Farm Wealth Inequality Within and Across States in the United States
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1 Farm Wealth Inequalty Wthn and Across States n the Unted States Ashok K. Mshra, Charles B. Moss, and Kenneth W. Erckson Ths paper uses Thel s (979) entropy-based measure of nequalty and farm-level data to examne changes n farm busness wealth (farm equty) of farm households. The farms assocated wth farm households are grouped by state nto ten regons of the Unted States. The Thel entropy measure s then calculated and used to decompose total nequalty of farm wealth nto wthn-state and across-states (between states) nequaltes for each regon. Results show that snce the enactment of the 996 Federal Agrcultural Improvement and Reform (FAIR) Act, nequalty n farm wealth among farms wthn a state has decreased relatve to the number of farms per state, across all regons. Further, most of the reducton n farm wealth nequalty s attrbuted to ncreased equalty n the dstrbuton of real estate assets of the farm households, a major component of farm wealth. Key Words: nequalty, Thel s nequalty, farm wealth, regonal decomposton, farm level, farm household, real estate assets, nventores Ths study analyzes changes n the dstrbuton of farm household wealth from 996 through 004 usng the Thel (967) measure of nequalty and farm-level data from the Agrcultural Resource Management Survey (ARMS). Ths study also measures nequalty n farm assets, partcularly real estate and non real estate assets, snce farm assets are a major component of farm wealth (Mshra et al. 00). The Thel nequalty measure allows for the decomposton of total nequalty nto varaton between farms wthn each state as well as varaton between average farms across states n each regon. Study results ndcate that nequalty n farm household wealth declned from 996 through 004. The results reveal that most of the reducton n nequalty occurred between farms wthn the states, across all regons. However, nequalty n farm wealth wthn each state remaned much greater than the range n nequalty between the average farms across states n each regon. Ashok Mshra and Kenneth Erckson are economsts n the Farm and Rural Household Well-Beng Branch of the Resource and Rural Economcs Dvson, Economc Research Servce, U.S. Department of Agrculture, Washngton, D.C. Charles Moss s Professor n the Food and Resource Economcs Department, Unversty of Florda, Ganesvlle. We are ndebted to anonymous revewers for helpful comments and suggestons. The authors would lke to thank Wes Musser for valuable dscussons, excellent suggestons, and patence. The vews expressed here are not necessarly those of the Economc Research Servce or the U.S. Department of Agrculture. Over the past quarter-century the economc lterature has been nundated wth studes on changes n ncome nequalty. Most of these studes support the convergence of ncome across countres. Ths convergence has been attrbuted to many factors ncludng ncreased nternatonal trade, captal movement, technologcal spllover, and nnovatons n nsttutonal desgn. At the same tme changes n nequalty wthn countres have been ambguous. Accordng to some studes the ncome nequalty for the developed economes of the Unted States and Western Europe actually ncreased n the 980s. Further, the textbook paradgm that ncreased nequalty encourages ncome growth was also contradcted by several emprcal studes. Apart from a general nterest n the effect of agrcultural ncome nequalty as a component of the general economy, several polcy questons partcular to the agrcultural sector motvate the examnaton of the dsperson of ncome and wealth across farm households. Frst, whle t would be dffcult to argue that socety has a preference for more equal ncome dstrbuton n agrculture, socety may prefer that farm payments have specfc effects on farm sze. At the very least, from a polcy perspectve, government polces should not dstort the dstrbuton of farm sze. However, some may prefer that the majorty Agrcultural and Resource Economcs Revew 35/ (October 006) 5 64 Copyrght 006 Northeastern Agrcultural and Resource Economcs Assocaton
2 5 October 006 Agrcultural and Resource Economcs Revew of farm payments go to so-called famly farms. These concerns were addressed by Leuthold (969), who examned the dstrbuton of farm payments across farm szes. Second, the dstrbuton of farm ncome may have mplcatons for the effcacy of the government safety net. As stated by Ahearn, Johnson, and Strckland (985), ncome mantenance has always been a polcy goal, but the heterogenety of farm households masks the true varablty of farm ncome. Much of the lterature has focused on changes n the dsperson or nequalty of ncome. Ths study nstead focuses on the nequalty of farm household wealth for three reasons. Frst, studes suggest that wealth s actually the mechansm that provdes for economc growth. Second, gven equal access to captal markets, wealth s actually a better measure of dfferences n consumpton than ncome. Fnally, ncome for the farm household can be mathematcally defned as the rate of return to equty multpled by the amount of wealth controlled by the household. Each of these lnkages between the economc well-beng of the farm household and farm household wealth can be demonstrated usng the optmal debt model presented by Ramrez, Moss, and Boggess (997). Ramrez, Moss, and Boggess (997) model the optmal debt level for a farm household usng an extenson of Merton s (969) lfetme portfolo specfcaton. In ths formulaton, farm households determne the level of debt that maxmzes the present value of expected utlty. Followng Merton s formulaton, they assume that farmers choose the level of debt (or leverage poston) to maxmze the expected utlty, whch they model usng the power functon () b Ct () UCt [ ( )] =, b where U( ) denotes utlty, C(t) denotes consumpton at tme t, and b denotes the relatve rsk-averson coeffcent. Consumpton s constraned by an equaton of moton for farmer equty, defned as () de() t = [ R () t E() t C()] t dt, E where de(t) denotes the contnuous change n the farmer s equty, E(t) s the farmer s equty, R E (t) s the rate of return on equty, and dt s the ncrement n tme. Expandng the rate of return on equty, change n equty can be expressed as (3) [ RA( t) K( t) δ( t)] de() t = E() t C() t dt, ( δ( t) ) where R A (t) s the rate of return on agrcultural assets, K(t) s the cost of debt captal, and δ(t) s the debt-to-asset rato. Ramrez, Moss, and Boggess derve the optmal level of farm debt, proporton of equty consumed, and the level of consumpton as functons of rsk averson, mean and varance of the rate of return on agrcultural assets, and the cost of debt captal, (4) * [ b] σa( t) δ () t = µ A() t K() t * * C t E t D t * D t () = () () r K() t b bkt [ ( ) µ ( t)] () =, A b [ b] σa( t) where δ * (t), C * (t), and D * (t) represent the optmum debt-to-asset rato, consumpton, and percent of equty consumed n perod t, µ A (t) s the expected rate of return on assets n perod t, σ A() t s the varance of the rate of return on assets n perod t, and r s a consumpton-based dscount rate (assumed constant over tme). Thus, the dsperson of farm consumpton s dependent (n part) on the dstrbuton of farm equty. Equaton 4 can be extended to ncorporate several dfferent polcy concerns. For example, the economc well-beng of farmers n the Unted States s dependent not only on returns to agrcultural assets, but also on the possblty of off-farm employment. Thus, equaton 4 can be reformulated as (5) * * C t D t E t RO t () = () () + (), where R O (t) s the return to off-farm employment. Further, the rate of return on agrcultural assets (R A (t)) s affected by government program payments as well as factors such as urban pressures that ncrease the prce of farmland over tme
3 Mshra, Moss, and Erckson Farm Wealth Inequalty Wthn and Across States n the Unted States 53 (Lvans et al. 006). Ths conceptual model helps explan why the sze dstrbuton of the wealth of farm households changes and why the sze dstrbuton of wealth vares across farm households cross-sectonally and over tme. Informatonal Measures of Inequalty A varety of measures have been used to measure the dsperson of nequalty of economc wellbeng n the farm sector (.e., the coeffcent of varaton, Gn coeffcents, and Lorenz curves). Ths study departs from these formulatons, applyng Thel s measure of nequalty (Thel 979). Ths approach has several theoretcal advantages and allows for the decomposton of the dsperson nto wthn and between-state measures n a gven regon. Ths secton frst presents Thel s measure of nequalty and descrbes how the measure can be used to decompose the overall nequalty nto among-farms-n-a-state and between-state measures of nequalty. We then dscuss the advantages of ths measure. Buldng on the general concept of Shannon (948) nformaton or entropy, the Kullback- Lebler relatve entropy s defned as (6) (, ) = ( )ln( ( )) ( )ln( ( )) D p q p x p x dx p x q x dx E px ( ) = px ( )ln dx, E qx ( ) where D(p,q) s a measure of the dfference (or dstance) between the two probablty measures, and p(x) and q(x) are probablty measures defned on x. The dscrete form of ths measure becomes (7) N p ( x) ( pq, ) = p ( x)ln = q ( x). In our applcatons we want to examne a unform dstrbuton of wealth aganst an emprcal dstrbuton of wealth: E N = p ( x)ln[ p ( x) + ln( N)] = N = ( ) = ln( N) + p ( x)ln p ( x). Ths measure s sometmes referred to as the relatve entropy n the sgnal. Thel s measure of ncome nequalty s an adaptaton of the dscrete form of the relatve dfference measure presented n Equaton 7: (9) N p I( p, q) = p ln = q, where I(p,q) s the measure of nequalty (or dsperson) of ncome, p s the share of ncome n state or regon, and q s the share of the overall populaton n that state or regon. Adaptng ths procedure to examne the nequalty n farm wealth, we let p be the share of farm wealth n state and q be the share of farmers n state. I(p,q) s then defned as the dsperson of farm equty. If the share of the number of farms s close to the share of farm equty, then there s lttle addtonal nformaton and the nformaton nequalty s small. A small nequalty means that the dstrbuton of farm wealth, per farm, s unform across states, and thus the value of I(p,q) approaches 0. Conversely, an ncrease n the nformaton nequalty ndcates dvergence n farm wealth across the states. An mportant aspect of the Thel measure of nequalty s ts decomposablty. To develop ths decomposablty we dvde the overall nequalty n Equaton 9 nto two groups: (0) p I( p, q) = p ln q = p p q G G [ ln( ) ln( )] [ ln( ) ln( )] = p p q [ ] + p ln( p ) ln( q ), (8) N p ( x) ( pq, ) = p ( x)ln = N The nomnal and real nformatonal nequalty s dentcal f nflaton s the same across regons.
