Baseline Study of Land Markets in and Around City’s Current and New International Airports

Report to the Lincoln Institute of Land Policy July 10, 2017

Paavo Monkkonen UCLA Luskin School of Public Affairs

Jorge Montejano Escamilla Felipe Gerardo Avila Jimenez Centro de Investigación en Geografía y Geomática

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Executive Summary

Government run urban mega-projects can have a transformative impact on local property and land markets, creating significant increases in the value of land through investment by the state. The construction of a New International Airport and the redevelopment of the existing International Airport will be one of the largest public infrastructure projects in in recent history. The potential impacts on the price of nearby land warrants consideration of a land value capture program. Regardless of the form this program takes, the city needs an accurate and well-justified baseline measure of the value of land and property proximate to the two airport sites.

This report contains three parts. The first is a review of relevant academic literature on property appraisals, the impacts of airports and mega-projects on land and property values, the role of value capture in infrastructure investment, and the methods and tools through which land value impacts can be estimated. This latter component of the literature review is especially important. Much of the data on land and property values in Mexico City are from appraisals and estimates rather than actual transaction records, and the methodology governments use to assess land values plays an important role in the credibility and political feasibility of efforts to recapture value increases.

The bulk of the report is a presentation, assessment, and analysis of available data on land and property values in Mexico City and the proximate municipalities of the . The market value of property is expressed infrequently – at the point of sale – and sales records are the best way to estimate average property values. In Mexico, however, there is no reliable, publically available record of sales prices. Nonetheless, we identify and acquire three sources of data on property values; official publically assessed values reported by local governments’ cadastre and Secretaries of Finance as part of the property tax system, a database of appraisals for new mortgages generated in part and managed by the Sociedad Hipotecaria Federal (SHF), and the sale and rental listings available on the internet and in newspapers.

The combination of three data sources on property values provides as comprehensive a picture as possible on land and property values in Mexico City. The values reported in the different sources vary. Values used by local government to calculate property taxes are a fraction of prices in listings of property for sale, and appraisals reported by the SHF are somewhere in between. There are some explanations for these discrepancies, based on our understanding of how the numbers are generated. Nonetheless, we also gathered data on neighborhood built environment attributes and jobs to assess the characteristics of the neighborhoods near the AICM and NAICM, and to provide a potential source of analytical check on value data.

The final section of the report is a summary of two additional analytical exercises. The first is two simple case studies of the price changes near recent major urban interventions in Mexico City; the CETRAM in Rosario and the Granadas urban upgrading project. We find that land values in these areas increased at a slightly higher rate than the average change for the city as a whole. The second is an overview of current real estate development activity in the central region of Mexico City starting near the current airport and extending into the more expensive core. From this analysis, we can learn a great deal about potential price impacts of the redevelopment of the existing airport. It also gives a valuable perspective on the price of property – construction costs among other things - and the ways in which we can evaluate the value of land.

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Table of Contents

1. Introduction: Land Value Capture and Mega-Projects

2. The Valuation of Land and the Impacts of Mega-Projects a. How much is urban land worth? b. Assessing the value of land for value capture c. Airports and property values

3. Data on Land and Property Value, and Study Area Characteristics a. Appraisal Data from the Sociedad Hipotecaria Federal b. Cadastral Data from Mexico City and the State of Mexico c. Publically Listed Prices for Property Sales d. Data on Built Environment, Socioeconomics, and Employment in Study Area

4. Analysis of Price Data and Assessment of Validity

5. Potential Impacts of Airport Transformation: Case Studies and Scenarios a. Property market impacts of the Granadas project and the CETRAM El Rosario b. Real estate projects in Mexico City c. Estimating a range of property market impacts

6. Conclusions

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1. Introduction: Land Value Capture and Mega-Projects

The Mexico City airport project has the potential to transform an entire district of the city. The scale of the public investment is such that it will inevitably impact the neighborhoods surrounding it – both the new and existing airport. If the city government is to capture some of the increase in land, it value needs an accurate and well-justified baseline measure of the value of land and property proximate to the two airport sites. Although there is no reliable, publically available record of sales prices, in this study we identify and summarize three sources of data on property values; those used in the property tax system, a database of appraisals for new mortgages, and advertised sales listings. In combination, these three sources of data provide an important perspective on the market price of property.

The neighborhoods around the site of the existing international airport of Mexico City (AICM) are somewhat above average in terms of neighborhood conditions and property prices for the Federal District of Mexico City. In an average Delegación of Mexico City, land was valued at 1,500 and 4,500 per square meter in 2014. Land in Venustiano Carranza – the location of the AICM – was valued by the government at 2,222 pesos per square meter in 2014, and 7,500 in property appraisals for mortgages. However, they are relatively close to the highest priced neighborhoods in the city, where land was valued at 4,500 and 10,000 pesos per square meter. Thus, though it depends on what is built at the site of the existing airport, it is likely that property in affected neighborhoods will gain value. According to one of our data sources, land within three kilometers of the AICM is assessed at 50 to 60 percent less on average than land in the same Delegation outside of this buffer. Thus there is great potential for dramatic change in the property market.

Land near new international airport of Mexico City (NAICM) is currently either undeveloped or developed at a low level of capital intensity, thus the transformation of these areas is almost guaranteed. In 2014, land was valued at about 700 pesos per square meter in the municipality of Texcoco by the government, and about 2,000 pesos in property appraisals for mortgages. Land in the area within three kilometers of the site of the NAICM was roughly half these values. Thus even if the neighborhood property values increased to those the municipality average, they would double, and if the municipality’s land value rose to that of an average neighborhood of Mexico City, it would also double.

Moreover, the NAICM as proposed is likely to have a greater positive impact on proximate neighborhoods than the old model of airport development. The new model of airport development does not emphasize industrial land or working class housing, rather, high-end housing and retail are often developed near new airports, and thus the nearby neighborhoods can become a destination not only for those traveling through. The academic study of the land market impacts of airports has traditionally focused on the negative impacts on property prices due to the noise planes make when landing and taking off, yet nature of the new kind of airport and real estate development proximate to them suggest it is time for revision in thinking about their relationship.

The map displayed in Figure 1 presents the majority of the core of the Mexico City urban region, with the Federal District at its center and extending well into the State of Mexico. The map displays the location of the existing and new International Airport of Mexico City, the boundaries of the

4 study area (a simple three kilometer buffer around the airports), as well as political (state and municipal) boundaries.

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Figure 1 also displays land values for the areas designated as homogenous by the property tax agencies of the government of Mexico City and the State of Mexico. The location of the existing International Airport, on the Mexico City side of the border between the Federal District and the State of Mexico, places it exactly on the edge of the most highly priced real estate in the city. Moving the airport to a new site to the northwest frees up this potentially highly valuable land and creates a new node of development, extending the potential for development into the State of Mexico. Most of the homogenous areas of Mexico City are grouped together in price in this map, but there is actually wide variation between them.1

There is a growing, positive consensus on the importance of value capture mechanisms for local governments engaged in mega-projects (Suzuki et al., 2015). There is no question that the construction – and removal or decommissioning – of airports represent mega-projects, and entail substantial public investment and attention. Best practices in computing and carrying out the capture of increased land values near these sites are fairly well established. It is extremely important than in a context of low planning credibility, these must be followed. As is clear from the controversy surrounding the inclusion of land value capture language in the constitution of Mexico City, the government must use a conservative, well-established practice.

