metadata: authors: 0: author: Leony,Larissa
1: author: Barros De Moura,Mauricio Jose Serpa
2: author: da Silveira Bueno, Rodrigo De Losso
count: Brazil
docna: 0: docna: How land title affects child labor ?
docty: Policy Research Working Paper
subtopic: Economic Theory & Research,Social Policy,Legal Products,Child Labor Law,Judicial System Reform,Industrial Economics,Agricultural Economics,Labor Markets,Child Labor,Labor Standards,Common Property Resource Development,Educational Sciences,Economic Growth,Legal Reform,Legislation,Regulatory Regimes,Rural Labor Markets
teratopic: Gender,Social Protections and Labor,Finance and Financial Sector Development
abstracts: cdata!: Secure property rights are considered a
            key determinant of economic development. However, evaluation
            of the causal effects of land titling is a difficult task.
            Since 2004, the Brazilian government, through a program
            called "Papel Passado," has issued titles to more
            than 85,000 families and has the goal to reach 750,000.
            Another topic in public policy that is crucial for
            developing economies is child labor force participation. In
            Brazil, about 5.4 million children and teenagers between 5
            and 17 years old are working full time. This paper examines
            the direct impact of securing a property title on child
            labor force participation. In order to isolate the causal
            role of ownership security, this study uses a comparison
            between two close and similar communities in the City of
            Osasco case (a town with 650,000 people in the São Paulo
            metropolitan area). The key point of this case is that some
            units participate in the program and others do not. One of
            them, Jardim Canaã, received land titles in 2007; the other,
            Jardim DR, given fiscal constraints, will not be part of the
            program until 2012, and for that reason became the control
            group. Estimates, generated using the
            difference-in-difference econometric technique suggest that
            titling results in a substantial decrease in child labor
            force participation for the families that received the title
            compared with the others. These findings are relevant for
            future policy tools for dealing with informality and how it
            affects economic growth.
geo_reg_key: 119228,517191
repnme: repnme: How land title affects child labor ?
display_title: How land title affects child labor
listing_relative_url: /research/2009/07/10914119/land-title-affects-child-labor
topicv3: Child Labor m1326042 1859,Economic Growth m1326241 471,Personal Property Rights m1326571 1907,Cadastre and Land Registration m1326617 890,Education m1327048 470
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: Gender,Social Protections and Labor,Finance and Financial Sector Development
no_of_pages: 33
author_keys: 0: author_key: 1000297
1: author_key: 967915
model_extractions: WPS5010 Policy Research Working Paper 5010 Impact Evaluation Series No. 37

# How Land Title Affects Child Labor?

_Mauricio Jose Serpa Barros de Moura Rodrigo De Losso da Silveira Bueno Larissa Leony_ The World Bank Syndication and Resources Mobilization-IFC Syndications Unit July 2009
Policy Research Working Paper 5010

# **Abstract**

Secure property rights are considered a key determinant of economic development. However, evaluation of the causal effects of land titling is a difficult task. Since 2004, the Brazilian government, through a program called _“Papel Passado,”_ has issued titles to more than 85,000 families and has the goal to reach 750,000. Another topic in public policy that is crucial for developing economies is child labor force participation. In Brazil, about 5.4 million children and teenagers between 5 and 17 years old are working full time. This paper examines the direct impact of securing a property title on child labor force participation. In order to isolate the causal role of ownership security, this study uses a comparison between two close and similar communities in the City of Osasco case (a town with 650,000 people in the São Paulo metropolitan area). The key point of this case is that some units participate in the program and others do not. One of them, _Jardim Canaã,_ received land titles in 2007; the other, _Jardim DR,_ given fiscal constraints, will not be part of the program until 2012, and for that reason became the control group. Estimates, generated using the difference-in-difference econometric technique suggest that titling results in a substantial decrease in child labor force participation for the families that received the title compared with the others. These findings are relevant for future policy tools for dealing with informality and how it affects economic growth.

This paper—a product of the Syndications Unit, Syndication and Resource Mobilization-IFC (Latin America and the Caribbean)—is part of a larger effort in the department to promote high standard business and public policy initiatives. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at mmoura@ifc.org.

_The Impact Evaluation Series has been established in recognition of the importance of impact evaluation studies for World Bank operations and for development in general. The series serves as a vehicle for the dissemination of findings of those studies. Papers in this series are part of the Bank’s Policy Research Working Paper Series. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# How Land Title Affects Child Labor ?

_Mauricio Jose Serpa Barros de Moura, IFC- World Bank Group_ _Rodrigo De Losso da Silveira Bueno EAESP/FGV - Brazil_ _Larissa Leony_ _John Hopkins University_

**Key Words:** Property rights, land titling, child labor force
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The most famous example is Peru in Latin America. The Peruvian government issued property titles to 1.2 million urban households during the 1990s. In Asia, millions of titles are being issued in Vietnam and Cambodia as shown in the _The Economist_ magazine in the March 15, 2007 edition. The same edition states on the front page: " _Property Rights: China's Next Revolution_ ". The survey shows that China intends to put into place the most ambitious land-titling program in the world's history and includes this initiative as one of the main points of the Chinese economic development model.

In Brazil, President Luiz Inácio Lula da Silva announced during his first week in office, back in 2003, a massive plan to title 750,000 families all over the country. The Brazilian federal government created a program called " _Papel Passado_ ". Since launched, the program has spent US$ 15 million per year from the federal budget, providing titles to over 85,000 and reaching 49 cities in 17 different Brazilian states. The official goal of the program is " _to develop land titles in Brazil and promote an increase in the quality of life for the Brazilian population_ ". However, the country still faces a very difficult scenario regarding land property rights: the Brazilian government estimates that 12 million people live under illegal urban conditions (IBGE, 2007).

Furthermore, child labor is a major issue faced by the global economy. In Brazil, about 5.4 million children and teenagers between 5 and 17 years old are working (PNAD, IBGE, 2007).

This paper investigates the impact of property rights on labor markets in an emerging economy such as Brazil by analyzing household response regarding to child labor force participation to an exogenous change in formal ownership status. In particular, the paper assesses the value to a squatter household of increases in tenure security associated with obtaining a property title in terms of hours of child labor supply.

Effects of land titling have been documented by several studies. A partial listing includes Jimenez (1985), Alston _et al._ (1996) and Lanjouw & Levy (2002) on real estate values. Besley (1995), Jacoby _et al._ (2002), Brasselle _et al._ (2002) and Do & Iyer (2003) on agricultural investment. Place & Migot-Adholla (1998), Carter & Olinto (2002) and Field & Torero (2002) on credit access, housing investment and income.

In urban settings, the value of property titles has been measured far less often and empirical work has focused on real estate prices. A major contribution is from the of paper by Jimenez (1984), involving an equilibrium model of urban squatting in which it is shown that the difference in unit housing prices between the non-squatting (formal) sector of a city and its squatting (informal) sector reflects the premium associated with security. The accompanying empirical analysis of real estate markets in the Philippines finds equilibrium price differentials between formal and informal sector unit dwelling prices in the range of 58.0% and greater for lower-income groups and larger households.

For Besley (1995), the findings were ambiguous; land rights appear to have a positive effect on agricultural investment in the Ghananian region of Angola but less noticeable impact on the region of Wassa. Using a similar approach, Jacoby _et al_ . (2002) find positive effects in China, whereas Brasselle _et al._ (2002) find no effects for Burkina Faso. Field & Torero (2002), in Peru, exploit timing variability in the regional implementation of the Peruvian titling program using cross-sectional data on past and future title recipients midway through the project, and also find positive effects, particularly in credit access and housing investments. In Brazil, Andrade (2006) using cross-section data from a sample of 200 families of the _Comunidade do Caju_ , an urban poor community in Rio de Janeiro, has demonstrated an increase effect on the income of those that had received the land title.

