metadata: authors: 0: author: Just, Richard
count: Mexico,United States
docna: 0: docna: Analyzing the effects of U.S. macroeconomic
            policy on U.S. agriculture using the USAGMKTS model
docty: Policy Research Working Paper
subtopic: Consumption,Fiscal & Monetary Policy,Livestock and Animal Husbandry,Public Sector Economics,Food Security,Inflation,Public Finance Decentralization and
            Poverty Reduction
teratopic: International Economics and Trade
abstracts: cdata!: This report describes the results of
            simulating effects of U.S. macroeconomic policy on U.S.
            agriculture using the USAGMKTS model.  The primary purpose
            for which the USAGMKTS model was developed is to determine
            the effects of potential changes in U.S. policy on the
            border prices of corn, sorghum, and soybeans.  The USAGMKTS
            model is a member of a set of interlinked models at
            macroeconomic and sectoral levels of Mexico and the U.S.
            (with enough specification of the rest of the world to close
            the system).  The effects of macroeconomic policy variables
            on macroeconomic variables affecting the agricultural sector
            are derived from the FAIRMODEL of the U.S. macroeconomy.
            These results will be used later to determine the effects of
            U.S. agricultural and macroeconomic policies on Mexican
            agriculture using the MEXAGMKTS model.
geo_reg_key: 119228,517191
repnme: repnme: Analyzing the effects of U.S. macroeconomic
            policy on U.S. agriculture using the USAGMKTS model
display_title: Analyzing the effects of U.S.
            macroeconomic policy on U.S. agriculture using the USAGMKTS model
listing_relative_url: /research/1990/07/700228/analyzing-effects-macroeconomic-policy-agriculture-using-usagmkts-model
topicv3: Agriculture and Food Security m1326205 435,Inflation m1326709 0870F4727ACED1CF8525815C00471347,Treasury m1327009 1045,Macroeconomic and Structural Policies
            m1327380 439,Livestock m1504490 4024
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: International Economics and Trade
origu: Policy, Research & Ect Affairs
no_of_pages: 39
model_extractions: **Policy, Research, and Fxternal Affairs**

# **Agricultural Policies**

# WPS 449

This paper - a product of the Agricultural Policics Division, Agriculture and Rural Development Department - is part of a larger clfon in PRE to understand thc dependencc of domestic agricultural markets on domestic macroecononmic policy anid the macrocconomic and trade policies of major trading partners. Copies are available free from the World Bank, 18 18 H Street NW, Washington **DC** 20433. Please contact Cicely Spooner, room N8-035, cxtension 30464 (34 pages with taibles).

T'he USAGMKTS model was developed to determine the cffects of potential changes in U.S. policy on the border prices of com, sorghum, and soybeans.

It is part of a set of intcrlinked macroeconomic and sectoral modcls that linik Mexico and the United States **('*** itli cnoug_ah specification for the rest ol thc world to close tlic system).

The results show that the effects of U.S. macrocconiomic policics on pricing and exports cani be substantial. Recent and pending macroeconomic policy adjustmcnts can change prices 15 pcrccnt or more. Moreover, the rcsponsc depcnds hcavily on current economic circumstances.

This model hielps countries that trade with thC United SItates to sort out the cffect of current cconlomliic circumrstance on U.S. policies.

The macroccoiionoic el-lects ol monclar\ and fiscal policy are estimated using thic FAIRNIODEL model ol thte '.S. nuiciroeconom y.

The PRE \Vorking Paper Serics du1i-mil.lt.> lh1z ,!:r'.> **A** .rk undcr **\Aa** in the Rank's Poolic\. Research, and Extemal Affairs Comrplex .An ohlective ol the eric' **i t** rCtC **lt 1i11e** ii(Tl1gK OUt (qUIk kl **CT\** e I rf)reieritations arc lcss than fully olished. The findings, interpretalions. and cotn l.ins r1 th.>e ;xrs do n1.1i1 re;ln eserlt official Ranlk po)licy.

P IRii.!:t.;S:
Analyzing the Effects of U.S. Macroeconomic Policy on U.S. Agriculture Using the USAGMKTS Model by

# Richard E. Just

# Table of Contents

|Introductin|1|
|---|---|
|The USAGMKTS Model Structure|1|
|The Crop Supply Structure|2|
|The Crop Demand Structure|5|
|The Livestock Supply Structure|7|
|The Meat Demand Structure|8|
|Detailed Specification|9|
|The FAIRMODEL|12|
|Estimated Effects of U.S. Macroeconomic<br>Policy on<br>U.S. Agriculture|14|
|Importance of Agricultural Policy Instruments|21|
|Summary|22|
|Tables|23|
|References|33|
# ANALYSIS OF THE EFFECTS OF U.S. MACROECONOMIC POLI;'

# ON U.S. AGRICULTURE USING THE USAGMKTS MODEL

# Introduction

This report describes the results of simulating effects of U.S. macroeconomnic policy on U.S. agriculture using the USAGMKTS model. The primary purpose for which the USAGMKTS model was developed is to determine the effects of potential changes in UJ.S. policy on the border prices of corn, sorghum, and soybeans. The USAGMKTS model is a member of a **set** of **interlinked** models at macroeconomic and sectoral levels of Mexico and the U.S. (with enough specification of the rest of the world to close the system). The Mexican agricultural model is discussed in the companion **report** by **O'Mara and** Ingco (1989). The effects of macroeconomic policy variables on macroeconomic variables affecting the agricultural sector are derived from t.ne FAIRMODEL of the U.S. macroeconomy (see Fair, 1984). These **results will** be used **later to** determine the effects of U.S. agricultural and macroeconomic policies on Mexican agriculture using the MEXAGMKTS model described by O'Mara and Ingco. The USAGMKTS Model Structure The USAGMKTS model is composed of several market components. The grain demand component disaggregates demands for feed grains and soybeans by consumption, market inventory, and exports following the specifications of Just and Chambers (1981). Demand for government stocks and the farmer owned reserve for feed grains follows the work of Rausser (1985) and Love (1987) with somewhat more structure to reflect the qualitative nature of policy instruments. Livestock supply is composed of three components corresponding to beef, pork, and poultry with each containing equations for livestock inventories, numbers on fees, and meat production. The meat demand component includes consumption demand equations for beef, pork, and broilers. The structure of the livestock model follows along lines used by Just (1981) with

**1**
revisions to incorporate some refinements developed by Rausser and Love. The grain supply com-onent uses logit equations to represent participation in the feed grain program following the spirit of the work by Chambers and Foster (1983) and later empiricized by Rausser and Love. The acreage equations in particular depart signiticantly from previous econometric practice and incorporate important aspects of the structural relationships among import, at program and market variables in the spirit of the intuitive and conceptual framework developed by Gardner (1988) and LiL.s (1988). The crop supply models are estimated using annual data while the crop demand models and meat supply and demand models are estimated using quarterly data.

