xt705q4rkd0x https://nyx.uky.edu/dips/xt705q4rkd0x/data/mets.xml   Agricultural Experiment Station, Department of Agricultural Economics, University of Kentucky 1973 journals kaes_research_rprts_15 English University of Kentucky Contact the Special Collections Research Center for information regarding rights and use of this collection. Kentucky Agricultural Experiment Station Research Report 15 : April 1973 text Research Report 15 : April 1973 1973 2014 true xt705q4rkd0x section xt705q4rkd0x  ? MONETARY CONDITIONS AND THE U.S. LUMBER
  John C. Redman and Vincent Cusumano
 I •
 . In cooperation with
I Northeastern Forest Experiment Station
  Forest Service—U.S. Department of Agriculture
I University of Kentucky : : College of Agriculture
Agricultural Experiment Station : : Department of Agricultural Economics
_ Lexington
_A  I

  '1`ABLl·l ()}·` (2()N'I`l·LN'l`S
I,lS'1` ()l·` '1`ABLES ...................................... 2
LIST 01* 1·`l(iURl·LS ..................................... 3
SL`MM,»\l{\' ......................................... 4 [
IN'1`R()1)l '(i'1`l()N ...............,...................... 5
'l`l1l·;()Rli'1`lL2.·\I. (J()NSll)l·lR.r\'1`l()NS ............................ 5
\l|·Q'1il()l)S .......................................... 6
1).·\'1 .·\ ANI) l{l·LSUI,'1`S ................................... 7
41`1iS'l`1N(}'1`l1l·L NULL HY1’()'1`l11iSIS ............................ 7.
'1 llli }·lX'1`I·lN'1`()l·` '1`Illi .·\l)_] L'S'1`I\1I·LN'1`S .......................... U
CONCLUSION ........................................ 13
I.I'1`I·1R.~\'1`L?R1·L C1'I`1·ll) .................................... 15
.»\1’l’1iN1)1X ......................................... 17

usr or rAm.1;s  
N0, Page
A Regression Results ................................... 8
· B Lumber lndustry Percentage Adjustments Over The Business Cycle .......... 9
· I

Page 1 No. Page
I 8 1 1 Composite Index ol '1`welve Leading Indicators, Reverse Trend Adjusted to Coincide
W1111 Business Cycle (1967 = 100) ............................ 17 -
l 9 I 2 Index ol Wholesale Lumber Prices, U. S. (1957-59 = 100) ................ 18
1 3 Index o1` Soltwood Prices, LJ. S. (1957-59 = 100) .................... 19 I
1 4 Index ol llurdwood Prices, U. S. (1957-59 = 100) .................... 20
1 5 'lotail Monthly Lumber Production, lj. S ......................... 21
  6 `lotul Monthly Soltwood Lumber Production, U. S. .................. 22
1 7 'I`ot;il Monthly Ilurdwood Lumber Production, I}. S ...... . ............ 23
1 8 ’1`0u1 110111111y s01`1»v·00t1 shipments, 1;. s. ....................... 24
  9 'I`otu1 Monthly llardwood Shipments, U. S ........................ 25
1 10 'lotul Monthly Lumber Shipments, L`. S. ........................ 26
1 ll `1`otnl Monthly Lumber Inventories, L`. S ......................... 27
1 12 `lotttl Monthly Soltwood Lumber Inventories, IQ. S. .................. 28
1 13 'Iotul Monthly Ilurdxvood Lumber Inventories, L`. S. .................. 29
1 14 'l`ot111 Industry Iimployment, U. S. ........................... 30

t The evidence reported in this study suggests that the U. S. lumber and wood products
p industry is highly sensitive to changes in money market conditions. The time period covered by
i this study (1952-70) includes most of the post World War II years, and most important, the
period following the Federal Reserve-Treasury accord of 1951 which activated monetary policy.
The generally accepted theoretical hypothesis that monetary policy has an unequal impact
on economic activity was tested. Employing ordinary least squares and regressing the respective
lumber industry economic indicator on a monetary policy proxy, i.e., interest rates on new issues
A of 3—month treasury bills, it was found that an inverse relationship exists between activities in this
‘ 1 industry and monetary conditions.
E The extent of the industry response was also calculated and the nature of its cyclical
. ` movements was described. Although the exact magnitude of the industry response varied,
depending on the specific indicator, it was observed that in all cases the apparent response
g · outweighed manyfolds similar reactions reported in the rest of the economy. This general
I tendency was especially magnified during periods of economic contraction.
E Assuming the cyclical variations noted in the rest of the economy as the "ideal" response, it
‘ was concluded that the impact of monetary policy on the U. S. lumber and wood products
i I industry appears to be excessive. Thus, this study supports the general notion that monetary
Y actions instigated by the Federal Reserve authorities have an uneven distributive effect on
A f economic activity.
4 1
’ 1

