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Land Administration and Management Project Phase 2

Real Property Valuation and Land Taxation Report – November 2009

T O W A R D S A R E F O R M P A C K A G E F O RRE AL PROPE RTY TRAN SFE R TAXE S

I N THE PHI LI PPI N E S

FINAL REPORT

November 2009

REPORT D47

Prepared by:

Land Equity International Pty Ltd





Towards a Reform Package for Real Property Transfer Taxes in the Philippines i

ACKNOWLEDGMENTS

This study was conducted in cooperation with the National Tax Research Center (NTRC) ofthe Department of Finance.

A Land Equity International (LEI) consultant, Norman R. Ramos, acted as Property TaxAdvisor. The technical advisory work focused on a) a review of available previous relatedlocal and international studies, relevant data and information; b) development of a revenuesimulation model for real property taxes including the estimation of the relevant numericalparameters; and using the findings and results of the revenue simulations to formulate a

proposed package of tax rate reforms for selected real property transfer taxes.

The team would like to acknowledge the highly relevant technical inputs and suggestionsas well as the organizational support given by the NTRC headed by Executive DirectorLina D. Isorena and Deputy Executive Director Dante V. Sy.

The key NTRC technical personnel led by the Executive Director and the Deputy ExecutiveDirector provided technical papers, data, information and experiences through a series ofmeetings/discussions that helped shape and refine the results of the technical assistancework.

The LAMP 2 PMO provided valuable logistical support to the Property Tax Advisor.

This synchronized and multi-level support enabled the Consultant to effectively functionand meet the extremely tight survey deadline.





Towards a Reform Package for Real Property Transfer Taxes in the Philippines ii

This report is a result of technical assistance managed by Land Equity International to the

Government of the Philippines. The TA was funded by AusAID and the views expressed in this work

do not necessarily represent the views of the Commonwealth of Australia.

TABLE OF CONTENTS

ACKNOWLEDGMENTS i

Table of Contents ii

Tables iii

FIGURES iv

ANNEXES iv

ACRONYMS v

DEFINITION OF TERMS vi

EXECUTIVE SUMMARY 1

1. Introduction 4

2. Analytical Framework 8

3. Statistical estimates of the parameters of the Real Property Market models 22

4. Guiding Points in the Formulation of Real Property Tax Rate Reform Package 30

5. The Proposed Real Property Transfer Taxes Reform Package 37

6. Tax Revenue Simulation Results 39

7. Conclusions and Recommendations 46

REFERENCES 47

Appendix A. Mathematical Derivation of the Elasticity Estimate A-1





Towards a Reform Package for Real Property Transfer Taxes in the Philippines iii

TABLES

Table 1 Parameter Estimates of Chaos-Type GDP Growth Forecast Equation With”

Time Trend Variable

17

Table 2 Parameter Estimates of Chaos-Type GDP Growth Forecast Equation With”

Time Trend Variable

18

Table 3 Regression Estimates for the Parameters of the Gross Value Added in Real

Estate (REGVA) Model

22

Table 4 Regression Estimates for the Parameters of the New Residential Floor Area

(RFA) Model

23

Table 5 Regression Estimates for the Parameters of the New Non-Residential Floor

Area (NRFA) Model

23

Table 6 Regression Estimates for the Parameters of the New Alterations and Repairs

Floor Area (ARFA) Model

24

Table 7 Inverse Matrix and Resulting Output Multipliers, Year 2000 Input-Output

Table

24

Table 8 Effective RPT Rates and Collection Efficiency, All Cities, 2007 25

Table 9 Effective RPT Rates and Collection Efficiency, Cities with 100 or Greater COE

Excluded, 2007

25

Table 10 Alternative “Unadjusted” GDP Forecasts, at Current Prices: 2009-2014 25

Table 11 Base GDP Growth Projections at Current Prices 26

Table 12 Revenue Simulation Results, Alternative Capital Gains Tax Rates, In MillionPhP at Current Prices: 2010-2014

37

Table 13 Revenue Simulation Results, Alternative Reductions in the Documentary

Stamp Tax, In Million PhP at Current Prices: 2010-2014

38

Table 14 Summary of Simulation Results of Tax Reforms Considered in the Short Term:

In Million PhP at Current Prices: 2010-2014

38

Table 15 Revenue Simulation Results, Abolition of the Estate and Donor’s Tax, In Million

PhP at Current Prices: 2010-2014

39

Table 16 Revenue Simulation Results, Impact of Proposed Medium-Term Tax Rate

Reform Package on the Capital Gains Tax, In Million PhP at Current Prices:

2010-2014

39

Table 17 Revenue Simulation Results, Impact of Proposed Medium-Term Tax Reform

Package on the Documentary Stamp Tax, In Million PhP at Current Prices:

2010-2014

40

Table 18 Revenue Simulation Results, Combined Revenue Effect of Proposed Medium-

term Property Transfer Tax Reform Package, In Million PhP at Current Prices:

2010-2014

40

Table 19 Revenue Simulation Results, Combined Revenue Effect of the Proposed

Medium-term Property Transfer Tax Reform Package on the Local Tax on the

Transfer of Land, In Million PhP at Current Prices: 2010-2014

41





Towards a Reform Package for Real Property Transfer Taxes in the Philippines iv

FIGURES

Figure 1 Collection Efficiency and Size of Taxable Property Values, PhilippineProvinces, 2007

3

Figure 2 Collection Efficiency and Size of Taxable Property Values, Philippine Cities,

2007

3

Figure 3 Relationship between the Market for Real Property, Overall Economic Activity,

and the Effective Real Property Tax Rate

5

Figure 4 Structure and Flow of Simulation Model 8

Figure 5 Tracking Performance of Two Alternative Chaos-Type

GDP Growth Forecast Equations

17

Figure 6 Statutory Maximum-Level Estate Tax Rate and

Gross Domestic Capital Formation, Selected Countries: 2005

20

Figure 7 Periodogram Values for Per Capita Local Revenues at 1985 Prices and the

Dummy Variable for Election Years: 1991-2004

31

ANNEXES

Appendix A Mathematical Derivation of the Elasticity Estimate A-1





Towards a Reform Package for Real Property Transfer Taxes in the Philippines v

ACRONYMS

ADB - Asian Development BankARFA - Alterations and repairs floor areaAusAID - Australian Agency for International DevelopmentBIR - Bureau of Internal RevenueBLGF - Bureau of Local Government FinanceCOE - Collection EfficiencyCGT - Capital Gains TaxDILG - Department of Interior and Local GovernmentDOF - Department of FinanceDST - Documentary Stamp TaxDOT - Donor‘s Tax EPTR - Effective Property Tax Rate

EST - Estate TaxGDP - Gross Domestic ProductGDCF - Gross Domestic Capital FormationIO - Input-OutputIRA - Internal Revenue AllotmentLAMP - Land Administration and Management ProjectLEI - Land Equity InternationalLGC - Local Government CodeLGU - Local Government UnitLN - Natural Logarithm, base = e = 2.71238NEDA - National Economic and Development AuthorityNFA - New Floor Area

NRFA - New Non-Residential Floor AreaNSO - National Statistics OfficeNTRC - National Tax Research CenterOLS - Ordinary Least SquaresPMO - Project Management OfficePSY - Philippine Statistical YearbookREGVA - Gross Value Added for Real EstateRFA - New Residential Floor AreaRPT - Real Property TaxSIE - Statement of Income and ExpenditureSMV - Schedule of Market ValuesTTRPO Tax on Transfer of Real Property OwnershipTXAV - Taxable Assessed ValueVAT - Value Added Tax





Towards a Reform Package for Real Property Transfer Taxes in the Philippines vi

DEFINITION OF TERMS

CAPITAL GAINS TAX – originally intended as a tax imposed on the gains presumed to

have been realized by the seller from the sale, exchange or other disposition of capitalassets. As presently applied, however, it has become a fixed sales tax with rate of 6% ofwhichever is higher among the following: Bureau of Internal Revenue‘s zonal value, fair market value of Provincial or City Assessor, or selling price of the property.

CHAOS-TYPE EQUATIONS – are deterministic systems (exhibiting regular andpredictable behavior) that also exhibit seemingly irregular, random, and even turbulentbehavior and are highly sensitive to initial conditions.

COLLECTION EFFICIENCY – ratio of actual amount collected to the total amountcollectible.

CORRELATION ANALYSIS – evaluates causal, complementary, parallel, or reciprocalrelationship, especially a structural, functional, or qualitative correspondence between twocomparable entities.

CROSS SECTION DATA – a series of observations generated across units ofclassification, e.g. cities, municipalities, households, income classes, etc., at a single pointin time. A series of cross-sections across time is known as panel data.

DOCUMENTARY STAMP TAX – tax imposed on documents, instruments, loanagreements, and papers evidencing the acceptance, assignment, sale, or transfer of anobligation, rights, or property incident thereto. Rate is based on a schedule, with PhP 15minimum and 1.5% for consideration exceeding PhP 1,000 for deeds of sale and

conveyances of real property.

DONOR‘S TAX – tax on a donation or gift, imposed on the gratuitous transfer of propertybetween two or more persons who are living at the time of the transfer. When thebeneficiary or donee is a stranger, the tax payable by the donor is 30% of the net gift.When the beneficiary is a relative, the amount of tax is based on a schedule of ratesranging from exempt to 15% of the net gift.

EFFECTIVE PROPERTY TAX RATE – ratio of property tax revenue collection to thecorresponding property tax base.

ESTATE TAX – tax on the right of the deceased person to transmit his/her estate to his/her

lawful heir and beneficiaries at the time of death and on certain transfers which are madeby law as equivalent to testamentary disposition. The amount of tax due is based on aschedule of rates ranging from exempt to 20% of the net estate.

GROSS DOMESTIC CAPITAL FORMATION (GDCF) – is a macroeconomic concept usedin official national accounts and statistically measures the value of additions to fixed assetspurchased by business, government and households less disposals of f ixed assets sold offor scrapped.

GROSS DOMESTIC PRODUCT (GDP) – or gross domestic income (GDI) is a basicmeasure of a country's economic performance and is the market value of all final goodsand services made within the borders of a country in a year. It is a fundamentalmeasurement of production and is often positively correlated with the standard of living.

http://en.wikipedia.org/wiki/Macro-economics

http://en.wikipedia.org/wiki/National_accounts

http://en.wikipedia.org/wiki/Fixed_assets

http://en.wikipedia.org/wiki/Fixed_assets

http://en.wikipedia.org/wiki/National_accounts

http://en.wikipedia.org/wiki/Macro-economics





Towards a Reform Package for Real Property Transfer Taxes in the Philippines vii

GROSS VALUE ADDED (GVA) – a productivity metric that measures the differencebetween output and intermediate consumption. Gross value added provides a peso valuefor the amount of goods and services that have been produced, less the cost of all inputsand raw materials that are directly attributable to that production.

INPUT-OUTPUT MODEL – in economics, an input-output model uses a matrixrepresentation of a nation's (or a region's) economy to predict the effect of changes in oneindustry on others and by consumers, government, and foreign suppliers on the economy.

NATURAL LOGARITHM – logarithm to the base e , where e is an irrational constantapproximately equal to 2.718281828. The natural logarithm is generally written ln(x ),loge (x ) or sometimes, where the base of e is implicit, just log(x ). In simple terms, thenatural logarithm of a number x is the power to which e would have to be raised to equal x .For example, the natural log of e 2 (approximately 7.389) is 2, the natural log of e itself is 1because e 1 = e , while the natural logarithm of 1 would be 0, since e 0 = 1.

