Net Farm Income, Market Prices and Agricultural Productivity ...
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Transcript of Net Farm Income, Market Prices and Agricultural Productivity ...
Give to AgEcon Search
The World’s Largest Open Access Agricultural & Applied Economics Digital Library
This document is discoverable and free to researchers across the globe due to the work of AgEcon Search.
Help ensure our sustainability.
AgEcon Search http://ageconsearch.umn.edu
Papers downloaded from AgEcon Search may be used for non-commercial purposes and personal study only. No other use, including posting to another Internet site, is permitted without permission from the copyright owner (not AgEcon Search), or as allowed under the provisions of Fair Use, U.S. Copyright Act, Title 17 U.S.C.
Net Farm Income, Market Prices and Agricultural
Productivity Growth in the United States
Sean A. Cahill
Research and Analysis DirectorateStrategic Policy Branch
Agriculture and Agri-Food Canada
April 2007
I would like to thank Eldon Ball for generously providing the data used here and for helpfulsuggestions. Any policy views, whether explicitly stated, inferred or interpreted from the contents ofthis paper, should not be represented as reflecting the views of Agriculture and Agri-Food Canada(AAFC).
Copyright 2007 by Sean A. Cahill. All rights reserved. Readers may make verbatim copies of this documentfor non-commercial purposes by any means, provided that this copyright notice appears on all such copies.
Selected Paper prepared for presentation at the American Agricultural EconomicsAssociation Annual Meeting, Portland, Oregon, July 29-August 1, 2007
1 Introduction
Real net farm income in the United States has been declining slowly butsurely. Between 1948 and 2002, U.S. real net farm income decreased inaggregate by about 2.2 Billion $1996 per year – see Figure 1.1 Yet for mostof this period, annual productivity growth was substantial [1, p. 1045].
This juxtaposition of declining net farm income and healthy productiv-ity growth represents one element of the ‘farm problem’ [8, p. 62]. An
additional feature of the problem is that the economic well-being of farmersand their families has been low, both in absolute terms and in relation tonon-farm families. This disparity has become less marked over time, butthe improvement has been due to growth in o¤-farm income, which has be-come an increasingly important part of farm household income.2 While theincome of farm and non-farm households has gradually equalized, the issueof low net farm income remains prominent in the justi…cation of variouspolicies designed to “ameliorate the farm problem” [8, p. 85].
The striking reduction in aggregate real net farm income illustrated inFigure 1 does not take into account another well-known feature of U.S.agriculture – the number of farms has also been steadily declining. In 2002there were about 2.2 million farms in the United States, 3.4 million fewerthan in 1948 [18, pp. 34-35]. This exit of about 63,000 farms per year meansthat any analysis of net farm income must allow for the e¤ect of reductionsin the number of farms.3
1The net farm income data are derived using price and implicit quantity data fromthe U.S. agriculture production account (see the Data and Results section for details onthe production account data). The data do not include government payments that arenot speci…cally tied to the production of one or more outputs, i.e. decoupled payments.These net farm income data are then de‡ated using the U.S. all-items CPI (base 1984-1986, scaled to 1996). The de‡ated series gives an idea of the spending power of net farmincome over time.
2 The proportion of total farm household income accounted for by farming income hasdecreased signi…cantly over time, from about 50% in 1964 to less than 30% in 1999 [14,p. 4].
3 Net farm income is often reported in aggregate and is an in‡uential and highly pub-licized statistic when about used to describe the health of the farm sector. Generallyspeaking, average net farm income per operation is a secondary statistic, even though it isprobably a better indicator. See, for example, [16] or the ERS 2007 Farm Income Forecast(obtainable at www.ers.usda.gov).
1
Figure 1. Real Aggregate Net Farm Income, United States, 1948-2002
-80,000
-40,000
0
40,000
80,000
120,000
160,000
1948 1954 1960 1966 1972 1978 1984 1990 1996 2002
Mill
ion
1996
$U
S
SOURCE: Calculations with ERS Agricultural Productivity database (see Annex 1)
2
This analysis addresses the farm problem in two stages. First, changes innominal net farm income are decomposed into market price and productivitygrowth e¤ects. Bennet indicators provide the elements of price and quantitychange in this decomposition.
In the second stage, elements quanti…ed in the …rst stage are related tochanges in the real implicit wage earned by the residual claimants, namelyfarm operators and unpaid family members that work on the farm. Thismakes it possible to show how productivity growth andmarket price changesa¤ect the economic well-being of the farm household.
The next section gives more precise de…nitions of net farm income andthe residual claimant. The third section outlines the methodology used todecompose nominal net farm income growth and the method used to relatethis decomposition to changes in the real implicit wage. Data used for thecomputations and results from the decomposition are presented in the fourthand …fth sections respectively. The last section provides some concluding
comments.
2 Net Farm Income and the Residual Claimant
Net farm income (NFI) is de…ned by the United States Department of Agri-culture, Economic Research Service (ERS) as the “share of output earnedby operator households and others who share risks” [7, p. 4] – ‘others’means other households, corporations and other entities that may be resid-ual claimants. If the others component does not play an important role inthe distribution of NFI, then the residual claimants are operators and un-paid family members. As Hottel and Gardner put it, this is the ‘essence offamily farming’.4
The ERS de…nition provides the basis for NFI measurement within thecontext of a production account for agriculture. In the account, the revenuefrom all agricultural outputs equals the cost of all inputs. This means thatpro…t, in the usual sense of the word, will always be zero in the account.
To ensure that the equality of cost and revenue holds, the price of one ormore inputs must adjust; the prices for these ‘residual claimant’ inputs are
4 See [11, p. 553]. The authors nevertheless choose equity capital as the residualclaimant. Their approach is generally consistent with analyses of returns in the non-agricultural sector, where capital is the residual claimant and the cost of capital servicesis measured as the gross operating surplus in the national accounts [6, p. 5].
3
thereby endogenously determined.5 Both the total value and the unit valueof the residual will depend upon the claimant – if owners of land were theresidual claimants, the return to these owners would usually be di¤erentfrom that to owners of another input (e.g. machinery).
In the computations made here, only operator and unpaid family labourwill be treated as the residual claimant – this is consistent with the ERS de-…nition of NFI. The methodology developed in the next section neverthelessallows for more than one residual claimant, so that an analyst can choosethe residual claimant or set of claimants without being bound by the onechosen here.
3 Methodology
The approach taken in this section is to …rst establish the manner in which a
change in nominal NFI growth can be decomposed into output price change,input price change and productivity growth components. Then the decom-position of the real implicit wage is speci…ed.6
Suppose that, in each year, N inputs are used to produceM agriculturaloutputs and that there are H < N residual claimants. Suppose also thatobservations on the prices and quantities of all of these inputs and outputsare available. Use the following notation: output prices in year t are thevariables p1;t; p2;t; : : : ; pM;t, where each price includes any subsidy that istied to production of that output.7 Transfer payments made to farmers bygovernments – i.e. payments that are are decoupled from production – arenot included in prices p1;t; p2;t; : : : ; pM;t; nor do they appear in the de…nitionof NFI used here.8
5This endogenous rate of return approach is “the most widely used methodology” forthe computation of total (multi) factor productivity statistics [17, p. 14]. Typically,the residual claimant input is one or more productive capital assets. In this case, theendogenous variable is the rate of return, which adjusts to ensure that total revenueequals total cost [17, pp. 3-4],[13, pp. 13-14].
6 The methodology outlined here need not be restricted to net farm income. It couldjust as easily be related to net income for any …rm or sector – the key is that one or moreinputs have an endogenous price or endogenous rate of return that ensured equality ofrevenue and cost.
7Output ‘price’ may be a price index or a unit value (e.g. $/tonne). Output ‘quantity’may be an actual quantity (e.g. ’000 tonnes of wheat) or an implicit quantity obtainedby dividing the nominal value of output by a price index.
8 These payments may, however, play an important role in determining the farm house-hold’s overall income from farming activity, the decisions made by the operators his/her
4
Gross output quantities are the variables y1;t; y2;t; : : : ; yM;t:Gross outputis de…ned, for any commodity or commodity aggregate i; as total sales ofi plus net additions to inventories. Sales of i include consumption of farmoutput by farm households, and sales made by farms to purchasers outsideof the farm sector.
Input prices are the variables w1;t;w2;t; : : : ; wN¡H;t ; where each priceincludes any rebate that is given for that input; input quantities are thevariables x1;t; x2;t; : : : ; xN¡H;t: Inputs are ordered so that inputs 1; 2; : : : ;N¡H have explicit prices, i.e. these are not residual claimants. When there isonly one residual claimant, the inputs are ordered so that the Nth input isthat residual claimant.
Total revenue is the sum of the values of individual outputs, i.e. Rt =pt ¢yt; where pt is the 1£M vector [p1;t; p2;t; : : : ; pM;t] and yt is the 1£Mvector [y1;t; y2;t; : : : ; yM;t] : Production cost for all but the residual claimantinput(s) is the sum of the expenditure on each of the N ¡ H inputs, i.e.Ct =wt ¢ xt; where wt is the 1£ (N¡H) vector [w1;t;w2;t; : : : ;wN¡H;t] andxt is the 1£ (N ¡H) vector [x1;t;x2;t; : : : ; xN¡H;t] :
Nominal NFI in year t; denoted by Ft; is the di¤erence between the totalvalue of agricultural output, Rt; and the cost of all inputs in the account –excluding residual claimant(s) – Ct: So
Ft = pt ¢ yt ¡wt ¢ xt. (1)
The change in nominal NFI is measured as:
FGt = Ft ¡Ft¡1 . (2)
This means, substituting (1) into (2), that
FGt = [pt ¢ yt ¡ pt¡1 ¢ yt¡1]¡ [wt ¢ xt ¡wt¡1 ¢ xt¡1] : (3)
The …rst term in square brackets on the right-hand side of (3) is thechange in total revenue between year t ¡ 1 and year t: The second term insquare brackets is the change in the cost of all inputs – excluding residualclaimant(s) – between year t¡ 1 and year t:
family members regarding on-farm and o¤-farm work (i.e. labour supply) and decisionsabout entry into, or exit from, farming.
5
The di¤erence in value (revenue or cost) between year t¡1 and year t canbe expressed as the sum of price change indicators and aggregate quantityindicators for the commodities or commodity aggregates produced or utilized[4, p. 313]. There are several possible formulas for these indicators, and theirproperties can be assessedwith a range of tests similar to those used to assessconventional index number formulas like the Fisher Ideal price index. Of thecandidates, the Bennet price and quantity change indicators ful…ll all of theproperties needed to meet the requirements of ‘well-behaved’ indicators [4,p. 331, Prop. 2].