4 54 October 006 Agrcultural and Resource Economcs Revew where G and G are mutually exclusve and exhaustve sets of ndvduals (states or regons). Defnng P = p, P = p, Q = q, and Q = q, G G G G the equalty represented n Equaton 0 can be rewrtten as () I( p, q) = p ln( p) ln( q) + {ln( P ) G ln( P) + ln( Q) ln( Q)} + p ln( p) ln( q) + {ln( P ) G ln( P) ln( Q) ln( Q)} + p P P = pln pln G q + G Q Q p P P + p ln q + p ln G G Q Q p p p P p P = P ln P ln GP q + G P q Q Q P P + Pln + Pln. Q Q Defnng the average nequalty wthn each group,.e., nequalty between farms n each state, as () p p p P p P I = P ln P ln G q + P G P q Q Q, and the nequalty between groups,.e., nequalty between states, as (3) P P IR = Pln + Pln, Q Q we are left wth the decomposton of the nequalty measure n a gven regon as (4) I = I + IR. Lettng p equal frm-level wealth (nstead of stateor regonal-level wealth) and q =/N f G or q =/N f G (e.g., N s the number of farms n group G and N s the number of farms n group G ), the decomposablty of the nequalty measure n Equaton 4 can be expanded to the frm level as (5) p p P P ln GP N I = I + IR = p p P + P ln G P N P P + Pln + P ln N N N N N N + + p p P ln( N) + ln G P P = p p + P ln( N) + ln G P P P P + Pln + Pln. N N N+ N N+ N Thus, Q =N /(N +N ) represents the share of farms n group as depcted n Equaton 3 and Q =N /(N +N ) represents the share of farms n group, as depcted n Equaton 3. Equaton 5 states that total nequalty n a gven regon s composed of nequalty wthn farms n a state and between states. As prevously stated, a number of nequalty measures have been proposed, ncludng the coeffcent of varaton, Lorenz curves, and Gn coeffcents. Gven ths dversty, t behooves the researcher to justfy the choce of nequalty measure. To justfy our applcaton of the Thel nequalty measure, we rely on the axomatc characterstcs developed by Foster (983), partcularly those emphaszng the role of decomposablty of nequalty. Foster develops four crtera
5 Mshra, Moss, and Erckson Farm Wealth Inequalty Wthn and Across States n the Unted States 55 for measurng nequalty: () the Pgou-Dalton transfer prncple, () symmetry, () homogenety, and (v) the populaton prncple. The Pgou-Dalton transfer prncple states that the measure of ncome nequalty must ncrease f ncome s taken from a poorer ndvdual and gven to a rcher ndvdual. Ths prncple would appear fundamental to the concept of equalty underlyng equty measurement, and further support for t can be found n Atknson (970). The prncples of symmetry and homogenety denote somewhat dfferent concepts n nequalty measurement than those found n consumpton and producton theory. In the measurement of nequalty the symmetry crteron states that the nequalty measure s unchanged when two ndvduals trade places (or ncome levels). The homogenety crteron states that only relatve ncome dsperson matters (.e., multplyng all ncomes by the same proporton does not change the level of nequalty). Whle several nequalty measures meet the frst three crtera (the Pgou-Dalton prncple, symmetry, and homogenety), Foster (983) shows that the Thel measure of nequalty alone satsfes the populaton prncple. The populaton prncple states that replcatng the sample (.e., addng a second dataset wth an dentcal ncome dstrbuton) should result n no change n the nequalty measure. Foster (983) demonstrates that the decomposablty of the Thel measure s a requrement to meet the populaton prncple. In fact, Foster shows n Theorem that... nequalty measure I satsfes PD [Pgou-Dalton], S [symmetry], H [homogenety], PP [Populaton Prncple], and WD [Weak Thel Decomposablty] f and only f I s a postve multple of the Thel measure of nequalty [p. ]. Hence, gven our nterest n the nequalty of farm wealth wthn varous farms n a state and states wthn a regon, the most approprate measure of nequalty s that proposed by Thel. Data The fnancal accountng concept defnes the elements of fnancal statements for busness enterprses and households. Based on Farm Fnancal Standards Task Force recommendatons, the sources of farm assets nclude () real estate, () farm equpment, () other fnancal assets (such as nvestment n cooperatves, prepad nsurance, etc.), and (v) other assets (such as breedng stock, crop and lvestock nventory, purchased nputs, etc.). Sources of farm debt nclude () real estate, () non real estate, () short-term debt (ncludes loans less than one year, accrued nterest, accounts payable, and the current porton of term debt), and (v) long-term debt (ncludes noncurrent real and non real estate debt). The Agrcultural Resource Management Survey (ARMS) of the U.S. Department of Agrculture (USDA) collects farm-level data on, n addton to other nformaton, all the elements necessary to construct total wealth and total debt for the farm busness. Annual ARMS data from 996, 000, and are used n ths study. Ths perod represents the perod after the enactment of the Federal Agrcultural Improvement and Reform (FAIR) Act of 996 and ncludes observatons under the Farm Securty and Rural Investment (FSRI) Act of 00. ARMS s conducted annually by the Economc Research Servce and the Natonal Agrcultural Statstcs Servce. It s the prmary source of nformaton about the fnancal condton and economc well-beng of farm busnesses and of farm households n the Unted States, and ncludes data on all the components of farm assets and debt of the farm busness. Farm wealth or the equty of farm households s derved n ARMS by subtractng total farm debts from total farm assets. ARMS uses a mult-phase samplng desgn and allows each sampled farm to represent a number of farms that are smlar, that number beng the survey expanson factor (see Kott 998 and Dubman 000 for more techncal detal). The expanson factor, n turn, s defned as the nverse of the probablty of the surveyed farm beng selected. The expanson factor can also be referred The Farm Fnancal Standards Task Force (FFSTF) n ts recommendaton publshed n the Fnancal Gudelnes for Agrcultural Producers (Forbes 99) sets forth a mnmum set of requrements for a fnancal statement that should nclude balance sheet and ncome statement nformaton and use fnancal accountng concepts. 3 Although data for other years are avalable, ncremental nformaton avalable s very small and results do not vary n any way. Therefore, we decded to present the results for selected years.
