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The Journal of Socio-Economics 40 (2011) 833–843

Contents lists available at SciVerse ScienceDirect

The Journal of Socio-Economics

journa l homepage: www.e lsev ier .com/ locate /soceco

rust, tenure insecurity, and land certification in rural Ethiopia

intewab Bezabiha,∗, Gunnar Kohlinb, Andrea Mannbergc

CEMARE, University of Portsmouth, United KingdomEnvironmental Economics Unit, University of Gothenburg, SwedenDepartment of Economics, Umea University, Sweden

r t i c l e i n f o

rticle history:eceived 19 November 2010eceived in revised form 13 July 2011ccepted 29 August 2011

EL classification:212

a b s t r a c t

This paper assesses the impact of a land certification program in Ethiopia on the level of interpersonal andinstitutional trust among households in the Amhara region. The land certification program is designedto enhance land tenure security of farmers, by maintaining (egalitarian) status quo land distribution andequity concerns. The major contribution of the analysis lies in the exogenous nature of the programwhich addresses the endogeneity problems that characterize related studies, assessing the impact ofpolicy related variables on trust. The effects of the land certification program on trust are identified bothby the difference-in-difference approach and by non-parametrical analysis of average treatment effects.

15

eywords:rustand certification

Overall trust is found to be enhanced by the certification program, with trust towards formal institutionsbeing more responsive to the program than interpersonal trust. The major policy implication of the resultis that trust could be invested on through policy changes regarding the economic betterment of societies.

nterpersonal and institutional trustifference-in-difference method

. Introduction

Formal and informal contracts, to a large extent, form the basisor social interactions on both the individual level and on moreggregate levels in society. Regardless of the degree of formal-ty, these contracts facilitate social interaction in terms of definingoth rights and liabilities. However, in many cases it is not possibleo postulate a contract that is complete in terms of enforceabil-ty without costly monitoring. Because of this, the realization of

any of the possible gains from exchange and market interactionsequires trust and reciprocity (Fehr et al., 1997). Indeed, there isow extensive evidence that trust is crucial for fostering coopera-ion among people, and that trustful relations reduce transactionosts within day to day economic interactions (e.g., Teraji, 2008).uch facilitative roles of trust have been shown to translate into

esirable social and economic outcomes at the individual levele.g. Gabre-Madhin, 2001) and national/societal levels (e.g. Putnam,993; Fukuyama, 1995; Knack and Keefer, 1997; Teraji, 2008).1

∗ Corresponding author at: Department of Economics, University of Sussex, BN1RH, United Kingdom. Tel.: +44 (0) 1273 872628; fax: +44 (0) 1273 678335.

E-mail addresses: M.bezabih@sussex.ac.uk (M. Bezabih),unnar.kohlin@economics.gu.se (G. Kohlin), Andrea.mannberg@econ.umu.se

A. Mannberg).1 The term “social trust” (generalized interpersonal trust) should be distinguished

rom “political trust” (confidence in political and public institutions). Social trust,s “generalized thin trust,” also should be distinguished from trust embedded inersonal relations, or “particularized thick trust” (You, 2005).

053-5357/$ – see front matter. Crown Copyright © 2011 Published by Elsevier Inc. All rioi:10.1016/j.socec.2011.08.015

Crown Copyright © 2011 Published by Elsevier Inc. All rights reserved.

Given its pivotal importance in acting as a lubricant in exchangeand other activities of economic importance, assessment of thedeterminants of trust has received considerable attention fromboth experimental and field research (e.g., You, 2005; Cox et al.,2009). Over time, two major strands of literature have emerged.The first strand relates to trust as a cultural and moral feature, whilethe second relates to trust as an incentive driven motive responsiveto institutional and policy measures (Bjørnskov, 2005).2

While determinants of trust associated with cultural or moralfeatures are exogenous, assessing the impact of policy related vari-ables on trust have been dogged by possible endogeneity of themeasures. For instance, democratic societies with fair proceduralrules, fair administration of rules with freedom from corruption andfair income distribution, are likely to produce incentives for trust-worthy behavior, develop norms of trustworthiness and enhanceinterpersonal trust (You, 2005). Similarly, secure property rights

could be the outcome of collective trust (Teraji, 2008). Givensuch plausible endogeneities, assessment of causal relationshipsbetween trust and policy related variables may yield misleading

2 Determinants of trust related to non-policy variables include measures of frac-tionalization regarding ethnic or ethno-linguistic diversity (Knack and Keefer, 1997;Zak and Knack, 2001; Knack and Zak, 2002; Uslaner, 2002; Bjørnskov, 2005), politicaldiversity (Bjørnskov, 2006) and religion (La Porta et al., 1997; Zak and Knack, 2001;Uslaner, 2002). Policy related factors affecting trust include the rule of law (Zak andKnack, 2001), economic freedom and democracy, political trust (Brehm and Rahn,1997) and education (Knack and Keefer, 1997; Knack and Zak, 2002), among others.

ghts reserved.

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34 M. Bezabih et al. / The Journal of

esults. Hence, assessing the responsiveness of trust to exogenousolicy changes is of importance in order to shed light on the

mportance of policy related variables in determining the level ofeneralized trust.

Accordingly, the major objective of this paper is to test thempact of a recently introduced rapid and low-cost rural land certi-cation program in Ethiopia. The stated purpose of the program

s to reduce the inherent insecurity of tenure in land holdingsn the level of trust among individuals and institutions. The linketween trust and the land certification program in the contextf Ethiopia stems from the historical land tenure structure in theountry and the central role land rights play on the livelihoods ofillions of farmers. Ethiopia’s land tenure relations are marked bylong legacy of state interventions in which the state has exerted

onsiderable influence on local land tenure systems throughout dif-erent political regimes (Crewett et al., 2008). Our major premise ishat such state interventions, and the associated negative experi-nces of unpredictable evictions and land redistributions, have lefthe land operating masses suspicious of the state (and its tenureolicy) as stewards of their best interests. The land certificationrogram, by granting tangible evidence of individual land rights,an potentially restore the mistrust the masses may have towardshe authorities. Using household level survey data from two zonesn the Amhara Region of Ethiopia, we examine how an exoge-ous change in land rights affects interpersonal and institutionalrust. The difference-in-difference approach is used to measurehe impact of the program on trust. Overall, trust is found to benhanced by the certification program, with trust towards formalnstitutions being more responsive to the program than interper-onal trust. The major policy implication of the result is that trustan be invested on through policy changes regarding the economicetterment of societies.

