Land Values in Frontier Settlements of the Brazilian Amazon

World Development Vol. 36, No. 11, pp. 2390–2401, 2008� 2008 Elsevier Ltd. All rights reserved

0305-750X/$ - see front matter

www.elsevier.com/locate/worlddevdoi:10.1016/j.worlddev.2007.11.014

Land Values in Frontier Settlements

of the Brazilian Amazon

FRANK MERRYWoods Hole Research Center, Woods Hole, MA, USA

Instituto de Pesquisa Ambiental da Amazonia, Belem, Para, Brazil

GREGORY AMACHER and EIRIVELTHON LIMA *

Virginia Polytechnic Institute and State University, Blacksburg, VA, USA

Summary. — Even in the absence of formal land markets, estimated values on agricultural frontiersof the Brazilian Amazon reflect the value-adding characteristics of the land. Understanding thesecharacteristics provides important insights to the incentives (or dis-incentives) to protect tropicalforests and reduce deforestation. A hedonic model is used to identify characteristics determiningsmallholder land values on the Amazon frontier. Years on the lot, area under agricultural produc-tion, and house values were found to add value; while distance from the nearest city and area underforest decreased values. Characteristics that do not appear to significantly affect land value includepasture area and the claim to hold definitive title. By not adding significantly to land values, pasturemay be used to establish property rights rather than to increase land value through positive rents.Our results also confirm the underutilization of the forest resource by smallholders.� 2008 Elsevier Ltd. All rights reserved.

Key words — Brazil, Amazon, smallholder, land value, hedonic model

* The authors gratefully acknowledge the receipt of

research funding from (in alphabetical order): the

European Union; the Gordon and Betty Moore Foun-

dation; the NASA Large Scale Biosphere and Atmo-

sphere Project (NASA LBA-ECO); the National Science

Foundation (NSF); and the United States Agency for

International Development (USAID-Brazil). We also

wish to recognize the support of the Fundacao Viver,

Presevar e Produzir in establishing our credibility with

the settlers of the TransAmazon highway. Finally, tha-

nks to the perseverance of the survey enumerators and

database managers, in particular Rose Guimares and

Ailton Alves of IPAM. Paul Lefebvre produced the map

in Figure 1 at the Woods Hole Research Center. All

errors and omissions are the authors’ alone. Final revi-sion accepted: November 28, 2007.

1. INTRODUCTION

For the dispossessed, the desperate, or thesimply adventurous, frontiers have long repre-sented an opportunity to start anew or improveone’s economic circumstance. History is litteredwith migration to frontiers for economicadvancement, and it is no different for settle-ment households in the Amazon. Families havebeen moving progressively deeper into the rain-forest for many years, in many cases seekingeconomic opportunity that land settlement isperceived to afford. Although beset by violenceand property rights uncertainty, even de factoownership represents vast economic gain formany settlers and an important step towardeconomic security. The TransAmazon highway,an infamous 3,000 km breach of Amazon rain-forest integrity, has been an important destina-tion for migrants to the frontier and is wellknown as an active sector for rapidly expand-

239

ing deforestation in the Brazilian Amazon(Walker, 2003).

0

LAND VALUES IN FRONTIER SETTLEMENTS OF THE BRAZILIAN AMAZON 2391

Built by General Medici in 1969–74, as partof a government program to settle and securedominion over the Amazon rainforest, thehighway is still largely unpaved and virtuallyimpassable for four months each year duringthe rainy season. Still, migration to the regionis relentless, as a constant stream of both for-mal and informal land occupation has followedthe early colonization projects of the 1970’s.The National Institute of Colonization andAgrarian Reform (INCRA), the federal landsettlement agency, has formally settled approx-imately 30,000 families on the 900 km stretchbetween the town of Maraba and Itaituba(Figure 1 and site of this research). Formal set-tlement is based on 100 ha lots in the now-clas-sic fishbone pattern, where feeder roads arestruck 5 km apart into the forest. Each lothas 400 m of road frontage and is 2,500 m(2.5 km) deep, fitting two neatly between eachfeeder road. In theory, a 3-year trajectory isall that is needed to acquire full title, but inpractice the process is rarely completed withinthis timetable (Alston, Libecap, & Mueller,1999; Merry et al., 2006). To add to the settle-ment pattern, formally settled households havebeen joined by countless number of informalsettlers; Lima et al. (2006) estimate that infor-mal settlement almost doubles the estimatednumber of families along the TransAmazon to57,000. With lots size well established, informal

Figure 1. Location of study region along the TransAmazon

Cent

settlement is made ‘‘easy’’ by finding the farpoint of the last lot and walking 400 m to markthe boundary of what then becomes their lot—the lot is then presumed to be the standard2.5 km deep. Lots may begin along a singlehand-cut trail into the forest or a road exten-sion made by illegal loggers searching for tim-ber in unclaimed government land beyond theformal settlement boundaries.