A common obstacle, faced by all studies mentioned above, is how to measure the influence of tenure security considering the potential endogeneity of ownership rights as pointed by Demsetz (1967) and Alchian & Demsetz (1973). Direct evidence of this is 3
<!-- Start of picture text --> In ascaleof 1to 10, considering 1 as no effect at all, and<br>10 if your life is really better because of the land title<br>40 a7 35<br>35<br>ww 28<br>a «30 25 24<br>2 25 22<br>a<br>= 20<br>=<br>5 15<br>z= 10 7<br>5211<br>0<br>12 3 4 5 6 7 8 i} 10<br>Scale<br><!-- End of picture text -->
Secondly, this research provides unique panel data through a natural experiment that helps to minimize the endogeneity aspect related to most of the studies on such subject (property rights).

Third, many aspects have been applied to try to explain the reasons for child labor. The most common are income, poverty, parents’ level of education, parents’ previous child labor experience, credit constraints, and others. This paper intends to provide an additional aspect that can be used as part of the explanation for the causes of child labor.

Last, but not least, this paper provides an initial impact measure, in terms of applied public policy, for the " _Papel Passado_ " program and gives a partial feedback for policymakers about the effects of land titling in variation of child labor force participation. Certainly, reducing child labor force participation is one of the main goals of federal and local governments. Social programs such as PETI ( _Programa de Erradicação de Trabalho Infantil_ ), an initiative that focuses on providing education opportunities for children engaged in labor activities and extra income for their poor families, is a great example of government's concern. Understanding the potential positive effects of land titling and property rights in such subject could be valuable to make any effort related to child labor participation stronger and more effective.

# **1. Child Labor Force Participation: The Economic Context**

Investing in and focusing on human capital development is a critical factor to increase economic growth, as stated by Becker and Lewis (1973), and given such a key assumption, The United Nations Millennium Development Goals include eliminating child labor as a crucial step into a better and equal world.

According to the International Labour Organization (2002), 246 million children and teenagers between 5 and 17 years old are engaged in child labor around the world. Furthermore, 75.0% of those children work for their own family activities. Asia, Africa and Latin America are the continents with the most the child labor in the world. Asia has the highest number of children in terms of volume but Africa is the leader relative to the total size of the work force.

In Brazil, data from PNAD (IBGE, 2007) has shown that from a 44.7 million population between 5 and 17 years old, 10.8% (4.8 million) are directly involved in child labor. The worst region of Brazil regarding this subject is the Northeast, with 13.4% of the 5-17 year old population working; Southeast holds the lowest average (7.9%). These statistics represent a positive evolution over the last 4 years (see Figure 3 below).

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Figure 3: Occupation level among the 5-17 year-old population (Percentual of total 5-17 population) <!-- Start of picture text --> 18<br>16<br>14<br>12<br>10<br>8<br>6<br>4<br>2<br>0<br>Brazil North Northeast Southeast South Mid-West<br>2004 2005 2006 2007<br>15.9<br>14.8 14.9<br>14.4<br>13.8 13.1 13.4 14.0 13.6 13.6<br>12.2 12.4<br>11.8 11.5 10.8 11.3 11.1 10.5<br>9.9 9.8<br>8.6 8.4<br>% 7.9 7.9<br><!-- End of picture text --> Source: IBGE, PNAD 2007 However, child labor is still a major issue for Brazilian policy makers and PNAD (IBGE, 2007) also indicates that. For example, 60.0% of the children between 5 and 13 years old are involved in non-paid activities. In the rural areas of Brazil, 40.0% of the 5-17 year old population works between 30 and 40 hours per week. In the Southeast, the richest region in the country, 30.0% work at least 40 hours per week.

Economic science has developed a range of potential theories to explain child labor. As Becker and Lewis (1973) state, child labor is an activity that generates current benefits in terms of income, but also creates future costs by reducing study and leisure. Given that, families evaluate the cost-benefits related to sending their children to school or to work. Rosenzweig (1981) has demonstrated that children's time allocation depends on the production capacity of the children and their parents and the substitution degree of the work force between both.

Basu & Van (1998) have built a model using one basic assumption: luxury. They consider that poverty is the main factor that makes parents send children to work. Hence, the children's time that is not allocated (school and leisure) to generate income is luxury, which low-income parents cannot afford. Ray (2001) has created a theory for emerging economies: child labor occurs mainly because of poverty and credit market imperfections. He has shown that if poor families had access to credit, in the presence of high returns for education, they would be willing to send their children to school instead of work. Furthermore, the same study showed the relationship between income inequality and child labor under credit constraints. The main conclusion states that a more equal income distribution would reduce child labor.

Kassouf (2002) demonstrates that an increase in the household's income reduces the probability of child labor and increases school attendance. Another element that affects the probability of child labor is the parent's education degree. Bhalotra & Heady (2003) find a negative effect given the mother's level of education and the child’s labor participation in Ghana. The effect of the mother's education profile is higher compared with the father’s. Kassouf (2002), in Brazil, obtains the same negative effect. Family composition is another relevant factor. Patrinos & Psacharapoulos (1994), for Paraguay, and Bhalotra & Heady (2003), for Pakistan, conclude that the more people there are in the family, the greater the chances of having child labor.

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Wahba (2002), using data from Egypt, shows a phenomenon called "dynastic poverty traps," which means that the probability of children being sent to work increases 10% when their parents had worked during their childhood. Emerson & Souza (2003) reach the same conclusion and explain such event as "social norms", parents that worked during their childhood years face child labor more naturally. As mentioned earlier, this paper aims to provide an additional element for that discussion and test the relation between land titling and child labor force participation using the case of the City of Osasco.

# **2. Microeconomic Framework – The Basics**

Cockburn (1998) points out that one of the principal gains of strong property institutions is to shift the burden of property protection and enforcement away from individual households and informal communities to the state.

There is little microeconomic evidence documenting the cost of informality to individual households. Carter & Zegarra (2000), World Bank (2000) and Field (2007) note that, in many settings, informal institutions arise to compensate for the absence of formal property protection. In such context, there is one important mechanism by which it is assumed that tenure security removes individuals from the labor force and incremental income. Untitled households are constrained by the need to provide informal policing, both to deter prospective invaders from invading private properties and to actively participate in community enforcement efforts to protect neighborhood boundaries.

Hence, an important outcome of titling efforts that effectively increase household tenure security should allow households and communities to reallocate time, resources and human talent away from this role.

The acquisition of a property title has a direct value in terms of freeing up hours of work (and income generation) previously devoted to maintaining tenure security through informal means.

_w_ = market wage _H_<sup>_m_</sup> = work in the outside market Assumptions: a) There is no outside labor market for provision of home/tenure security. Assuming a missing labor market for the provision of home security is reasonably justified by incomplete contracts (there some risk involved in employing non-members to guard property - especially in those poor communities in Brazil).

b) Leisure and home production hours are assumed to be perfect substitutes for the hours individual spend on property protection.

c) All households face a common wage _wi_ .

d) The household is assumed to maximize per capita leisure ( _li_ ) and not the leisure of individual members.

e) Household talent ( _Φ_ ) and endowment ( _E_ ) are assumed to be fixed.

Assuming, Z = time spent at home = H<sup>h</sup> +L H<sup>h</sup> = work at home and L = leisure And L = ∑ = li,H<sup>h</sup> = ∑ = H<sup>h</sup> ,H<sup>m</sup> = ∑ = H<sup>m</sup> ,X = ∑ = X N is the number of household members, NN NN li is leisure, NN xi consumption, NN H<sup>hi</sup> work hours in ii=1 ii=1 ii=1 ii=1 home production, and H<sup>m</sup> outside market work hours of household member i, and xi = X/N, li = L/N.

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The value of work at home is given by production function q(H<sup>h</sup> ) and _w_ is the value of work outside or the market wage.

Household utility is an increasing function of _per capita_ leisure (li); _per capita_ consumption (xi), and home security tenure (S) (S = home tenure security function) and also concave.

The tenure security function implies that the production of home security is only determined by exogenous variable Ω (Ω = exogenous parameter, household formal property rights) and the amount of time spent in the home.