The study makes three major contributions to the existing lit-rature on the impact of property rights on trust. First, a large partf the empirical literature on the impact of property rights on trustnd social capital is based on experimental analysis of the impactf property rights. The results of these studies are mixed. Fahr andrlenbusch (2000) shows that, within the context of ultimatumames, property rights in combination with strategic interactionay lead to diminished trust. However, the results from Ostrom

t al. (1992) suggest that the lack of property rights creates aisk of over-exploitation of common pool resources. Concerningirect effects on trust, Cox et al. (2009) finds that an allocation ofroperty rights in a common property setting causes a marginal

ncrease in the level of trust. In a related study, Cox and Deck2005) shows that the context in which decisions are made has aignificant effect on reciprocally-motivated behavior. This findingrom Cox and Deck (2005) suggests that institutional character-stics may play a key role on whether cooperation emerges ands sustained, in terms of affecting the degree of reassurance aso the expected actions of others (see also Walker and Ostrom,007).

The above studies have contributed important insights relatedo the link between property rights, cooperation and trust. How-ver, due to the experimental setting, the potential to draw generalonclusions is limited. In a real world context, trust may be stickynd may not be readily responsive to exogenous changes in prop-rty rights regimes in a short period of time. In light of thesexperimental results, our analysis provides the opportunity tossess the importance of changes in property rights regimes in aeal world setting.

Second, while the direct individual benefits of land reforms,

uch as enhanced investment and increased credit access, haveeen analyzed to a relatively large extent, the indirect spill-overffects, such as enhanced trust, have not been thoroughly inves-igated. A number of studies across the developing world show

-Economics 40 (2011) 833–843

that increased secure land tenure enhances land related invest-ment (e.g. Besley, 1995; Sjaastad and Bromley, 1997; Holden andYohannes, 2002; Deininger and Jin, 2006). In many instances,tenure security is also found to correlate with participation in theland rental market (e.g., Gebreselassie, 2006; Ghebru and Holden,2008; Lunduka et al., 2008). Furthermore, additional findings indi-cate that rural land security conditions produce desirable socialoutcomes, such as the performance of local institutions (Deiningeret al., 2003; Deininger and Jin, 2006) and even of the state (Banerjeeand Iyer, 2005). However, the extent to which tenure insecu-rity goes further than increasing individual economic gains toenhance institutional and interpersonal performance has not beenstudied.

Third, the positive impact of enhanced rights to land on trustdepends on the effectiveness of the reform itself. As discussedabove, while secure rights to land confers a number of individ-ual and community level benefits, the realization of such benefitsdepends on the degree to which land titling programs them-selves translate to increased tenure security. In many parts of theworld, such land titling programs have led to enhanced tenuresecurity and increased economic gains. In Africa, however, suchland titling initiatives have had relatively disappointing results.The failure of these programs to achieve their intended targetsof enhancing tenure security is at large attributed to their designand implementation (e.g., Deininger et al., 2003; Crewett et al.,2008). Crewett et al. (2008) argues that the structure of existingland tenure systems in Ethiopia have been largely characterizedby the top down approaches without taking into account specificlocal needs. With its participatory approach and low cost imple-mentation, the certification program is believed to have overcomethe shortcomings of traditional land titling programs in Africa(Deininger et al., 2009). Hence, analyzing the trust impacts of theland certification program is an opportunity to assess whetherthe impacts of this particular land reform are positive in thecontext that the certification program is arguably an exogenouschange.

The rest of the paper is organized as follows. Section 2 presentsan overview of the land tenure system in Ethiopia. In Section 3, thedata employed in the empirical analysis is presented and the econo-metric methodology employed is discussed. Section 4 discusses theempirical findings and Section 5 concludes the paper.

2. State ownership of rights in Ethiopia, tenure insecurityand the land certification program

2.1. The land tenure system in Ethiopia: a background

Given the importance of land as a source of livelihood to themajority of the population and as a source of political and eco-nomic power to all groups who aspire to hold political power, theland tenure system in Ethiopia has been a central policy themefor generations (Adal, 2000, 2003; Rahmato, 2004). In the decadesprior to and during the imperial era, which ended in 1975, the landtenure in Ethiopia was characterized by a complex system of own-ership that included communal (rist), grant land (gult), freehold orsometimes referred to as private (gebbar tenures), church (samon)and state (maderia, mengist) tenure regimes (Rahmato, 1984; Adal,2003; Yirga, 2007). Land was typically concentrated in the handsof absentee landlords, tenure was highly insecure and arbitraryevictions posed serious threats to tenant farmers (Rahmato, 1984;Jemberre, 2000). This tenure system has been widely conceived

as unjust among the rural peasantry as much as among themore progressive urban elites and is believed to be the centralreason for the downfall of the imperial regime (Crewett et al.,2008).

Socio

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gram in Ethiopia lies in its relatively innovative low cost approach,which is in contrast to similar previous programs in Africa.4

3 The focus of this study is the Amhara region certification program.4 Although many developing countries have recently adopted highly innovative

and pro-poor land laws, difficulties with implementation are seen to hamper theireffectiveness. Examples of potential problems include attempts at land grabbing by

M. Bezabih et al. / The Journal of

The socialist derg regime, that overtook power from the imperialegime of Haile Selassie through a military coup in 1974, profoundlyltered the agrarian structure and the mechanisms of access to landarked by the land reform proclamation of February 1975. This

and reform is known for nationalizing all rural land and trans-erring usufruct rights to the rural peasantry. In some instances,mallholder farmers were evicted from their holdings to give wayor state farms and producer cooperatives. Access, distributionnd tenure terms of user rights were defined by the state and itsocal representatives (Rahmato, 1984; Yirga, 2007; Crewett et al.,008).

The land reforms, along with the right of Peasant AssociationsPA) and other governmental bodies which redistributed land inractice, undermined the tenure security among farmers. This isspecially so since redistribution in some cases was used for polit-cal ends (Ege, 1997). In addition, transferability of land throughease, sale, exchange or mortgage and the use of hired labor wererohibited and inheritance was possible only among immediateamily members during the Derg regime. Consequently, anybodynvolved in land rental ran the risk of losing his or her land. Sim-larly, land use rights were contingent on proof of permanenthysical residence, thus preventing migration from rural areasDeininger et al., 2009).

With the end of the socialist derg regime of Mengistu in 1991,he transitional government, and the new constitution of 1995hat followed, approved and confirmed the state ownership ofand in Ethiopia. The only major changes to the tenure system

ere stalling land redistribution in some regions, bringing alongome tenure security and the reintroduction of informal land leasearkets (Adal, 2003). Even with rental of land being officially

llowed (Pender and Fafchamps, 2006), the regional governmentstill imposed restrictions on the extent of land that could be leasedr the duration of rental contracts (Nega et al., 2003a,b).