The CroR Supply Structure The basic form of the acreage equations is as follows. First, acreage in a market free of government programs is assumed to follow (1) Af - Af(Wn,x,,Af'_l) where

- Af - free market acreage of the crop in question

- anticipated short-run profit per acre from production of the crop in question with free market price

- =a -anticipated short-run profit per acre from production of competing crop(s)

Af 1 - lagged free market acreage (to represent production fixities, etc.). Profit per acr_ is defined by price times yield less per acre production cost, e.g., (2) 7r n P. Y, - C where

- P. market price

- Ya- expected yield

2
C - **short-run cost per acre.** When government programs are voluntary,<sup>the nonparticipating component</sup> of acreage is assumed to follow equation<sup>(1) on the nonparticipating</sup> proportion of the acreage so nonparticipating<sup>acreage is</sup> (3) An - (1 - *) Af(xfn,,,aAf..l) where A,- nonparticipating acreage

- rate of participation in the reLevant government<sup>progr.~.n.</sup> The participating acreage is largely<sup>determined by program limt,ations with</sup> (4) Ap - B (1 - 0 9) - D(Ga)

where B - program base acreage 9 - minimum diversion 1 quirement for participation D - additional diversion beyond the minimum _Ga,_ payment per acre for additional diversion.

The estimating equation for observed total<sup>acreage given the participation</sup> level is obtained by combining (3)<sup>and (4),</sup> (5) At - B X (I - 9) - D(Ga) + (1 - 0) A,(ln,7a,Af .), where D( ) and Af( ) follow linear specifications.

Determining the level of participation in<sup>this framework is crucial.</sup> Each farmer is assumed to participate if his/her<sup>perceived profit per acre is</sup> greater under participacion than under nonparticipation<sup>ir-</sup> > n. Assuming that individual perceived profits differ from<sup>an aggregate bv an amount</sup> characterized by an appropriate random distribution<sup>across farmers, the</sup> participation rate can be represented by a logistic<sup>relationship with</sup> 3
> (6) ln i- = **4 *(Xno**

where sp - :he profi. per acre under compliance.

Given the qualitative nature of numerous agricultural policy instruments, a conceptually plausible specification of short-run profit per unit **of land (producing plus diverted) on complying farms follows** (7) **rp** - (1 **I** - - + **_-G,_** _+_ **-max;Gv, fp)** where p is the maximum proportion of base acreage that can be divarted in addition to minimum diversion, Gm is the payment per unit of land for minimum diversion (zero is no payment is offered for minimum d.version), G, is the payment per unit of land for voluntary diversion beyond the minimum, and X2 is the short-run profit per unit of producing land under compliance. The latter term suggests no voluntary additional diversion if **Gv** < **x,** and voluntary additional diversion to the maximum if Gv < sr.

Conceptually, x, follows (8) _nr_ - 'max(Pt,Pm) Yp + max(Ps,Pm) max(Ya - YP,O) + max(rm - rO)Psa-C where P. is the government target price, YP is the program yield, P, is the price support, rm is the market rate of interest, and rg is the government subsidized rate of interest on commodity loans under the program (Love). Equation (8) reflects the complicated relationship through which a participating farmer is entitled to at least the target price on his program yield, at least the (lower) support price on all of his production, and gains an ddditional interest subsidy on a loan against his stored crop (at harvest time) evaluated at the support price. These benefits must be balanced against the opportunity loss of having to divert some of land from production reflected by equation (7).

4
Once acreage is determined in this framework,<sup>it is simply multiplied by</sup> yield and added to carryin to determine crop supply.<sup>Of course, the</sup> relationships in (7) and (8) do not necessarily apply<sup>exactly. For example,</sup> an uncertain anticipated market price may be discounted<sup>by a farmer compared</sup> to a target or support price which is known with<sup>certainty at the time of</sup> acreage decisions. Also, not all farmers place<sup>their crop under federal loan</sup> to take advantage of the interest subsidy. Nevertheless,<sup>intuition and</sup> experience implies that equations (7) and (8) apply<sup>as reasonable</sup> approximations and, furthermore, the approximations<sup>apply in a global sense.</sup> By comparison, the large number of variables<sup>with numerous qualitative</sup> relationships involved in these relationships suggests<sup>significant problems</sup> with objective econometric identification<sup>of functional form and makes the</sup> possibility of obtaining even plausible signs<sup>remote with estimation of ad hoc</sup> or flexible forms. See Just (1989) for further<sup>details.</sup> The CroD Demand Structure Following numerous previous studies, the<sup>demand for crops is broken into</sup> food, feed, export, and inventory components<sup>for ,:.rposes</sup> of specification and estimation of a quarterly model. The inventory<sup>component is further broken</sup> into farmer owned reserve, government owned, and market<sup>components for crops</sup> with government programs. The demand system<sup>for a given crop is thus of the</sup> form 5
**Qr,t-1** + **Q&.t-j** + Q.,t_j + **At-Y. -** Qi + **Qf** + Q. + Q. + Qs + Q. including the supply-demand identity where

- **Q,** - quantity demanded (z - i for industry or food, z - f for feed, z - x - -

- for export, z r for farmer owned reserve, z g for government -

- stocks, z m for market stocks)

- P,,market price

- X, - exogenous variables which determine the relevant demand

- Y - actual average yield

- Y- - per capita consumer income

- T- - quarterly shift terms

- FJ - numbers of various types of livestock on feed

-

- P, prices of various types of livestock meat

- E - trade weighted exchange rate

Ps - support price

- Pr - release price

D - shift term reflecting the 1983 PIK program.