mpact by .6
' l$$¤<$$ john C. Redman and Vincent Cusumanol
in this
yicllcal I"U°d“Cti°" impact of monetary policy on a particular
TES; VH _ _ i_ industry. It purports to measure the price,
ggncml l_ ` · “_ “f‘3"l°'[l(]“   lmonéldfl production, shipments, inventory and
PU ILM 1“>U?»=*l* } *1* * LN RCWYW employment responses of the lumber and
l System to combat inflationary tendencies in wood products industry (Standard Industry
m$€» il aggregate economic activity, has become a Code 24), which is perhaps one of the most
Oducli paramount political as well as economic issue. fragmented and atomistically structured
·¤€i¤Y}' Since the 1951 Federal Reserve-Treasury industries in the United States today.
ECI 011 accord, economists have argued that Characteristically, this industry is labor
monetary controls have adifferential impact intensive, located near its raw material
on the various sectors and subsectors of the sources, and provides employment for more
L`. S. economy. Structural differences in the than 600,000 rural persons [23].
economic fabric are alleged to contribute to
this uneven distributive effect Small business,
residential construction, and state and local Theoretical Considerations
governments tue believed to be most effected
by monetary controls, largely because of their Evaluation of the nature of industry
overall dependency on the loanable funds response to changes in monetary policy and
· market [8, 10, 11]. aggregate economic activity should be
Although a number of studies have predicated on some type of theoretical
either quantitatively or qualitatively behavioral constructs. Although considerable
examined the relative effect of a restrictive debate exists as to the exact nature of the
m0¤Ct1try policy on sectorial activity [1, 7, 8, macroeconomic adjustment process that takes
9, 10, 11, 14, 23] , attempts to determine the place because of changes in the availability of
short-run responses of a particular industry financial assets, many economists adhere to
life not documented. The primary purpose of some variation of the portfolio theory [3, 5, [
A this study is, therefore, to assess the overall 6, 12]. [
, Briefly, the theory postulates a series of
E casual responses generated by spending units
____ as they react to changes in macro conditions.
—___—__ Thus, a change in the ratio of financial assets
  1Pf0fessor of Agricultural Economics,and Research Assistant to real assets Induced   an Increase Or I
] in Agricultural Economics, respectively. decrease 111 the stock of rI10rl€y CHUSCS the
[ 5
l i

  r supply price of capital2 to either increase or does this paper want to suggest that  
_ decrease. This change in the supply price of decision-making in the lumber and wood  
capital or interest rates affects the general products industry is restricted to monetary  
, level of economic activity. Rising interest variables. Industrial decisions are too complex  
i rates, for example, brought about by a for such a simplistic treatment. lt does,
. restrictive monetary policy will have a however, purport to identify the l
I dempening effect on long—run and short-run consequences of a restricted monetary policy
decision making, both at the firm and at the on this industry.
household level. Consequently, the _
i I ` postponement or curtailment of investments
I or purchases of durable goods has the Methods
  eventual impact of decreasing aggregate
· . demand, and of course, the desired effect of In order to accomplish this task, the
; dampening the inflationary spiral. By a similar study was divided into three stages. First,
Q l _ argument, the opposite effect could be traced monthly figures for wholesale prices,
, out for periods of decreasing interest rates or production, shipments, inventories, and
  easy monetary policy. Here the objective ofa employment were gathered [16, l7, 18, 19,
  . relatively easy monetary policy would be to 20, 21]. Likewise, monthly levels of interest
, T stimulate economic activity. rates on new issues of 3-month treasure bills
l I ` Applying this general theoretical notion and the index of l2 leading indicators, reverse
. of the lumber and woods product industry, trend adjusted to coincide with the business
1 i we can hypothesize, a priori, similar cycle, were obtained and analyzed [2, 22].
V I directional responses in the industry’s However, because of the extremely erratic
l economic indicators to changes in monetary nature of the lumber statistics, it was
, i conditions. That is to say, an inverse necessary to calculate l2—month moving
relationship is expected between interest rates averages to isolate the cyclical variation in
(the monetary policy proxy variable) and these data. Second, ordinary least squares was
lumber production, shipments, and wholesale used to determine the directional response of
~ lumber prices; while a direct relationship is the U. S. lumber and wood products industry
» expected between interest rates and the levels to changes in monetary conditions. Thus, the
I of the end-of-the—month inventories. general form of the lumber industry response I
t Two questions are basic to this study. equation was formulated as follows:3 f
First, are the observed fluctuations in these l
lumber industry economic indicators Y, = f(it_6)
consistent with a priori theoretical responses?  
Q Second, if these fluctuations are consistent where Y represents a vector of industry wide  
` with theoretical expectatives, what is the responses, be it prices, production levels, ‘
magnitude of these adjustments? At the shipments, inventories, or employment; i
· outset it should be emphasized that in no way denotes the interest rates on new issues of
_,m._..._....-.m Bit is recognized that this type of estimation procedure is  
` subject to a variety of errors, some of which may bc
I sufficiently large to reduce the value of the estimate. ln this
` 2 I _ I I I study the errors stem basically from lack of knowledge of
The supply price of caprtalis that price at which holders of the precise nature of the industry response, and more
wealth are willing to forego present consumption for future importantly from nonspecification of other important
consumption. casual variables.