Given the set of talent Φ and endowment E: Maximizing the utility function: _U_ ( _xi_ , _li_ , _S : Φ, E_ ) where _S = S (Z,Ω),_ where the endogenous variables are _H_<sup>_h_</sup> _, H_<sup>_m_</sup> , _xi_ , _li_ , and _S._ Budget ( _pX_ ) and time ( _T_ ) constraints to the maximization problem: Assumption: _L, H_<sup>_h_</sup> _, H_<sup>_m_</sup> _, xi ≥ 0_ Where _q(.)_ satisfies the decreasing marginal productivity _(q′ > 0, q"< 0)_ . Then, normalizing prices to one, the household's optimization problem is: This equation requires the following first-order conditions for an interior solution ( _H_<sup>_m_</sup> _> 0; H_<sup>_h_</sup> _> 0; H_<sup>_m_</sup> _+H_<sup>_h_</sup> _< T_ ): Equation 1 establishes that, at the optimum, households equate the marginal value of an additional hour of outside labor with the marginal utility of leisure. Equation 2 states that they also equate the marginal utility of leisure with the marginal value of an additional hour of work at home.

Given such context, the demand functions of work hours in the outside market and in home production which depends on _Ω_ and _ω_ are: _H = H_ Assume that x _≥ 0, ≥ 0, ≤ 0_ ii XXiiXXii lliixx UU UU UU In that case, households’ ability to increase security by staying close to home implies that optimal allocation of work hours across home and market will depend on the formal tenure rights. In particular, maximizing the above utility function subject to the basic budget and time constraints mentioned above generates the following inequalities: 8
For households involved in both types of labor, an increase in formal tenure security decreases work hours at home and increases work hours in the outside market.

The conditions imply that, in aggregate, strengthening formal property rights decreases work hours inside the house and increases time spent outside, reflecting the fact that an exogenous increase in formal property protection, lowering the opportunity cost of outside labor and making stronger the probability to increase the current income of those households as represented by _I(Income) = f(w;H_<sup>_m_</sup> _)._ In the empirical analysis, data limitations prevent the separation of employment hours inside and outside the home. Given that, and with respect to the net effect of a property title on total labor hours, the model predicts that households with zero home production hours _exante_ ( _H_<sup>_h_</sup> _=0_ ) will increase total household work hours by some positive amount in response to a land title and property rights.

# **3. Microeconomic Framwork – Labor Supply of Children**

An extension of the model, and a significant part of the present study approach, incorporates differences in the household supply of adult and child labor when only adults contribute to home security provision. This extension formalizes the intuitive idea that, if adults have comparative advantage in the provision of home security, in the absence of property rights, children will substitute for adults in the labor market. In this case, while total household labor hours rise with an increase in formal rights – as demonstrated above, child labor hours will actually fall. Here, _Na_ and _Nc_ are the number of adult and child household members, respectively, _la_ and _lc_ are per capita adult and child leisure, _La_ and _Lc_ are total adult and child leisure and _Ta_ and _Tc_ are total adult and child time endowments. In this setting, the household maximization problem is: The first-order conditions corresponding to each employed adult member _i_ and child _j_ are: In households in which children are labor force participants, child labor hours will fall and adult labor hours will rise with an increase in tenure security. For all other households, adult labor hours will rise and child labor hours will remain at zero. Thus, given a positive amount of ex-ante child labor, the aggregate number of child labor hours will unambiguously fall, while the number of adult hours rises with an increase in property rights.

Although this model focuses on optimal labor allocation, the income effect that follows from relaxing the household time constraint provides a plausible alternative explanation for a decrease in child labor with an increase in formal rights, and one that has been proposed by other authors. In particular, a decrease in child labor would follow from the luxury and axioms of the Basu & Van (1998) model of labor supply, in which children can substitute for adults in the labor market and the family will send children to the labor market only if the family's income from non-child labor sources falls below some threshold amount.

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# **4. The Data**

The empirical analysis of household labor supply and income responses to changes in formal property rights relies on a data survey developed especially and exclusively for this paper, in the City of Osasco, an important town in the São Paulo metropolitan area with a population of 654,000 people.

The federal government has chosen Osasco, as one of the participants of the " _Papel Passado_ " - a program that intends, as mentioned earlier in the paper, to provide land titles to families living under illegal conditions - given its relevant economic and social role.

The city of Osasco has 30,000 people (about 6,000 families) living under informal conditions, which represents almost 4.5% of its total population. The program timetable for Osasco establishes that all the communities living in illegal conditions will be part of the " _Papel Passado_ " during the period between 2007 and 2014 (the main reason that all communities are not receiving the land title at the same time is becuase fiscal resources are limited). Officially, as released by the Osasco City Hall, the priority follows random criteria. Unofficial sources from local communities in Osasco express the feelings that a "political" agenda is present in the decision.

The first community to receive the land title was _Jardim Canaã_ , in 2007, which has 500 families. The closest neighbor of _Jardim Canaã_ is a community called _DR_ , with 450 families. The _DR_ 's households will be part of the " _Papel Passado_ " program schedule in 2011. Hence, the data of this particular paper consist of 326 households distributed across _Jardim Canaã_ and _DR_ (185 from _Jardim Canaã_ and 141 from _DR_ ).

# **4.1 Minimizing Endogeneity Bias Concerns**

Given the nature of the research conducted in the city of Osasco, some steps were taken to minimize the bias related to the data collected.

First of all, a technique from Bolfarine & Bussab (2005) was used to choose randomly 326 sample households. The approach was basically to choose the first 150 households (from the _Canaã_ and _DR_ ) that have the closest birth dates (day and month) in comparison with the three field researchers that conducted the survey interviews (important to mention that the field researchers are not from Osasco). Each researcher got 50 names initially as first base. Additionally, after reaching each of those households, they could go and pick the third and the fifth neighbor on the right hand side.

Secondly, Heckman & Hotz (1989) states that constructing counterfactuals is the central problem in the literature evaluating social programs given the impossibility of observing the same person in both states at the same time. The goal of any program evaluation is to compare only comparable people. An important step to minimize such issue in this study was to use a comparison between those two neighbors ( _Jardim Canaã_ and _DR_ ) with very similar characteristics. _Canaã_ and _DR_ are not only official neighbors but there is no physical "borderline" among them, both are geographically united (if someone walks there, it is hard to identify the boundaries -- even for the local households).

One of them, _Jardim Canaã_ , fortunate to receive the titles in 2007, is qualified, for the paper proposal, as the main sample. The other, _DR_ , only part of the program schedule in 2011, became the control group. This approach enables a comparison of households in a neighborhood reached by the program with households in a neighborhood not yet reached and makes it possible to produce a panel of data.

Another aspect to be mentioned about the data collected is that it produced a unique match within the same geographic area, which helped to ensure that comparison units come from the same economic environment. Rubin & Thomas (2000) indicate that impact estimates 10
based on full (unmatched) samples are generally more biased, and less robust to missspecification of the regression function, than those based on matched samples.

Given such conditions, the data were produced from a two-stage survey focused on the property right issue. However, to minimize bias, the way that survey was prepared and conducted by the researchers does not provide any direct information for the households on what exactly the research is about. Officially for the people interviewed, the study was about general living conditions in the City of Osasco.

The survey was based on a 39-question questionnaire applied to the 326 families randomly sampled as described above. The survey instrument, in many of its questions and methodologies, closely mirrors the IBGE Living Standards Measurement Survey (PNAD - _Pesquisa Nacional de Amostra de Domicílios do Instituto Brasileiro de Geografia e Estatística_ ) in content, and therefore contains a variety of information on household and individual characteristics. In addition, there are six questions designed to provide information on a range of economic, social and personal benefits associated with property formalization. (See Appendix A for the complete stage I and stage II questionnaires.) The first stage of the survey was conducted in March 2007, before titles had been issued to _Jardim Canaã_ , and the second collected in August 2008, almost a year and a half after the first titles had been issued (with exactly the same households and with 98.0% recall -- or 2.0% missing, which means that almost all the households interviewed in the first survey were found and interviewed during the second stage). The reason for the time gap was to give the an opportunity to all the households interviewed during the first survey stage to have at least 1 year with the land title. The exactly dates that each household interviewed received the title were provided by the 2nd _Cartório de Osasco_ (2nd Osasco's Office of Registration) along with the formal authorization from the Osasco's City Hall to conduct the research.