The demand system was not estimated in the form of (9) because a system that determines price through an identity equation tends to pzoduce erratic price estimates particularly when demands are inelastic. Alternatively, a demand equation in (9) can be solved for price, (10) Pm - Qi (Qi,Xi)I and then the identity can be used to determine Qi. This Approach suffers in practice because the coefficient estimates of exogenous variables in the inverted equation are susceptible to spurious correlations with other factors in the system. This can lead to an unreasonably large contribution of these variables relative to other exogenous variables in the system in determining price predictions in practice. The approach used in this study is to solve 6
the system in (9) for a partial reduced form price equation which is thenl used to replace one of the demand equations in (9). This partial reduced form equation can be regarded as a convex combination of equations such as (10) which essentially produces a composite price forecasting equation in the sense of Johnson and Rausser (1982) where the weigh.. are estimated simultanieously with the coefficients of the price equation. The number of such equations to combine in this manner is roughly determined by the tradeoff between increased forecasting accuracy of combining more forecasting equations and reduced identification as the total number of variables in the composite forecasting equation increases.

To capture the qualitative nature of government market involvement on the demand side, the government inventory demand equation is e'timated including a qualitative relationship between market and support price. For example, the government inventory demand for feed grains equation is of the. form

- - Qs Q.(max(O,(P, Pm>) Qg.-,i D,Tj).

This equation captures the qualitative relationship whereby stocks are not turned over to the government until the market price falls to the government support level but are increasingly turned over as the market price falls below the support (note that only grain -:roduced under voluntary compliance with the program is supported so the market price cati fall below the support price).

The Livestock SuPplV Structure The supply of livestock accounts for the dynamic nature of breeding herd adjustment and the long lags in breeding and raising livestock to market weight. The basic form of the model for each species is as follows. First, a stock equation is included for the size of the national breeding herd of the 7
form

- (11) Hi HI(P,/PI,HI , ir,,T2<sup>)</sup>

- where Hi is herd size for species i (e.g., i cattle), P, is the price of - corn, Pi is the price of meat from species i (e.g., beef for i cattle), and TJ represents quarterly shift terms. Next, an equation is included for numbers on feed of the form

- (12) Fi Fi(Hi,_k,Pc/Pi,Tj)

where k is the number of quarters required to reach feeding age in species i. Finally, a meat production **equz,_'on** is included of the form (13) Mi - Mi(Fi,Hi - Hi l,PC/Pi,r,T )

- where Mi is the production of meat from species i. The term Hi Hi,1<sup>, is</sup> included to capture the addition to meat production caused by culling breeding herds.

The livestock production model consists of a set of equations similar to (1l)-(13) for cattle, hogs, and poultry.

# The Meat Demand Structure

The mLat demand system is considered independently of the crop demand systems since meats and grains are not very closely related except as grain prices affect meat supply. Each demand equation is estimated in price dependent form with P1/Y - Pi(Pj/YC,PO/YC,C;/N,TJ) where Y is per capita income, PJ represents prices of other meats (included individually), PO is a price index for i.-n-farm prices, Ci is domestic consumption of meat i, and N is population. The meat demand system is completed by net import/export equations of the form Ii - Ii(Pi,Ii 1 1<sup>,E,Tj)</sup> where I, is net imports (negative for net exports) and E is a trade weighted 8
# exchange rate **ar.d** identities of the form

Mi + - Ci.

# Detailed SRecificaLion

The structure of the model is evident from the discussion above and the variable definitions given in Tables 1 through 4. Endogenous variables determined in the various components of the USAGMKTS model are listed in Table 1. Exogenous agricultural policy variables are listed in Table 2. Macr)economic variables affecting the USAGMKTS modei are listed in Table 3. These variables are determined endogenously by the FAIRMODEL. Table 4 lists the other exogenous variables which consist of time, population, and a world production variable.

The feed grain supply component ionsists of a logistic equation that explains program participation, an equation that explains nonparticipating feed grain acreage and variation from program acreage (base acreage less minimum diversion requirements) on participating farms, an equation that represents feed grain yield, and an equation that explains how per acre costs of feed grain production respond to feed grain prices. The participation equation follows (6) with a dummy variable added to represent years when diversion was not required to receive program benefits. The acreage equation follows (5) with soybeans as _thu_ competing crop. The yield equation is a simple time trend modified to represent response of yields to diversion which presumably removes poorer acreage from production first. The cost equation specifins cost of production as a function of output price following the arguments of Gardner (1984) whereby the prices of inputs are bid up to exhaust rents. Finally, a production identity is included which expresses production as the product of acreage and yield.

9
**The soybean supply** component **has a** structure **similar** to feed grains except that **no par** :ipation equation **is** included since there has been no voluntary program. Hence, the acreage equation follows the free market form in (1). The yield equation follows a simple time trend with variations in response to feed grain diversion (which presumably removes poorer acreage from soybean as well as corn production) and the ratio of profit per acre for feed grain production to that for soybean production (representing the shift of higher quality land toward the more profitable crop). The structure of the cost-of-production equation and the production identity is the same as for the feed grain supply component.

For purposes of estimation, the demand for feed grains is broken into the demand for feed, industrv, exports, farmer owned reserve, government owned stocks, and feed grain price which implicitly determines free stocks through an identity. Feed demand depends on cattle, hog, and broiler numbers since all three types of livestock are heavy users of corn as well as on the ratio of corn price to meat price. Industry demand is driven primarily bv consumer income and export demand depends heavily on the exchange rate. The demand for farmer owned reserves depends on the support and release prices and the interest rate subsidy with further alterations associated with the payment-in-kind (PIK) program. Government demand for stocks depends on the relationship of market and support prices and on the level of program participation. Market stocks are dU.t rmined by a market supply-demand identity where the major determinants of feed grain prices are stock levels, the exchange rate and world market conditions, and the price of meat.

The soybean demand block contains equations for exports, crushings, and price with inventory determined implicitly by a supply-demand identity. The structure of the export equation is essentially the same as for feed grains.

10
Crushings are determined by livestock numbers, reflecting the feed use of soybean meal, and consumer income, reflecting demand for soybean oil. The major determinants of price are livestock numbers, stocks, world market conditions, and interest rates.