Three guiding principles should shape the capture of land value. First, governments should conservatively identify price increases attributable to the investment itself, to avoid backlash and not cut into local government revenues from property taxes. Second, governments should levy fees or taxes on a large enough geographic area, to ensure fairness. Finally, and importantly, governments should levy fees or taxes periodically on all parcels - rather than on specific sites at the point of development – to minimize distortionary impacts. Charging for development rights or imposing linkage fees might be politically expedient way to exact value from property, both approaches reduces development activity, and unfairly leave those who do not develop their land to enjoy unearned profits.

The state of the art tools of land market analysis are not exceedingly complex, yet any effort is severely limited if the right data – microdata with property characteristics - are not available. As this report makes clear, we can estimate the “true value” of a property even if actual sales amounts are not recorded, but we will not know it definitely. In Mexico, there are three sources of data that get us close to an estimate of the market value. List prices, however, are not regularly collected thus an effort to do that – and to accurately record sales prices – would provide the government with a much more comprehensive understanding of the market. In lieu of this, if the microdata that are the basis of the averages reported by the Sociedad Hipotecaria Federal by postal code were released it would enable a better estimate of actual trends in land values.

1 Note: We could do many different kinds of maps depicting prices, but will wait for discussion over which would be most useful.

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2. The Valuation of Land and the Impacts of Mega-Projects

Urban planning and infrastructure interventions in cities benefit greatly from an understanding and analysis of land and property markets. Moreover, this analysis is essential if governments intend on capturing the increase in value in land associated with urban growth or infrastructure investment. The accuracy of government estimates is important, if a policy is to be sustainable.

How much is urban land worth?

There are two basic sets of challenges to assessing the value of urban land. The first are challenges that stem from the nature of property markets and apply to any kind of real estate analysis. The market value of a property is expressed infrequently, only at the point of sale. Unlike homogeneous goods like cars or pens, two properties are never identical thus any estimation of market value is inherently imprecise. More transactions and in markets with less heterogeneity of property makes it easier estimate values.

The second challenges are specific to land valuation. Data on the value of land in urban areas is primarily obtained indirectly. Most property transactions are of parcel that is already developed and the sale includes the land and structure. There are different techniques for disaggregating these two values, though all have challenges. Thus, land and property markets are studied together not only because the market for urban land is a core input to property development, but also because land values are mostly estimated indirectly using data on the sale of already built housing or commercial real estate.

Although improvements in information technology have led to more sophisticated spatial and statistical analysis of land and property markets in recent years, the basic tool for property market analysis remains the hedonic pricing model (Rosen, 1974). This model is a multivariate regression that models the sales price of property as a function of its most important attributes – size, physical condition, proximity to amenities and jobs, etc. – for as large a sample of properties as possible. Then, the price of an unsold property can be estimated by applying the coefficients generated for different attributes in the statistical model to the features of an actual property.

The statistical approach is a formal and more systematic version of a common approach to valuing properties used by appraisers, the “comparable sales” approach. This approach consists of finding properties similar to the one in question and making judgement calls as to the price difference implied by any differences in attributes.

There are two common ways to assess land values. The most straightforward would be to simply use data on vacant land sales, however, these data are difficult to come by as most urban land is already built on. The more common is to use data from all property and impute the value of the underlying land, known as the ‘residual’ approach. Both approaches present challenges.

Examples of the direct measurement of land sales in the United States include the geographically comprehensive study by Albouy and Ehrlich (2012), though they analyze values at the metropolitan level, which enables them to overcome the problem of few observations in some parts

6 of cities. An effort at the scale of sub-metropolitan unit is that of Kok, Monkkonen, and Quigley (2016), who use land sales records in the San Francisco Bay Area to assess the price impacts of regulatory stringency.

A more common method of estimating land value is to subtract an estimate of the value of a building from the sale price of a property. This is the ‘residual’ method. For example, if a house sells for $1 million and replacing the structure itself would cost an estimated $400,000 based on standard construction costs, then the land can be assumed to be worth $600,000. This is a more common method of land valuation, as data on sales of vacant land are generally hard to obtain. Davis and Palumbo (2008) use this residual method to generate estimates of land values across US metros. They find that land represented about half of housing costs in 2004, up from 32 percent in 1984. Case (2007) uses a similar method, but arrives at a much lower estimate (38 percent in 2005).

Assessing the value of land for value capture

Beyond the challenges of measuring land values, isolating the impacts of nearby investments on the value of land in a neighborhood land presents additional challenges. Most importantly, defining the ‘affected’ area well and isolating the effects of the investment itself on nearby land values beyond any price changes that would have occurred in its absence is difficult.

Questions about the timing of land price impacts are also relevant. The expectation of future changes after the announcement of a major project had long been demonstrated to affect prices (Damm et al., 1980), in fact, in some cases prices have even come down relatively after the completion of infrastructure projects. In a rigorous study of this phenomenon in Hong Kong, Yiu and Wong (2005) showed how the expectation of a new tunnel across the harbor changed real estate prices. In a different political environment, Torre and colleagues (2014) demonstrated how the impact of expectations about future urban investments is mitigated by the probability that proposed projects will come to fruition. As is expected, projects that are less likely to be completed due to controversy have a lower price impact.

The implementation of Tax Increment Financing (TIF) by local governments in the United States gives an important lesson for the practice of estimating land value capture increments. TIF is a common tool of local governments to recapture some of the cost of public investments pioneered in California, but now made illegal there – in part because of a poorly justified methodology. Local governments designate a TIF area of influence around redevelopment projects. Then, they shift all property tax revenues from the increase in the assessed value of properties in that zone into a redevelopment fund.

Figure 2 presents the most common way to estimate the size of contributions in a TIF zone on the left, and an alternative model on the right. This alternative model incorporates the reasonable assumption that urban property increases in value over time, and does not attribute all value increases to government investment nearby. Determining the exact slope of this ‘inflation adjusted increment’ will be a challenge and surely contested by property owners as it is essentially a counterfactual without a control group.

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A major lesson from the TIF experience in California is that governments should not assume that all increases in property values in a certain area are from a specific investment. Not only does this overstate the impact of public investment, it makes the government vulnerable to credibility challenges. It is difficult to isolate the impact of a nearby development on property values in a causal manner in the best data environment, and it is almost never the case that other changes in an urban area would not impact land and property values.

Thus, the more conservative approach to assessing what tax increments from a nearby area are eligible for recapture depicted on the right hand side of Figure 2 is more justifiable and retains credibility on the part of the government. Instead of assuming that all of the increase in property value is attributable to the nearby investment, the assumption is that the property would have increased in value at the city’s average rate.

Airports and property values

Residential property near airports has traditionally hypothesized to be less valuable, because airports are noisy. This is especially the case along the flight path of arriving and departing airplanes, and for airports that operate at night. Noise, measured in decibels (dB), typically ranges from about 65 to 80 dB in close proximity to airports. In urban areas generally, noise levels are about 50-60 dB during the day and 40 dB during the night (Nelson, 2004). Partly because of this lower level of noise at night, flights many airports have a curfew on flights.