The decomposition of the change in revenue between year t¡ 1 and yeart can be expressed as the sum of the Bennet indicators of output price andoutput quantity change [4, pp. 313-314], i.e.
pt ¢ yt ¡pt¡1 ¢ yt¡1 ´ IR (pt; yt;pt¡1; yt¡1)+ (4)
VR (pt;yt;pt¡1;yt¡1)
where
IR (pt;yt;pt¡1;yt¡1) =XM
i=1ymi;t (pi;t ¡ pi;t¡1) (4a)
is the Bennet indicator of aggregate output price change;
ymi;t = (yi;t + yi;t¡1) =2
is the arithmetic average of the quantity of output i in year t and year t¡ 1;
VR (pt;yt;pt¡1;yt¡1) =XM
i=1pmi;t (yi;t ¡ yi;t¡1) (4b)
is the Bennet indicator of aggregate output quantity change; and
pmi;t = (pi;t + pi;t¡1)=2
is the arithmetic average of the price of output i in year t and year t¡ 1.
A change in the cost of all inputs – excluding residual claimant(s) –between year t ¡ 1 and year t can be decomposed in a similar manner:
wt ¢ xt ¡wt¡1 ¢ xt¡1 ´ IC¡wt;xt;wt¡1;xt¡1
¢+ (5)
VC¡wt; xt;wt¡1; xt¡1
¢;
6
where
IC¡wt;xt;wt¡1;xt¡1
¢=XN¡H
j=1xmj;t (wj;t ¡ wj;t¡1) (5a)
is the Bennet indicator of price change for the aggregate of all but theresidual claimant input(s);
xmj;t = (xj;t +xj;t¡1)=2
is the arithmetic average of the quantity of input j used in year t and yeart¡ 1;
VC¡wt;xt;wt¡1;xt¡1
¢=XN¡H
j=1wmj;t (xj;t ¡ xj;t¡1) (5b)
is the Bennet indicator of quantity change for the same aggregate; and
wmj;t = (wj;t +wj;t¡1)=2
i.e. this is the arithmetic average of the price of input j in year t and yeart¡ 1:
Substitution of (4) and (5) into (3) gives the following decomposition ofa change in nominal NFI:
FGt = IR (pt;yt;pt¡1;yt¡1)¡ IC¡wt;xt;wt¡1;xt¡1
¢+PFPGt; (6)
where
PFPGt =£VR (pt;yt;pt¡1;yt¡1)¡ VC
¡wt; xt;wt¡1; xt¡1
¢¤(7)
is partial factor productivity growth. The formulas for the price change
indicators in (6) are given by (4a) and by (5a). The formulas for the quantitychange indicators in (7) are given by (4b) and by (5b).
Expression (6) shows that a change in nominal NFI between year t ¡ 1and year t can be decomposed into three parts: (i) the change in the outputprice component; less (ii) the change in the input price component; plus (iii)partial factor productivity growth. All of the components are measured innominal dollars – this means that the productivity measure PFPGt is thedollar value contribution to nominal NFI from partial factor productivitygrowth.
Note that expression (6) is the same as that for a single Bennet indi-cator of overall quantity change when production is cast in a net output
7
framework – see [5, pp. 5-6]. Expression (6) is also much the same as theexpression for the decomposition of pro…t given in [12, pp. 32-33], once thegross productivity and scale impacts given there are combined and termsare eliminated. With the decompositions in [5] and [12], however, the mea-sure of productivity change is TFPG, rather than PFPG, since pro…t is thedollar amount of revenue in excess of the opportunity cost of all inputs.Where owners of …rms pay a wage or salary to operators (e.g., as in a cor-poration with common shareholders), such ‘pure pro…t’ can exist, since it isdisbursed as dividends to the owners once all inputs are assigned a price inthe …rm’s accounts. To measure the change in returns to a residual claimantor claimants, and to decompose this change, expression (6) is therefore moreappropriate than the decomposition formulas in [12] or [5].
Similar decompositions to (6) can also be found in [9] and in [15]. Thesestudies, however, not only allow for pure pro…t, but also treat the change in
net income as the ratio of net income in year t to that in year t¡ 1; i.e. theyuse the ratio Ft=Ft¡1 – see [9, p. 3] and [15, p. 4]. Finally, an approachsimilar in spirit to (6) was applied in [3], but in relation to a measure called‘normal income’.
The measure of productivity growth (7) is partial because the indicator ofinput quantity change excludes the change in use of the residual claimant(s)input. Partial factor productivity growth (PFPG) can be related to otherproductivity measures such as labour productivity growth and total factorproductivity growth.
When there is only one residual claimant (the Nth input), the implicitprice for this input is estimated as:9;10
9As noted earlier, in analyses of the non-agricultural sector, capital is often the residual
claimant. In this case, the residual can be related to a cost of capital formula and therebyused to compute an ‘internal rate of return’ – see [10, p. 346],[13, p. 14].10 The real implicit wage need not be positive. For example, the data presented in Figure
1 show that real NFI was negative over the period 1981-1984. An interpretation of thisis that, over this period, operators and their families, acting as farm-household members,received a ‘negative wage’ from the labour they supplied to their farms – in reality thismeans that they had to use other forms of farm-household income to meet the cost of theother N ¡1 farm inputs, and that they also received no wage at all. It would appear thateven this form of subsidization of the farm by farm families was insu¢cient to prevent theexit of many farms. Although bankruptcy data for this period do not exist, there is littledoubt that farm bankruptcies were very common in the U.S. between 1981 and 1984. Theearly to mid-1980’s have been referred to as the “second episode of concern about farmerbankruptcies in the 20th century” [18, pp. 13], i.e., that in terms of farm …nancial stress,
8
wIN;t = Ft=xN;t . (8)
Where this Nth input is operator and unpaid family labour, xN;t is thequantity of labour (measured as hours of work) supplied to the farm by theoperator and his/her family members, and wIN;t is the implicit wage thatthey receive. In other words it is the ‘take-home pay’ from the labour thatthey supply to the farm.
To compare movements inwIN;tover time, the implicit wage must be con-
verted into real terms, using an appropriate de‡ator. De‡ation of wIN;t witha consumer price index (CPI) allows the wage to be related to its spend-ing power in purchasing consumer goods to be used by the farm household.De…ne the real implicit wage as
wIRN;t = (Ft=ht)=xN;t ; (9)
where ht is a CPI (with base year b; where hb = 1):
To link the decomposition (6) to changes in the real implicit wage (9),…rst note that the change in the real wage between any two years t¡ 1 andt is
wIRGN;t = (Ft=ht)=xN;t ¡ (Ft¡1=ht¡1) =xN;t¡1 : (10)
Expression (10) can be related to FGt in (6) as follows. Add Ft¡1= (htxN;t)¡Ft¡1= (htxN;t) to the right-hand side of (10) to get
wIRGN;t = Ft=htxN;t ¡ Ft¡1=htxN;t¡ (11)
[Ft¡1= (ht¡1xN;t¡1)¡Ft¡1= (htxN;t)] :
Note that
Ft¡1= (htxN;t)´ wIRN;t¡1 (ht¡1xN;t¡1) =(htxN;t) :
With this equivalence and some rearrangement, (11) can be re-expressed as
this period was second only to the years immediately following the Great Depression.The subsidization of farm operations by the farm household appears to have been im-
portant in other years as well, although this is not evident from the aggregate data. Forexample, in 1997, 60% of farm households appear to have made net contributions to thefarm business [14, p. 34].
9
wIRGN;t = FGt = (htxN;t) ¡w
IRN;t¡1 [1¡ (ht¡1=ht) (xN;t¡1=xN;t)] : (12)
The …rst term on the right-hand side of (12) is the change in nominalNFI between t ¡ 1 and t; converted into real dollars per hour of operatorand unpaid family labour supplied in year t – this can be viewed as theincremental change in the real implicit wage due to a change in nominal NFI.The second term on the right-hand side of (12) – the ‘CPI-hours factor’ –captures the e¤ect on a change in the real implicit wage from changes inthe CPI (in‡ation) and from changes in the number of hours supplied tothe farm by the operator and his/her family. The ratio ht¡1=ht is less thanone when there is positive in‡ation; when there is no change in any other
right-hand side variable, this means that the real implicit wage decreases.Similarly, when the ratio xN;t¡1=xN;t is less than one, the operator andfamily members that work on the farm have increased their labour input.Again, when there is no change in any other right-hand side variable, thisincrease in hours of work means that the real implicit wage is lower than itotherwise would have been.
The relationship between the decomposition of a change in nominal NFIand changes in the real implicit wage can now be determined. Substitute(6) into (12) to get:
wIRGN;t = IR (pt;yt;pt¡1;yt¡1)= (htxN;t)¡ (13)
IC¡wt; xt;wt¡1; xt¡1
¢= (htxN;t) +PFPGt=(htxN;t)¡
wIRN;t¡1 [1¡ (ht¡1=ht) (xN;t¡1=xN;t)] :
There are four components to this decomposition. These components are,in real dollars per hour: (i) an output price change component; (ii) aninput price change component; (iii) a partial factor productivity growthcomponent; and (iv) a CPI-hours component.
10
4 Data
The data are comprised of M = 10 outputs and N = 7 inputs, for the years1948-2002. The outputs and inputs (with indicator numbers) are listedin Table 1. Nine of the ten outputs are aggregates of commodities andcommodity groups that are broadly representative of the crops and livestockcomposition of U.S. agriculture. The tenth – secondary output – refersto output that is not agricultural in nature, but that is produced using
the farm’s resources. Examples would be machine and labour services andrecreation services (tours, etc.). Further details about both the output andthe input data de…nitions are given in Appendix A.
Of the seven input aggregates, the last (the Nth) is operator and unpaidfamily labour. Inputs 1-6 are the ‘N ¡ H’ inputs, and these cover themain input categories: ‘capital excluding land’ (machinery, buildings andother non-land capital); ‘land’ (a quality-adjusted measure of land input);hired labour; farm-produced inputs (agricultural outputs that are also usedas inputs, for example feed produced and used on the farm); purchasedmaterials (from outside the agricultural sector, such as feed concentrate,fuel, etc.); and purchased services (custom harvesting, veterinarian services,etc.).
The series pi;t; yi;t (i = 1;2; : : : ; 10); the serieswj;t; xj;t (j = 1;2; : : : ; 6); theseries x7;t – the hours of operator and unpaid family labour – and the series
ht (CPI) are given in Appendix A, Table A1 and Table A2 – these seriescomprise the raw data.