NEW FLOOR AREA – new floor area in square meters (sq.m.) constructed consisting ofresidential, non-residential, and alterations and repairs.

NON-LINEAR RELATIONSHIP – is a relationship where there is a wider range of possibledependencies allowed.

PROBIT REGRESSION – an alternative log-linear approach to handling categoricaldependent variables. It is used to analyze relationships between one or more independent(predictor) variables and a categorical dependent variable at two levels. Its assumptionsare consistent with having a categorical dependent variable assumed to be a proxy for atrue underlying continuous normal distribution. The probit model ensures that predictionsfor the dependent variable will always lie between 0 and 1.

REAL PROPERTY TAX – levied on owners of land, building, machinery and otherimprovements; based on the assessed value of the property, which is derived by applyingassessment levels to the fair market value of the property.

REGRESSION ANALYSIS – includes techniques for modeling and analyzing severalvariables, when the focus is on the relationship between a dependent variable and one ormore independent variables. More specifically, regression analysis helps us understandhow the typical value of the dependent variable changes when any one of the independentvariables is varied, while the other independent variables are held fixed. Most commonly,regression analysis estimates the conditional expectation of the dependent variable giventhe independent variables — that is, the average value of the dependent variable when theindependent variables are held fixed.

RIDGE REGRESSION - used when the explanatory variables are highly inter-correlatedand stable estimates of the regression coefficients cannot be obtained through ordinaryleast squares (OLS). Ridge regression adds a constant λ to the diagonal of the correlationmatrix, which is then re-standardized, so that all diagonal elements are equal to 1.0, andthe off-diagonal elements are divided by the constant. In other words, ridge regressionartificially decreases the correlation coefficients so that more stable estimates of the betacoefficients can be computed.

http://en.wikipedia.org/wiki/Economics

http://en.wikipedia.org/wiki/Matrix_(mathematics)

http://en.wikipedia.org/wiki/Logarithm

http://en.wikipedia.org/wiki/Base_(mathematics)

http://en.wikipedia.org/wiki/E_(mathematical_constant)


http://en.wikipedia.org/wiki/Irrational_number

http://en.wikipedia.org/wiki/Dependent_variable

http://en.wikipedia.org/wiki/Independent_variable

http://en.wikipedia.org/wiki/Conditional_expectation

http://en.wikipedia.org/wiki/Conditional_expectation

http://en.wikipedia.org/wiki/Independent_variable

http://en.wikipedia.org/wiki/Dependent_variable

http://en.wikipedia.org/wiki/Irrational_number


http://en.wikipedia.org/wiki/Base_(mathematics)

http://en.wikipedia.org/wiki/Logarithm

http://en.wikipedia.org/wiki/Matrix_(mathematics)

http://en.wikipedia.org/wiki/Economics





Towards a Reform Package for Real Property Transfer Taxes in the Philippines viii

SIMULATION – the process of starting with an initial value in each variable and running theset of equations for multiple time increments. At each time increment, all equations areprocessed to generate new variable values from the current values. The resulting data forvariables at each time increment represents one run of the simulation. During simulation, a

model is driven by input data and produces output data. Data can come from initial valuesin the model, user entry, or a data file.

TIME SERIES – a set of observations generated sequentially in time.

TIME SERIES FORECASTING – a category of forecasting that assumes that the historicaldata is a combination of a pattern and some random error. Its goal is to isolate the patternfrom the error by understanding the pattern‘s level, trend, and seasonality.

TAX ON TRANSFER OF REAL PROPERTY OWNERSHIP – imposed by a province or cityon the sale, donation, barter, or any other mode of transferring ownership or title of realproperty. Maximum rate set by the Local Government Code is 0.5% for provinces and 1%

for cities based on the total consideration involved in the acquisition of the property or fairmarket value, whichever is higher.

VALUE ADDED TAX – business tax imposed and collected from the seller in the course oftrade or business on every sale of properties, lease of goods or properties, or vendors ofservices; an indirect tax and thus can be passed on to the buyer. Imposed on VAT-registered persons with sale/lease above the following amounts: PhP 1.5 million for sale ofresidential lot, PhP 2.5 million for sale of residential house and lot and other residentialdwellings, and PhP 10,000 for monthly rental of residential units.





Towards a Reform Package for Real Property Transfer Taxes in the Philippines 1

EXECUTIVE SUMMARY

The real property market-- land and improvements1 -- is among the oldest asset market in

human history. Social structure, marriage institutions, inter-state relations and, morebroadly, socio-economic organizations, have been affected by and simultaneously haveinfluenced the nature and functioning of real property markets. 2

Housing is a mixed consumption-investment good, and the attributes of commercial realestate are a function of derived demand emanating from the user business sector. Bothtypes of real property demand will ultimately be affected by the state of economy asmeasured by the Gross Domestic Product (GDP).3

The positive impact of growing macroeconomic activity on the demand for real estate is,however, restricted by statutory limitations on land ownership and use. Regulations,especially property tax laws, affect real estate operations and profitability, and

consequently, demand for real estate.

While there is general consensus on the degree of the positive impact of the macro-leveleconomic performance on the real property market, the degree to which property taxesaffect the real estate market and tax compliance is a subject of continuing debate.

The tax instruments used by governments to raise revenues can have an impact on thenature, location, and density of development. Urban form can be influenced not only withplanning tools but also with financial tools. In some cases, financial tools work togetherwith planning tools, but in other cases they may have the opposite effect.4 Changes in taxrates could also affect tax compliance.

The total market for real property estate is a function of the economic activity as measuredby the country‘s Gross Domestic Product (GDP) and effective real property tax rate(EPTR).

The Philippine real property market as measured in value terms — gross value added forreal estate at current prices — and physical area terms — new floor space construction — positively responds to changes in economic activity (Δ GDP) and negatively related tochanges in tax rates (Δ EPTR).

In the Philippines, landowner reactions to changes in the aforementioned economicvariables in terms of both magnitude and speed may be affected by the strong attachmentof Filipinos to land. People may ―hold on to their land even if not economically viable‖ 5 or

1Collectively referred to as real estate.

2 See Ashok Bardhan and Robert Edelstein. ―Real Estate Through The Ages: The Known, The Unknown, and

The Unknowable,‖ in Diebold, Doherty and Herring, eds., The Known, The Unknown, and the Unknowablein Risk Management. Princeton: Princeton University Press, 2007.

3 The phenomenon of globalization has added another dimension affecting both the level and quality of

demand for commercial real estate. 4

See a study of 25 countries by Richard M. Bird and Enid Slack, eds., Land Taxation in Practice: Selected

Case Studies , Toronto, March 2002. 5 This has been succinctly pointed out by NTRC Executive Director Lina D. Isorena and Deputy Executive

Director Dante V. Sy during a discussion held 24 September 2009.






even resort to ―outright violence to defend their real property holdings against publicauctions of tax delinquent properties‖6.

The net tax revenue effect of reductions in real property tax rates will be a balance of the

revenue reductions arising from the rate cutbacks vis-à-vis the potential positive revenueeffects of the resulting increase in the revenue base (REGVA) through the tax rate effectand the increase in GDP due to the increased real property market activity via the multipliereffect of the property sector.

The revenue effect of the tax reforms will come from increased real property marketactivities arising from the direct tax rate effect and the secondary income effect arising froman increased GDP stimulated by increased property market activities.

Considering a) the revenue yield aspects, b) fiscal decentralization and growth aspects, c)administrative cost aspects, d) taxpayer resistance aspects, and e) the governmentviewpoint, the focus of the proposed property tax reform program will be the four (4)

national property transfer taxes — Capital Gains Tax (CGT), Documentary Stamp Tax(DST), Estate Tax (EST), and Donor‘s Tax (DOT).

The Value Added Tax (VAT) on the sale and lease of real property option is not at thispoint considered a politically viable option given that it will require redefining the concept ofVAT and amending a recent piece of legislation that had faced stiff public resistance.

Reforming the local Tax on the Transfer of Real Property Ownership (TTRPO) will requireamending the 1991 Local Government Code (LGC), which may not be easily doneconsidering that amendments to the LGC have been brought up as early as the 1998-2001Congress and no progress has been attained since then.

The tax reform package proposes combined tax rate changes that seek to:

a) Reduce property transfer taxes to stimulate the real property sector and toencourage formalization of property transfers. Such stimulative effects areexpected in the long-run to more than compensate for revenue losses arising fromthe rate reduction or even elimination of certain property taxes.

b) Do away with property related taxes that have relatively low revenue yields vis-à-visadministrative costs.

c) Maintain revenue neutrality during the critical first year of the projection period — 2010.

Reduction or abolition of certain property transfer taxes like the EST and DOT could in thelong-run enhance the volume of property market transactions, encourage tax complianceand thus, enhance revenues from the other remaining property taxes. Expected to bebenefitted are the CGT, the DST and the TTRPO.

In 2010, the Department of Finance (DOF) could seriously consider reducing the CGT ratefrom the present 6% to 5%, and effecting a 10% reduction in the DST. These tax breakswill help boost the real property market during the present economic downturn and result inimproved revenue collection. At the same time, if implemented or even publicly announced

6 This has been observed in many LGUs across the Philippines, a few of which were personally observed by

the Advisor.






by 2010, it can boost the popularity rating of the present administration in an election year.

a) The expected annual average net increase in CGT revenues arising from theproposed 1% CGT tax rate cut for the period 2010-2014 is about PhP 1.2 billion .

The proposed tax rate cut is expected to be revenue neutral if implemented in 2010.The present value of the potential net revenue gain from the 1% CGT rate cutbetween 2010 and 2014 (―with reform‖ less ―without reform‖ tax revenues) at adiscount rate of 4.5%7 could be expected at PhP 5.1 billion.

b) The expected annual average net increase in DST revenues arising from theproposed 10% DST tax rate cut for the period 2010-2014 is about PhP 343 million .The proposed tax rate cut is expected to be revenue neutral if implemented in 2010.The present value of the potential net revenue gain from the 10% to 15% DST ratecut between 2010 and 2014 (―with reform‖ less ―without reform‖ tax revenues) at adiscount rate of 4.5%8 could be expected reach PhP 1.5 billion.

Beyond 2010, the DOF should seriously consider adopting the proposed real propertytransfer tax reform package consisting of a) halving both the CGT and DST rates and b)abolition of the EST and the DOT .

a) The abolition of the EST and the DOT is in line with current international practicesin both developed and developing countries.

b) It will result in higher national revenue collections from real property transfer taxesas the expected increases in the revenue collection from the CGT and DST arisingfrom the implementation of the overall tax rate reform package will more than offset the revenue losses from the abolition of the EST and DOT .

The annual average net national revenue gain from the proposed tax ratereform package is projected at PhP 7.0 billion for the period 2010-2014,and the present value of the net revenue gain attributable to the reformpackage for the period is estimated at PhP 30.1 billion .

c) It will also help improve LGU collection from the local TTRPO. For provinces withtheir relatively limited revenue base, the improvement could be critical in their drivefor lesser dependence on the Internal Revenue Allotment (IRA).

The reform package at the national level can be expected to result inannual average TTRPO collection of PhP 2.6 billion over the five-yearperiod or about double the PhP 1.3 billion average annual TTRPO revenues

from 2003 to 2007. The present value of the net revenue effect of thenational transfer tax reform package on the TTRPO is estimated at PhP 5.6 billion over the 5-year period.

7This is the current 1-year Treasury Bill rate. The T-Bill rate serves as the opportunity cost of property taxrevenues raised since government revenue shortfalls are financed through borrowings.

