Real property valuation processes Jānis Gredzens 19.04.2016.

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Presentation transcript:

Real property valuation processes Jānis Gredzens

Topics to be discussed 2 Valuation cycle OLAP database Discoverer plus Ratio analysis  Information required for analysis  Desired format  Using SPSS  Using R Adjustment of base values and/or zonings GIS (geographic information system) structure and examples

Stages of real property valuation processes 3

Tools (software) used OLAP database Oracle BI Discoverer SPSS/R GIS (geographical information system) MS Excel MS Access 4

Database structure 5 LR - Land register CIS – Cadastral information system MDB – Market database GIS – Geographical information system

OLAP database OLAP – online analytical processing Database data is already up to date and calculated which makes it faster and easier for user to retrieve desired results that one can later use for further calculations Database data is denormalized which allows user to retrieve desired data with less joins than it would be possible with relational database OLAP for market – information only about properties that have been a part of a deal OLAP for cadastre – information about all objects that have been registered in cadastre 6

Discoverer Plus User friendly application for data retrieval and analysis Possibility to implement new variables depending on user’s needs Easily accessible statistics Statistics can be retrieved fast but lacks built-in functions for complicated statistics and statistical significance tests Any kind of workbooks can be created that one can come up with User does not need to know the joins in order to retrieve data Personal workbooks Shared workbooks 7

Discoverer workbook wizard example 1.Window where all calculations are stored 2.Window where all conditions are stored 3.Choosing database 4.Maps that can be joined are yellow 5.Maps that need to be joined through other maps are grey 6.SQL syntax can be automatically generated from created workbook Discoverer workbook wizard 8

Discoverer workbook example 9 Deal count by the structure of the object for each year

Discoverer workbook example Deal count by structure of the object for each year Count of the typical and atypical deals in biggest cities 10

Discoverer workbook example Typical and atypical deal proportion by property type and year All land transactions 11

Required information for ratio analysis Property price Current property appraisal value Land and building use Land area Year of construction Deal time Location parameters Information about whether or not the deal is typical Other characteristics that may be used for different stratum purpose 12

Ratio analysis usage Base value for each zoning is assigned according to the results of ratio analysis Ratio is calculated as AV/PP, where AV is appraised value and PP is property price Desired ratio analysis central tendency measure (such as mean or median) value is ~1.00 We assume that data are statistically significant in area if there are atleast 20 transactions taken place in particular area over chosen time period (atleast 2 years) Results must be in a format that would be easily reviewable for everyone 13

Desired output for ratio analysis 14

Ratio analysis using SPSS Data retrieval using Discoverer Exporting data to Excel Excluding data that is not needed Checking for missing values Predefining grouping variables Inserting data into SPSS Calculating ratio analysis for each data subset Exporting the acquired result to Excel format Formatting to get desired result 15

Ratio analysis using R Done in two ways:  Similar data preperation as with SPSS  Data retrieval by Discoverer  Exporting data to Excel  Preparing data  Saving as.txt file in order to read data in R  Connecting directly to database with RODCB  Allows us to connect to SQL server and use SQL language for data selection in R  Must check if data doesn’t contain errors (missing values, NA’s, data structure, etc.) Calculation and output is the same in both cases Demonstration after presentation 16

Advantages/disadvantages using R over SPSS Disadvantages  Takes some time to compute syntax  Not as user-friendly as SPSS therefore can take lots of time to learn Advantages  Open source software  Less time required for calculations  Data manipulation much faster  Formatting acquired results requires less time and effort  No need for extra preperation files (if second method is used)  Possibility to implement new calculations (that are not available in SPSS) if needed  Any syntax can be modified 17

Adjusment Valuers adjust base values for zonings according to the results that are acquired by calculating ratio analysis If newly constructed building area is the reason for low ratios then new zone is extracted Property group may better fit into neighbouring zone (zone borders are changed) Extra attention towards possibility of atypical transactions Adjusment is done repeatedly until market value is reached with no significant bias 18

GIS (geographical information system) structure 19

GIS layers GIS has multiple layers: Layer of current zonings Layer of administrative borders for different scales Layer of addresses Layer of cadastral groups Layer of cadastral map Layer of base map Layer of orthophoto All kinds of layers can be added depending on what the user wants 20

GIS correction smart tools Copying object to another map layer or copy geometry from one zoning to another Merge zones Creating new zones using parcel borders Changing existing borders using parcel borders Splitting a zone in two Why «smart» tools?  Doing a correction for specific area automatically adjusts nearby areas therefore eliminating the possibility of human mistakes and making whole process faster  Ending correction with automatic topology examination 21

Property usage map example 22

Commercial zoning in Riga 23

Construction year for buildings 24

Example of agricultural land ratio map 25

GIS tools and cadastre map 26

Ratio analysis with R demonstration