In the absence of easy access to formal titleand with continual competition for land, set-tlers must establish ownership through some‘‘productive’’ activity, such as cattle ranchingor agricultural production. On the other hand,forest based activities in the Brazilian Amazonare not considered to be a ‘‘productive’’ use andtherefore do not advance tenure. This is impor-tant because even in unregulated and risky landmarkets such as the Amazon, the settlementprocess, whether formal or informal, can even-tually lead to entry into the land market, asthose who settle may seek to earn the rent asso-ciated with their settlement actions by sellingtheir land after it has been ‘‘developed.’’ Devel-opment may simply be recognition of residencythat infers de facto title, or some form of tem-porary title granted by the government. Anychange in infrastructure quality (such as clear-ing of land for crops or building of a house)may also be capitalized to various degrees inland values, which can then translate into sales.

highway. Source: Paul Lefebvre, Woods Hole Research

er.

2392 WORLD DEVELOPMENT

The connection between land use and land val-ues then reveals important information on theincentives for deforestation, as well as the pos-sibilities for equitable development on the fron-tier. Should forest area, for example, reduceland value, there will be a clear incentive fordeforestation. Similarly, should agricultural orpasture area increase land value, these incen-tives will be exacerbated. Here, we examinethe determinants of land value on theTransAmazon highway as a step forward inunderstanding the economic incentives for landuse change in the Amazon.

In this region sales are often poorly regis-tered, and so we study land value as estimatedby the owner. A model is estimated relatingland value to several characteristics, includingpolitical, market, and site variables. Settlers inboth the formal and informal settled categoriesmay not have paid for their lots upon settle-ment, and thus we are interested in their per-ception of the characteristics imputed in theirperceived land value. If we can assess thesecharacteristics, then we will know what vari-ables encourage smallholders to migrate andsettle in the Amazon frontiers, to seek title,determine production choices, and to protecttheir land as a longer-term investment. Wecan also assess the value embodied in land bygovernment investment in infrastructure—inthis case roads and road maintenance.

Further, we ask whether property rights mat-ter in a fluid ill-defined land market such asthose common to the frontier. Does obtainingdefinitive title to the land, which comes at someundefined additional cost—in both transactioncosts associated with bureaucracy and the cashoutlay—impute sufficient additional value to bea positive return on investment? In otherwords, is it worthwhile for a settler to even ob-tain title? If it is not, then the barriers to formalentry into a property rights market will create adis-incentive to formal ownership and subse-quent benefits. In addition important questionis to ask whether smallholders impute any valueto forests on their lot. Knowing this will pro-vide an important hint at the incentives (ordis-incentives) to protect these forests andavoid additional deforestation.

Regardless of how land is settled, there is lit-tle formal information concerning what drivesthe value of land in the Amazon frontier. Someimportant exceptions are Alston et al. (1999)who, like us, use smallholder perceived landvalues in lieu of secondary data on land salesto examine the role of conflict and property

rights imputed in these land values. Indeed,the lack of available spatial information onland values led Chomitz and Thomas (2003)to use cattle stocking density as a proxy for va-lue. Further, there are several other excellentstudies, not related to the land value objectiveof our paper, that have examined the humanecology and political economy of Amazon set-tlements (e.g., Perz & Walker, 2002; Simmons,2004; Walker, 2003), and deforestation (e.g.,Aldrich, Walker, Arima, & Caldas, 2006;Brondizo et al., 2002). Collectively, this workhas not considered land markets or the impor-tance of settlement regimes to these markets.Our large scale examination of smallholdersover various settlement regimes and marketconditions allow a deeper examination of theemerging land market in the Amazon. Our va-lue estimates presented here hint at the impor-tant signals of land value once formal marketshave fully developed in the future.

The rest of the paper is structured as follows.In Section 2, we present a brief background onhedonic valuation models and how they mightbe applied in the case of smallholders in theAmazon. In Section 3, we discuss our surveydesign and data, and in Section 4 we present re-sults from applying this model to the differentsettlement types. Finally, we offer concludingremarks.

2. HEDONIC MODELS OF LAND VALUE

The value of a good to an individual is basedon the cumulative values of its componentcharacteristics, some of which may be non-mar-ket in nature (such as environmental quality).Under this assumption, hedonic models are awell-established method for determining themarginal value of each characteristic (Rosen,1974) to the individual. This method is particu-larly useful in housing markets, where, forexample, the number of rooms in a building,square footage, and neighborhood featuresare characteristics contributing to value (Can,1992). It is also a common method in the anal-ysis of land markets where proximity to urbanareas, topography, soils, and other environ-mental and market access characteristics deter-mine value (Chicoine, 1981; Shi, Phipps, &Colyer, 1997; Shonkwiler & Reynolds, 1986).It has also been widely applied to study envi-ronmental amenity values, where particularenvironmental characteristics may factor indetermining land and housing values (Bastian,


McLeod, Germino, Reiners, & Blasko, 2002;Legget & Bockstael, 2000; Smith & Huang,1995).