Both output and input mix in U.S. agriculture changed substantiallybetween 1948 and 2002. To illustrate this, it is helpful to create Fisher idealimplicit quantity indexes for crops and livestock, using the …ve individualcrop aggregates (i = 1¡ 5) and four individual livestock aggregates (i =6¡9) respectively. A third quantity index, that for all outputs, provides thedenominator. Denote the crop quantity index as yCt ; the livestock quantityindex as yLt and the total output quantity index as yt. Estimation of log-linear trends with the ratios yCrt = yCt =yt; y
Lrt = yLt =yt and y
Srt = y10;t=yt
indicate that the livestock output share fell by about 0.4% each year between1948 and 2002.11
11 These growth rates were estimated using an exponential trend equation of the formln(ykrt )=®
k + ¯kt – where k = C;L; S). Since autocorrelation was present in all threeequations, a …rst-order autoregression was estimated for livestock and secondary output,and a second-order autoregression for crops.
11
Table 1. Output and Input Coverage in the NFI Decomposition Database
OUTPUTS INPUTS
Crop Aggregates1. Grain and Forage Crops
2. Industrial Crops
3.Vegetables
4. Fruits and Tree Nuts
5. Other Crops1
Livestock Aggregates6. Meat Animals
7. Poultry and Eggs
8. Dairy
9. Miscellaneous Livestock
Other Aggregates10. Secondary Output2
1. Capital excluding Land
2. Land
3. Hired Labour
4. Farm-Produced Inputs3
5. Purchased Materials4
6. Purchased Services
7. Unpaid Operator and Family Labour
1 Horticulture, potatoes and fruit, vegetables produced using farm resources but consumed by the
farm family.
2 Output from activities that are not related to crop or livestock production and that use the farm’s
resources to do this. Examples are value-added activities such as packaging/processing and the
provision of services related to agricultural production, such as custom harvesting.
3 Agricultural outputs that are produced on farm but also used as inputs, for example feed
produced and used on the farm.
4 Purchased from outside the agricultural sector.
12
Over the same period, there was no statistically signi…cant change in theshare of crops, but the share of secondary output grew by about 1.6% peryear. These results indicate that there were substantial changes in compo-sition of agricultural output over the period, with livestock activities givingway to crops and to secondary agricultural outputs.
A similar analysis of input/output ratios captures the degree to whichinput intensities have changed both between inputs and over time. Esti-mated coe¢cients from log-linear trend equations show annual reductionsof input intensities for capital (-1.0%), land (-2.4%), hired labour (-3.7%),farm-produced inputs (-1.9% ) and services (-0.6%), while the intensity ofpurchased materials actually increased at an average annual rate of about0.4%.12;13 Together with the results for outputs, these calculations showthat the composition of U.S. agricultural output and the mix of inputs usedin production has changed substantially since the late 1940’s. While this is
a well-known fact, these …gures lend precision to the generality that ‘thingshave changed’.
The raw data are used to derive Ft;Ft¡1; and FGt ; to calculate the arith-
metic means ymi;t ; pmi;t ; for each i and the arithmeticmeans x
mj;t ;w
mj;t for each j.
Due to the lag needed to compute changes, all these derived data (other thanF1948) cover the years t = 1949;1950; ¢ ¢ ¢2002: These data are then used withthe raw data to compute values for the Bennet aggregate output and inputprice change indicators – IR (pt; yt;pt¡1;yt¡1) and IC
¡wt;xt;wt¡1;xt¡1
¢respectively – and the Bennet aggregate output and input quantity changeindicators VR (pt; yt;pt¡1; yt¡1)and VC
¡wt;xt;wt¡1;xt¡1
¢respectively:The
nominal implicit wage wI7;t is computed using the derived series Ft along with
the series x7;t and ht; the derived nominal implicit wage series is then used,along with the raw and other derived data to compute the growth in realimplicit wage wIRG
7;t series:
12 The same method used for output trends is employed here. Since autocorrelationwas present in the equations for all inputs, …rst-order autoregressions were estimated forall six inputs and second-order autoregressions were estimated for capital and purchasedmaterials. Note that the mean of annual growth rates and the estimated compound growthrate is similar to the estimated trend rate in all cases.13 These results can also be related to partial factor productivity growth rates, where
H = 1 in each case. Average annual partial factor productivity growth rates by inputwere as follows: capital, 1.0%; land, 2.2%; hired labour, 3.6%; farm-produced inputs,1.8%; purchased inputs -0.6%; purchased services, 0.4%. Only purchased inputs displayednegative partial productivity growth.
13
Figure 2 presents the derived real implicit wage between 1948 and 2002.In contrast with real net farm income, the real implicit wage did not displaya noticeable trend; on average, it decreased by only 6 cents/hour each year.There was, however, substantial year-to-year variation – variability aroundthe mean real implicit wage of $8.31/hour can be divided into …ve distinctsub-periods (see Figure 3). For 1948-1964, 1980-1985 and 1999-2002 theaverage real implicit wage was consistently below the mean, at $6.29/hour,-1.76/hour and $5.43/hour respectively. In the two sub-periods 1965-1979and 1986-1998, the average real implicit wage was consistently above themean, at $11.98 and $12.28 respectively. These …ve sub-periods, since theyso clearly de…ne ‘above-average’ and ‘below-average’ income performance,will be useful in summarizing the decomposition results that follow in thenext section.
Based on these data, farm income – expressed as a real implicit wage– has shown a lack of growth, but has not displayed the steady declineindicated by the aggregate net farm income data (as illustrated in Figure1). This suggests that a re-phrasing of the farm problem is needed, relativeto the language used in the Introduction. In particular, it may be moreappropriate to express the farm problem as ‘a lack of growth in the realimplicit wage, in spite of positive productivity growth’, and to analyze the
data in this context.
5 Results
Together, the raw and derived data described above provide all of the infor-mation needed to compute the decomposition (13) for the period 1949-2002.The results of these computations are summarized in Table 2 – the completeresults are given in Table B1.
The data in column (A) of Table 2 are average values for the derivedseries wIRG
7;t . The series in columns (B)-(E) are average annual values forseries derived using (13), with the following concordance:
(B) IR (pt;yt;pt¡1;yt¡1)= (htxN;t) ;
(C) ¡ IC¡wt;xt;wt¡1;xt¡1
¢= (htxN;t) ;
(D) PFPGt= (htxN;t) ; and
(E) ¡ wIRN;t¡1 [1¡ (ht¡1=ht) (xN;t¡1=xN;t)] :
14
Figure 2. Real Implicit Wage for Operator/ Unpaid Family Labour, U.S. Agriculture, 1948-2002
-10
-5
0
5
10
15
20
25
1948 1954 1960 1966 1972 1978 1984 1990 1996 2002
1996
$U
S/h
our
Figure 3. Deviations of Real Implicit Wage from 1948-2002 Average, U.S. Agriculture
-20
-15
-10
-5
0
5
10
15
1948 1954 1960 1966 1972 1978 1984 1990 1996 2002
199
6 $U
S p
er h
our
15
18/0
4/20
07be
nnet
_rea
l_la
b_t3
US
_KLL
EM
S_1
0out
_LA
B.x
ls
Tab
le 2
. Dec
om
po
siti
on
of
Rea
l Im
plic
it W
age
to O
per
ato
r an
d U
np
aid
Fam
ily L
abo
ur,
U.S
. Ag
ricu
ltu
re, 1
949-
2002
ALL
VA
LUE
S A
RE
199
6 D
OLL
AR
S P
ER
HO
UR
re
al im
plic
it w
age
grow
th d
ecom
posi
tion:
ave
rage
ann
ual c
hang
esre
al im
plic
itav
erag
e an
nual
outp
ut p
rice
inpu
t pric
ew
age
at s
tart
chan
ge in
rea
lch
ange
chan
geP
FP
GC
PI-
hour
spe
riod/
of p
erio
d/im
plic
it w
age*
*co
mpo
nent
com
pone
ntco
mpo
nent
fact
orsu
b-pe
riod
sub-
perio
d*(A
)(B
)(C
)(D
)(E
)
1949
-200
27.
53-0
.06
0.75
-1.3
60.
64-0
.09
1949
-196
47.
53-0
.03
-0.1
9-0
.18
0.18
0.17
1965
-197
96.
980.
392.
68-2
.60
0.52
-0.2
119
80-1
985
12.8
3-1
.59
0.29
-3.5
31.
79-0
.14
1986
-199
83.
280.
540.
34-0
.42
0.83
-0.2
219
99-2
002
10.2
7-1
.49
-0.6
5-1
.31
0.63
-0.1
6
* T
his
is th
e le
vel i
n th
e ye
ar p
rior
to th
e st
art o
f the
per
iod/
sub-
perio
d. T
hus,
the
real
impl
icit
wag
e at
the
sta
rt o
f the
194
9-19
64 s
ub-p
erio
d is
the
leve
l in
1948
. **
The
ave
rage
ann
ual c
hang
e is
ave
rage
of y
ear-
over
-yea
r ch
ange
s w
ithin
eac
h pe
riod/
sub-
perio
d.
16
So the sum of the series (B)-(E) equals series (A), where di¤erences aredue only to rounding.
The results – all are average annual changes measured in 1996 dollars –show that the contribution of PFPG to the change in the real implicit wagefor the whole period 1949-2002 was 64 cents/hour, while the output pricechange component was 75 cents/hour. Both of these e¤ects, however, were
negated by the input price change component, which was -$1.36/hour, andto a small negative CPI-hours factor of -9 cents/hour.14 Market conditionstherefore worked against PFPG in elevating the real implicit wage.
The sub-period results in Table 2 illustrate the degree to which therewas variability in the relative magnitude of the three main components,depending upon the direction of change in the real implicit wage. Over the1949-1964 sub-period, output prices decreased – the output price changecomponent was -19 cents/hour – and so, even though the CPI-hours e¤ect
was positive, and there was modest PFPG, the real implicit wage fell by 3cents/hour. For this sub-period, then, the crucial element was the decreasedoutput price.
During the second sub-period, 1965-1979, the real implicit wage in-creased; an important part of this was the positive output price changecomponent. The PFPG component was about three times that in the …rstsub-period as well. The input price change component was large but, evenwith the negative CPI-hours component (due to CPI in‡ation) this only
partially o¤set the output price change and PFPG components.
Between 1980 and 1985, PFPG, at $1.79/hour, was much higher thanin the previous sub-period, but the output price change component, whilepositive, was only 29 cents/hour. Together, these components were insuf-…ciently large to o¤set the input price change and CPI-hours componenttogether.
