussed on the demand for wood products by

category, species and source for a single buyer, a natural extension of this research would be tobroaden the level of detail to include product grade within a species, and to investigate other

international demanders.

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It is further recommended that future research include an analysis of the major wood

producing countries' supply functions with as much attention to product detail as possible. Asidefrom improving extensions of the present analysis as noted, this would allow for a better

understanding of future trade flow scenarios, and offer price forecasting abilities.

Finally, as this study has utilized a static analysis, estimating short-run (one-year) demandresponses, it would be desirable to utilize a dynamic approach to obtain longer-run demand

elasticities.

In summary, this study has shown that there has been a wide range in the strength of theJapanese demand for various wood products. To the extent possible, it was shown that the

Japanese have been willing to pay for quality, and that this it is not likely to change in the future.From the demand side, this research needs to be extended to further quantify this demand for

quality, and to extend the analysis beyond Japan. This includes, but is not limited to, developingbetter methodologies for investigating cross-price effects. Even more importantly, this research

should be complemented with research on the supply of wood products by category, species, andby grade, concentrating initially on BC. Only at this point will it be possible to utilize more powerful

tools, such as spatial trade modelling, as an aid in price forecasting, identifying future marketpotentials, and as a tool in forest policy.

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BIBLIOGRAPHY

Adams, D.M. 1977. Effects of National Forest Timber Harvest on Softwood Stumpage,Lumber, and Plywood Markets: An Econometric Analysis. Oregon State University,School of Forestry, Research Bulletin 15, Corvallis. 50 pp.

Adams, D.M., R. Boyd and J. Angle. 1992. Evaluating the Stability of Softwood LumberDemand Elasticity by End-Use Sector: A Stochastic Parameter Approach. ForestScience 38(4): 825-841.

Allen, R.D.G. 1953. Mathematical Analysis for Economists. Macmillan and Co., Limited(London, England). 548 pp.

Alston, J.M., C.A. Carter, R. Green and D. Pick. 1990. Whither Armington Trade Models. American Agricultural Economics Association, May: 455-467.

Armington, P.S. 1969. A Theory of Demand for Products Distinguished by Place ofProduction. International Monetary Fund Staff Paper 16: 159-177.

Babula, R. 1978. An Armington Model of U.S. Cotton Exports. Journal of AgriculturalEconomics Research 39: 12-22.

Brooks, D. 1993. Market Conditions for Tropical Timber Products, appendix in The EconomicLinkages Between the International Trade in Tropical Timber and the SustainableManagement of Tropical Forests, Barbier, et al., London Environmental EconomicsCentre, London, U.K.

Buongiorno, J. 1979. Income and Price Elasticities of Demand for Sawn Wood and Wood-based Panels: a Pooled Cross-section and Time-series Analysis. Canadian Journal ofForest Research 9(2): 141-147.

Buongiorno, J., J.P. Chavas and J. Uusivuori. 1988. Exchange Rates, Canadian LumberImports, and United States Prices: A Time-Series Analysis. Canadian Journal of ForestResources 18: 1587-1594.

Canadian Global Almanac. 1995. MacMillan Canada, Toronto, Ontario. 792 pp.

Cardellichio, P.A., C.S. Binkley and V.K. Zausaev. 1989. Potential Expansion of Soviet FarEast Log Exports to the Pacific Rim. Working Paper 21, Center for International Tradein Forest Products, University of Washington, Seattle. 23 pp.

Chen, N.J., G.C.W. Ames and A.L. Hammett. 1988. Implications of a Tariff on ImportedCanadian Softwood Lumber. Canadian Journal of Agricultural Economics 36: 69-81.

Chou, J.J. and J. Buongiorno. 1983. United States Demand for Hardwood Plywood Imports byCountry of Origin. Forest Science 29(2): 225-237.

Cohen, David H. 1992. Adding Value Incrementally: A Strategy to Enhance Solid WoodExports to Japan. Forest Products Journal 42(2): 40-44.

Constantino, Luis F. 1986. Modelling Wood Quality, Productivity, Demands and Supplies in

-59-

the Sawmilling Industry: British Columbia Coast and the Pacific Northwest Westside. Unpublished Ph.D. Thesis, Department of Forest Resources Management, University ofBritish Columbia. 289 pp.

Constantino, Luis F. 1988. Analysis of the International and Domestic Demand for IndonesianWood Products. Report to the Food and Agriculture Organization (mimeo.), Dept. ofRural Economy, University of Alberta, Edmonton.

Constantino, Luis F. and David Haley. 1988. Wood Quality and the Input and Output Choicesof Sawmilling Producers for the British Columbia Coast and the United States PacificNorthwest, West Side. Canadian Journal of Forest Research 18(2): 202-208.

FAO Yearbook. Various Issues. FAO Forestry Series No. 27. Food and AgricultureOrganization of the United Nations, Rome, Italy.

Flora, Donald F. 1986. An Equilibrium Model of Pacific Rim Trade in Small Softwood Logs. Canadian Journal of Forest Research 16: 1000-1006.

Flora, Donald F. 1991. Trade Issues in the Northern Pacific Rim Countries. Presented at theSociety of American Foresters: Economics, Policy and Law Working Group, SanFrancisco, California. 7 pp.

Flora, Donald F. 1992. A Mesoeconomic Perspective on Wood Quality. Paper presented at“Pruning Conifers in Northwestern North America: Opportunities, Techniques, Impacts”,Olympia, Washington. 7 pp.

Flora, Donald F. 1993. Forest Sustainability and the Pacific Rim. Presented to the SustainableDevelopment in the Pacific Rim International Exchange Conference, Lewis-Clark StateCollege. 6 pp.

Flora, Donald F., Andrea L. Anderson and Wendy J. McGinnis. 1991-a. Pacific Rim LogTrade: Determinants and Trends. USDA Research Paper PNW-RP-432, ForestService, Pacific Northwest Research Station, Seattle, Washington. 72 pp.

Flora, Donald F., Andrea L. Anderson and Wendy J. McGinnis. 1991-b. Future Pacific RimFlows and Prices of Softwood Logs, Differentiated by Grade. USDA Research PaperPNW-RP-433, Forest Service, Pacific Northwest Research Station, Seattle, Washington. 22 pp.

Flora, Donald F. and Wendy J. McGinnis. 1989. Alaska Midgrade Logs: Supply and OffshoreDemand. Research Paper PNW-RP-411, Forest Service, Pacific Northwest ResearchStation, Seattle, Washington. 13 pp.

