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ArtĂ­culo cientĂ­fico / Research pap= er

 

Precio del suelo dado por la oferta del mercado y el avalĂşo municip= al:

Relaciones y distribuciĂłn espacial en la ciudad de Cuenca

 

Price = of land determined by the market supply and the municipal appraisal:

Relati= ons and spatial distribution in the city of Cuenca

 

Jaime B= ojorque Iñeguez1 , Cristina Chuquiguanga Auquilla2 , Cristina Peralta Peñaloza3= , Paula Flores Chafla3

1 Pro= fesor de= la Facultad de IngenierĂ­a, Departamento de IngenierĂ­a Civil, Universidad de Cuenca, A= v. 12 de Abril y AgustĂ­n Cuenca, Cuenca, Ecuador, 01.01.168. <= /p>

2 Pro= fesora de= la Facultad de Arquitectura y Urbanismo, Universidad de Cuenca, Av. 12 de Abril y Agust= Ă­n Cuenca, Cuenca, Ecuador, 01.01.168.

3 Arq= uitecta, e= gresada de la Facultad de Arquitectura y Urbanismo, Universidad de Cuenca.

Aut= or para correspondencia: jaime.bojorque@ucuenca.edu.ec

Fecha de recepciĂłn: 3 de septiembre de 2020 - Fecha de aceptaciĂłn: 19 de septiembr= e de 2020

 

 

RES= UMEN

En el presente documento se analiza la relación entre el precio de mercado y el valor catastral de los lotes baldíos, urbanizados y de propie= dad horizontal, y su distribución espacial dentro del área urbana de la ciuda= d de Cuenca, con una superficie aproximada de 74 km2. El valor catast= ral de los lotes se obtuvo del portal del Gobierno Municipal Autónomo Descentralizado del Cantón Cuenca. Mientras que el precio de mercado se consiguió de las ofertas inmobiliarias publicadas en el período septiembr= e 2019 a marzo de 2020. De los 100,203 lotes, dentro del área de estudio, 994 lot= es, de los cuales se encuentran disponibles el precio de mercado y el valor catastral, fueron incluidos en el estudio. En total, se utilizaron en el análisis 421 lotes sin construir, 518 parcelas construidas y 55 propiedades horizontales. El precio del suelo según la tasación municipal equivale, en promedio, al 54.15% del precio de mercado, lo que demuestra que el valor catastral de las propiedades está subvalorado. La autocorrelación espacial entre el precio de mercado y el valor catastral se derivó utilizando las estadísticas I de Moran y Gi*. Se determinaron lotes con precio de mercado= alto con respecto al valor catastral, el 5% de los predios mostraron valores superiores al 4.82 con un máximo de 11.39. Considerando estos aspectos, los municipios, dado que la sociedad cambia a un ritmo acelerado, deben moderni= zar y renovar el sistema catastral, que tradicionalmente se considera que funci= ona bien, pero en muchos casos está desactualizado.

Palabras clave: Precio del sue= lo, precio de mercado, avalĂşo municipal, Cuenca.

 

 

ABSTRACT<= /b>

The paper ana= lyzes the relationship between the market price and the cadastral value of vacant lots, built-up lots, and horizontal property, and its spatial distribution within the urban area of the city of Cuenca, covering an area of approximat= ely 74 km2. The cadastral value of the lots was obtained from the Autonomous Decentralized Municipal Government of the Canton Cuenca. Whereas, the market price was obtained from the publis= hed real estate offers in the period September 2019-March 2020. Of the 100,203 = lots within the study area, 994 lots, of which the market price and cadastral va= lue are available, were retained in the study. In total 421 unbuilt-plots, 518 built-plots, and 55 horizontal properties were used in the analysis. The la= nd price by the municipal appraisal equals on average 54.15% of the market pri= ce, showing that the cadastral value of the properties is undervalued. The spat= ial autocorrelation between market price and the cadastral value was derived us= ing Moran’s I and Gi* statistics. Lots were observed with a high market price= , 5% of the properties presented values higher than 4.82 with a maximum of 11.39. These high values do not have a clear explanation, except speculation given= by the market. Given the difference between both measures, municipalities, giv= en society changes at a rapid pace, should modernize and renew the cadastral system, which traditionally is seen as well-functioning but in many cases is outdated.

Keywords: Land price, market price, municipal appraisal, Cuenca.

 


= 1.      =       INTRODUCCIĂ“N

 

El suelo es fundamental para el progreso de los ciudadanos, no solo porque la vivienda, la propiedad comercial,= el espacio público y el transporte se desarrollan sobre este, sino además af= ecta al mercado laboral y de productos. A pesar de este rol importante del suelo= , es considerado propiedad privada en casi todo el mundo, alcanzando precios muy altos. Pero ¿Cuál es el valor referencial del suelo urbano?, esta es una pregunta muy difícil de contestar y alrededor de la cual se han desarrolla= do varias teorías, por ejemplo, la Teoría de la Renta del Suelo Urbano (Jara= millo, 2009).

El suelo es un bien único y no reproducible; escaso por naturaleza = y un monopolio sobre el cual se generan valores diferenciales a lo largo de la estructura urbana. En este sentido, adquiere sus cualidades en función de = la inversión económica que realiza la población para hacerlo habitable y de atributos externos a él que califican su contexto (Granda, Cuesta, & <= span class=3DSpellE>Villagomez, 2017). Los bienes inmuebles representan u= n bien agrupado que consiste en suelo y capital incorporado. Con respecto al prime= ro, las influencias de las fuerzas económicas, sociales y legales se reflejan = en los valores del suelo. Por lo tanto, estos guían la formación de las ciud= ades y generan ingresos para los gobiernos locales (Womack, 2015). Los precios son, por lo general, una expresión del valor que el mer= cado otorga a los bienes según sus características. Las particularidades que m= ás influyen en el precio del suelo urbano son las extrínsecas, como la ubicac= ión relativa que tiene en la distribución urbana con respecto a otros lotes, m= ás que sus características intrínsecas, como el tamaño o la forma del terre= no (Erba, 2013). La naturaleza de la propiedad del suelo,= el método de realizar las transacciones y la falta de información pública s= uman a las imperfecciones del mercado inmobiliario. La mayoría de las negociacion= es se realizan de forma privada, e incluso cuando se conocen los resultados de las transacciones, no son útiles debido a la ausencia de información detallada sobre cuestiones como el tamaño y el estado de los edificios y el título = legal.

