No Slide Title

Report
Illinois Farmland
Assessment Process
March 9, 2012
Champaign, Illinois
Bruce J. Sherrick
University of Illinois
Dept. of Ag and Consumer Econ.
Illinois Farmland Assessments (PA 82-121)
– Current Law Implemented in 1981, minor updates
– Use Valuation approach (common in most
MidWest states for ag land, various forms)
– Considered preferential relative to Market Value
– Tied to productivity index of soils, prevalent crop
rotations, and average prices and costs over
previous five-year rolling windows, no
government payments, with 10% limits on change
– Gross return less non-land cost calculated at each
point on the PI scale to arrive at income potential
Illinois Farmland Assessments (continued)
– Income potential is then capitalized by 2032a rate
to determine Ag Use Value (AUV)
– AUV divided by 3 to arrive at Equalized Assessed
Value or EAV
– EAV changes limited to +/- 10% annually, by PI
– Points on PI scale below lowest cropped land have
straight line relationship down to 1/6 of lowest PI
– Implemented on soils-weighted (rather than parcel
weighted) basis, a few difficulties remain.
Illinois Farmland Assessments (continued)
– Applies to:
• Cropland
• Permanent Pasture
PI-based
• Other farmland
• Wasteland
• Related: Woodland areas – but complicated
taxonomy that is not particularly satisfying
– Acre weighted SEF basis, Soil classifications
SSURGO – UI listing (Bulletin 810 from 1156)
Illinois Farmland Assessments (continued)
Some details that matter:
Time Line Scematic:
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
For tax bills in:
Calc's done in:
Using data from:
Illinois Farmland Assessments (continued)
– FBFM Certified Grain Farm Records used as basis
for nonland costs (NLC), crop rotations, and property
taxes paid. Accounting data are of very high quality.
– Large number of acres, PI points, etc., summarized at
each PI point each year for actual costs and returns
information, Gross Return (Gross) weighted by acres
in corn, soybeans, wheat, oats, hay, sorghum.
– Yield functions for an “average” producer at each PI
point for each crop, with time trend reflected.
– Numerous record keeping changes by FBFM through
time have been reflected in process.
Illinois Farmland Assessments (continued)
– FBFM data (about 2,600 records per year, 5 years
in each set) on operated acre basis to accurately
reflect differences in lease types through time.
– Yields standardized at 810 scale adjusted for time
(good or bad management does not affect income
potential). Examples for 125 PI farm:
Year
PI
2011
125
Yield Models
Corn
Soybeans Wheat Oats
Hay
Sorghum
186.09
51.54
65.72
84.67
5.65 120.59
Crop Rotations vary little through time….
Percentage of acres by crop/year:
Year
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Corn
Soybeans
Wheat
Oats
Hay
Sorghum
49.8%
49.8%
50.3%
51.2%
53.1%
55.5%
52.8%
61.1%
57.4%
56.7%
57.1%
47.6%
47.9%
47.4%
45.4%
43.0%
41.3%
43.3%
35.2%
38.6%
40.0%
41.0%
1.7%
1.5%
1.4%
1.8%
2.3%
1.6%
2.4%
2.3%
2.7%
2.2%
0.8%
0.1%
0.0%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.7%
0.8%
0.6%
1.2%
1.4%
1.3%
1.3%
1.2%
1.2%
1.1%
1.0%
0.1%
0.1%
0.2%
0.2%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.0%
Prices used in average do vary through time….
Example Corn Averaging Process
Monthly Average Corn Farm Price Received in Illinois
for the 2000 - 2011 Calendar Year(s)
Aves
Year
Jan
Feb
Mar
Apr
May
Jun
$/bu.
Jul
Aug
Sep
Oct
Nov
Dec
Avg*
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
1.97
1.97
2.01
2.37
2.37
2.23
2.06
3.01
3.88
4.34
3.63
4.94
…
2.03
2.00
1.98
2.35
2.65
2.02
2.08
3.44
4.58
3.75
3.48
5.64
2.11
2.00
1.98
2.36
2.77
2.09
2.12
3.52
4.69
3.74
3.53
5.73
2.02
1.92
1.96
2.40
2.97
2.09
2.20
3.48
5.15
3.81
3.42
6.68
2.20
1.86
2.00
2.43
2.93
2.05
2.26
3.52
5.25
3.95
3.49
6.65
1.89
1.83
2.05
2.39
2.87
2.12
2.28
3.64
5.71
4.01
3.41
6.56
1.66
1.95
2.24
2.20
2.49
2.23
2.28
3.32
5.43
4.10
3.51
6.57
1.54
1.99
2.47
2.16
2.35
2.03
2.15
3.16
5.17
3.32
3.73
6.96
1.64
1.94
2.50
2.18
2.20
1.92
2.20
3.21
4.99
3.27
4.05
6.09
1.80
1.85
2.36
2.13
2.22
1.83
2.62
3.31
4.29
3.59
4.52
5.87
1.92
1.91
2.33
2.21
2.08
1.87
3.01
3.53
4.11
3.55
4.62
5.90
2.03
2.06
2.37
2.34
2.17
2.01
3.00
3.73
4.09
3.56
4.86
5.92
1.90
1.94
2.19
2.29
2.51
2.04
2.36
3.41
4.78
3.70
3.85
6.13
Prices used in average do vary through time….