Flora, Donald F. and Christine Lane. 1994. Timber Trade Forecasting and Policy Analysis withNon-Optimizing Equilibrium Models. Presented at conference, “Current Issues inInternational Trade”, Oregon State University, Corvallis, Oregon. 6 pp.

Flora, Donald F., Christine Lane and Richard Haynes. 1993. Wood Products Trade, ForestReplanning and Forest Habitat Conservation in the U.S. Northwest. Review Draft, USDAForest Service, Pacific Northwest Research Station, Seattle and Portland. 8 pp.

-60-

Flora, Donald F., Wendy J. McGinnis and Christine L. Lane. 1993. The Export Premium: WhySome Logs are Worth More Abroad. USDA Research Paper PNW-RP-462, ForestService, Pacific Northwest Research Station, Seattle, Washington. 18 pp.

Flora, Donald F., Ulla Woller and Michael Neergaard. 1990. Tradeoffs and Interdependencein the Alaska Cant and Log Markets. Research Paper PNW-RP-422, Forest Service,Pacific Northwest Research Station, Seattle, Washington. 11 pp.

Gaston, C.W., D. Cohen and R. Prins. 1994. Environmentalism as a Driver for Wood ProductQuality. Working Paper 204, Forest Economics and Policy Analysis Research Unit,University of British Columbia, Vancouver. 22 pp.

Gellner, B., L. Constantino and M. Percy. 1991. Dynamic Adjustments in the United Statesand Canadian Construction Industries. Canadian Journal of Forest Research 21: 326-332.

Grennes, T., P.R. Johnson and M. Thursby. 1978. The Ecomics of World Trade. PraegerPublishers (New York). 129 pp.

Haley, D. and M.K. Luckert. 1990. Forest Tenures in Canada: A Framework for PolicyAnalysis. Forestry Canada Information Report E-X-43, Ottawa, Ontario

Haley, D. and M.K. Luckert. 1995. Tenures as Economic Instruments for Achieving Objectivesof Forest Policy in British Columbia. Executive Workshop on Economic Instruments forProtection of Forest Resources, Faculty of Law, University of Victoria, British Columbia. 36 pp.

Haynes, Richard W. and Roger D. Fight. 1992. Price Projections for Selected Grades ofDouglas-Fir, Coastal Hem-Fir, Inland Hem-Fir, and Ponderosa Pine Lumber. ResearchPaper PNW-RP-447, Forest Service, Pacific Northwest Research Station, Portland,Oregon. 20 pp.

Hseu, J. and J. Buongiorno. 1992. Price Elasticities of Substitution Between Species in theDemand for U.S. Softwood Lumber Imports from Canada. Canadian Journal of ForestResearch 23: 591-597.

Iwai, Yohsiya. 1986. Timber Producing Districts in Japan and the demand for Housing Timber. Paper in IUFRO, Division 4, The Current State Of Japanese Forestry (V), The JapaneseForest Economic Society, Tokyo: 1-11.

Jacques, R., M. Martin and R. Samson. 1982. Analysis of the Demand for Canadian SoftwoodLumber. Canadian Forest Service, Environment Canada, Ottawa. 11 pp.

Japan Tariff Association. Various Issues. Imports of Commodities by Source. Tokyo, Japan.

Japan Wood Products Information and Research Centre. Various Issues. Wood Supply andDemand Information Service, Tokyo, Japan and Seattle, Washington.

Johnston, J. 1984. Econometric Methods. Third Edition, McGraw-Hill Publishing (New York). 568 pp.

-61-

Judge, G.G., R.C. Hill, W.E. Griffiths, H. Lütkepohl and T. Lee. 1988. Introduction to theTheory and Practice of Econometrics. Second Edition, John Wiley & Sons (New York). 1024 pp.

Kalt, J.P. 1994. Report for the First Administrative Review in Certain Softwood LumberProducts from Canada. Prepared for the International Trade Administration, UnitedStates Department of Commerce. 291 pp.

Kato, Takashi. 1982. Comparison of Softwood Lumber Manufacturing and Selling CostsBetween the Pacific Coast of North America and Japan. Paper in IUFRO, Division 4,The Current State Of Japanese Forestry (II), The Japanese Forest Economic Society,Tokyo: 30-39.

Kennedy, P. 1992. A Guide to Econometrics. Third Printing, The MIT Press (Cambridge). 410 pp.

Lewandrowski, J. 1989. A Regional Model of the U.S. Softwood Lumber Industry: Includingthe Role of Price Expectations, the Role of Finished Product Inventory, and the Impactsof Trade Restrictions on Canadian Softwood Products. Ph.D. Thesis, North CarolinaState University. 220 pp.

McKillop, W.L.M, T.W. Stuart, and P.J. Geissler. 1980. Competition Between Wood Productsand Substitute Structural Products: An Econometric Analysis. Forest Science 26(1):134 - 148.

Mochida, Haruyuki. 1989. Problems of Cost Reduction in Japanese Forestry. Paper inIUFRO, Division 4, The Current State Of Japanese Forestry (VI), The Japanese ForestEconomic Society, Tokyo: 39-49.

Moffett, Jeffrey L. 1993. A Comparison of Product Diffusion and Distributed Lag Models forEstimating Wood/Non-wood Substitution in the US Window Market. Working Paper 42,Center for International Trade in Forest Products, University of Washington, Seattle. 29pp.

Moffett, Jeffrey L. And Thomas R. Waggener. 1992. The Development of the JapaneseWood Trade: Historical Perspective and Current Trends. Working Paper 38, Center forInternational Trade in Forest Products, University of Washington, Seattle. 125 pp.

Mori, Yoshiaki. 1992. Timber Market in Japan: An Econometric Analysis. Memoirs of theCollege of Agriculture 139: 179-191, Kyoto University, Japan.

Nicholson, W. 1989. Microeconomic Theory: Basic Principles and Extensions. Fourth Edition. The Dryden Press (Chicago). 793 pp.

Otsuka, Fumiko. 1992. Japanese Market fir Dimensional Lumber: a Gravity Model Approach. Unpublished M.Sc. Thesis, University of British Columbia, Vancouver. 92 pp.

Pearse, Peter H. 1993. Determination of Harvest Rates in the Transition to Sustained Yield. Mimeo., Department of Forest Resources Management, University of British Columbia,Vancouver. 19 pp. plus appendix.

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Penson, J. And R. Babula. 1988. Japanese Monetary Policies and U.S. Agricultural Exports. Journal of Agricultural Economics Research 40: 11-18.

Perez-Garcia, J.M. 1993. Global Forestry Impacts of Reducing Softwood Supplies from NorthAmerica. CINTRAFOR Working Paper, #43, University of Washington, Seattle,Washington. 35 pp.