Heckman & Hotz (1989) add that is not necessary to sample the same persons in different periods -- just persons from the same population. This particular survey instrument design has clearly the advantage that the same households were tracked over time to form a panel data set. Ravallion _et al._ (1995) argue that making a panel data with such characteristics should be able to satisfactorily address the problem of miss-matching errors from incomplete data, a very common issue regarding public policy evaluation.

Furthermore, it is also important to emphasize again another aspect that helps minimize the selection bias. Based on the first survey, 95.0% of the survey participants (from _Canaã_ and _DR_ ) did not expect to receive any land title, i.e., they were not aware of " _Papel Passado_ " and the meaning of it. Such lack of information about the subject provides the study a nonbias aspect regarding the importance of property rights because it avoids a potential behavior deviation from households included in the program.

Finally, the study also tracks the households that moved outside both communities to check if the land title effect stands. From the original sample only 8.0% of the households that received the land title have moved away from _Canaã_ (one of the main concerns from local authorities in Osasco was that most citizens would receive the land title, sell the property right away and return to an informal living conditions and that not has been materialized). From the control group, only 1 household (out of 140) has moved during the same period.

# **5. Basic Findings – Child Labor Force**

This study has used basically four questions to address the issue of child labor using the survey. The first question was: _“Do you have any children?”_ (Please refer to Appendix A for the complete stage I and stage II questionnaires.) Of the combined sample and control group, about 75.0% of the households said they have children (about 73.0% of the sample and 76.0% of the control group).

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After the initial question mentioned above, the survey included the following: a) _“Are there any children helping in the family’s income? How many? (under 18 years old)”_ , b) _“How many hours do they work daily?”_ and c) _“How many days per week do minors work?”_ On top of that, from those households that have children, 25.5% responded that they have minors helping the family’s income (sample 35.4% and control group 64.8%).

Additionally, the diagram below summarizes the household’s answers (2007 and 2008) about weekly hours of child labor. The main issue that arises is related to the fact that for the sample, children are working lower hours (and even households that have children working in 2007 changed path in the survey’s second round) and for the control group the scenario gets worst over time.

Figure 4: Child Labor Force Hours Worked Weekly x Number of Households <!-- Start of picture text --> 10<br>9<br>9<br>8<br>8<br>7<br>6<br>5<br>4 2007<br>4<br>3 3 2008<br>3<br>2<br>1 1<br>1<br>0<br>0<br>1 - 4 h 5 - 9 h 10 - 19 h 20 - 29 h 30 - 39 h 40 or more<br>Hours worked weekly<br>N° of households<br><!-- End of picture text --> Source: Research from the Osasco Land Title Survey – 2008

# **6. Econometric Model: Difference-in-Difference Estimates**

# **6.1 Difference-in-Difference Estimates: Estimator – General Framework**

The econometric method used was Difference-in-Difference Estimatation, known as DIFF-in-DIFF (DD), given the data characteristics described above. As Bertrand _et al._ (2004) define, Differences-in-Differences consists of identifying a specific intervention or treatment (often a passage of a law). One then compares the difference in outcome after and before the intervention for groups affected by the intervention to the same for unaffected groups.

Such approach involves basically two regimes: "0" and "1" given an observed outcome _Y_ , which means _Y_ 1 _=dY_ 1 _+(1-d)Y_ 0. Given _d=1_ , we observe _Y_ 1 and with _d=0_ , _Y_ 0 is observed.

As Heckman & Hotz (1989) state, the parameter most commonly invoked in the program evaluation literature, although not the one actually estimated in social experiments, is the effect of randomly picking a person with characteristics _X_ and moving from "0" to "1":

# _E(Y_ 1 _-Y_ 0 _/X)=E(Δ/X)_

In practice, most non-experimental and experimental studies do not estimate _E(Δ/X)_ . Instead, studies usually estimate the effect of treatment on the treated.

12
Given the data characteristics, this particular study aims, as previously mentioned, to provide a comparison between "treated" and "untreated" to estimate the impact of treatment on the treated with a counterfactual.

Again as Heckman & Hotz (1989) point out, it is impossible to form change in outcomes between "treated" and "untreated" states for anyone. However, it is possible to form one or the other terms for everyone with the counterfactual mechanism.

Under such scenario, the current study also has the "before-after" estimator which incorporates time _t_ in the model.

Let's assume that the program/treatment occurs only at the time period k and _t > k > t′._ Furthermore, _yit_ is the "treated" group at period _t_ , if _i=1_ and "untreated" if _i=0_ . Additionally, consider _d=1_ is the "treated" group and _d=0_ the "untreated" group.

Hence, the main focus is to estimate the following: and given that it is possible to decouple the equation above between "treated" and "untreated" given two different periods, or _t > t′_ . The Difference-in-Difference estimator is: And, the assumption is: This basically means that between periods _t_ and _t′_ , the variation of the "treated" and "untreated" averages are the same. Hence: Given the fact that there is no treatment at _t′_ , the "treated" differentiates from the "untreated" as _(y_ 0 _t′|d=1)=y1t′_ and _(y_ 0 _t|d=0)=y_ 0 _t′_ . Following the equation above:

Finally, the estimator can expressed as follows: Given the case the _Δyi = ΔXβi +ui_ , the regression is: Assuming that _β_ 1 _-β_ 0 _=0_ , except for the constant, follows: _Δy=ΔXβ_ 0 _+dα+u_ 0 _+d(u_ 1 _-u_ 0 _)_ and _α_ is the focus parameter.

13
# **6.2 Difference-in-Difference Estimates: The Regression Model**

Difference-in-Difference estimates and their standard error, according to Greene (2002), most often derive from using Ordinary Least Squares (OLS) in repeated cross sections (or a panel) data on individuals in treatment and control groups (no treatment) for a period before and after a specific intervention. As Meyer (1995) argues, the great appeal of DD estimation comes from its simplicity as well its potential to circumvent many of the endogeneity problems that typically arise when making comparisons between individuals.

The standard DD estimates the following regression:

# _Yist=As+Bt+cXist+βIst+εist_

where _As_ and _Bt_ are fixed effects for states and years respectively, _Xist_ are relevant individual controls and εist is a error term. The estimated impact of the intervention is the OLS estimate _β_ . Standard errors used to form confidence interval for _β_ are usually OLS standard errors sometimes corrected to account for correlation of shocks within each year. Considering the data characteristics mentioned earlier, this study will assume that the estimated coefficient of intervention is variable (given _Xist_ ) but does not help to determine program participation (land titles were given randomly and households were mostly unaware about receiving the title).

Hence, this specification is a common generalization of the most basic DD, and it will be the foundation for this particular study’s econometric technique. The basic assumption is that changes in the outcome variable over time would have been exactly the same in both the treatment and the control group in the absence of the intervention.

# **6.3 Difference-in-Difference Estimates: Land Title Specification**

In this paper, formally, the dependent variable is hours weekly hours of work of child labor force _Yist_ (the outcome of interest for household _i_ in group _s_ by time _t_ ). The dependent variable would be posted as the difference among weekly hours of child labor in 2008 and 2007.

Also, _δ_ indicates whether the household lives in a neighborhood that has been reached by the program -- being the dummy for whether the land title has affected the group _s_ at time _t_ ; with fixed effects and _Xi_ is a vector of characteristic controls.

Hence, the coefficient _δ_ is the estimated program effect, which provides a measure of conditional average difference in time worked by children in households in the program area versus the non-program area.

In addition, _Xi_ includes the following controls: sex (dummy), marital status (dummy, example: single) and ethnicity (dummy, example: African Brazilian).

