Limitations

This is one of the first data analyses at the parcel level conducted for land development impacts of BRT systems in Latin America. However, despite the large number of observations (Bogota: 98,176 per year, and Quito: 13,551 per year) included in the data analyses and its longitudinal structure (panel data in Bogota for 2000, 2004, 2009 and 2013, and longitudinal data in Quito for the dependent variable and population density) a study of impacts contains several challenges. The first challenge is the implementation of a quasi-experiment study by taking

171

parcels selected for the treatment effect (BRT) and taking as controls those parcels that have not received this treatment yet (Bogota: parcels along “Av 68” and “Av Boyaca”, Quito: future “Corredor Suroccidental”). In the case of Bogota, “Av 68” and “Av Boyaca” as two main arterial roads that have not been subject to become bus rapid transit corridors to date, make them the best control corridors for the purposes of this study. Nevertheless, the other arterial roads “Av Caracas”, “Autonorte” and “Av Calle 80” were selected for BRT first based on a non-random reason. This aspect is further developed in the analysis of the semi-structured interviews in the qualitative data analysis (chapter 5). In the case of Quito, to find a control corridor is even more challenging because all bus rapid transit corridors are already under operation. This dissertation took “Corridor Suroccidental” considering that it is the most recent corridor under operation, thus, leaving a time window that could allow seeing changes on built-up area over time.

Furthermore, to find comparable parcels constitutes a challenge itself. The propensity score analysis conducted in this dissertation overcame this challenge by estimating the

probability of receiving treatment between parcels located in trunk corridors of this mass transit system and parcels located along two main arterial roads that still nowadays, in the case of Bogota, have not been subject to treatment (transit investments). It is still unclear if both main arterial roads will become BRT trunk corridors in the future. The current new administration of Bogota is determined to construct a BRT corridor along “Av Boyaca”, while “Av 68” has been subject of debate about being subject of a light-rail transit (LRT) system vs a BRT system.

Although the data analysis is estimating the treatment effects for the years 2004, 2009 and 2013, another limitation of this dissertation is that the analysis is looking at changes for only these three years after the base line (2000). A more robust analysis is recommended by including data for the years in between and beyond in order to conduct a more comprehensive data analysis

172

with the same parcels with a larger longitudinal data base. Another limitation is that the base line data in Bogota (2000) was collected in 1999 when the BRT was under construction. In the case of Quito, the base line data (2001) is one year prior the operation of “Ecovia” (2002). There was no data availability in Bogota before the year 2000 at this level of detail (panel data yearly at the parcel level) as well as there was not availability of parcel data in Quito from 1990s. A limitation of the built-up variable in Quito is the missing pre-existing data. The built-up area variable for the data analysis in Quito was constructed based on the year of construction data provided by the City Planning Department. Thus, the built-up area data before the year of construction is missing, adding a limitation to the analysis. Data availability has been a big challenge not only for this dissertation but also a limitation in conducting studies at this level of detail in Latin America, which is clearly reflected in the absence of these types of studies in the literature.

Another limitation of this study constitutes the exclusion of parcels that did not have data for some of the covariates or dependent variables. The observations included in the analysis are only those that have parcels with data for all dependent variables and covariates in Bogota (four years) and Quito (dependent variables). The data set in both cities could be capturing anticipated effects, if any, of the BRT system on land development. However, this could be the case for land prices and property values data, while the development and even more the redevelopment of parcels take much more time to change than land prices or property values, this limitation is not the same as in the case of a study looking at prices data.

There could be a potential bias in the time dummy variables included in the difference in difference models. This study seeks to address this limitation by providing data over time in order to see trends in time a window that expands 14 years in Bogota and at least one decade in

173

Quito. Another limitation with the time dummy variables in a difference-in-difference model is serial correlation which is addressed with placebo tests (Bertrand, Duflo, & Mullainathan, 2001). However, the data available for Bogota and Quito does not allow conducting placebo tests with pre intervention data several years before the intervention of the BRT corridors. In the case of Bogota, it was not possible to access data before the year 2000. In the case of Quito, given the dollarization of the economy in 2000, the data analysis focuses on the period of time in which the economy had the US dollar as its official currency. This data availability issue also implies the limitation of measuring anticipatory effects. The literature on BRT is limited on this regard but one study found no anticipatory effects on land prices with the announcement of a BRT corridor in Mexico DF (Flores Dewey, 2012). Another limitation is the interference issue of the results. The treatment and control parcels are part of the same real estate market within both cities so that there might be some interference of the real estate market in the comparison between both

groups (Cervero & Landis, 1997).

Given that this data sets are based on secondary data provided by the City Planning Department and the Cadaster Departments of Bogota and Quito, this study does not have control on the data collection and potential measurement errors in variables such as built-up area and land uses. However, this study conducted a careful calculation of multiple variables using GIS such distances, areas and ratios that seek to address any measurement errors the data sets may have. This study also seeks to address the limitation of external validity by conducting the data analysis in two cities located in two different countries and then comparing the results. In this way, findings such as the similarities in terms of built-up areas increasing within the same distance ranges from current and future stations (100m to 500m) in both cities points towards external validity. In the same manner, differences in both cities in terms of distances to CBD

174

points to external validity in relation to how local characteristics plays a crucial role on the relationship between land development and mass transit.

Finally, another limitation of this study is the buffer area. In the literature different catchment areas have been used in order to test the effects of mass transit systems on the built environment. Given the intersection of some of the treatment and control corridors used in this study, the buffer area of 500 meters at both sides of the corridor (1km in total) was determined as the most convenient area of analysis for this study in both cities in order to avoid additional overlaps. However, this study seeks to address this limitation by including distances to current and future BRT stations beyond 500 meters as it was explained before. Future studies could include 1km buffer areas in order to determine the extent by which the impact of transit investments on development and land use change could take place at longer distances than the ones used in this study.