Pesonen, Miikka. 1993. Japanese Market for Scandinavian Wood Products. Department ofForest Economics Reports, No. 1, University of Helsinki. 116 pp. plus appendix.

Phelps, Susan E. 1993. A Summary of Elasticities of Demand and Supply for North AmericanSoftwood Lumber. Research Note, Forestry Canada, Economic Studies Division, Policyand Economics Directorate, Ottawa. 13 pp.

Price Waterhouse. 1995. Analysis of Recent British Columbia Government Forest Policy andLand Use Initiatives. Prepared for the Forest Alliance of British Columbia, Vancouver. 66 pp. plus appendix.

Prins, Robert G. 1993a. The Economic and Environmental Impacts of Reduced TimberHarvests and Increased Softwood Lumber Prices. Working Paper, Forestry Canada,Economic Studies Division, Policy and Economics Directorate, Ottawa. 39 pp.

Prins, Robert G. 1993b. Substitution Between Tropical and Temperate Wood Products: ALiterature Review. Research Note, Forestry Canada, Economic Studies Division, Policyand Economics Directorate, Ottawa. 12 pp.

Random Lengths. Various Issues. Yearbook, Random Lengths Publications Inc. Eugene,Oregon.

Robertson, Guy and Thomas R. Waggener. 1995. The Japanese Market for SoftwoodSawnwood and Changing Pacific Rim Wood Supply Conditions: Implications for USPacific Northwest Producers. Working Paper 52, Center for International Trade inForest Products, University of Washington, Seattle.71 pp. plus appendix.

Robinson, V.L. 1974. An Econometric Model of Softwood Lumber and Stumpage Markets,1947-1967. Forest Science 20(2): 171-179.

Rockel, M L and J Buongiorno. 1982. Derived Demand for Wood and Other Inputs inResidential Construction: a Cost Function Approach. Forest Science 28(2): 207-219.

Savin, N.E. and K.J. White. 1977. The Durbin-Watson Test for Serial Correlation with ExtremeSample Sizes or Many Regressors. Econometrica 45: 1989-1996.

Sedjo, Roger A., A. Clark Wiseman, David J. Brooks and Kenneth S. Lyon. 1994. ChangingTimber Supply and the Japanese Market. Discussion Paper 94-25, Resources for theFuture, Washington, D.C. 31 pp.

Singh, B.K. and J.C. Nautiyal. 1986. An Econometric Analysis of Markets for CanadianLumber. Wood and Fiber Science 18(3): 382-396.

Smith, Ramsay. 1989. Use of Pacific Northwest Wood Products in Japan. Reprint Series 18,

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Center for International Trade in Forest Products, University of Washington, Seattle. 7pp.

Spelter, H. 1985. A Product Diffusion Approach to Modelling Softwood Lumber Demand. Forest Science 31(3): 685-700.

Spelter, H. 1992. Technology-driven Substitution in the Forest Sector - the Variable PriceElasticity Model Revisited. In Forest Sector Analysis - Proceedings of IUFROCentennial Conference, Berlin, Germany: 24 -29.

Sutton, W.J.R. 1994. The World's need for Wood. In Proceedings No. 7319, TheGlobalization of Wood Supply: Supply. Processes, Products and Markets, MadisonWisconsin: 21-29.

van Kooten, G.C. 1993. Land Resource Economics and Sustainable Development: EconomicPolicies and the Common Good. UBC Press (Vancouver). 450 pp.

Varian, H.R. 1984. Microeconomic Analysis. Second Edition, WW Norton & Company (NewYork). 348 pp.

Varian, H.R. 1993. Intermediate Microeconomics: A Modern Approach. Third Edition, WWNorton & Company (New York). 623 pp. plus appendix.

Vincent, Jeffrey R., David J. Brooks and Alamgir K. Gandapur. 1991. Substitution BetweenTropical and Temperate Sawlogs. Forest Science 37: 1484-1491.

Waggener, T.R., G.F. Schreuder, and H.M Hoganson. 1978. Elasticities of Demand for ForestProducts over Time. Office report on file at the Pacific Northwest Forest and RangeExperiment Station, Portland, Oregon. 112 pp.

Webb, A.J., E.E Figueroa, W.E. Wecker and A.J. McCalla. Impact of the Soviet GrainEmbargo; a Comparison of Models. Journal of Policy Modeling 11:361-89.

Youn, Y.C. and S.C. Yum. 1992. A Study on the Demand and Supply of Timber in SouthKorea. Paper presented at the Symposium on Forest Sector, Trade and EnvironmentalImpact Models: Theory and Applications, CINTRAFOR, Seattle, Washington.

Yu, Xiaoming and Yoshiaki Mori. 1990. Timber Demand in Japan. Paper in InternationalTrade in Forest Products Around the Pacific Rim, Y.C. Youn and G.F. Schreuder,editors, Institute of Forestry and Forest Products, Seoul National University: 206-216.

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APPENDIX A

Literature Review on Log and Lumber Substitutions:Elasticity Estimates and Methodologies

Estimates of the Price Elasticity of Demand

There are a number of potential responses to a rise in the price of domestic lumber. These

responses can be placed in one or more of the following categories: 1) increased efficiency of wooduse and/or reduced consumption of finished products; 2) substitution by wood from another

location, different form (for example, lumber for logs) or different species; and 3) substitution ofnon-wood inputs for wood inputs.

Estimates of Wood for Wood SubstitutesThere has been a considerable amount of research which investigates demand elasticities

for timber products, primarily for US lumber. Tables A.1 through A.3 highlight some of this

research. The summary information is largely adapted from the review by Phelps (1993).

The most obvious consistency found in Table A.1, which presents own-price demandelasticity studies, is that softwood lumber demand is shown to be inelastic, with a range of -0.023

to -1.15, and an average of roughly -0.4. In other words, these studies suggest that a 10%increase in the domestic price of lumber will decrease the local quantity demanded by an average

of 4%. Not surprisingly, demand elasticities which are smaller in value are from studies whichestimate short-run demand responses. In the very short run substitutes do not, for all practical

purposes, exist.

Measurements of elasticities must also consider the specific years being investigated.Spelter's (1985) results illustrate this by showing that elasticities (in this case share elasticities)

have fallen over time. This trend, according to Spelter, may be attributable to improved technologyand utilization, both of which have helped to alleviate scarcity. One must also note that elasticity

estimates are affected by the price range over which they are measured. For example, elasticityestimates derived from data where prices tended to be low will likely be significantly different from

a comparable study over a different time period where prices tended to be high.