Another set of variables included, to extend to include fixed effects, and convergent with Becker & Lewis’s (1973) suggestion, level of income -- measured in terms of minimum wage (please refer to question number P-38 at Appendix A for details). Furthermore, weekly hours of adult work is an essential variable to understand child labor according to Rosenzweig (1981).

Patrinos & Psacharapoulos (1994) for Paraguay, Grootaert (1998) for Ghana, and Heady (2003) for Pakistan conclude that the more people there are in the family, the higher are the chances of having child labor. Given such a framework, the number of household members is also included. The same applies for the years of education of the family head. For income, 14
weekly hours, number of household members and years of education, also the difference between the survey collection results in 2008 and 2007 is applied (example: the independent variable of income is = Income 2008 - Income 2007 and so on with the other variables mentioned).

As a robustness check, this study also estimates a regression including the households that moved from _Canaã_ (households that got the title, sold the property and moved right away). The goal is to check if the land title still has a positive effect even considering those that are not living in the original community.

Given all the conditions mentioned above, the basic econometric structure is the following: _- Yi = α+δ(Land title)+β(Hours worked weekly adult)+β(Income)+β(Households number)+ β(Years of education)+α′Xi+ei_ Furthermore, the main hypothesis to be tested is the following: _H_ 0 _=δ<0 H_ 1 _=δ≥0_

# **7. Results**

The summary of basic statistical results is presented in Table 1 (Sample Means). Consistent with the study’s basic findings, one main aspect demands special attention. The average weekly hours of child labor has decreased in the program households and increased in the non-program households. Additionally, for land title owners, weekly hours worked of adults increase more. This could provide a potential signal that child labor is being substituted by adult work.

Table 1: Sample means - with all households that have children

|||**Pre-Program**<br>**(N = 251)**|||**Post-Program**<br>**(N= 240)**||
|---|---|---|---|---|---|---|
||**Ia**<br>**(program)**|**Ib**<br>**(non-program)**|**IC**<br>**|tΔ|**|**IIa**<br>**(program)**|**IIb**<br>**(non-program)**|**IIC**<br>**|tΔ|**|
|Mean age|42.0|45.0|-3.0|42.8|45.9|-3.1|
|Time in residency<br>(# months)|146.2|158.4|-12.1|157.8|175.0|-17.1|
|Household number<br>(# members)|3.8|4.0|-0.2|3.9|4.1|-0.2|
|Number of rooms|3.3|3.7|-0.7|3.3|3.7|-0.4|
|Income (number of MW)|2.0|3.0|-1.0|2.0|3.0|-1.0|
|Years of Education|9.0|5.0|4.0|9.0|5.0|4.0|
|Hours Worked Weekly|9.8|9.2|0.5|19.5|10.0|9.5|
|Child Labor Hours<br>Weekly|3.5|9.1|-5.6|0.5|11.9|-11.4|

Source: Author's Estimates 15
Table 2: Child Labor and Land Title

|**Independent**|**Depe**|**ndent Variable**|
|---|---|---|
|**Variables**||**Income**|
|||_Robustne_<br>_ss check_|
|Constant|5.66|5.62|
||(1.92)|(1.86)|
|Sex|0.39|-0.11|
||(0.90)|(0.97)|
|Single|-3.38|-4.23|
||(1.56)|(1.77)|
|African Brazilian|-3.20|-3.22|
||(1.90)|(1.92)|
|Years of Education|0.69|0.12|
||(0.11)|(0.12)|
|Households number|-0.51|-0.50|
|(# members)|(0.31)|(0.30)|
|Income|-0.0001|0.00001|
|(number of MW)|(0.0005)|(0.0003)|
|Hours worked weekly|-0.004|0.002|
||(0.05)|(0.05)|
|Land Title|-6.28|-7.26|
||(1.16)|(1.22)|
|R<sup>~~2~~</sup>|0.20|0.20|
|RootMSE|7.07|7.34|
|N|240|251|

Source: Author's Estimates (*) significant at 5% ( ) standard deviation Econometric results appear in Table 2. This study default estimates include the entire set of regressors consistent with the current theory regarding child labor and land titles and the data collected during the survey. In such specification, the estimate of the land title _δ_ coefficient is -6.82, with a robust standard error of 1.16.

This outcome is highly consistent with our hypothesis, that property rights (Land Title) decrease child labor by 6.82 hours worked per week. With a t-statistic of over 5, the coefficient is different from zero at any reasonable level of statistical significance.

The robustness part of the table provides our robustness check, adding (as mentioned previously) to the regression analysis, households that moved. The robustness outcome not only remains but also makes it even more significant (-7.26). This result should help to reinforce the conclusion that land titling has a positive effect on individuals, and not only on property. Households that moved had the same attitude toward child labor.

Hence, the effect of land titling, given the conditions and variables applied, is clearly positive, and helps to minimize the number of weekly hours worked by children.

# **Conclusion**

This paper has presented new evidence on the value of formal property rights in urban squatter communities in a developing country. By studying the relationship between the exogenous acquisition of a land title and child labor force participation, the study has provided additional empirical support for the evidence that property titling appears to reduce household demand for child labor in the majority of households.

16
Although existing studies indicate significant effects on access to credit, income, home investment and fertility (Field 2007; Andrade 2006), this particular study aims at helping to fill an important gap in the literature on property rights and child labor force participation. Furthermore, the results indicate that, unlike employment responses to most welfare programs, which tend to involve an income effect that potentially removes adult households from the labor force, government property titling programs appear to have a different effect -- removing child labor from the labor force.

Regarding further research, it will certainly be interesting to apply the same survey in different locations and compare outcome results. Ravallion _et al_ . (2005) argue that the same program works well in one village but fails in another. An example is Bangladesh's _Food for Education Program_ . The program worked well in reaching the poor in some villages but not in others, even in relatively close proximity. Furthermore, it will also add value in keeping tracking of the same households with other surveys to check the consistency and robustness of the results over time.

It is clear that understanding the multiple channels through which land titles influence economic outcome is particularly important given that governments across the world are considering titling programs to address urban informality. In addition, the results have potential implications for understanding labor market frictions in developing countries (Goldsmith, 1995). In places characterized by high levels of residential informality, such as most developing and poor countries, informal property protection may constitute an important obstacle to labor market adjustment. Hence, land titling could be applied as an asset to improve public policy actions that directly impact economic growth.

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FIELD, Erica & TORERO, Maximo. Do Property Titles Increase Credit Access among the Urban Poor? Evidence from Peru. _Research Program in Development Studies_ , Working Paper No. 223, Princeton University, 2002.

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# **APPENDIX A: Complete stage I and stage II questionnaires**

# **Stage I**

**Good morning/Good afternoon. My name is___________. We are doing a research to develop an academic study about the local living conditions. I would like to count on your cooperation to understand what is your level of satisfaction regarding such matter.**

|NAME|||
|---|---|---|
|HOME PHONE|COML|MOBILE PHONE<br>**SAMPLE**<br>**1 2 3**|
|FAMILY’S HEAD NAME||**LIST CODE**|
|ADDRESS|||

**PF1** – **GENDER** 1 Male            2  Female

**COMPLEXION** 1 White-Caucasian      2 African-Brazilian     3 Asian      4  African-Indian      5  Indian

**PF2** – How old are you?

## **(TAKE NOTE ON THE BOX AND FILL THE AGE GROUP)**

1. 18 to 24       2. 25 to 34        3. 35 to 44      4. 45 to 59       5. 60 – more

**P1.** Currently, do you work? **(IF YES)**

1 YES → **CONTINUE** 2 NO → **GO TO P.8**

**P2.** What is your main activity? **(THROUGH OF THE OCCUPATION, IDENTIFY THE BETTER SITUATION).**

**PEA (Active Economic Population)**

1 Wage Employee - Registered 2 Wage Employee - Unregistered 3 Public Servant 4 Regular Self-Professional (Pays Social Security ex: maid) 5 Self Professional (with college degree ex: lawyer) 6 Entrepreneur 7 Free-lancer 8 Internship (with salary) 9 Others **(TAKE NOTE)** _____________________

**P3** . What’s your main activity?

**P4** . Where do you work? **(READ UNTIL THE QUESTION MARK) (STIMULATED AND UNIQUE)**

1 at Home 2 Own Neighborhood 3 Another neighborhood 4 Another town

**P5** . How many hours do you work each day?

**TAKE NOTE THE TOTAL NUMBER OF HOURS**

**P6.** How many days per week? **(STIMULATED AND ONLY) (THE HIGHEST AVERAGE FREQUENCY)** 1 day         2 days        3 days       4 days    5 days    6 days    7 days (everyday)

21
**P7.** Do you just study / Are you a retired / Are you a housewife / Are you unemployed? **(IF UNEMPLOYED)** Are you looking for a job or not?