Dozens of empirical studies – of increasingly high statistical quality and broad coverage of cases - have attempted to isolate the impact of airport noise on property prices. For example, a sophisticated study of one of the world's busiest airports, Chicago O'Hare, found that home values were roughly nine percent lower within the 65 dB noise contour band in 1997 (McMillen, 2004). A broad meta-analysis by Nelson (2004) examines the effect size – i.e. the percentage depreciation per decibel increase in airport noise – found in over 20 hedonic property value studies of over 30 airports in Canada and the United States. He finds that properties for every dB increase in noise, properties suffer a 0.5-0.6 percent price reduction. Thus, there is a 10 percent price difference between a house located in an area with daytime noise of 55dB and an otherwise identical one in area with 75dB of noise, typical of neighborhoods close to airports.

Research design and modeling strategy matter in this empirical endeavor. As Pennington and colleagues (1990) point out, unsophisticated models will overstate the impact of airport noise because of omitted neighborhood variables – neighborhoods near airports are different from others in many ways. Ironically, though they raise doubts about the universality of deleterious impacts of proximity to airports on the prices of residential properties, they also open the possibility of large effects of airports in some contexts. Moreover, the vast majority of studies, as well as recent work that controls for spatial and apartment heterogeneity and often omitted variables, find similar impacts as the meta-analysis mentioned above. On average, apartment rents drop by about 0.5% per decibel of airport noise though noise effects are not constant over the entire range of noise (Boes and Nüesch, 2011)

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Yet this theme of the empirical research relevant to the present study is that many aspects of the noise-property price relationship– such as housing type - do not have a systematic relationship across countries (Nelson, 2004). Simply put, context matters. Moreover, as Mcmillen (2004) argues, because aircraft are becoming less noisy, airports might be expanded and operating hours increased without a meaningful decrease property values nearby. In fact, as Knippenberger (2010) points out, airports are currently undergoing a transition in many places, from simple infrastructural nodes, to multifunctional real estate development locations. Property located near the new Airport Cities (Güller and Güller, 2001) of the 21st century might well be much more valuable, in spite of the noise.

Notably, in reviewing literature on property prices and airport noise, we could not find any hedonic price studies in countries outside of Europe, Australia, the United States, or Canada, with most of them are from the latter two. The property price impacts of being near an airport are likely to be different in Mexico, though in which direction is uncertain a priori. On the one hand, regulations on noise, the timing of flights, and the rules governing development on flight paths land might be more permissive to airlines in Mexico. On the other hand, the price sensitivity to noise might be lower in urban contexts with more ambient noise. Nonetheless, there is good grounds to expect a negative impact due to proximity to the airport.

3. Data on Land and Property Value, and Study Area Characteristics

Housing and other kinds of real estate are heterogeneous goods. Every property is unique in some ways therefore price discovery is challenging. Asking prices can often differ significantly from final sales prices, which are taken as the true market value by most analysts. Unfortunately, final sales prices are often not recorded in many countries, in order to avoid taxes. In fact, access to data on sales remains a limit to an understanding of how markets function in most cities.

In many contexts, data must be gathered through surveys. The standard approach to surveying land brokers is outlined by Dowall in the 1995 Land Market Assessment (LMA), and its update in 2010. Though there have been improvements in the surveying of informal land markets (Development Workshop, 2011; Napier, 2007), the core approach is similar. Brokers and other kinds of real estate agents, who have knowledge of a market are asked to appraise different kinds of hypothetical properties in different neighborhoods. Several experts are surveyed for overlapping neighborhoods and the median estimate is often taken as more reliable. Recently, the use of satellite imagery has also been employed in the categorization of housing stock and incorporation of transportation infrastructure and urban growth in LMAs (Bertaud, 2008).

Fortunately, Mexico has several reliable sources of data to draw on and we did not resort to surveying agents. We have obtained and processed three kinds of data – estimates of value by local governments, average appraisals for mortgage lending, and list prices for sales – on land and property values from four core sources. Table 1 below identifies the source, content and coverage of four databases. The following sections describe them one by one, including processing we have conducted and other relevant features of the dataset.

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The fact that the study area includes land in two jurisdictions - the Federal District and the State of Mexico - presented a minor challenge in terms of data collection. Most states or municipalities collect data in different formats, and this case is no exception. Thus, although we obtained cadastral data for both areas, they are created and reported in differently in both jurisdictions. Fortunately, the appraisal database is consistent in all places, thus can be used in combination with the cadastral data to get a more accurate and complete measure of land values.

In the end, these four sources of data can be narrowed to two sets of variables. The first is official land value for property tax purposes, official structure value for property tax purposes (in Mexico City only), and average land and structure values from appraisals. The second set of variables are currently listed sales prices of different types of residential property, gathered from the internet and from field calls. Table 2 reports values for these variables across the study area and the entire CDMX.

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The study area – the three kilometer buffer around the two airport sites – appears as a somewhat average part of the city in terms of the official appraisals of the property market, but one with less expensive properties advertised for sale. Land values are slightly higher than average according to cadastral data, though construction values are quite similar in that same dataset. Properties are quite average in the appraisal data – higher median values but lower mean values. Properties listed for sale online or in street signs are significantly lower in the study area according to the list price dataset, though coverage of this dataset is biased upward because

The more outstanding aspect of Table 2 is the significant discrepancy in price per square from the three sources of data. Land and structure values in the data from Sociedad Hipotecaria Federal (SHF) are more than twice as high on average as compared to official values reported in the cadastral data. This might be seen as surprising given both numbers are from professional appraisers. Yet the probable explanation is twofold. On the one hand, there is a common assertion that property is undervalued in cadastres because homeowners seek to lower their tax burden by underreporting purchase prices. On the other hand, appraisals in the SHF data are not necessarily representative. They are appraisals made for houses being purchased with mortgage loans, thus more likely to be newer units and units with formal legal status, which will bias their value upwards.

More dramatically, the prices per square meter listed in sales advertisements are many multiples of the valuations by both groups of appraisers. These list prices do not disaggregate land from structure as the other two sources of data do, which is one major reason they are higher. Nonetheless, even adding together land and structure values per square meter the other sources of data would suggest average prices are about 3,000 pesos per square meter in the cadastral data and something above 6,000 in the appraisal data from SHF. As with the comparison of SHF data and official values reported in the cadaster, properties advertised online will likely be the higher-priced properties in a given neighborhood. Moreover, it is quite possible that sellers advertise their

10 properties at a higher price than they expect to sell them. Nevertheless, the difference is remarkable.

As per the Financial Code of the State of Mexico and the Fiscal Code of Mexico City, property values for taxation purposes are determined using unit values of land and structure for each different homogenous area of the city, and separate classes of property.

The data presented in Table 2 also mask substantial variation across political jurisdictions. Table 3 reports average values of the two official data sources for the major political jurisdictions of the region; the Delegations of Mexico City and the Municipalities of the State of Mexico. These are averages of aggregations of the base geography of the data to that of the political jurisdictions. As is described in detail described below, official cadastral values are reported in roughly 180 large geographic areas and appraisal are reported in over 2,000 postal codes.

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The wide variation corresponding to a classic monocentric urban structure with land in centrally located jurisdictions valued at more than ten times that of land in outlying municipalities of the State of Mexico. Indeed, within Delegations/Municipalities there is also dramatic variation in value. For example, appraisals in the least expensive postal code of the Alvaro Obregon Delegation of Mexico City value land at 1,700 pesos per square meter in 2014, whereas in the most expensive postal code land it is 50,000. The following subsections describe these sources of data in detail.