The range of elasticity estimates shown can also be partially explained by what is beingmeasured. For example, Adams, et al.'s (1992) results show that the demand for lumber used in

residential construction is less elastic than for non-residential construction, supporting the point thathome buyers are not greatly influenced by the price of an input which makes up a relatively small

portion of the total purchase price, as well as the fact that in non-residential construction more

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TABLE A.1 Own-price Elasticity of Demand for Softwood Lumber in N.A.

Elasticity Time Frame Author Comments

United States

-0.173 McKillop et al. (1980) US softwood lumber wholesale price1947-1974 index

-0.35 Waggener et al. US softwood lumber price1950-1974 (1978)

-0.38 Gellner et al. (1991) US softwood lumber price07/79-12/84

-0.075 Adams (1977) US softwood lumber price index,1947-1974 1 year lag

-0.285 1950 (Point) Spelter (1985) US softwood lumber price-0.162 1960 ( “ )-0.130 1970 ( “ )-0.111 1980 ( “ )

-0.88 1950-1954 Spelter (1985) US softwood lumber price-0.39 1970-1974

-0.91 Rockel and Buon- US Douglas-fir wholesale price index01/68-12/77 giorno (1982)

-0.88 1947-1967 Robinson (1974) Douglas-fir

-0.667 Lewandrowski � Southern pine-0.149 (1992) � Douglas-fir

01/77-12/87

-0.55 1950-1987 Adams et al. (1992) � Residential construction-1.15 � Non-residential construction

Canada

-0.29 01/71-02/82 Jacques et al. (1982) Domestic softwood lumber purchases

-0.023 Sharma (1986) Softwood lumber for residential1970-1982 construction

-0.05 01/71-02/92 Prins (1993) Total shipments of softwood lumberless exports

substitutes in the form of non-wood materials are available and acceptable. Lewandrowski's (1992)results show that elasticities can vary by species, here suggesting that southern pines (e.g., Pinustarda) have more substitutes (i.e., the quantity demanded is more price sensitive) than Douglas-fir.This is an important point, and will be returned to.

Table A.2 shows some estimates of cross-price elasticities of demand for softwood lumber

in different regions, in this case primarily the US demand for imports from Canada. The mostobvious point is that the demand response is now elastic (greater than 1), or at least more elastic

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TABLE A.2 Cross-price Elasticities of Demand for Similar Lumber in Different Regions

Elasticity Time Frame Author Comments

United States

1.283 Adams (1977) Imports from Canada; ratio of US to1947-1974 Canadian import prices.

0.81 Jacques, et al. (1982) Demand for Canadian shipments; US01/71-02/82 lumber price index.

1.48 01/74-01/86 Buongiorno et al. Demand for imports from Canada; prices(1988) of softwood lumber in the US.

0.56 1950-1982 Singh and Nautiyal Demand for Canadian lumber; US price(1986) index for all lumber.

-0.80 1963-85 Flora et al. (1991) � Off shore demand facing the US in

-1.95 � Off shore demand facing the US in1987; performance grade.

1987; construction grade.

-3.088 Chen et al. (1988) � Demand for Canadian softwood

2.27 � Price of US softwood lumber.

1965-1985 lumber; import price from BC.

4.39 1975-1985 Constantino (1988)Sawnwood

12.30Plywood

World imports of hardwood fromIndonesia; importing country's price ofhardwood.

Note: When interpreting the sign of the elasticity values, it must be noted which price is being considered.With Chen, et al.'s (1988) results, for example, a 10% decrease in the BC price of lumber willincrease US import demand by over 30%. Conversely, a 10% decrease in the US price of lumberwill decrease US import demand from Canada by over 22%.

than for own-price. This clearly shows, as would be expected, a willingness to substitute for a

similar commodity from another geographic area. One might expect these elasticity values to behigher than indicated. That they are not suggests that while the imports are good substitutes for

domestic production, they are far from being perfect substitutes. This may be partially due to thefact that aggregate imports in these studies are not equivalent to aggregate domestic production,

neither by species nor other characteristics.

Finally, Table A.3 shows some estimates of cross-price elasticities of demand for differenttypes of lumber. Although the estimates are mostly greater than uni t, the demand is generally less

elastic than for similar wood products in different regions. This suggests that consumers are lesswilling to substitute hardwoods for softwoods than Canadian S-P-F for US southern pine.

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TABLE A.3 Cross-price Elasticity of Demand for Different Lumber

Elasticity Time Frame Author Comments

1.30 Constantino (1988) World imports of hardwood fromSawnwood Indonesia relative to importing

0.75Plywood

1975-1985

country's price of softwood.

1.45 Brooks (1993) US imports of tropical lumber relative1971-1991 to US price of softwood lumber.

1.06 1970-1989 Youn and Yum World imports of hardwood logs from(1992) Korea relative to importing country's

price of softwood logs.

Estimates of Non-Wood for Wood SubstitutesAnother possible reaction to higher lumber prices is, of course, substitution for wood

products with non-wood commodities. For construction lumber, this includes steel, concrete,bricks, plastics, etc. Recent price increases in lumber have already initiated an extensive program

by the American Iron and Steel Institute to promote the replacement of wood structural and non-structural members in construction with steel members (Haws, 1994). Surveys undertaken in 1993

indicate that 45% of builders in California would consider switching to steel due to the high andunstable price of wood products.

There are a number of studies which have examined the cross-price demand elasticities

between wood and non-wood materials. A better understanding of the substitution impact isachieved when the extent to which non-wood materials substitute for wood is examined, and the

extent to which wood substitutes for non-wood materials. Table A.4 summarizes the results ofMcKillop, et al. (1980) for the US.

First, it should be noted that all of the own-price elasticities (the diagonal from top-left to

bottom-right) have the expected negative signs and are all less than 1, indicating inelasticdemands. Second, the table indicates that the price of lumber influences the quantity demanded

of non-wood materials. By contrast, however, the price of substitutes does not influence thequantity demanded of lumber to the same degree. For example, a 10% increase in the price of

steel will increase the demand for lumber by 3.7%. Conversely, a 10% increase in the price oflumber will increase the demand for steel by 7.9%.