Se debe tener en cuenta, sin embargo, que el método de valoración a elegir depende de los fines o del interés por obtener dicha información. = Así, los propietarios estarán atraídos por conocer el precio de venta o de alq= uiler que pueden solicitar a su propiedad; los agentes inmobiliarios, generalment= e, analizan los precios de oferta según la ubicación que genere mayor rentabilidad; los compradores (o inquilinos) indagan el mercado para saber cuánto deben pagar; los acreedores hipotecarios se encuentran interesados = por el valor de la propiedad para la garantía del préstamo y los dueños por = conocer sobre su derecho a compensación e impuestos. De aquí que, el enfoque para= la estimación del valor en un caso puede ser diferente a otro y, con el tiemp= o, se han desarrollado enfoques o métodos de valoración separados (Shapiro, Mackmin, & Sams, 2013= ). El precio de un bien se puede calcular en función de sus diferentes características, sean estas cualidades o cantidades. En este concepto se b= asa el modelo hedónico de valuación y también el de costo de reposición. El= modelo hedónico es adecuado al incluir un variado número de factores en la estim= ación del precio (Paterson & Boyle, 2002), sin embargo, tiene limitaciones en= el sentido de que no considera los efectos espaciales que ocurren en cada regi= ón, las cuales se superan con econometría espacial (Kim & Kim, 2016), y la necesidad de contar con una amplia información de las características específicas de cada predio. Adicionalmente, el valor de un inmueble que se encuentre bajo explotación económica puede ser calculado en función de l= as expectativas de rentas. En este sentido, la oferta del mercado está ligada= a la demanda que genera la correcta explotación de las potencialidades del terr= eno (Erba, 2013).

En el Ecuador, el Código Orgánico de Organización Territorial, Au= tonomía y Descentralización (COOTAD) orienta la definición de políticas y mecani= smos para el desarrollo territorial. En su Art. 495, menciona que, el costo de la propiedad se establecerá mediante la suma del valor del suelo y de las construcciones que se hayan edificado. El término “valor del suelo” ha= ce referencia al precio unitario de suelo, determinado por un proceso de comparación con precios de venta de inmuebles de condiciones similares u homogéneas del mismo sector, multiplicado por la superficie del predio. Es= te valor sirve de base para la determinación de impuestos y para otros efectos tributarios y no tributarios a partir del cual las municipalidades pueden establecer criterios de valor de los inmuebles dados por intervención púb= lica, social u otro factor de incremento (COOTAD, 2010). Es importante destacar q= ue, este documento normativo, plantea una estimación simplificada para el cál= culo del costo del terreno, dejando a la especulación tomar espacio, sin realiz= ar un verdadero análisis técnico del precio que puede tener un suelo consideran= do un adecuado desarrollo territorial.

En condiciones normales, los precios de mercado son el resultado de estimaciones realizadas por compradores y vendedores sobre la base de preci= os previamente pagados por otras propiedades similares. Sin embargo, en moment= os en que las condiciones del mercado no son estables, pueden surgir diferenci= as más significativas. Por ello, es importante, ir más allá de la oferta y = la demanda para realizar una estimación del valor del suelo, debido a los múltiples aspectos de desarrollo que están involucrados en este análisis= , por ejemplo, el derecho a vivienda digna. En el estudio realizado en la ciudad = de Tena-Ecuador, Granda, Cuesta, & Villagomez = (2017) muestran que la valoración de la tierra urbana es muy subjetiva, pues los criterios que caracterizan a cada uno de los predios urbanos son, en su mayoría, provenientes de una cualificación urbanística. Esto se evidenci= a de igual manera en otras regiones del país. Así, el precio, como expresión = de la relación del interés que tiene un determinado sujeto con respecto al pred= io urbano, viene a representar el soporte para la decisión individual de las partes intervinientes en el proceso de valoración; es decir, constituye normalmente las fronteras de negociación.

En es= te complicado proceso de valoración del suelo, es importante resaltar las estimaciones que realizan los Gobiernos Autónomos Descentralizados Municip= ales en Ecuador para el cobro del impuesto al predio urbano. Por ejemplo, en Cue= nca, el 15.07% del total recaudado por concepto de tributos se relaciona con cob= ros de impuestos por el predio (Quille & Quizhipi, 2011). Vale la pena resaltar que, el precio= comercial del suelo difiere en gran medida del avalúo municipal, generalmente la valuación masiva presenta problemas de subvaluación con respecto al valor= real comercial de los bienes inmuebles ya sea por razones técnicas o en su mayo= ría por cuestiones políticas (Borrero, 2010), inclusivo en América Latina se = ha identificado que los valores catastrales suelen ser manipulados para privilegiar a ciertos grupos (Erba, 2007).=

Las municipales, en general, enfrentan dificultades para determinar el valor catastral, por un lado, mantener un catastro vigente con información cartográfica y temática dem= anda altos costos, más aún cuando la actualización no es parte de la actividad diaria, y por otro, contar con información real de las transacciones inmobiliarias requiere trabajar en nuevas metodologías que agiliten el pro= ceso, de aquí que la aplicación de modelos predictivos para la valuación masiv= a, y a la vez, la creación de observatorios en las que se recopile información d= e los
precios de venta, puede ser una alternativa (Lozano-Gracia & Anselin, 2012)= .