The usual econometric approach to hedonicmodel estimation is to relate land value to char-acteristics important to the buyer,

P ¼ P ðZ1; Z2; . . . ; Zn;cÞ; ð1Þ

where P represents the market value of land,(Z1, Z2, . . . , Zn) represents the levels of eachcharacteristics of land important to the pur-chaser, and c is an error term. The value estab-lished by the hedonic model results in animplicit price an individual places on each indi-vidual characteristic (Xu, Mittlehammer, &Barkley, 1993). Specifically, the imputed valueof any one characteristic is the marginal contri-bution (or marginal effect) of the variables inthe estimation of (1). In the absence of underly-ing determinants, the choice of functional formis not well agreed upon (for a discussion of this,see Cropper, Deck, & McConnell, 2001; Legget& Bockstael, 2000). In the analysis below, wechose a log–log specification because it mimicsseveral types of utility functions underlyingthe choice implicit in (1).

As we noted earlier, our dependent variablein (1) is the smallholder’s perceived land value.For explanatory variables, the literature pro-vides some guidance if one considers propertystudies in developed countries (see Shi et al.,1997 for an excellent review). For example, ina seminal study of farmland values at the urbanfringe, Chicoine (1981) uses characteristics suchas distance to town, road quality, parcel size,zoning, distance to water source, among othersto estimate land value. In a similar study, Xuet al. (1993) include as explanatory variableslot size, area in pasture, the distance to town,agricultural production value, house size andage, and production infrastructure. Shonkwilerand Reynolds (1986) use area cultivated andparcel size, distance to roads and airports,and the size of the woodlands in their estima-tion of land values on the urban fringe. Theirexplanatory variables included distance to thecity, possession of formal title, percent of landcleared, level of agricultural investment, and adummy variable for jurisdiction.

We apply (1) to a data set comprising of2,494 smallholders collected from theTransAmazon region. The following specificexplanatory variables are used to predict per-ceived land value: time, distance to improvedroads and markets, local infrastructure, land

production choices, settlement regime, andmunicipality. Unlike other work, we also incor-porate market and property rights variablesspecific to the Brazilian Amazon. In this region,land markets can be completely informal suchthat sales are often poorly registered, landown-ers may not pay a price at settlement time, andthe structure of purchase and settlement re-gimes vary greatly across settlements. Thus,market prices for land transactions are notavailable or easily observed. But while manysmallholders, such as squatters and informalsettlers, have not paid a price for their landupon settlement, their perception of land value,and of important characteristics imputed inthat value, gives a suitable instrument for amarket land price. Although any landowner’sassessment is clearly a non-market estimate,that is, the value is not the result of an actualsale (an equivalent price might be a ‘‘listingprice’’ in a fully functioning land market), itdoes represent the best valuation available.We expect, therefore, that the characteristicsimputed in this value indicate what attributesthe smallholder values the most.

A justification for our dependent variable in(1) follows from asset pricing theory literature,which has formed the basis for much work onland values (e.g., Clark, Fulton, & Scott,2001; Fountnouvelle & Lence, 2002; Lavin &Zorn, 2001; Lloyd, 1994; Robison, Lins, &VenKatamaran, 1985). This work suggests thatan exact relationship exists between land rentsand land value, so that production valuesshould be capitalized into actual market landvalues. To validate our data, we tested thisprinciple by computing the ratio of total pro-duction value (the sum of annual agriculturalproduction and cattle sales) to the lot valueestimates each smallholder declared. The re-sults show that the capitalization across small-holders in the entire sample is reasonable butwith considerable variation across settlementregimes: for the whole sample the ratio of pro-duction value to total lot value was 16%; forthose who had bought the lot it was 8%; for-mally settled smallholders estimated the ratioat 39%; and informal settlers at 5%.

Another validation comes from the fact that,in a land market, the net present value of infi-nite returns for using the land in productionis an estimate for land prices. Our results showthat the infinite net present value of annualcrop returns and the difference in this fromthe smallholder’s perceived land value equals,respectively, R$48,792 and 6,876 for the entire


sample, R$48,607 and 6,344 for those whopurchased their lot, R$62,719 and 16,705 forthose formally settled, and R$26,455 and�4,459 for squatters. These figures are closefor purchasers and the entire sample, whereasformal settlers underestimate value and infor-mal settlers slightly overestimate land values.

Perhaps the most important reason for usingperceived land value, however, is to understandwhat characteristics a smallholder feel’s aremost important for his/her land investment;these perceptions of value are critical to under-standing land use decisions. Perceived land va-lue represents the landowner’s valuation ofland characteristics, which affects individualincentives to produce, preserve, or protect land.The smallholder’s assessment reflects activitiesthey judge to be important in imputing this va-lue such as land clearing for pasture or cropproduction and the value impact of landremaining in forests.