] 7
that   3-month treasure bills lagged six months discussing these data and results it should be
wood   [15]. T`he t-test was then used to test for reiterated that actual data observed in the
ietary   statistical significance. That is to say, if the literature of economic indicators are not
miplex   calculated beta coefficient falls beyond the shown in these figures. Instead, the plotted
does,   prespecified cri tical region, the points represent a series of 12-month moving
the ( null·hypothesis that no significant averages centered around the month of july
policy g relationship between industry responses and from 1953 to mid-1971. ’
. movements in interest rates exists was It should also be noted that because of
  rejected, and it was concluded that monetary the very nature of this study, the information
e policy had an effect that cannot be illustrated in these figures had to be
attributable to a change variation alone   dichotomized into periods of economic
Fluctuations of the respective lumber contraction and periods of economic
lt, the industry figures were then examined relative expansion. Hence, the shaded areas isolate
First, to the business cycle, identified by the periods of economic recession from the boom
prices, National Bureau of Economic Research’s periods.
and (NBER) index of 12-leading indicators,
8, 19, reverse trend adjusted to coincide with the
iterest business cycle [22]. The objective of this Testing the Null Hypothesis
·e bills final stage was twofold. First, it measured the
·everse percentage adjustments and second, to As summarized in Table A, the null
isiness determine the excessive nature of these hypothesis that no significant association
, 22]. adjustments, it compared these ups and exists between monetary policy and
erratic downs with those registered in the rest of the lumbering activities must be rejected. The
t was economy. statistical results indicate the monetary policy
noving variable is important in explaining the
ion in variation in the respective dependent variable.
es was Data and Results The calculated t—values for the interest rate
inse of regression coefficient are all significant at the
dustry The data for this study are summarized 0.01 percent level. In general, therefore, it
us, the on 14 charts (Figs. 1-14) found in the may be concluded that monetary policy hasa
sponse   Appendix, while the results of the statistical definite impact on overall activities registered
  tests and measurements are presented in the lumber and wood product industry.
  subsequently in Tables A and B. The Excluding lumber prices the signs on the
  statistical findings of testing the null estimated beta coefficients are supportive of
[ hypothesis that no significant correlation the theoretical expectations that rising
y wide   exists between monetary policy and U. S. interest rates have a dampening effect on the
levels, E lumbering activities are summarized in Table industry.4
nent; i A. The percentage adjustments that i
sues of apparently took place in the lumber industry
as a result of monetary policy and changes in ________..
the business cycle from 1953 to 1970 are
found in Table B.
Cyclical and secular movements in the U. 4N<>_ ¤¤=¤¤P¤ ¤¤ ¢1¤¤§<{¤`·¤¤¢ 09 dw magnitude °f thm .
. . . . . . estimated beta coefficients will be made because of the
eedurc is S. lumber industry definitely exist (F1gS· potential m]sund3{s[andi¤g that my result. Since we
,3];:/,]:)]; 2*14) and similar movements in the eomposite excluded other explanatorgf vaziebles fromcgg §:pg;;¢
mlgdtgoig index of economic activity BIC €l€21flY :$hu;tl;;I]n,t;i;;:n§itirgstdiissgtugy,liiriifvtiiieriiiistiie gan <>f the
,mpnn,nn dl$tmg'¤1Sh&bl€ (Fig. l). However, before coefficient,