The structure of meat supply follows the earlier generic discussion of livestock supply with breeding-herd, numbers-on-feed, and production equations. The beef supply component has a breeding herd equation driven by the corn-beef price ratio and interest rates, a cattle-placed-on-feed equation driven by lagged breeding herd size and the corn-beef price ratio, and a beef production equation driven by cattle placed on feed, the change in breeding herd size, and the corn-beef price ratio. In addition, an equation is included to explain cattle on feed as a function of cattle placed on feed with appropriate lagging.

The hog supply component has a breeding herd equation driven by the corn-pork price ratio and interest rates, a pig crop equation driven by breeding herd size and the corn-pork price ratio, and a pork production equation driven by the pig crop, the change in breeding herd size, the corn-pork price ratio, and the interest rate.

The poultry supply component has an equation for pullets placed in broiler hatchery flocks driven by previous placements and the corn-broiler price ratio, an equation for broilers hatched depending on the corn-broiler price ratio and hatchery flock size (represented as a linear combination of previous pullet placements), and an equation determining broiler production as a function of broilers hatched and the corn-broiler price ratio.

The meat demand component has three sets of equations. The first is a system of domestic demand equations where each demand equation is represented in price dependent form with each demand depending on the prices of the other 11
two meat types and the price of all other goods. Consumer income is included and homogeneity is imposed by expressing all prices relative to consumer income. The second set of equations determines net trade demand for each meat type as a function of the exchange-rate modified (world) price. The third set of equations are supply-demand equations which close the system.

The exchange rate equation is a simple partially reduced form equation designed to reflect the effects on exchange rates of major changes in macroeconomic policy. Since the major macroeconomic policies of interest are monetary and fiscal policy, the two variables most commonly used as measures of the corresponding effects are included -- the real interest rate and the federal deficit.

# The FAIRMODEL

The FAIRMODEL of the U.S. macroeconomy is described in detail by Fair (1984). The model contains 128 equations consisting of 30 stochastic equations and 98 identities. The specification of these equations bases matcroeconomic phenomena on microeconomic foundations, allows for possible disequilibrium in some of the markets some of the time, and incorporates balance sheet and flow-of-fund constraints explicitly. The data base is quarterly beginning in 1952. The model is estimated by two stage least squares.

The FAIRMODEL consists of six sectors: a household sector, a firm sector, a financial sector, a federal government sector, a state and local government sector, and a foreign sector. The household sector consists of nine stochastic equations including three consumption equations, one residential investment equation, four labor supply equations, and a demand for money equation. Consumption tends to follow the Keynesian paradigm when employment is low but tends to follow the classical paradigm as full 12
**employment is reached.** The demand for money depends on income and the short term **interest rate.**

The firm sector consists of twelve stochastic equations determining production, plant and equipment investment, employment demand, the price level, the wage rate, and the firm sector demand for money. The price level depends heavily on the import price deflator. The demand for money depends on sales and the short term interest rate.

The financial sector contains five stochastic equations determining bank borrowing from the Federal Reserve, the bond interest rate, the mortgage interest rate, the change in stock prices, and the demand for currency.

The federal government sector contains two stochastic equations explaining interest payments by the federal government and the three-month Treasury bill rate. Interest payments are a function of the amount of government securities outstanding and the short and long term interest rates. The three-month Treasury bill rate is determined by inflation, labor market tightness, real growth, and lagged money supply growth. This interest rate is normally endogenous in the model but can alternatively be handled as an exogenous policy instrument.

The state and local government and foreign sectors are simple containing one stochastic equation each. The first has an equation explaining unemployment insurance benefits while the second has an equation explaining demand for imports. Demand for imports follows the standard specification depending on prices and income.

The FAIRMODEL is designed to simnllate a variety of alternative U.S. macroeconomic policy scenarios. Four policy scenarios are selected here to represent a plausible set of alternative adjustments in U.S. macroeconomic policy instruments. They include the following: 13
1. A change in the U.S. Treasury bill rate.

2. A change in U.S. government expenditures.

3. A change in the U.S. personal income tax rate.

4. A change in the U.S. federal deficit.

Each of these alternatives represent major changes that have taken place in the U.S. macroeconomy over the past decade. Conceivably, major adjustments in these policy instruments could again be exercised. For example, the present U.S. federal deficit that is looming so large in political debate in Washington could be resolved by any one or a combination of these measures.

The first step in the calculation of macroeconomic effects on agriculture here is to simulate the FAIRMODEL to determine the effect of increasing each of these policy instruments on the various macroeconomic transmission variables that affect the agriculture sector. These transmission variables include inflation (as reflected by the GNP price deflator), the interest rate (the three-month U.S. Treasury bill rate), disposable income, the price level of nonfarm sales (the GNP price deflator for nonfarm total sales), and the U.S. federal deficit.

Estimated Effects of U.S. Macroeconcmic Policy on U.S. Agriculture Using the estimated effects of U.S. macroeconomic policy variables on the macroeconomic transmission variables, the US.AGMKTS model is used here to calculate the resulting effects on major IJ.S. agricultural prices and trade. To generate estimates that can be interpreted as elasticities, the macroeconomic simulations are done with each of the alternative macroeconomic policy instruments increased by 1.0 jercetnt from historically observed levels. The resulting effects on macroeconomic transmission variables are then fed directly into the USAGMKTS model to estimate effects on U.S. agricultural prices and trade which have elasticity interpretations. Note, however, that 14
the elasticities are general equilibrium elasticities rather than partial elasticities since they estimate responsiveness given all adjustmnents in related markets.

The results holding U.S. agricultural policies constant at their historical levels are reported in Tables 5 through 8. Table 5 reports estimated price elasticities and Table 6 reports estimated trade elasticitie. where macroeconomic policies are altered beginninig with the first quarter of 1981. Tables 7 and 8 report corresponding estimates where macroeconomic policies are altered beginning with the first quarter of 1984. The estimates in eacn case are reported for a two year horizon with quarterly responses summarized by yearly averages. The main purpose in presenting a two year time horizon is to illustrate effects in the short-run before production has a chance to respond (the first crop following the change in policy is harvested near the end of the first year) as well as in a longer-i:uci peiiod after production has been able to respond.