3. DATA COLLECTION ANDDESCRIPTIVE STATISTICS

Our data for estimating (1) is taken from anenumerated random survey of 2,494 smallhold-ers along the TransAmazon highway under-taken during June–December 2003. Thesurvey was designed by the authors and imple-mented by a team of 10 enumerators accompa-nied by the authors. Enumerators were trainedby both the authors and the Instituto dePesquisa Ambiental da Amazonia (IPAM).Data were collected within eight municipalitieson the main stretch of the TransAmazon high-way. The sampling strategy was first opportu-nity-based along feeder roads emanating fromthe main highway. The first opportunity ap-proach has been employed in various guises inthis type of data collection where systematicsample collection is difficult (Perz & Walker,

Table 1. Sample dista

Municipality Mean SD

Brazil Novo 28.90 19.7Placas 31.03 13.0Pacaja 33.97 19.5Medicilandia 34.08 17.0Uruara 48.47 16.6Itupiranga 105.94 33.3Novo Repartimento 141.22 48.9

Measured in kilometers from main city.

2002; Walker, Perz, Caldas, & Silva, 2002);our extensive survey, where farms are inter-viewed along a 900 km stretch, also providessufficient spatial distribution to minimize clus-tering. In six of the eight municipalities thesampling began at the entrance from the Tran-sAmazon highway; access to the other two re-stricted this approach and sampling wasconducted further from the highway aroundlarge formal settlements. A target sample sizeof approximately 300 was set for each munici-pality. In the smaller municipalities (i.e., BrazilNovo) we were able to sample almost all feederroads. In the larger municipalities the samplewas spread evenly along the distance of themunicipality. The sampling range is from2 km to 280 km from the city, with a mean dis-tance of 63 km (SD 51 km). In general, our re-sults match well with other surveys done ofsmallholders both in this region and elsewhere(Merry et al., 2006; Walker et al., 2002). Table1 shows the descriptive statistics of the sampledistribution by municipality.

The mean estimated lot value for the wholesample was R$41,927 (SD 45,988), or approxi-mately US$14,000 (Table 2). Per hectare priceswere approximately R$511 (SD 526) orUS$175. There is no significant difference inland price estimates between those who pur-chased land and those who were formally set-tled (p 6 0.05), but informal settlers estimatedtheir land price significantly lower (p 6 0.05)at approximately R$374 (SD 378). This mayindicate similar levels of de facto propertyrights, or that formal settlers and those whopurchase land have access to better qualityland. These valuation estimates made by small-holders match well with broad land price esti-mates presented in Chomitz and Thomas(2003), which showed crop land ranging from$147 in Para to $454 in Mato Grosso. Meanlot size for the whole sample is 83 ha (SD 45,maximum 500 ha), which shows some degree

nce and distribution

Min. Max. N

9 2.00 105.00 2047 6.00 68.00 2906 3.00 115.00 3048 2.00 86.00 2677 3.00 110.00 2614 9.00 220.00 3368 3.00 280.00 394

Table 2. Descriptive statistics for model variables

Description Unit Full sample Purchased lot Formally settled Informal settlementn = 2,358 n = 1,377 n = 629 n = 395

Mean (SD) Mean (SD) Mean (SD) Mean (SD)

Estimated lot value R$ 41,926.57(45,988.32)

42,285.77(46,334.56)

46,170.08(49,971.03)

30,915.35(31,982.41)

Lot size ha 82.71 (44.72) 84.73 (46.76) 79.00 (44.38) 83.37 (41.13)Estimated value per hectare R$ 511.28 (526.02) 523.63 (560.48) 548.60 (518.05) 374.26 (347.43)Years residing on the lot years 10.25 (8.41) 8.68 (7.26) 14.12 (9.25) 9.02 (8.19)Distance to the nearest city km 63.42 (51.13) 58.77 (48.49) 70.46 (53.67) 67.92 (53.56)Km of all weather dirt

highwaykm 14.55 (40.80) 12.51 (36.87) 22.49 (49.11) 9.82 (38.27)

Value of the house on the lot R$ 3,110.42(4,312.41)

3,048.08(3,879.89)

3,644.00(5,536.14)

2,297.54(2,909.06)

Area in pasture at presenttime

ha 21.25 (22.29) 23.46 (24.49) 20.11 (17.69) 15.94 (21.20)

Own cattle % 69.85 (45.90) 74.66 (43.51) 70.68 (45.56) 52.66 (49.99)Herd size head 27.03 (49.33) 31.17 (54.06) 25.33 (45.01) 15.31 (31.70)Number of cattle sold last

yearhead 4.54 (13.46) 5.87 (16.59) 3.44 (7.84) 2.01 (9.08)

Value of cattle sales last year R$ 980.46(3,188.03)

1,223.42(3,801.70)

837.47(2,508.58)