The land tenure system, with state ownership of land as its maineature, has been held as a major culprit in the lack of significantncreases in productivity, significant land management problemsnd agrarian immobility. However, the merits of private over pub-icly owned land are not unambiguous. Proponents of state landwnership argue that it protects the rural peasants from sellingff their land to wealthy individuals leaving them landless andithout a source of livelihood. In addition, it grants tenure secu-

ity to the Ethiopian farmers that has experienced land deprivationnd land expropriation through different mechanisms for centuriesCrewett et al., 2008). Similarly, previous experience of land titlinguggests that corrupt practices creates a risk that land will be allo-ated to the elite, while the poor masses risk losing their access toand (Deininger et al., 2003). However, as is relatively clear fromhe Ethiopian experience, the absence of secure property rights isqually problematic. Advocates of the privatization of land propertyights to small holder farmers argue that ownership of land pre-ents the development of a land market, which discourages farmerso invest on land (Adal, 2001; Crewett and Korf, 2008). Lately, effortsave been made to implement property rights that avoid the neg-tive side effects of land titling and still secure land rights. Thethiopian land certification program is one of the first such pro-rams to be implemented. Below, we give a brief description of therogram.

.2. The land certification program

The Ethiopian certification program has contributed to the

argest delivery of non-freehold land rights per time unit in Subaharan Africa. Since the onset of the program 1998, over 5 millionertificates have been delivered to farm households across EthiopiaDeininger et al., 2008).

-Economics 40 (2011) 833–843 835

The program is implemented in the four major regions of thecountry: Tigray, Amhara, Oromiya and the Southern Nations andNationalities (SNNR). The Tigray region started the land registrationand certification process in 1998–1999, followed by the Amhararegion in 2003, with Oromiya and SNNR’s certification commencingin 2004 (Holden et al., 2009).3

The major feature of the program is a decentralized imple-mentation process through elected Land Use and AdministrationCommittees (LACs) at the village level (Deininger et al., 2008). TheLACs are primarily involved in land registration and certification.The certification and registration process is carried out in a partici-patory manner where the work by LACs is at large uncompensated(Holden and Tefera, 2008). The implementation has been rapid, asevidenced by the majority of rural households in Ethiopia beingcovered by the process within 2–3 years from the start of imple-mentation. The process has also been implemented at a cost of amagnitude below what is reported anywhere else in the literature,a further evidence of its high cost-effectiveness (Deininger et al.,2008).

The program may be considered as an overall implementationsuccess in terms of it being relatively pro-poor, and for adheringto the requirements of procedures and recipients’ appreciation ofcertificates (as further evidenced by an investigation of their will-ingness to pay for a certificate) (Deininger et al. (2008)). This viewis supported by Holden and Tefera (2008), whose findings showthat labor-poor households are significantly more likely to havea land certificate than other households. Furthermore, while theparticipation of women in the administration of the certificationprogram has been much lower than expected, the percentage ofwomen that has been issued certificates are almost equal to thatof men. In addition, Holden and Tefera (2008) show that certifica-tion has increased perceptions of tenure security for both womenand men, and that poorer households have the same probability ofreceiving land certificates as less poor households. Finally, Holdenet al. (2011) examine the incidence of land-related conflict andfinds that the number of conflicts was lower during registrationand certification than before.

Despite this, some limitations of the implementation processshould be noted. In particular, smaller farms and livestock-poorhouseholds have been found to be significantly less likely to receivea certificate than other households (Holden and Tefera, 2008).Other limitations include the imposition of obligations on certifi-cate holders, penalties for violations in terms of the maximumamount of land to rent out and lack of clarity with respect toCommon Property Resources (CPR) and public investment pro-grams (Holden et al., 2011). Based on this, Deininger et al. (2008)suggest that improving clarity of policy guidelines, providingaccess to legal and policy information in written form, includingcoverage of common property resources (CPRs), ensuring betterparticipation by women and, in some regions, their inclusion oncertificates would enhance the effectiveness of the certificationprocess.

Given this, the essence of analyzing the land certification pro-

local elites and bureaucrats at the expense of the poor (Jansen and Roquas, 1998),replacement of stable and operational local institutions with new ones associatedwith the land titling (Deininger and Castagnini, 2006), corruption, poor implementa-tion, high costs of obtaining land titles and disregard for rights (Besley and Burgess,2000; Cotula et al., 2004).

8 Socio-Economics 40 (2011) 833–843

3

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Table 1Description of variables used in the regressions.

Variable name Variable description

Socio-economic characteristicsSex of household head 1 = female household head, 0 = male

household headAge of the household head Head’s age (years)Household head can read Head’s formal education (1 = read only;

0 = otherwise)Household head can write Head’s formal education (1 = read and

write; 0 = otherwise)Number of female adults in the

householdThe number of females over 15 yearsold within the household

Number of male adults in thehousehold

The number of males over 115 yearsold within the household

Tenure security variablesExpect an increase in land holdings Dummy variable for whether the

household expects increase in landholdings (1 = Yes, 0 = No)

Expect a decrease in land holdings Dummy variable for whether thehousehold expects no change in landholdings (1 = Yes, 0 = No)

Expect no change in land holdings Dummy variable for whether thehousehold expects decrease in landholdings (1 = Yes, 0 = No)

Previous experience of land conflictEast Gojjam Zone Dummy variable for the Zone the

household is located in (1 = EastGojjam, 0 = South Wollo)

Trust variablesTrust towards the federal

governmentA categorical variable indicatingwhether the individual believes thegovernment can be trusted (agreestrongly = 1; agree somewhat = 2;neither agree nor disagree = 3; disagreesomewhat = 4; disagree strongly = 5;and cannot say = 6)

Trust towards the regionalgovernment

A categorical variable indicatingwhether the individual believes theregional government can be trusted(agree strongly = 1; agreesomewhat = 2; neither agree nordisagree = 3; disagree somewhat = 4;disagree strongly = 5; and cannotsay = 6)

Trust towards the localgovernment (kebele)

A categorical variable indicatingwhether the individual believes thegovernment can be trusted (agreestrongly = 1; agree somewhat = 2;neither agree nor disagree = 3; disagreesomewhat = 4; disagree strongly = 5;and cannot say = 6)

Trust towards NGOs (SIDA) A categorical variable indicatingwhether the individual believes thelocal government can be trusted (agreestrongly = 1; agree somewhat = 2;neither agree nor disagree = 3; disagreesomewhat = 4; disagree strongly = 5;and cannot say = 6)

Trust towards other people(individual trust)

A categorical variable indicatingwhether the individual believes otherpeople can be trusted (agreestrongly = 1; agree somewhat = 2;neither agree nor disagree = 3; disagreesomewhat = 4; disagree strongly = 5;

36 M. Bezabih et al. / The Journal of

. Empirical approach

.1. Description of the data

The analysis presented in this paper involves household levelata collected in the years 2005 and 2007 in the Amhara Nationalegional state of Ethiopia. The data was collected as part of a house-old survey on sustainable land use from a SIDA/SAREC-fundedollaborative research project between the Ethiopian Developmentesearch Institute (EDRI) and University of Gothenburg, Sweden.he dataset consists of a stratified random sample of around 1500ouseholds across 14 villages in two zones, East Gojjam and Southollo, within the state. The stratification was based upon indica-

ors of agricultural potential, market access and population density.urvey instruments covered household composition and assets,ccess to markets and infrastructure as well as aspects of croproduction during the two production years.