8This is the current 1-year Treasury bill rate. The T-Bill rate serves as the opportunity cost of property taxrevenues raised since government revenue shortfalls are financed through borrowings.






1. INTRODUCTION

The real property market-- land and improvements9 -- is among the oldest asset market inhuman history. The significance of various types of real property assets (agricultural,

residential and commercial real estate assets) in human history is well known in terms ofboth oral and written stories. Social structure, marriage institutions, inter-state relationsand, more broadly, socio-economic organizations, have been affected by andsimultaneously have influenced the nature and functioning of real property markets. 10

In terms of the risk-return trade-off, real estate is either lower or at par with the risk-returnprofile of common stocks, and higher risk-reward than Treasury Bills (T-Bills), municipalbonds, mortgage backed securities, and investment grade corporate bonds, in that order.11

Housing is a mixed consumption-investment good, and the attributes of commercial realestate are a function of derived demand emanating from the user business sector. Bothtypes of real property demand will ultimately be affected by the state of economy asmeasured by the Gross Domestic Product (GDP).12

The positive impact of growing macroeconomic activity on the demand for real estate is,however, restricted by statutory limitations on land ownership and use. Every nationimposes certain public limitations on land ownership and use for the common good of allcitizens. Four forms of governmental control include: 13

a) Taxation -- Power to tax the land to provide public revenue and to return to thecommunity the costs incurred to pay for the various public benefits, services andenvironmental protection, which are provided by the government;

b) Eminent Domain -- Right to use, hold or take land for common public uses andbenefits;

c) Police Power -- Right to regulate land use for the welfare of the public, in the areasof safety, health, morals, general welfare, zoning, building codes, traffic regulationsand sanitary regulations; and

d) Escheat -- Right to have land revert to the public's agent, the government, whentaxes are not paid or when there are no legal heirs.

These regulations, especially property tax laws, affect real estate operations andprofitability, and consequently, demand for real estate.

While there is general consensus on the degree of the positive impact of the macro-leveleconomic performance on the real property market, the degree to which property taxesaffect the real estate market and tax compliance is a subject of continuing debate.

9Collectively referred to as real estate.

10 See Ashok Bardhan and Robert Edelstein. ―Real Estate Through The Ages: The Known, The Unknown, and

The Unknowable,‖ in Diebold, Doherty and Herring, eds., The Known, The Unknown, and the Unknowablein Risk Management. Princeton: Princeton University Press, 2007.

11Ibid.

12 The phenomenon of globalization has added another dimension affecting both the level and quality of

demand for commercial real estate. 13

See Chapter 2 of the Philippine land market study prepared by the Property Tax Policy Adviser in LAMP 1-DENR. Final Report: Land Markets Study . Manila, May 2004.






The tax instruments used by governments to raise revenues can have an impact on thenature, location, and density of development. Urban form can be influenced not only withplanning tools but also with financial tools. In some cases, financial tools work togetherwith planning tools, but in other cases they may have the opposite effect. 14

Changes in tax rates could also affect tax compliance. In the Philippines, for example,where the nominal annual real property tax (RPT) rate is as high as 2% to 3%, 15 theeffective rate has been estimated at only 0.07% during the early nineties.16

The effective real property rate is defined as the Effective Annual Property Tax Rate(EPTR) which is equal to the Real Property Tax Collected in Year t (RPTt) divided by theTaxable Assessed Value in Year t-1(TXAVt-1), or:

(1.0)

where: EPTR = Effective Annual Property Tax RateRPT t = Real Property Tax collected in year tTXAV t-1 = Taxable Assessed Value in year t-1

Effective rates have since then improved but are still below the nominal rates. Available2007 RPT collection and local government unit (LGU) property assessment data from theBureau of Local Government Finance (BLGF)17 indicate that the average effective RPTrates for cities stand at 1.67% (1.81% for Metro Manila cities and 1.44% for cities outsideMetro Manila).18 For provinces, the average effective property tax rate is only 0.55%.

The same set of data indicates no statistically significant relationship between collectionefforts and the size of taxable property values. Larger property tax bases do not

necessarily get translated to more intensive and productive collection efforts.

Collection Efficiency (COE) for the real property tax is defined as the Real Property TaxCollected in Year t (RPTt) divided by the Total RPT Collectible in Year t, or:

(2.0)

where: COE = Collection Efficiency for Real Property TaxRPT t = Real Property Tax collected in year tRPT Collectible = Total Real Property Tax Collectible in year t

14See a study of 25 countries by Richard M. Bird and Enid Slack, eds., Land Taxation in Practice: Selected Case Studies , Toronto, March 2002.

15The total RPT rate cannot really go down below 1% since the 1991 Local Government Code pegs theSpecial Education Fund (SEF) tax rate at 1%.

16See Milwida M. Guevara, Joyce P. Gracia, and Ma. Victoria C. Espano, ―A Study of the Performance andCost Effectiveness of the Real Property Tax,‖ Manila, July 15, 1994 as cited in Bird and Slack.

17There is probably an upward bias in these average results as the real property tax (RPT) collection figuresinclude arrears and penalties that artificially increase the current year performance.

18116 cities and 79 provinces with complete data were represented in the sample.






Figure 1. Collection Efficiency and Size of Taxable Property Values,Philippine Provinces, 2007

Figure 2. Collection Efficiency and Size of Taxable Property Values,

Philippine Cities, 200719

Given these complex interactions, real property tax reform efforts in the Philippines havebecome more of a political exercise as it is a technical study.

19Collection efficiencies close and above 100% are due to the inclusion of arrears and penalties in the RPTcollection data for the year.






This technical report presents a quantitative model that views the real property marketmodel as basically a demand function for real property with demand being influenced by anincome effect and a tax effect. The quantitative model also includes a GDP forecastingmodule with a ―chaos-type‖ structure. The developed model can be used to simulate20 the

impact of alternative real property tax rate reforms for use as technical inputs in theformulation of a package of reforms for selected property taxes in the Philippines. Taxrevenue simulation results for alternative real property transfer tax rate reforms using themodel are also presented. Based on the simulation results, a proposed set of short- andmedium-term tax rate reforms are proposed for a selected set of national real propertytransfer taxes.

Chapter 1 of this paper sets the background and describes the content of the paper.

Chapter 2 lays down the analytical framework, the structure of the simulation model, andthe GDP forecasting module.

Chapter 3 presents the results of the statistical analyses on the real property marketmodels as well as the alternative GDP forecasts.

Chapter 4 lays out the key points and considerations that guided the choice of the realproperty transfer taxes to be considered for inclusion in the tax package subjected to taxrate reform analysis.

Chapter 5 presents the tax rate reform package subjected to revenue simulation.

Chapter 6 shows the revenue simulation results for selected national real property transfertaxes — the Capital Gains Tax (CGT), the Documentary Stamp Tax (DST), the Estate Tax

(EST), and the Donor‘s Tax (DOT).

Chapter 7 summarizes the proposed recommendations.

Appendix A sets out the mathematical derivation of the elasticity estimate.

20Simulation is the process of starting with an initial value in each variable and running the set of equations for

multiple time increments. At each time increment, all equations are processed to generate new variablevalues from the current values. The resulting data for variables at each time increment represents one runof the simulation. During simulation, a model is driven by input data and produces output data. Data can

come from initial values in the model, user entry, or a data file. See Harold Hableib. ―System Models andSimulation.‖ The Project Perfect White Paper Collection in www.projectperfect.com.au, July 11, 2007.

http://www.projectperfect.com.au/








2. ANALYTICAL FRAMEWORK

This section sets out the conceptual basis and the theoretical framework that served as thebasis for the formulation of the simulation model. Section 2.1 presents the analytical model

that formalizes the interactions between real property markets, macroeconomic activitylevel, and real property tax rates. Section 2.2 lays out the form of the empirical equation,parameters of which are estimated from available time series and cross-section data.Section 3 presents the statistical techniques used in estimating the parameters.

2.1. Analytical Model

The demand for physical space comes from different types of users: residential,commercial or industrial. These users need to maintain the same level of space servicesthat may have been reduced by demolition or withdrawal. In equilibrium, the supply ofproperty should be equal to the demand at various levels of property prices. 21

The impact of real property taxes on the market for real estate measured in terms of GrossValue Added for Real Estate (REGVA) or new floor space construction (FA) is shown inFigure 3. Both will be analyzed in this paper. However, since property tax is imposedbased on value per area rather than floor area per se, it was deemed that the propertymarket expressed in value terms (REGVA) be the one utilized for simulation purposes.

Figure 3. Relationship22

between the Market for Real Property,Overall Economic Activity, and the Effective Real Property Tax Rate

21Property prices respond to demand changes and over time, such price changes are translated to newconstruction (with corresponding financing sources) to keep the market in equilibrium.

22

The relationship need not be linear. The linear representation was made to simplify the graphicpresentation. In fact, the empirical equation used in the simulations posited a ―power curve‖ in log -linearform.






The total market for real property estate is a function of the economic activity as measuredby the country‘s Gross Domestic Product (GDP) and effective real property tax rate(EPTR). Mathematically, this can be expressed as:

M = f(GDP, EPTR) (3.0)

where: GDP = Gross Domestic ProductEPTR = Effective Real Property Tax Rate

As the solid market line M023 indicates, there is an inverse (or negative) relationship

between real property tax rates (EPTR) and the market for real estate (M0).24 Whenever

there is an increase (decrease) in the property tax rate while keeping economic activitylevel constant, quantity demanded decreases (increases) correspondingly.25

On the other hand, the level of economic activity as measured by the GDP positively (directrelationship) affects the real property market. Whenever economic activity increases (or

decreases), there is a corresponding upward (or downward) shift in the real propertymarket.26

In the Philippines, landowner reactions to changes in the aforementioned economicvariables in terms of both magnitude and speed may be affected by the strong attachmentof Filipinos to land. People may ―hold on to their land even if not economically viable‖27 oreven resort to ―outright violence to defend their real property holdings against publicauctions of tax delinquent properties.‖28

The structure of the simulation model is presented in Figure 4.

A reduction in the tax rate will result in a direct tax rate effect consisting of:

a) Reduction in tax revenues as a direct immediate result; and

b) Increase in the real property revenue base as measured by the Gross ValueAdded in Real Estate (REGVA) due to:

people undertaking a larger volume of real property transactions; and

more people formalizing their property transactions.

23The market line need not be linear, it could be curvilinear.

24This is so because the real property tax acts as a tax on capital and increases the cost, and consequently,the selling price of real estate. In some research work, the effective property tax rate is referred to as a ―taxprice.‖ The market curve in Figure 3 shows the relationship between the tax price (EPTR in this case) ofreal estate and real property market size while keeping the level of economic activity (GDP) constant.

25This downward (or upward) movement along the same market line (often referred to in the literature as achange in quantity demanded ) is illustrated by the downward (or upward) sloping arrows on top andparallel to M0.

26Whenever the level of economic activity changes, the entire market line correspondingly shifts upwards (asindicated by dashed market line M2) or downwards (as indicated by dashed market line M1).

27 This has been succinctly pointed out by NTRC Executive Director Lina D. Isorena and Deputy Executive

Director Dante V. Sy during a discussion held on 24 September 2009. 28

This has been observed in many LGUs across the Philippines, a few of which were personally observed bythe Advisor.






Figure 4. Structure and Flow of Simulation Model






Because of the multiplier effect, the increase in economic activities in the real estate sectorwill also increase economic activities in related sectors such as construction, mining andquarrying, manufacturing, services and finance. All the increased economic activities willincrease the total economy as measured by GDP.