6 56 October 006 Agrcultural and Resource Economcs Revew to as the observaton s weght. Each verson of ARMS has a unque expanson factor that expands the sample to the target populaton. ARMS collects data to measure the fnancal condtons (farm ncome and expenses) and operatng characterstcs of farm busnesses, the cost of producng agrcultural commodtes, and the wellbeng of farm operator households. It s mportant to pont out that ARMS s not a longtudnal database. Each year dfferent farms are surveyed, and wth weghtng schemes the number of farms add up to the U.S. total. The dstrbuton of farms usng ARMS data based on reported farm busness wealth categores 4 hghlghts changes n the spatal and temporal dstrbuton of farm wealth. For example, Fgure shows that the dstrbuton of farms n the lower tal of the wealth categores has decreased over the perod, whle the percentage of farms n the hghest category has ncreased. The percentage of farms n the $50,000 $999,999 wealth category ncreased by about 0 percent durng the perod, from approxmately 43 percent n 996 to 45 percent n 004. However, durng the same tme perod the share of farms n the largest category ($ mllon or more) ncreased by approxmately 76 percent, from approxmately percent n 996 to nearly 37 percent n 004. In ARMS, farm wealth s domnated by farm real estate (76 percent) (Mshra and El-Osta 005). The average value of farm assets of famly farm busness ncreased from $74,396 n 994 to $677,353 n 004, an ncrease of 47 percent. On the other hand, the average farm debt ncreased from $,00 n 99 to $3,408 n 004, an ncrease of only 54 percent (USDA, varous years). The average wealth of famly farm busnesses ncreased from $53,385 n 996 to about $644,945 n 003, a 50 percent ncrease over a decade (USDA, varous years). However, regonal dfferences exsted n the wealth of famly farm busnesses (Table ). Fgure shows the dstrbuton of farms for selected regons and years. One can draw two nferences from ths fgure. Frst, across all re- 4 In ths study farms were categorzed nto sx dfferent wealth categores. These categores were based on the reported wealth of the famly farm busness. These categores are () $0 $4,999, () $5,000 $49,999, () $50,000 $99,999, (v) $00,000 $49,999, (v) $50,000 $999,999, and (v) $,000,000 or more. gons, the percentage of farms n the $50,000 or more wealth categores has ncreased and the dstrbuton of farms n the lower wealth classes ($50,000 or less) has remaned relatvely stable over the same tme perod. Second, the share of farms n the largest wealth category ($ mllon or more) s hghest n the Pacfc regon, followed by the Corn Belt and Southeast regons. Further, the fgure also shows that an ncrease n the percentage of farms n the largest wealth category for the Pacfc, Corn Belt, and Southeast regons has been accompaned by decreases n the percentage of farms n the $00,000 $49,999 and $50,000 $99,999 wealth categores. These fndngs are consstent wth El-Osta and Morehart s (00) study of wealth concentraton n U.S agrculture. Table shows the mean farm wealth of farm households n varous wealth categores for selected regons and years usng ARMS mcro-level data. These results llustrate the range of varaton wthn a regon between years n the selected wealth categores and wthn a wealth category between regons n each year, and the patterns of dfferences wthn a wealth category across regons over tme. The table shows that average farm wealth vares wthn a regon and over tme. Results Table presents the mportance of each component (farms wthn a state and between states) of total nequalty n terms of the Thel measure of nequalty. In general the results ndcate that the dstrbuton of farm wealth changed sgnfcantly from 996 through 004. Inequalty between farms n a state contrbuted the most, about percent, to the total nequalty. A smlar pattern s observed n all ten regons of the Unted States. Ths fndng s consstent wth the fact that there s consderable varablty n farm sze, farm assets (real estate, manly land, and non real estate assets, manly crop and lvestock nventores), and farm debt among farms n a state. Further, aggregaton of farms at the state level reduces the varablty n the components of wealth and hence reduces the level of nequalty n farm wealth when comparng farms wthn dfferent states and wthn a gven regon. Table shows that total farm-level nequalty, across all regons, has decreased over the perod