Se debe de considerar, adicionalmente, que el precio del suelo urbano es una variable espacial auto correlacionada tanto a nivel de ciudad como de región, es decir, depende d= e su entorno local y regional. Muchas investigaciones han verificado la autocorrelación del valor inmobiliario urbano a nivel de ciudad, identificándose que la autocorrelación espacial del precio del suelo urba= no es causada principalmente por la autocorrelación espacial económica (Conway = et al., 2010; Jiao & Liu, 2012; Xiao et= al., 2017). Pero su grado de autocorrelación espacial es menor que los factores económicos porque el precio de la tierra de referencia urbana también est= á influenciado por otros factores locales especiales, como: la población, la= infraestructura de la ciudad, el suministro de tierras, entre otros (J= iao & Liu, 2012). La autocorrelación espacial es una evaluación de la correlación de una variable en referencia a la ubicación espacial de la variable. Para el análisis de la autocorrelación espacial se pueden emple= an estadísticas como la I de Moran y Gi* (Liu, Li, Sun, & Ma, 2006).

A nivel mundial, el avalúo del = suelo se toma como un referencial para imponer impuestos, así como una base para establecer y ejecutar diversas políticas gubernamentales. De aquí que es necesario realizar investigaciones en esta área y sustentar la legislació= n en la aplicación de modelos estadísticos espaciales para estimar los precios oficiales del suelo.

El objetivo de este documento es analizar la relación existente entre los precios del suelo dados por la of= erta de mercado y el precio del suelo indicado en el avalúo municipal, e identi= ficar posibles relaciones espaciales. Se parte de más de mil precios obtenidos d= e un intenso trabajo de campo durante el periodo septiembre 2019 a marzo 2020, y= se contrastan con los avalúos municipales vigentes de la ciudad de Cuenca. Finalmente, apoyado en la metodología del I de Moran local y agrupamiento espacial Gi*, se analiza el comportamiento espacial de la relación entre p= recio del mercado y el valor de avalúo.

 

 

= 2.      =       MATERIALES Y MÉTODOS

 

= 2.1.      =   Zona de estudio

La zona de estudio corresponde al área urbana = de Cuenca en Ecuador, con una extensión aproximada de 74 km2. El c= antón Cuenca según el VII Censo de Población y VI de Vivienda del 2010, realiza= do por el Instituto Nacional de Estadísticas y Censos (INEC), tenía 505,585 habitantes, de los cuales 331,888 habitantes (65.6% del cantón) residían = en el área urbana, y 173,697 habitantes (34.4%) en el área rural. La Secretaria Nacional de Planificación, estima al 2020 para la ciudad, una población de 418,152 habitantes. El total de viviendas en la ciudad de Cuenca se determi= nó en 89,789 (INEC, 2010), y el porcentaje de hogares que habitan en viviendas propias en el 45.53% (PDOT Cuenca, 2016). Para el año 2020 existen más de 100,000 predios registrados en el catastro municipal.

=  

2.2.=         Recop= ilaciĂłn de informaciĂłn

Ofert= as del mercado

Los precios del suelo se derivar= on de la oferta inmobiliaria en la ciudad de Cuenca entre septiembre 2019 a ma= rzo 2020. Se emplearon diversas fuentes de información entre las que destacan: publicidad (letreros), redes sociales e inmobiliarias. La publicidad fue la mayor fuente de datos, y fundamentalmente esta información fue recogida en= un recorrido por la ciudad, en el cual se realizó un registro fotográfico de= los diferentes letreros mediante la aplicación Google fotos, que permite administrar información relativa a la hora y ubicación de la fotografía.= Las redes sociales e inmobiliarias, a su vez, fueron la segunda fuente de información; la búsqueda se realizó principalmente en páginas relaciona= das a venta de propiedades tales como: OLX, Marketplace de Facebook, Plusvalía, y páginas web de inmobiliarias. Es necesario mencionar que, las fuentes rela= tivas a publicidad en periódicos (prensa) fue utilizada de manera esporádica, d= ebido a la repetición continua de dichos anuncios en los medios digitales mencio= nados anteriormente. La información levantada según el tipo de propiedad compre= nde: la superficie del lote (m2), el precio del lote, y observaciones= (en caso de que la situación amerite). Para lotes con edificaciones, informaci= ón adicional como la superficie de construcción (m2), el precio de= la propiedad, el material de la estructura, y año de construcción, fue levan= tada. Adicional a los datos indicados, se identificó la clave catastral, cuyo fi= n es facilitar el geoprocesamiento de los datos, la información fue obtenida de= l Geoportal-Web Municipal.

Para la determinar el tamaño de= la muestra, la unidad de análisis es el predio urbano (se cuenta con 100,203 = lotes en la base de datos) y se considera el área de estudio el límite urbano, aprobada en la ordenanza que sanciona el Plan de Desarrollo y Ordenamiento Territorial de Cuenca (GAD Cuenca, 1998). La metodología empleada es el muestreo estratificado con afijación proporcional (Sc= heaffer, Mendenhall, Ott, & Ger= ow, 2012), teniendo como universo poblacional al suelo urbano, se establece el = peso de los estratos (sectores de planeamiento), fijando la cantidad de datos a levantar en cada sector para efectos del análisis. Se excluyeron aquellos sectores considerados “especiales” que por su uso de suelo no forman pa= rte de la muestra, como se detallan a continuación: Los sectores S-24, S-14 y N-1= 0, que corresponden a los predios de la Universidad de Cuenca, de la Universid= ad del Azuay y de la Universidad Politécnica Salesiana, respectivamente. Los sectores E-19, E-26 y N-7A, pertenecientes a las estaciones militares de Batallón de Infantería Nº9 Cayambe, Grupo de caballería mecanizada Nº6= General Dávalos y Tercera Zona Militar, respectivamente; y, el Sector E-24, correspondiente a las lagunas de oxidación del sistema de alcantarillado d= e la ciudad.