In contrast to trust-related variables in many other surveys,uch as the World Values Survey, which only gives a relativelyrude measure of trust (trust in most people), the dependent vari-bles used in the below analysis relates to both interpersonal andnstitutional trust. These variables were constructed using ques-ions regarding the level of trust towards formal institutions suchs the federal, regional and local government (kebele), NGOs suchs SIDA (Swedish International Development Agency), along withuestions relating to interpersonal relations to other individualspeople in general) and individuals with whom the respondentrades with (trade partners). For each of the above trust indicators,espondents were asked the question “In general, do you think that. . .] can be trusted?” The respondents were then provided with

set of choices from which they would pick one as an answer.he alternative answers included: “completely untrustworthy”,somewhat untrustworthy”, “average”, “somewhat trustworthy”,completely trustworthy” and “cannot say”. Consequently, theependent variables used in the below analysis consists of a setf categorical variables with one of the above five possible values.espondent giving the answer “cannot say” are treated as missingbservations.5

The certificate variables, our major explanatory variables ofnterest, are constructed using information on participation in theand certification program. We follow Deininger et al. (2009) inerms of creating the certificate (treatment) variable on villageevel, i.e. we identify respondents based on whether or not they

ere living in a village where land certificates were made availablen the year 2005. The difference in difference strategy is viable sincehe certification process was completed 12 months or more beforemplementation of the 4th round of our survey in treatment vil-ages, thus possibly allowing sufficient time for the effect on trusto appear.

The trust level of individuals may naturally also be affectedy household-specific characteristics. Household characteristics

nclude those related to human capital, labor supply and to theife-cycle phase of the household, such as age and gender of theousehold head. We therefore include the number of male and

emale adults in each household, age, gender of household headnd variables related to literacy as control variables in the regres-ions. In addition, wealth may affect the level of trust. In Ethiopia,

5 It should be noted that the survey is conducted in one language in all the sur-ey villages (Amharic), and that the translation of the question in English has anquivalent and a straightforward translation in Amharic. In order to circumventhe problem of respondent reluctance to give full information in the survey, at thetart of the interview, the respondents were read a paragraph that states that thenswers are used for research purposes and their individual answers are anony-ously treated.

and cannot say = 6)Trust towards people one trades

withA categorical variable indicatingwhether the individual believes thepeople one trades with can be trusted(agree strongly = 1; agreesomewhat = 2; neither agree nordisagree = 3; disagree somewhat = 4;disagree strongly = 5; and cannotsay = 6)

M. Bezabih et al. / The Journal of Socio-Economics 40 (2011) 833–843 837

Table 2Descriptive statistics of variables used in the regressions.

Variable 2005 2007

Mean SD Mean SD

Post treatment 0.000 0.000 0.407 0.491Age of head of household 49.528 16.600 51.748 15.082Head of household is female 0.174 0.379 0.164 0.371Respondent can write 0.405 0.491 0.338 0.473Respondent can read 0.063 0.243 0.079 0.271Number of livestock owned by household 4.376 3.569 4.578 3.702Number of oxen owned by household 1.734 1.458 1.768 1.516Household rents out land 0.140 0.347 0.157 0.364Total land area by household 1.774 2.907 1.998 1.838Number of male adults in household 1.972 1.249 2.189 1.342Number of female adults in household 1.909 1.031 2.114 1.155Expect a decrease in size of land holdings 0.185 0.388 0.201 0.401Expect no change in size of land holdings 0.256 0.437 0.392 0.488

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Expects an increase in landholdings 0.363Previous experience of land conflict 0.188East Gojjam Zone 0.410

he number of livestock owned by the household is an impor-ant indicator of wealth. Hence, we include the number of tropicalnits of livestock6 as a proxy for wealth. Since landholdings consti-ute another important indicator of wealth, a variable measuringhe total land area to which the household holds user rights islso included in the regressions. In order to control for differencesetween the two geographical zones in the Amhara region, we

nclude a dummy relating to whether the respondent householdives in East Gojjam or South Wollo. Finally, previous experiencef land-related conflicts and expectations of future land redistribu-ion may affect the level of trust both for other individuals and theuthorities, and we therefore also control for these aspects.

Definition of the variables used in the regressions and theirespective descriptive statistics are presented in Tables 1 and 2.

.2. Empirical methodology and estimation considerations

An ideal setting for an impact evaluation would require thatarticipants and non-participants have the same chance ex ante ofeceiving the program. The implication is that observed or unob-erved attributes of participants and non-participants, prior to thentervention, are then independent of whether or not a unit actu-lly receives the program. This guarantees that the observed exost difference in mean outcomes between the treatment and con-rol groups is attributable to the program. In reality, however,mpact evaluation generally involves purposive placement, reflect-ng both the choices made by those eligible and the administrativessignment of the opportunities to participate, thus introducing aelection bias problem into the evaluation exercise. Hence, appro-riate impact evaluation estimators need to address selection biastemming from inadequate controls for observable heterogeneitynd then bias stemming from unobservables (Ravallion, 2007).

A popular way of addressing such selection biases is the use ofhe difference-in-difference approach. This approach allows us toontrol for the time of the decision to participate in certification andor the presence or absence of individual-specific traits of partici-ation. The basic intuition of the difference-in-difference approach

s that we study the impact of some ‘treatment’ (i.e. a comparisonf the performance of the treatment group pre- and post-treatment

elative to the performance of some control group). In principle, theontrol group shows what would have happened to the treatmentroup in the absence of any treatment (Slaughter, 2001).

6 Tropical livestock unit (TLU) is an aggregate measure of varying types of livestockith different weights attached to the different types of livestock.

0.481 0.327 0.4690.391 0.215 0.4110.492 0.385 0.487

Our analytical problem coincides with a case where the outcomeis observed for two groups in two time periods. One of the groupsis exposed to a treatment in the second period but not in the firstperiod. The second group is not exposed to the treatment duringeither period. In the case where the same units within a group areobserved in each time period, the average gain in the control groupis subtracted from the average gain in the treatment group. Thisremoves biases in second period comparisons between the treat-ment and control group that could be the result from permanentdifferences between those groups, as well as biases from compar-isons over time in the treatment group that could be the result oftrends (Wooldridge, 2002).

Technically, the level of individual/institutional trust isdetermined by household level characteristics, village level char-acteristics and the policy variable (certification). Accordingly, forhousehold i and year t, the trust equation is given by:

y∗it = ˛+ X ′

it� + �Cit + ϑT + ˇCitT + �i + uit (1)

where y∗it

is the latent variable underlying our observed variablewith ordered categories for different levels of trust. Hence, whatwe observe is:

yit =

⎧⎪⎪⎪⎪⎪⎪⎨⎪⎪⎪⎪⎪⎪⎩

0 if y∗it

≤ 0,

1 if 0< y∗it

≤ �1,

2 if �1 < y∗it

≤ �2,

3 if �2 < y∗it

≤ �3,

4 if �3 < y∗it

≤ �4,

(2)

where �j are the thresholds for the different categories (Greene,2007). In Eq. (1), Xit represents the set of covariates, includingsocio-economic characteristics; Cit represents the certificate vari-able which captures possible differences between the treatmentand control groups prior to the policy change, T is a dummy vari-able for the second time period. This variable captures aggregatefactors that would cause changes in y∗

ieven in the absence of a pol-

icy change. Finally, �i are individual unobserved effects, and uit isan error term.