Appraisal Data from the Sociedad Hipotecaria Federal

The first source of land and property value data is appraisals. The Sociedad Hipothecaria Federal (SHF) is a housing finance agency of the federal government, originally created to supervise a secondary mortgage market in whose mission is to find housing finance solutions in Mexico. It is one of the federal government agencies that actively generates and aggregates data, and undertakes research including the State of Mexico’s Housing annual reports. SHF has developed a housing price index based on a rich database of individual appraisals. Every mortgage issued in the country requires an appraisal and these are reported by the internal Unidades de Valuación and publically available.

Property appraisers (peritos valuadores) in Mexico are trained in and governed by guidelines about methodologies for estimating land values. The National Banking Commission on Values published a norm2 and the Secretary of Public Education has guidelines for courses for appraisers that together established three valuation methods. The first is based on estimates of construction costs for a given property, the second based on comparable recent sales, and the third is an income capitalization method based on the present value of future rents. Nonetheless, it is unclear at this point whether there is an official guideline followed by all appraisers.

The rich appraisal database contains many variables, including average prices for housing (separated by land and structure) disaggregated for different types of housing stock (detached

2 Available online at: www.cnbv.gob.mx/Paginas/NORMATIVIDAD.aspx (last accessed May 19th, 2017).

11 single family, multifamily, etc.) and classes of housing (residential being the most expensive, middle, and social interest). These data are also available at different geographic scales. The smallest area is postal code. The GIS layer for postal code boundaries is not available from the SHF, so we obtained it from the Secretaría de Comunicaciones y Transportes (SCT) and the Correos de México.

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Figure 3 shows the boundaries of postal codes, focusing on the area surrounding the AICM and the NAICM. It also presents a buffered study area of three kilometers. There are roughly 181 postal codes, which are roughly one square kilometer on average, in this study area.

Appraisal data from SHF are available by year from the year 2004. Importantly, for each postal code, the number of appraisals that were used to obtain the average price per year is reported by SHF. This is important because in some years, some postal codes have seen few mortgages issued and thus few appraisals conducted. In these cases, the triangulation with other data is especially important for greater statistical validity.

This data forms one of the core components for the study, as it covers and is consistent across both Mexico City and the State of Mexico, and contains disaggregated and reliable measures of average values for land and structures for many years (we focus on 2014 to match the cadastral data), as well as an indicator of the validity of these averages (the number of appraisals). Table 3 (above) reports averages by of appraisal data by Delegacion/Municipio from 2014.

Cadastral Data from Mexico City and the State of Mexico

The second data source for land and property values is from the municipal cadaster and the Secretary of Finance. We obtained data on official values for land and construction for the State of Mexico and Mexico City separately, and we have merged them in what are fairly consistent geographic areas.

For the state of Mexico, data came from the Instituto de Información e Investigación Geográfica, Estadística y Catastral del Estado de Mexico (IEGECEM), Dirección de Catastro, through official channels (see letter in Appendix A). They aggregate data on land values from all the municipalities of the state. The IGECEM released digital archives of in the dwg (Autodesk) format, with data reported for spatial units they refer to as Areas Homogeneas (AH). The AH are bigger than the postal codes (on average 1.7 square kilometers) and have associated data for land and property values, land use information, and socioeconomic classification.

These data were obtained in various formats and some processing was required to create the database that is compatible with that of the SHF and census data (e.g. converting the dwg file to shp file). This processing is complete for the AH of the municipalities of Ecatepec, Atenco, Nezahualcóyotl, Texcoco, Chimalhuacán, and . IGECEM data cover the years 2010-2017 for the majority of land, but in some areas (including the location of the NAICM itself and some

12 surrounding lands) data was only available for the year 2017. Nonetheless, these most recent numbers will be useful.

The Mexico City cadaster data are rich. From the Secretaría de Finanzas del Gobierno, we obtained the parcel map of the cadaster for the years 2010 and 2013. In addition, from the Código Fiscal del Distrito Federal 2014 we obtained the official land and property (construction) values for the year 2014. These latter values are actually published in the government gazette (Diario Oficial) and we manually inputted these numbers. By combining these data, we have created an impressive database of land use, type, extent and class of construction for over a million parcels. Although there are over a million parcels, most variables do not vary within blocks, and additionally many do not vary within ‘zones’, similar to the ‘Homogenous Areas’ used by the municipalities in the State of Mexico. Most importantly, per square meter land and property values are the same within zones according to the government, thus these will be the operative geographic unit for much of our purposes.

The precise methodologies used by the State of Mexico and Mexico City for determining the boundaries of homogenous zones is somewhat unclear, though the general approach is stated on page 344 of the Código Fiscal del Distrito Federal, as a “Group of blocks with similar characteristics in infrastructure, urban equipment, types of buildings and real estate dynamics.” The document does not specify the exact definitions of these features.

The precise method of land and structure valuation is also described in the official documentation (the Código Fiscal del Distrito Federal). Article 129 states “Said unit values will respond to the market price of land and structures in the Federal District.” Later (page 368), the Fiscal Code mentions a technical manual that contains the details of appraisal process (the Manual de Procedimientos y Lineamientos Técnicos de Valuación Inmobiliaria). We were unable to gain access this manual at this time.

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Figure 4 shows the boundaries of the Areas Homogeneas that match cadastre data from the State of Mexico as well as the census blocks that match the cadastre data from Mexico City. As noted, the small blocks in Mexico City are grouped into zones for the purposes of land and property valuation. These zones are actually several times larger than the Areas Homogeneas, though they vary dramatically in size. Thus, while 94 Areas Homogeneas are in the study area, only 23 zones in the Mexico City cadastre are. Table 3 (above) reports averages cadastral data by Delegacion/Municipio from 2014.

Publicly Listed Prices for Property Sales

The last source of data on property prices are prices asked by those selling properties. Almost 800 data points of prices and rents for property in the study area were gathered manually from two sources; the internet (real estate websites segundamano.mx, vivanuncios.com.mx, lamiduli.com.mx, metroscubicos.com, inmuebles24.com, silovendes.mx, tuportalonline.com, and casas.trovit.com) and from calling sellers through signs posted on buildings (the research team

13 used Google street view to obtain phone numbers). Data were collected in the following categories: vacant parcels, offices, commercial space, house, and apartments. They have been aggregated to postal code, and serve as an additional input into the triangulation of average values for these units.

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Table 4 presents averages of these list price data for the Delegations of the City of Mexico and some municipalities of the State of Mexico. As discussed previously they are much higher than the values estimated by appraisals managed by the SHF or by local governments for property tax purposes. This is not only due to the fact that these data are much more recent (2017 vs 2014). The difference in the average values of different types of property is striking. On average, apartments are the most expensive property class and detached homes the least expensive. This is likely due to the fact that they are newer than detached homes, and more likely to be formally built on speculation by developers. The majority of new residential development in expensive neighborhoods is in apartment buildings, in response to greater demand for certain locations.

A second noteworthy feature of these data is that values across Delegations correlate strongly (Spearman correlation coefficient above 0.85) across the three main types of property. Further, although values listed as sale prices are much higher than appraised values, the correlation with those reported in the SHF data is also strong (0.66), suggesting the data are relatively consistent.