**NO PEA (Non-Active Economic Population) NO PEA**

11 Only housewife 12 Only retired 13 Only student 14 Other forms of income 15 Other **(TAKE NOTE)** 16 Unemployed (Don’t seeking for a job) – NO PEA 17 Unemployed (Seeking for a job) – PEA

# **P8.** Do you have any children? **(STIMULATED AND ONLY)**

1 Yes 2 No

**P9.** How many people, including yourself, live in your place? **(TAKE NOTE)**

TAKE NOTE **P10.** Are there any children/teenager helping in the familiar income? How many? (= UNDER 18 years old) TAKE 99 There are no children working **GO TO P.13** NOTE

**P11** . How many hours they work daily ?  IF THERE ARE MORE THAN ONE WORKING, PLEASE CHECK THE AVERAGE OF WORKED HOURS BETWEEN THEY ALL (PER DAY) - DON’T PROVIDE THE SUM

TAKE NOTE - QUANTITY OF WORKED HOURS

**P12** . How many days per week do minors work? (SPONTANEOUS AND UNIQUE) (THE HIGHEST AVERAGE FREQUENCY)

1 day 2 days 3 days 4 days 5 days 6 days 7 days (everyday)

**P13.** Do you have some other source of income? .... **(READ UNTIL THE QUESTION MARK)** 1)   Alimony             2) Pension                               3) Retirement                           4) Unemployment Insurance 5)  Any rent                            6) Donations                           7) Occasional jobs                   8) Social programs **OR** 98  Other? Which?________________________ **99 – NO ONE**

**P14.** Are you (or someone in your home) benefited by any Government social program?

1) Yes 2) No → **go to P18**

**P15.** Which social program benefits you (or someone in your home)? **READ THE ALTERNATIVES**

1 Bolsa família 2 Bolsa escola 3 Student pass 4 Unemployment pass 5 LOAS/BPC 6 Basket good 7 Housing Program 8 Medicines 9 Donations 10 PRONAF 11 PROGER 98 Other. Which?__________________

**P16.** What’s your marital status? **(SPONTANEOUS AND UNIQUE)**

1. Single                        2. Married                         3. Widowed                        4. Divorced

**P17.** About the house where you live, you think you are... **(READ UNTIL THE QUESTION MARK) (STIMULATED AND ONLY)**

1. Housewife / Head of family / mother / wife **(ONLY FOR WOMEN)**

2. Head of family / husband / father **(ONLY FOR MEN)** 3. Son / Daughter (older than 18 years old) **OR** 4. Other adults (18 or older)

**P18.** "Taken all together, how would you say things are these days - would you say that you are ... **READ UNTIL THE QUESTION MARK:**

1 Not too happy 2 Pretty Happy OR 3 Very happy ?

22
**P19.** On the whole, about the life that you lead, are you... **READ UNTIL THE QUESTION MARK:**

1 Not at all satisfied 2 Fairly Satisfied **OR** 3 Very satisfied?

# **LET’S TALK ABOUT YOUR HOME**

**P20.** How long do you and your family live here? **<u>(TAKE NOTE)</u>** Year Months

**P21.** Which the size of your property?

1 Until 20m<sup>2</sup> 2 More than 20 m<sup>2</sup> - 40m<sup>2</sup> 3 More than 40m<sup>2</sup> - 60m<sup>2</sup> 4 More than 60m<sup>2</sup> 5 Don’t know

**P22.** How many rooms have your place? **(TAKE NOTE)**

1 One 2 Two 3 Three 4 Four 5 Five 6 Six 7 Seven 8 Eight 9 Nine 10 Ten 98 Other TAKE NOTE ________

**P23** . Do you use your place only as home?

1 Yes → **GO TO PP.26** 2 No → **CONTINUE**

|**P24. What kind of trade/service there is in your home?**|**P25. How long are you doing that in your home?**|
|---|---|
|1. Bar|1. Less than 1 year|
|2. Mini-market|2. 1 to 3 years|
|3. Beauty and Cosmetics|3. More than 3 to 5 years|
|4. Homemade food and candies|4. More than 5 to 10 years|
|5. Mechanics and Auto-service|5. More than 10 to 15years|
|6. Deposit of recycle material|6. More than 15 years|
|7. Church|7. Don’t know|
|8. Other. Which one ?................................................||

**P26.** How did you acquire this residence? **( SHOW THE CARD AND READ IT)**

1. Bought the property from the Householders Association

2. Bought the property from other household and built the house 3. Bought an already built house 4. Occupied the property and built the house 5. The property was conceded **<u>definitely</u>** by the former owner 6. The property was inherited by a relative that passed away 7. Rent the house 8. The property was **<u>temporarily</u>** borrowed by the current owner **9. Was officially transferred by the local government/ Has received the land title from the local**

**officials**

9. Other. Which one TAKE NOTE

|96. Don’t know / Don’t remember|R$|
|---|---|
|**P276**.**(TO P26 = 1,2,3)**Could you tell me how much did you pay for this property?**(TAKE NOTE)**||
|**P26b. (TOP27# 7 and 8**Have you ever have rented this property to another household?**(TAKE NOTE)**||
|1 Yes How much? R$_______________________________________ 2 No<br>R$||

**P26c** . Do you know what is the market value of this property today? **(TAKE NOTE)**

23
**P27.** Could you tell me if during the last year have you purchased something by credit? **(SPONTANEOUS AND ONLY)** 1  Yes                    2 No **(GO TO P30)**

**P28.** What was the payment method chosen to make this purchase? ( **READ THE ALTERNATIVES) (STIMULATED AND MULTIPLE)**

1) Credit card 2) Debit card 3) Postdated check 4) Payroll credit 5) Installment payment slip 6) Store collection statement 7) Financing 8) Other **(TAKE NOTE)**

**P29.** Last year did you take any personal loan? **(SPONTANEOUS AND ONLY) 1  Yes**  **1** Bank/financing company/insurance **2** Family/Friends **3** Credit card **4 Other ____________        96 No**

**P30.** Have you delayed any payment of personal loan or purchase on credit? **(TO P.28=1 or P30 =1)** 1)  Yes                     2) No **(GO TO P 33)**

**P31. (TO P.27=1 or P29 =1)  (For those who delayed  payments last year)** How past due was/is the delay? **(READ THE ALTERNATIVES) (STIMULATED AND MULTIPLE)**

1) Less than 30 days 2) Between 31 to 60 days 3) Between 61 to 90 days 4) More than 90 days 5) More than 180 days

**P32.** Thinking about the payment methods which you use regularly, I would like to know which of them you use more frequently **: READ EACH ITEM_________**

# **P33. FOR EACH PAYMENT METHOD THAT YOU REGULARLY USE, I would like to know the level/degree that you**

**use between 1 and 5** **<mark>,</mark> 1 is the lowest and 5 the hi** **<mark>g</mark> hest** **<mark>(</mark> STIMULATED** **<mark>)</mark>**

||**Lowest use**||||**Highest use**|
|---|---|---|---|---|---|
|A) Check<br>1 Yes 2 No|1|2|3|4|5|
|B) Postdated check<br>1 Yes 2 No|1|2|3|4|5|
|C) Debit card<br>1 Yes 2 No|1|2|3|4|5|
|D) Credit card<br>1 Yes 2 No|1|2|3|4|5|
|E) Store card<br>1 Yes 2 No|1|2|3|4|5|
|F) Installment payment<br>li<br>1 Yes 2 No|1|2|3|4|5|
|sp<br>G) Cash<br>1 Yes 2 No|1|2|3|4|5|
|I) Others ?**(TAKE**<br>**NOTE)**|1|2|3|4|5|