The coefficient of interest, ˇ, multiplies the interaction term,CitT, which is the same as a dummy variable equal to one for thoseobservations in the treatment group in the second period. Thedifference-in-differences estimate is:

ˇ = (y2007 − y2005) − (yC − yNC ) (3)

where y2007 is year 2007, y2005 is year 2005, yC is the treatmentgroup and yNC is the control group.

838 M. Bezabih et al. / The Journal of Socio-Economics 40 (2011) 833–843

Table 3Ordinal generalized linear model (OGLM): difference in difference effects on trust.

Kebele Regional government Federal government Police SIDA People Trade partners

Post treatment 0.0824 0.328*** 0.356*** 0.130** 0.215** 0.176** 0.171**

(1.03) (5.27) (6.13) (2.14) (2.44) (2.17) (2.30)Household in treatment village −0.0270 0.0197 −0.0125 0.166*** 0.137** −0.0794 −0.0867

(−0.52) (0.39) (−0.26) (3.29) (2.42) (−1.31) (−1.47)Ethiopian calendar year is 1999 −0.0765 0.129*** 0.0980** 0.342*** 0.146** 0.0857 0.0253

(−1.37) (2.80) (2.20) (7.36) (2.45) (1.55) (0.51)Household rents out land 0.0419 0.00258 0.0161 0.0613 −0.000404 −0.126** −0.0854

(0.73) (0.06) (0.38) (1.45) (−0.01) (−2.10) (−1.56)Age of head of household 0.000634 0.00204* 0.00232** −0.000331 0.000738 0.000341

(0.45) (1.77) (2.04) (1.03) (−0.21) (0.51) (0.25)Head of household is female 0.0283 0.0750 0.0713 0.0119 0.0157 0.0905 0.0291

(0.43) (1.62) (1.61) (0.26) (0.24) (1.56) (0.57)Respondent can read 0.0124 −0.0300 −0.00998 −0.0543 0.0296 −0.0648 −0.0723

(0.16) (−0.45) (−0.15) (−0.90) (0.32) (−0.84) (−1.05)Respondent can write 0.0990** −0.0137 0.0139 −0.0309 0.0248 −0.0161 −0.0415

(2.26) (−0.38) (0.38) (−0.84) (0.50) (−0.34) (−0.99)Number of male adults in household 0.0304* 0.0117 0.0172 0.0127 0.0148 0.0184 0.0150

(1.70) (0.79) (1.18) (0.89) (0.77) (1.02) (0.92)Number of female adults in household 0.0415** −0.00782 0.0119 0.0152 0.0118 −0.0113 0.0161

(2.21) (−0.53) (0.81) (1.01) (0.54) (−0.59) (0.98)Number of oxen owned by household 0.00553 −0.0334* −0.0272 −0.0186 −0.0449* −0.0139 −0.0424**

(0.24) (−1.74) (−1.49) (−0.99) (−1.69) (−0.57) (−1.98)Number of livestock owned by household −0.0119 0.00548 0.00710 0.000891 0.00401 −0.00385 0.00531

(−1.28) (0.70) (0.94) (0.11) (0.37) (−0.39) (0.61)Total land area by household −0.00705 0.0141** 0.00657 −0.00105 −0.00266 −0.00918 0.000535

(−1.12) (1.97) (0.93) (−0.12) (−0.34) (−1.56) (0.08)Expect a decrease in size of land holdings 0.0235 −0.00963 −0.0226 0.0502 0.0125 −0.136** −0.0336

(0.48) (−0.23) (−0.56) (1.20) (0.21) (−2.42) (−0.67)Expect no change in size of land holdings −0.0746 0.0153 0.0261 0.0265 −0.0282 0.0391 0.0669*

(−1.62) (0.43) (0.76) (0.77) (−0.59) (0.84) (1.68)Previous experience of land conflict 0.0336 −0.0308 0.00790 −0.0271 −0.0427 −0.0480 −0.0643

(0.73) (−0.78) (0.20) (−0.71) (−0.80) (−0.93) (−1.34)East Gojjam Zone −0.361*** −0.120*** −0.112*** 0.0339 −0.0323 −0.0614 −0.209***

(−7.70) (−3.46) (−3.31) (0.98) (−0.68) (−1.37) (−5.10)ln sigmaEthiopian calendar year is 1999 −0.165*** −0.431*** −0.456*** −0.287*** −0.285***

(−3.38) (−10.35) (−10.59) (−7.93) (−8.17)Zone −0.225*** 0.177*** 0.141***

(−4.64) (4.89) (3.95)Household in treatment village −0.153*** −0.212*** −0.109***

(−3.64) (−4.88) (−2.91)Household rents out land −0.178*** −0.159*** −0.142**

(−3.14) (−3.09) (−2.49)Head of household is female −0.170***

(−3.08)Previous experience of land conflict 0.109**

(2.47)�1

Constant−1.059*** −0.703*** −0.631*** −0.632*** −0.872*** −0.964*** −0.787***

(−11.79) (−8.89) (−7.90) (−7.94) (−8.49) (−10.06) (−9.09)�2

Constant−0.480*** −0.0930 −0.0495 0.164** −0.133 0.383*** 0.258***

(−5.53) (−1.20) (−0.63) (2.05) (−1.29) (4.05) (2.94)�3

Constant−0.0460 0.233*** 0.264*** 0.608*** 0.407*** 1.138*** 0.785***

(−0.53) (2.98) (3.36) (7.29) (3.91) (11.45) (8.49)�4

Constant0.593*** 0.927*** 0.909*** 1.396*** 1.221*** 1.697*** 1.273***

(6.66) (10.99) (10.79) (14.72) (11.36) (15.94) (12.84)

N 2231 2570 2548 3025 2413 3265 3154Log likelihood −3434.1 −3883.3 −3844.2 −4507.1 −3780.4 −4464.5 −4495.7Chi2 254.6 547.5 604.4 438.9 80.08 62.02 135.9d.f. 19 20 20 20 18 18 20

t-Statistics in parentheses, robust standard errors adjusted for clusters in hhid.*

ticv

p < 0.10.** p < 0.05.

*** p < 0.01.

The above model can be estimated by a random effects estima-

or. However, if the error term is correlated with the unobservablesn the model, the random effects estimator is not consistent. In thisase, a fixed effects model is commonly employed. For dependentariables of an ordinal scale, however, the standard fixed effect

estimator is not consistent even if the unobservables are uncor-

related with the explanatory variables (Wooldridge, 2002). Wetherefore employ the Chamberlain (1984) and Mundlak (1978)correlated random effects estimator. To remedy the potential biasstemming from correlations between the unobserved

M. Bezabih et al. / The Journal of Socio-Economics 40 (2011) 833–843 839

Table 4Ordinal generalized model (OGLM) with Chamberlain–Mundlak’s approach.

