1.3. Revisión histórica de la figura empresarial 19
1.3.4. Escuelas modernas del pensamiento en emprendimiento 32
Previous research has found that although in many cases busways have provided significant improvements in corridor capacity, the impacts of these facilities on the nearby land value have been minor. A case in Canada (Mullins, et. al., 1990) suggests that highly patronized busway systems that incorporate a substantial amount of
permanent fixed facilities may have a significant influence on land use. The prior expectations of this study about the significant influence that busways may have on land use/value were grounded in the new concept for delivering bus service that is
revolutionizing transit systems around the world, particularly in Latin America. These new BRT or busway systems feature intensive infrastructure facilities and their effects in terms of accessibility and mobility have been impressive.
Based on this previous premise, this study examined the impact of busway transit service upon residential properties available and advertised for rent in Bogotá. The study uses structural residential properties and neighborhood attributes to evaluate the beneficial impacts arising from increased local and regional accessibility and the deleterious impacts arising from proximity to the busway right-of-way. Overall, the study finds strong evidence that accessibility benefits of busways are capitalized into residential property rental prices. The capitalization effects of local accessibility suggests that properties located 0.1 km closer or more accessible to a busway station exhibit premiums
between 2.4 and 3.7 percent in the advertised rental price, all else held equal. Said differently, a one percent increase in distance to the closest busway station is associated with property monthly rental price premiums that range between 21.7 percent and 31.2 percent. Given the empirical housing rent-land value relationship, these results suggest that property rental prices are a theoretical representation of the land value for housing services.
The data also were able to discriminate between the benefits of access to a busway station from the nuisance effects such as proximity to the right-of-way. Properties located 0.1 km closer to the busway right-of-way exhibit a discount between 4.1 and 7.0 percent in the advertised rental price. Evaluated at the mean advertised rental price and distance to the busway right-of-way, the estimated effect translates into an elasticity of between 0.24 and 0.44.
To the degree that the results from this study can be generalized, this is the first empirical study that consistently provides evidence regarding the nature and magnitude of
accessibility and proximity-related impacts of busways or BRT. Such evidence has a wide range of practical applications, from determining the usefulness of innovative land- based tax instruments that hinge on the capitalization of positive busway effects, to informing policy makers about the land development consequences of transportation infrastructure alternatives.
By determining the capitalization of positive busway effects, the localized evidence from this study provides tools for exploring the usefulness of innovative land-based tax
instruments. These results are expected to inform local transportation planners and policy makers about the potential of public funding tools for transit infrastructure, such as value capture. In addition to being a potential source of revenue to help pay off the debt on transit investments, value capture stands also to pay for upfront and ancillary
neighborhood improvements that can help leverage transit-oriented developments
(Cervero and Duncan, 2002). Value capture represents an alternative approach of capital cost recovery that has not been fully explored and examined in the tax policy context. Using a land-based tax on properties that directly benefit from positive busway effects satisfies the virtues of sound taxation theory14, in addition to being economically neutral15.
Only few studies have asked if public transit could be financed itself from a combination of fare revenue and the increase in the nearby property values. For example, in a report to the Congress in January 2001 it was noted that after $9.5 billion in expenditures, Washington, DC’s Metro had generated between $10 and $15 billion in new land value (Smith, 2001). However, this estimate of land value is not based on the specific positive impacts of the Metro system. Using a methodologically more accurate approach
(hedonic price models), Batt (2001) found that while a nine-mile stretch of the New York
14 These virtues include a policy that is stable, simple, administrable, progressive, and most of all, efficient
(Batt, 2001; Rosen, 1999; Wolf, 1998).
15 It imposes no distortions on economic choices because land, particularly strategically located land, is
state Interstate Highway System (I-87) cost $128 million, the additional land value within two miles of the road that has been generated by its construction has totaled $3.7 billion. Other researchers have recommended that funding the construction of transit can also come from new development along transit lines by co-development of land in a
public/private partnership, which is less politically risky than taxing land (Smith, 2001). For example, in Tokyo, private co-development of transit and real estate projects has shown profitable results by internal cross-subsidizing practices among the companies’ businesses (e.g., locating retail near transit).