An Increase in Interest Rates. The results show t-hat an increase in interest rates (the Treasury bill rate) has a depressing effect on agricultural prices with a mixed effect on agricultltral .r.Kc' These effec-. occur along two avenues. On the macroeconomic side, the h`1gher interest attract capital inflows that bid up the price of the dolia; i .:erm.s of foreign currency (EXR, which is the inverse of the price of -re dollar, declines in Table 5). This makes U.S. exports more expensive abroad and thu2 weakens demand for U.S. grain exports and puts downward ,ressure on feed gra.n and soybean prices. On the agricultural side, the higher int,erest rates increase costs of carrying livestock inventories. This results in selling off herds which puts downward pressure on Tei -'..v B . . d :Or feed which, in turn, puts downward pressure 3r **:LL,** w. .rices. *sw-s l5
Given the magnitude of interest rate adjustments that were occurring in the early 1980s, these effects can be substantial. For example, using the estimates from Table 5, a doubling of interest rates (100 percent increase) produces a 27 percent decline ;n the price of teed grains in the first year and a 37 percent decline in the second year. The effects for soybeans are of almost the same percentage magnitudes. These effects are not unlike what was observed in the early 1980s. Corn price declined from $3.09 per bushel in the fourth quarter of 1980 to $2.39 a year later and $2.12 two years later.

The reasons for the mixed effects on agricultural trade are as follows. The effects on livestock feeding activity are mixed because the lower meat prices are offset by lower feed prices. For example, the corn price declines by more in relative terms than beef price which implies according to the estimated model that cattle numbers and beef production increases. On the other Wand, the price of pork declines by more in relative terms than corn price which implies according to the estimated model that hog numbers and pork production declines. The increase in beef production and decline in pork pro... tion account for the reduction in beef imports and increase in pork imports in Table 6. Similarly, broiler price declines by less than corn price which tends to increase broiler production which explains the increase in broiler exports in Table 6. [The reader should bear in mind that trade in meats by the U.S. is small particularly for pork. Thus, a small change in the production-consumption balance can produce a large percentage change in meat trade.] The increase in soybean exports is somewhat difficult to explain but is apparently due to several factors. First, soybean exports are less exchange ra- sensitive than corn. Second, sovbean price declines somewhat less than corn price which leads to a shift in acreage toward sovbean production.

.6
Third, the feed demand equations appear to<sup>reflect relatively more feeding of</sup> corn compared to soybeans in the price and<sup>livestock numbers situation caused</sup> by higher interest rates.

Turning to the results in Tables 6 and 7,<sup>which correspond to the</sup> 1984-85 period rather than 1981-82, the<sup>effects of an increase in interest</sup> rates are qualitatively identical.<sup>However, the magnitude of effects is</sup> considerably less. The reason for the smaller<sup>effects is largely explained by</sup> the smaller exchange rate effects generated<sup>by the state of the macroeconomy.</sup> This difference is due to the relative<sup>effects of the Treasury bill rate on</sup> the rate of inflation and the government deficit<sup>generated by the FAIRMODEL.</sup> The FAIRMODEL is nonlinear and given<sup>the more extreme real interest levels and</sup> budget tightness in 1984-85, a given<sup>change in the Treasury bill rate</sup> generates a greater change in inflation<sup>(smaller change in the real interest</sup> rate) and smaller change in the budget<sup>deficit.</sup> An Increase in Government Expenditure.<sup>The results in Tables 5 and 6</sup> show that an increase in government expenditures<sup>has a positive effect on most</sup> agricultural prices immediately but that<sup>the effect can turn negative for some</sup> commodities in the second year. These<sup>effects occur through two important</sup> channels. First, increased government<sup>expenditures cause higher consumer</sup> income and, thus, higher domestic demand<sup>for agricultural commodities. The</sup> higher demand for meat is reflected in<sup>livestock numbers and feed demand and</sup> prices more in the second Year after<sup>more herd size adjustment is possible.</sup> Second, the increased expenditure by government<sup>causes inflation which resul-s</sup> in a decline in the value of the dollar<sup>(EXR increases in Table 5). This</sup> tends to increase the demand for exports<sup>for feed grains and soybeans as</sup> re,lected by Table
The differing effects on beef and pork imports are again explained by the differing effects on the corn-meat price ratios. The corn-beef price ratio increases while the corn-pork price ratio declines. As a result, beef production declines and beef imports increase while hog numbers and, thus, pork: prodUC-:ion increases and pork imports decline. The decline<sup>in broiler</sup> exports is explained by an increase in demand for poultry resulting from the higher pork price. 1his effect outwe'ghs the positive effect of the declining corn-broiler price ratio on broiler production. The decline in livestock prices in the second year is apparently a dynamic effect of increased herd size motivated by the higher livestock prices of the first year.

Turning to the effects of increasing government expenditure in 1984-85 in Tables 7 and 8 (as opposed to the effects in 1981-82), the effects on feed grain markets are again qualitatively the same. However, the magnitude of many effects is larger and even the qualitative effects differ for sovbeans and livestock. The reason for the difference in effects is due to the different state of the feed grain program in 1984 compared to 1981. In 1981, there was no program participation requirement so program benefits were available without planting restrictions. In 1984, participants were required to plant 10 percent less than base acreages to be eligible for program benefits. The result is that a given increase in market price in 1984 causes a decline in program participation which results in a larger increase in acreage than in 1981. This both moderates the feed grain price increases and stimulates the feed grain export effects. The smaller feed grain price effects give more strength to livestock markets in the second year and permit the positive meat and soybean price effects to be sustained.

An Increase in the Personal Income Tax Rate. The effects of an increase in the personal tax rate are, broadly speaking, the mirror image of effects of 18
**increasing government expenditure.** That **is,** according to the<sup>standard</sup> national accounts equation, increasing government expenditure has the<sup>same</sup> effect on the government deficit as reducing income taxes. Indeed,<sup>the</sup> results in Tables 5 through 8 verify that, aside from a few minor cases,<sup>the</sup> qualitative effects are exactly the opposite. The same intuitive<sup>explanation</sup> follows accordingly. Basically, the effects of an increase<sup>in the tax rate</sup> are a reduction in consumer disposable income and inflation, an<sup>increase in</sup> the value of the dollar, and a resulting decline in feed<sup>grain prices and</sup> exports.