535.66(3,103.64)

Stocking density head/ha 1.31 (4.39) 1.42 (4.46) 1.26 (4.90) 0.98 (2.84)Crop area last year ha 3.12 (3.92) 3.33 (4.24) 2.82 (3.40) 2.93 (3.45)Total value of crop

productionR$ 3,191.38

(10,992.48)3,106.69

(10,902.54)4,136.78

(13,103.56)1,721.18

(5,210.13)Sum of crop and livestock

sales (VS)R$ 3,173.05

(11,288.28)3,160.17

(10,126.99)4,109.24

(15,239.78)1,721.10

(7,326.83)Area deforested R$ 30.93 (25.14) 32.35 (26.81) 30.98 (22.80) 26.17 (23.31)Area in forest ha 50.84 (36.47) 51.18 (37.73) 47.26 (33.87) 56.70 (35.85)Claims definitive title to lot % 26.88 (44.34) 26.04 (43.90) 34.98 (47.73) 12.13 (32.69)Has bought lot % 58.40 (49.30)Formally settled at present % 26.76 (44.28)Squatted on lot % 16.75 (37.35)


of accumulation, but not as much as wasexpected from other studies (Walker, 2003).The value of the homes on the lot were approx-imately R$3,110. The only groups that hadnoticeable differences here were informalsettlers with homes valued lower at onlyR$2,297, and those with definite title whosehomes were valued considerably higher at$4,740.

The mean distance to the city in the sample is63 km with 14 km in all weather dirt highways(see Table 1). In the difficult conditions of theTransAmazon highway, the quality of the roadis paramount; poor roads soon disappear or be-come impassable in the wet season. The portionof the road improved with gravel (picarra) var-ied among the settlement groups; overall thepercentage of gravel roads was 23%. Our resultsshow that the formal settlers had access to thebest quality roads (judged solely by the highest

percentage of distance with gravel), at 31%.Those who bought their lots have access to21% of the road graveled, and the informal set-tler had only 14% of improved roads. On aver-age individuals attained their lots 3 years afterthe road was built. Formal settlers, however,arrived almost simultaneously with the roads,informal settlers arrived 2.3 years later, andpeople who purchased their lots arrived onaverage 4.8 years after the establishment ofthe road. The mean years in residence on thelot for the whole sample is 10.2 years (SD8.4). Individuals who were formally settledhave been on the lots significantly longer(p 6 0.05) than both informal settlers and thosewho had purchased their lots. This seems toindicate that the process of formal settlementbrings an initial wave of settlers, who are thenfollowed, approximately 5 years later, by wavesof land procurement in both purchases and


squatting. There is therefore, some period ofconsolidation of formal settlement process be-fore other in-migration begins.

Mean deforestation for the sample is 31 ha ofland cleared, or approximately 38% of totallandholding at a rate of 3.3 ha per year; this var-ied little between those who purchased or wereformally settled, but informal settlers hadcleared only an average of 32% of their land,while those with definite title cleared an averageof 46%. Of land cleared, between 60% and 70%was put into pasture. Smallholders who boughtthe lot and those with definite title had the high-est percentage of cleared land in pasture. Cattleproduction takes place on 70% of the lots, atstocking densities of 1.3 head/ha. The averageherd size was 27 head with a mean estimated va-lue of R$7,561. This result is comparable to esti-mates of 24 head/herd in smallholder systems inPara by Walker (2003) and is also roughly con-sistent with other estimates throughout theAmazon. Cattle sales were estimated at4.5 head/year with a mean sales value ofR$979 or approximately R$216 per head. Cropswere produced on an average of only 3.12 haper lot, which generated an average total agri-cultural income of R$3,191, or R$1,021 perhectare. The value of agricultural productionin this case is divided into agricultural sales(mean R$2,387, SD R$10,515) and an imputedvalue of agricultural consumption, based onmarket prices (mean R$811, SD R$2,216). Thearea left in forest on the lots was approximately51 ha of the total mean of 82 ha; only 27% ofthe individuals, however, had sold wood.

There are three distinct smallholder groupsrepresented in the data (Table 2): individualswho had bought their lots (58% of sample); indi-viduals formally settled by INCRA (27% ofsample); and individuals who settled informally(16% of sample). When considering the results itis important to remember that while the threesettlement regimes are mutually exclusive, thosewho hold definite title come from all groups. In-deed, of the 27% of the sample who claim tohold definitive title, 56% had bought their lots,32% were formally settled, and 10% had settledinformally; a similar distribution to the originalsample suggests that individuals of all settle-ment regimes have roughly equal access to title.