7 Mshra, Moss, and Erckson Farm Wealth Inequalty Wthn and Across States n the Unted States 57 $,000,000 or more $50,000-$999,999 Farm equty class $00,000-$49,999 $50,000-$99,999 $5,000-$49,999 $0-$4, Percent of farms Fgure. Dstrbuton of Farms by Wealth (Equty) Categores for Selected Years Source: USDA (varous years) The hghest level of total nequalty (8.3) was observed n 996 for farms located n the states belongng to the Southern Plans regon, followed by that for farms located n the states belongng to the Northern Plans and Appalachan regons. Table also shows that nequalty among farms wthn states and regons decreased over the perod. For example, wthn-state nequalty for farms located n the Southern Plans decreased by nearly 0 percent durng and by approxmately 8 percent durng The largest reducton n overall or total nequalty (approxmately 5 percent) was observed among farms located n the Northern Plans durng the perod, and next largest (about 6 percent) among farms located n the Corn Belt regon durng Ths reducton s manly due to a sgnfcant reducton n the nequalty n farmland values across farms located n these states and eventually across states n the regon. Further, the general trend for nearly all regons s that both real estate and non real estate assets became more equally dstrbuted snce most relatve changes from the prevous years (996 and 000) are negatve (Tables 3 and 4). In general, farmland values reflect farm nvestors expectatons about future dscounted returns both from the market and from government payments on base acres. The FAIR Act of 996 generally lowered the market prce and output dstortons ntroduced by government prce support programs. As a result, producers could and dd respond more and more to market-based prce sgnals. For example, although the dstrbutons of real estate and non real estate assets became somewhat more unequally dstrbuted n 000 than n 996, these dstrbutons became more equally dstrbuted n 004 versus 000. However, n the Northern Plans, these dstrbutons became more equally dstrbuted much sooner, begnnng n 000. Ths may be due to the fact that adjustng the crop mx n the Corn Belt mght be easer to do snce t largely nvolves only changng rotatons. Some Northern Plans farmers
8 58 October 006 Agrcultural and Resource Economcs Revew Table. Average Farm Wealth (Equty) by Wealth Categores for Unted States (selected regons and years) Year and Wealth Class Unted States NE Regon Corn Belt Regon No. Plans Regon Southeast Regon So. Plans Regon Pacfc Regon Dollars $0 4,999 0,95 (63,60) $5,000 $49,999 38,3 (8,395) $50,000 $99,999 76,483 (303,987) $00,00 $49,999 57,48 (777,98) $50,000 $999, ,934 (,66,34) $,000,000 or more,960,3 (5,683,687) 000 $0 4,999 5,37 (46,898) $5,000 $49,999 37,353 (60,379) $50,000 $99,999 74,99 (335,753) $00,00 $49,999 70,308 (779,95) $50,000 $999,000 48,390 (,670,654) $,000,000 or more,6,974 (45,939,54) 004 $0 4,999,603 (8,74) $5,000 $49,999 37,995 (9,974) $50,000 $99,999 73,850 (05,555) $00,00 $49,999 75,543 (577,694) $50,000 $999, ,88 (,979,00) $,000,000 or more,359,5 (4,,33) Source: USDA (varous years). Note: Numbers n parentheses are standard devaton. 8,037 (34,38) 33,345 (56,37) 75,46 (08,79) 69,79 (699,749) 497,043 (,35,504),4,375 (7,033,803),063 (5,758) 35,97 (94,035) 70,607 (40,59) 70,98 (789,89) 473,355 (,456,385),850,045 (,,8) 4,07 (0,09) 4,83 (47,44) 70,33 (33.667) 86,930 (663,579) 5,408 (3,34,736),63,04 (6,34,55) 3,65 (5,48) 39,44 (65,609) 85,36 (4,755) 6,843 (807,099) 436,036 (,4,9),496,590 (4,045,568) 0,438 (59,904) 34,6 (69,09) 77,534 (99,677) 70,86 (93,808) 477,08 (3,36,758),703,605 (,077,96),89 (88,956) 38,63 (3,467) 73,9 (9,5) 68,334 (633,938) 487,99 (,9,388),09,878 (,88,943) 5,475 (58,4) 39,58 (39,57) 73,38 (334,6) 66,93 (59,539) 56,378 (,95,069),593,0 (7,80,633) 9,903 (,060) 38,98 (73,87) 70,68 (7,360) 66,447 (694,9) 53,538 (,43,00),769,8 (5,684,409) 4,69 (94,78) 39,064 (44,79) 78,69 (30,7) 80,747 (367,348) 57,489 (,776,76),984,5 (0,387,558) 3,54 (49,70) 37,07 (96,858) 77,079 (03,394) 68,035 (745,45) 488,893 (,47,76),5,954 (7,483,495) 6,66 (,96) 30,477 (5,70) 75,708 (45,687) 74,767 (740,09) 46,47 (,509,43),987,398 (0,46,904),905 (46,95) 37,005 (0,563) 79,790 (38,86) 76,6 (43,59) 508,507 (,594,974),599,478 (7,436,686) 3,33 (53,834) 40,665 (68,05) 8,588 (458,363) 48, (69,668) 546,535 (3,067,58),08,584 (0,053,45) 9,06 (30,5) 37,86 (3,89) 77,996 (565,456) 70,68 (9,94) 477,496 (,696,956),07,994 (57,570,066) 7,706 (43,933) 3,7 (95,6) 75,6 (57,08) 67,86 (77,500) 464,835 (,6,97), (,48,444) 3,8 (55,49) 30,366 (79,406) 7,735 (37,53) 57,57 (88,696) 450,07 (,3,00),78,909 (9,443,758),57 (6,43) 35,657 (30,30) 67,370 (75,343) 74,46 (68,848) 486,879 (,893,90),584,45 (40,34,47) 7,44 (54,530) 35,36 (40,735) 78,63 (96,54) 90,333 (308,975) 547,6 (,44,63) 3,4,0 (7,7,005)
9 Mshra, Moss, and Erckson Farm Wealth Inequalty Wthn and Across States n the Unted States % 0% 40% 60% 80% 00% % 0% 0% 30% 40% 50% 60% 70% 80% 90% 00% $0-$4,999 $5,000-$49,999 $50,000-$99,999 $00,000-$49,999 $50,000-$999,999 $,000,000 or more Fgure. Dstrbuton of Farms by Farm Wealth Categores (selected regons and years) Source: USDA (varous years).