Rockel and Buongiorno (1982) specifically examined the demand for wood products for

residential construction (as opposed to total US demand) (Table A.5). The non-wood substitutes

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TABLE A.4 Own-price and Cross-price Demand Elasticities for Construction Materials

Q Lumber Q Plywood Q Steel Q Aluminum Q Concrete

P Lumber 0.79 0.24 -0.54-0.17

P Plywood 0.14 -0.4 0.54-0.67

P Steel 0.37 0.74-0.93

P Aluminum 0.02 0.47 -0.83

P Concrete -0.51

Source: McKillop, et al. (1980)

TABLE A.5 Own-price and Cross-price Demand Elasticities for ConstructionMaterials

Q Lumber Q Plywood Q Non-Wood

P Lumber 0.05 0.12-0.91

P Plywood 0.09 0.12-0.95

P Non-Wood 0.09 0.05 -0.88

Source: Rockel and Buongiorno (1982)

included in the study were structural steel, cement, bricks, plumbing and heating fixtures, and

selected fabricated metal products. The extremely low cross-price elasticities indicated in the tableare the result of aggregating all these inputs into a single basket of goods.

In Table A.6, the result of time on elasticities (primarily technological change) is

demonstrated by Spelter for the US. As can be seen, both the own-price and the cross-priceelasticities fell (with the exception of concrete) from the 1950s to the 1980s.

Finally, Prins (1993) examined wood/non-wood substitution in Canada (Table A.7). Note

that while the results suggest that a 100% increase in the price of lumber will cause only a 5%reduction in the demand for lumber, it also creates a 51% increase in the demand for bricks, a 15%

increase in cement and a 32% increase in steel. This demonstrates the dominance of wood usein construction: 5% of all lumber used in construction is a significant volume of material relative to

32% of all steel used. Also, note that price increases in non-wood substitutes have a greaterimpact on the demand for wood than suggested by the previous studies.

TABLE A.6 Own-price and Cross-price Demand Elasticities for US SoftwoodLumber

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1950 1960 1970 1980

P Lumber -0.285 -0.162 -0.13 -0.111

P Plywood 0.109 0.04 0.009 0.004

P Steel 0.026 0.017 0.012 0.005

P Concrete 0.006 0.006 0.006 0.006

Source: Spelter (1985)

TABLE A.7 Own-price and Cross-price Demand Elasticities for SelectedCanadian Construction Materials

Q Lumber Q Brick Q Cement Q Steel

P Lumber 0.51 0.15 0.32-0.05

P Brick 0.49 0.73-0.3

P Cement 0.78 0.71 -0.5

P Steel 0.55 0.56 -2.09

P Gypsum -0.31

P Panels 0.09 0.08

Source: Prins (1993)

Demand Elasticity Estimation TechniquesFrom the outset, it should be emphasized that only a small number of the demand elasticity

studies listed in the previous tables made any attempt to disaggregate the data beyond softwoodlogs or lumber. As mentioned in the previous chapter, the likely reason for this is the lack of

published disaggregated data.

All of the studies reported to this point have involved econometric techniques in estimatingthe price elasticities of demand. While the estimation techniques employed were not unusual

(normally ordinary least squares, two or three stage least squares, non-linear least squares orgeneralized least squares), a few studies utilized an approach of interest to the present study.

Flora and his colleagues at the USDA Forest Service, Pacific Northwest Research Station

in Seattle have conducted North American wood product demand studies which have made directreference to quality or grade (Flora and Lane, 1994; Flora, et al., 1993; Flora, 1993; Flora, 1992;

Flora, et al., 1991-a; Flora, et al., 1991-b; Flora, 1991; Flora, et al., 1990; Flora and McGinnis,1989; Flora, 1986). In one of the studies (Flora, et al., 1991-b), the researchers developed export

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supply functions for Pacific Rim log suppliers (US, Canada, Chile, New Zealand and the Soviet

Union), and import demand functions for Pacific Rim buyers (Japan, Korea, China and Taiwan).These supply and demand functions were then summed across quantities to yield aggregate

demand and supply functions. To estimate trade flows pertinent to an individual region, thedemand or supply facing that region is developed by netting out all of the other regions' demand

and supply functions. The individual equations used by Flora tend to be very simple, with quantitydemanded typically a function of price, GDP and housing starts, and quantity supplied a function

of plantation area, timber harvest, and possibly a sawmilling cost index.

Flora's methodology suffers from three specific limitations. First, where price projectionsare made, projections of all variables except price and volume are done outside of the model (by

making assumptions relative to a present-day "base case"). This means either heavy reliance onother studies, use of other modelling techniques, or significant personal judgement.

The second limitation is Flora's method of dealing with disaggregated trade data. Notes

Flora, et al. (1991-b, page 6):Because log-trade data are rarely reported by grade, quality class, or economiccategory, it was necessary to judge the proportions and relative values. ...Futurevolume-share shifts among grades were assumed...

This, unfortunately, offers little guidance for dealing with such data over a wide range of

applications.

Finally, Flora's models are limited to a single grade at a time. This does not allow for themeasurement of cross-price elasticities of demand across grades or species. However, the own-

price elasticities which resulted do suggest that elasticities of demand are negatively correlated withquality (as quality increases, demand becomes more inelastic).

Flora (1991-b) categorized logs into one of four grades:

Select logs whose value derives from "appearance" grade lumber;

Performance Coast and Cascade Grade No. 2 sawlogs; second- and old-growth logs with scaling diameters between 12 and 24 inches;

Construction Coast Grade No. 3 sawlogs; second-growth logs with scalingdiameters between 6 and 12 inches;

Utility submerchantable in the export market.

Flora’s conclusions suggest that the performance grade will have rising real price growth through

the turn of the century, and that the construction grade will see declines due to internationalcompetition. As shown in Table A.2, the authors pegged the price elasticity of demand facing the

US in 1987 for the performance grade at -0.80 as compared to -1.95 for construction (the authordid not analyse the two extremes in grades, reasoning that selects will always be scarce and that

Sjt b1j � b2j Sdt � b3j Wjt

QA b1 � b2 PA � b3 PUS � b4 PJ � b5 HS � M ciPi

Unlike the other methodologies reported here, Haynes and Fight (1992) are using domestic market1

data (as opposed to export data). Given the noted premium for export markets (see Flora, et al., 1993), thiswill underestimate the price premium for higher grades.

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the utility grade is unimportant for the export market).

Haynes and Fight (1992), also working with the USDA Forest Service in the PNW,

conducted a study on projecting prices of selected grades of Douglas-fir, Coast Hem-fir, InlandHem-fir and ponderosa pine lumber. Working with historical volumes and prices from

representative invoices submitted to the Western Wood Products Association for the PNW region ,1

the authors estimated the relationships between the prices of the selected lumber grades and the

price of the dominant lumber grade for each species in the general form:(A.1)

where: S = regional lumber price for the j species and grade in year t;jtth

S = price of the dominant species and grade in year t, and;dt

W = the proportion of total lumber production in year t that comes from jjtth

species and grade.With the values of the b 's estimated, the authors predicted the price for each grade byij

independently projecting the price of the dominant grade (S ) and grade production proportions.dt

Their results supported the notion that increasing scarcity of high-grade material will result in higher

prices. However, given the confines of their analysis, projections out to the year 2040 showed thatthe relative price spread for each grade remains virtually unchanged. This is in contrast to

historical changes in price spreads over grades. As noted by Flora, for example, in Japan in 1978,Alaska Prime spruce cants were worth 3 times as much as US #3 hemlock logs; by 1992, the

multiple increased to 20.