4. ESTIMATION RESULTS

Table 3 presents results from estimating (1)with our data. The results comprise estimation

with respect to the entire sample, a sub-sampleof those who have bought their lots, a sub-sam-ple of those who had formally settled, and asub-sample of those who settled informally (Ta-ble 3). 1 Interviews with missing values were ex-cluded from the estimation. All results areadjusted for heteroskedasticity using White’smethod (Greene, 1997). As Table 3 shows, allequations have highly statistically significantequation F-statistics. 2 Each equation also hasconsistent t-statistics for significant variables.Given the log–log functional form, the impactof the coefficients is calculated at the meanusing the following equations for numericaland dummy variables, respectively:ðdy

dx� YXÞ ¼ b, and eb, where b is the estimated

coefficient of the explanatory variable of inter-est in Table 3, Y is the mean of the dependentvariable (perceived land value), and X is themean of the explanatory variable of interest.The first term is simply an elasticity of per-ceived value with respect to the characteristic.We now explain the results in three sectionsrepresenting important variable groups: dis-tance and infrastructure; lot characteristicsand production; and time on lot and settlementregime.

(a) Distance and infrastructure

Distance to a city, as expected, has an overallstrong negative effect on land value for settlers:for each additional kilometer, per hectare val-ues decline by R$2.19. This result is roughlyconsistent over all settlement regimes, indicat-ing that distance plays an important role inland values. For example, if we assume thatper hectare values are approximately R$1,000at the city (sample mean plus one SD), land val-ues would be driven to zero at approximately450 km distance, all else equal. The resultsshow, however, that the quality of the road,as measured in kilometers of all weather dirthighways, does not significantly affect land val-ues. This may indicate that all weather dirthighways are not yet present on a sufficientlylarge scale (currently these comprise only 22%of total average distance) to affect land values.

Location within political districts of theTransAmazon highway itself is important toland values due to a combination of accessand political stability differences. There are 10municipalities (we sampled in eight) along themain stretch of the highway. Each of thesehas physical and management attributes thatmay affect value. To test this hypothesis, we in-

Table 3. Regression results (log–log) for estimation of lot value

Description Full samplecoefficient (t-stat.)

Purchased lotcoefficient (t-stat.)

Formally settledcoefficient (t-stat.)

Informalsettlement

coefficient (t-stat.)

Constant 6.538 (21.1)*** 6.407 (14.8)*** 6.826 (11.5)*** 5.957 (8.0)***

Distance to thenearest city

�0.285 (�4.7)*** �0.302 (�3.5)*** �0.246 (�2.4)** �0.293 (�2.3)**

Km of all weatherdirt highway

�0.002 (�0.1) 0.020 (0.6) �0.060 (�1.5) 0.066 (2.3)**

Located inItupiranga

�0.137 (�0.8) �0.096 (�0.4) �0.396 (�1.3) 0.345 (0.6)

Located in NovoRepartimento

0.225 (1.4) 0.239 (1.0) 0.084 (0.3) 0.678 (1.3)

Located in Pacaja �0.413 (�3.2)*** �0.415 (�2.5)** �0.615 (�1.7)* 0.038 (0.1)Located in ofAnapu

�0.372 (�2.8)*** �0.400 (�2.4)** �0.346 (�1.4) 0.083 (0.2)

Located inMedicilandia

�0.196 (�1.7)* �0.366 (�2.5)** �0.162 (�0.8) 0.338 (0.7)

Located in Uruara �0.666 (�5.0)*** �0.720 (�4.2)*** �0.468 (�1.8)* �0.474 (�0.9)Located Placas �0.259 (�2.4)** �0.372 (�2.8)*** �0.174 (�0.9) 0.582 (1.3)Value of the house

on the lot0.099 (3.5)*** 0.126 (2.7)*** 0.076 (1.5) 0.049 (1.2)

Area in pasture 0.024 (0.9) 0.035 (1.1) 0.047 (0.8) 0.039 (1.0)Area in crop

production0.066 (2.2)** 0.069 (2.0)** �0.051 (�0.8) 0.205 (3.4)***

Area in forest �0.160 (�4.1)*** �0.157 (�2.8)*** �0.242 (�3.1)*** �0.074 (�1.4)Years residing on

lot0.202 (5.6)*** 0.153 (3.7)*** 0.262 (2.8)*** 0.162 (2.5)**

Claims definite titleto lot

0.040 (0.6) 0.121 (1.3) �0.209 (�1.5) �0.047 (�0.2)

Formally settled �0.117 (�1.7)*

Informally settled �0.128 (�1.8)*

n = 1,426; R2 = 0.17 n = 797; R2 = 0.18 n = 434; R2 = 0.17 n = 223; R2 = 0.29Adj. R2 = 0.16; Adj. R2 = 0.16; Adj. R2 = 0.14; Adj. R2 = 0.24;F[17, 1,408] = 17.23;p = 0.00;

F[15, 781] = 11.33;p = 0.00;

F[15, 418] = 5.82;p = 0.00;

F[15, 207] = 5.55;p = 0.00;