**P34** Now, I will ask some questions about your home. Such information is required only for socioeconomic classification. Do you have in your house _____ (Ask to each item below)_ ? How many?

|**Items**|**Ther**<br>**e’s no**|**THERE IS**|**(QUANTITY)**|
|---|---|---|---|
|||**1**<br>**2**|3|
|Color TV|0|1<br>2|3|
|Videocassette/ DVD|0|2<br>2|2|
|Radios|0|1<br>2|3|
|Baths|0|4<br>5|6|
|Vehicles|0|4<br>7|9|
|Maid|0|3<br>4|4|
|Washing machines|0|2<br>2|2|
|Refrigerator|0|4<br>4|4|
|Freezer (*)|0|2<br>2|2|

_(*) independent or 2 doors on refrigerator_ 24
**P35.** Which level of education have the head of the family reached?

|**English**|**Points**<br>**Fill**|**Portuguese**|
|---|---|---|
|Illiterate/ Elementary school incomplete|0|Analfabeto/ até 3a Série<br>Fundamental|
|Elementary school completed/ middle school<br>incomplete|1|4a Série Fundamental|
|Middle school completed/ High school incomplete|2|Fundamental completo|
|High school completed/ College incomplete|4|Médio completo|
|College complete|8|Superior completo|

# **P36  (SHOW THE “INCOME CARD”)**

Now, I will read some income groups and I would like you tell me what group is your monthly familiar income included. I mean, the sum of income of all people living in your home, including you. Your monthly familiar income (last month) was? **(READ THE INCOME GROUPS) (STIMULATED AND ONLY)**

|**(SM = Minim**<br>|**um wage)**<br>||
|---|---|---|
|1|Until R$ 380,00|Until 1 SM|
|2|R$ 381,00 to R$ 760,00|More than 1 to 2<br>|
|3|R$ 761,00 to R$ 1140,00|~~SM~~<br>More than 2 to 3<br>|
|4|R$ 1141,00 to R$ 1.520,00|~~SM~~<br>More than 3 to 4<br>|
|5|R$ 1.521,00 to R$ 2.660,00|~~SM~~<br>More than 4 to 7<br>|
||||
|6|R$ 2.660,00 to R$ 4.560,00|More than 7 to 12<br>~~SM~~|
|7|R$ 4.560,00 to R$ 8.740,00|More than 12 to<br>~~23SM~~|
|8|More than R$ 8.741,00|More than 23 SM|

P37) Do you expect to receive any land title from the local officials or the Household Association during the next year?

1 Yes 2 No

**Thank you for the cooperation.**

25
# **Stage II**

**Good morning/Good afternoon. My name is___________. We are doing a research to develop an academic study about the local living conditions. I would like to count on your cooperation to understand what is your level of satisfaction regarding such matter.**

|NAME||
|---|---|
|HOME PHONE COML|MOBILE PHONE<br>**SAMPLE**<br>**1 2 3**|
|FAMILY’S HEAD NAME|**LIST CODE**|
|ADDRESS||

**PF1** – **GENDER** 1 Male            2  Female

**COMPLEXION** 1 White-Caucasian      2 African-Brazilian     3 Asian      4  African-Indian      5  Indian

**PF2** – How old are you?

## **(TAKE NOTE ON THE BOX AND FILL THE AGE GROUP)**

1. 18 to 24       2. 25 to 34        3. 35 to 44      4. 45 to 59       5. 60 – more

**P1.** Currently, do you work? **(IF YES)**

1 YES → **CONTINUE** 2 NO → **GO TO P.8**

**P2.** What is your main activity? **(THROUGH OF THE OCCUPATION, IDENTIFY THE BETTER SITUATION).**

**PEA (Active Economic Population)**

1 Wage Employee - Registered 2 Wage Employee - Unregistered 3 Public Servant 4 Regular Self-Professional (Pays Social Security ex: maid) 5 Self Professional (with college degree ex: lawyer) 6 Entrepreneur 7 Free-lancer 8 Internship (with salary) 9 Others **(TAKE NOTE)** _____________________

**P3** . What’s your main activity?

**P4** . Where do you work? **(READ UNTIL THE QUESTION MARK) (STIMULATED AND UNIQUE)**

1 At home 2 Own Neighborhood 3 Another neighborhood 4 Another town

**P5** . How many hours do you work each day?

**TAKE NOTE THE TOTAL NUMBER OF HOURS**

**P6.** How many days per week? **(STIMULATED AND ONLY) (THE HIGHEST AVERAGE FREQUENCY)** 1 day         2 days        3 days       4 days    5 days    6 days    7 days (everyday)

**P7** . These hours are greater, equal to or lower compared to one year ago? **(STIMULATED AND ONLY)**

> 1   Greater           2  Equal to          3  Lower

**P8.** Do you just study / Are you a retired / Are you a housewife / Are you unemployed? **(IF UNEMPLOYED)** Are you looking for a job or not?

**NO PEA (Non-Active Economic Population) NO PEA**

26
11 Only housewife 12 Only retired 13 Only student 14 Other forms of income 15 Other **(TAKE NOTE)** 16 Unemployed (Don’t seeking for a job) – NO PEA 17 Unemployed (Seeking for a job) – PEA

# **P9.** Do you have any children? **(STIMULATED AND ONLY)**

1 Yes 2 No

# **P10.** How many people, including yourself, live in your place? **(TAKE NOTE)**

|TAKE|
|---|
|NOTE|

**P11.** Are there any children/teenager helping in the familiar income? How many? (= UNDER 18 years old)

|TAKE<br>NOTE|99 There are no children working**GO TO P.15**|
|---|---|

**P12** . How many hours they work daily ?  IF THERE ARE MORE THAN ONE WORKING, PLEASE CHECK THE AVERAGE OF WORKED HOURS BETWEEN THEY ALL (PER DAY) - DON’T PROVIDE THE SUM

TAKE NOTE - QUANTITY OF WORKED HOURS

**P13** . How many days per week do minors work? (SPONTANEOUS AND UNIQUE) (THE HIGHEST AVERAGE FREQUENCY) 1 day         2 days        3 days       4 days    5 days    6 days    7 days  (everyday)

**P14** . The number of hours is greater, equal to or less than one year ago? (STIMULATED AND ONLY) 1   Greater           2  Equal to          3  Lower

**P15.** Do you have some other source of income? .... **(READ UNTIL THE QUESTION MARK)** 1)   Alimony 2) Pension                     3) Retirement               4) Unemployment Insurance              5)  Any rent

6) Donations 7) Occasional jobs 8) Social programs 98) Other? Which?___________________ **99 – NO ONE**

**P16.** Are you (or someone in your home) benefited by any Government social program?

1) Yes 2) No → **go to P18**

**P17.** Which social program benefits you (or someone in your home)? **READ THE ALTERNATIVES** 1  Bolsa família                 2  Bolsa escola           3  Student pass                        4  Unemployment pass 5  LOAS/BPC                    6  Basket good          7  Housing Program                8  Medicines 9  Donations                      10  PRONAF               11 PROGER                          98 Other. Which?__________________

# **P18.** What’s your marital status? **(SPONTANEOUS AND ONLY)**

1. Single                        2. Married                         3. Widowed                        4. Divorced

**P19.** About the house where you live, you think you are... **(READ UNTIL THE QUESTION MARK)**

# **(STIMULATED AND ONLY)**

5. Housewife / Head of family / mother / wife **(ONLY FOR WOMEN)** 6. Head of family / husband / father **(ONLY FOR MEN)** 7. Son / Daughter (older than 18 years old) **OR** 8. Other adults (18 or older) 27
**P20.** "Taken all together, how would you say things are these days - would you say that you are ... **READ UNTIL THE QUESTION MARK:**