Sedjo, et al. (1994) offer a study which specifically investigates cross-price elasticities ofwood inputs. Noting the effect of the price of US logs on the log import behaviour of Japan, the

authors reason that imports from any region will be a function of that region’s timber price to Japan,the price of Japanese domestic timber, the level of construction activity in Japan, the price of US

timber to Japan, and the price of timber to Japan from any other source that may substitute for theregion in question's timber. A multiple regression analysis was used, with the quantity of timber

demanded from region "A" as the dependent variable, and each of the above factors taken asindependent variables, over the period 1970-1991:

(A.2)

where: QA = quantity imported from region "A";PA = price of region A's timber in Japan;PUS = price of US logs to Japan;PJ = Japanese domestic price of logs;HS = number of Japanese new wooden housing starts;P = prices of timber to Japan from regions other that "A" or the US.i

EQA,PUS b3 (PUS/QA)

As will become apparent in the following review of Armington (1969) and applications by Chou and2

Buongiorno (1983) and Hseu and Buongiorno (1992), such multicollinearity is a major limitation of tradestudies which have many price regressors of “similar” products in the same equation.

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Interestingly, the results showed no significance for the domestic price in Japan ("sugi"

conifer logs), suggesting either that import decisions were made independently of domesticproduction (possibly suggesting different end uses), or that perhaps there was too little variation

in domestic production to estimate the effect. The price parameter on imports from Canada(Douglas-fir lumber) was also found to be insignificant, with the authors reasoning a high degree

of multicollinearity of Canadian lumber exports (roundwood equivalent) to Japan and US Douglas-fir logs exported to Japan . The other regions investigated, all of which were found significant,2

included the Philippines, Indonesia, New Guinea, and Malaysia, collectively called "tropical" (lauanveneer tropical logs); Russia (larch logs); and Chile/New Zealand, collectively called "radiata".

The elasticities of Japanese imports from these three regions/wood type with respect to the

independent variables were then calculated. Due to the objective of the study, the authors focusedon the cross-price elasticity of Japanese imports with respect to the price of US logs. This cross-

price elasticity of wood quantity from region "A" (QA) with respect to the US log price (PUS) is thepercentage change in Japanese imports from A for each unit percentage change in the US price,

given by:(A.3)

where: b = the regression coefficient of PUS in the previous equation;3

(PUS/QA) = value using the mean over the study period.

Using ordinary least squares, the recovered cross-price elasticities for Japanese importswith respect to the US log price were 0.58, 5.0, and 0.84 for tropical, radiata and Russia,

respectively.

Unfortunately, none of the methodologies reviewed to this point are totally adequate foraddressing the main objective of the present study, being to estimate the substitution possibilities

among a significant number of disaggregated wood inputs in the Japanese market. The problemwhich needs to be addressed is how to estimate own- and cross-price elasticities for a number of

potentially unique, yet similar, price series.

Armington (1969) offers a potential solution. Recognizing the heterogenous nature ofproducts, even when of a similar “kind”, Armington relaxes the assumption that a particular “good”

produced in a particular country is a perfect substitute for the “same” good produced in anothercountry (relaxing the assumption that the elasticity of substitution between, say, softwood lumber

from Canada and softwood lumber from New Zealand is infinate). This is accomplished byassuming that an importer performs a two-stage optimization process. In stage one, the importer

decides the total amount of the commodity “kind” to import from all sources (say, softwood lumber,

Xij Xij(D,P11,P12, ... ,P1m, P21,P22,P2m, ... , Pn1,Pn2, ...Pnm)

Xij Xij Xi,Pij

Pi1

,Pij

Pi2

, ... ,Pij

Pim

Xi Xi(D,P1,P2, ... ,Pn)

Note that this function is of the needed linear and homogenous form.3

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or even all wood products in aggregate). In the second stage, the importer determines the optimal

levels of “good” imports (say, softwood lumber from a number of different sources).

Armington makes four assumptions, “systematically simplifying the product demandfunctions to the point where they are relevant to the practical purposes of estimation and

forecasting” (Armington, 1969; page 160). The first is that importer preferences arehomogeneously separable. This assumption is necessary to incorporate two-stage optimization.

It is next assumed that market shares depend only on relative prices of the products in the market,not on the size of the market itself. In the absence of these assumptions, a country would havemn demand functions in the general form:

(A.4)

where: m = number of supplying countries (specific product);n = number of goods (groups of products);X = specific product demand;ij

D = income;P = specific product price.ij

With Armington’s first two assumptions, this is reduced to m+n demand functions:

(A.5)

where

(A.6)

and: X is any good, and X is any product.i ij

From Armington’s first two assumptions, Equation A.5 requires that a linear, homogeneous

quantity index function, Q, be utilized for each market, such that X = Q (X , X , ..., X ). The reasoni i1 i2 im

for this is that if imports of products of the same kind from different countries are considered to be

imperfect substitutes, the arithmetic sum of various imports would not be an appropriate index oftotal imports.

Recognizing that equation A.5 is still too complicated to be of practical use when more thana few countries are identified, Armington proposes two further simplifying assumptions. These are

that the elasticities of substitution are constant for each market, and that the elasticity ofsubstitution between any two products competing in a market is the same as that between any

other pair of products competing in the same market. These assumptions are equivalent tospecifying that the Q’s above are constant elasticity of substitution (CES) functions, having the

general form :3

[bi1Xi1'i

� bi2Xi2'i

� ... � bimXim'i]

1'i

Xij bij)i Xi

Pij

Pi

)i

Xij

Xi

bij)i

Pij

Pi

)i

dXi Xij

Xi

dXi � Xij

Pij

dPij � Xij

Pi

dPi

Xij

Xi

dXi )iXijPij1dPij � )iXijPi

1dP

dXij

Xij

XijXi

XiXij

dXi

Xi

)i

dPij

Pij

� )i

dPi

Pi

dXij

Xij

dXi

Xi

)i

dPij

Pij

dPi

Pi

Xi � Qi (Xi1, Xi2, ..., Xim)

This derivation follows Armington (1969), Appendix II.4

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(A.7)

With these added assumptions, it can be shown that equations A.5 have the general form:

(A.8)

where: ) = the constant elasticity of substitution in the i market;ith

b = a constant.ij

Armington notes that equation A.8 can also be written to express the market share as the

dependent variable:

(A.9)

The advantages of Armington’s assumptions are obvious. As stated by the author, “these

assumptions yield a specific form for the relation between demand for a product, the size of thecorresponding market, and relative prices; and the only price parameter in this function [equation

A.8 or A.9] is the (single) elasticity of substitution in that market” (Armington, 1969; page 161). Theproblem of multicolliniar data has been greatly reduced.