Para el cálculo de la muestra (= n) se considera; el tamaño de la población (N), el nivel de significa= ncia (z), el error esperado (e), la probabilidad de éxito (p) y fracaso= (q), según la ecuación siguiente:

 

 

Para cada sector de planeaciĂłn se determina el nĂşmero muestral del estrato (ne) en funciĂłn de la proporciĂłn del estrato (pe), como:

 

 

AvalĂşos municipales

Los avalĂşos municipales de los predios se obtuvieron de la página institucional del GAD Municipalidad de Cuenca[1], en la cual se = revisĂł el informe predial que constituye un reporte con datos que describen las principales caracterĂ­sticas. Los avalĂşos se relacionan con el plano de va= lor del suelo urbano de la cabecera cantonal bienio 2020-2021 (GAD Cuenca, 2019= ). La informaciĂłn levantada corresponde al periodo febrero a marzo 2020. Para relacionar, y posteriormente contrastar la informaciĂłn levantada (precio de mercado) con el avalĂşo municipal, se emplea la clave catastral. Vale seña= lar que, en algunos casos, el área del terreno registrado en el municipio, asĂ= ­ como el área de construcciĂłn no corresponden a la superficie señalada por el vendedor. Estas discrepancias se deben, entre otros aspectos, a la falta de actualizaciĂłn de la base de datos municipal, desconocimiento del oferente, lotizaciones aĂşn sin divisiones registradas, por señalar las identificada= s. Por ello, se considera una variaciĂłn máxima de 15% del área del lote, entre = la registrada y la proporcionada por el oferente, para incluir el predio en el análisis.

 

= 2.3.      =   DeterminaciĂłn del precio de sue= lo por metro cuadrado

El proceso para la obtención de valores de = suelo de la oferta inmobiliaria en la ciudad de Cuenca se realiza según el tipo = de bien registrado, sea estos: predios sin edificación, con edificación y propiedad horizontal. Con el fin de identificar posibles variaciones en los valores debido al tipo de lote se emplean técnicas estadísticas para eval= uar el comportamiento de grupos de valores. Las técnicas de análisis estadístico pueden determinar si los datos son aleatorios o se pueden agrupar en conjun= tos similares. Quizás el método de análisis más útil es la prueba Student t-test, que se usa para identificar si la diferencia entre valores promedio es lo suficientemente grande como para implicar que los valores medios son diferentes (Larsen & Marx, 2006).

 

Predios sin edificaciĂłn

Dado que el predio no incluye construcción, el precio por metro cua= drado (m2) del suelo es el precio divido por su área.

 

Predios con edificaciĂłn

El proceso empleado consiste en valorar la edificación en función = de sus características, el estado y las condiciones particulares indicadas por el propietario o intermediario. La estimación del costo inicial de las edificaciones se realiza a partir de las especificaciones técnico-construc= tivas predominantes en la propiedad, a saber; materiales de la estructura, parede= s, piso y cubierta estableciendo un costo por m2 según el tipo de acabados, el cual fue determinado por la experiencia de los constructores d= e la zona. Posteriormente, para determinar el precio final de la construcción, = se considera que, al finalizar la vida útil de una edificación, el valor res= idual corresponde al 30% del precio inicial. La vida útil depende del tipo de material; para estructuras de hormigón, metálica y compuesta es de 50 añ= os, para adobe y madera 40 años, y para bareque 30 años. Las correspondientes= tasas de depreciación anual, según el tipo de estructura, varía entre 2.38% y = 2.97%. Vale la pena señalar que los datos de precios de los materiales utilizados corresponden al periodo enero a febrero 2020.

El valor de la edificación es el resultado de multiplicar el precio= base de la construcción por la tasa de depreciación anual elevado a la edad de= la construcción en años, según la siguiente ecuación:

 

 

donde Pe =3D precio final de la construcción, = Pb =3D precio base de la construcción, t =3D tasa de depreciación anu= al, y e =3D edad de la construcción en años.<= /o:p>

 

Así, el precio por m2 será el resultado de restar el pr= ecio solicitado por el oferente menos el costo de la construcción y dividido po= r el área total. En casos donde la construcción es obsoleta, es decir, ya ha alcanzado su vida útil, el precio del m2 de construcción repre= senta únicamente el valor del terreno. Debido a la complejidad y a las particularidades de las edificaciones en venta, es necesario realizar un proceso intermedio para la valuación de la propiedad: i) Para las propieda= des cuya edificación se encuentra en obra gris, el m2 de construcci= ón representa el 50% del valor estimado del precio base de edificaciones nueva= s, y ii) Se consideró la fuente de la información,= es decir, si la propiedad es ofertada por una inmobiliaria, el precio final de= la construcción se resta su valor en un 4%, este porcentaje representa la gan= ancia del corredor de bienes raíces por la venta de la edificación.<= /span>

 

Propiedad horizontal

El cálculo para estos predios es similar al de predios con edificac= ión. A partir del precio (precio promedio, si existen más de una oferta en la m= isma propiedad) por m2 de departamento, se calcula el costo total del proyecto al multiplicar dicho valor por el área de construcción. Posteriormente, se calcula el precio base del predio, a partir de una estimación del costo por m2 de construcción en altura en funci= ón de los acabados, y se aplica el método residual para la obtención del valor = final de la edificación. El precio por m2 de suelo es el resultado de restar el costo estimado del proyecto del valor de la construcción y divid= ir para la superficie del lote.