 8 .
Table A.--Regression Results
Interest 2 i
Dependent Constant Rate T-Value R 1
` Variable (Y) Coefficient i
Industry-wide Employment 689.6 -20.6 -10.1* .59 Q
Total Lumber Shipments 3107.5 -26.7 -5.1* .27 5
Softwood Shipments 2532.1 -26.6 -7.0* .41 §
Hardwood Shipments 574.4 .0152 .008 .0001 I
_ 1 Total Lumber Production 3124.2 -28.6 -5.6* .31 i
Softwood Production 2535.9 -23.2 -6.2* .35 i
, . Hardwood Production 585.9 -3.8 -2.5* .08 Q
Total End Month Inventories
I (1961-70) 6527.0 58.3 4.2* .45 .
I Composite Index of Lumber
Prices 88.5 4.6 7.9* .47 7
*Statistical1y significant at the .99 level. I §
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'I`he Extent of the Adjustments greater than the general decrease in aggregate
A economic activity (Table B). In the 1969-70
Once it was established that monetary economic slump, for instance, the wholesale
policy did indeed play a paramount role in price index of lumber decreased some 15.9
determining fluctuations in lumber activities, percent while the composite index showed a
the second phase of this study focused on the decrease of only 1.8 percent. An equally [
extent of these cyclical fluctuations, important observation is noted in the general
especially during periods of economic tendency of wholesale lumber price index to
contraction in part instigated by a tight reach its respective peak sometime before the
monetary policy. rest of the economy, while lagging behind on
Before elaborating on the exact nature the downturn (Fig. 2).
of this apparent response, a comparative basis A comparative study of wholesale prices
should be established. Monthly movements in of softwoods and hardwoods reveals
the U. S. economy since 1953 were based on characteristics similar to the wholesale prices
the National Bureau of Economic Research’s of lumber (Figs. 3 and 4). That is, there is a
index of 12-leading indicators—reverse trend definite cyclical pattern in both hardwoods
adjusted to coincide with the business cycle and softwood prices, and the sarne general
(Fig. 1). By measuring from peak to trough, lead-lag characteristic is exhibited. Also,
the following reference dates are easily hardwood prices generally tend to lag behind
isolated: softwood prices. For example, softwood
prices were showing signs of adjusting back
  Peak Trough upward during the 1969-70 economic
recessions while hardwood prices show no
4/57 to 3/58 noticeable signs of upward movements. Also,
10/59 to 10/60 the amplitudes of softwood price fluctuation
3/66 to 2/67 are relatively greater than those of hardwood
1 1/69 to 8/70 prices. In a small way, this might be indicative
of greater price stability in hardwoods than in
The percentage adjustments during these softwoods, although the 7.4 percent decrease
dates were calculated (Table B). Since 1953, in hardwood prices during the 1966-67
the largest single negative percentage change downturn might contradict this.
r in aggregate economic activity took place Movements in total lumber production
during the 1957-58 recession when the index suggest a pattern consistent with the general
decreased some 4.8 percent During the business cycle (Fig. 5). From through to peak,
expansion period of 1961·66, the yearly the average increase in production levels has
increase averaged about 12 percent, whereas been about 12 percent, while averaging about
the 1969-70 economic downturn was 14 percent on the downside of the general (
reflected by a 1.79 percent decrease in the business cycle. Comparisons of these 1
index. production responses with those registered in
The general pattern of monthly prices reveal that in recessionary periods the
fluctuations in the wholesale price of lumber percentage decrease in production is much
(Fig. 2) has been to increase during periods of greater than the percentage decrease in
economic boom and diminish in periods of wholesale lumber prices. During economic '
recession, which is consistent with the booms, however, the percentage increase in
business cycle. The overall lumber price price outweighs the percentage increase in
decrease, because of unfavorable business production A plausible explanation for this (
conditions, ranges from two to seven times might lie in the presence of many marginal