In the fourth sub-period, 1986-1998, the PFPG component was muchsmaller than in the previous sub-period, but at 83 cents/hour, still higherthan that in the …rst two sub-periods. This did not translate into a similarincrease in the real implicit wage, which increased by 54 cents/hour, because14With few exceptions, there was an annual reduction in the hours of operator and
unpaid family labour over this period and an annual increase in the CPI for all but twoyears. So the negative e¤ect of the CPI-hours component can be fully attributed to CPIin‡ation.
17
the output price change component was only about half that of the combinede¤ect of the input price change and CPI-hours components.
Between 1999 and 2002, the real implicit wage fell by -$1.59/hour. Al-though the PFPG component was smaller than in the two previous sub-periods, at 63 cents/hour it was still larger than that in the …rst two sub-periods. A key reason for the decrease in the real implicit wage was the neg-ative output price component – at -65 cents/hour, this ampli…ed the e¤ect ofinput price change (-$1.31/hour) combined with the CPI-hours component(-16 cents/hour).
Figure 4 summarizes the results by sub-period, comparing the PFPGcomponent with the change in the implicit wage for each period. These re-sults demonstrate that the contribution made by PFPG to the real implicitwage has been substantial, and, although varying between sub-periods, gen-erally increased over time. If one were to look solely at the PFPG numbers,one would expect to …nd non-trivial growth in the real implicit wage over
the same period. Instead, that growth has not occurred; as illustrated inFigure 4, PFPG e¤ects have either been muted (as in the …rst and fourthsub-period) or negated (as in the other three sub-periods).
The largest factor driving this result is the input price component. In3/5 sub-periods, this component was negated or nearly negated the outputprice components. And, in the other two sub-periods, this the input pricecomponent ampli…ed the negative e¤ect of input price changes on the realimplicit wage.
Given the importance of input price changes in the relationship betweenthe real implicit wage and PFPG, the question arises: which were the mostimportant elements to this input price change component?
The calculations underlying the results, namely the individual Bennetindicators of input price change, provide the answer.15 These data showthat the price change indicator for land generally exceeded those for otherinputs. Since the cost of land in the U.S. production account is determinedby the opportunity cost of capital, a large part of the negation of PFPGe¤ects came from increases in the bond rate.
15 The individual input price change indicators underly the results in column (C) ofTable 2 and of Table B1. The interested reader can derive these using the data in TableA2 and expression (5a).
18
Figure 4. Decomposition of Real Implicit Wage Growth,United States Agriculture, 1949-2002
-$2.00
-$1.50
-$1.00
-$0.50
$0.00
$0.50
$1.00
$1.50
$2.00
1949-1964 1965-1979 1980-1985 1986-1998 1999-2002
1996
$U
S p
er h
our
average annual change in real implicit wage average annual PFPG component
19
Purchased materials generally accounted for the second-largest inputprice change indicator, in spite of only modest price increases for this input.This price change aspect of the indicator is important and is a characteristicof the methodology – see (5a). It is possible to have a relatively large pricechange indicator for any input, even if there is only a small price change,providing that the quantity used is large enough. This is especially trueif the input use is increasing – as the trend analysis in the previous sec-tion indicated, purchased materials was the only input used with increasedintensity over the 1949-2002 period.
The third most important Bennet indicator of input price change was forhired labour, which generally ranked behind land and purchased materialsbut ahead of the remaining inputs. When these e¤ects for labour are com-bined with those for land and purchased materials, over 71% of the averageoverall Bennet indicator of input price change is accounted for.
6 Conclusion
One objective of this analysis has been to …nd reasons for an apparent para-dox and one element of the ‘farm problem’, namely that productivity growthin U.S. agriculture has been accompanied by a decline in net farm income(before direct payments). Adjustment for the number of hours worked byoperators and unpaid family members shows that the real implicit wage totheir labour has been fairly stable between 1949 and 2002. Nevertheless,observed partial factor productivity growth has not led to increases in thiswage that would be expected. A Bennet decomposition of growth in the realimplicit wage indicates that market price changes have been an importantfactor in this lack of income growth from productivity improvements.
The results obtained here suggest that the accepted wisdom – namelythat agricultural productivity growth is key to the sector’s prosperity – hasnot taken into account the e¤ect of output and input market price changes
that happen at the same time. These price changes may amplify, mute ornegate potential income gains due to productivity.
In essence, the consequences of productivity growth for net farm incomecannot be evaluated only in a partial manner (i.e. holding all prices …xed).While this analysis does not address the possible relationship between pro-ductivity growth and movements in output and input prices, it is probablethat there is a link, i.e. that the two elements are not independent of each
20
other. For example, adoption of a higher-yielding variety both by U.S. farmoperators and their international competitors may lead to lower internationalprices. Similarly, demand for inputs created by new productivity-increasingvarieties may raise the price of those inputs.
The questions posed by this analysis regarding the relationship betweenproductivity growth and net farm income growth will hopefully stimulatedebate on the subject. The other aspect of the analysis – use of the Ben-net decomposition methodology – may also lead to greater interest in thisstraightforward but powerful tool for economic analysis.
21
References
[1] Ball, V. E., J.-C. Bureau, R. Nehring and A. Somwaru (1997). “Agricul-tural Productivity Revisited”, American Journal of Agricultural Eco-nomics, 79, 1045–1063.
[2] Ball, V.E., F.M. Gollop, A. Kelly-Hawke and G.P. Swinland (1999).“Patterns of State Productivity Growth in the U.S. Farm Sector: Link-ing State and Aggregate Models”, American Journal of AgriculturalEconomics, 81, 164-179.
[3] CSO (1961). “Productivity Measurement in Agriculture”, Economic
Trends, No. 91 (a publication of the Central Statistical O¢ce, U.K.)
[4] Diewert, W.E. (2005). “Index Number Theory Using Di¤erences Ratherthan Ratios”, The American Journal of Economics and Sociology, 64,311-360.
[5] Diewert, W.E. (2000). “Productivity Measurement using Di¤erencesRather Than Ratios”, Discussion Paper 2000/1, School of Economics,University of New South Wales.
[6] Diewert, E., A. Harrison and P. Schreyer (2004). “Cost of Capital Ser-vices in the Production Account”. Paper presented at the meeting ofthe Canberra Group, London, September.
[7] ERS (2002). Agricultural Income and Finance Outlook, AIS-79, Eco-nomic Research Service, United States Department of Agriculture, Sep-tember.
[8] Gardner, B.L. (1992). “Changing Economic Perspectives on the FarmProblem”, Journal of Economic Literature, 30, 62-101.
[9] Gordon, D.V., D.P. Dupont, K.J. Fox and R.Q. Grafton (2003). “Pro…tandPrice E¤ects of Multi-Species Individual Transferable Quotas”, Dis-cussion Paper 2003-08, Department of Economics, University of Cal-gary.
[10] Harper, M.J., E. R. Berndt and D. O. Wood (1989). “Rates of Return
and Capital Aggregation Using Alternative Rental Prices”; in Jorgen-son, D. W. and R. Landau (eds.), Technology and Capital Formation,Cambridge:MIT Press.
22
[11] Hottel, J.B. and B.L. Gardner (1983). “The Rate of Return to In-vestment in Agriculture and Measuring Net Farm Income”, AmericanJournal of Agricultural Economics, 65, 553-557.
[12] Han, S.-H. and Hughes, A. (1999). “Pro…t Composition Analysis: ATechnique for Linking Productivity Measurement & Financial Perfor-mance”, Research and Information Paper TRP 99-5, New South WalesTreasury.
[13] Hulten, C.R. (2001). “Total Factor Productivity: A Short Biography”,in Hulten, C.R., E.R. Dean and M.J. Harper (eds), New Developmentsin Productivity Analysis, Chicago: University of Chicago Press.
[14] Mishra, A.K., H. S. El-Osta, M. J. Morehart, J. D. Johnson, and J.W. Hopkins (2002). “Income, Wealth, and the Economic Well-Being of
Farm Households”, Agricultural Economic Report No. 812, EconomicResearch Service, United States Department of Agriculture
[15] Lawrence, D., W.E. Diewert and K.J. Fox (2004). “The Contribu-tions of Productivity, Price Changes and Firm Size to Productiv-ity”, paper downloaded as a pdf from the worldwide web via the url:
http://www.ipeer.ca/SSHRC.htm
[16] Schnepf, R. (2006). ”The U.S. Farm Economy”, Con-gressional Research Service report RS21970, September6 (available on worldwide web as a pdf …le via the urlhttp://fpc.state.gov/documents/organization/75261.pdf)
[17] Shreyer, P. (2004). “Measuring Multi-Factor Productivity when Ratesof Return are Exogenous”, paper presented at the SSHRC InternationalConference on Index Number Theory and the Measurement of Pricesand Productivity, Vancouver, June 30-July 3. Paper downloaded as pdf
from the worldwide web via the url: http://www.ipeer.ca/SSHRC.htm
[18] Stam, J.M. and B. L. Dixon (2004). “Farmer Bankruptcies and FarmExits in the United States, 1899-2002”, Agriculture Information Bul-letin Number 788, Economic Research Service, United States Depart-ment of Agriculture.
[19] USDA(2000). “Commodity Costs and Returns Estimation Handbook,Report of the AAEA Task Force on Commodity Costs and Re-turns, February (available on worldwide web as a pdf …le via the urlhttp://www.economics.nrcs.usda.gov/care/Aaea).
23
Appendix A. The Data
The data for the aggregates listed in Table 1 were obtained from EldonBall (Economic Research Service). While the output and input variables aredocumented in [1] and at the ERS web site1, the main features of the dataare reiterated here.
The output data underlying the aggregates used here cover over 100 com-modities and commodity aggregates. Output for each commodity was derivedas the quantity sold to the non-farm sector plus net additions to inventory andconsumption by farm-households. Net additions to inventory re‡ect any useof the commodity within farm and transactions between farms (e.g. grain forfeed), since this consumption is assumed to be drawn out of opening stocks;thus, output is measured in gross rather than value-added terms. Price datafor each of these commodities was then used, along with the quantity data,to compute Fisher Ideal indexes for the ten aggregates listed in Table A1.
‘Capital excluding Land’ is an aggregate measure of capital services from:(i) automobiles, trucks, tractors, other farm machinery; (ii) farm structures(excluding residential) and (iii) crop/livestock inventories. Capital stocks forthe various items in (i) and (ii) were constructed using investment data anda hyperbolic decay formula. User costs for these items were also constructedbased on the formula corresponding to hyperbolic decay, which includes theinvestment de‡ators and opportunity cost of capital.
