This paper formulates an information measure for changes in asset values and applies the formulation to farmland values in the United States for 1960-99. The results indicate that changes in asset values contained significant information following the Russian wheat sale in the early 1970s and the financial crisis in agriculture in the mid 1980s. Further, information about preceding year's asset value largely explains the regional distribution of current year's farmland values.Land Economics/Use,

Erickson, Kenneth W.

Mishra, Ashok K.

Moss, Charles B.

English

Research Papers in Economics

1
NEXT YEAR ON THE U.S. FARMLAND MARKET: AN INFORMATIONAL
APPROACH
Charles B. Moss,
Ashok K. Mishra,
And
Kenneth Erickson
†
Paper for presentation at the 2005 AAEA annual meeting
 Providence, RI
July 24-27, 2005
Copyright 2004 [Moss, Mishra, and Erickson]. All rights reserved. Readers may make
verbatim copies of this document for non-commercial purposes by any means, provided
that this copyright notice appears on all such copies.
                                                
† Charles Moss is a professor in the Food and Resource Economics Department at the University of Florida.
Ashok Mishra and Kenneth Erickson are economist with the United States Department of Agriculture,
Economic Research Service. The views presented in this manuscript represent those of the authors and do
not necessarily reflect those of the USDA. Corresponding author: Charles Moss, Department of Food and
Resource Economics, University of Florida, P.O. Box 110240, Gainesville, FL 32611-0240. Email:
cbmoss@mail.ifas.ufl.edu.2
NEXT YEAR ON THE U.S. FARMLAND MARKET: AN INFORMATIONAL
APPROACH
Abstract: This paper formulates an information measure for changes in asset
values and applies the formulation to farmland values in the United States for 1960-99.
The results indicate that changes in asset values contained significant information
following the Russian wheat sale in the early 1970s and the financial crisis in agriculture
in the mid 1980s. Further, information about preceding year’s asset value largely explains
the regional distribution of current year’s farmland values.
Keywords: information measurement, farmland values
1.  Introduction
Measuring the informational content of asset values is not new. Theil and Leender (1965)
and Fama (1965) both present methodologies for measuring the informational content of
stock markets based on informational measures (Theil, 1967). Both studies focused on
information in asset prices based on the number of stocks advancing, remaining constant
or declining from one trading day to the next. Based on these measurements, Theil and
Leender concluded that stock markets in Amsterdam were not informationally efficient
while Fama concluded that the New York stock market was efficient. This study departs
from the formulation in these studies to examine the information content of changes in
relative asset values. Our formulation allows for a regional decomposition of the
information in asset value changes. The informational measure is then applied to
farmland values in the United States. The results indicate that significant information in
farmland values in the United States occurred during the mid 1970s and mid 1980s.3
2.  Measurement of Information
The general formulation of the information measure is presented in detail in Theil (1967).
The information measure used by both Theil and Leenders and Fama can be expressed as
1
ln
N
i
i
i i
p
Ip
q =

= 
 ∑ (1)
where  I is the information index (or the information inequality), pi is the posterior
probability, qi is the prior probability, and N is number of observations. The information
approach assumes that the two sets of probabilities embody the effect of a signal. As
described in Theil and Leenders, I measures the information in that signal or, more
precisely, the difference between the distribution functions resulting from observing
some signal. In both Theil and Leenders and Fama, the difference in the number of stocks
advancing, remaining constant, or declining between two time periods provided evidence
of trends in the stock market. If the measure of information was small, the stock market
possessed a memory.
The specific application of the information index in equation 1 is one of a host of
uses to which information inequality has been applied. Theil (1967) demonstrates how
the index could be applied to measure income inequality. Other studies such as Theil
(1989) built on this application. In this application, qi is defined as the share of income to
group i (usually defined by a geographic region such as a state or country) and pi is
defined as the population share in region i. In addition to demonstrating the versatility of
the information measure, these applications emphasize the measure’s decomposability.
Specifically, grouping the geographic regions into C different groups ( 1, cC = L ) such
that each state belongs to one group, it is possible to show that4
1
1
ln
,
ln
R
C
c
Rc
c c
ci c i
ic ic
C
cc
c
i
c i
c
c i ic
c
III
Q
IQ
P
Qq Pp
IQ I
q
Q q I Q p
P
=
⊂⊂
=
⊂
=+

