Is there a “wine premium” in Chilean rural land values?

William Foster, Gustavo Anríquez, Oscar Melo, and Jorge Ortega

Some questions regarding Chilean rural land values

• Main question: What factors explain rural land values in Chile?

• A motivating concern: Can we anticipate the impact on land values of possible future climate scenarios?

• An additional question: Beyond characteristics of a geographic area related to future income-generating potential (e.g., soil types, climate, distance to markets and likely future demographic trends), does information regarding specific activities add to our ability to predict land values?

Specifically, to what degree might wine grape cultivation contribute to a rural areas land values?

• The value of rural land in a geographic area (such as a county) should reflect the present discounted value of future income streams from farming activities and (as yet unrealized) potential residential use. – We look at Chilean “comunas” – municipalities.

• Once one has accounted for all of a geographic area’s relevant characteristics, it would be reasonable to presume that per-hectare land values should be predictable in a cross-section without reference to the specific composition of agricultural activities taking place at a given time.

If land use decisions are optimal, basic characteristics should determine profit-maximizing

crop mix at a specific place and point in time.

• There is, however, the possibility that a particular type of land use, such as wine grape cultivation, might be associated both with– significant immobile investments, such as plantations, the

value of which should be bid into vineyard values, – and with other activities, such as wineries and tourism,

which have external effects on the value of all land in the surrounding area.

• So land use composition could offer additional information regarding area-wide land values beyond that of the area’s intrinsic characteristics of climate, market access, soil types, etc.

Distance from markets / market potential0

Example: Simple von Thunen model : land value is proportional to yearly rent, which depends on activity selected.

Activity A

Activity B

Activity C

Activity net income depends on value of crop sales at center and cost of transport. Activity A is a high-value perishable, C is durable, bulk commodity.

Yearly rent per hectare

Empirical approach

• Let’s look at the correlation between rural land values at the municipal level and basic factors: climate, market potential, and others.

• Then add farm activities in “comunas” – does this add information or is it redundant?

• Account for geographic correlation and possible spillover effects.

• Results are “exploratory” and needs refining.

Land value data

• Two sources of Chilean rural land value data:– Classified ads for sales offers (Revista del Campo)– Transactions recorded in CBRs – registries.

• We use data from 37 land registry offices out of the 118 CBRs in total covering full area of study.

• Registries were selected randomly in a stratified sampling framework to ensure adequate geographic coverage. The geographic unit of analysis is the municipality.

• 15 agro-ecological zones and 5 macro zones (north to south) combined to 28 strata.

• In each stratum, the sample of 1-3 CBR were chosen with probability proportional to number of farms.

Land value data

• Data for 1980, 1990, 1997 and 2007 were gathered from recorded land transactions in 37 land registries covering 9 regions and 178 municipalities from Region III to Region X.

• After processing the basic data, information is available for land area and per-hectare values for 32,453 individual land transactions.

• Initial analysis of the real (cost-of-living-corrected) value per hectare of land shows that parcel values vary significantly according size and region.

Región 1980 1990 1997 2007 Total 3 63 143 120 195 521 4 307 242 238 201 988 5 329 485 560 872 2,246 6 1,040 971 1,367 1,237 4,615 7 1,639 1,345 2,033 2,561 7,578 8 824 1,092 1,436 2,576 5,928 9 753 1,062 1,685 2,543 6,043 14 267 310 252 423 1,252 10 319 424 1,097 1,442 3,282

Total 5,541 6,074 8,788 12,050 32,453

Count of recorded rural transactions by Chilean Region and Year

Región 1980 1990 1997 2007 Total3 31.00 8.50 5.42 1.96 5.204 16.70 2.50 2.26 0.51 3.605 9.09 0.76 0.75 0.73 0.976 10.40 2.00 2.04 1.00 2.987 15.85 2.62 1.50 1.45 3.158 34.40 5.00 3.00 2.10 3.709 40.00 8.74 4.21 4.20 6.00

14 47.50 9.91 5.48 3.00 9.9410 44.20 8.40 1.26 1.09 2.23

Total 17.80 3.81 2.04 1.78 3.40

Median number of hectares in recorded transactions

Región 1980 1990 1997 2007 Total3 13.25 6.15 20.88 144.44 38.734 15.92 52.12 62.07 652.70 49.055 27.77 238.03 703.20 591.88 375.386 39.32 89.65 194.63 366.34 131.147 14.03 64.50 125.12 154.01 73.688 7.57 17.85 42.60 66.36 38.419 7.86 12.86 47.28 51.84 30.27

14 14.30 21.97 41.61 91.90 34.0610 10.30 18.26 142.00 108.77 71.12

Total 14.86 32.16 90.40 107.80 59.17

Our variable of interest: Median value per hectare in UF in recorded transactions.