‘Land’ is a quality-adjusted quantity and price index. The quantity indexwas constructed using land area and value data for agricultural districtsacross the United States. The price is an ex ante real bond rate.
‘Hired Labour’ is a quality-adjusted quantity and price index for hiredagricultural labour. Changes in the quality of hired labour over time wereaccounted for using cross-classi…cations based on characteristics such as ageand education. A quantity index for hired labour was then computed usingthe cross-classi…ed data – the aggregation method gives greater weight toan hour of labour from an employee with a higher marginal product (wage)than one with a lower marginal product. The price index was then computedimplicitly as the ratio of total expenditure on hired labour to the quality-adjusted quantity index.
1See the web page www.ers.usda.gov/data/AgProductivity/methods.htm.
124
The ‘Farm-Produced Inputs’ aggregate is a Fisher Ideal index computedusing farm use data for each of the 100 or so outputs produced. These datainclude seed and feed that are drawn from opening stocks and used on-farm.
The ‘Purchased Materials’ and ‘Purchased Services’ aggregates are alsoFisher Ideal indexes constructed using data for a variety of materials and ser-vices purchased from businesses outside of the agricultural sector. Purchasedmaterials include feed, seed and fertilizer purchased from agricultural inputsuppliers. Purchased services include veterinary services, custom machineservices and equipment leasing.
The …nal input category, ‘Unpaid Operator and Family Labour’ is thetotal hours of unpaid work that operators and their families supplied to theirfarming enterprises. These data are not used when computing the input costcomponents of the Bennet decomposition, but do provide the denominatorin (10) when computing the real implicit wage to operator and unpaid familylabour and in computing the ‘CPI-hours in‡ation factor’
The hours of operator and unpaid family labour are also taken from theERS database. The CPI data are from the United States Bureau of LabourStatistics (BLS). The input series, hours of operator/unpaid family labourseries and the CPI series are given in Table A2.
225
18/0
4/20
07da
ta_t
able
.xls
Tab
le A
1.1
Un
ited
Sta
tes
Ag
ricu
ltu
ral O
utp
uts
: C
rop
s, 1
948-
2002
Cro
ps
1. G
rain
/For
age
Cro
ps2.
Ind
ustr
ial C
rops
3.
Ve
ge
tab
les
4. F
ruits
and
Tre
e N
uts
5. O
ther
pric
eim
plic
itpr
ice
imp
licit
pric
eim
plic
itpr
ice
imp
licit
pric
eim
plic
it
Ye
ar
ind
ex
qu
an
tity
ind
ex
qu
an
tity
ind
ex
qu
an
tity
ind
ex
qu
an
tity
ind
ex
qu
an
tity
19
48
0.4
63
29
,36
90
.41
01
3,1
81
0.3
81
8,5
18
0.2
29
4,9
36
0.2
63
2,5
96
19
49
0.4
26
26
,58
50
.36
31
4,0
23
0.3
10
8,5
70
0.2
13
4,3
57
0.2
56
2,7
34
19
50
0.3
83
26
,67
70
.44
41
1,1
08
0.2
84
8,6
66
0.2
76
4,3
10
0.2
39
3,1
78
19
51
0.4
19
25
,89
10
.43
91
4,0
76
0.3
29
7,8
97
0.2
43
4,7
53
0.2
75
2,7
85
19
52
0.4
32
28
,07
80
.42
71
4,0
66
0.4
21
8,2
95
0.2
35
4,6
67
0.2
89
2,6
38
19
53
0.3
99
27
,48
70
.40
81
4,5
60
0.3
04
8,7
80
0.2
51
4,7
77
0.2
58
2,7
30
19
54
0.4
06
27
,38
00
.40
71
3,8
26
0.2
92
8,1
77
0.2
45
4,9
85
0.2
55
2,6
53
19
55
0.3
75
28
,20
10
.37
81
4,7
08
0.3
09
8,3
26
0.2
45
5,2
06
0.2
64
2,3
62
19
56
0.3
61
28
,10
30
.38
41
4,4
33
0.3
45
8,4
92
0.2
62
5,1
88
0.2
62
2,6
29
19
57
0.3
43
29
,82
00
.37
71
2,4
57
0.3
00
8,3
53
0.2
44
5,2
89
0.2
97
2,2
08
19
58
0.3
47
33
,96
70
.37
81
3,7
24
0.3
04
8,5
94
0.2
85
4,8
97
0.2
71
2,4
70
19
59
0.3
33
32
,48
20
.37
81
4,9
32
0.3
07
8,4
58
0.2
84
5,3
22
0.2
64
3,0
77
19
60
0.3
30
35
,10
80
.36
21
5,5
09
0.3
38
8,3
85
0.2
69
5,6
79
0.2
77
3,3
03
19
61
0.3
42
32
,61
10
.40
41
6,4
12
0.2
97
8,8
95
0.2
73
5,8
98
0.2
88
3,2
86
19
62
0.3
89
32
,81
80
.38
91
7,1
11
0.3
08
8,6
25
0.2
62
6,0
21
0.2
72
3,7
07
19
63
0.4
00
34
,54
20
.39
61
7,9
37
0.3
07
8,6
10
0.2
90
5,7
94
0.2
80
3,7
68
19
64
0.3
91
32
,93
70
.38
11
7,6
79
0.3
81
8,0
14
0.3
05
5,9
10
0.2
95
3,6
94
19
65
0.3
93
36
,52
10
.40
51
7,8
08
0.4
31
8,8
61
0.2
67
6,1
86
0.3
10
3,7
12
19
66
0.4
42
36
,49
90
.44
51
6,1
02
0.3
82
8,9
57
0.2
74
6,3
69
0.3
27
3,6
71
19
67
0.3
85
40
,16
80
.46
11
5,1
76
0.3
74
9,0
95
0.2
86
6,3
49
0.3
32
3,7
44
19
68
0.3
72
39
,77
10
.43
01
7,3
32
0.3
78
9,3
83
0.3
28
6,2
33
0.3
42
3,7
79
19
69
0.3
95
40
,20
20
.40
51
8,8
39
0.3
91
9,1
23
0.2
93
7,4
01
0.3
48
3,8
44
19
70
0.4
24
37
,39
00
.44
81
8,0
59
0.3
95
9,2
53
0.2
95
7,0
15
0.3
50
3,9
77
19
71
0.3
99
45
,20
80
.48
81
8,4
59
0.4
03
9,1
85
0.3
16
7,3
03
0.3
65
4,0
89
19
72
0.4
41
43
,90
90
.52
12
0,3
27
0.4
35
9,3
26
0.3
90
6,5
64
0.3
94
4,0
82
19
73
0.6
71
45
,98
60
.73
72
1,8
19
0.5
78
9,3
81
0.4
33
7,9
49
0.4
29
4,5
77
19
74
0.8
78
41
,52
30
.96
81
9,1
26
0.7
11
10
,01
70
.42
28
,14
40
.45
64
,32
9
19
75
0.7
80
48
,39
60
.74
12
1,2
86
0.6
63
9,6
90
0.4
08
8,7
25
0.4
78
5,4
67
19
76
0.7
42
48
,70
50
.80
32
0,0
99
0.6
53
10
,24
00
.43
98
,46
10
.50
15
,68
4
19
77
0.6
51
50
,50
80
.83
72
4,4
05
0.6
58
10
,37
60
.51
58
,94
30
.51
95
,91
8
26
18/0
4/20
07da
ta_t
able
.xls
Tab
le A
1.1
Un
ited
Sta
tes
Ag
ricu
ltu
ral O
utp
uts
: C
rop
s, 1
948-
2002
Cro
ps
1. G
rain
/For
age
Cro
ps2.
Ind
ustr
ial C
rops
3.
Ve
ge
tab
les
4. F
ruits
and
Tre
e N
uts
5. O
ther
pric
eim
plic
itpr
ice
imp
licit
pric
eim
plic
itpr
ice
imp
licit
pric
eim
plic
it
Ye
ar
ind
ex
qu
an
tity
ind
ex
qu
an
tity
ind
ex
qu
an
tity
ind
ex
qu
an
tity
ind
ex
qu
an
tity
19
78
0.6
77
52
,78
20
.88
02
4,2
54
0.6
91
10
,74
50
.65
08
,86
10
.56
57
,72
4
19
79
0.7
45
56
,79
50
.91
42
8,2
35
0.6
90
10
,76
20
.68
29
,47
70
.60
88
,05
6
19
80
0.8
52
51
,70
01
.00
72
3,4
11
0.7
76
10
,64
20
.63
51
0,3
19
0.6
33
8,6
49
19
81
0.8
83
61
,35
70
.97
92
7,4
97
0.9
52
11
,00
70
.65
21
0,1
34
0.6
58
8,7
93
19
82
0.8
56
61
,94
20
.86
32
7,1
11
0.8
55
11
,33
00
.67
41
0,0
90
0.6
66
9,4
50
19
83
1.1
89
42
,98
91
.05
42
0,2
83
0.8
98
11
,24
60
.60
41
0,0
28
0.6
99
9,6
90
19
84
0.9
63
59
,27
61
.04
52
5,2
32
0.9
48
11
,90
60
.67
69
,95
80
.70
31
0,9
50
19
85
0.8
56
63
,03
20
.84
92
6,3
05
0.8
27
12
,34
70
.70
69
,84
40
.71
11
1,3
36
19
86
0.8
15
58
,78
60
.82
32
2,9
42
0.8
22
12
,21
20
.76
29
,51
30
.72
61
2,1
45
19
87
0.7
91
53
,51
80
.82
92
5,6
86
0.8
82
13
,11
50
.74
01
0,8
90
0.7
45
13
,27
0
19
88
0.9
31
41
,78
70
.99
92
3,4
64
0.8
90
12
,52
20
.77
21
1,6
96
0.7
79
13
,72
7
19
89
0.9
08
53
,74
00
.92
92
5,0
30
1.0
37
13
,03
20
.81
81
1,1
91
0.8
33
13
,73
5
19
90
0.8
66
58
,16
20
.91
32
7,0
68
0.9
93
13
,72
40
.85
51
1,0
01
0.8
53
14
,78
6
19
91
0.8
29
53
,79
90
.86
12
9,3
05
0.9
56
14
,09
00
.90
91
0,8
72
0.8
71
15
,15
3
19
92
0.8
27
63
,19
60
.84
42
9,7
17
0.9
30
14
,62
40
.89
41
1,3
55
0.8
81
15
,79
1
19
93
0.8
37
51
,33
80
.89
82
6,8
53
1.0
38
15
,34
60
.84
71
2,1
74
0.9
34
15
,38
4
19
94
0.8
64
63
,69
50
.90
73
3,5
68
0.9
56
17
,29
60
.81
71
2,6
41
0.9
58
15
,94
0
19
95
0.9
55
53
,63
10
.92
02
9,5
67
1.0
93
15
,67
90
.93
71
1,8
17
0.9
78
16
,36
5
19
96
1.0
00
61
,10
81
.00
03
1,6
50
1.0
00
17
,07
21
.00
01
1,9
04
1.0
00
16
,66
9
19
97
0.8
62
61
,98
50
.97
63
4,5
41
1.0
09
16
,55
10
.93
41
4,0
74
1.0
50
17
,16
0
19
98
0.7
61
63
,44
70
.87
73
2,9
62
1.0
53
16
,44
10
.94
21
2,5
45
1.0
63
17
,31
5
19
99
0.7
02
62
,55
00
.79
93
3,2
09
0.9
93
17
,54
10
.88
41
3,4
63
1.0
65
17
,40
3
20
00
0.7
07
62
,67
80
.82
73
3,0
62
1.0
36
17
,77
90
.87
71
4,2
92
1.0
59
18
,53
9
20
01
0.7
26
60
,92
60
.93
63
0,4
57
1.0
55
16
,78
40
.87
21
3,7
90
1.0
59
18
,84
8
20
02
0.7
72
56
,98
60
.73
03
2,1
28
1.1
94
16
,71
30
.91
81
4,2
04
1.0
90
18
,35
3
Not
e: T
he b
ase
year
for
all p
rice
inde
xes
is 1
996.