10 60 October 006 Agrcultural and Resource Economcs Revew Table. Total Inequalty of Farm Wealth by Farms (Wthn and Between States) and Its Decomposton (by regon and varous years) Regon Wthn State Across States Wthn State Across States Change n Wthn State (%) Change n Across States (%) Wthn State Across States Change n Wthn State (%) Change n Across States (%) Northeast Lake States Cornbelt Northern Plans Appalachan Southeast Delta Southern Plans Mountan Pacfc Source: Authors calculatons usng ARMS data (USDA, varous years).
11 Mshra, Moss, and Erckson Farm Wealth Inequalty Wthn and Across States n the Unted States 6 Table 3. Inequalty n Real Estate Assets Among Farms n a State (by regon and varous years) Regon Wthn State Wthn State Relatve Change n Wthn State ( ) Percent Wthn State Relatve Change n Wthn State ( ) Percent Northeast Lake States Cornbelt Northern Plans Appalachan Southeast Delta Southern Plans Mountan Pacfc Source: Authors calculatons usng ARMS data (USDA, varous years). Table 4. Inequalty n Non Real Estate Assets Among Farms n a State (by regon and varous years) Regon Wthn State Wthn State Relatve Change n Wthn State ( ) Percent Wthn State Relatve Change n Wthn State ( ) Percent Northeast Lake States Cornbelt Northern Plans Appalachan Southeast Delta Southern Plans Mountan Pacfc Source: Authors calculatons usng ARMS data (USDA, varous years). argued n the md-990s that plantng flexblty dd not really provde them much beneft snce they had more lmted alternatves and were already plantng the best crop wheat. However, ths may have changed somewhat as more soybeans are now planted n that regon, perhaps because new varetes of soybeans have provded more croppng optons. Decomposng the overall nequalty nto dsperson between farms wthn-state and across-states (between states) for a gven regon, one can derve addtonal nsght. 5 Varatons between states tend to reflect macroeconomc factors such as changes n farm structure (.e., farm sze, farm type). Varatons wthn-state reflect mcroeco- 5 It should be noted that the tme perod for ths analyss ( ), thrteen years, s not large enough to have a sgnfcant mpact on number of farms n country or between regons. In general, number of farms has been stable, around. mllon over the last 5 years.
12 6 October 006 Agrcultural and Resource Economcs Revew nomc condtons (such as farmland prces), whch tend to be correlated among states n a regon. Snce farmland comprses about 80 percent of farm household wealth, changes n farm wealth are largely drven by changes n farmland supply and demand. Therefore, changes n the betweenand wthn-state dstrbuton of farm wealth suggest the extent to whch farmland markets are becomng ncreasngly ntegrated across farms n the states and across states. Changes n Inequalty Wthn State Overall, the nequalty between farms wthn a state accounted for nearly 97 percent of the reducton n the total nequalty n farm wealth between 996 and 004. The wthn-state nequalty of farm wealth or equty ( I n Equaton ) for each of the ten Economc Research Servce (ERS) regons s presented n Table. There s a consstent pattern that emerges from ths table; for example, wthn-state nequalty n all regons has declned over the perod , but the rate of declne vares wth a regon. In general, a reducton n farmland values and crop and lvestock nventores nequalty were the reasons behnd the declne n the nequalty n farm wealth among farms located n varous regons. However, durng the perod, wthn-farm nequalty ncreased n the Corn Belt (3 percent) and Mountan (about 7 percent) regons. Ths s partly due to the rsng nequalty n real estate assets (or farmland values) of about percent (Table 3), and ncreased levels of nequalty n crop and lvestock nventores (3 percent) (Table 4) wthn farms n the Corn Belt regon. However, rsng nequalty n crop and lvestock nventores (about percent) outpaced nequalty n farmland values (3 percent), and rsng farmland values were a reason for ncreased farm wealth nequalty wthn farms located n the Mountan regons (Tables 3 and 4). Table also presents the nequalty n farm wealth of farms located n the Northeast, Mountan, and Pacfc regons. Farms n the Northeast and Appalacha regons tend to be small and agrculture labor-ntensve. Begnnng n 997, the nequalty n farmland values and nventores of crop and lvestock has been ncreasng among farms n the Northeast (Tables 3 and 4). Ths rse could be partly due to the growth n farmland values drven by urban pressure (Lvans et al. 006) and to global trade (Blandford 999). Ths growth n farmland values provdes unrealzed captal gans, thereby enhancng farm wealth. In addton, ncreased off-farm ncome from suburban employment opportuntes may have also contrbuted to the growth n farm equty. However, n recent years wthn-state nequalty n farmland values and crop and lvestock nventores has decreased, leadng to an overall declne n nequalty n wealth among farms