We use the median values per hectare in UF in recorded transactions at the municipality level – 89 comunas for 4 years

The final assumption is that the observed value of parcel j , Vj , is the maximum value over all possible activities (a = 1,2,…,A):

1 2ln max ln , ln ,..., lnj j j AjV V V V

As Schlenker, Hanemann and Fisher (2009) note that, if in the decomposition of the error term into a parcel effect and an activity effect (uaj = vj + εa), the error associated with the activity effect is not extreme-value distributed, then there is no closed-form solution for the expected value of the value equation; and the generic hedonic expression

ln j j jV X

is an approximation to the land-value envelope of the possible rents over all activities.

Basic conceptual model of land values

100

200

300

400

500

600

UF

/HA

1997 2007

No yes

If the municipality has Vineyard more than 1% of agricultural areaLand value per hectare in the Municipalities of Chile

100

200

300

400

500

UF

/HA

1997 2007

No yes

If the municipality has Fruits more than 5% of agricultural areaLand value per hectare in the Municipalities of Chile

Looking only at activities, certainly there is a strong correlation with median

municipal land values and whether or not comuna has

vineyards and fruit production. Or can we explain this by more

basic characteristics?

Wine grapes

Fruit

Spatial Durbin model – SDM – available in Stata – includes both endogenous and exogenous interaction effects (LeSage and Pace, 2009; Elhorst, 2010; Vega and Elhorst, 2013).

W is determined by distance (inverse). We use random effects, because with fixed we lose the climate information.

SEM : spatial error model M

-50

510

15

ln(U

F/H

a)

0 2 4 6 8 10ln(Hectares)

lnUF_HA Fitted values

R-sq=0.05; Beta=-0.26; n=503

Mean data at Comuna level

-50

510

ln(U

F/H

a)

0 2 4 6 8ln(Hectares)

lnUF_HA Fitted values

R-sq=0.45; Beta=-0.77; n=503

Median data at Comuna level

Land prices and Land size

X’s – What explains per-hectare land values?

- Size of the transaction (parcel size), climate, soils, distance to markets and population centers, local population density.

, hs s sG G w p

Market potential is an index summarizing the distance-weighted incomes of markets near and far:

Incomes and prices vary over time, parameters from

Félix Modrego, Philip McCann, William E. Foster, M. Rose Olfert. 2014. “Regional Market Potential and the Number and Size of Firms: Observations and Evidence from Chile.” Spatial Economic Analysis, 9(3): 327-348.

------- 2015. "Regional entrepreneurship and innovation in Chile: a knowledge matching approach." Small Business Economics. 44(3): 685-703.

(1 )

1

rs

Rd

r s ss

MP Y e G

Region mean lnMP

3 13.844 14.785 18.096 17.947 17.218 17.279 16.1510 15.3414 16.58

Meteorological stations are not optimally positioned for used by economists

Climate variables

Climate variables• Average and standard deviation of temperature and

precipitation, annual, based on monthly records for 533 weather stations from 1964-2012. Municipal stats based on weighting stations based on distance.

510

15

20

Deg

ree

s C

els

ius

1 2 3 4 5 6 7 8 9 10 11 12Month

Curicó_100km Rancagua_100kmParral_100km Osorno_100km

Pitrufquén_100km Los_Angeles_100kmTalca_100km Carahue_100kmSan_Felipe_100km

More X variables• Municipalities are classified by urban/rural-ness, essentially

according to population. 6 types from very rural to metropolitan. RIMISP – Berdegue, et al., 2011.