The real advantages to Armington’s assumptions come in the analysis of price changes

(determining the elasticities of demand). Total differentiation of the market demand equation (A.6)and the product demand equation (A.8) yields the relationship between changes in X and changesij

in the explanatory variables. Beginning with the latter :4

(A.10)

Dividing both sides by X :ij

(A.11)

Given that the partial elasticity of X with respect to X equals unity:ij i

(A.12)

dXi

Xi

�idDD

=i

dPi

Pi

� =i/k

dPk

Pk

dXij

Xij

�idDD

=i

dPi

Pi

� =i/k

dPk

Pk

)i

dPij

Pij

dPi

Pi

dPi

Pi

M Sik

dPik

Pik

, where Sik PikXik

PiXi

dXij

Xij

�idDD

[(1 Sij))i � Sij=i]dPij

Pij

� M [Sik)i Sik=i]dPik

Pik

, � M =i/k

dPk

Pk

Xi

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The first term reflects the growth in the X market, while the second term reflects the percenti

change in X ’s share of the market. The next step is to differentiate equation A.6 in terms of dX/X:ij i i

(A.13)

where: � = the income elasticity of demand for ;i

= = the direct price elasticity of demand for Xi i;

= = the cross elasticity of demand for X with respect to P .i/k i k

Substituting into equation A.11:

(A.14)

It should be noted that there is no P term in equation A.12, without which it is not possible toik

derive an expression for the cross price elasticity of X . Armington shows that: ij

(A.15)

where: S = the market share of X in value terms.ik ik

This substitution for dP /P is possible due to Armington’s assumption of a linear and homogeneousi i

indexing function, Q.

To sum, it is shown that the effects on X of changes in prices of products competing in theij

i market depend not only on ) and = but also on market shares. By substituting A.14 into A.13,thi i

Armington arrives at:

(A.16)

with the first bracketed coefficient being the own-price elasticity of demand for X , and the secondij

bracketed coefficient being the cross-price elasticity of demand for X with the respect to any otherij

product price in the i market. Both of these bracketed expressions contain two terms; the firstth

notes that a price change alters relative prices, creating a substitution effect. The second notes

that a price change also alters the price level in the market, creating a market “expansion” effect.

The Armington model has been applied in a number of studies reported in the literature; itspopularity is undoubtably supported by its simplicity and its ability to deal with multicollinearity

problems. Agricultural applications are the most prevalent, a cross-section of which can be foundin Babula (1987), Grennes, et al. (1977), Penson, et al. (1988), Webb, et al. (1989), and Adelman,

(Qi/Qj) (bi/bj)) (PMi/PMj)

)

ln(Q1/Qj) ) ln(b1/bj) � ) ln(PM1/PMj) � uj

Q �PM

PDAY !

As Chou and Buongiorno use monthly data, they utilize lags in their estimation. For the purposes5

of describing their overall approach, however, the lags are omitted here.

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et al. (1989). Extensive use of the Armington model is made in the equilibrium modelling of the

International Monetary Fund (see Grennes, et al., 1977). Although all of these studies stress theadvantages of the model, Armington is not without his critics. Alston, et al. (1990), for example,

find that the restrictive assumptions used by the Armington model lead to underestimated priceelasticities.

While applications of the Armington model in forest products’ trade studies are scarce,

Chou and Buongiorno (1983) use this approach in their estimation of the US demand for hardwoodplywood imports by country of origin (Taiwan, Korea, Japan, Philippines and “rest of world”).

Following Armington’s stepwise approach to import demand specification, the authors begin byestimating the constant elasticity of substitution :5

(A.17)

where: Q,Q = quantity imported from country i and j, respectively (igj);i j

P , P = CIF price of Q and Q , respectively.i j i j

The values of the b / b and ) coefficients are estimated from four simultaneous equations, settingi j

i = 1 (Taiwan) and j = 2, ..., 5 (Korea, Japan, Philippines and “rest of world”), restricting the ) to beconstant and linearizing equation A.16 by converting it to a logarithmic form:

(A.18)

where: u = a random residual.j

Their estimate for the constant elasticity of substitution between hardwood plywood imports of

different origin, ), is -1.74 and highly significant. The fact that this value is significantly differentfrom zero shows that the two different sources of plywood are not considered complements; the

fact that the value is not very high suggests that plywood imports from different sources are alsofar from being perfect substitutes (requiring that ) = �).

The next step followed by Chou and Buongiorno is to estimate demand for total hardwood

plywood imports in the US. Expanding an earlier paper (Chou and Buongiorno, 1982), they utilizea demand function derived from residential construction:

(A.19)

where: Q = total quantity of plywood imported by the US;PM = the price of total imports;PDA = US producer price index for all commodities;Y = US housing starts.

Q (biQi

)1)

)

)1

PM * bi) PMi

1)1

1)

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However, to link this total demand to the elasticity of substitution from above, the researchersestimate equation A.19 by replacing Q and PM by their equivalent CES quantity and price indices,

defined as:

and,(A.20)

where: * = sum from i = 1 to 5.

The b weights needed to calculate these indices can be determined from the estimated parametersi

on b / b in equation A.18, adding that the sum of the b’s must sum to one; this translates into five1 j i

equations and five unknowns, allowing for the recovery of each b .i

The resulting value of the � parameter, being the price elasticity of demand for UShardwood plywood imports in aggregate (equation A.19) is -2.20 and significant. This compares

to a value of -1.98 when the researchers utilize arithmetic indices (Chou and Buongiorno, 1982)as opposed to the CES indices. With value of the aggregate elasticity of demand, �, the constant

elasticity of substitution, ), and knowledge of the average market share by value for each of thenoted supplying regions, the researchers are now in the position to calculate individual own- and

cross-price elasticities as outlined by Armington. The results are shown in Table A.8, breaking outthe substitution and market expansion effects.