1 Not too happy 2 Pretty Happy OR 3 Very happy ?

# **LET’S TALK ABOUT YOUR HOME**

**P21.** How long do you and your family live here? **(TAKE NOTE)**

|Year<br>Months|
|---|

# **P22.** Which the size of your property?

1 Until 20m<sup>2</sup> 2 More than 20 m<sup>2</sup> - 40m<sup>2</sup> 3 More than 40m<sup>2</sup> - 60m<sup>2</sup> 4 More than 60m<sup>2</sup> 5 Don’t know

# **P23.** How many rooms have your place? **(TAKE NOTE)**

1 One 2 Two 3 Three 4 Four 5 Five 6 Six 7 Seven 8 Eight 9 Nine 10 Ten 98 Others TAKE NOTE ________

**P24** . Do you use your place only as home?

1 Yes → **GO TO PP.27** 2 No → **CONTINUE**

|**P25. What kind of trade/service there is in your home?**|**P26. How long are you doing that in your home?**|
|---|---|
|1. Bar|1. Less than 1 year|
|2. Mini-market|2. 1 to 3 years|
|3. Beauty and Cosmetics|3. More than 3 to 5 years|
|4. Homemade food and candies|4. More than 5 to 10 years|
|5. Mechanics and Auto-service|5. More than 10 to 15years|
|6. Deposit of recycle material|6. More than 15 years|
|7. Church|7. Don’t know|
|8. Other. Which one ?................................................||

**P27.** How did you acquire this residence? **(SHOW THE CARD AND READ IT)**

1. Bought the property from the Householders Association

2. Bought the property from other household and built the house 3. Bought an already built house 4. Occupied the property and built the house 5. The property was conceded **<u>definitely</u>** by the former owner 6. The property was inherited by a relative that passed away 7. Rent the house 8. The property was **<u>temporarily</u>** borrowed by the current owner

**9.  Was  officially  transferred by  the local government/ Has received the land title from the local**

# **officials**

9. Other. Which one TAKE NOTE 96. Don’t know / Don’t remember

|R$|
|---|

**P27a** . **(TO P27 = 1,2,3)** Could you tell me how much did you pay for this property? **(TAKE NOTE)**

**P27b. (TOP27# DE 7 and 8** Have you ever have rented this property to another household? **(TAKE NOTE)** 1   Yes   How much? R$_______________________________________ R$ 2  No

- **P27c** . Do you know what is the market value of this property today? **(TAKE NOTE)**

28
**P28.** Could you tell me if during the last year have you purchased something by credit? **(SPONTANEOUS AND ONLY)** 1  Yes                    2 No **(GO TO P30)**

**P29.** What was the payment method chosen to make this purchase? ( **READ THE ALTERNATIVES) (STIMULATED AND MULTIPLE)**

1) Credit card 2) Debit card 3) Postdated check 4) Payroll credit

- 5) Installment payment slip             6) Store collection statement             7) Financing               8) Other **(TAKE NOTE)**

**P30.** Last year did you take any personal loan? **(SPONTANEOUS AND ONLY)**

**1  Yes**  **1** Bank/financing company/insurance **2** Family/Friends **3** Credit card **4 Other ____________             96 No**

**P31.** Have you delayed any payment of personal loan or purchase on credit? **(TO P.28=1 or P30 =1)**

1) Yes 2) No **(GO TO P 33)**

**P32. (TO P.28=1 or P30 =1)  (For those who delayed  payments last year)** How past due was/is the delay? **(READ THE ALTERNATIVES) (STIMULATED AND MULTIPLE)**

1) Less than 30 days 2) Between 31 to 60 days 3) Between 61 to 90 days 4) More than 90 days 5) More than 180 days

**P33.** Thinking about the payment methods which you use regularly, I would like to know which of them you use more frequently **: READ EACH ITEM_________**

# **P34. FOR EACH PAYMENT METHOD THAT YOU REGULARLY USE, I would like to know the level/degree that you**

**use between 1 and 5** **<mark>,</mark> 1 is the lowest and 5 the hi** **<mark>g</mark> hest** **<mark>(</mark> STIMULATED** **<mark>)</mark>**

|||**Lowest use**|||**Highest use**|
|---|---|---|---|---|---|
|A) Check|1 Yes 2 No|1|2|3<br>4|5|
|B) Postdated check|1 Yes 2 No|1|2|3<br>4|5|
|C) Debit card|1 Yes 2 No|1|2|3<br>4|5|
|D) Credit card|1 Yes 2 No|1|2|3<br>4|5|
|E) Store card|1 Yes 2 No|1|2|3<br>4|5|
|F) Installment payment<br>slip|1 Yes 2 No|1|2|3<br>4|5|
|<br>G) Cash|1 Yes 2 No|1|2|3<br>4|5|
|I) Others ?**(TAKE**<br>**NOTE)**||1|2|3<br>4|5|

**P35.** On the whole, about the life that you lead, are you... **READ UNTIL THE QUESTION MARK:**

1 Not at all satisfied 2 Fairly Satisfied **OR** 3 Very satisfied?

29
**P36** Now, I will ask some questions about your home. Such information is required only for socioeconomic classification.

Do you have in your house _____ (Ask to each item below)_ ? How many?

|**Items**|**Ther**<br>**’**|**THERE IS**|**(QUANTITY)**|
|---|---|---|---|
||**es no**|<br>||
|||**1**<br>**2**|3|
|Color TV|0|1<br>2|3|
|Videocassette/ DVD|0|2<br>2|2|
|Radios|0|1<br>2|3|
|Baths|0|4<br>5|6|
|Vehicles|0|4<br>7|9|
|Maid|0|3<br>4|4|
|Washing machines|0|2<br>2|2|
|Refrigerator|0|4<br>4|4|
|Freezer (*)|0|2<br>2|2|

_(*) independent or 2 doors on refrigerator_

**P37.** Which level of education have the head of the famil <mark>y</mark> reached?

|**English**|**Points**<br>**Fill**|**Portuguese**|
|---|---|---|
|Illiterate/ Elementary school incomplete|0|Analfabeto/ até 3a Série<br>Fundamental|
|Elementary school completed/ Middle<br>school incomplete|1|4a Série Fundamental|
|Middle school completed/ High school<br>incomplete|2|Fundamental completo|
|High school completed/ College incomplete|4|Médio completo|
|College complete|8|Superior completo|

P38 **(SHOW THE “INCOME CARD”)** Now, I will read some income groups and I would like you tell me what group is your monthly familiar income included. I mean, the sum of income of all people living in your home, including you. Your monthly familiar income (last month) was? **(READ THE INCOME GROUPS) (STIMULATED AND ONLY)**

|**(SM = Mi**<br>|**nimum wage)**<br>|||
|---|---|---|---|
|1|Until R$ 380,00||Until 1 SM|
|2|R$ 381,00 to R$ 760,00||More than 1 to 2|
|3|R$ 761,00 to R$ 1140,00|~~SM~~<br>|More than 2 to 3|
|4|R$ 1141,00 to R$ 1.520,00|~~SM~~<br>|More than 3 to 4|
|5|R$ 1.521,00 to R$ 2.660,00|~~SM~~<br>|More than 4 to 7|
|6|R$ 2.660,00 to R$ 4.560,00|~~SM~~<br>~~SM~~|More than 7 to 12|
|7|R$ 4.560,00 to R$ 8.740,00||More than 12 to|
|||||
|8|More than R$ 8.741,00||More than 23 SM|

**ONLY IF P27 = 9 - TO FINISH** , you told me you got **, last year, the land title from the local officials** . I would like you tell me how such event has changed your life. In a scale of 1 to 10, considering 1 as no effect at all, and 10 if your life is really better because of the land title

1 2 3 4 5 6 7 8 9 10 96 Don’t know

**Thank you for the cooperation.**

30