Data on Built Environment, Socioeconomic, and Employment Attributes of Study Area

We also use two datasets to characterize the neighborhoods of the study area and to assess the validity and support our estimates of land and property values. The first is the 2010 census of population and housing from INEGI, focusing on socioeconomic, housing and infrastructure characteristics of neighborhoods. The second is the Directorio Estadístico Nacional de Unidades Económicos (DENUE), which contains geographically detailed data on the location and nature of firms in Mexico. We use these data to assess the heterogeneity of neighborhoods in the study area and the rest of the city, the validity of the appraisal and cadaster data, and to estimate some measure of economic activity by Postal Code as a further check on the validity of our land value data.

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Figure 5 shows the census tract boundaries within the study area. Roughly 400 of them are in the study area. As with the postal codes, census tracts are not drawn for the entire study area. INEGI only draws census tracts for populated land, and a significant portion of the land surrounding the NAICM is not populated. In addition, we include data on relevant public transportation infrastructure (metro, trolleybus, and major roads) and some land use categories from the Mexico City government (not pictured in Figure 5).

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Table 5 presents a comparison of the built environment and employment characteristics of the study area compared to the rest of the Mexico City Metropolitan area. The study area is

14 surprisingly average. In fact, for two of the variables we assessed – people per house and the share of the population with basic education or less - the average values are identical. As befits its relatively central location, the study area has a higher population density, lower housing vacant rate, more small houses, and greater access to infrastructure. A greater share of the population does not have access to health care services, though more households have computers/internet access. There are many more jobs located in this part of the city than in the average postal code, and more of those jobs are in services rather than manufacturing.

4. Analysis of Price Data and Assessment of Validity

With the goal of establishing baseline values for land and property, our analysis follows three steps. The first is to carefully assess the different sources of value data to generate the most accurate measure possible. In order to do this, we need a consistent geography to be able to compare the information contained in the three different measures of property value. We aggregate the different datasets to a consistent set of geographic boundaries. Postal Codes are the best base layer of geographic data. They are drawn consistently for the entire metropolitan region, and they are of a medium size compared to census tracts or cadaster zones.

We are proportionally allocating the cadaster data to the postal codes. Proportional allocation is the process by which one first calculates what percent of a certain polygon lies within the base polygon (in this case postal codes), then weights the attribute data (in this case land and property value) by that percentage, and finally sums the weighted attributes of all polygons that lie within the base polygon.

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Figure 6 shows an example of how proportional allocation works. On the left, we see the boundaries of AH in grey, with two identified as AH1 and AH2. On the right, we have overlaid the postal codes in red, and identified one of them as A. Exactly half of postal code A lies in AH1 and half in AH2, therefore we would assign a value from the AH data that is 50% of AH1 and 50% of AH2. As is clear in this description, proportionally allocating data from parts of polygons assumes that there is a homogeneity in the variable being allocated within that polygon, which is generally not the case.

5. Potential Impacts: Case Studies and Scenarios

Property market impacts of the Granadas project and the CETRAM El Rosario

Projecting the impacts of mega-projects is extremely difficult to do with precision. We examined the possibility of price impacts due to the changes in land use in the AICM and the construction of the NAICM based on the evidence from the literature as well as the analysis of two recent major infrastructure projects in Mexico City; the urban transformation in the Granadas neighborhood of the delegation of Miguel Hidalgo (the most expensive part of the city), and the Multi-modal

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Transfer Center (CETRAM) in the Rosario neighborhood, located in the Delegation of Azcapozalco, a part of the city more comparable to the location of the AICM.

The Granadas area, also known as due to its proximity to that neighborhood, was once a neighborhood of warehouses and factories. In the early 2000s, its transformation to high-end housing, commercial, office, and cultural land uses - including two major museums - began. The change in this neighborhood has been noteworthy, and complaints of excessive development led to a Master Plan in 2013 to regulate the neighborhood’s transformation. There have been reports of dramatic increases in office rents, which in 2014 were ten times higher than they were when leasing began in 2005 (Valle, 2014), but no conclusive analysis.

The construction of the CETRAM Rosario, which is a multi-modal transit center located at the end of a metro line, began in 2011. It includes commercial spaces, a hospital, hotel parking and spaces for cultural and sporting activities. Its name is derived from the proximity to one of the largest housing developments by INFONAVIT dating back to 1972, El Rosario, which by the year 2000 had been decried in the press as a ‘no man’s land’ due to crime and disinvestment in the area. Thus, the CETRAM project, which is noteworthy as a public-private partnership that channeled private investment into the area, represented a major urban upgrading effort.

We examine changes in the land values adjacent to both of these areas, using the data on property appraisals from the Sociedad Hipotecaria Federal to assess whether there had been relatively greater changes compared to the city at large. We gathered data on land values from 2005 to 2015, anticipating that both have increased greatly. Also, that the Granadas experienced had a much greater increase than the CETRAM, given the high end nature of much of the real estate development in the zone.

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Figure 7 shows trends in the nominal, appraised price of land per square meter for all Mexico City postal codes, and separately for the postal codes adjacent to the CETRAM Rosario and Granadas neighborhood in the years 2005-2015. Clearly, the land near Granadas is much higher value than that near the CETRAM Rosario, nearly two times as high, and the land near the CETRAM Rosario is almost exactly the same value on average as the city as a whole. More importantly perhaps, is there is no dramatic difference between trends in appraisal values in these different groups of postal codes. Land values increased in these areas, but only by a small degree more than did land values across the entire city.

For example, land in El Rosario was lower than average between 2005 and 2007, jumped to average in 2008 and has increased in value steadily with the city’s overall increase since then. Prices in Granadas jumped dramatically after 2013, when the master plan was adopted. The relative assessed price of land was 1.6 times that of the city’s average when the urban transformation began in 2005-2006, and 1.8 times higher in the more recent period 2014-2015.

This suggestive evidence is not a firm conclusion, however, because the nature of these land value data. They are derived from appraisals of properties obtaining mortgages. Thus, they are the average land values of the properties that were appraised in a given year, and different kinds

16 of property might be appraised in one year than another. For example, better located parcels could have been appraised in 2006 than in 2005, leading to an apparent increase in prices not due to market trends but the mix of property being sold. Ideally, price indexes are either quality controlled using a regression to control for the bias of the characteristics of property sold in a given year, or based on repeat sales, which track the change in price of the same property sold at multiple points of time. In this case, neither of these techniques are possible because the SHF does not release microdata of their appraisals, it only reports averages.

Real Estate Development in Mexico City and Potential in Study Area

In considering possible impacts of the two airport projects, we also sought to assess the potential impacts on real estate development. Again, standard caveats about projections are necessary, but some an overview of the types of real estate projects currently underway in the neighborhood proximate to the AICM, compared to those being built in higher priced-neighborhoods nearby, are useful in framing the potential changes in the study area.

Through informal conversations with several developers and the careful evaluation of recently completed and pre-sale buildings advertised online, we selected six to eight recent or ongoing residential projects from four Delegations of Mexico City: Venustiano Carranza, Cuauhtemoc, Miguel Hidalgo and Benito Juárez. Venustiano Carranza is the location of the existing airport and gives us the base type of development. The other three are the delegations moving eastward in direction and upwards in price. Table 6 reports the average estimates of property and land value from three different sources described previously in these four parts of the city.

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We evaluate projects in these different districts according to their construction costs, estimates of land costs, and profit margins to gain further insight into potential changes in the nature of real estate development projects near the AICM. Table 7 presents a core component of this analysis, semi-official estimates of construction costs for new residential buildings in Mexico City, published by the Instituto Mexicano de Ingenieria de Costos. The construction costs in this table also gives a useful perspective on the discrepancy between appraisal values for properties reported by the SHF and listed sales prices we gathered.