An Increase in the Federal Deficit. Intuitively, the effect<sup>of the</sup> federal deficit would seem to be the same as government expenditures<sup>and</sup> opposite of the effect of income taxes. Indeed, the results<sup>for increasing</sup> the deficit in Tables 5 and 6 are qualitatively almost identical to the<sup>case</sup> of increasing expenditures and almost opposite to the case of<sup>increasing the</sup> tax rate. However, exogenous control of the deficit in the FAIRMODEL<sup>causes</sup> some substantive differences from the case where expenditures or taxes<sup>are</sup> controlled exogenouslI These differences are illustrated by Tables 7 and 8 where the effects of the deficit are qualitatively similar<sup>to the effects of</sup> the tax rate and almost the opposite of the effects of<sup>expenditures.</sup> The contrast of results between the two time periods turns<sup>on the</sup> exchange rate effects. The reason for the different effects is that<sup>an</sup> increase in the deficit has offsetting effects on the exchange<sup>rate; which</sup> effect iominates depends on current circumstances.<sup>On one hand, an increase</sup> in the deficit (say, by an increase in expenditure) has a<sup>positive effect on</sup> inflation which tends to reduce the real interest rate<sup>and the real cumulated</sup> deficit. On the other hand, an increase in the deficit causes<sup>government to</sup> increase the demand for capital to finance the deficit<sup>which tends to bid up</sup> 19
the real interest rate and increase the real cumulated deficit. When an expenditure increase is imposed exogenously (second column of Tables 5 through 8), inflation tends to cause a reduction in the real cumulated deficit and a reducticn in the real interest rate both of which reduce government payments of interest. This effect tends to offset the increase in expenditure as it affects the deficit and tends to mitigate the increased demand for capital and upward effect on nominal interest rates that would otherwise occur. When the deficit is increased exogenously (fourth column of Tables 5 through 8), neither the effect on the deficit nor its capital demand effects on nominal interest rates can be mitigated.

In the results for 1981-82, the inflation effect on the real interest rate is strong enough to dominate the upward effect on nominal interest rates and the deficit effect on the exchange rate while in 1984-85 the deficit and nominal interest rate effects override the inflation effect. If these aspects of the FAIRMODEL and the exchange rate equation estimated here are realistic, the results have some interesting implications for effects on agriculture of reducing the U.S. federal deficit through a direct deficit control measure such as the Gramm-Rudman bill versus direct control of spendirg or taxes. The results in Table 7 i]lustrate that direct control (reduction) of the deficit is more likely to reduce the value of the dollar and stimulate agricultural export demand than direct control (reduction) of government expenditure or direct intervention to increase the tax rate.

I'he results in Tables 5 through 8 for controlling the federal deficit imply that pending U.S. federal deficit measures could have substantial effects on both prices and exports of major U.S. agricultural commodities. For example, if the flow deficit is reduced by 100 percent to achieve a balanced budget, the estimates show that feed grain prices could change 20
anywhere from -15 percent to +4 percent depending on conditions in the rest of the economy at the time of the change. Feed grain exports could change by -16 to +9 percent with much larger effects after adjustment. Apparenitly, soybean prices could change by much greater percentages by the second stear of adjustment. Thus, an ability to sort out the role of current economic circumstances appears to be important for trading partners of the U.S. itl anticipating effects of U.S. fiscal policies on trade conditions and the necessity of enacting policies to deal with the effects.

ImDortance of Agricultural Policy Instruments Another issue of critical importance in sorting nut the effects of U.S. macroeconomic policies on U.S. agricultural prices is the role of U,S. agricultural policy instruments. For example, if an agricultural commodity price is supported at a sufficiently high level. then presumably a change in macroeconomic policy would not have an impact on the nominal commodity price. Since U.S. feed grain policy has a significant price support component, it is interesting to see how agricultural price responsiveness to macroeconomic policies is affected by the level of agricultural price policy instruments.

Table 9 estimates the effects corresponding to Table 5 where the level of U.S. agricultural support and target prices are reduced 10 percent from historical levels. The interesting results here are that agricultural price responsiveness to macroeconomic policy adjustmets.Lcan be substantially greater when agricultural prices are not being supported as heavilv. The elasticities of feed grain price responsiveness to the Treasury bill rate in Table 9 are about 20 percent greater; the elasticity is -. 435 in the second year compared to -.368 in Table 5. The response of feed grain prices to the federal deficit are about 50 percent greater; the elasticity is .214 in the second year of Table 9 compared to .148 in Table 5.

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**These results reveal** that **the** interactions **of** agricultural and **macroeconomic policy are** important. A careful analysis of the likely impacts **of alternative** U.S. policy options from the standpoint of trading partners requires joint consideration of both agricultural and macroeconomic policy alternatives.

# Summary

This study reports the estimated effects of macroeconomic policy on U.S agriculture using a model of U.S. corn, sorghum, and soybeans (USAGM.K1S) that includes the role of U.S. agricultural policies and related livestock markets. The macroeconomic effects of monetary and fiscal policy are estimated using the FAIRMODEL of the macroeconomy. The results show that the effects of U.S. macroeconomic policies on prices and exports can be substantial. Price effects of recent and pending macroeconomic policy adjustments on the order of 15 percent or more are not unreasonable. Furthermore, the extent of response depends heavily on current economic circumstances. Thus, a policy response capability for countries that trade with the U.S. requires an ability to sort out the effect of current economic circumstances on U.S. policy effects. This study has attempted to develop a model that can help to serve these purposes.