The net own-price elasticities reported in Table A.8 (the highlighted diagonal values) and

the net cross price elasticities are determined by adding the substitution and market expansionvalues in any one cell. Beginning with the own-price, note that the net effects have their expected

minus sign, and that the substitution effect varies somewhat, with Korean plywood standing out.Also note that the market expansion effect reduces with the supplying country’s market share,

Table A.8 Elasticities of Demand of US Hardwood Plywood Imports by Country of Origin

Market Korea Taiwan Japan Philip- Rest ofShare pines World

Korea 0.45 s 0.42 0.24 0.12 0.17x -0.53 -0.31 -0.15 -0.22

-0.96-0.99

Taiwan 0.24 s 0.78 0.24 0.12 0.17x -0.99 -0.31 -0.15 -0.22

-1.32-0.53

Japan 0.14 s 0.78 0.42 0.12 0.17x -0.99 -0.53 -0.15 -0.22

-1.50-0.31

Philippines 0.07 s 0.78 0.42 0.24 0.17x -0.99 -0.53 -0.31 -0.22

-1.62-0.15

Q �P �Pd�Pa

6Y 5

Qi

Q i

Pi

P

)i

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Rest of World 0.10 s 0.78 0.42 0.24 0.12x -0.99 -0.53 -0.31 -0.15

-1.57-0.22

s=substitution effect; x=market expansion effect

Source: Chou and Buongiorno (1983)

which is what one would expect. Finally, it can be noted that the net own-price elasticities do not

vary much by country of origin, ranging from -1.77 to -1.95. Keeping in mind that a constantelasticity of substitution is “forced”, this outcome should not come as a surprise.

Turning to the cross-price elasticities of demand reported in the table, note that while the

substitution effects show the expected positive signs, the net effect is negative. As stated by theauthors, “a rise in the price from country j causes a reduction in the total United States hardwood

plywood imports which more than offsets the gains of country i arising from the substitution ofcountry i’s plywood for that of country j”. It can be seen that the net effect depends on the relative

values of the elasticity of substitution ()) and the aggregated import price elasticity of demand (�);when the latter is larger in value as compared to the former, cross-price elasticities will be negative.

It can be noted that the net cross-price elasticities are all highly inelastic, with the highest valuebeing -0.21, the import quantity response in the US for non-Korean hardwood plywood against a

price increase in Korean product. In all cases, the market expansion effect counteracts anysubstitution effect.

Recognizing the potentially restrictive nature of Armington’s assumptions, a study by Hseu

and Buongiorno (1993) attempts to use a more “realistic” approach by allowing the elasticity ofsubstitution to vary. Further, rather than disaggregating the second stage demand by country of

origin, the researchers investigate the US demand for Canadian softwood lumber by species.

Starting with a production function for the construction of houses in the US, the researchersbegin by specifying the derived demand for total lumber imported from Canada:

(A.21)

where: Q = aggregated quantity of Canadian softwood lumber imported;P = average price of Q;P = price of US domestic softwood lumber;d

P = price of all other inputs;a

Y = US housing starts.

Next, the share of a particular species is assumed to depend on the price of that species relative

to the price of all imports:

(A.22)

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where: Q = is the quantity of softwood lumber of species i imported from Canada;i

P = the average price of species i;i

) , = constants specific to species i.i i

The authors note: “equation [A.22] differs slightly from Armington’s (1969) theory in that theelasticity of substitution ) varies by species”. Equations A.21 and A.22 are estimated separatelyi

in log-log form, and own- and cross-price elasticities calculated from the total differential as inArmington (1969) and Chou and Buongiorno (1983).

While the hypothesis that the elasticities of substitution by species are significantly different

from one another is worthy of investigation, it is not at all clear how the researchers link such anhypothesis back to Armington’s theory. In fact, there are a number of major problems with this

methodology.

First, getting separate estimates for the single � and the numerous ) ’s does not constitutei

a two-stage optimization; the Q in equation A.21 must somehow be linked to the Q in equation

A.22. With Armington (1969) and Chou and Buongiorno (1983) this is accomplished by using theCES indices.

Second, estimating equation A.22, while shown to be possible under Armington’s

assumptions (see equation A.9), becomes problematic without some way of “collapsing” all the Q’si

into Q (as is done with Armington’s Q function). As is, Hseu and Buongiorno’s equation A.22

violates one of the assumptions of the classical linear regression model. The right-hand-sidecontains a component which is not independent of a left-hand-side variable: P, being the price of

the aggregate imports of softwood lumber from Canada, is determined as the arithmetic mean, *Pi

Table A.9 Elasticities of Demand of US Softwood Lumber imports from Canada by Species

Market Spruce Pine Fir Hemlock Red OthersShare Cedar

Spruce 0.57 s 0.34 0.42 0.27 0.23 0.42x -0.18 -0.22 -0.14 -0.12 -0.22

-1.63-1.13

Pine 0...09 s 3.85 0.74 0.47 0.41 0.74x -1.13 -0.22 -0.14 -0.12 -0.22

-6.15-0.18

Fir 0.11 s 0.06 0.01 0.01 0.01 0.01x -1.13 -0.18 -0.14 -0.12 -0.22

-0.09-0.22

Hemlock 0.07 s 2.27 0.36 0.44 0.24 0.44x -1.13 -0.18 -0.22 -0.12 -0.22

-3.70-0.14

Red 0.06 s 0.55 0.09 0.11 0.07 0.11Cedar x -1.13 -0.18 -0.22 -0.14 -0.22

-0.91-0.12

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Other 0.11 s 0.51 0.08 0.10 0.06 0.05x -1.13 -0.18 -0.22 -0.14 -0.12

-0.80-0.22

s=substitution effect; x=market expansion effect

Source: Hseu Buongiorno (1992)

X Q / Q. While the second problem could have been avoided by defining Q as the total aggregatei

quantity less Q, and P the average price of this new Q, other problems with the application ofi

Armington’s theory remain. Most importantly, without the linear, homogeneous aggregation

function, the substitution for dP / P in Armington’s equation A.15 cannot be made.i i

These problems not withstanding, Hseu and Buongiorno do get interesting empirical resultsthat are worth exploring. As shown in Table A.9, own-price elasticities vary considerably across

species and cross-price elasticities exceed unity in some cases. While the market expansion effectremains constant over species in both the calculations of own- and cross-price elasticities, note that

by allowing the “share elasticity” to vary by species, the substitution effect changes. In calculatingthe share elasticities, the researchers employ a seemingly unrelated regression estimation (SURE).

“To test the validity of [Armington’s] simplification, [equation A.22] was re-estimated with therestriction that ... ) ... [was] the same across equations” (Hseu and Buongiorno, 1992, p. 595). Thisi

was rejected with a computed X statistic which was significantly higher than the critical value.2

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APPENDIX B

Japanese Import Volume and Real Pricesof

Wood Products by Type, Source, and Species

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