All
impl
icit
quan
titie
s ar
e M
illio
ns o
f 199
6 D
olla
rs.
Sou
rce:
Uni
ted
Sta
tes
Dep
artm
ent o
f Agr
icul
ture
(U
SD
A),
Eco
nom
ic R
esea
rch
Ser
vice
(E
RS
)C
onta
ct: E
ldon
Bal
l, U
SD
A, E
RS
, Res
ourc
e E
cono
mic
s D
ivis
ion
Roo
m N
4086
, 180
0 M
Stre
et N
W, W
ashi
ngto
n D
C, 2
0036
tele
phon
e: 2
02-6
94-5
601
; em
ail:
ebal
l@er
s.us
da.g
ov
27
18/0
4/20
07da
ta_t
able
.xls
Tab
le A
1.2
Un
ited
Sta
tes
Ag
ricu
ltu
ral O
utp
uts
: L
ives
tock
, Oth
er, 1
948-
2002
Live
stoc
k
6.
Me
at
An
ima
ls7
. P
ou
ltry
an
d E
gg
s8.
Dai
ry9.
Mis
c. L
ives
tock
Sec
onda
ry O
utpu
t
pric
eim
plic
itpr
ice
imp
licit
pric
eim
plic
itpr
ice
imp
licit
pric
eim
plic
it
Ye
ar
ind
ex
qu
an
tity
ind
ex
qu
an
tity
ind
ex
qu
an
tity
ind
ex
qu
an
tity
ind
ex
qu
an
tity
19
48
0.4
40
19
,58
50
.96
53
,25
00
.31
51
6,3
48
0.4
35
57
70
.11
83
,06
9
19
49
0.3
72
20
,61
60
.82
53
,76
80
.25
81
6,8
45
0.3
69
61
30
.12
22
,84
7
19
50
0.4
03
22
,07
40
.69
14
,11
00
.25
41
6,9
04
0.4
01
66
30
.12
52
,62
9
19
51
0.4
77
23
,69
50
.80
14
,50
10
.29
51
6,5
90
0.4
77
83
80
.13
12
,86
3
19
52
0.4
07
24
,18
00
.71
44
,66
10
.31
31
6,6
04
0.4
04
69
20
.13
63
,14
7
19
53
0.3
43
23
,98
00
.74
24
,85
20
.28
11
7,4
34
0.3
42
81
00
.14
03
,26
3
19
54
0.3
42
24
,98
40
.58
25
,17
40
.25
81
7,7
12
0.3
41
82
40
.14
33
,30
7
19
55
0.2
90
26
,29
30
.62
05
,19
70
.26
11
7,8
50
0.2
88
94
00
.14
43
,53
8
19
56
0.2
79
25
,47
40
.55
55
,86
60
.27
01
8,1
58
0.2
80
1,2
74
0.1
51
3,8
23
19
57
0.3
30
24
,58
20
.50
56
,08
50
.27
61
8,1
49
0.3
32
1,1
72
0.1
59
4,4
71
19
58
0.3
98
25
,15
20
.51
86
,47
00
.27
31
7,9
66
0.3
95
81
60
.16
45
,44
0
19
59
0.3
60
27
,00
80
.44
26
,76
90
.27
61
7,7
98
0.3
58
1,0
43
0.1
72
8,2
20
19
60
0.3
44
26
,39
20
.46
37
,10
50
.28
01
7,9
82
0.3
44
1,2
98
0.1
77
8,8
21
19
61
0.3
51
27
,52
00
.41
77
,69
50
.28
21
8,3
87
0.3
50
1,1
82
0.1
80
8,6
51
19
62
0.3
63
28
,01
60
.42
67
,65
20
.27
51
8,4
83
0.3
62
1,1
96
0.1
83
8,4
25
19
63
0.3
38
29
,47
00
.42
87
,80
90
.27
61
8,3
39
0.3
38
1,3
00
0.1
86
8,6
80
19
64
0.3
14
30
,29
70
.41
88
,09
10
.28
01
8,6
16
0.3
16
1,4
88
0.1
91
7,8
42
19
65
0.3
68
28
,78
40
.42
98
,35
90
.28
61
8,2
14
0.3
66
1,1
11
0.1
98
7,8
90
19
66
0.4
23
29
,79
50
.46
98
,84
30
.32
41
7,5
90
0.4
22
1,0
70
0.2
08
7,6
71
19
67
0.3
95
31
,16
50
.39
09
,27
70
.33
91
7,4
27
0.3
93
99
50
.21
97
,95
8
19
68
0.4
04
31
,59
50
.42
38
,98
00
.35
51
7,2
13
0.4
03
1,0
61
0.2
30
7,4
39
19
69
0.4
64
31
,69
30
.47
79
,18
40
.37
21
7,0
57
0.4
62
88
30
.24
37
,02
0
19
70
0.4
80
33
,57
30
.44
49
,56
90
.38
71
7,1
98
0.4
77
76
60
.25
96
,13
5
19
71
0.4
66
34
,03
40
.40
69
,74
10
.39
81
7,4
41
0.4
64
78
90
.28
06
,20
4
19
72
0.5
73
34
,32
90
.41
71
0,0
27
0.4
11
17
,66
00
.57
28
25
0.2
91
6,0
70
19
73
0.7
34
35
,65
20
.71
39
,68
60
.48
41
6,9
89
0.7
33
79
80
.32
16
,49
1
19
74
0.6
34
34
,69
90
.63
99
,73
10
.56
41
7,0
08
0.6
32
78
00
.37
46
,27
1
19
75
0.6
62
31
,49
80
.71
49
,53
50
.59
21
6,9
78
0.6
59
83
20
.40
86
,49
7
19
76
0.6
68
32
,91
50
.70
41
0,1
64
0.6
54
17
,69
10
.66
89
09
0.4
39
6,4
21
19
77
0.6
58
33
,09
90
.69
61
0,3
56
0.6
58
18
,06
40
.65
71
,19
50
.48
46
,38
5
28
18/0
4/20
07da
ta_t
able
.xls
Tab
le A
1.2
Un
ited
Sta
tes
Ag
ricu
ltu
ral O
utp
uts
: L
ives
tock
, Oth
er, 1
948-
2002
Live
stoc
k
6.
Me
at
An
ima
ls7
. P
ou
ltry
an
d E
gg
s8.
Dai
ry9.
Mis
c. L
ives
tock
Sec
onda
ry O
utpu
t
pric
eim
plic
itpr
ice
imp
licit
pric
eim
plic
itpr
ice
imp
licit
pric
eim
plic
it
Ye
ar
ind
ex
qu
an
tity
ind
ex
qu
an
tity
ind
ex
qu
an
tity
ind
ex
qu
an
tity
ind
ex
qu
an
tity
19
78
0.8
81
32
,92
10
.74
71
0,8
52
0.7
18
17
,89
30
.87
91
,02
60
.52
47
,04
4
19
79
1.0
71
33
,67
60
.76
31
1,6
98
0.8
12
18
,18
31
.06
71
,07
50
.59
17
,02
0
19
80
0.9
94
34
,93
90
.77
31
1,8
47
0.8
70
18
,94
40
.99
01
,27
10
.66
36
,15
9
19
81
0.9
64
34
,84
20
.80
81
2,3
13
0.9
30
19
,59
10
.96
01
,45
30
.74
05
,18
9
19
82
0.9
93
33
,52
50
.77
21
2,3
31
0.9
18
19
,98
40
.98
71
,65
60
.75
68
,12
8
19
83
0.9
47
34
,06
50
.80
31
2,4
24
0.8
83
20
,59
30
.94
51
,99
90
.78
18
,49
7
19
84
0.9
59
33
,37
90
.96
11
2,7
47
0.8
74
19
,87
00
.95
82
,17
40
.79
98
,20
7
19
85
0.9
12
33
,31
50
.84
11
3,3
27
0.8
53
21
,07
00
.91
02
,31
50
.77
19
,53
1
19
86
0.9
30
33
,25
40
.91
61
3,8
68
0.8
20
21
,09
20
.92
92
,32
40
.74
89
,09
9
19
87
1.0
57
33
,66
70
.76
31
5,0
85
0.8
33
21
,04
71
.05
62
,29
20
.79
01
0,6
99
19
88
1.0
73
34
,36
40
.83
21
5,4
47
0.8
26
21
,39
51
.07
02
,38
90
.83
91
3,2
21
19
89
1.1
03
34
,30
90
.95
61
6,0
83
0.9
13
21
,23
91
.09
72
,35
10
.87
51
4,3
71
19
90
1.2
33
34
,14
70
.89
31
7,1
19
0.9
27
21
,81
21
.22
42
,15
20
.88
71
4,4
62
19
91
1.1
89
35
,20
10
.84
81
7,8
60
0.8
26
21
,80
91
.18
22
,24
10
.88
01
5,2
52
19
92
1.1
05
35
,54
30
.83
11
8,6
96
0.8
82
22
,29
11
.10
02
,65
10
.88
61
4,9
19
19
93
1.1
76
35
,38
60
.89
01
9,5
12
0.8
61
22
,26
91
.17
12
,66
40
.91
21
5,6
40
19
94
1.0
19
36
,42
30
.90
32
0,4
75
0.8
74
22
,72
11
.02
13
,35
90
.92
21
5,6
75
19
95
0.9
66
36
,77
10
.89
72
1,2
67
0.8
60
22
,98
10
.96
53
,64
40
.93
21
7,3
84
19
96
1.0
00
35
,36
11
.00
02
2,4
55
1.0
00
22
,79
51
.00
03
,61
01
.00
01
5,9
70
19
97
1.0
79
35
,66
30
.97
02
2,9
50
0.9
08
23
,11
21
.07
53
,33
70
.98
81
7,6
99
19
98
0.9
17
36
,70
30
.98
22
3,3
74
1.0
37
23
,29
50
.91
34
,06
30
.91
71
9,9
61
19
99
0.9
29
37
,28
20
.93
82
4,4
13
0.9
64
24
,10
40
.92
54
,21
10
.88
92
1,3
30
20
00
1.0
54
37
,52
20
.87
92
4,8
26
0.8
31
24
,84
21
.04
83
,94
30
.89
72
0,0
05
20
01
0.7
69
39
,92
80
.97
42
5,2
02
1.0
08
24
,52
90
.76
75
,06
20
.92
62
0,8
74
20
02
0.9
51
37
,73
80
.80
42
6,1
79
0.8
17
25
,17
40
.95
04
,07
90
.94
32
0,5
18
Not
e: T
he b
ase
year
for
all p
rice
inde
xes
is 1
996.