•Recent higher prices
replace older lower prices
in 5-yr ave process.
• Corn and Soybean
weights dominate the
process
•Cost side somewhat
parallel movements, but
not fully
Calendar Year Average Prices
$/Bu
$/Bu
Year
Corn Soybeans
2004
$2.51
$7.51
2005
$2.04
$6.02
2006
$2.36
$5.75
2007
$3.41
$7.97
2008
$4.78
$11.66
2009
$3.70
$10.29
2010
$3.85
$10.14
2011
$6.13
$12.79
Ave 06-10
$3.62
$9.16
Ave 07-11
$4.37
$10.57
$/Bu
Wheat
$3.41
$3.19
$3.62
$5.17
$6.67
$4.27
$5.09
$6.86
$4.96
$5.61
• expect higher gross returns for some period in future
Capitalization Rate based on 2032(a) for Illinois
2032a Rate
(01-05)
(02-06)
(03-07)
(04-08)
(05-09)
(06-10)
Year
2006
2007
2008
2009
2010
2011
Rate
0.0644
0.0602
0.061
0.0638
0.0650
0.0641
*
* No estate tax rate published originally by IRS,
recently released for use in 2011 for 2010 values.
Putting the components together…
– FBFM operated acre records used
• (50% share on 100 acres +50 acres owned =100 operated acres)
– Yc×Pc×Sc+Ys×Pc×Ps … across crops used to get gross
income potential using each year’s data.
– Weighted by rotations, each observation w/PI
– NLCs from accounting data (not allocated at crop level)
for each operator record
– LR calculated = Gross-NLC – importantly, these are
observations at each farm with associated PI
– Must summarize the LR by SPI relationship
(Stacked 5-yr data sets each assessment year)
Putting the components together…
-
Gross less NLC = LR
Summarized at Each PI by
regression across FBFM data.
Matches closely with direct
land income (operator charges
for unpaid labor differ, etc.).
=
How stable is this process?
Yearly Change decomposition ‘10-‘11
Fairly stable summary through time
Recapping the steps so far…
1. Gross calculated using rolling average income potential
for SPI given rotations, prices, yield functions.
2. LRt,i,SPI = Gross-Non Land Costs – using FBFM data
3. Summarized over all records and years to get LR by SPI
4. LR converted to AUV = LR/r where r is the 2032(a) rate
5. AUV converted to base EAV* by dividing by 3
6. EAV* is then subjected to test for movement from
previous year’s EAVcert =min(max(LL,EAV*),UL) where
LL is previous EAV*×.9 and UL = is previous EAV*×1.1
Seems like a 10% limitation at first glance, right?
Illinois Farmland Assessments (continued)
– Repeated application of 10% limit, and other
historic artifacts has resulted in a highly “kinked”
relationship between PI and EAVS with low end
“stuck” in narrow band.
– Higher productivity soils not constrained as much
• 10% of $10 is a small change. 10% of $500 can matter.
– Cap Rate changes have been minor (less variable
than comparable point on yield curve) but will
matter in future (see later slide).
Change Limits have resulted in kinks and curves in
Certified EAVs (the ones that matter to tax bills)….
Certified EAVs and Limits (2011)
600
500
EAV
400
LL
300
UL
200
100
0
80
90
100
110
PI
120
130
Illinois Farmland Assessments (continued)
– Fact that the calculated EAVs are generally well
above the certified can lead to worse relative
certified EAVs through time. Many taxing bodies
at Extension Limitation (thus, can’t raise rates).
– Examining alternatives to implementing rate
change limitations.
– PTELL separately addresses rate of increase in
EL, not part of this set of calculations.
– Woodlands a separate issue as well.
What happens over time?