 

 

2.4.        AutocorrelaciĂłn espacial

Con la finalidad de visualizar la distribuci= ón espacial de los precios en todo el límite urbano de la ciudad, se realiza = una interpolación espacial con el método de Kriging (ESRI, 2020). El Kriging emplea una variable de interés, en este caso el precio del suelo, para hacer estimaciones del val= or posible en ubicaciones no muestreadas.

También, se emplea las estadísticas del I de Moran local y Gi* con= el fin de identificar posibles variaciones espaciales en los precios de suelo dados por la oferta y el avalúo municipal. La estadística Gi* guía a identificar dónde se agrupan espacialm= ente los elementos con valores altos o bajos (puntos calientes/hotspots). Para representar un punto caliente estadísticamente significativo, una ent= idad debe tener un valor alto y también estar cerca de otros elementos con valo= res altos. La suma local para una entidad y sus vecinos se compara proporcionalmente con la suma de todos los elementos; cuando la suma local = es muy diferente de la esperada, y esa diferencia es demasiado grande como para ser el resultado de una opción aleatoria, se obtiene como consecuencia una= puntuación z estadísticamente significativa (ESRI, 2020). La estadística Gi* se evalúa a través de la siguiente expresión:

 

Donde xj es el atributo del elemento j, wi,j es el peso espacial entre el elemento i y j, n es el nĂşmero total de elementos.

La estadística de I de Moran local permite, dado un conjunto de elementos ponderados, identificar puntos calientes, puntos fríos y valores atípicos espaciales estadísticamente significativos. El valor de autocorrelación espacial a través del I de Moran se establece como (ESRI, 2020):

Donde xi es el atributo del elemen= to i,  es la media de atributo correspondiente= , wi,j es = el peso espacial entre el elemento i y j.

Con n igual al nĂşmero total de elementos.

En ba= se a este análisis se establece la puntuación de z (número de desviaci= ones estándar que hay por encima o por debajo de la media de población), y el = valor p (valor de probabilidad), ambos datos se emplean para identificar la significancia estadística del análisis.

La puntuaciĂłn z<= sub>Ii se determina como:

Un valor positivo para el I de Moran indi= ca que una entidad tiene elementos vecinos con valores de atributo altos o baj= os similares, representando un grupo. Un valor negativo para I representa que = un elemento tiene elementos vecinos con valores diferentes; el cual puede ser = un valor atĂ­pico. En ambos casos, el valor p para el elemento debe ser= lo suficientemente pequeño para que el grupo o el valor atĂ­pico se consideren estadĂ­sticamente significativos. El grupo o valor atĂ­pico distingue entre= un grupo de valores altos (HH), un grupo de valores bajos (LL), un valor atĂ­p= ico en el que un valor alto está rodeado por valores bajos (HL) y un valor atĂ= ­pico en el que un valor bajo está cercado por valores altos (LH). La importancia estadĂ­stica se establece en un nivel de confianza del 95%.

 

=  

3.&n= bsp;           RESULTADOS Y DISCUSIONES

 

En base al análisis estadĂ­stic= o de muestreo por sector de planeamiento, considerando el tamaño de la poblaciĂ= łn (N=3D100,203), nivel de significancia (z=3D1.96, 95% confiabilidad), error estimado (e=3D4%), probabilidad de Ă©xito (p=3D0.5) y fracaso (q=3D0.5), resulta el = nĂşmero de muestras n=3D594. Se debe considerar que, a diferencia que otros componente= s de estudios, los lotes en venta se basan en el deseo de vender de sus propietarios, lo cual puede limitar el nĂşmero de muestras disponibles en c= ada sector. Sin embargo, en el periodo de levantamiento, la oferta inmobiliaria= fue mayor y se ajustĂł a lo establecido en la muestra, recolectándose 1493 pre= cios del mercado. En aquellas zonas donde no se alcanzĂł el nĂşmero de datos establecidos, fundamentalmente, se expresan usos forestales por inundacione= s y limitaciones topográficas, lo que disminuye la oferta inmobiliaria. De este total, los lotes que se pueden correlacionar con informaciĂłn oficial del municipio fueron 1058, esto debido a que se cuenta con la clave catastral p= ara estos lotes que corresponden a la registrada en el municipio. De este total= se verificĂł que las áreas registradas en el municipio y las informadas por l= os oferentes sean similares, con una variaciĂłn máxima del 15%, quedando 994 predios. En la Figura 1 se presenta


Figura 1. Distribución espacial de los 994 datos de precios del suelo en el área ur= bana de Cuenca.

 


la ubicación espacial de los lotes seleccionados en función de las características de ocupación del lote. Se tiene información de precios e= n toda el área urbana de la ciudad, excluyendo los sectores especiales. El númer= o de predios sin edificación es de 421, con edificación 518 y propiedad horizo= ntal 55. Se puede indicar que los predios de edificación horizontal se encuentr= an ubicados en ciertos sectores, excluyendo, por ejemplo, el centro y Este del área de estudio.

 

Los resultados estadĂ­sticos del avalĂşo municipal y los precios de = oferta del suelo se presentan en la Tabla 1. Los precios del suelo segĂşn el avalĂ= şo municipal tienen una media de 244.24 USD/m2, mientras que los precios de mercado tienen un valor de 451.04 USD/m2, lo que representa una relaciĂłn de 54.15% del avalĂşo con respecto al precio del mercado. Este porcentaje está en proporciĂłn con el 50% determinado en un análisis realizado a 100 predios en la ciudad de Cuenca (Quille & Quizhpi, 2011). Los valores municipales a menudo se establecen por debajo de los valores de mercado. En Alemania, los valores municipales se establecen en el 33% de los valores de mercado, mien= tras que en otros paĂ­ses el porcentaje es mayor. En Corea, una reforma fiscal a= la propiedad considerĂł alinear los valores imponibles con los valores de merc= ado, pero los obstáculos polĂ­ticos mantienen el porcentaje entre el 60 y 70% (= Blöchliger, 2015).