The increase in GDP will have a second round income effect, leading to an additionalincrease in REGVA.

The net tax revenue effect of reductions in real property tax rates will thus be a balance ofthe revenue reductions arising from the rate cutbacks vis-à-vis the potential positiverevenue effects of the resulting increase in the revenue base (REGVA) through the tax rateeffect and the increase in GDP due to the increased real property market activity via themultiplier effect of the property sector.

The revenue effect of the tax reforms will come from increased real property marketactivities arising from the direct tax rate effect and the secondary income effect arising from

an increased GDP stimulated by increased property market activities.

The model will estimate the initial REGVA ―with‖ and ‗without‖ tax reform. The multiplier

effect of the REGVA on the GDP will then be estimated and the 2nd round effect of theincreased GDP on REGVA calculated. Based on 1988 to 2008 data, the country‘s GDP --―with‖ and ―without reform‖ -- will be forecasted using a chaos-type time trend equation.The primary (initial tax rate effect on GVARE) and secondary (second round GDP effect onGVARE) net tax revenue resulting from the tax reform will be measured and its presentvalue derived using the current Treasury-Bill rate of 4.5%.

2.2 The Empirical Real Property Market Models

Two empirical real property market models will be tested against available time series data.The first model has gross value added in real estate (REGVA) as the dependent variablewhich is measured in peso terms (‗000 PhP) at current prices while the second model hasnew floor space construction (FA) as the dependent variable which is measured in floorarea (‗000 sqm.).

2.2.1 Gross Value Added in Real Estate as a Measure of the Real Estate Market

The empirical counterpart of the conceptual model presented in 2.1 in value terms is shownas Equation 1.0.

REGVAt = a0 + a1 * GDPt + a2 * EPTRit (4.0)

where: REGVAt = Gross Value Added in Real Estate in million PhP at current prices in year t

GDPt = Gross Domestic Product in million PhP at current prices year t

EPTRit = the effective property tax rate in percent for property tax type i in year t

a0 = the intercept

a1 = the change in REGVA resulting from a unit change in GDP keeping EPTR

constant (

) 29

29Mathematically, a1 and a2 are interpreted as the partial derivatives (denoted by ∂) of REGVA with respect toGDP and EPTR, respectively.






a2 = the change in REGVA resulting from a unit change in EPTR keeping GDP

constant (

)

The expected signs are (+) for a1 and (-) for a2.

2.2.2 New Floor Space Construction as a Measure of the Real Estate Market

The empirical counterpart of the conceptual model presented in 2.1 in terms of additionalphysical space constructed is shown as Equation (5).

NFAkt = a0 + a1 * GDPt + a2 * EPTRit (5.0)

where: NFAkt = new floor space construction of type k in year t with k = residential (RFA),non-residential (NRFA), and alteration/addition/repairs (ARFA)

GDPt = Gross Domestic Product in million PhP at current prices year tEPTRit = the effective property tax rate in percent for property tax type i in year t

a0 = the intercept

a1 = the change in NFAkt resulting from a unit change in GDP keeping EPTR

constant (

)

a2 = the change in NFAkt resulting from a unit change in EPTR keeping GDP

constant (

)


To derive the elasticities of the property market (REGVA) with respect to the economicactivity level (GDP) and the effective real property tax rate (EPTR), Equations (4.0) and(5.0) were transformed to their respective natural logarithmic forms30 shown as Equations

(6.0) and (7.0).

LN REGVAt = LN a0 + a1 * LN GDPt + a2 * LN EPTRit (6.0)

LN NFAkt = LN a0 + a1 * LN GDPt + a2 * LN EPTRit (7.0)

where: LN = natural logarithm, variables are as previously defined in Equations (4.0) and(5.0)

LN a0 = intercept in logarithmic form

a1 = % change in REGVA or NFA as the case may be resulting from a 1% change

in GDP keeping EPTR constant: ( Δ

Δ ) or (

Δ

Δ

a2 = % change in REGVA or NFA as the case may be resulting from a 1% change

in EPTR keeping GDP constant: ( Δ

Δ ) or (

Δ

Δ


30See Appendix A for the mathematical derivation.






The equations were estimated with the intercept LN a0 = 0 since if GDP = 0, then REGVA,a component of the GDP, is necessarily equal to zero, and there will be no newconstruction.

2.3 Related Models

2.3.1 Output Multiplier Effect of the Real Property Markets

The impact of the increased real estate market activity (REGVA) on GDP will be measuredbased on the following natural log regression equation (Equation 8.0) relating GDP in year tto REGVA in year t.

LN GDPt = a1 * LN REGVAt (8.0)

where; LN = natural logarithm

GDPt = Gross Domestic Product in million PhP at current prices in year t

a1 = % change in GDP resulting from a 1% change in REGVA: ( Δ

Δ )

REGVA = Gross Value Added in Real Estate in million PhP at current prices in year t

The full impact of REGVA on GDP – the total industry activity multiplier – will be fullyrealized within the current year. Regression runs indicate that almost all of the multipliereffects occur within the year in which the real estate expenditure was made with only0.02% spilling over to the next year.

2.3.2. Real Property Tax Rates and Tax Compliance

The impact of statutory real property tax rates on compliance as proxied by the collectionefficiency (COE) rate will be measured against available 2007 city level data using theelasticity measure shown in Equation (9.0).

(9.0)

where: COE = Collection Efficiency for the Real Property Tax (see Equation 2.0)EPTR = Effective Real Property tax rate (see Equation 1.0)

Note that this model could not be tested against provincial data because there was novariation in the statutory RPT rate imposed by provinces. In addition, no municipal levelproperty assessment data could be secured.

2.3.3 National Transfer Taxes and the Local Tax on the Transfer of Real PropertyOwnership (TTRPO)

The TTRPO is the last tax to be paid by a real property transferor after the CGT for a saleand EST and DST for an inheritance or a donation followed by the DST in order toformalize/legalize the transfer.

With no change in the TTRPO rate and assuming the same assessment and collection,efforts by LGUs, the potential effect of the proposed national transfer tax reform packageon the TTRPO will be made to depend on the statistical relationship between the TTRPO






and the CGT — the biggest and first tax to be paid during the transfer formalizationprocess. This relationship is as follows:

LN TTRPOt = a1 * LN CGTt (10.0)

where; LN = natural logarithm

TTRPOt = Tax on the Transfer of Real Property Ownership in million PhP at currentprices in year t

a1 = % change in TTRPO resulting from a 1% change in CGT: ( Δ

Δ )

CGT = Capital Gains Tax in million PhP at current prices in year t

2.4 Statistical Estimation Techniques

In most of the cases, ordinary least squares (OLS) regression techniques using the

regression module of Microsoft EXCEL 2007 or the General Regression Module (GRM) ofSTATISTICA 6.0 were utilized in estimating the regression parameters.31

In cases where simple correlation analyses indicated significant multi-collinearity betweenthe explanatory variables, ridge regression technique using STATISTICA 6.0 was used inestimating the regression coefficients.32

2.5 The GDP Forecasting Module

A key driver of the analytical model used to simulate the revenue effects of the selectedproperty tax reform proposals is the level of economic activity represented by the GrossDomestic Product (GDP) at current prices.

This section presents the results of the GDP forecasting efforts done by the consultant interms of the alternative forecasting techniques used and the results of the application ofsuch techniques on available Philippine national income accounts data.

The alternative forecasting techniques used were all based on time series models since thelimited amount of time available to the Consultant precluded the estimation and use of full-blown econometric models of the Philippine economy. Furthermore, given the relativelyshort forecast period of six years, the use of time series analysis models will probably yieldbetter growth forecasts in terms of ―closeness‖ to the historical growth performances asinternational forecasting experiences have shown.

One of the models ―tracked‖ seemingly chaotic movements of the annual percentagechanges in GDP between 1990 and 2008 based on ―chaos‖ model principles. This timeseries model with a ―chaos type‖ structure was used to estimate GDP data to generate thetrend ―without tax reform‖ GDP forecasts.

31Since no categorical or dummy explanatory variables are used in the model, the two regression modulesyield identical results.

32Ridge regression is used when the explanatory variables are highly inter-correlated and stable estimates ofthe regression coefficients cannot be obtained through ordinary least squares (OLS). Ridge regressionadds a constant λ to the diagonal of the corr elation matrix, which is then re-standardized, so that alldiagonal elements are equal to 1.0, and the off-diagonal elements are divided by the constant. In other

words, ridge regression artificially decreases the correlation coefficients so that more stable estimates of thebeta coefficients can be computed. See A. E. Hoerl. ―Application of Ridge Analysis to RegressionProblems,‖ Chemical Engineering Progress , 58, 54-59.






The period of analysis is limited to five (5) years. Beyond five years the forecast errors forthe ―without tax reform‖ GDP becomes too large making the forecasts statisticallyunreliable.

To make the multi-year net revenue effects comparable across time, they are converted totheir present value equivalent using the 1-year T-Bill rate as the discount rate. The T-Billrate serves as the opportunity cost of property tax revenues raised since governmentrevenue shortfalls are financed through borrowings.

2.5.1 Time Series Forecasting and Models

Time series is a set of observations generated sequentially in time. The usage of timeseries models is two-fold:

a) obtain an understanding of the underlying forces and structures that producedthe observed data; and

b) fit a model and proceed to forecasting and monitoring.

Time series forecasting is a category of forecasting that assumes that the historical data isa combination of a pattern and some random error. Its goal is to isolate the pattern fromthe error by understanding the pattern‘s level, trend, and seasonality.33

A simple and pragmatic model for a time series would be to consider each observation asconsisting of a constant (b ) and an error component (Epsilon ), that is:

Xt = b +t.

The constant b is relatively stable in each segment of the series, but may change slowlyover time.

For this study, three (3) major non-seasonal time series models were utilized in developingalternative GDP forecasts.

2.5.2. Single Exponential Smoothing Model

One way to isolate the true value of b , and thus the systematic or predictable part of theseries, is to compute a kind of moving average, where the current and immediatelypreceding ("younger") observations are assigned greater weight than the respective older

observations. Simple exponential smoothing accomplishes exactly such weighting, whereexponentially smaller weights are assigned to older observations. The specific formula forsimple exponential smoothing is:

S[1]t = *Xt + (1-)*St-1 (11.0)

where S[1]t = single exponential smoothing ―smoothed‖ estimate for time period t

Xt = historical value at time t

α = smoothing constant between 0 and 1.

33In this particular case, the data are annual so seasonality is not a concern.






When applied recursively to each successive observation in the time series, each newsmoothed value (forecast) is computed as the weighted average of the current observationand the previous smoothed observation; the previous smoothed observation was computedin turn from the previous observed value and the smoothed value before the previous

observation, and so on. Thus, in effect, each smoothed value is the weighted average ofthe previous observations, where the weights decrease exponentially depending on thevalue of parameter (alpha ). If is equal to 1 (one) then the previous observations areignored entirely; if is equal to 0 (zero), then the current observation is ignored entirely,and the smoothed value consists entirely of the previous smoothed value (which in turn iscomputed from the smoothed observation before it, and so on; thus all smoothed valueswill be equal to the initial smoothed value S 0 ). Values of in-between will produceintermediate results. Regardless of the theoretical model for the process underlying theobserved time series, simple exponential smoothing will often produce quite accurateforecasts.34

A trend component may be included in the exponential smoothing process, wherein an

independent trend component is computed for each time, and modified as a function of theforecast error and the respective parameter. If the (gamma) parameter is 0 (zero), thenthe trend component is constant across all values of the time series (and for all forecasts).If the parameter is 1, then the trend component is modified "maximally" from observationto observation by the respective forecast error. Parameter values that fall in-betweenrepresent mixtures of those two extremes.

