The Amenity Value of Agricultural Landscape and Rural-Urban Land Allocation

Aliza Fleischer and Yacov Tsur

Department of Agricultural Economics and Management The Hebrew University of Jerusalem

Rationale:

• Population and income growth 1. Increases housing demand (urban land)

2. Increases demand for environmental amenities (incl rural landscape)

• Ag landscape is public good • market failure and need for regulation

Objectives:• Analyze the role of agricultural landscape in rural-urban

land allocation, allowing landscape amenity value to vary across crops

• Evaluate welfare loss due to market failure

• Study effects of population and income growth

• Draw policy implications

Model:

Urban sector: • N households, derive utility from housing land

(H =LH/N), other private goods z, and crop-specific agricultural landscape (L = (L0,L1,L2,…,LJ):

u(z,H,L) = up(z,H) + ue(L)

• Max u over {z, H} subject to budget constraint gives demands z(rH,y) and H(rH,y). Inverting H(rH,y) inverse demand for urban land DH(H,y): 

Urban land demand

AHLLL

DH

$/ha $/ha

Urban sector WTP for Ag landscape

Indirect utility:

v(y , L) = up(z(rH,y),H(rH,y)) + ue(L)

Willingness to pay (WTP) to preserve landscape pattern L = (L0,L1,L2,…,LJ), denoted wtp(y,L) is defined by

v(y + wtp(y,L) , 0) = v(y , L)

Conditional WTP:

Conditional WTP to preserve land type j (Lj) given all other crops land allocation (L-j):

Jjdsssywtpywtpj

jjjj ,...,2,1,0,]/),,([),,(0

L

LLL

Ag sector: Farmland demand NA identical farmers growing K crops

Fk(xk,k) crop k production function,

MAX_{xk}

xk(k), k = 1,2,…,K (prices suppressed as arguments)

k(k) = pkF(xk(k),k) - pxxk(k), k = 1,2,…,K

At land rental rate r, farm’s demand for cropland k:k(Lk/NA) = r, k = 1,2,…,K

Demand for Ag land: horizontal summation:

K

k kxkkkk xpxFp1

}),({

$/ha

ha

Crop 1Crop 2Crop 3

Aggregate

Market Allocation

Market equilibrium:

The region size is given, thus:

Market allocation:

KkNLyNLD AkkHH ,...,2,1),/('),/(

LLLK

kkH

1

MHL and M

kL , k = 1,2,…,K

Market Allocation

AH LLL

LA MAL

$/ha $/ha

Ag land demand Urban land demand

Social allocation

Max:

FOC:

Social land allocation:

K

kAkkA

NL

HKH NLNywtpdyDNLLLLWH

1

/

0

21 )/(),(),(),...,,,( L

KkNLL

ywtpNyNLD AKk

kHH ,...,2,1),/('

),(),/(

L

SHL and S

kL , k = 1,2,…,K

Schematic (incorrect) view:

AH LLL

DH

DA

SAL LA

MAL

$/ha $/ha

DW loss

Population effect:

AH LLL

SAL

LA MAL

$/ha $/ha

Application to the South Sharon region in Israel

• Non-metropolitan region

• 10,190 ha, of which 200 ha are parks

• Number of households: about 70,000

Agricultural Data and Land Use Distribution of the Study Region

Land use (1,3) (ha)

Revenue(2)

($/ha) Cost(2) ($/ha)

Profit= revenue-cost

($/ha) (2) Flowers (greenhouses) 190 98,358 83,596 14,762

Other orchards 440 20,780 14,224 6,554

Vegetables 2,080 53,587 47,078 6,509

Citrus groves 1670 10,173 7,669 2,504

Irrigated field crops 670 2,224 1,956 268

Unirrigated field crops 840 740 651 89

Natural open space 200 - - -

Housing 4,100 - - -

CRS technology: farmers' derived demand for land

1000 2000 3000 4000 5000 6000

2000

4000

6000

8000

10000

12000

14000

Greenhouses

Orchards Vegetables

Citrus

Irrigated field crops Unirrigated field crops

Hectares

$ ha-1

Urban land demandDescriptive Statistics of the Regional Councils' Data

Variables Description Mean SD

ph Payment to the ILA ($ per ha) (1) 758,357 828,568

h Developed land per household (ha) (2) 0.12 0.07

distance Measured in distance rings from metropolitan center(3)

2.4 2.0

rank Socio-economic ranking of local authority (4) 31.5 14.9

age The median age in the Regional Council(4) 26.7 3.7

permatriculation Percent of high-school graduates receiving matriculation certificate as a share of the age group 18-19(4)

52.9 12.2

area Total area of Regional Council in km2 (2) 285.1 186.2

motorate Percent of car owners (4) 26.6 8.7

Urban Land demand estimation

Variable Coefficient SE

h0 10.65** 1.63

log(h) -0.712*** 0.44

log(distance) -1.36** 0.31

log(rank) 0.56* 0.31

R2 0.60

N 33

iihRihdhhihhi Rankdistancep )]log()log([)log()log( 0

WTP data, specification & Estimation

• Data collected via double-bounded-dichotomous-choice elicitation method

• Focus groups, pre-test and face-to-face questionnaire

among 350 respondents

• Respondent received pictures of crops landscape; confronted with scenario under which the agricultural landscape would be developed