Kebele Regional government Federal government Police SIDA People Trade partners

Post-treatment 0.0883 0.331*** 0.359*** 0.132** 0.225** 0.185** 0.171**

(1.09) (5.30) (6.16) (2.18) (2.53) (2.27) (2.30)Household in treatment village −0.0330 0.0173 −0.0142 0.164*** 0.132** −0.0821 −0.0890

(−0.64) (0.34) (−0.29) (3.25) (2.33) (−1.35) (−1.50)Ethiopian calendar year is 1999 −0.0589 0.116** 0.0906* 0.358*** 0.165*** 0.130** 0.0344

(−0.99) (2.42) (1.93) (7.29) (2.61) (2.20) (0.65)Household rents out land 0.0506 0.00591 0.0226 0.0612 0.00224 −0.124** −0.0793

(0.87) (0.14) (0.53) (1.44) (0.04) (−2.06) (−1.45)Age of head of household 0.000810 0.00220* 0.00246** 0.00117 −0.000270 0.000524 0.000416

(0.57) (1.90) (2.15) (1.00) (−0.17) (0.36) (0.31)Head of household is female 0.0282 0.0752 0.0705 0.0169 0.0173 0.0942 0.0279

(0.43) (1.62) (1.58) (0.37) (0.26) (1.62) (0.55)Respondent can read 0.0144 −0.0324 −0.0124 −0.0533 0.0298 −0.0608 −0.0700

(0.18) (−0.48) (−0.19) (−0.88) (0.32) (−0.78) (−1.01)

Respondent can write 0.0987** −0.0139 0.0120 −0.0270 0.0290 −0.0139 −0.0404(2.25) (−0.38) (0.33) (−0.73) (0.58) (−0.29) (−0.96)

Number of male adults in household −0.00594 0.00216 0.0160 −0.0712 −0.105 −0.103 −0.0239(−0.09) (0.04) (0.32) (−1.33) (−1.54) (−1.52) (−0.37)

Number of female adults in household 0.0117 0.0592 0.0464 0.0436 0.0382 −0.0933 0.0144(0.19) (1.30) (1.02) (0.89) (0.58) (−1.55) (0.28)

Number of oxen owned by household 0.0168 −0.0285 −0.0295 −0.00998 −0.0330 −0.0119 −0.0397*

(0.67) (−1.42) (−1.51) (−0.52) (−1.21) (−0.45) (−1.77)Number of livestock owned by household −0.0208* 0.00184 0.00581 −0.00190 −0.00132 −0.00536 0.00273

(−1.96) (0.23) (0.74) (−0.24) (−0.12) (−0.51) (0.30)Total land area by household −0.00361 0.0154** 0.00841 −0.00173 −0.00196 −0.00992* 0.00138

(−0.64) (2.12) (1.19) (−0.20) (−0.26) (−1.65) (0.20)Expect a decrease in size of land holdings 0.0261 −0.00879 −0.0235 0.0502 0.00923 −0.138** −0.0335

(0.53) (−0.21) (−0.58) (1.20) (0.16) (−2.46) (−0.67)

Expect no change in size of land holdings −0.0716 0.0174 0.0284 0.0262 −0.0309 0.0394 0.0659*

(−1.55) (0.49) (0.82) (0.75) (−0.64) (0.85) (1.65)Previous experience of land conflict 0.0350 −0.0337 0.00618 −0.0279 −0.0449 −0.0476 −0.0643

(0.76) (−0.85) (0.16) (−0.73) (−0.83) (−0.92) (−1.34)Zone −0.349*** −0.116*** −0.105*** 0.0302 −0.0323 −0.0644 −0.205***

(−7.35) (−3.31) (−3.07) (0.86) (−0.68) (−1.42) (−4.97)avg land −0.000632** 0.000653*** 0.000532** −0.0000551 0.0000588 0.00157*** 0.000828***

(−2.16) (4.22) (2.41) (−0.33) (0.24) (5.69) (2.93)avg livestock 0.0109 0.00341 0.000935 0.00229** 0.00207*

(1.23) (1.22) (0.32) (2.20) (1.58) (0.54) (1.73)avg oxen −0.0003 0.0003 0.0115 −0.0142** −0.0127 −0.00470 0.003

(−0.02) (0.03) (0.95) (−2.36) (−0.99) (−0.47) (0.39)

avg femaleadult 0.0308 −0.0748 −0.0388 −0.0339 −0.0331 0.0869 −0.000481(0.49) (−1.57) (−0.81) (−0.66) (−0.49) (1.38) (−0.01)

avg maleadult 0.0388 0.0120 0.00198 0.0917 0.128* 0.129* 0.0415(0.57) (0.23) (0.04) (1.64) (1.82) (1.84) (0.63)

ln sigmaEthiopian calendar year is 1999 −0.163*** −0.429*** −0.454*** −0.287*** −0.284***

(−3.36) (−10.29) (−10.50) (−7.97) (−8.15)Zone −0.223*** 0.178*** 0.143***

(−4.61) (4.91) (4.00)Household in treatment village −0.155*** −0.212*** −0.109***

(−3.68) (−4.86) (−2.90)Household rents out land −0.177*** −0.160*** −0.135**

(−3.12) (−3.13) (−2.37)Head of household is female −0.164***

(−2.94)Previous experience of land conflict 0.106**

(2.41)�1

Constant−1.010*** −0.702*** −0.622*** −0.631*** −0.858*** −0.931*** −0.769***

(−10.81) (−8.63) (−7.57) (−7.81) (−8.23) (−9.53) (−8.69)�2

Constant−0.429*** −0.0920 −0.0389 0.166** −0.117 0.419*** 0.278***

(−4.72) (−1.15) (−0.48) (2.05) (−1.12) (4.33) (3.10)�3

Constant0.00585 0.234*** 0.276*** 0.611*** 0.424*** 1.174*** 0.805***

(0.06) (2.90) (3.39) (7.25) (4.03) (11.57) (8.54)�4

Constant0.648*** 0.929*** 0.923*** 1.400*** 1.241*** 1.733*** 1.294***

(6.93) (10.70) (10.59) (14.67) (11.42) (15.95) (12.81)

N 2231 2569 2547 3024 2412 3264 3153Log likelihood −3429.6 −3878.5 −3839.6 −4502.9 −3775.9 −4460.3 −4492.3Chi2 266.8 621.6 626.8 484.8 83.23 110.8 199.7d.f. 24 25 25 25 23 23 25

t-Statistics in parentheses, robust standard errors corrected for clusters in hhid.* p < 0.10.