Two alternative trend components were tried in the analyses:

a) a linear trend; and

b) an exponential trend.

1) Linear Trend

The introduction of a linear trend assumes that the level of a particular variable slowlyincreases across time by a fixed absolute amount over time (the linear trend component).

In order to compute the smoothed value (forecast) for the first observation in the series,both estimates of S0 and T0 (initial trend) are necessary. By default, these values arecomputed as:

T0 = (Xn-X1)/(N-1) (12.0)

where N is the length of the series; and

S0 = X1-T0/2. (13.0)

The single exponential smoothing with a linear trend GDP forecasts were based on α =

0.10 and γ = 0.10.

34Empirical research has shown simple exponential smoothing to be the best choice for one-period-aheadforecasting, from among 24 other time series methods and using a variety of accuracy measures. See

Makridakis, S., Andersen, A., Carbone, R., Fildes, R., Hibon, M., Lewandowski, R., Newton, J., Parzen, R.,& Winkler, R. (1982). The accuracy of extrapolation (time series) methods: Results of a forecastingcompetition. Journal of Forecasting , 1, 11-153.






The mean average percent error (MAPE) is 3.27%.35

2) Exponential Trend

The introduction of an exponential trend assumes that the variable being forecastincreases by a certain percentage or factor, resulting in a gradual exponential increase inthe absolute value of the variable.

To compute the smoothed value (forecast) for the first observation in the series, bothestimates of S0 and T0 (initial trend) are necessary. By default, these values are computedas:

T0 = (X2/X1) (14.0)

and

S0 = X1/ T0 (15.0)

The data was further smoothened using the 4253h filter provided in STATISTICA 6.0. Thistransformation consists of several passes of moving average/median smoothing, and is apowerful filter for smoothing a series. The following transformations were performed:

a) A 4-point moving median centered by a moving median of 2;

b) A 5-point moving median;

c) A 3-point moving median;

d) A 3-point weighted moving average using Hamming weights36

(.25, .5, .25);

e) Residuals were computed by subtracting the transformed series from theoriginal series;

f) Steps 1 through 4 above were then repeated for the residuals; and

g) The transformed residuals were added to the transformed series.

In practice, this filtering method often produces a smooth series while maintaining thesalient characteristics of the original series.

The single exponential smoothing with an exponential trend GDP forecasts were alsobased on α = 0.10 and γ = 0.10.

The mean average percent error (MAPE) is 2.69%.

35This means that on the average, estimated values differed from the actual values by 3.27%.

36The process smoothens out spikes in the data via a weighted moving average transformation. This weight

function will assign the greatest weight to the observation being smoothed in the center of the window, andincreasingly smaller weights to values that are further away from the center. The weights are standardizedso that their sum is 1.






2.5.3. Double Exponential Model

The double exponential model applies single exponential smoothing twice, once to theoriginal data and then to the resulting single exponential smoothed data.

Crystal Ball Predictor (a simulation and forecasting add-in to Microsoft EXCEL) uses Holt‘sdouble exponential smoothing as follows:

S[2]t = β * S[1]t + (1 – β) * S[2]t-1 (16.0)

Where S[2]t = double exponential smoothing ―smoothed‖ estimate for time period t

S[1]t = single exponential smoothing ―smoothed‖ estimate for time period t

β = smoothing constant between 0 and 1, which may or may not bedifferent from the

The double exponential model forecasts based on the raw GDP time series data werebased on α = 0.945 and a β = 0.923.

The double exponential model forecasts based on the 4253H-filtered GDP time series datawere based on α = 0.999 and β = 0.999.

2.5.4. Chaos-Type Model

Chaos-type equations are deterministic systems (exhibiting regular and predictablebehavior) that also exhibit seemingly irregular, random, and even turbulent behavior andare highly sensitive to initial conditions.

Seemingly chaotic movements of the annual percentage changes in GDP (∆ GDPt) from1990 to 2008 shown in Figure 5 were statistically modeled using the two alternativedynamic equations: 37

a) One with a time trend variable, and

b) Another without:

The equation with a time trend variable shows a better performance in terms of tracking the―turning points‖ in Figure 5 although the statistical significance of the time trend variable isonly 0.76.38

The lagged change in GDP (∆ GDPt-1) follows usual time series models where the pastperiod‘s value affects the current period value. Introducing a quadratic GDP termintroduces a ―hump ‖ — in this case a maximum. Changes or variations in the value of

37 They are considered dynamic because of the time lag elements. The form of the equation used is as

follows:

* Square Root of the Time Trend (t,, ,…,n 38

The time trend variable is represented by the square root of time. The statistical significance of the

regression coefficient of the square root of time is computed as 1 – probability of insignificance (0.24 in Table1) = 0.76. The relatively low statistical significance of the time trend variable is probably due to the presenceof strong multicollinearity between the variable and the explanatory variables ∆ GDPt and ∆ GDPt-1.






variables like GDP and prices have been observed to be proportional to the square root of the time .39

The election variable introduces a cyclical element wherein elections ―dampen‖ the

growth of the economy probably due to the uncertainties and fears generated byadministration changes. The uncertainty generated by the constant challenge, e.g., EDSA3, to the legitimacy of the presidency between 2001 and 2003 dampened the growth of theeconomy. The extraordinary huge presidential election expenditures in 2004 boosted thegrowth of the economy.

The standard errors of estimate of both equations (See Tables 1 and 2) are within 15% oftheir mean historical values from 1990 to 2008.

Given the better historical tracking performance of the chaos model with a time trendvariable, the model forecasts were the ones adopted as ―unadjusted‖ GDP base forecasts.

Adjustments were made on the original and unadjusted model forecasts using thedeviations of the model projections for 2009 and 2010 from the Asian Development Bank

(ADB) revised forecasts for those years —

. The adjustment

factors linearly increases40 based on the assumption that it will take about 5 years beforethe Philippine economy can fully get back to its modeled potential growth path from the2009 downturn. The ―adjusted‖ GDP growth projections at current prices are presented inTable 11 in Chapter 3.

39See Regnault Jules. 1863. Calcul des chances et philosophie de la Bourse. Paris: Mallet-Bachelier. Asquoted by Benoit Mandelbrot in Mandelbrot, Benoit. 2004. The (Mis)Behavior of Markets: A Fractal View of Risk, Ruin and Reward . New York: Basic Books, p. 283.

40The deviation from the potential growth path correspondingly declines.






Figure 5. Tracking Performance of Two Alternative Chaos-TypeGDP Growth Forecast Equations

Table 1. Parameter Estimates of Chaos-Type

GDP Growth Forecast Equation With” Time Trend Variable

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

18.0%

1 9 9 0

1 9 9 2

1 9 9 4

1 9 9 6

1 9 9 8

2 0 0 0

2 0 0 2

2 0 0 4

2 0 0 6

2 0 0 8

A n n u a l G D P G r o w t h R a t e

% Change % Change (est1) % Change (est2)






Table 2. Parameter Estimates of Chaos-TypeGDP Growth Forecast Equation “Without” Time Trend Variable






3. STATISTICAL ESTIMATES OF THE PARAMETERS OF THE REAL

PROPERTY MARKET MODELS

This section presents and discusses the findings of the statistical analyses done to validatethe conceptual models presented in Section 2.0. A total of 27 time series-based equationsand two (2) cross-section based equations were estimated for the two basic real propertymarket models. The regression estimates for the REGVA model and the three (3)components of NFA — RFA, NRFA, and ARFA — are presented in Tables 3, 4, 5, and 6.The multiplier effect of the real property sector in terms of annual GDP growth rate isshown in Equation (17.0).

3.1. Results of Elasticity Analyses

The elasticities of both gross value added in real estate (REGVA and new floorarea construction with respect to economic activity (GDP) and the effective real

property tax rate (EPTR) are all statistically significant and are of the correctsigns: (+) with respect to GDP and (-) with respect to EPTR. The (-) sign withrespect to EPTR confirms the often expressed belief/opinion that property taxeshave a dampening effect on real estate investment. In fact, almost all of theestimated tax rate elasticities with respect to new floor area construction are allgreater than 1.

Analyses of available international cross-section data indicate that the estate tax negatively affects investments . Figure 6 shows a negative tax rateelasticity of 0.8441 between the statutory estate tax rate42 of a country and itsgross domestic capital formation (GDCF). This implies that for every 1%reduction in the maximum level estate tax rate of a country, there is a potential

0.84% increase in a country‘s GDCF.

In recognition of this negative effect of the estate tax rate on a country‘s capitalformation, 24 developed and developing countries out of 50 countries surveyed byPrice Waterhouse Coopers have no estate or inheritance tax . They includeArgentina, Australia, Canada, China, Colombia, Cyprus, Czech Republic, Estonia,India, Indonesia, Israel, Latvia, Lithuania, Malaysia, Malta, Mexico, N. Zealand,Portugal, Russia, Slovak Republic, Slovenia, Sweden, Switzerland, and Thailand.43

41R

2= 0.54 which can be considered quite high for a cross-section based regression equation. The elasticity

estimate is significant at the 99% confidence level. 42

Refers to the maximum statutory tax level. The maximum level estate tax rate is the more relevant measuresince it is the high income brackets who save the most and whose estates constitute bulk of a country‘sGDCF.

43See Chris Edwards. ―Repealing the Federal Estate Tax.‖ Tax and Budget Bulletin. No. 36, June 2006.






Figure 6. Statutory Maximum-Level Estate Tax Rate andGross Domestic Capital Formation, Selected Countries: 2005

Source: Calculated from estate tax rate data from coming from the Cato institute and GDCF data fromthe World Bank web page.

44

The coefficients of determination (R2) of the regression equations are all higher

than 90% indicating that the equations are useable for forecasting purposes. 45

Substantial tax rate effects can be expected from the Estate Tax, the Donor‘sTax, and the Value Added Tax (VAT).

The floor area-based model exhibited much higher tax rate elasticities for theCapital Gains Tax (CGT), the Documentary Stamp Tax (DST), the Tax onTransfer of Real Property Ownership (TTRPO), and the RPT compared to theREGVA-based models. REGVA includes land while new construction floor areais limited to improvements. This implies that the real estate market — land +improvements — is less responsive to tax rate changes than improvementsalone especially when measured in physical terms. The results can thus beviewed as probably symptomatic of the failure to regularly update the landvalues which serve as the basis of property tax assessment. With peoplepaying a lesser amount of tax on the land component of their real estateproperties than what they should actually pay, their response to tax ratechanges imposed on the value of the combined land and improvements is lowerthan their response in terms of physical improvements alone.46 Their passive

44Ibid and World Bank webpage, www. Worldbank.org.

45Even the R

2adjusted for sample sizes are all within 85 to 90%.

46In the case of the property-related transfer taxes, this is exacerbated by numerous avoidance techniques. A

thriving industry of lawyers and accountants specializing in ―estate planning‖ is in place, and their servicesare effectively availed of by the high value estates – the main target of these transfer taxes. Thus, it is thisindustry that thrives from the transfer of high value estates rather than the government.






land tax avoidance arising from government neglect makes them less sensitiveto tax rate changes that affect both land and improvements.

3.2. Output Effect of the Real Property Sector

Equation (17) implies that for every 1% change in REGVA in year t, there will be acorresponding 1.45% change in GDP.