The extent to which positive effects of Bogotá’s busway system are capitalized into property values provides a promising approach for public institutions to fund busways and general transit infrastructure. With extensions planned over the next 13 years, when a 388-kilometer (241 miles) busway network will be completed in Bogotá using almost $2 billion of scarce public funds, issues related to both its beneficial and deleterious impacts may become of growing concern to both the affected public and to transit planners. When completed, 85 percent of the population will be located in a 500-meter busway influence area where positive and negative impacts are expected to influence property values. Moreover, the empirical evidence provided in this study is expected to help the local planning process debate about potential threats to property values and to determine compensation to affected parties.
Table 9 – OLS Hedonic Models of Property Rent Asking Price (local and regional measures of accessibility)
N=494 Linear Semi-log Double-log
Coefficients Std. Error Beta Coefficients
Std. Error Beta Coefficients Std. Error Beta
ULAREAL 0.004*** 0.001 0.452 0.005*** 0.000 0.402 0.361*** 0.052 0.355 ULAREA_d -0.127*** 0.047 -0.084 -0.137*** 0.050 -0.068 -0.170*** 0.051 -0.084 BEDS -0.002 0.023 -0.007 0.034** 0.017 0.077 0.062 0.049 0.059 BATHS 0.026 0.029 0.048 0.095*** 0.026 0.134 0.179*** 0.044 0.142 LROOM 0.318*** 0.113 0.193 0.094 0.067 0.043 0.274*** 0.062 0.126 AGE 0.046** 0.019 0.062 0.084*** 0.026 0.085 0.081*** 0.026 0.081 AGE_d -0.135*** 0.042 -0.076 -0.142** 0.059 -0.061 -0.169*** 0.060 -0.072 STRATUM 0.101*** 0.024 0.225 0.124*** 0.025 0.208 0.149*** 0.023 0.250 POP_DENSL -0.004** 0.002 -0.072 -0.006** 0.003 -0.087 -0.052 0.042 -0.046 EMP12_DENSL -0.008*** 0.003 -0.094 -0.015*** 0.004 -0.131 -0.018 0.017 -0.044 EMP3_DENSL 0.001 0.001 0.059 0.001 0.001 0.045 0.024 0.019 0.053 COMER_% 0.006 0.005 0.065 0.007** 0.003 0.061 0.004 0.004 0.039 RESID_% 0.005 0.006 0.048 -0.003 0.004 -0.021 -0.001 0.004 -0.007 INST_% -0.003* 0.002 -0.052 -0.004** 0.002 -0.063 -0.003* 0.002 -0.044 POVER_% -0.004 0.005 -0.026 -0.010 0.006 -0.042 -0.009 0.007 -0.040 ROB_RESL -0.421** 0.188 -0.073 -0.804*** 0.267 -0.106 -0.152*** 0.052 -0.114 ROB_PERL 0.066*** 0.014 0.180 0.133*** 0.018 0.277 0.368*** 0.048 0.384 HOMICIDESL -0.033 0.036 -0.045 -0.143*** 0.054 -0.148 -0.148*** 0.038 -0.211 BUSWAY -0.021 0.067 -0.018 -0.033 0.083 -0.022 -0.012 0.046 -0.008 LOCAL_ACCL -0.122** 0.061 -0.149 -0.207** 0.087 -0.192 0.024 0.051 0.030 REG_ACCL -0.002 0.015 -0.010 0.013 0.021 0.039 -0.005 0.090 -0.002 DIST_CBDL 0.000 0.007 0.004 -0.015 0.011 -0.094 0.002 0.012 0.008 DIST_DTL 0.004 0.010 0.035 -0.008 0.014 -0.051 0.015* 0.009 0.070 DIST_BUSWL 0.178*** 0.069 0.186 0.301*** 0.101 0.239 0.026 0.034 0.048 DATA -0.023 0.019 -0.029 -0.001 0.026 -0.001 0.002 0.027 0.002 Constant -0.211 0.210 -1.820*** 0.225 . -3.618*** 0.305 . Goodness of fit: Adjusted R2 0.691 0.729 0.720
***, **, and * denote coefficient significantly different from zero at the 1%, 5%, and 10% level of significance (two-tail test), respectively. LLogarithmic transformed variables for the Double-log model.