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The longer description of analysis of residential projects is presented as Appendix C. For each project, we estimate total revenues and costs for developers, and extrapolate profit margins. Below, we summarize the nature of new residential projects in the four delegations. Clearly, projects in Venustiano Carranza sell for less. Units are smaller. Also, estimated profit margins are lower than in the other Delegations, roughly on average 50% as compared to about 70% in other areas. The following paragraphs summarize the four Delegations

Delegación Venustiano Carranza: The general characteristics of recently built apartments for sale in this part of Mexico City are buildings of four to seven stories, with construction categorized as

17 middle-class quality. Projects are built on parcels anywhere from 300 square meters to 6,000, with a similarly wide range of units per project. Units are more similar in size and cost, about 60 square meters on average with a price between one and two million pesos

Delegación Cuauhtemoc: The general characteristics of recently built apartments for sale in the Cuauhtemoc Delegation of Mexico City are buildings of four stories and higher, with construction in the middle-class, semi-luxury and luxury categories. Projects are mostly large, upwards of 50 units, on parcels anywhere from 400 to 1,200 square meters. Units are generally 90 square meters and larger, with a price between four and six million pesos.

Delegación Miguel Hidalgo: The general characteristics of recently built apartments for sale in the Miguel Hidalgo of Mexico City are buildings of three stories and up, again with construction in the middle-class, semi-luxury and luxury categories. Projects range widely in size, from two dozen units to four hundred in one instance. Units are generally large, from about 70 square meters to almost 200 in several cases. Prices for units are as low as three million pesos in some buildings but several are over 10 million pesos.

Delegación Benito Juarez: The general characteristics of recently built apartments for sale in the Benito Juarez Delegation of Mexico City are surprisingly of a lower average price and size than some of the more expensive buildings in Miguel Hidalgo, Despite the fact that it is on average the most expensive part of the city. Buildings are of four stories and higher, with construction in the middle-class and semi-luxury categories. Projects are mostly smaller, with 20 to 40 units, though there are some large projects with 500 plus units. Units range from 60 to 150 square meters, and are priced between two and six million pesos.

6. Conclusion: What we know and how confident we can be

The International Airport of Mexico City (AICM) sits at the edge of the Federal District, at the edge of a continuous gradient of land and property prices proximate to the most expensive real estate in the region. According to average values of property appraisals by private agents and the government, land within three kilometers of the AICM is between 50 and 60 percent less valuable on average than land in the same Delegation outside of this buffer. The difference in the zone of the NAICM compared to its municipality and the larger region is even greater. There is potential for dramatic change in both property markets.

This study attempts to outline an accurate and well-justified baseline measure of the value of land and property proximate to the two airport sites. Acknowledging the limitations imposed by the lack of reliable sales price records, we identify and summarize the next best thing. Three sources of data on property values. The first is public data on the value of land and structure published by the government of Mexico City and the State of Mexico for the purposes of calculating the property tax base. The second is a large database of appraisals for mortgages, published by the Sociedad Hipotecaria Federal. The final is advertised sales listings from the internet and the field. In combination, these three sources of data provide an important perspective on the market price of property. Moreover, we combine these data sources with an analysis of real estate development projects to generate a more complete picture of potential changes.

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The transformation of the existing airport and the construction of a new airport are both expected have transformative effects on proximate real estate. The way in which government might capture some of this increase in land value, however, must be carefully considered. Perceptions of the purpose of this value recapture, i.e. where will revenues be invested, as well as the way in which it would be implemented, are important for the political legitimacy of the enterprise. The need for legitimacy was made clear by the vague mention of land value capture in a draft constitution of Mexico City and the outcry that followed. In California, the source of the land value recapture strategy Tax Increment Financing, the courts eventually outlawed this method because of its clearly questionable methodological justification. Thus, any method for recapturing land value must convincingly isolate the increment in land value generated by the public investment, and the way in which funds gathered will be used should be clearly spelled out.

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Tables

Table 1. Source, Content, and Coverage of Core Databases on Land and Property Value

Geographic Temporal Source Description Key variables Coverage coverage Sociedad Hipotecaria Appraisal data Value of land Mexico City & 2011-2015 Federal (SHF) for all sales and structure State of Mexico Secretaría de Finanzas Municipal Value of land Mexico City 2014 del Gobierno de Ciudad cadastre data and structure de México y Código Fiscal del Distrito Federal

Instituto de Información Municipal Value of land State of Mexico 2010-2017 e Investigación cadastre data and structure Geográfica, Estadística y Catastral del Estado de México (IGECEM)

Online and field Current sales Asking price for Mexico City & 2017 data land and State of Mexico property

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Table 2. Average Land and Structure Values from Various Sources, 2014*

Mexico City Region Study Area (3km buffer) Variable Mean Median Mean Median

Land Value per m2 from 1,147 988 1,244 1,198 Local Government

Structure Value per m2 1,795 1,682 1,691 1,559 from Local Government**

Land Value per m2 from 3,627 2,365 3,632 2,914 appraisals

Structure Value per m2 3,724 4,087 3,408 3,791 from appraisals

List price* per m2 of 23,157 20,701 16,332 15,027 apartments for sale** Source: Authors with data from the Instituto de Información e Investigación Geográfica, Estadística y Catastral del Estado de México, Código Fiscal del Distrito Federal, Socidad Hipotecaria Federal, and the following online sources: segundamano.mx, vivanuncios.com.mx, lamiduli.com.mx, metroscubicos.com, inmuebles24.com, silovendes.mx, tuportalonline.com, and casas.trovit.com, and from calling sellers with signs posted on buildings.

Notes: * All values are 2014 except for list prices are from 2017. ** Structure value only available for Federal District of Mexico City.

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Table 3. Averages Prices by Delegacion/Municipio of the 2014 Cadastral and SHF Data

Cadastre 2014 SHF 2014 Average Federal Average Land Average Construction Delegation/Municipality Entity Value Land Value Value DF 1842 7711 6722 Coyoacan DF 2653 9786 6080 de DF 1751 4663 8955 Gustavo A. Madero DF 1498 6553 5032 DF 1938 6967 6111 DF 1257 5635 4688 La DF 1498 4224 6386 DF 350 4078 5916 Alvaro Obregon DF 1853 6578 6994 Tlahuac DF 863 3552 4548 DF 1571 6735 6708 DF 1034 3323 4224 Benito Juarez DF 4014 12173 9141 Cuauhtemoc DF 4113 10822 6635 Miguel Hidalgo DF 4780 10262 8170 Venustiano Carranza DF 2222 7595 5172 Acolman Mexico 221 1435 4738 Atenco Mexico 378 1108 4112 Coacalco de Berriozabal Mexico 1657 2484 4257 Chalco Mexico 394 1518 4237 Chicoloapan Mexico 150 2170 4200 Chimalhuacan Mexico 1488 1976 3743 Mexico 1183 2697 4000 Huixquilucan Mexico 1680 5337 9073 Juchitepec Mexico 134 732 3580 de Juarez Mexico 4544 4664 4770 Nezahualcoyotl Mexico 1540 4034 3577 La Paz Mexico 1490 2420 4145 Teotihuacan Mexico 32 1204 5011 Tepetlaoxtoc Mexico 255 907 4000 Texcoco Mexico 689 1974 4588 Mexico 266 465 2571 Mexico 902 4239 4197 Solidaridad Mexico 769 2002 3601 Source: Authors with data from Instituto de Información e Investigación Geográfica, Estadística y Catastral del Estado de México, Código Fiscal del Distrito Federal, Socidad Hipotecaria Federal.