located n the Northeast regon. The Pacfc and Mountan regons show a very smlar pattern over tme. The nequalty n farm wealth wthn farms located n the Mountan regon ncreased from 6.54 n 996 to 7.60 n 000, an approxmately 9 percent ncrease over the perod Ths was due to rsng nequalty n farmland values and crop and lvestock nventores. For example, durng ths perod farms n the regon observed a 3 percent rse n nequalty n real estate assets (manly farmland) coupled wth a percent rse n nequalty n non real estate assets, such as crop and lvestock nventores. However, durng the perod, nequalty n non real estate assets decreased by approxmately percent (Table 4), more than compensatng for the rse n farmland values, less than percent (Table 3). Farms located n the Pacfc regon (Calforna, Oregon, and Washngton) saw ther share of equty rse because of ncreased foregn and domestc demand for grans, fruts, and vegetables. Wthn-farm wealth nequalty n the Pacfc regon decreased by almost 7 percent, from 7.05 n 000 to 5.86 n 004. Ths s due to rsng equalty n farmland values and crop and lvestock nventores. Table 3 shows that nequalty n farmland values decreased by approxmately 6 percent over the perod , whereas nequalty n crop and lvestock nventores decreased by about 8 percent (Table 4). One plausble explanaton s that farms n ths regon produce fruts and vegetables and hgh value crops, whch have domestc as well as foregn markets, and also that the regon s agrcultural sector s expandng, such as n dary farmng and value-added through dary farmng. Another possble explanaton for a 6 percent decrease n the wthn-state Thel entropy measure ( ) n the Pacfc states may be the nfluence of urbanzaton and other non-farm factors affectng the demand for and prce of farmland n the Pacfc states.
13 Mshra, Moss, and Erckson Farm Wealth Inequalty Wthn and Across States n the Unted States 63 Changes n Inequalty Between Farms Across State The nequalty n farm wealth across states (I R ) n a gven regon accounted for percent or less n the total nequalty between 996 and 004. Durng ths perod, agrculture n the Unted States went through sgnfcant structural changes. The average sze of farms ncreased through consoldaton. These changes were partly due to a more open and global economy, greater captal and labor moblty, and the deregulaton of captal markets. The expanson/consoldaton of agrculture resulted n a more even dstrbuton of wealth across the regons relatve to the number of farms n each state. Table shows that durng the perod, between-farm nequalty across states ncreased for Mountan states, Lakes states, and the Delta regon. On the other hand, durng the perod, between-farm nequalty across states ncreased for the Appalachan and Delta regons. However, n absolute terms these changes are very small and have a low mpact on the total nequalty n farm wealth (Table ). Ths suggests that snce 996 the regons have been becomng more smlar, and/or that macroeconomc and structural dfferences n agrculture have declned. Snce 994 the dstrbuton of farm assets (a major component of farm wealth) became more unformly dstrbuted between regons. Ths s consstent wth a regme shft from 996 to the present. Under the FAIR Act, farmers were able to make more market-orented plantng and croppng decsons. As a result, short-run assets (nventores, purchased nputs, and other farm fnancal assets) and real estate (long-term) were reallocated across crop portfolos, and net returns and farm wealth became more unformly dstrbuted across regons [Blank, Erckson, and Moss 005 (p. ), Blank et al. 004 (pp )]. Also, the Food Securty and Rural Investment Act of 00 (or 00 Farm Bll) bulds on prevous polcy and nsttutonalzes an mproved safety net for farmers through a new countercyclcal ncome stablzaton program. The FSRI Act contnues the seres of fundamental changes n commodty and other agrcultural polces desgned to move the sector toward more market-orented decsons. Program changes for dry peas, lentls, dary, and peanuts suggest ncreases n producton of these commodtes. Addtonal market effects may result from countercyclcal payments, drect payments, and provsons of the 00 Farm Act that permt the updatng of base acreage and payments yelds. These payments may provde ndrect ncentves that nfluence producton decsons and overall agrcultural output. Summary and Conclusons Ths study analyzes the change n the dstrbuton of farm wealth n farms wthn state and between states for a gven regon, usng Thel s measure of nequalty. It uses farm-level data from the USDA s Agrcultural Resource Management Survey (ARMS) for the years 996, 000, and 004. Thel s measure s used n ths study because of ts consstency and the desrable propertes t has compared to other measures of nequalty, Gn coeffcents, or the coeffcent of varaton. Most of these desrable propertes result from the decomposablty of the Thel measure. Specfcally, the aggregate Thel