 

Figura 2. Histogramas de precios del suelo segĂşn el avalĂşo municipal y la oferta de mercado

 

En la Figura 2 se expone los histogramas de los valores correspondie= ntes al avalúo municipal y precios de la oferta de mercado. Se observa que el histograma del avalúo municipal es más estrecho, con la mayoría de valores centrados en los 50 y 350 USD/m2, mientras que para los


Fig= ura 3. Ma= pas interpolados mediante Kriging, a) avalĂşos municipales, y b) precios de mercado.


precios de mercado la distribución es más extensa, indicando valor= es más dispersos. Se realizó una interpolación espacial de los valores, empleand= o el método Kriging, tanto para datos de avalúo co= mo para precios de mercado, con el fin de obtener un mapa general del área de estu= dio que evidencia el comportamiento del mercado de suelo.

La Figura 3 se presenta las superficies interpoladas, tanto para los datos del precio del suelo del avalúo municipal como para precios del merc= ado levantados en este estudio. Se observa que el avalúo (Fig. 3a) tiene mayor= es picos en ciertas zonas, indicado que existe diferencias mayores; en el cent= ro de la ciudad donde se presentan los valores más altos, la superficie estim= ada tiene una concentración más definida. Hacia el límite urbano, los precio= s del suelo van disminuyendo, sin embargo, no se visibiliza un patrón específic= o. Los precios de menor valor, en el caso del avalúo, se distribuyen espacialment= e de manera similar, aunque en un área más extensa y en ciertas zonas puntuale= s, en comparación con los menores valores registrados de la oferta del mercado. = La forma que se representa el mapa de avalúos responde a la discretización realizada en función de la sectorización en zonas homogéneas, esto se re= laciona con el plano de valor del suelo del bienio 2020-2021. Para determinar las z= onas homogéneas en los catastros, generalmente, se considera la dotación de servicios públicos, el uso del suelo, aspectos socio económicos, entre ot= ros. En el caso de los precios de oferta (Fig. 3b) se evidencia una distribució= n de precios más uniforme en toda la zona urbana, pero de igual manera con la mayoría de precios más altos en el centro del = área urbana. Estas diferencias se pueden deber a las dificultades que tienen los municipios de mantener un catastro vigente con información cartográfica y temática actualizada, lo que demanda altos costos, por lo que se requiere trabajar en nuevas metodologías que agiliten el proceso para la valuación masiva del suelo urbano.

Para analizar posibles variaciones de los precios en base al tipo de predio levantado, en la Tabla 2, se presenta, por separado, los estadístic= os de avalúos y ofertas en función del tipo del predio, es decir, entre los pre= dios sin edificación, con edificación y propiedad horizontal. La diferencia en= las medias se puede validar estadísticamente mediante la prueba = Student t-test. Para los precios de mercado, de la prueba para dos muestras suponie= ndo varianzas iguales, entre predios sin y con edificación, el valor de probabilidad es 4.8E-06<0.05, lo que indica que la hipótesis nula es rechazada, mostrando una diferencia significativa al 5% entre las medias. P= ara el caso de predios sin edificación y propiedad horizontal, la prueba muest= ra, de igual manera, una diferencia de medias con probabilidad de 2.8E-08, mucho menor al valor crítico. Para el caso de predios con edificación y propied= ad horizontal, la prueba rechaza, así también, la hipótesis de medias igual= es con un valor de 2.1E-3<0.05. Este análisis indica que los grupos de valores= para las tres categorías son diferentes en el caso de los precios de mercado.

Para los precios del avalúo municipal, el valor de probabilidad del= Student t-test es de 8.0E-08<0.05, lo cual indica = que la hipótesis nula es rechazada para los predios sin y con edificación. Para = el caso de predios sin edificación y propiedad horizontal, la prueba indica, de ig= ual manera, una diferencia de medias con probabilidad de 4.5E-05. Para el caso = de predios con edificación y propiedad horizontal, la hipótesis nula, en este caso, no se rechaza con un valor de 0.1>0.05, lo que muestra que las med= ias de estos dos grupos son similares según sus grupos de análisis. Los predi= os del avalúo sin edificación tienen una media de 212.77 USD/m2, con edificación 264.14 y propiedad horizontal 297.72, lo que representa un incremento con respecto al primero de 24.14% y 39.93%, respectivamente. En = el caso de los precios de mercado, la media para predios sin edificación es de 405.97 USD/m2, con edificación 474.22 y propiedad horizontal 57= 7.62, representado un 16.81% y 42.28%, respectivamente, con respecto a los predios sin edificación.

La relación del precio de suelo dado por el avalúo y el precio de mercado se presenta en la Tabla 3. En este caso, no se determina una difere= ncia en las medias, según los análisis de la prueba Stude= nt t-test, por lo que el análisis de resultados se realiza de forma conjunta.= La media total de la relación O/A es de 2.27, indicando que el precio de merc= ado es más de dos veces aquel registrado en el avalúo municipal. Es de espera= rse que el avalúo municipal sea menor que el comercial, sin embargo, se consid= era conveniente analizar el rango de valores de tales diferencias que pueden contribuir para mejorar la recaudación de impuestos (beneficioso para el gobierno local) y en caso de expropiaciones (beneficio para el propietario), entre otras transacciones que se basan en el avalúo. Es interesante observ= ar que, la diferencia puede alcanzar a valores de 11.39 veces, lo que indica q= ue se está beneficiando de alguna manera a los propietarios de esos lotes con= los avalúos actuales o existe una fuerte especulación del suelo urbano. O en = su defecto, los valores de los bienes inmuebles no se han actualizado durante = años o incluso décadas, como es el caso en varios países miembros de la Organi= zación para la Cooperación y el Desarrollo Económico, lo que puede crear distors= iones e injusticia para los propietarios (Blöchliger, 2015). Así también, existen predios en los cuales el precio de venta es m= enor que el avalúo municipal, lo que puede deberse a factores propios del terre= no, como características geográficas y físicas de los terrenos.