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Table 4. Average List Price per square meter by Delegacion/Municipio, 2017

Detached Delegation house Condominium Apartment Vacant lot* Alvaro Obregón, DF 24,271 26,108 28,668 10,480 Azcapotzalco, DF 13,326 15,830 17,519 15,011 Benito Juárez, DF 40,750 54,364 29,612 139,833 Coyoacán, DF 19,706 23,533 23,347 22,716 Cuajimalpa, DF 25,691 26,371 35,727 28,866 Cuauhtémoc, DF 21,584 19,050 23,282 47,876 Gustavo A. Madero, DF 13,372 15,093 15,694 11,823 Iztacalco, DF 13,463 12,339 17,759 29,167 Iztapalapa, DF 10,552 12,799 11,763 4,754 Magdalena Contreras, DF 16,699 20,994 26,443 7,515 Miguel Hidalgo, DF 34,446 37,930 38,117 21,359 Tlalpan, DF 17,705 19,635 23,218 7,158 Tláhuac, DF 8,783 12,576 10,858 9,000 Venustiano Carranza, DF 11,546 12,313 16,384 55,357 Xochimilco, DF 13,902 17,848 15,979 6,513 Acolman, Mexico 7557 6484 6233 Chalco, Mexico 7191 7323 7122 Chicoloapan, Mexico 7741 5863 850 Ecatepec, Mexico 8358 8023 22981 Huixquilucan, Mexico 23386 22844 27767 Naucalpan, Mexico 16543 17846 19881 4435 Nezahualcoyotl, Mexico 8667 8781 12256 La Paz, Mexico 9740 8132 6234 2086 Tlalnepantla, Mexico 12797 13047 15426 11689

Notes: All available data was gathered during March and April of 2017. * In some jurisdictions there were very few listings for vacant lots only, thus there is small sample size bias.

Source: The following online sources: segundamano.mx, vivanuncios.com.mx, lamiduli.com.mx, metroscubicos.com, inmuebles24.com, silovendes.mx, tuportalonline.com, and casas.trovit.com, and from calling sellers with signs posted on buildings.

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Table 5. Characteristics of Study Area and the Rest of , 2010

Study Area Rest of MCM Variable Mean Median Mean Median Pop. Density (000s per km) 54 17 41 8 People per House 3.9 3.9 3.9 3.9 Share pop basic educ. or less 24 25 24 25 Share no health care 38 37 36 34 Share hsg. Vacant 9 9 11 10 Share houses small (< 3 rooms) 28 29 31 31 Share w basic infrastructure 97 99 95 98 Share w/o computer/internet 56 58 53 56 Share jobs manufacturing 10 9 14 10 Share jobs services 47 45 44 43 Jobs per person 2.4 0.2 0.9 0.2

Source: Authors with data from the 2010 Censo de Poblacion y Hogares and DENUE.

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Table 6. Average Property and Land Value per square meter in Four Delegations

Appraisal Land Value Appraisal Structure Avg. List in Cadastre Land Value Value SHF Delegation Price psm psm SHF psm psm

Venustiano Carranza 16,384 2222 7595 5172 Cuauhtemoc 23,282 4113 10822 6635 Miguel Hidalgo 37,930 4780 10262 8170 Benito Juarez 54,364 4014 12173 9141

Source: Authors with data from Instituto de Información e Investigación Geográfica, Estadística y Catastral del Estado de México, Código Fiscal del Distrito Federal, Socidad Hipotecaria Federal, and the following online sources: segundamano.mx, vivanuncios.com.mx, lamiduli.com.mx, metroscubicos.com, inmuebles24.com, silovendes.mx, tuportalonline.com, and casas.trovit.com.

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Table 7. Construction Costs for New Residential Buildings in Mexico City

Cost Type of building (pesos per square meter)

Mid-rise luxury housing $13,120

Mid-rise semi-luxury housing $11,928

Mid-rise middle-class housing $9,059

Mid-rise social interest housing $6,189

Source: Instituto Mexicano de Ingenieria de Costos, 2014.

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Figures

Figure 1. CDMX Region with Airports, State and Municipal Boundaries

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2A. Common TIF Model 2B More Realistic Model

Figure 2. Tax Increment Financing Models of Land Value Recapture

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Figure 3. Two Airports and study area over Postal Codes

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Figure 4. Two Airports and study area over Cadastral Data from CDMX and EdoMex

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Figure 5. Two Airports and study area over census tracts

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1 A

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Figure 6. Proportional allocation example: Homogenous Areas to Postal Codes

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18000

16000

14000

12000

10000

8000 LandValue

6000

4000 Pesosper square meter(nominal)

2000

0 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Year

Las Granadas El Rosario All Mexico City

Figure 7. Average land price for postal codes near Rosario and Las Granadas and CDMX

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Appendix A. Datasets a) SHF Dataset: Land and Structure Values by Postal Code 2011-2015 b) Cadastral Data from Mexico City and State of Mexico 2014 by Homogenous Area c) Census and DENUE data by AGEB c) Proportionally allocated Census and Cadastral data by Postal Code

Appendix B. Relevant Official Documents a) Código Financiero del Estado de México b) Diario Oficial del Estado de México c) Ponencia del IGECEM d) Código Fiscal del Distrito Federal e) Explainer on Property Tax Calculation from the Secretaría de Finanzas del Distrito Federal

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Appendix C. Current Real Estate Development Context of Four Delegations of Mexico City In this appendix, we report summary details of six recently completed or ongoing projects in four Mexico City Delegations: Venustiano Carranza, Cuauhtemoc, Miguel Hidalgo and Benito Juárez. We report project addresses and include a picture. The focus is on the costs and revenues, howver, and we present the total and per square meter sale price of units to estimate the total revenue from the sale of all units, and compare to calculations of investment - both construction costs and land costs - in order to estimate and percentage profit margin.

Project Details Delegation Venustiano Carranza 1. Del. Venustiano Carranza/ Col. Magdalena Mixhuca

Total price of an apartment: $2.3 million pesos Price per square foot: Total sale price of building: $106.7 million pesos

Construction cost (28% indirect): $9,059 /m2 Average land cost in the area: $2,670 /m2 Total investment: $39.7 million pesos

Profit margin: 63%

2. Del. Venustiano Carranza/ Col. Moctezuma

Total price of an apartment: $1.3 million pesos Price per square foot: Total sale price of building: $168.9 million pesos

Construction cost (28% indirect): $9.059 /m2 Average land cost in the area: $2,670 /m2 Total investment: $85.2 million pesos

Profit margin: 50%

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3. Del. Venustiano Carranza/ Col. Ampliacón Aviación

Total price of an apartment: $1.1 million pesos Price per square foot: Total sale price of building: $105.9 million pesos Construction cost (28% indirect): $9.059 /m2 Average land cost in the area: $2,670 /m2 Total investment: $56.5 million pesos Profit margin: 47%

4. Del. Venustiano Carranza/ Col. 20 de Noviembre

Total price of an apartment: $1.1 million pesos Price per square meter: $18,519/m2 Total sale price of building: $391.5 million pesos Construction cost (28% indirect): $9,059 /m2 Average land cost in the area: $2,670 /m2 Total investment: $207.6 million pesos Profit margin: 47%