** p < 0.05.*** p < 0.01.

8 Socio

haXih

�

ivseiaC

taoeOttTt

�

zsvti

itsia

sttttiic

pcbpc

E

wtta

A

is likely to be associated with both a more stable role in societyand more experience of interactions with authorities. Similarly,

7 Results available from the authors upon request.8 Since the ordered probit results do not lend themselves to direct interpreta-

tion, the discussion of the results is based on the marginal effects results. In general,however, a positive coefficient in Tables 3 and 4 implies an increase in the prob-

40 M. Bezabih et al. / The Journal of

eterogeneity �i and the regressor, Mundlak (1978) suggestsmodel where the relationship between time varying regressors

it and the unobservable effect �i are explicitly modeled in an aux-liary regression. This approach implies specifying the unobservedeterogeneity:

i = + X i� + ei ei|xi∼N(0, �2e ) (4)

In Eq. (4), X i is the average of the time varying variablesn Xit and �2

e is the variance of ei in Eq. (3). Adding the meanalues of time varying observed covariates controls for the unob-erved heterogeneity without the data transformation in the fixedffects estimator, as well as the associated shortcoming of remov-ng any time-constant explanatory variables along with �i. Thispproach is commonly known as the pseudo-fixed effects or thehamberlain–Mundlak’s Random Effects Model.

The presence of heteroskedasticity in non-linear models such ashe ordered probit model is associated with the risk of both wronglyscribing non-existent effects significance and the non-detectionf real effects. In order to avoid this, we employ the Ordinal Gen-ralized Linear Model (Williams, 2010) for heterogeneous choice.GLM allows for differences in the variance across cases by simul-

aneous estimation of two equations; one for the determinants ofhe outcome, and one for the determinants of the residual variance.he choice equation is given by Eq. (1) above. However, in additiono Eqs. (1) and (4), we also specify the variance equation:

i = exp

⎛⎝∑

j

zij�j

⎞⎠ (5)

Eq. (5) shows how the latent variable is scaled for each case.ij can be constituted by both discrete and continuous variables,uch as gender and income, believed to cause differences in theariances. A convenient feature of OGLM is the possibility to firstest variables that are associated with heteroskedasticity and thennclude these variables in the variance equation.

An alternative to the parametric difference in difference methodn ensuring strict exogeneity of the treatment (in this case cer-ification) is a semi-parametric analysis by the use of propensitycore matching. The main approach in the propensity score match-ng method is to balance the observed distribution of covariatescross the groups of certificate recepients and non-recipients.

The first step of computing a propensity score in propensitycore matching to estimate a standard probit or logit participa-ion model with control variables. The predicted values are usedo estimate the propensity score for each observation in the par-icipant and the non-participant samples. The comparison group ishen formed by identifying the “nearest neighbor” for each partic-pant (Jalan and Ravallion, 2003) to test for systematic differencesn the covariates between the treatment and comparison groupsonstructed by propensity score matching.

Rosenbaum and Rubin (1983) showed that matching on theropensity score is equivalent to matching on all the observedovariates. Based on this property, the propensity score can alsoe used to delineate the common support group, where the non-articipants with the same propensity score is higher than someut-off level.

The propensity score is given by:

(x) ≡ Pr(w|X = x) = E(w|x = X) (6)

here w is the indicator of exposure to treatment, and x is the mul-idimensional vector of pretreatment characteristics. Accordingly,

he average treatment effect on the treated (ATT) can be estimateds:

TT = {E[y|w = 1], Pr(x)} − {E[y0|w0 = 0], Pr(x)|w = 1} (7)

-Economics 40 (2011) 833–843

4. Results and discussion

The main estimation results are presented in Tables 3 and 4.The distinction between the results in the two tables is that timevariant household characteristics are controlled for in the latter,making the results in Table 4 akin to pseudo fixed effects results(Mundlak, 1978; Chamberlain, 1984). In both Tables 3 and 4, thefirst 4 columns relate to determinants of institutional trust in termsof authorities as well as the local (kebele), regional and federalgovernment along with trust for the police and NGOs (SIDA). Thelast two columns relate to interpersonal trust in terms of people ingeneral and trade partners.

As mentioned above, the dependent variable is of ordinal scalewith 5 categories and the main estimations are consequently car-ried by a heteroskedasticity adjusted ordered probit approach(Williams, 2010). For comparison purposes, we run standard OLSand homoskedastic ordered probit regressions in addition to theresults reported in Tables 3 and 4. A comparison of the Chi-square values in Tables 3 and 4 and these additional regressionsshows that the heteroskedasticity corrected ordered probit modelestimated with Chamberlain–Mundlak effects fits the data to ahigher extent than the simple ordered probit and the OGLM with-out Chamberlain–Mundlak effects.7 The individual coefficients are,however, very stable over all estimations.

The marginal effects of the significant variables, based on theestimated coefficients of the ordered probit estimation are pre-sented in Table A1.8 Our variable of interest, certification (posttreatment), is consistently and significantly associated with ahigher degree of trust for both authorities and interpersonal rela-tions. Indeed, for most of the trust variables relating to authorities,certification holds the single most important explanatory power.The only exception in which certification is not significant is whentrust is measured in terms of trust for the kebele (local) govern-ment.

Trust for the local (kebele) government is shown to be higherfor households in which the household head is able to write, hasa relatively low wealth in terms of livestock and lives in the EastGojjam Zone. This result could be interpreted as a suggestion thathouseholds, whose members are able to understand written com-munication from authorities, trust the local government to a higherextent than other households. Turning to trust for people in general,next to land certification, the single most important determinantis whether or not the household expects a reduction in land hold-ings in the future and whether or not the household rents out land.Trust in other people is also lower for households with larger landholdings. Previous research (Holden and Bezabih, 2008) has pointedto the fear of losing land to tenants. Hence, this finding could beinterpreted as that, although the acquisition of a land certificateincreases security and therefore trust in other people, underlyingland tenure insecurity may still constitute a problem for individu-als renting out land.9 Finally, for trust in the regional and federalgovernment, we see that age has a positive and significant impacton trust. This result is perhaps best explained by the fact that age

ability that the respondent considers the institution or person to be somewhat orcompletely trustworthy.

9 It should be noted that while certification may reduce tenure insecurity, it maynot completely do away with it, given the history of the landtenure system in thecountry.

M. Bezabih et al. / The Journal of Socio-Economics 40 (2011) 833–843 841

Table A1Marginal effects of significant variables in ordered probit.