La Figura 4 presenta la distribuciĂłn espacial de la relaciĂłn entre= el precio del suelo segĂşn la oferta del mercado con respecto al avalĂşo munic= ipal (relaciĂłn O/A). Se evidencian zonas en la que existen concentraciones de mayores diferencias de la relaciĂłn O/A, esto se observa en


 

Figura 4. DistribuciĂłn espacial de la relaciĂłn entre el p= recio del suelo segĂşn la oferta del mercado y el avalĂşo municipal.


la parte norte del área urbana. En toda la zona central se tiene va= rios predios con las menores diferencias en la relación O/A. Lo que podría evidenciar que el modelo empleado para el cálculo del avalúo catastral pr= esenta un menor nivel de precisión en ciertas zonas. La variabilidad en relación= con los precios de venta de los inmuebles puede significar la necesidad de ajus= tes globales o parciales en los modelos propuestos de valuación (Erba, 2007).

Fig= ura 5. Fr= ecuencia acumulada de la relaciĂłn entre el precio del suelo dado por la oferta de mercado y el avalĂşo municipal.

 

En la Figura 5 se presenta la frecuencia acumulada de la relación p= recio de mercado versus avalúo. Se puede indicar que, el 6.4% de los datos analizados, es decir, 64 lotes de 994 tienen precios de oferta inferiores al avalúo municipal, con valores de la relación O/A<1. El percentil 50% c= on un valor de 1.93, indica que 497 lotes tienen valores menores o iguales a 1.93, dando 433 predios entre 1 y 1.93 del avalúo (43.6%). En el caso del percen= til 95%, 944 predios tienen valores menores o iguales a 4.82 y solamente el 5% = (50 predios) tienen valores superiores al 4.82, con un máximo de 11.39.

Con la finalidad de determinar diferencias acentuadas entre las relaciones de precios de mercado y el avalúo municipal, se determinaron pu= ntos calientes según la metodología de Gi*. Si bien, los elementos con un valo= r alto o bajo son puntos de interés, sin embargo, es posible que no sean puntos calientes estadísticamente significativos, debido a que, para ser un punto caliente estadísticamente significativo, un elemento debe tener un valor a= lto o bajo y también estar rodeado por otros elementos con valores altos. En la Figura 6 se presenta el resultado obtenido para la estimación de puntos calientes bajo los criterios mencionados, considerando diferentes niveles de confiabilidad de 90, 95 y 99%.

Se observa una concentración de puntos calientes (valores altos) en= el norte del área y fríos (valores bajos) en el centro del área urbana. Los= puntos fríos ubicados en el centro del mapa representan valores que tienen una diferencia menor en la relación precio de mercado y avalúo municipal que = el resto de los datos de análisis, indicando que los precios de mercado son cercanos a los del avalúo, presentándose relaciones bajas. Los puntos cal= ientes ubicados, principalmente, en el norte del mapa, indican que los precios de mercado son superiores en comparación con los otros datos de la zona urban= a, por lo que los avalúos en estas zonas son muy inferiores a los requerimien= tos económicos de los propietarios. Lo que puede evidenciar un grado de especulación ya sea por las expectativas de desarrollo generadas en esos lugares, desconocimiento del vendedor del precio del lote, o incluso el involucramiento de intermediarios (Nuñez &= Schovelin, 2002). En la parte central se tienen las relaciones más bajas con un mínimo de 0.38 y un máximo de 3.37.


Fig= ura 6. Pu= ntos calientes y frĂ­os en base a estadĂ­stica Gi*.

Fig= ura 7. Pu= ntos de interés en función de análisis de valores atípicos según I de Moran.

 


En base de un análisis de valor= es mediante el I de Moran, se identifican puntos que salen de las expectativas locales de las relaciones espaciales esperadas. La Figura 7 se presenta el = mapa con la identificaciĂłn de puntos atĂ­picos dentro de cada zona de agrupaciĂ= łn. Del análisis de autocorrelaciĂłn espacial se han identificado valores atĂ­picos dentro de los grupos. Se tiene 78 puntos HH (alto-alto), indicando que corresponden a valores altos pero que están rodeando de valores tambiĂ©n a= ltos a su alrededor, estos se presentan en su mayorĂ­a en la zona norte del mapa. Dentro de la zona de relaciones altas, se presentan 34 puntos LH (bajo-alto) que muestran que son valores menores a los esperados en la zona de análisi= s. En el centro del mapa se presenta la mayorĂ­a de los valores de relaciĂłn bajo= -bajo LL (218) y algunos puntos (32) salen de este comportamiento de valores bajo= s, identificados como HL (alto-bajo), mostrando valores más altos de los espe= rados en estas zonas. En general, lo que permite identificar este análisis es la= existencia de valores que salen del comportamiento esperado en cada sector, lo que deb= erĂ­a generar estudios posteriores con la finalidad de entender de mejor manera e= ste comportamiento. La implementaciĂłn del impuesto a la propiedad sigue siendo difĂ­cil para los paĂ­ses en desarrollo donde los desafĂ­os polĂ­ticos son = las deficiencias administrativas, financieras y tĂ©cnicas de la autoridad tributaria; falta de datos legĂ­timos, un sistema de valoraciĂłn adecuado y voluntad polĂ­tica; mercados inmobiliarios inmaduros; y sistemas de registr= o, adquisiciones, legislaciĂłn e hipotecas subdesarrollados (Hoque, 2019).