LN GDPt = 1.45199 * LN REGVAt (17.0) (0.99999)

R2 = 0.99962

The number in parentheses represents the statistical significance of the regressionequation.

Input-output analysis also indicates a substantial output multiplier for the real propertysector. Available Year 2000 Input-Output (IO) data show that the real property sector has atotal industry activity multiplier ≈ 1.20, meaning that every peso spent in real property yieldsa peso of direct sales to the other sectors plus PhP 0.20 of indirect sales to the othersectors of the economy.47

Table 7 shows the inverse matrix of the 11 X 11 sector Year 2000 IO table for thePhilippines along with the corresponding output multipliers.

3.3. Local RPT Rates and Compliance

As shown in Tables 8 and 9, real property tax compliance and statutory RPT rates areinversely related with a tax rate elasticity that ranges from -0.09 to -0.12 indicating that a1% reduction in RPT rate could increase collection efficiency by 0.09 to 0.12%.

No relevant statistical analyses could be made for provinces as there is no variation in theirstatutory rates — all provinces pegged their statutory rates to the maximum allowed by the1992 LGC. For purposes of comparison, the average collection efficiency of provinces is just 27.38% as against the 63.18% average of Philippine cities. Against a statutory rate of2.0%, provinces only attained an effective rate of 0.55% or just about one-fourth of thestatutory rate. Cities with their more varied statutory rates and assessment levels wereable to attain an average effective rate of 1.67% against an average statutory rate of2.46%. Metro Manila cities attained an average effective rate of 1.81% versus an average

statutory rate of 2.56% with an average collection efficiency of 70.52%.

The result is supportive of the proposal to base the RPT directly on market values and justcompensate by lowering the tax rate. Such a lowering will help encourage RPTcompliance in Philippine LGUs.

3.4. CGT and TTRPO

Equation 18.0 indicates that for every 1% change in CGT revenues, there is acorresponding 0.84% change in TTRPO revenues.

47Computed as QMULT j = i INVij where INVij are the coefficients of the inverse matrix. The outputmultipliers represent the sum across rows of the inverse matrix.






LN TTRPOt = 0.838727 * LN REGVAt (18.0)

(0.99999)

R2 = 0.99843

The below 1.0 elasticity is symptomatic of the widespread evasion in the payment of theTTRPO even if the CGT and the DST are paid for at the BIR.

3.4. The GDP Forecasts

The ―adjusted‖ GDP forecasts presented in Table 11 were used as the ―base‖ GDPforecasts in the revenue simulations. From a forecast 4.8% growth rate at current prices in2009, the economy is expected to pick up steadily to reach a growth rate of 12.4% by2014.

The Asian Development Bank (ADB) 2009 and 2010 forecasts were used to calibrate the

results of the ―chaos model‖ forecasts since they were more updated than the comparableNational Economic Development Authority (NEDA) forecasts, and the Philippine growthforecasts prepared by the ADB were consistently linked to global and regional modelforecasts. Furthermore, the update of the most recent available NEDA forecasts was onlyfor 2009 and 2010.

The use of the more optimistic NEDA forecasts for 2009 and 2010 would only result inhigher potential tax revenue gains and would thus strengthen the recommendations basedon the simulation results using the ―adjusted‖ GDP forecasts.

Table 3. Regression Estimates for the Parameters of the

Gross Value Added in Real Estate (REGVA) Model






Table 4. Regression Estimates for the Parameters of theNew Residential Floor Area (RFA) Model

Table 5. Regression Estimates for the New Non-Residential Floor Area (NRFA) Model






Table 6. Regression Estimates for the Alterations/Repairs Floor Area (ARFA) Model

Table 7. Inverse Matrix and Resulting Output Multipliers,

Year 2000 Input-Output Table

Source: NSCB web page for the inverse matrix. Output multipliers were calculated by the author.






Table 8. Effective RPT Rates and Collection Efficiency, All Cities, 2007

Table 9. Effective RPT Rates and Collection Efficiency,Cities with 100 or Greater COE Excluded, 2007

Table 10. Alternative “Unadjusted” GDP Forecasts, at Current Prices: 2009-2014






Table 11. Base GDP Growth Projections at Current Prices






4. GUIDING POINTS IN THE FORMULATION OF REAL

PROPERTY TAX RATE REFORM PACKAGE

This section lays out the guiding facts and points considered in formulating the propertytransfer tax reform options. These guiding facts and points include: a) revenue yieldaspects, b) fiscal decentralization and growth aspects, c) administrative cost aspects, d)taxpayer resistance aspects, and e) government viewpoint.48

4.1. Revenue Yield Aspects

In this section, the real property tax revenue performance of the Philippines isbenchmarked against co-developing countries and against advanced countries.

a) Property taxes in 29 selected developing countries including the Philippines forthe years 2000 and 2001 constituted on the average 0.6% of Gross Domestic

Product (GDP).

49

b) In the Philippines, national property related taxes constituted 1.81% of totalBureau of Internal Revenue (BIR) collections in 2005 or a decline of 0.15% fromits 1.96% share in 2001.50

c) Relative to GDP

1) National property-related taxes represented just 0.18% of GDP in 2005or a decline of 0.03% from its 0.21% in 2001.

2) Local property-related taxes constituted 0.46% of GDP in 2005 or more

than double its 0.15% share in 2001.

51

3) Combined, the two constituted 0.64% of GDP in 2005 or just about theaverage for developing countries.52

d) In comparison, the ratio in Organization for Economic Cooperation andDevelopment (OECD) countries is about 2.12% or more than 3 times.53

e) The International Monetary Fund (IMF) does not classify property taxes as amajor tax.54

48These guiding points and the developed simulation model formulated during the TA work benefitted fromthe comments and suggestions made by key NTRC staff members led by Executive Director Lina Isorenaand Deputy Executive Director Dante Sy.

49See Bahl, Roy and Jorge Martinez-Vazquez (2008). ―The Property Tax in Developing Countries: CurrentPractice and Prospects‖ in Making The Property Tax Work in Developing and Transitional Countries , ed. ByRoy Bahl, Jorge Martinez-Vazquez and Joan Youngman. (Cambridge: Lincoln Institute of Land Policy).Computed by the authors from IMF (various years) Global Financial Statistics Data .

50See

Land Equity International Pty, Ltd. (August 2008). Report D-22: Review of National and Local Land-

Related Taxes and Fees . Manila, NTRC/LEI. 51

Computed by the author from unpublished Statement of Income and Expenditure (SIE) data generouslyprovided by the Bureau of Local Government Finance (BLGF) of the Department of Finance (DOF) andfrom national accounts data published in the 2007 Philippine Statistical Yearbook (PSY).

52Ibid.

53See Bahl, Roy and Jorge Martinez-Vazquez (2008).

54Ibid.






f) Reduction or abolition of certain property transfer taxes like the Estate Tax andDonor‘s Tax could in the long-run enhance the volume of property markettransactions, encourage tax compliance and thus, enhance revenues from otherproperty taxes.

1) The real property market as measured by the gross values added inreal estate (REGVA) is significantly and negatively affected by propertytax rates55 as shown in Table 3.56

2) Substantial tax rate effects can be expected from the Estate Tax, theDonor‘s Tax, and the Value Added Tax (VAT).

3) Every 1% increase in the Estate Tax and Donor‘s Tax rate in thePhilippines depresses the property market as measured by REGVA by1.4% (see Table 3). It also discourages new floor area construction.For every 1% increase in the Estate Tax and Donor‘s Tax rate in the

Philippines, new floor space constructed is reduced by 1.2% (see Table4).

4) In the case of Philippine cities, real property tax compliance andstatutory RPT rates are inversely related with a tax rate elasticity thatranges from -0.09 to -0.12 indicating that a 1% reduction in RPT ratecould increase collection efficiency by 0.09 to 0.12%.57

4.2. Fiscal Decentralization and Growth Aspects

a) The property tax is an important component of fiscal decentralization. Theshare of local real property-related taxes to total local revenues is positively

associated with local revenue size .58

55The coefficients of determination (R

2) of the regression equations are all higher than 90% indicating

that the equations are useable for forecasting purposes. The elasticity estimates are also statisticallysignificant at the 80 to 90% confidence levels.

56Similar results are obtained using new floor area construction as measure of the real property market.

57Ibid. No analyses can be done for provinces and municipalities since they all adopted uniform statutoryrates – the maximum allowed by the 1991 Local Government Code (LGC).

58

See NR Ramos et al. (2008). Survey of Public Perception on Real Property-Related Taxes and Fees .Manila, Philippines: Philippine-Australia Land Administration and Management Project Phase 2 (LAMP 2)and the National Tax Research Center (NTRC).






b) Higher income countries and more decentralized countries use property taxesmore intensively.59

c) 1990, 1995 and 2000 panel data from 70 countries show that expenditure

decentralization and per capita GDP have significant positive effects on theeffective property tax rate.60

4.3. Administrative Cost Aspects

a) Benchmark annual administrative costs (International Property Tax Institute)61

1) 2 to 5% of revenues in developed countries.

2) 10% or greater are symptomatic of problems.

b) In the Philippines62

1) Capital Gains Tax (CGT): 1.28%

2) Documentary Stamp Tax (DST): 5.12%

3) Estate Tax (EST): 11.38%

4) Donor‘s Tax (DOT): 17.22%

5) Value Added Tax (VAT): 3.13%

The high ratio of administrative costs to total revenue collected for the Estate and Donor‘s

Tax is due to the high costs of ―administration and enforcement‖ combined with a taxable base that is effectively reduced at the highest level by a ―large and wasteful estateplanning and avoidance industry.‖63 The Philippines has numerous high-paid lawyers andaccountants doing paperwork, litigation, asset appraisals, and creating financial structuresto minimize the tax burden using trusts, life insurance, and private foundations.

4.4. Taxpayer Resistance Aspects

a) Visibility of property taxes relative to other taxes.

1) People know how much property tax to pay and the amount is paid in lump-sum and quite early in the year, generally to take advantage of discounts.

2) Who could even guess how much VAT they pay for the commodities andservices they consume.

b) Property tax awareness and transparency issues.

59See Bahl, Roy and Jorge Martinez-Vazquez (2008).

60Ibid.

61See International Property Tax Institute (2007). Benchmarking 2007: Summary Report Toronto, Canada:IPTI.

62 See Land Equity International Pty, Ltd. (August 2008). 63

See Chris Edwards (2006).






1) Property taxpayers — owners and developers — in four (4) study LGUs — Iloilo City, Naga City, Marikina City and the Municipality of Pili in CamarinesNorte — had no problems with the CGT, DST, VAT, TTRPO, and RPT asthey found the tax base and tax rates easy to understand and compute.

They, however, considered the schedules and rates of the EST and DOT as―complicated‖ and ―difficult‖ to understand.64

2) The tax authority‘s assessment is perceived to be judgmental.

c) Break between the amount of tax liability and the ability to pay.

1) The EST imposes a cash burden on taxpayers especially during a period offamily crisis, and discourages registration of properties transferred tosurviving heirs, given the cash flow burden imposed by a one-time paymentwith six months deadline, and the large penalty and accumulated interestsimposed after the six month period lapses.

2) Issue of being ―asset rich‖ and ―cash poor‖ – property taxes being based onthe accumulated value of the property rather than on the annual incomederived from the property.

d) Special attachment to land especially in rural areas.

e) Present levels of public service provision are considered not worth the propertytaxes they pay.