= 

==
=


= 


∑
∑∑
∑
∑
(2)
where  I is the average inequality in each region,  R I is the inequality across regions,  c Q is
the relative share of  i q  in region c,  c P  is the relative share of  i p in region c, and  c I is the
inequality within region c. Equation 2 allows for the decomposition of the information in
the signal into an average within region measure and a measure of the information in the
signal across regions.
3.  Measurement of Information in Asset Values
We propose to measure the relative information in asset values by comparing the relative
value in the share of asset values across time periods. Specifically, we define vi,t as the
relative share of asset values in state i at time t:
,, ,
,, ,
11
it it it
i NN
it it it
ii
Va l
v
Va l
==
==
∑∑
(3)
where Vi,t is the total value of farmland in state i at time t, ai,t is the acres of farmland in
state i at time t and li,t is the price of land per acre in state i at time t. We can then define a
measure of relative change in asset prices over time as
,1
,1
1 ,
ln
N
it
it
i it
v
Iv
v
+
+
=

=  

∑  .  (4)5
This inequality then measures the relative persistence in the spatial value of land prices.
From equation 3 it is apparent that the changes in information index may be the result of
either relative changes in farmland prices or spatial changes in the acres of farmland in
each state. Accordingly, a similar measure as presented in equation 4 can be derived to
analyze relative changes in the total acres in farmland in each state.
Table 1 presents the information measure utilizing the regional decomposition
1
presented in equation 2. Farmland values in each state were taken from the Balance Sheet
of the Farm Sector published by the United States Department of Agriculture, Economic
Research Service. The total inequality, average regional inequality, and across-region
inequality are also presented graphically in figure 1. These results indicate two periods of
significant information in the change in asset values. The first corresponds with the 1973-
78 period and the second period is from 1983-89. The second period corresponds with the
financial crisis in the agricultural sector during the 1980s. Harl (1990) and others have
suggested that the combination of expansionist fiscal policy and tight monetary policy
during this time period resulted in significant losses in agricultural equity. Particularly
hard hit were the regions that were dependent on export markets for grains such as the
Corn Belt, Lake States, and Northern Plains. The first period corresponds to several
changes in the agricultural sector. First, the grain markets in 1973 experienced dramatic
                                                
1 The regions used in this study are the10 farm production regions used by the Economic
Research Service. The ten regions include the Northeast (Connecticut, Delaware, Maine,
Massachusetts, Maryland, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island,
and Vermont), the Lake States (Michigan, Minnesota, and Wisconsin), the Corn Belt (Illinois,
Indiana, Iowa, Missouri, and Ohio), the Northern Plains (Kansas, Nebraska, North Dakota, and
South Dakota), Appalachia (Kentucky, North Carolina, Tennessee, Virginia, and West Virginia),
the Southeast (Alabama, Florida, Georgia, and South Carolina), the Delta (Arkansas, Louisiana,
and Mississippi), the Southern Plains (Oklahoma and Texas), the Mountain States (Arizona,
Colorado, Idaho, Montana, Nevada, New Mexico, Utah, and Wyoming), and the Pacific States6
increases as a result of increased exports of grain to Russia. Second, the period roughly
corresponds with the oil crisis. Finally, the entire period 1973-78 is typically cited as a
period of excessive inflationary pressure on farmland prices. Thus, the exact cause of the
relative change in information cannot be assigned a priori.
The foregoing discussion implicitly attributes all the informational value to
changes in farmland prices. However, as implied in equation 3 another possibility is that
regional changes in farmland have affected farmland values. Figure 2 presents the
information index applied to relative acres. This figure demonstrates that the information
in relative changes of acreage is small except in 1975 and 1993. The realignment in 1993
can be traced to an adjustment in accounting for Indian land. One possible explanation of
the anomaly in 1975 is the redefinition of the farm. In 1975, a farm was redefined as an
entity with agricultural sales of $1,000 or more. In either case, the results support the
conclusion that the information fluctuations (relative persistence in the spatial values of
land) presented in figure 1 are largely the result of fluctuations in farmland prices rather
than to changing relative acres of farmland in each state.
4.  Conclusions and Suggestions for Further Research
This study examines the persistence of asset values using an informational approach
similar to that developed by Theil and Leender (1965). However, while Theil and
Leender focus on the number of stocks that advance, stay constant, or decline, we
examine the change in relative value of each asset. Specifically, we ask whether the share
of the value of an asset in one year is a good indicator of the share of that asset in the next
year. It is our contention that this formulation is more consistent with the original
                                                                                                                                                