All
impl
icit
quan
titie
s ar
e M
illio
ns o
f 199
6 D
olla
rs.
Sou
rce:
Uni
ted
Sta
tes
Dep
artm
ent o
f Agr
icul
ture
(U
SD
A),
Eco
nom
ic R
esea
rch
Ser
vice
(E
RS
)C
onta
ct: E
ldon
Bal
l, U
SD
A, E
RS
, Res
ourc
e E
cono
mic
s D
ivis
ion
Roo
m N
4086
, 180
0 M
Stre
et N
W, W
ashi
ngto
n D
C, 2
0036
tele
phon
e: 2
02-6
94-5
601
; em
ail:
ebal
l@er
s.us
da.g
ov
29
18/0
4/20
07da
ta_t
able
.xls
Tab
le A
2. U
nit
ed S
tate
s A
gri
cult
ura
l In
pu
ts a
nd
Co
nsu
mer
Pri
ce In
dex
, 194
8-20
02
1. C
apita
l exc
l. La
nd2.
Lan
d3.
Hire
d La
bour
4. F
arm
-Pro
duce
d In
puts
5. P
urch
ased
Mat
eria
ls6.
Pur
chas
ed S
ervi
ces
7. O
pera
tor/
Unp
aid
pric
eim
plic
itre
al r
ate
cons
tant
$ v
alue
pric
eim
plic
itpr
ice
impl
icit
pric
eim
plic
itpr
ice
impl
icit
F
amily
Lab
our
CP
IY
ear
inde
xqu
antit
yof
ret
urn
(Mill
ion
$199
6)in
dex
quan
tity
inde
xqu
antit
yin
dex
quan
tity
inde
xqu
antit
y
(m
illio
n ho
urs)
1996
=119
480.
110
18,8
980.
09%
827,
770
0.16
618
,144
0.41
317
,408
0.27
621
,179
0.14
713
,889
17,9
200.
154
1949
0.11
021
,503
0.07
%83
0,62
20.
167
16,8
570.
374
19,8
250.
260
24,0
270.
147
13,5
1617
,766
0.15
219
500.
109
23,9
390.
07%
832,
605
0.16
117
,574
0.32
818
,938
0.25
925
,598
0.14
714
,060
16,4
390.
154
1951
0.12
226
,135
0.08
%83
3,48
20.
172
16,9
680.
372
18,6
300.
278
27,8
600.
158
15,4
1615
,574
0.16
619
520.
126
26,7
160.
08%
833,
014
0.17
416
,579
0.38
918
,810
0.29
327
,844
0.15
916
,450
14,8
120.
169
1953
0.12
928
,812
0.11
%83
1,06
50.
171
16,1
050.
344
19,0
120.
264
28,6
750.
168
15,6
3313
,707
0.17
019
540.
125
29,9
690.
11%
827,
271
0.17
315
,184
0.35
117
,648
0.28
027
,650
0.17
015
,219
13,3
150.
171
1955
0.12
830
,515
0.12
%82
1,15
50.
175
14,9
230.
327
18,0
530.
244
32,0
300.
172
15,8
9213
,538
0.17
119
560.
139
30,9
020.
16%
812,
885
0.19
113
,627
0.31
418
,349
0.23
433
,492
0.18
016
,550
12,8
920.
173
1957
0.15
830
,579
0.26
%80
3,33
70.
209
13,0
730.
295
18,7
180.
230
35,0
050.
187
16,7
7411
,858
0.17
919
580.
165
30,4
050.
30%
794,
053
0.22
013
,169
0.29
520
,904
0.24
635
,120
0.18
817
,725
10,9
960.
184
1959
0.17
730
,672
0.35
%78
6,95
30.
232
12,8
540.
283
20,7
820.
244
36,4
430.
191
20,8
1111
,007
0.18
519
600.
179
31,0
330.
38%
783,
372
0.24
312
,856
0.29
219
,784
0.23
237
,927
0.19
420
,252
10,6
290.
189
1961
0.18
030
,851
0.38
%78
2,15
70.
251
12,7
970.
272
19,7
580.
250
36,9
020.
196
19,9
0710
,060
0.19
119
620.
182
30,7
810.
39%
781,
634
0.26
312
,776
0.30
420
,125
0.25
338
,972
0.19
920
,075
9,75
20.
192
1963
0.18
331
,021
0.38
%78
0,53
60.
270
12,7
540.
325
20,9
160.
261
40,8
120.
201
19,8
329,
344
0.19
519
640.
183
31,4
420.
39%
778,
014
0.30
411
,502
0.31
520
,345
0.25
841
,969
0.20
619
,117
8,83
60.
198
1965
0.18
831
,820
0.41
%77
3,41
30.
332
10,8
280.
316
19,2
290.
265
42,3
890.
210
19,4
788,
628
0.20
119
660.
191
32,7
160.
41%
766,
786
0.37
19,
754
0.36
321
,078
0.27
744
,675
0.21
519
,646
8,04
20.
207
1967
0.20
333
,693
0.51
%75
8,26
80.
404
9,06
20.
324
20,1
160.
277
47,3
710.
225
20,4
427,
578
0.21
319
680.
200
34,9
330.
48%
748,
054
0.43
38,
770
0.30
020
,731
0.26
848
,539
0.23
519
,967
7,20
40.
222
1969
0.21
235
,543
0.57
%73
6,45
60.
458
8,84
60.
317
20,7
300.
262
52,7
570.
247
19,2
826,
942
0.23
419
700.
243
35,9
250.
82%
724,
018
0.47
68,
914
0.34
220
,721
0.27
455
,160
0.26
218
,376
6,75
50.
247
1971
0.25
136
,244
0.87
%71
1,83
60.
482
8,81
50.
344
20,0
960.
283
55,5
830.
281
18,3
166,
592
0.25
819
720.
261
36,7
540.
94%
701,
186
0.49
98,
779
0.36
121
,722
0.29
256
,419
0.29
218
,226
6,49
40.
266
1973
0.29
337
,347
1.22
%69
3,34
10.
580
8,90
90.
553
21,8
070.
392
58,4
370.
312
19,4
326,
478
0.28
319
740.
333
38,9
881.
38%
689,
517
0.63
79,
482
0.77
921
,135
0.48
058
,959
0.35
019
,453
5,70
50.
314
1975
0.31
040
,234
1.00
%69
0,25
90.
680
9,63
00.
723
20,1
930.
556
51,4
380.
389
19,6
865,
625
0.34
319
760.
320
41,1
781.
03%
693,
645
0.75
69,
738
0.72
321
,126
0.56
855
,080
0.41
420
,805
5,48
20.
363
1977
0.37
142
,109
1.63
%69
7,21
80.
829
9,49
90.
642
20,3
160.
588
53,6
960.
448
21,2
765,
302
0.38
619
780.
414
43,1
232.
10%
698,
518
0.91
48,
932
0.62
323
,160
0.59
960
,123
0.48
624
,742
5,05
70.
416
1979
0.49
443
,948
2.78
%69
5,86
70.
957
9,26
80.
692
24,3
960.
677
62,9
220.
537
26,0
584,
809
0.46
319
800.
644
45,8
674.
43%
690,
287
1.00
09,
190
0.82
025
,519
0.77
963
,153
0.59
823
,474
4,67
60.
525
30
18/0
4/20
07da
ta_t
able
.xls
Tab
le A
2. U
nit
ed S
tate
s A
gri
cult
ura
l In
pu
ts a
nd
Co
nsu
mer
Pri
ce In
dex
, 194
8-20
02
1. C
apita
l exc
l. La
nd2.
Lan
d3.
Hire
d La
bour
4. F
arm
-Pro
duce
d In
puts
5. P
urch
ased
Mat
eria
ls6.
Pur
chas
ed S
ervi
ces
7. O
pera
tor/
Unp
aid
pric
eim
plic
itre
al r
ate
cons
tant
$ v
alue
pric
eim
plic
itpr
ice
impl
icit
pric
eim
plic
itpr
ice
impl
icit
F
amily
Lab
our
CP
IY
ear
inde
xqu
antit
yof
ret
urn
(Mill
ion
$199
6)in
dex
quan
tity
inde
xqu
antit
yin
dex
quan
tity
inde
xqu
antit
y
(m
illio
n ho
urs)
1996
=119
810.
830
45,3
726.
41%
683,
459
0.98
29,
148
0.85
323
,570
0.83
860
,266
0.66
322
,296
4,73
40.
579
1982
0.85
844
,784
6.55
%67
7,03
61.
218
8,20
90.
832
25,2
330.
808
57,2
350.
690
24,2
384,
635
0.61
519
830.
914
43,7
526.
82%
672,
248
1.06
39,
068
1.00
826
,172
0.82
157
,307
0.69
923
,842
4,33
20.
635
1984
1.00
541
,757
7.18
%66
8,76
01.
148
8,44
80.
865
21,5
360.
824
58,9
890.
721
22,9
094,
393
0.66
219
850.
912
40,9
335.
46%
665,
889
1.33
67,
357
0.78
722
,144
0.76
856
,175
0.72
323
,464
4,18
40.
686
1986
0.81
938
,537
3.96
%66
2,99
31.