4.5. Government Viewpoint65

a) Devolution of national property-related taxes desirable from BIR viewpoint sinceit would mean reduction in work effort with only a small (1.8%) reduction inrevenues.

b) LGUs would welcome devolution since it would mean a substantial increase intheir local revenues with minimum additional administrative costs. The trackrecord of the average LGU, however, indicates serious problems with their―willingness-to-charge‖ as evidenced by the following:

1) LGUs postponing the regular revision of the Schedule of Market Values asmandated by the 1991 Local Government Code (LGC).

2) LGUs providing generous and regular property tax amnesties.

3) Elected officials finding it politically difficult to bring aggressive enforcementmeasures against delinquents, especially against the politically powerful.

c) This track record has resulted in poor property tax collection performances withcities as exceptions.66

64See N.Ramos (2008).

65 The importance of this point was emphasized by NTRC Executive Director Lina D. Isorena during a

discussion held 16 July 2009.






1) For RPT , both provinces and municipalities have revenue to tax baseelasticities that are less than 1 — 0.20 for provinces and 0.33 formunicipalities — indicating their failure to fully capture the taxes due fromthe growing real property base proxied by the gross value added in real

estate (REGVA).

2) The cities are more aggressive in capturing the taxes due from theirrapidly growing real property bases with an elasticity of 1.70 .

3) There is a three-year revenue cycle associated with election years.Election years negatively affect major local revenue sources of LGUs.67Results of cross-spectrum analysis68 between per capita local revenues at1985 prices (PCLR85) and the dummy variable69 for election years between1991 and 2004 shown in Figure 7 shows only one peak indicating astatistically significant periodic relationship between PCLR85 and theelection year dummy only at a wave frequency of 0.33 70 or once every 3 years .71 The squared coherency 72 at the same frequency is 0.7307

meaning that the election dummy can account for 73% of the periodicity ofPCLR85.

4) The cities are more aggressive in capturing the taxes due from theirrapidly growing real property bases with an elasticity of 1.70 .

d) The DOF equates reduction in current national revenues with the wideningnational budgetary deficits.

66See ADB and BLGF (2007) and Asian Development Bank (ADB) and the Bureau of Local GovernmentFinance (BLGF), (2007). Appendix A.6. ―Proposed Time Period Interval for the Periodic Review of theIncome Reclassification of Local Government Units (LGUs).‖ Philippines: Local Government Finance and Budget Reform (ADB TA 4556) Final Report — Technical paper prepared by the Consultant of the TAproject, pp. 4-9.

67See also Asian Development Bank (ADB) and the Bureau of Local Government Finance (BLGF), (2007). Appendix D.1. ―A Financial and Economic Model for Determining LGU Fiscal Capacity for use by theBureau of Local Government Finance (BLGF).‖ Philippines: Local Government Finance and Budget Reform (ADB TA 4556) Final Report — Technical paper prepared by the Consultant of the TA project, p. 29.

68Cross-spectrum analysis may be thought of as the frequency analysis equivalent of correlation analysis.

69The variable assumes a value of 1 during the election years and 0 in all other years.

70There is zero or near-zero interaction between the two variables in the other frequencies.

71 Period = 1/frequency. 72

The squared coherency in cross-spectrum analysis is the equivalent of the R2.






Figure 7. Periodogram Values for Per Capita Local Revenues at 1985 Prices and theDummy Variable for Election Years: 1991-2004

Source: Computed from local revenue data from the BLGF BOS and SIE data,

NSO population data, and NSCB GDP Implicit Price Deflators.

Given these facts, the following points were considered in formulating the property taxreform recommendations:

a) Administration is costly in terms of both the setup and operating costs incomparison to current tax yields, especially for the EST and DOT.

b) Trade-offs characterize the development of property tax policy options.

1) Issue of piecemeal tax-by-tax reform that would yield marginal revenueimprovements but less politically costly versus a comprehensive reform that

will redefine the property tax as a consolidated package that has thepotential to reach a revenue yield comparable to that of developedcountries, say 1% of GDP or about half of that of developed countries atadministrative costs no more than 5% of revenues.

2) Devolution of national property taxes could enhance long-term revenueyields and the local tax revenues of LGUs, but reduce national revenues.Such a move should, however await the implementation of key propertyvaluation reforms as well the professionalization of key LGU financemanagers.






c) Consolidating all real property-related transfer taxes under a high yield, lowadministrative cost VAT could result in higher net tax take for the governmentbut could be regressive and could face significant taxpayer resistance andpolitical costs, especially at the beginning.

Given these guiding facts and points, the focus of the proposed property tax program willbe the four (4) national property transfer taxes — CGT, DST, EST, and DOT.

The VAT option is not at this point considered a politically viable option given that it willrequire redefining the concept of VAT and amending a recent piece of legislation that hadfaced stiff public resistance.

Reforming the TTRPO will require amending the LGC, which may not be easily doneconsidering that amendments to the LGC have been brought up as early as the 1998-2001Congress and no progress has been attained since then.

The tax rate reform package will formulate tax rate changes that seek to:

a) Reduce property transfer taxes to stimulate the real property sector and toencourage formalization of property transfers. Such stimulative effects areexpected in the long-run to more than compensate for revenue losses arisingfrom the rate reduction or even elimination of certain property taxes.

b) Do away with property related taxes that have relatively low revenue yields vis-à-vis administrative costs.

c) Maintain revenue neutrality during the critical first year of the projection period— 2010.






5. THE PROPOSED REAL PROPERTY TRANSFER TAX

REFORM PACKAGE

This section presents the tax rate reform package subjected to revenue simulation.

The proposed tax rate reform package that is subjected to revenue simulation wasformulated based on the following considerations.

a) The Estate Tax and Donor’s Tax

i) Of the four taxes proposed to be subjected to reforms, the two lowest in termsof revenue yield are the Estate Tax and the Donor ‘s Tax. In 2007, the EstateTax only yielded PhP 647 million and between 2000 and 2007 only averagedPhP 487 million per year. The Donor‘s Tax only yielded PhP 311 million in 2007and between 2000 and 2007 only averaged PhP 237 million per year.

ii) These two taxes also have transaction costs that are 2 to 3 times higher thanthe international benchmark of 5% collection costs. For every peso of taxcollected, the BIR spends PhP 0.11 for the Estate Tax and PhP 0.17 for theDonor‘s Tax.

iii) The two taxes also have highest negative effect on the growth of the realestate market (see tax rate elasticities in Table 3, where tax rate elasticities ofEstate Tax = -1.44; and Donor‘s Tax = - 1.45).

iv) The two are also the most ―disliked ‖ of the national real property transfer

taxes.

73

The Estate Tax and the Donor‘s Tax mainly affect the middle class. The rich areable to avoid these taxes by hiring lawyers and accountants who undertake estateplanning. In the United States, it is estimated that ―the resources spent on avoidingestate taxes may be as large as the amount that the tax collects‖. 74

v) The two taxes also have high and statistically significant cross-tax rateelasticities with the CGT and the DST. The cross-tax rate elasticities of theCGT with respect to the Estate Tax and the Donor‘s Tax are -1.14 and -1.16,respectively. For the DST, the cross-rate elasticities are 0.95 for the Estate Taxand 0.96 for the Donor‘s Tax. The cross tax elasticity is the elasticity of the

revenue collection of a certain tax with respect to the tax rate of another tax.For instance, when Estate Tax rate decreases by 1%, CGT collections increaseby 1.14%. This indicates that reductions in the Estate and Donor‘s Tax ratescan be readily captured by the CGT and the DST through the stimulative effectsof such reductions on the real property market.

73See N. Ramos (2008).

74 This statement is attributed to Alicia Munnell, a member of former US Pres. Clinton‘s Council of Economic

Adviser by D. Miller (May 2006). ―Costs and Consequences of the Federal Estate Tax‖ as quoted in Chris

Edwards (June 2006).






a) The Capital Gains Tax

i) The CGT has the highest revenue yield among the four taxes proposed to besubjected to reforms. Between 2000 and 2007, CGT collections averaged PhP

4.0 billion yearly.

ii) Its transaction cost of 1.28% is just about one-fourth (25.6%) of the internationalbenchmark of 5%.

b) The Documentary Stamp Tax

i) Annual DST collection averaged PhP 1.0 billion between 2000 and 2007.

ii) While it is perceived as onerous, property owners still willingly pay it because itmakes property transfers official.

Given these considerations, the proposed tax reform package will consist of small reductions in the CGT and DST rate in the period 2010 to 2011 and complete abolition of the Estate and D onor’s Tax combined with a major reduction in the CGT and the DST rates after 2011.






6. TAX REVENUE SIMULATION RESULTS

This section presents revenue simulation results for the proposed tax rate reform directionsfor 1) the Capital Gains Tax, 2) the Documentary Stamp Tax, 3) the Estate Tax, and 4) the

Donor‘s Tax. The revenue simulations were generated using the simulation processpresented in Figure 4 and on the base economic growth scenario shown in Table 11. Thesimulations also assume existing collection efforts by the BIR, but improved tax complianceby taxpayers at 0.12% per 1% cutback in the nominal CGT rate (see Table 8).

6.1. Short-term: Period 2010 to 2011

a) The Capital Gains Tax: The revenue simulation results shown in Table 12indicate that if implemented singly, the DOF should consider a 1% reduction inthe CGT rate from the existing 6.0% rate to 5.0%. Implementation is financiallyfeasible by 2010 when the economy will be starting on a higher growthtrajectory. Within this range, the stimulative effect of a tax rate reduction will

more than outweigh revenue losses from the rate cut. The expected annualaverage net increase in CGT revenues arising from the proposed 1% CGT taxrate cut for the period 2010-2014 is about PhP 1.2 billion. The proposed taxrate cut is expected to be revenue neutral if implemented in 2010. The presentvalue of the potential net revenue gain between 2010 and 2014 (―with reform‖less ―without reform‖ tax revenues) at a discount rate of 4.5%75 can be expectedat PhP 5.1 billion.

Implemented singly, the originally proposed halving of the CGT from 6 to 3% isnot financially feasible during the period 2010 to 2014 as the potentialrevenue gains arising from the stimulative effects of the rate cut on the realproperty market will not be enough to compensate for the revenue losses

arising from the rate cut. With such a halving of the CGT rate, a total net revenue loss of PhP 3.3 billion over the five-year period in present valueterms can be expected.

b) The Documentary Stamp Tax: The revenue simulation results shown in Table13 indicate that if implemented singly, the range of reduction for the DST ratethat the DOF should consider is between 10% and 15% . Implementation by2010 seems to be feasible when the economy will be starting on a highergrowth trajectory. Within this range, the stimulative effect of a tax rate reductionwill more than outweigh revenue losses from the rate cut. Within this range, theexpected annual average net increase in DST revenues arising from theproposed 10% to 15% DST tax rate cut during the period 2010-2014 can range

from PhP 343 to 837 million . The proposed tax rate cut is expected to berevenue neutral if implemented in 2010. Within this range, the present value ofthe potential net revenue gain between 2010 and 2014 (―with reform‖ less―without reform‖ tax revenues) at a discount rate of 4.5% can be expected torange from PhP 1.5 to 1.1 billion.

c) Table 14 shows a table summary of revenue simulation results of the taxreforms considered in the short term.

75This is the current 1-year T-Bill rate. The T-Bill rate serves as the opportunity cost of property tax revenuesraised since government revenue shortfalls are financed through borrowings.