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**Table 1. Endogenous Variable Definitions for the** USAGMKTS **Model.**

# Variable Definition

# Feed Grain Supply Compoorient

- COMPFGA - Feed grain program participation of corn and grain sorghum in percent of acreage

- ACGSN - Acreage of corn and grain sorghum in million acres

- YLDCGS - Yield per planted acre of corn and grain sorghum in bushels per acre

- COSTCGS - Variable costs per acre for corn and sorghum in dollars (includes seed, chemicals & labor) weighted by the respective acreages and deflated by the GNP price deflator

- PRDFG - U.S. production of feed grains (corn, sorghum, oats, barley), million metric tons

# Soybean Supply Component

AS - Acreage of soybeans in million acres

- YLDS - Yield per planted acre of soybeans in bushels per acre

- RCOSTS - Variable costs per acre for soybeans in dollars (includes seed, chemicals & labor) deflated by the GNP price deflator

- PRDS'1 - U.S. production of soybeans, million metric tons

# Feed Grain Demand ComRonent

- DLVKFG - U.S. feed and residual of feed grains (corn, sorghum, oats, barley), million metric tons

- DINDFG - U.S. feed grain use by industry, million metric tons XFG - U.S. exports of feed grains (corn, sorghum, oats, barley), million metric tons

- KFORFGE - U.S. ending farmer owned reserve stocks of feed grains, million metric tons

- KGOVFGE - Ending government owned feed grain stocks (total CCC inventory), million metric tons

- KMKTFGE - Ending inventories controlled by market forces (privately held stocks pius stocks under CCC loan)

- RPAFC - U.S. average price of corn at farm in dollars per bushel deflated by the GNP price deflator

- RPAFSG - U.S. average price of grain sorghum at farm in dollars per bushel deflated by the GNP price deflator

# Soybean Demand Component

XSB - U S. exports of soybeans, million metric tons CRUSH - U.S. crushings of soybeans, million metric tons

- KPRISBE - U.S. ending free soybean stocks, million metric tons

- RPAFS - Soybeans, price at farm, U.S. average in dollars per bushel deflated by the GNP price deflator

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# Beef **Supply** ComDonent

- TCOWKE - Cows & heifers that have calved (cow inventory) in the U.S., 1,000 head

- PRDBEEF - Commercial production of beef, million pounds COF - Cattle on feed in 13-states, 1,000 head

- CATPL - Cattle placed on feed in 13-states, 1,000 head

# Hog SUDDly Component

BRHOGKE - Breeding hog inventory for 10-states, 1,000 head

- PRDPORK - Commere.ial production of pork, million pounds PIGC - Pig crop for 10-states, 1,000 head

# Poultry Supplv Component

- PRDBR - Total production of young chicken, million pounds CPL - Pullet chicks placed in broiler hatchery supply flocks in thousands

- BRCH - Broiler-type chicks hatched, millions

# Meat Demand ComDonent

- RPBEEF - Average retail price of choice beef in cents per pound deflated by the GNP price deflator

- RPPORK - Average retail price pork in cents per pound deflated by the GNP price deflator

- RPBR - Average retail price in 4-regions of broilers in cents per pound deflated by the GNP price deflator

- PCDBEEF - Per capita disappearance of carcass weight of beef in pounds

- PCDPORK - Per capita disappearance of carcass weight of pork in pounds PCDBR - Per capita civilian disappearance of young chickens in pounds MBEEF - U.S. net imports of beef, million pounds MPORK - U.S. net imports of pork, million pounds XBR - U.S. net exports of poultry, million pounds

# Exchange Rate Component

- EXR - Trade weighted Exchange rate index in dollars per unit of foreign currency, 1972 - 1.00

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# Table 2. Exogenous U.S. Agricultural Policy Variable Definitions for the USAGMKTS Model.

|Variable|Definition|
|---|---|
|ICCCA-<br>BAC-<br>BAGS-<br>YLDFGP-|Interest charged on CCC non-recourse loans in percent<br>Base acreage of corn in million acres<br>Base acreage of grain sorghum in million acres<br>Program yield of feed grains (corn & grain sorghum) in bushels per<br>acre|
|TPC-<br>SPRC-<br>DRFG-<br>DPC - <br>VDFG-|Target price of corn in dollars per bushel (support price and<br>additional support payment prior to 1973)<br>Support price of corn in dollars per bushel<br>Diversion requirement of feed grains in percent of base acreage<br> Diversion payment for corn (paid diversion) in dollars per acre<br>Additional voluntary paid diversion for feed grains in percent of<br>base acreage|
|VDPC-<br>NOPROG-<br>SPRC-<br>SPFORC-<br>RELFORC-|Additional voluntary diversion payment for corn in dollars per acre<br>Dummy variable, 1 if a feed grain program is in effect, 0 if not<br>Regular CCC support price of corn in dollars per bushel<br>Support price for farmer owned reserve corn in dollars per bushel<br>Release price for the farmer owned reserve corn in dollars per<br>bushel|
|DMYPIK-|Dummy variable for PIK Program, 1 if third or fourth quarter of<br>1983, 0 if not|
|ICCC-|Interest rate charged for CCC non-recourse loans in percent|

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**Table** 3. **Predetermined Macroeconomic Variable Definitions** for the USAGMKTS Model (Variables Determined by the FAIRMODEL).

Variable Definition GNPD - GNP price deflator RS - Three month U.S. Treasury-bill rate (percentage points) YD - U.S. disposable income in billion dollars PF - U.S. GNP price deflator for nonfarm total sales using 1982 dollars SGP - U.S. federal deficit 26
**Table** 4. **Other Exogenous Variable Definitions for the USAGMKTS Model.**

Variable Definition YEAR - Two digit year (e.g., 1985 - 85) D70 - Dummy variable, 1 if 1970, 0 if not D71 - Dummy variable, I if 1971, 0 if not D72 - Dummy variable, 1 if 1972, 0 if not D73 - Dummy variable, 1 if 1973, 0 if not D74 - Dummy variable, 1 if 1974, 0 if not - Ql Quarterly dummy variable for first quarter - Q2 Quarterly dummy variable for second quarter Q3 - Quarterly dummy variable for third quarter Q4 - Quarterly dummy variable for fourth quarter WPRDFG - World production of feed grains (corn, sorghum, oats, barley), million metric tons N - U.S. total population in millions POP - U.S. noninstitutional population over 16 years in millions from the FAIRMODEL 27
# Table 5. Elasticities of Response to Major U.S. Agricultural Prices to Macroeconomic Policies, 1981-82