j ( firms that are perhaps forced out of the with respect to time;hardwoods, on the other
i lumbering business during economic hand, register a long-run upward trend. A
recessions. Because of the loss of these firms, In line with general hypothesized
the lumber industry is unable to meet the expectations, end-of—the-month inventory
‘ expanding demand during the expansionary levels indicate definite contracyclical
periods. variations (Figs. 11, 12 and 13). Inventory
Avery erratic pattern ofthe fluctuations levels of both softwoods and hardwoods .
I in hardwood and softwood production increase in economic recessions and diminish
existed (Figs. 6 and 7). Although difficult to during economic expansions. However, the (
  discern, a cyclical behavior pattern may also impact of changing economic conditions
I be deduced. The impact of unfavorable seems to be relatively greater on hardwoods
  market conditions seems to be greater for the than on softwoods. Inventory levels for
_ 1 ` hardwood firms than for the softwood firms. hardwoods increased some 90.7 percent
i Note also that the long—run trend in hardwood during 1969-70. By contrast, in the same
. — production is an increasing one, while for the interval of time, softwood inventories i
I A softwood production levels, the long—run increased only 15.7 percent. (
Q trend is decreasing. The ever decreasing role Finally, the movement in industry-wide
I of softwood in the general construction employment levels is also cyclical (Fig. 14).
{ industry and the increasing demand for The observed pattern is also consistent with
· f — hardwood furniture partially explain these the general cyclical movements in aggregate
A I secular tendencies. activity. Employment patterns, however,
I ( Cyclical variation in the quantity of differ in the long—run tendency of substituting
  lumber demanded, as measured by the level of capital for labor. In periods of economic
I monthly lumber shipments (Fig. 8) also booms, the average increase in the number of
, moves with the business cycle, i.e., adjusting people employed in the industry, has been of
A upward in the boom periods and downwardin about 5 percent. But, during periods of
. slumps. The lumber shipments averaged contracting economic activity the average
— approximately 14 percent on the upward decrease has been about 12 percent. These
swings and about 13 percent on the characteristics also support the hypothesis
downward movements. Relative to the that many marginal firms in the industry are
wholesale lumber price adjustments, these forced out of business because of adverse
- quantity changes are similar to the production business conditions. For example, the I
I responses. Again, the decrease in the levels of 1969-70 slump in the general economy
_ lumber shipment is from four to six times resulted in a 13.7 percent decrease in total
_ that of the decrease in aggregate activity. This industry employment. Considering that this
; is exemplified in the 9,14 percent negative industry is normally located close to the .
i adjustment in the 1969-70 recession. Also source of raw materials or in remote rural
consistent with the basis cyclical behavior areas, and also that this industry is perhaps
` _ I patterns established in the other series were one of the most labor intensive industries, the »
‘ the cyclical and secular trends in shipments of impact of a restrictive monetary policy is felt
I hardwoods and softwoods (Figs. 9 and l0). by many rural workers in terms of
I Softwoods show a decreasing long-run trend unemployment.
l I `
/ i l

esiled The results of these analyses lead to the lumber industry, and the presence of many
nioYY COIIClUSl()H that IhC United St2:l[CS lUITlb€I` marginal firms, the impact Of  
relieal . lnclu$llY is hll8hlY sensitive te changes in aggregate conditions and monetary policy is
emory nloneldly Pollel and _“Sgregele eeenemie excessive. This is emphatically documented in r
Needs Condlumle Ihc _`/lslblc Cyclical and Table B. In every instance, the adjustment A
¤1n1$h contracyclical behavior patterns and the h t resulted in the 1 ber lndust
7, illc _ results of regression analysis provide the basis l e . um . ry
llmms for this Conclusion. outweights lmanyfold the decrease. 1n the
tvoods llowever, in assessing these results a compeslte Index Of ecenomlc acuvltlo The
S for judgment as lo the desirability Ul these excessive- nature of this impact on lumbering
srcent relationships must be made. First, from the ls dlnpllhed if developmental dllnenslons are
same . viewpoint of macroeconomics and economic lhlown inte Pel$PeenVe· Sawlnllls must be
il`.OI‘lCS gtabilityl a question can bc rgtiged Cgriccrrijrig located DCU Of not far from th€iI‘ SOUICCS of
the desirability of the United States lumber raw material, er in rural areas, if they are te
l-Wide industry fluctuating according to changes in Y¤l¤lmlZih€Sl$ activity. That is to say, industrial activity In eenelusien, although ll nllghl be
ry are Should respond to monetary policy so as to economically desirable for industries to reltlct
dverse en un ge t n e e it c es give nature of to monetary policy and to the extent that t is
, the lrlgcrggcongmjg fgrqeg grid [hug bring 3_bOu[ CyCllC3.l ICSPOIISC is excessive, monetary  
»nomy economic stability. Thus, in the general sense, 8PP€€iT$ te be unfair and diseriniinatins- The
l total the cyclical nature of lumbering is an United States lumber industry apparently
tt this economically deSlf&1blY behavior pattern, if suffers from such treatment, i.e,, assuming
o the the cyclical variation is only a response to that the impact of monetary policy on other
rural market forces. Conversely, it may be argued seeters of the cconolnY is lellected hY the .
erhtips that because of the atomistic structure of the index ol oconolnlc aetitritr
es, the
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