Table 10 – OLS Hedonic Models of Property Rent Asking Price (combined measure of accessibility)
N=494 Linear Semi-log Double-log
Coefficients Std. Error Beta Coefficients
Std. Error Beta Coefficients Std. Error Beta
ULAREAL 0.004*** 0.000 0.454 0.005*** 0.000 0.403 0.363*** 0.052 0.356 ULAREA_d -0.127*** 0.040 -0.083 -0.137*** 0.050 -0.068 -0.170*** 0.050 -0.084 BEDS -0.001 0.014 -0.004 0.037** 0.017 0.082 0.062 0.049 0.059 BATHS 0.023 0.021 0.043 0.091*** 0.026 0.128 0.179*** 0.044 0.143 LROOM 0.315*** 0.054 0.191 0.091 0.067 0.042 0.271*** 0.062 0.125 AGE 0.046** 0.021 0.061 0.083*** 0.026 0.083 0.081*** 0.026 0.081 AGE_d -0.136*** 0.048 -0.077 -0.145** 0.059 -0.062 -0.169*** 0.060 -0.072 STRATUM 0.102*** 0.020 0.227 0.126*** 0.025 0.212 0.149*** 0.022 0.251 POP_DENSL -0.004* 0.002 -0.075 -0.006** 0.003 -0.090 -0.053 0.041 -0.046 EMP12_DENSL -0.008** 0.003 -0.091 -0.014*** 0.004 -0.120 -0.020 0.016 -0.047 EMP3_DENSL 0.001 0.001 0.059 0.001 0.001 0.043 0.024 0.019 0.053 COMER_% 0.005* 0.003 0.061 0.007** 0.003 0.060 0.004 0.004 0.038 RESID_% 0.004 0.003 0.046 -0.003 0.004 -0.022 -0.001 0.004 -0.005 INST_% -0.003** 0.002 -0.055 -0.005** 0.002 -0.065 -0.003* 0.002 -0.043 POVER_% -0.005 0.005 -0.028 -0.011* 0.006 -0.046 -0.009 0.006 -0.039 ROB_RESL -0.419** 0.210 -0.073 -0.831*** 0.260 -0.109 -0.153*** 0.049 -0.115 ROB_PERL 0.065*** 0.015 0.178 0.131*** 0.018 0.272 0.367*** 0.047 0.383 HOMICIDESL -0.032 0.043 -0.044 -0.146*** 0.054 -0.151 -0.145*** 0.036 -0.207 BUSWAY 0.014 0.068 0.012 0.028 0.084 0.019 -0.013 0.046 -0.008 COMB_ACCL -0.008* 0.004 -0.141 -0.010** 0.005 -0.138 -0.004 0.041 -0.006 DIST_CBDL 0.001 0.006 0.008 -0.009 0.007 -0.055 0.002 0.012 0.007 DIST_DTL 0.007 0.010 0.064 0.002 0.012 0.015 0.015* 0.008 0.071 DIST_BUSWL 0.167** 0.070 0.175 0.235*** 0.086 0.187 0.042 0.028 0.079 DATA -0.023 0.021 -0.030 -0.001 0.026 -0.001 0.002 0.027 0.002 Constant -0.215 0.181 . -1.810*** 0.224 . -3.606*** 0.323 . Goodness of fit: Adjusted R2 0.692 0.729 0.720
***, **, and * denote coefficient significantly different from zero at the 1%, 5%, and 10% level of significance (two-tail test), respectively. LLogarithmic transformed variables for the Double-log model.
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