measure can be decomposed nto regonal nequalty measures that obey the Pgou-Dalton transfer, symmetry, and homogenety prncples requred of nequalty measures. Ths decomposton allows for analyss of nequalty across and wthn regons. Ths allows for the comparson of macroeconomc factors affectng the nequalty across regons wth mcroeconomc factors that typcally affect the nequalty wthn each regon. In general the results ndcate that the dstrbuton of farm wealth has changed sgnfcantly from 996 through 004. The hghest level of total farm-level nequalty (8.46) was observed n 996 for farms located n Texas and Oklahoma n the Southern Plans regon of the Unted States, followed by farms located n the Northern Plans, Appalachan, and Delta regons. Ths study shows that total nequalty among farms n varous states has decreased over the perod. However, durng the same perod, total nequalty ncreased for farms located n the Corn Belt and Mountan regons of the Unted States. Ths s manly due to a rse n the nequalty n farmland values n these regons ( and 3 percent, respectvely). Further, results also show that wthnfarm nequalty, rangng from approxmately 95 to 99 percent, contrbuted more to the total ne-
14 64 October 006 Agrcultural and Resource Economcs Revew qualty. Under the 996 FAIR Act, farmers were freer to make more market-orented plantng and croppng decsons. As a result, short-run assets (nventores, purchased nputs, and other farm fnancal assets) and real estate (long-term) assets were reallocated across crop portfolos. Consequently, net returns and farm wealth became more unformly dstrbuted wthn farms n a state and across states. Addtonally, the 00 Farm Act may also provde ncentves to expand producton n nontradtonal commodtes, such as dry peas and lentls, and to ncrease proftablty and farm wealth. References Ahearn, M., J. Johnson, and R. Strckland The Well- Beng of Farm Households: Farm, Off-Farm, and In-Knd Sources of Income. Amercan Journal of Agrcultural Economcs 67(5): Atknson, A.B On the Measurement of Inequalty. Journal of Economc Theory (3): Blandford, D Globalzaton and Northeast Agrculture: Implcatons for the Upcomng Round of World Trade Negotatons. Agrcultural and Resource Economc Revew 8(): Blank, S.C., K.W. Erckson, and C.B. Moss Proft Patterns across Amercan Agrculture. Journal of Agrcultural and Resource Economcs 30(): Blank, S.C., K.W. Erckson, C.B. Moss, and R. Nehrng Agrcultural Profts and Farm Household Wealth. Amercan Journal of Agrcultural Economcs 86(5): Dubman, R.W Varance Estmaton wth USDA s Farm Costs and Returns Surveys and Agrcultural Resource Management Study Survey. Report No. AGES 00-0, Economc Research Servce, U.S. Department of Agrculture, Washngton, D.C. El-Osta, H., and M. Morehart. 00. The Dynamcs of Wealth Concentraton Among Farm Operator Households. Agrcultural and Resource Economc Revew 3(): Forbes, S. (Charman). 99. Recommendatons of the Farm Fnancal Standards Task Force: Fnancal Gudelnes for Agrcultural Producers. Fnancal Accountng Standards Board, Norwalk, CT. Foster, J.E An Axomatc Characterzaton of the Thel Measure of Income Inequalty. Journal of Economc Theory 3(): 05. Kott, P.S Usng the Delete-a-group Varance Estmator n NASS Surveys. Draft research report, Natonal Agrcultural Statstcs Servce (NASS), U.S. Department of Agrculture, Washngton, D.C. Leuthold, R.M Government Payments and the Dstrbuton of Income n Agrculture. Amercan Journal of Agrcultural Economcs 5(5): Lvans, G., C.B. Moss, V.E. Breneman, and R.F. Nehrng Urban Sprawl and Farmland Prces. Amercan Journal of Agrcultural Economcs 88(4): Merton, R.C Lfetme Portfolo Selecton under Uncertanty: The Contnuous-Tme Case. Revew of Economcs and Statstcs 5(3): Mshra, A.K., and H.S. El-Osta Decomposton of Varablty n Farm Household Assets and Debt. Journal of Agrbusness 3(): Mshra, A.K., H.S. El-Osta, M.J. Morehart, J.D. Johnson, and J.W. Hopkns. 00. Income, Wealth, and the Economc Well-Beng of Farm Households. Agrcultural Economcs Report No. 8, Economc Research Servce, U.S. Department of Agrculture, Washngton, D.C. Ramrez, O.A., C.B. Moss, and W.G. Boggess A Stochastc Optmal Control Formulaton of the Consumpton/ Debt Decson. Agrcultural Fnance Revew 57(): Shannon, C.E Mathematcal Theory of Communcaton. Urbana, IL: Unversty of Illnos Press. Thel H Economcs and Informaton Theory. Amsterdam: North-Holland Press World Inequalty and Its Components. Economc Letters (): U.S. Department of Agrculture Farm Balance Sheet Data. Economc Research Servce, U.S. Department of Agrculture. Avalable at balancesheet (accessed August 8, 005).. Varous years. Agrcultural Resource Management Survey. Annual farm survey (for years ), jontly conducted by Economc Research Servce and Natonal Agrcultural Statstcs Servce, U.S. Department of Agrculture, Washngton, D.C. Avalable at data/arms/ (accessed Aprl 5, 006).
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