• Whether or not there is mining in the comuna.• 7 agro-ecological zones: soils, valley vs. piedmont, dryland vs.

irrigation availability, and volcanic/sandy, good for grains.• Percentages of various types of ag activities from Ag census:

– Annual field crops– Grasslands, pasture– Forestry– Fruits– Vineyards– Others: fallow, marginal, structures, unused.

Problem: While there is variation cross-section, the % of

fruits and vineyard do not change very much over time.

But, yes, for crops and forestry.

Summary of results

• With a dummy variable (comuna > 1% of land in vineyards) – close to SAG classification.

• Two periods with Ag Census data for crop proportions by municipality: 1997 and 2007.

• Using four periods (1980, 1990, 1997, 2007) with simple % of plantings in 1997 or 2007, or their average.

• Comparison of results : OLS, RE, SAR, SEM, and SDM.

SDM with random-effects Number of obs 356

Group variable: Comuna2 Number of groups 89

Time variable: periodo Panel length 4

lnUF_HA Coef. Std. Err. z P>z

lnDimensión -0,40 0,04 -8,95 0,00

Ln(market pot. Index) 0,13 0,03 3,87 0,00

Vinas % ave 9707 6,50 2,36 2,75 0,01

Fruit % ave 9707 -0,26 0,83 -0,32 0,75

T_mean 3,29 2,00 1,64 0,10

T2_mean -0,14 0,07 -2,02 0,04

T_cv -0,38 11,65 -0,03 0,97

PP_mean -0,15 0,04 -3,63 0,00

PP2_mean 0,00 0,00 3,58 0,00

PP_cv -2,56 4,80 -0,53 0,59

within = 0,76between = 0,85overall = 0,80

lnUF_HA Coef. Std. Err. z P>zRegión2

5 -1,10 0,92 -1,200,236 -0,97 0,69 -1,410,167 -0,39 0,57 -0,680,508 -0,67 0,40 -1,660,109 -0,58 0,28 -2,060,0414 0,06 0,96 0,060,95

Macro_zonas2rPrecordillera 0,48 0,21 2,290,02

Secano costero 0,09 0,26 0,350,73Secano interior -0,09 0,26 -0,350,73Trumao lomaje 0,65 0,25 2,640,01Valle de secano 0,60 0,20 2,930,00

Valle riego 0,21 0,23 0,920,36TipoTF

Metropolitano (mayor 250m) -0,03 0,22 -0,130,90Rural pluricomunal -0,35 0,20 -1,730,08Rural unicomunal -0,22 0,20 -1,120,26

Rural-Urbano (C18-40m) -0,28 0,25 -1,140,26Rural-Urbano (C40-80m) 0,19 0,22 0,880,38

Bottom line: there is something valuable about having vineyards.

• From dummy model: Municipalities with vineyards have 25-50% higher median land values than otherwise, controlling for climate, soils, market potential, etc.

• From % vineyard model: A 1 point increase in percentage in vineyards increases median value by at least 3%, but in most models 5-7%, relative to “other” uses – mainly marginal land, fallow and structures.

• Plus indirect effects, total impact reaches 10 to 20%.• Ceteris paribus, the proportion of land in fruit production

does not add any information. Ditto for other activities. This suggests that the added value of vineyard is more than the value of plantations.

Other results• Climate important: higher median

temperatures, higher land values, decreasing rate. Lower precipitation, higher land values, decreasing.

• As expected, market potential important. Ceteris paribus, increasing MP from that of the region with the least to that of the highest, the gain in value is on the order of 40%

• Elasticity of transaction size is about -0.4.

Possible sources of wine premium in a municipality’s median per-hectare value.

• Missing variables: endogeneity everywhere? Terroir?• Special and significantly larger land-tied investments

associated with wine grape production, more than fruit plantations.

• Spillovers onto value of all land of having local wine and wineries – the cachet, prestige associated with having a property or

(second?) home in a wine region.– Wineries, tourism

Future detective work

• Is it just wine as an aggregate? We have plantings by variety and asking prices from classified ads, which contain more information regarding property aptitudes. Shorter time span.

• Tourism - is it the presence of wineries, not just the vineyards? Locate wineries, but all or just of a “prestige” level?

• More, better information on basic characteristics.

thanks