Variable 1 2 3 4 5Completelyuntrustworthy

Somewhatuntrustworthy

Average Somewhattrustworthy

Completelytrustworthy

People in generalPost treatmenta −0.044 −0.02 0.024 0.019 0.021Treatmenta 0.031 0.011 −0.017 −0.013 −0.013Tradeouta 0.038 0.011 −0.02 −0.014 −0.014Total land area by hh 0.000 0.000 0.000 0.000 0.000Expect a decrease in size of land holdings 0.037 0.011 −0.02 −0.014 −0.014Zonea 0.012 0.004 −0.006 −0.005 −0.005KebelePost treatmenta −0.019 −0.017 −0.006 0.009 0.034Treatmenta −0.023 −0.019 −0.006 0.011 0.038Number of male adults in household −0.009 −0.008 −0.002 0.004 0.015Number of female adults in household −0.011 −0.009 −0.003 0.005 0.018Expect no change in size of land holdings 0.023 0.018 0.005 −0.011 −0.035Zonea 0.09 0.069 0.019 −0.044 −0.135Regional governmentPost treatmenta −0.089 −0.084 −0.022 0.052 0.142Age −0.001 0.000 0.000 0.000 0.001Total land area by hh 0.000 0.000 0.000 0.000 0.000Zonea 0.037 0.026 0.003 −0.025 −0.041Federal governmentPost treatmenta −0.09 −0.088 −0.028 0.043 0.164Age −0.001 0.000 0.000 0.000 0.001Number of male adults in household −0.007 −0.005 −0.001 0.004 0.009Total land area by hh 0.000 0.000 0.000 0.000 0.000Zonea 0.031 0.023 0.004 −0.019 −0.039PolicePost treatmenta −0.036 −0.04 −0.002 0.039 0.039Treatmenta −0.034 −0.035 0.000 0.036 0.033Total land area by hh 0.000 0.000 0.000 0.000 0.000SIDAPost treatmenta −0.049 −0.033 −0.002 0.035 0.049Treatmenta −0.035 −0.021 0.001 0.025 0.031Number of oxen owned by household and present 0.012 0.007 0.000 −0.008 −0.01Total land area by hh 0.000 0.000 0.000 0.000 0.000Trade partnersPost treatmenta −0.06 −0.022 0.022 0.024 0.035Treatmenta 0.032 0.008 −0.012 −0.012 −0.016Tradeouta 0.03 0.007 −0.011 −0.011 −0.014Number of oxen owned by household and present 0.014 0.004 −0.005 −0.005 −0.007Total land area by hh 0.000 0.000 0.000 0.000 0.000

hr

ctotTio

tiboFi

piemoii

Zonea 0.047

a dy/dx is for discrete change of dummy variable from 0 to 1.

ouseholds with larger land holdings display greater trust for theegional government than households with smaller landholdings.

The heterogeneous choice model further allows us to analyzehanges in the residual variances. The results in Table 3 suggesthat the residual variance in trust has fallen during the time periodf observation. In addition, households in treatment villages tendo be less variable concerning their level of trust for authorities.aken together, these results may point to the effect of increasednteraction with authorities and thus better knowledge on whetherr not to trust these.

From the marginal effects presented in Table A1, we see thathe acquisition of a land certificate is associated with a 14.2%ncrease in the likelihood of perceiving the regional government toe completely trustworthy, and a 16.4% increase in the probabilityf conceiving the federal government as completely trustworthy.or the police authority and SIDA, the corresponding percentagencrease in perceived degree of trust is 3.9 and 4.9 respectively.

Average treatment effect on the treated (ATT) based on the semi-arametric analysis with propensity score matching are presented

n Table A2, which reports the estimates of the average certificationffects estimated by Nearest Neighbour and Mahalanobis matching

ethods. The results are reported in terms of increase in the level

f trust. The results reveal that certification consistently increasesnstitutional trust in (increasing trust in the range of 15–80%), yett shows no significant changes impact in the interpersonal trust.

0.012 −0.018 −0.018 −0.023

These estimated impacts are also large in the nearest neighbor esti-mates.

A comparison of the results in Tables 3 and 4, below with theresults of alternative estimation techniques presented in AppendixA, show that although the coefficients do change in magnitude,the sign and significance level of the results are strikingly stableregardless of the estimation procedure used for the regression. Theonly exception is interpersonal trust between people in general, forwhich the average treatment effect is non-significant.

5. Conclusions

To the extent that trust helps determine the effectiveness ofcommitted relations, the outcomes of efficiency enhancing marketinteractions rely on the level of trust. In contrast, a lack of trustin relations has negative economic consequences because almostall economic transactions have embedded within them a certainlevel of trust (Putnam, 2000; Teraji, 2008). Accordingly, there hasbeen a growing interest, both within experimental and within fieldresearch, in understanding the links between trust and economicperformance and assessing the determinants of interpersonal and

institutional trust.

Empirical studies assessing the determinants of trust identifytrust as a cultural, moral or as an incentive driven motive responsiveto institutional and policy measures. The institutional determinants

842 M. Bezabih et al. / The Journal of Socio-Economics 40 (2011) 833–843

Table A2ATT nearest neighbour (average treatment on the treated, nearest neighbour).

Variable ATT N. control N. treatment S.E. t-Stat.

Kebele −0.021 168 612 0.143 −0.146Regional government 0.65 209 648 0.109 5.941Federal government 0.806 208 646 0.115 6.999Police 0.44 322 668 0.092 4.772SIDA 0.535 174 632 0.148 3.605People in general 0.06 391 674 0.086 0.699

N

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Aciency. Resources for the Future, Washington, DC.

Trade partners 0.157 360

ote: S.E. does not take into account that the propensity score is estimated.

f trust are of particular interest to policy makers as they tend toe less sticky and their significance implies that trust is respon-ive to policy changes. In practical econometric studies, however,nstitutional variables tend to be conditioned by the overall levelf trust, making such variables endogenous in trust regressions.y the use of an exogenous policy change in the assessment of theeterminants of trust, the analysis in this paper makes an importanteparture to the literature that largely uses (potentially) endoge-ous policy related variables as determinants of trust.

This paper particularly focuses on the land certification pro-ram in Ethiopia, which may be considered as an exogenous policyhange, and its impact on the level of interpersonal and institutionalrust. The land certification program is designed to enhance landenure security of farmers by maintaining (the egalitarian) statusuo land distribution and equity concerns. The program is institu-ionally innovative in maintaining the status quo that guard equityoncerns by enhancing private land ownership rights and being lowost in implementation.

The difference-in-difference approach is used to measure thempact of the program on trust, by controlling the time of the deci-ion to participate in certification and the presence, or absence, ofndividual-specific traits of participation. To ensure the robustnessf our results, we also employed semi-parametric analysis of theole of certification on trust. Overall, trust is found to be enhancedy the certification program, with trust towards formal institutionseing more responsive to the program than interpersonal trust. Theajor policy implication of the result is that trust could be invested

n through policy changes to the economic betterment of societies.This study has several important implications. First, unlike

everal similar policy variables, that are possibly endogenous,ssessment of the responsiveness of trust to exogenous changesn private land ownership sheds light on the true responsivenessf trust to policy measures. Second, the greater responsiveness ofnstitutional trust to exogenous policy measures, as opposed tonterpersonal trust, implies that interpersonal trust is of the typehat takes time to form. Hence, policy measures that aim towardsuilding stronger interpersonal trust should focus on more longerm measures.

ppendix A.

See Tables A1 and A2.

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