|||Macroeconomic|Policy Instrument||
|---|---|---|---|---|
|Commodity<br>|Treasury|Government|Income|Federal|
|Price|Bill Rate|Expenditure|<br>Tax Rate|Deficit|
|First Year|||||
|Corn (PAFC)|- .266|.014|- .051|.149|
|Sorghum (PAFSG)<br>|- .266<br>|.020|- .052|.151|
|Soybeans (PAFS)|- .246|.008|.019|- .047|
|Beef (PBEEF)|- .063|-.001|.045|- .077|
|Pork (PPORK)|- .307|.030|- .082|.463|
|Broilers (PBR)|- .146|.074|-.364|1.748|
|Exchange rate (EXR)|<br>- .085|.038|-.090|.255|
|Second Year|||||
|Corn (PAFC)|-.368|.021|- .018|.148|
|Sorghum (PAFSG)<br>|-.368<br>|.022|-.017|.148|
|Soybeans (PAFS)|-.319|- .001|.197|-1.265|
|Beef (PBEEF)|-.098|- .017|.230|-1.882|
|Pork (PPORK)|-.232|- .004|.145|-1.024|
|Broilers (PBR)|-.217|- .057|.022|.796|
|Exchange rate (EXR)|<br>-.122|.084|- .161|1.038|

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# Table 6. Elasticities of Response<sup>of U.S. Agricultural Exports to</sup> Macroeconomic Policies, 1981-82

# Macroeconomic Policy Instrument

|Export<br>Commodity|Treasury<br>Bill Rate|Government<br>Expenditure|Income<br>Tax Rate|Federal<br>Deficit|
|---|---|---|---|---|
|First Year|||||
|Corn|||||
|& Sorghum (XFG)|-.035|.025|-.057|.160|
|Soybeans (XSB)|.095|.015|-.044|.114|
|Beef (MBEEF)|-.065|.015|-<br>.022|.075|
|Pork (MPORK)|.950|-.443|1.016|-2.931|
|Poultry (XBR)|.028|-.012|.139|-.546|
|Second Year|||||
|Corn|||||
|&Sorghum (XFG)|<br>-.059|.076|-.156|.895|
|Soybeans (XSB)|.062|.025|-.108|.632|
|Beef(MBEEF)|-.119|.029|.035|-.441|
|Pork (MPORK)|1.849|-1.250|2.397|-17.757<br>|
|Poultry(XBR)|.157|.089|-.044|-.566|

* Elasticities are for net imports<sup>in the case of beef and pork and net</sup> exports in the case of all other<sup>commodities.</sup>

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# Table 7. Elasticities of Response to Major U.S. Agricultural Prices to Macroeconomic Policies, 1984-85

|||Macroeconomic|Policy Instrument||
|---|---|---|---|---|
|Commodity|Treasury|Gove. nient|<br>Income|Federal|
|Price|Bill Rate|Expenditure|<br>Tax Rate|Deficit|
|First Year|||||
|Corn (PAFC)|-.108|.010|-.013|-.020|
|Sorghum (PAFSG)|-.107|.009|-.012|-.020|
|Soybeans (PAFS)|-.143|.008|-.003|-.009|
|Beef (PBEEF)|-.032|-.013|.056|.082|
|Pork (PPORK)|-.128|.003|.002|.026|
|Broilers (PBR)|-.040|.035|-.140|-.117|
|Exchange rate (EXR)|<br>-.065|.047|-.082|-.105|
|Second Year|||||
|Sorn(PAFC)|-.227|.025|-.029|-.039|
|Sorghum (PAFSG)|-.226|.025|-.029|-.039|
|Soybeans(PAFS)|-.166|.023|.031|-.025|
|Beef(PBEEF)|-.048|-.035|.132|.231|
|Pork (PPORK)|-.112|.000|.051|.059|
|Broilers(PBR)|-.081|.031|-.073|-.371|
|Exchange rate (EXR)|<br>-.075|.096|-.146|-.168|

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Table 8. Elasticities of Response of U.S. Agricultural Exports to Macroeconomic Policies, 1984-85

|||Macroeconomic Po|licy Instrument||
|---|---|---|---|---|
|Export|Treasury|Government|Income|Federal|
|Commodity|Bill Rate|Expenditure|Tax Rate|Deficit|
|First Year|||||
|Corn|||||
|& Sorghum (XFG)|<br>-.033|.041|-.067|-.091|
|Soybeans (XSB)|.088|.034|-.060|-.100|
|Beef (MBEEF)|-.045|.016|-.011|-.008|
|Pork (MPORK)|.203|-.166|.273|.363|
|Poultry (XBR)|.035|-.026|.148|.207|
|Second Year|||||
|Corn|||||
|&Sorghum (XFG)|<br>-.038|.103|-.159|-.174|
|Soybeans (XSB)|.058|.042|-.101|-.050|
|Beef (MBEEF)|-.066|.029|-.008|.031|
|Pork (MPORK)|.677|-.864|1.288|1.566|
|Poultry (XBR)|.107|-.028|.135|.469|

* Elasticities are for net imports in the case of beef and pork and net exports in the case of all other commodities.

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# Table 9. Elasticities of Response of Major U.S.<sup>**Agricultural Prices to**</sup> Macroeconomic Policies with Ten Percent Lower Target<sup>and</sup> Support Prices, 1981-82

|||Macroeconomic Po|licy Instrument||
|---|---|---|---|---|
|Commodity|Treasury|Government<br>|Income|Federal<br>|
|Price|Bill Rate|Expenditure|Tax Rate|Deficit|
|First Year|||||
|Corn (PAFC)|-.291|.023|-.057|.171|
|Sorghum (PAFSG)|-.290|.015|-.058|.166|
|Soybeans (PAFS)|-.247|.008|.018|-.040|
|Beef (PBEEF)|-.065|.000|.040|-.052|
|Pork (PPORK)|-.312|.032|-.090|.508|
|Broilers (PBR)|-.153|.078|-.380|1.843|
|Second Year|||||
|Corn(PAFC)|-.435|.025|-.025|.214|
|Sorghum (PAFSG)|-.433|.027|-.025|.213|
|Soybeans (PAFS)|-.312|-.001|.190|-1.254|
|Beef (PBEEF)|-.110|-.020|.221|-1.788|
|Pork (PPORK)|-.261|-.008|.132|-<br>.883|
|Broilers (PBR)|-.256|-.067|.004|1.030|

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