Log-L = �2,041.96; Log-L = �1,149.38; Log-L = �643.07; Log-L = �255.93;R.Log-L = �2,176.72; R.Log-L = �1,227.84; R.Log-L = �684.25; R.Log-L = �293.62;DW 1.91;BP Chi2 = 380.02

DW 1.78;BP Chi2 = 237.18

DW 1.94;BP Chi2 = 165.25

DW 2.22;BP Chi2 = 122.57

*p < 0.10; **p < 0.05; ***p < 0.01.


cluded a dummy variable for each municipalityin the regressions. In this case the dummy var-iable comparison is made to the municipality ofBrazil Novo, a well-developed municipality lo-cated close to the main city of Altamira in thecenter of the TransAmazon, where we expectedland prices to be the highest. The results showthat location within a municipality is an impor-tant determinant of overall land values. TheMunicipalities Ituprianga and Novo Reparti-mento, however, both of which are closest tothe PA150 (a major highway) and the largetowns of Novo Repartimento and Maraba,

showed no significant difference in land valuesfrom Brazil Novo. All other municipalitiesshowed significant decreases in land values.

In the sub-samples, the ‘‘Municipal effect’’ isheld true for individuals who had purchasedtheir lots, but was not so for formal and infor-mal settlers: there were no significant differ-ences on land values attributable to locationwithin a municipality for these two groups. Apossible explanation for this is that formal set-tlement is not driven by the market (and thuschoice of location) as much—because the deci-sion is not that of the settler but rather IN-


CRA—and by the fact that smallholders aremost likely to settle on the poorer quality landwith worse location and access. Thus, these twogroups value the land characteristics of theindividual lot rather than the effects capturedin the Municipal dummy variables.

Overall the value of a house on the lot is animportant component of overall land valueand thus can be used as a proxy for a compo-nent of on-farm infrastructure. This is anotherespecially important policy issue for land settle-ment agencies. In formal settlements, INCRAnormally commits to providing a house valuedat R$3,100 as part of the settlement package.Unfortunately, the process of construction isthrough government bids to construction com-panies, which leaves smallholders at a disad-vantage. The quality of house construction ispoor at best, and in many cases the house isnever built leaving the smallholder to constructhis/her own house over time. Many of thehouses on the lots are simple structures fillingonly the basic needs of a dwelling, and so it islogical that the marginal value of these tendstoward the estimate of an INCRA house, whichitself provides only the basic elements of ahome. This conclusion is supported by the factthat the value of the home on both formally set-tled and informally settled lots is insignificant.

(b) Production characteristics

In this group of variables we examine theproduction decision of the smallholder on landvalue using area allocated to each crop as aproxy. The three categories are pasture, croparea (summing permanent and annual), andforests. Of these categories, pasture area hasan insignificant effect on land values acrossthe whole sample and among all settlement re-gimes. One could argue that pasture does notadd value simply because it is not profitable—mean sales of R$978 do not account for thecosts of production. This conclusion, however,is contrary to some recent estimates of positivepasture rents for the Amazon in general(Arima, Barreto, & Brito, 2006; Arima & Uhl,1997; Faminow, 1997; Margulis, 2003).Regardless, the result supports the long heldidea that land is often used for cattle (or putinto pasture regardless of the stocking rate) toestablish or maintain ownership and to secureland rights, and cattle are also held as a readilyliquid asset. Pasture land is easier to monitoragainst encroachment than forest, and titledlandowners may be more interested or able to

enforce their rights. It is also irrefutable thatpasture formation has been one of the majorstrategies to establish de facto property rightsin the Amazon.

As expected the impacts of area allocated incrop production on land values is positive forthe whole sample. The results suggest that anadditional hectare of crop area will addR$10.81 to the overall per hectare land values,all else equal; the only exception here is for thesample of formal settlers where crop area isinsignificant in determining land values. Final-ly, research has shown that sustained timberproduction has a tremendous potential forbuilding wealth smallholder systems along theTransAmazon highway. However, due to infor-mation and bureaucratic complications restrict-ing use it is highly underutilized (Lima et al.,2006). Indeed, we show that across all propertyregimes, more land in forestry significantly re-duces land values; an additional hectare of for-est will reduce overall per hectare land valuesby R$1.60. This at least partially confirms thatforest land, whether from underutilization oradherence to the forest code that requires land-owners to set aside between 50% and 80% oftheir land, continues to be viewed as costly tothe landowner.

(c) Time on the lot and settlement regime

In this section we consider the influence oftime on the lot, the quality of title, and the typeof settlement regime on lot value estimates.Across all sub-samples, the longer the individu-als remain on the lot, the higher they value theirland. Overall per hectare land values increaseby R$10.08 for every year of ownership, all elseequal, suggesting that de facto settlement rightsestablished through time are important ele-ments of value even if the individual has pur-chased the lot. Greater clearing of land overtime might also imply more secure enforcementby the smallholder. This coupled with the re-sults that holding definitive title does not signif-icantly affect land values reinforces the image ofa market where physical presence is a moreimportant determinant of land value, throughde facto land rights, than paper title. However,it appears that entry into a formal marketthrough purchasing lots does increase land va-lue slightly, as all else equal, formally and infor-mally settled lots are less valuable thanpurchased lots, by R$1.13 and R$1.14 per hect-are, respectively. This is clearly not a strong ef-fect on land values.


