1. Using Assessed Values in Property Valuations Dr Song Shi School of Economics and Finance Massey University

2. Motivation Using assessed values to improve the sales comparison approach in property valuations – Identify valuation error sources – How to correct them – Provide new thinking and technique for real estate appraisals

3. Literature The selection and comparison of sales can be sophisticated and complicated – Lentz and Wang (1998) classify the evolution of the appraisal methodologies into three categories – The contemporary adjustment-grid method by Vandell (1991), Gau, et al. (1992, 1994), and Lai, et al. (2008). – Non-traditional regression model,artificial intelligence and spatial analysis methods, e.g. by Peterson and Flanagan (2009), Zurada, et al. (2011), Bourassa, et al. (2010), Osland (2010) and Beamonte, et al. (2013).

4. What Is The Research Problem? However, as pointed out by Epley (1997) all these methods are “based on the presumption that a sufficient number of closed sales of comparable properties always exist in a finite time period such that a statistically reliable sample can be found…The theory is good, but not measurable or applicable (p.175-176)”.

5. Review of The Traditional Sales Comparison Approach

6. The Proposed Approach – “The Improved Net Rate” Analysis

7. An Example of the Improved Net Rate Methodology Comparable salesSale 1Sale 2Sale 3Sale 4Sale 5 Calculations of net rates Total sale price175,000215,000230,000250,000245,000 Less assessed land value38,00081,00087,00052,00078,000 Improvement value137,000134,000143,000198,000167,000 Less other improvements10,00015,000 18,00014,000 Value of the dwelling127,000119,000128,000180,000153,000 Floor area (sqm)130120 Net Rate ($psm)9779921,0671,5001,275 Adjustments of net rates Sales time5.00%3.00%2.00% Building age-3.00%0.00%-5.00%0.00% Construction materials5.00%0.00% 5.00% Condition0.00% -10.00%-15.00% Floor area0.00%-3.00% Modernisation/Character/Appeal0.00% -10.00%-5.00% Total adj.7.00%0.00%-6.00%-21.00%-16.00% Adjusted net rate ($psm)1,0459921,0031,1851,071 Weights on comparable sales30% 15%10%15% Weighted average net rate1,041 Property valuation Floor area of the subject property130sqm Calculated dwelling value135,330 Plus the assessed land value80,000 Plus other improvements10,000 Total current market value of property225,330 Market value breakup Market value of land90,000 Market value of improvements135,330 Current market value of property 225,330say225,000 Notes: For the subject property, its assessed land value is given at $80,000; its market land value is assumed at $90,000. Other improvements value (garage, shed and fencing, etc.) is estimated at $10,000.

8. Estimation Errors In The Proposed Approach “Within” estimation error due to the proposed estimation approach – Controlled and correctable “Outside” estimation error due to the assessment errors in tax assessment – Non-controlled, but its impact is small when adding more sales.

9. The “Within” Estimation Error

10. An Example Of Calculation α, β, γ, δ and The “Within” Estimation Error The “within” estimation error is calculated at 0.3%, assuming δ=15%

11. The “Outside” Estimation Error Due to assessment process and methods Assessment errors are almost unavoidable, but systematic errors such as horizontal and vertical inequities are discouraged – Assessments must meet the minimum compliance requirements (e.g. the IAAO (1999) standard) Empirical test show the systematic errors are small – Allen & Dare (2002); Cornia & Slade (2005); Goolsby (1997) Allen & Dare (2002Cornia & Slade (2005Goolsby (1997 – Clapp (1990); Sirmans, Diskin & Friday (1995); Cornia & Slade (2005)199019952005 – Shi (2014) It is arguable problems of assessment errors in assessed land values are likely to be smaller than assessed values in whole, due to – The Rich GIS information for land and neighbourhoods is ready to obtain – New sophisticated techniques for land valuations (e.g. Clapp (2003), Longhofer and Redfearn (2009), and Özdilek (2012).

12. Empirical Study Area

13. Summarised Statistics Of Dwelling Sales for Palmerston North city, March 2011 to February 2012

14. An Example of Calculated “Within” Estimation Errors

15. Theoretical Simulation Results of “Within” Estimation Errors

16. Theoretical Simulation Results Of “Outside” Estimation Errors

17. Empirical Simulation Results

18. Estimation Strategy

19. Conclusions The method provides a very attractive solution to the traditional sales comparison approach when comparable sales are limited. The impact of assessment errors is small and when more sales are added, the accuracy of valuation is improved. The key assumption is that neighbourhood effects are capitalised into land assessments which are uniformly assessed in an urban residential area. The method is easy to adopt in practice.