• Preserving ag landscape requires a tax (at the bid level)

Transforming Crops to Crop-groups based on data

Crops Crop groups

Index k Description Area symbol Index j Description Area symbol

1 Flowers (greenhouses)

L1 1 Orchards and

citurs (k=2, 4) L1=L2+L4

2 Orchards

L2 2 Field crops, vegetables and open space (k = 3, 5, 6, 0)

L2 = L3 + L5 + L6 + L0

3 Vegetables L3 3 Flowers (k=1) L3=L1

4 Citrus L4

5 Irrigated field crops

L5

6 Unirrigated field crops

L6

0 Reserved open space

L0

WTP specification (permits interaction)

3223311321122

21

3

1

)( iiiiiiijjj

ijijiwtp LLLLLLLL

Conditional WTP:

wtp1i = (1 +1yyi + 1AAgei)Li1+ (12Li2 + 13Li3)Li1+ 0.51Li12

wtp2i = (2 +2yyi + 2AAgei)Li2+ (12Li1 + 23Li3)Li2+ 0.52Li22

wtp3i = (3 +3yyi + 3AAgei)Li3+ (13Li1 + 23Li2)Li3+ 0.53Li32

Likelihood of i’th observation:

nnifBLwtp

nyifBLwtpBwtp

ynifBwtpBUwtp

yyifBUwtp

ijj

ijj

ijj

ijj

ijj

ijj

ijj

ijj

ijj

ijj

ijj

ijj

ij

1

11

11

1

)]11

exp(1[

)]11

exp(1[)]11

exp(1[

)]11

exp(1[)]11

exp(1[

)]11

exp(1[1

Descriptive stat of WTP data

Variables Description Mean SD

Age Years, head of household 43.2 16.9

Income Monthly income after tax ($) 1,674 788

L1 (1) Area of crop group 1 (citrus and other orchards) 2,124 1,184

L2 (1) Area of crop group 2 (field crops, vegetables,

open space) 4,804 5,279

L3 (1) Area of crop group 3 (greenhouses) 123 187

Estimation results (MLE)Group1 (orchards and citrus) Coefficient Std. Err. 1/1 (own effect) ** -5.410-7 1.8610-7 13/1 (interaction with greenhouse) ** 7.4110-7 3.910-7 12/1 (interaction with field crops) -2.210-8 1.9910-8 1/1

** 0.00127 0.00044 1y/1 (income) * 4.2810-8 2.2810-8 1A/1 (age)** -1.1910-5 510-6 1/1

** 0.057 0.0053 Group 2 (vegetables, field crops and open areas) 2/2 (own effect) -8.6510-9 9.610-9 23/2 (interaction with greenhouses) 1.4210-7 2.0210-7 2/2

** 2.8110-4 1.4310-4 2y/2 (income) 6.8310-9 7.9710-9 2A/2 (age) ** -4.5710-6 1.6710-6 1/2

** 0.057 0.0068 Group 3 (greenhouses) 3/3 (own effect)** -1.510-5 6.8910-6 3/3 0.00545 0.00468 3y/3 (income) -1.1710-7 2.9710-7 3a/3 (age) -710-7 7.810-7 1/3

** 0.069 0.0066

Market Allocation

2000 4000 6000 8000 9,990

100

200

300

400

500

600

DAM

DH

LAM = 4,490 ha LH

M = 5,500 ha

Social Allocation

5000 5500 6000 6500 7000 7500 8000

100

200

300

400

500

DH

DAM

DAS

LAM = 4,490 ha LA

S = 5,061 ha

Population effect (doubling the population)

4750 5000 5250 5500 5750 6000

100

200

300

400

500

600

700

DAM

DAS )N=70000(

S N (

) (

DH )N=70000(

DA ) =140000

DH N=140000

LAS )N=70000= ( 5,061 ha LA

S )N=140000 = (5,234 ha

Summary of empirical findings

Total area: 10,190Reserved open space: 200 haArea for allocation between crop production and housing: 9,990 ha

N= 70,000 householdsN = 140,000 households

MarketSocial MarketSocial

LA (ha)4,490 ha5,061 ha4,380 ha5,234 ha

LH (ha)5,500 ha4,929 ha5,610 ha4,756 ha

Aggregate WTP)$( 3,478,350

3,594,780

6,910,0007,260,000

WTP as a share of return from

farming)%( 15.51631.633.5

Main empirical findings:

• Accounting for Ag landscape reduces urban land allocation by 10 % and increases farmland allocation by about 13 %

• Aggregate WTPs for Ag landscape are currently about 16 % of total return to farming and will increase to 33 % with a doubling of the population

• Population growth calls for an increase in Ag land (contrary to market allocation)

Policy:

• Intervention:

• zoning

• Market-based mechanisms, e.g., rural tourism infrastructure

• Ag landscape subsidies

•Implications for farm programs