5. CONCLUSION

In theory land values reflect the returns toproduction. But in the absence of formal mar-kets, land values reflect a more complex mixof production returns—rents—and the estab-lishment of property rights. Some activitiesmay therefore be undertaken solely to capturethe value associated with land tenure. Further-more, other determinants of land values, suchas roads, land cleared, infrastructure, andagricultural production, reflect the incentivesfaced by a landholder in the drive to increaseland values. For example, in a frontier regionthe interaction between agricultural produc-tion, pasture, and logging reflect more thanan optimization from these three activities.Along with financial returns, the relative levelof land allocation reflects the fact that landmust be cleared to be claimed, and forestsdo not conclusively provide tenure. These areimportant considerations in the efforts to re-duce deforestation. If there are economicincentives to clear land to secure title, thenreducing deforestation in smallholder lots willbe difficult.

In this paper we use a hedonic model toquantify the impact of land and infrastructurecharacteristics to land values in three separatesettlement regimes along an important anddeveloping Amazon frontier. We evaluate landvalues for three types of property rights/settle-ment regimes: individuals who bought theirlots, individuals formally settled by the govern-ment, and informal squatters. The study areacomprised a large survey of settlers along theTransAmazon highway. The interest here is toidentify the most important determinants inthe perceptions smallholders have about theirland value. These perceptions are importantin the incentives as smallholders have to protectand use their land over the long term. Our sur-vey and methods contribute to existing litera-ture by providing the most comprehensivelook yet at land markets and land value inexpanding Amazon frontiers.

Because the market for land is largely infor-mal along the TransAmazon frontier, we usesmallholder perceptions of land values as aninstrument for actual land value in the hedonicmodel. Several types of explanatory variablesimportant to land values in the previous work

are used, including location and infrastructure,property and lot characteristics, productioncharacteristics, and the presence of titling. Animportant aspect of the analysis is determiningwhat groups of characteristics are most impor-tant for each property rights/settlement regime.Tests are also performed to assess the appropri-ateness of our instrument for land value, draw-ing on land rent capitalization literature.Although competitive markets might adjustland value perceptions higher or lower, accord-ing to the error in landowner expectations weassume that the error would be random andthe variation essentially the same. Indeed, cap-italization of important features of land to per-ceived land value appears consistent in our dataacross settlement regimes. Furthermore, use ofperceived land values is the only way to assessthe important components of land value inmixed formal and informal land markets foundon the frontier.

Overall the results show that the strongestcharacteristics adding value to land on theTransAmazon highway are physical presencein the form of time on the lot, area under agri-cultural production, and house values. Impor-tant characteristics that tend to decreaseperceived land values include distance fromthe nearest city and area under forest. Interest-ingly, characteristics that do not appear to sig-nificantly affect land value perceptions includepasture area and the claim to hold definitive ti-tle. These components of value are largely sim-ilar across settlement regimes, with someimportant differences, such as houses and Mu-nicipal location, being insignificant in both for-mal and informal settlements.

All of the results point to a market which,commensurate with expectation and other for-mal land markets, has proximity to servicesand agricultural production as important com-ponents of value. But higher value also requiresphysical presence but not definite title, which iscontrary to what is typically found in more for-mal land markets. Further, our results suggestthat pasture, by not adding significantly to landvalues, is part of the strategy to establish prop-erty rights rather than to increase land valuesthrough positive rents. Finally, since more for-est land lowers land values, our results tend toconfirm the underutilization of the forest re-source by smallholders.


NOTES

1. We tested the need to estimate separate regressionsas opposed to a single regression with dummy variablesover settlement regimes. This was done using a likeli-hood ratio test for the null hypothesis that the estimatedcoefficients of all explanatory variables in each separateregime regression are identical to the coefficients in thesingle regression with dummy variables defining eachregime given in the first column of Table 3. If the nullhypothesis is rejected, it implies that there is significantstatistical evidence that separate regime regressions offeradditional insight beyond the single regression. Resultsof this test show that the null hypothesis is rejected at a p

value of 10% or greater for all regressions. Thus, theseparate regime regressions are presented along with thefirst column regression in Table 3.

2. The use of a multiple regression for the full samplewith dummy variables for different property regimes isequivalent to an ANOVA approach where propertyregimes are treatments, except that the multiple regres-sion approach has the advantage of allowing one tocorrect for heteroskedasticity (for a discussion, seeDraper & Smith, 1981, pp. 427–429).

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Land Values in Frontier Settlements of the Brazilian Amazon