Table 12. Revenue Simulation Results, Alternative Capital Gains Tax Rates,In Million PhP at Current Prices: 2010-2014






Table 13. Revenue Simulation Results, Alternative Reductions in the Documentary StampTax, In Million PhP at Current Prices: 2010-2014






Table 14. Summary of Simulation Results of Tax Reforms Considered in the Short Term:In Million PhP at Current Prices: 2010-2014

6.2. Medium-term: Period beyond 2011

a) The Proposed Real Property Tax Reform Package

The proposed reform package that DOF should consider for implementationbeyond 2011 consists of the following:

1) A halving of the CGT from 6 to 3%.

2) A halving of the DST rate.

3) Abolition of the Estate and Donor‘s Tax in line with current internationalpractices in both developed and developing countries.

b) Revenue Impact of Tax Rate Reform Package

1) Abolition of Estate and Donor’s Tax. The abolition of the Estate andDonor‘s Tax is projected to result in an average yearly revenue loss ofPhP 1.2 billion between 2010 and 2014, the present value of which for thefive year study period is about PhP 5.7 billion (see Table 15).






Table 15. Revenue Simulation Results, Abolition of the Estate and Donor’s Tax,In Million PhP at Current Prices: 2010-2014

2) Abolition of Estate and Donor’s Tax Combined with Halving of CGTRate. The combined stimulative effects of the abolition of the Estate andDonor‘s Tax and a halving of the CGT rate on the real property markettransactions in terms of new investments and increased formalization oftransactions can be expected to result in a net average annual revenue gain of PhP 6.8 billion. The present value of the net gains for the fiveyear study period is PhP 29.6 billion (see Table 16).

Table 16. Revenue Simulation Results, Impact of Proposed Medium-Term Tax RateReform Package on the Capital Gains Tax, In Million PhP at Current Prices: 2010-2014






3) Abolition of Estate and Donor’s Tax Combined with Halving of DSTRate. The combined stimulative effects of the abolition of the Estate andDonor‘s Tax and a halving of the DST rate on the real property markettransactions in terms of new investments and increased formalization of

transactions can be expected to result in a net average annual revenue gain of PhP 1.4 billion. The present value of the net gains for the fiveyear study period is PhP 6.2 billion (see Table 17).

Table 17. Revenue Simulation Results, Impact of Proposed Medium-Term Tax ReformPackage on the Documentary Stamp Tax, In Million PhP at Current Prices: 2010-2014

4) Proposed Tax Reform Package: Abolition of Estate and Donor’s TaxCombined with Halving of CGT and DST Rate. The annual average net revenue gain from this proposed reform package is projected at PhP 7.0 billion during the period 2010-2014 and the present value of the netrevenue gain attributable to the reform package during the period isestimated at PhP 30.1 billion (see Table 18).

Table 18. Revenue Simulation Results, Combined Revenue Effect of Proposed Medium-TermProperty Transfer Tax Reform Package, In Million PhP at Current Prices: 2010-2014






Thus, the expected increases in the revenue collection from the CGT andDST will more than offset the revenue losses from the abolition of theEstate and Donor’s Tax due to the high cross tax rate elasticity of theEstate and Donor‘s Tax with the CGT and the DST.

In the United States, Edwards (2005) argued that the bigger damage of theEstate Tax is its negative effect on savings, investment and businessactivity. Its abolition is expected to result in higher CGT revenues.76

5) Effect of Proposed Tax Reform Package on TTRPO. An added positiveeffect is that with increased real estate activities and formalization of suchactivities, LGU collection from the local TTRPO can be expected toincrease . As shown in Table 19, the reform package at the national levelcan be expected to result in annual average TTRPO collection of PhP 2.6 billion over the five-year period or about double the PhP 1.3 billion averageannual TTRPO revenues from 2003 to 2007. The present value of the net

revenue effect of the national transfer tax reform package on the TTRPO isestimated at PhP 5.6 billion over the 5-year period.

Table 19. Revenue Simulation Results, Combined Revenue Effect of the Proposed Medium-Term Property Transfer Tax Reform Package on the Tax on Transfer of Real Property

Ownership (TTRPO), In Million PhP at Current Prices:2010-2014

76 See American Council for Capital Formation, ―New International Survey Shows U.S. Death Tax Rate amongHighest,‖ July 2005.






7 CONCLUSIONS AND RECOMMENDATIONS

a) The Philippine real property market as measured in value terms — gross value addedfor real estate at current prices — and physical area terms — new floor space

construction — positively responds to changes in economic activity (Δ GDP) andnegatively related to changes in tax rates (Δ EPTR).

b) Reduction or abolition of certain property transfer taxes like the Estate Tax and Donor‘s

Tax could in the long-run enhance the volume of property market transactions,encourage tax compliance and thus, enhance revenues from the other remainingproperty taxes. Expected to be benefitted are the CGT, the DST, and the TTRPO.

c) In 2010, the DOF should seriously consider reducing the CGT rate from the present 6%to a range of 5 to 4.75%, and effecting a 10% reduction in the DST. These tax breakswill help boost the real property market during the present economic downturn and

result in improved revenue collection. At the same time, if implemented or evenpublicly announced by 2010, it can boost the popularity rating of the presentadministration in an election year.

d) Beyond 2010, the DOF should seriously consider adopting the proposed real propertytransfer tax reform package consisting of a halving of both the CGT and DST rates andthe abolition of the Estate Tax and Donor‘s Tax.

1) It will result in higher national revenue collections from real property transfertaxes.

2) It will also help improve LGU collection from the local TTRPO. For provinceswith their relatively limited revenue base, the improvement could be critical intheir drive for lesser dependence on the Internal Revenue Allotment (IRA).






REFERENCES

American Council for Capital Formation. (July 2005). ―New International Survey ShowsU.S. Death Tax Rate among Highest,‖ July 2005.

Asian Development Bank (ADB) and the Bureau of Local Government Finance (BLGF),(2007). Appendix D.1. ―A Financial and Economic Model for Determining LGUFiscal Capacity for use by the Bureau of Local Government Finance (BLGF).‖Philippines: Local Government Finance and Budget Reform (ADB TA 4556) Final Report — Technical paper prepared by the Consultant of the TA project.

Asian Development Bank (ADB) and the Bureau of Local Government Finance (BLGF),(2007). Appendix A.6. ―Proposed Time Period Interval for the Periodic Review of the Income Reclassification of Local Government Units (LGUs).‖ Philippines: Local Government Finance and Budget Reform (ADB TA 4556) Final Report — Technicalpaper prepared by the Consultant of the TA project, pp. 4-9.

Bardhan, Ashok and Robert Edelstein. (2007) ―Real Estate Through The Ages: TheKnown, The Unknown, and The Unknowable,‖ in Diebold, Doherty and Herring,eds., The Known, The Unknown, and the Unknowable in Risk Management.Princeton: Princeton University Press.

Bahl, Roy and Jorge Martinez-Vazquez (2008). ―The Property Tax in Developing Countries:Current Practice and Prospects‖ in Making The Property Tax Work in Developing and Transitional Countries , ed. By Roy Bahl, Jorge Martinez-Vazquez and JoanYoungman. (Cambridge: Lincoln Institute of Land Policy).

Bird, Richard and Enid Slack, eds. (March 2002). Land Taxation in Practice: Selected Case Studies , Toronto.

Bureau of Internal Revenue (BIR), Department of Finance (DOF). Annual reports,various years.

Bureau of Local Government Finance (BLGF), Department of Finance (DOF).Statement of Income and Expenditures (SIE), various years.

Cato Institute webpage, www.cato.org.

Edwards, Chris. (June 2006) ―repealing the federal estate tax‖ tax and budget bulletin. No. 36, as downloaded from the Cato institute webpage, www.cato.org.

Espanola, Ma. Victoria, Joyce P. Gracia, and Milwida M. Guevara. (July 1994). ―A Study of the Performance and Cost Effectiveness of the Real Property Tax,‖ Manila.

Hablieb, Harold. (July 2007) ―System Models and Simulation.‖ The Project Perfect WhitePaper Collection in www.projectperfect.com.au.

Hoerl, A.E., ―Application of Ridge Analysis to Regression Problems,‖ Chemical Engineering Progress.

International Property Tax Institute (2007). Benchmarking 2007: Summary Report Toronto,Canada: IPTI.








Land Equity International Pty, Ltd. (Aug 2008) Report D-28: Review of National and Local Land-Related Taxes and Fees . Manila.

Makridakis, S., Andersen, A., Carbone, R., Fildes, R., Hibon, M., Lewandowski, R.,

Newton, J., Parzen, R., & Winkler, R. (1982). ―The accuracy of extrapolation (timeseries) methods: Results of a forecasting competition.‖ Journal of Forecasting , 1,11-153.

National Statistical Coordination Board (NSCB). 2007. Philippine Statistical Yearbook (CDversion). Manila.

National Statistical Coordination Board (NSCB). 2009. www.nscb.gov.ph . Manila.

National Statistics Office (NSO). 2009. www.census.gov.ph. Manila.

Ramos, Norman R et al. (May 2004). Final Report: Land Markets Study . Manila,

Philippines: Philippine-Australia Land Administration and Management ProjectPhase 1. And the Department of Environment and Natural Resources (DENR).

Ramos, Norman R et al. (August 2008). Survey of Public Perception on Real Property- Related Taxes and Fees . Manila, Philippines: Philippine-Australia LandAdministration and Management Project Phase 2 (LAMP 2) and the National TaxResearch Center (NTRC).

Ramos, Norman R. (September 2009). The Real Property Tax Simulation Model . Manila,Philippines: Philippine-Australia Land Administration and Management ProjectPhase 2 (LAMP 2) and the National Tax Research Center (NTRC).

Regnault Jules. 1863. Calcul des chances et philosophie de la Bourse. Paris: Mallet-Bachelier. As quoted by Benoit Mandelbrot in Mandelbrot, Benoit. 2004. The (Mis)Behavior of Markets: A Fractal View of Risk, Ruin and Reward . New York:Basic Books, p. 283.

World Bank webpage, www.worldbank.org.

http://www.census.gov.ph/

http://www.worldbank.org/

http://www.worldbank.org/

http://www.census.gov.ph/





APPENDIX A. MATHEMATICAL DERIVATION OF THE

ELASTICITY ESTIMATE

The relevant elasticities are estimated by fitting a multivariate logarithmic function (Y = α +Β1 ln X1 + Β1 ln X2 +, …Bn ln Xn) using multiple regression analysis on the paired time seriesand cross-section data for each revenue item, by LGU type and where the variables areexpressed in terms of natural logarithms (ln). The partial slope coefficients (Bs) of theestimated multiple regression equations for each revenue item and for each LGU categorymeasures the elasticity (% change) of the revenue item for each LGU type with respect to a% change in each of the explanatory variables, e.g., gross value added in real estate, grossdomestic product, etc. The mathematical derivation is as follows:

The elasticity of Y with respect to X (έ) =Y

X

dX

dY

With the functional form Y X

έ=Y

X

dX

dY =

X

X X

1 =

X

X = B

This can be shown more rigorously as follows:

If Y = f(X) and a change ΔX are imposed leading to a change ΔY, then:

Y

X

X

Y

X

X

Y

Y

measures the proportionate change in Y per unit proportionate change in X, i.e., the %change in Y resulting from a 1% change in X. The elasticity of Y with respect to X is definedas the limiting value of this ratio as ΔX→0, that is:

Elasticity of Y with respect to X (έ) =Y

X

dX

dY

)(ln

)(ln

X d

Y d

where ln denotes the natural log.

Given a double-log functional form

ln Y= A + β ln X,)(ln

)(ln

X d

Y d = β

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