295
7,09
40.
653
21,0
290.
713
58,8
100.
721
21,7
033,
826
0.69
919
870.
865
36,2
914.
11%
659,
500
1.29
87,
254
0.60
619
,949
0.72
857
,663
0.75
422
,373
3,75
20.
724
1988
0.90
535
,021
4.02
%65
5,06
11.
399
7,62
10.
831
18,9
820.
802
59,0
260.
795
22,5
043,
825
0.75
419
890.
907
33,9
843.
66%
650,
162
1.64
46,
996
0.86
016
,678
0.83
858
,987
0.83
924
,066
3,91
00.
790
1990
0.94
033
,335
3.98
%64
5,51
81.
907
7,10
50.
831
19,0
260.
833
62,0
600.
866
23,1
323,
812
0.83
319
910.
924
33,0
003.
87%
641,
963
1.86
87,
151
0.77
419
,319
0.83
263
,414
0.87
324
,270
3,84
50.
868
1992
0.90
432
,152
3.76
%64
0,33
11.
953
6,71
80.
758
18,5
530.
830
62,9
050.
887
23,5
703,
666
0.89
419
930.
919
31,4
823.
91%
641,
154
2.17
16,
592
0.80
318
,402
0.83
665
,403
0.91
826
,559
3,49
50.
921
1994
0.96
530
,523
4.12
%64
3,56
62.
222
6,55
30.
838
18,5
630.
869
66,7
880.
934
27,5
863,
558
0.94
519
950.
996
30,2
284.
40%
646,
468
2.30
97,
165
0.87
719
,192
0.89
469
,042
0.96
028
,748
3,60
60.
971
1996
1.00
029
,348
4.58
%64
8,92
42.
553
6,49
31.
000
17,4
151.
000
65,5
641.
000
27,6
473,
623
1.00
019
971.
030
29,1
864.
90%
650,
124
2.57
06,
833
0.96
517
,838
0.97
270
,494
1.00
429
,291
3,57
61.
023
1998
1.01
428
,983
4.71
%64
9,61
62.
683
6,96
00.
839
18,2
370.
880
75,7
290.
990
30,8
593,
402
1.03
919
991.
123
28,8
856.
11%
647,
387
2.66
47,
299
0.73
319
,133
0.85
176
,910
0.99
331
,742
3,47
91.
062
2000
1.15
928
,678
6.38
%64
3,76
72.
537
6,92
10.
745
18,3
560.
904
73,5
321.
035
29,9
803,
404
1.09
820
011.
119
28,6
225.
77%
639,
096
2.72
56,
854
0.82
317
,256
0.93
473
,487
1.06
930
,630
3,35
91.
129
2002
1.13
428
,698
5.99
%63
3,77
12.
844
6,83
70.
864
16,8
640.
929
74,5
181.
084
28,6
133,
330
1.14
7
Not
e 1:
The
bas
e ye
ar fo
r al
l pric
e in
dexe
s is
199
6. A
ll im
plic
it qu
antit
ies
are
Mill
ions
of 1
996
Dol
lars
.In
put D
ata
Sou
rce:
Uni
ted
Sta
tes
Dep
artm
ent o
f Agr
icul
ture
(U
SD
A),
Eco
nom
ic R
esea
rch
Ser
vice
(E
RS
)In
put D
ata
Con
tact
: Eld
on B
all,
US
DA
, ER
S, R
esou
rce
Eco
nom
ics
Div
isio
n, R
oom
N40
86, 1
800
M S
tree
t NW
, Was
hing
ton
DC
, 200
36.
Tel
epho
ne:
202-
694-
5601
; em
ail:
ebal
l@er
s.us
da.g
oC
PI S
ourc
e: U
nite
d S
tate
s D
epar
tmen
t of L
abor
, Bur
eau
of L
abou
r S
tatis
tics
(BLS
)N
ote
2: C
PI d
ata
data
obt
aine
d by
follo
win
g th
e m
enu
star
ting
from
http
://st
ats.
bls.
gov/
cpi/h
ome.
htm
#dat
a. T
he s
peci
fics
of th
e se
ries
are:
S
erie
s Id
CU
UR
0000
SA
0, N
ot S
easo
nally
Adj
uste
d, U
.S. c
ity a
vera
ge, A
ll ite
ms,
Bas
e P
erio
d: 1
982-
84=
100
31
US
_KLL
EM
S_1
0out
_LA
B.x
lsbe
nnet
_rea
l_la
b_t2
18/0
4/20
07
Tab
le B
1. D
eco
mp
osi
tio
n o
f R
eal I
mp
licit
Wag
e to
Op
erat
or
and
Un
pai
d F
amily
Lab
ou
r, U
.S. A
gri
cult
ure
, 194
9-20
02A
LL V
ALU
ES
AR
E 1
996
DO
LLA
RS
PE
R H
OU
R
im
plic
it w
age
grow
th d
ecom
posi
tion*
real
chan
ge in
impl
icit
real
impl
icit
outp
ut p
rice
inpu
t pric
epr
oduc
tivity
CP
I-ho
urs
wag
ew
age*
grow
th c
ompo
nent
grow
th c
ompo
nent
grow
th c
ompo
nent
fact
orye
arpe
r ho
ur(A
)(B
)(C
)(D
)(E
)
1948
7.53
-
-
-
-
1949
5.55
-1.9
8-1
.94
0.43
-0.6
30.
1619
506.
030.
48-0
.01
0.41
-0.2
90.
3719
517.
051.
011.
60-0
.81
0.36
-0.1
319
527.
04-0
.01
-0.3
4-0
.33
0.44
0.22
1953
6.36
-0.6
8-1
.80
0.52
0.09
0.51
1954
6.19
-0.1
7-0
.51
-0.2
30.
430.
1419
555.
60-0
.59
-0.9
80.
55-0
.08
-0.0
819
565.
40-0
.19
-0.1
7-0
.22
0.00
0.19
1957
4.85
-0.5
50.
10-0
.60
-0.3
30.
2819
586.
261.
411.
04-0
.61
0.75
0.24
1959
5.34
-0.9
2-0
.92
-0.3
00.
35-0
.05
1960
5.82
0.48
-0.1
6-0
.15
0.69
0.10
1961
6.63
0.81
0.37
-0.2
40.
410.
2719
627.
000.
370.
85-0
.59
-0.0
40.
1419
637.
210.
21-0
.01
-0.4
70.
480.
2119
646.
98-0
.23
-0.2
9-0
.11
-0.1
40.
3219
658.
871.
881.
52-0
.60
0.91
0.05
1966
10.1
61.
292.
99-1
.27
-0.8
10.
3819
678.
83-1
.33
-1.9
8-0
.52
0.88
0.30
1968
9.76
0.93
0.18
0.48
0.19
0.09
1969
10.5
90.
821.
98-0
.95
-0.0
4-0
.16
1970
8.47
-2.1
11.
54-2
.70
-0.6
6-0
.30
1971
9.44
0.97
-0.3
3-0
.96
2.41
-0.1
519
7212
.32
2.89
4.39
-1.1
9-0
.16
-0.1
619
7319
.67
7.34
14.6
1-7
.74
1.16
-0.6
919
7415
.64
-4.0
36.
99-7
.75
-3.7
20.
4519
7515
.67
0.04
-3.7
0-0
.34
5.18
-1.1
019
7613
.51
-2.1
60.
57-1
.23
-1.0
3-0
.47
32
US
_KLL
EM
S_1
0out
_LA
B.x
lsbe
nnet
_rea
l_la
b_t2
18/0
4/20
07
Tab
le B
1. D
eco
mp
osi
tio
n o
f R
eal I
mp
licit
Wag
e to
Op
erat
or
and
Un
pai
d F
amily
Lab
ou
r, U
.S. A
gri
cult
ure
, 194
9-20
02A
LL V
ALU
ES
AR
E 1
996
DO
LLA
RS
PE
R H
OU
R
im
plic
it w
age
grow
th d
ecom
posi
tion*
real
chan
ge in
impl
icit
real
impl
icit
outp
ut p
rice
inpu
t pric
epr
oduc
tivity
CP
I-ho
urs
wag
ew
age*
grow
th c
ompo
nent
grow
th c
ompo
nent
grow
th c
ompo
nent
fact
orye
arpe
r ho
ur(A
)(B
)(C
)(D
)(E
)
1977
11.5
0-2
.01
-1.4
7-3
.50
3.35
-0.3
919
7812
.38
0.88
6.53
-3.3
2-2
.04
-0.2
919
7912
.83
0.45
6.35
-7.3
62.
15-0
.69
1980
0.06
-12.
763.
18-1
2.09
-2.6
5-1
.20
1981
-1.8
1-1
.88
1.53
-10.
176.
77-0
.01
1982
-3.0
2-1
.21
-1.8
0-0
.90
1.42
0.07
1983
-7.7
0-4
.68
7.41
-3.0
7-8
.91
-0.1
119
84-1
.38
6.32
-2.7
6-1
.50
10.1
60.
4219
853.
284.
66-5
.80
6.52
3.96
-0.0
219
869.
185.
90-0
.63
7.54
-1.2
50.
2419
8710
.96
1.78
0.95
-1.2
72.
24-0
.15
1988
8.52
-2.4
34.
79-3
.87
-2.7
2-0
.64
1989
14.1
95.
671.
87-1
.04
5.40
-0.5
719
9014
.38
0.20
0.47
-1.5
31.
64-0
.38
1991
11.9
6-2
.42
-2.3
70.
77-0
.12
-0.7
019
9215
.91
3.95
-0.9
70.
264.
450.
2219
9312
.77
-3.1
52.
43-1
.53
-4.3
40.
3019
9415
.18
2.42
-1.4
7-1
.89
6.32
-0.5
419
9510
.11
-5.0
72.
10-1
.85
-4.7
0-0
.62
1996
14.4
44.
333.
48-3
.72
4.90
-0.3
319
9711
.81
-2.6
4-2
.49
-0.1
70.
16-0
.14
1998
10.2
7-1
.53
-3.7
12.
90-1
.14
0.42
1999
5.30
-4.9
7-2
.94
-2.1
30.
55-0
.45
2000
6.21
0.91
0.63
-2.0
12.
34-0
.06
2001
5.93
-0.2
8-0
.01
-0.2
10.
03-0
.09
2002
4.30
-1.6
3-0
.27
-0.9
0-0
.42
-0.0
4
aver
age
1948
-200
28.
31-0
.06
0.75
-1.3
60.
64-0
.09
* N
ote
that
thes
e ar
e al
l cha
nges
in r
elat
ive
to th
e pr
evio
us y
ear.
33