 

 

= 4.      =       CONCLUSIONES

 

La recaudación de impuestos por concepto del suelo se basa en planos de valor del suelo urbano, los mismos = que, en la mayoría de casos, son elaborados en base = de la información de los precios dados por la oferta del mercado. Si bien, los municipios reducen, en cierta medida, los valores de mercado, no se han identificado procedimientos claramente definidos para tal fin. La metodolog= ía propuesta por el COOTAD para la definición del precio del suelo en base de comparación con precios de venta de inmuebles de condiciones similares u homogéneas del mismo sector, abre la puerta a q= ue el mercado rija en un bien tan importante para el desarrollo de los ciudadanos, como es el suelo. Por otro lado, al no existir un control en el precio que pueda solicitar un propietario por su lote, esto contribuye a la especulaci= ón del precio, basado en la oferta y la demanda del mercado.=

En base a una comparación de 994 precios del mercado de lotes en venta en el área urbana de Cuenca, se ha determinado la relación del precio del suelo dado por la oferta del mercad= o con respecto al avalúo municipal del terreno. Se determinó que, en promedio, = el precio del suelo dado por el avalúo municipal es el 54.15% con respecto al precio del mercado, observándose que, el avalúo catastral es subvalorado = en ciertos sectores. Se identificó que, dependiendo del tipo de lote; sin edificación, con edificación o propiedad horizontal, los precios difieren= . Los precios del suelo dados por la oferta de mercado para predios con edificaci= ón son un 24.14% mayores a aquellos sin edificación, para propiedad horizonta= l el aumento es de 39.93%, lo que indica que los propietarios recargan un precio= adicional al suelo por concepto de edificación. Este incremento, debido a la construcción, también se observa en el avalúo municipal con un 16.81% pa= ra predios con edificación y 42.28% para los de propiedad horizontal.

Se determinĂł que la gran mayorĂ= ­a de los lotes analizados (93.6%) tienen precios de suelos superiores a los estimados por el avalĂşo municipal, existiendo apenas un 6.4% de precios de oferta inferiores al avalĂşo municipal, que puede estar subvalorando la edificaciĂłn y gravando más al suelo. La mitad de los propietarios que est= án vendiendo sus terrenos han solicitado precios que van desde 1.93 a 11.39 ve= ces el precio del avalĂşo municipal, lo que puede evidenciar, entre otros aspec= tos, la especulaciĂłn del suelo. De aquĂ­, se considera necesario revisar el ava= lĂşo municipal, empleando una metodologĂ­a adecuada para tal fin. Las diferencias obtenidas entre los valores dados por la oferta de mercado y el avalĂşo catastral, demuestra la necesidad de revisar la metodologĂ­a empleada con f= ines catastrales a fin de identificar un modelo que se ajuste de mejor forma a la realidad de la ciudad, por ejemplo, a travĂ©s de modelos predictivos que permitan identificar las variables que determinan el precio del suelo en la ciudad de Cuenca.

En base a un análisis de autoco= rrelación espacial se observó que la distribución de los precios dados por la ofert= a del mercado es más homogénea que aquella dada por el municipio. Se han determ= inado zonas en donde las diferencias en el precio del suelo dado por la oferta y = el avalúo son mayores, principalmente en zonas hacia el norte de la ciudad, indicando que el avalúo en dichos sectores debe ser revisado y por lo tanto actualizar el plano de valor del suelo, puesto que se puede estar beneficia= ndo a un cierto sector de la población. Así también, se identificaron valores atípicos, lo cual indican que existen propietarios que solicitan precios f= uera de lo esperado según el comportamiento de los predios vecinos, lo que se p= uede deber a pura especulación del precio.

Es importante mencionar que aspe= ctos externos como: localización del sitio, servicios cercanos, infraestructura, áreas verdes, entre otros factores, que influyen en el precio esperado por= el propietario, están fuera del análisis del presente estudio. Así también= , los municipios contemplan diferentes factores de reducción o aumento del preci= o del valor referencial según condiciones físicas de los terrenos. Sin embargo,= estos aspectos indicados afectan en igual magnitud a los precios dados por la ofe= rta de mercado que los considerados en el avalúo, por lo que los análisis realizados en el presente estudio son válidos.

Debido a que en una misma zona se presentan diferencias de relaciones, esto permite concluir que existe un aspecto especulativo en la ganancia esperada por un lote. Este análisis pe= rmite también identificar que el actual plano de valor del suelo subestima los valores que en la realidad se solicitan por los predios, independiente de l= os factores de reducción que el municipio maneja.

Es necesario avanzar en el desarrollo de metodologías de valuación masivas de suelo que permitan a l= as municipalidades: reducir costos, mantener la credibilidad de los ciudadanos= y garantizar la aceptación de los valores e impuestos. El presente estudio pretende llamar la atención a los municipios del país para que empleen herramientas más técnico - científicas para la determinación del valor = del suelo, sin perjudicar la recaudación de impuestos por subvalorar los preci= os de los predios, ni perjudicar a los propietarios con una sobrevaloración de <= span class=3DGramE>los mismos.

 

 

AGRADECIMIENTO=

=  

Los autores desean agradecer el apoyo emitido por la Dirección de Investigación de la Universidad de Cuen= ca a través del aval al proyecto “Aplicación de la teoría de la renta de la= tierra en la valuación del suelo urbano con fines catastrales para la gestión de= las municipalidades en el Ecuador”. Así también, al Arq. Alfredo Ordoñez, = docente de la Universidad de Cuenca, por su aporte referente al análisis de precio= s de construcción.

 

 

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[1] https://enlinea.cuenca.gob.ec/#/informe-predial

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