5. Del. Venustiano Carranza/ Col. Lorenzo Boturini

Total price of an apartment: $ million pesos Price per square meter: $27,228/m2 Total sale price of building: $33.7 million pesos Construction cost (28% indirect): $9,059 /m2 Average land cost in the area: $2,670 /m2 Total investment: $15.7 million pesos

Profit margin: 53%

6. Del. Venustiano Carranza/ Col. Moctezuma 1ª Sec.

Total price of an apartment: $1.6 million pesos Price per square meter: $27,119/m2 Total sale price of building: $23.1 million pesos

Construction cost (28% indirect): $9,059 /m2 Average land cost in the area: $2,670 /m2 Total investment: $8.3 million pesos Profit margin: 64%

Project Details Delegation Cuauhtemoc 1. Del. Cuauhtémoc/ Colima 0, Col. Roma Norte

Total price of an apartment: $6.9 million pesos Price per square meter: $48,582/m2 Total sale price of building: $41.1 million pesos Construction cost (28% indirect): $11,928 /m2 Average land cost in the area: $8,900 /m2 Total investment: $15.1 million pesos

Profit margin: 63%

2. Del. Cuauhtémoc/Pedro Moreno 216, Col. Buena Vista

Total price of an apartment: $1.3 million pesos Price per square meter: $24,615/m2 Total sale price of building: $34.2 million pesos

Construction cost (28% indirect): $9,059 /m2 Average land cost in the area: $4,450 /m2 Total investment: $20 million pesos

Profit margin: 41%

3. Del. Cuauhtémoc/ 150, Col. Juárez

Total price of an apartment: $5.2 million pesos Price per square meter: $85,110/m2 Total sale price of building: $2,160 million pesos

Construction cost (28% indirect): $13,119/m2 Average land cost in the area: $26,700/m2 Total investment: $403 million pesos

Profit margin: 81%

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4. Del. Cuauhtémoc/Tehuantepec 209, Col. Roma Sur

Total price of an apartment: $7.6 million pesos Price per square meter: $64,024/m2 Total sale price of building: $213 million pesos

Construction cost (28% indirect): $13,119/m2 Average land cost in the area: $8,900/m2 Total investment: $52 million pesos

Profit margin: 76%

5. Del. Cuauhtémoc/ Río Nilo 6 Col. Cuauhtémoc

Total price of an apartment: $4.7 million pesos Price per square meter: $56,707/m2 Total sale price of building: $148 million pesos

Construction cost (28% indirect): $13,119 /m2 Average land cost in the area: $8,900 /m2 Total investment: $42 million pesos

Profit margin: 72%

6. Del. Cuauhtémoc/ Chicontepec 57, Col.

Total price of an apartment: $5.9 million pesos Price per square meter: $70,072/m2 Total sale price of building: $708 million pesos

Construction cost (28% indirect): $13,928/m2 Average land cost in the area: $14,240/m2 Total investment: $164 million pesos

Profit margin: 76%

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Project Details Delegation Miguel Hidalgo 1. Del. Miguel Hgo./ Mártires de la Conquista, Col. Escandón

Total price of an apartment: $4.4 million pesos Price per square meter: $55,133/m2 Total sale price of building: $72.3 million pesos

Construction cost (28% indirect): $11,928/m2 Average land cost in the area: $8,010/m2 Total investment: $21.2 million pesos

Profit margin: 71%

2. Del. Miguel Hgo./Ejercito Nal.225, Col. Verónica Anzures

Total price of an apartment: $5 million pesos Price per square meter: $61,573/m2 Total sale price of building: $1,421 million pesos

Construction cost (28% indirect): $11,928 /m2 Average land cost in the area: $12,460 /m2 Total investment: $338 million pesos

Profit margin: 78%

3. Del. Miguel Hgo./Blas Pascal 222, Col. Polanco I

Total price of an apartment: $14.5 million pesos Price per square meter: $96,667/m2 Total sale price of building: $1,372 million pesos

Construction cost (28% indirect): $13,119 /m2 Average land cost in the area: $17,800 /m2 Total investment: $252 million pesos

Profit margin: 82%

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4. Del. Miguel Hgo./Calz. M. Tacuba 1501, Col. Argentina Pte.

Total price of an apartment: $2.8 million pesos Price per square meter: $50,909/m2 Total sale price of building: $408 million pesos

Construction cost (28% indirect): $9,059 /m2 Average land cost in the area: $6,230 /m2 Total investment: $315 million pesos

Profit margin: 23%

5. Del. Miguel Hgo./Suderman 235, Col. Morales

Total price of an apartment: $17 million pesos Price per square meter: $102,410/m2 Total sale price of building: $ 408 million pesos

Construction cost (28% indirect): $13,119 /m2 Average land cost in the area: $14,240 /m2 Total investment: $88 million pesos

Profit margin: 78%

6. Del. Miguel Hgo./Arquímedes 138, Col. Polanco

Total price of an apartment: $11.6 million pesos Price per square meter: $77,180/m2 Total sale price of building: $752 million pesos

Construction cost (28% indirect): $13,119/m2 Average land cost in the area: $17,800/m2 Total investment: $84 million pesos

Profit margin: 89%

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Project Details Delegation Benito Juarez

1. Monte Alban 13, Col. Vertiz Narvarte Total price of an apartment: $3.5 million pesos Price per square meter: $36,839/m2 Total sale price of building: $74.4 million pesos

Construction cost (28% indirect): $9,059/m2 Average land cost in the area: $8,010/m2 Total investment: $29.1 million pesos

Profit margin: 61%

2. Del. Benito Juárez/Romero 114, Col. Narvarte Total price of an apartment: $1.9 million pesos Price per square meter: $32,000/m2 Total sale price of building: $318 million pesos

Construction cost (28% indirect): $9,059/m2 Average land cost in the area: $8,010/m2 Total investment: $52.7 million pesos

Profit margin: 83%

3. Del. Benito Juárez/Xochicalco 408, Col. Narvarte Total price of an apartment: $4.6 million pesos Price per square meter: $39,396/m2 Total sale price of building: $187.5 million pesos

Construction cost (28% indirect): $11,928/m2 Average land cost in the area: $8,010 /m2 Total investment: $74.7 million pesos

Profit margin: 60%

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4. Del. Benito Juárez/Alabama 42, Col. Nápoles

Total price of an apartment: $6.6 million pesos Price per square meter: $54,526/m2 Total sale price of building: $532 million pesos

Construction cost (28% indirect): $11,928 /m2 Average land cost in the area: $8,900 /m2 Total investment: $74.7 million pesos

Profit margin: 71%

5. Del. Benito Juárez/S. Simón 160, Col. S. Simón Ticumac

Total price of an apartment: $2.4 million pesos Price per square meter: $56,707/m2 Total sale price of building: $63.9 million pesos

Construction cost (28% indirect): $9,059 /m2 Average land cost in the area: $6,230 /m2 Total investment: $23.1 million pesos

Profit margin: 64%

6. Del. Benito Juárez/Emiliano Zapata 167. Col. Portales Nte. Total price of an apartment: $2.9 million pesos Price per square meter: $34,819/m2 Total sale price of building: $1,514 million pesos

Construction cost (28% indirect): $9,059 /m2 Average land cost in the area: $4,450 /m2 Total investment: $40.4 million pesos

Profit margin: 98%

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