(California, Oregon, and Washington). In addition, while Alaska and Hawaii are not typically7
question posted by Theil and Leender and Fama (1965), that is whether information
exists in the asset market from day to day (or in our application from year to year). While
our application focuses on farmland markets in the United States, the procedure can be
extended to broader capital markets. Further, the decomposition of the informational
approach could be used to examine whether informational content exists for various
market segments (i.e., does more information exist in technology stocks than in
manufacturing stocks).
For the example developed in this study, information about the preceding year’s
farmland values largely explains the regional distribution of this year’s farmland values.
Therefore, the preceding year’s farmland values are a good leading indicator for
forecasting future farmland prices. The exceptions are the emergence of regional
financial stress in the Corn Belt, Lake States, and Northern Plains during the 1980s and
the regional changes that emanated from the Russian grain deal of 1973. Another spike in
the informational inequality in 1993 can be largely attributed to statistical changes in the
definition of farmland.
                                                                                                                                                
used because of idiosyncratic factors, we include these states as a separate region.8
References
Fama, E. F. (1965) Tomorrow on the New York Stock Exchange, Journal of Business,
38, 285–99.
Harl, N. E. (1990) The Farm Debt Crisis of the 1980s Ames, Iowa: Iowa State University
Press.
Theil, H. (1967) Economics and Information Theory. New York: Elsevier-North Holland.
Theil, H. (1989) Development of International Inequality: 1960–1985, Journal of
Econometrics, 42, 145–55.
Theil, H. and C. T. Leenders (1965) Tomorrow on the Amsterdam Stock Exchange,
Journal of Business, 38, 285–99.9
Table 1. Information Inequality for Farmland Values over time
Year Northeast
Lake
States Cornbelt
Northern
Plains Appalachia Southeast
Delta
States
Southern
Plains
Mountain
States
Pacific
States
Alaska &
Hawaii
Average
Inequality
Regional
Inequality
Total
Inequality
1961 602 17 331 127 246 334 42 196 608 2 6 243 237 480
1962 32 102 99 216 183 2 191 0 465 16 18 121 102 222
1963 57 28 116 835 85 213 245 351 748 170 1161 269 138 407
1964 665 31 435 1087 532 337 315 75 1228 237 1534 478 322 799
1965 596 10 338 1234 547 700 214 1081 770 909 13 596 206 802
1966 940 24 716 395 297 121 540 183 478 2 37 399 190 589
1967 749 123 186 300 705 499 1059 54 595 241 1 374 211 585
1968 68 51 166 118 189 634 87 383 260 212 41 198 125 322
1969 385 61 314 75 164 6 142 16 581 57 1 189 116 306
1970 184 202 156 149 19 182 395 202 350 48 151 174 214 388
1971 81 104 584 174 69 355 527 150 292 21 115 270 228 498
1972 385 70 365 727 46 7 137 682 1524 84 0 406 309 715
1973 2258 1152 716 876 476 373 251 306 378 66 1 661 400 1062
1974 390 317 471 285 1972 2027 972 57 2697 132 887 747 1508 2254