Relative disparity gets worse…. Income ratio and
value ratio of 2:1 has assessment ratio of 60+
Calculated EAVs make sense and have about the right
ratio from low to high PI points – not a calculation issue
$3,000
IDOR Farmland Assessment Items
$2,500
2011
$/Acre
$2,000
$1,500
EAV
AUV
$1,000
LR
$500
$0
80
85
90
95
100
105
110
SPR (810 conversion)
115
120
125
State level information: SPR
Jo DaviessStephenson
Winnebago
BooneMchenry Lake
Carroll
Illinois
Ogle
Whiteside
Kane
De Kalb
Du Page
Cook
Lee
Kendall
Will
Rock Island
Henry
Bureau
La Salle Grundy
Putnam
Mercer
Stark
Kankakee
Marshall
Knox
Livingston
Henderson
Warren
Peoria Woodford
Tazewell
Ford
Mclean
HancockMcdonough Fulton
Mason
Schuyler
Adams
Vermilion
Champaign
Piatt
Dewitt
Logan
Brown Cass
Iroquois
Menard
Macon
Pike
Morgan
Scott
Douglas
Sangamon
Christian
Edgar
Moultrie
Coles
Shelby
Clark
Cumberland
Greene
Macoupin
Montgomery
Calhoun
Jersey
SPI county ave farmland
90 to 94
94 to 97
97 to 104
104 to 112
112 to 117
117 to 121
121 to 122
122 to 127
No data
Effingham
JasperCrawford
Fayette
Bond
Madison
Clay
Marion
Richland
Lawrence
Clinton
St Clair
Monroe
Washington
Jefferson
Perry
Randolph
Wayne
Wabash
Edwards
HamiltonWhite
Franklin
JacksonWilliamson
SalineGallatin
Union Johnson
Hardin
Pope
PulaskiMassac
Alexander
State level information: PTELL
Jo DaviessStephenson
Winnebago
BooneMchenry Lake
Carroll
Illinois
Ogle
Whiteside
Kane
De Kalb
Du Page
Cook
Lee
Kendall
Will
Rock Island
Henry
Bureau
La Salle Grundy
Putnam
Mercer
Stark
Kankakee
Marshall
Knox
Livingston
Henderson
Warren
Peoria Woodford
Tazewell
Ford
Mclean
HancockMcdonough Fulton
Mason
Schuyler
Adams
Vermilion
Champaign
Piatt
Dewitt
Logan
Brown Cass
Iroquois
Menard
Macon
Pike
Morgan
Scott
Douglas
Sangamon
Christian
Edgar
Moultrie
Coles
Shelby
Clark
Cumberland
Greene
Macoupin
Montgomery
Calhoun
Jersey
Effingham
JasperCrawford
Fayette
Bond
Madison
Clay
Marion
Richland
Lawrence
Clinton
PTELL Counties 2010
Not PTELL
PTELL
No data
St Clair
Monroe
Washington
Jefferson
Perry
Randolph
Wayne
Wabash
Edwards
HamiltonWhite
Franklin
JacksonWilliamson
SalineGallatin
Union Johnson
Hardin
Pope
PulaskiMassac
Alexander
Cropland tax Per Acre (approx. ave)
5.09
12.46 10.92 13.11 10.32 7.22
Jo DaviessStephenson
Winnebago
BooneMchenry Lake
12.58
Carroll
Illinois
14.97
Ogle
9.69
Whiteside
16.55
21.74
Kane 9.67
De
Kalb
14.69
Du Page
Cook
Lee
17.04
Kendall
6.79
13.04
15.82
Will
Rock Island14.00
18.66 11.74
Henry
Bureau
15.20
13.46
La Salle Grundy 7.78
19.63 Putnam
Mercer
Kankakee
16.35
Stark
17.89
Marshall
12.12
15.04 21.65 Knox
Livingston
10.39
13.55 18.66
Henderson
Warren
13.61
Iroquois
Peoria Woodford
Ford
15.33
19.91
21.72 12.92 Tazewell
14.46
Mclean
Mcdonough
Fulton
Hancock
7.13
17.11
20.42 18.23
Mason
11.85
21.28
Vermilion
Dewitt
24.32
18.53
Champaign
Schuyler
Logan
8.00
8.89 13.61
Piatt
Menard
Adams Brown Cass
23.43
19.36
19.25
Macon
16.51
Douglas 19.03
8.21
Sangamon
6.33
20.15
13.86
Morgan
Edgar
Scott
17.69
Pike
Christian Moultrie
10.33
Coles
4.91
Shelby
12.58
3.33
9.81
7.95
Clark
Greene
Cumberland
Montgomery
5.71 7.30 Macoupin
2.51
Calhoun
Jersey
2.85Effingham 2.95 3.74
JasperCrawford
3.31 Fayette
5.89
Bond
2.49
Madison
2.12 2.48
2.16
Clay
Richland
Lawrence
3.85
Marion
Clinton
5.26
2.38 3.204.50
3.34
St Clair
WayneEdwards
Wabash
3.25
Washington 1.93
Monroe