1975 1184 2216 1147 1335 373 1325 1737 2 2516 265 2486 1178 1575 2753
1976 978 316 1298 444 359 877 1670 89 2189 441 1106 868 654 1522
1977 662 238 1142 3341 1475 653 21 2272 1952 152 31 1170 165 1336
1978 1164 530 1771 6865 83 61 510 2807 1947 36 1 1587 170 1757
1979 341 231 1128 4157 569 72 413 4 1682 866 203 1057 1062 2119
1980 1260 455 1012 2150 1446 1901 399 383 1575 167 1585 1018 856 1874
1981 704 481 2505 840 1413 2621 1773 1181 3154 188 1520 1465 607 2072
aNumbers represent 100,000 times the actual index measure.
Source: Authors’ computations based on the USDA/ERS Farmland Values from the Balance Sheet of the Farm Sector.10
Table 1. Information Inequality for Farmland Values over time (continued)
Year Northeast
Lake
States Cornbelt
Northern
Plains Appalachia Southeast
Delta
States
Southern
Plains
Mountain
States
Pacific
States
Alaska &
Hawaii
Average
Inequality
Regional
Inequality
Total
Inequality
1982 653
a 53 546 1418 441 368 923 1739 1414 8 298 684 255 939
1983 256 427 329 1300 419 557 491 1925 788 265 34 648 376 1025
1984 408 220 1283 1330 1359 511 572 317 821 69 74 733 1150 1883
1985 342 165 688 353 729 261 225 1 757 204 57 396 664 1059
1986 154 121 370 370 890 161 796 327 311 15 3 307 394 701
1987 351 11 144 400 543 358 316 29 1496 449 181 354 115 469
1988 430 1 412 431 437 68 301 127 422 129 62 271 401 672
1989 49 339 377 1928 49 685 828 202 654 112 12423 567 867 1434
1990 515 156 615 818 409 757 366 43 392 14 13015 454 514 968
1991 380 415 312 84 97 147 769 3 673 2127 484 505 577 1083
1992 367 799 599 487 215 171 208 0 378 519 51 395 631 1026
1993 251 203 2336 35 198 91 99 60 161 1 701 502 627 1129
1994 217 220 1502 243 202 297 888 250 183 145 1939 445 975 1420
1995 113 103 1944 516 68 379 712 183 1897 237 3211 734 1766 2500
1996 289 1611 1047 384 140 49 87 145 476 1 19 462 368 829
1997 438 361 152 983 174 24 338 1451 1044 354 46 469 1058 1526
1998 1710 165 1112 806 1288 509 441 479 508 52 0 675 1680 2355
1999 247 407 616 2287 225 75 280 59 258 318 52 542 308 850
2000 426 615 743 268 125 228 147 502 396 143 342 376 708 1084
2001 1138 404 979 192 369 405 320 726 781 37 300 542 430 972
2002 1420 588 247 241 398 1204 98 4 1703 48 1881 569 1241 1810
aNumbers represent 100,000 times the actual index measure.
Source: Authors’ computations based on the USDA/ERS Farmland Values from the Balance Sheet of the Farm Sector.11
0.000
0.002
0.004
0.006
0.008
0.010
0.012
1960 1965 1970 1975 1980 1985 1990 1995 2000
Year
I
n
f
o
r
m
a
t
i
o
n
 
I
n
e
q
u
a
l
i
t
y
Average Inequality Regional Inequality Total Inequality
Figure 1. Total, Regional, and Average Information in Land Values over Time12
0.000
0.000
0.000
0.001
0.001
0.001
0.001
0.001
1960 1965 1970 1975 1980 1985 1990 1995 2000
Year
I
n
f
o
r
m
a
t
i
o
n
 
I
n
e
q
u
a
l
i
t
y
Average Inequality Regional Inequality Total Inequality
Figure 2. Total, Regional, and Average Information in Land Area over Time

NEXT YEAR ON THE U.S. FARMLAND MARKET: AN INFORMATIONAL APPROACH

Abstract

Similar works

Full text

Available Versions

Research Papers in Economics