Jefferson
2.41
2.42 4.36
2.83
Perry 2.68 HamiltonWhite
Randolph
Franklin
Approx Farmland Tax Per Acre
0.00 to 2.83
2.83 to 3.83
3.83 to 7.13
7.13 to 10.33
10.33 to 13.55
13.55 to 16.51
16.51 to 19.63
19.63 to 25.32
No data
3.18
1.91 2.97 6.47
JacksonWilliamson
SalineGallatin
4.13
3.35 1.65
Hardin
Union Johnson2.34
Pope
3.16
7.653.49
Massac
Pulaski
Alexander
% Extensions from farmland
Jo DaviessStephenson
Winnebago
BooneMchenry Lake
Carroll
Illinois
Ogle
Whiteside
Kane
De Kalb
Du Page
Cook
Lee
Kendall
Will
Rock Island
Henry
Bureau
La Salle Grundy
Putnam
Mercer
Stark
Kankakee
Marshall
Knox
Livingston
Henderson
Warren
Peoria Woodford
Tazewell
Ford
Mclean
HancockMcdonough Fulton
Mason
Schuyler
Adams
Vermilion
Champaign
Piatt
Dewitt
Logan
Brown Cass
Iroquois
Menard
Macon
Pike
Morgan
Scott
Douglas
Sangamon
Christian
Edgar
Moultrie
Coles
Shelby
Clark
Cumberland
Greene
Macoupin
Montgomery
Calhoun
Jersey
Effingham
JasperCrawford
Fayette
Bond
Madison
Clay
% Farm Extension of Total
0% to 6%
6% to 11%
11% to 16%
16% to 20%
20% to 26%
26% to 30%
30% to 39%
39% to 53%
No data
Marion
Richland
Lawrence
Clinton
St Clair
Monroe
Washington
Jefferson
Perry
Randolph
WayneEdwards
Wabash
HamiltonWhite
Franklin
JacksonWilliamson
SalineGallatin
Union Johnson
Hardin
Pope
PulaskiMassac
Alexander
How does income potential relate to farm value
through time? One proxy would be cash rent.
$7,000
$200
$180
Farmland Value
$6,000
$160
Cash Rent
$140
$120
$4,000
$100
$3,000
$80
$60
$2,000
$40
$1,000
$20
$0
1970
$0
1975
1980
1985
1990
year
1995
2000
2005
2010
Rent - $/Acre
Price - $/Acre
$5,000
Does the Land Market make sense?
Illinois Farmland Rent/Value
14%
12%
10%
8%
6%
4%
2%
10-Yr Constant Maturity Treasury
Illinois Rent/Value ratio
2010
2008
2006
2004
2002
2000
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
1970
0%
Does the Land Market make sense?
Comparison of IL Farmland Value and
Capitalized Value
6,000
5,000
3,000
IL Farmland value
Capitalized value
2,000
1,000
2010
2008
2006
2004
2002
2000
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
0
1970
$/acre
4,000
25,000
0.00%
20,000
-10.00%
-20.00%
15,000
-30.00%
10,000
-40.00%
5,000
-50.00%
0
-60.00%
0
0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2
Price impact of 1% Cap Rate change
Price/acre
What are the largest risks?
Capitalization Rate
$400 Rent
$300 Rent
$200 Rent
%Price Sensitivity
Yield Curve and Cap rate issues
Example Utility for Counties’ Use (farmland section)
Case Identifier
PIN
Champaign - Busey Royal M et. al
25-15-18-200-001
Calculated AUV equivalent
Per Acre AUV equivalent
Per Acre EAV equivalent
Acres Entered
$294,404.88
$3,717.23
$1,239.08
79.2
Enter Information in yellow shaded boxes below
Soil ID
SEF Acres
Soil Name
1
149 A
3.98 Brenton silt loam
2
679 B
2.41 Blackberry silt loam
3
56 B
16.63 Dana silt loam
4
152 A
55.34 Drummer silty clay loam
5
56 B
0.84 Dana silt loam
6
PI
125.1
126.0
116.0
127.3
116.0
Adj. PI
125.1
124.7
114.8
127.3
114.8
Other Tools at:
Farm.Analysis.Solution.Tools
•
•
•
•
•
Real Estate Purchase Analysis
Soil Productivity Utilities
Farm Rent Evaluator
Lease Form Templates
Other farmdoc resources
– url: www.farmdoc.illinois.edu
Thanks!
[email protected]
Control composition changing
Source: FBFM and USDA
Illinois farmland

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