Probit analysis of planning statistics on case study zone Author(s ... · to 2004). For the selected zones, it is found that getting planning permissions in OU (Business) Zones from

TitleProbit analysis of planning statistics on case study zoneseparation between other specified annotated business zonesand industrial zones in Hong Kong /

OtherContributor(s) University of Hong Kong

Author(s) Kwong, Wai-chun; 鄺為臻

Citation

Issued Date 2005

URL http://hdl.handle.net/10722/48872

Rights Creative Commons: Attribution 3.0 Hong Kong License

THE UNIVERSITY OF HONG KONG

PROBIT ANALYSIS OF PLANNING STATISTICS ON CASE STUDY:

ZONE SEPARATION BETWEEN OTHER SPECIFIED ANNOTATED

BUSINESS ZONES AND INDUSTRIAL ZONES IN HONG KONG

A DISSERTATION SUBMITTED TO

THE FACULTY OF ARCHITECTURE

IN CANDIDACY FOR THE DEGREE OF

BACHELOR OF SCIENCE IN SURVEYING

DEPARTMENT OF REAL ESTATE AND CONSTRUCTION

BY

KWONG WAI CHUN

HONG KONG

APRIL 2005

Declaration

I declare that this dissertation represents my own work,

except where due acknowledgment is made, and that it has

not been previously included in a thesis, dissertation or

report submitted to this University or to any other

institution for a degree, diploma or other qualification.

Signed : __________________________

Name : KWONG WAI CHUN

Date : April 2005

Witnessed by : ___________________________

(Professor Lawrence Wai-Chung Lai)

Acknowledgements

This dissertation was completed with the help and advice from many people.

Firstly, I would like to show my greatest gratitude to my supervisor,

Professor Lawrence Wai-Chung Lai, for his invaluable advice and guidance.

Without his continuous support, this dissertation would hardly be completed.

Secondly, I would also like to thank Miss Lin Yuet Yim, Veronica,

B.Sc.(Surveying), Ph.D. Candidate, for her valuable advice and assistance

on data analysis.

Thirdly, special thanks are given to the staff of the Planning Department

who handled my enquiries and my classmates who assisted me in many

ways.

I must also express my profound indebtedness to my family members for

their constant care and support.

- 1 -

Summary. This dissertation uses a Probit Model to evaluate non-aggregate

data to investigate zone separation between Other Specified annotated

Business (OU (Business)) Zones and Industrial (I) Zones. This dissertation

employs 1986 sets of town planning application data (with a span from 1975

to 2004). For the selected zones, it is found that getting planning permissions

in OU (Business) Zones from the Town Planning Board is easier than that in

the Industrial Zones. They also refute the supposed distinction between the

two selected zones in respect of commercial and office uses. The proposition

about rent-seeking activities in favour of large developers is refuted. The

findings prove that obtaining planning permissions in Sha Tin is easier. On

the contrary, it is difficult to obtain them in Aberdeen & Ap Lei Chau. The

proposition that a higher chance is associated for development after January

2001 by Town Planning Board is not refuted. The two common uses,

residential and office, are proved to stand higher chances of getting

permissions. It is also more difficult to obtain planning approvals on review

under s.17 after an application under s.16 is rejected in the first instance.

- 2 -

1. Introduction

Due to the changes in the global division of labour, Hong Kong industry

activities have shifted from manufacturing and production-oriented to

management and service-oriented activities1. Since 19 January 2001, the

Town Planning Board has introduced a new type of designated zone, the

“Other Specified annotated Business (OU (Business)” Zone, to allow greater

flexibility in new development and existing industrial or industrial-office

buildings2. Together with the existing Industrial “I” Zones, the town

planning intention of this new type of zones is to facilitate the continuous

growth in the economy and avoid the decay of existing industrial buildings.

Most past research was concerned with the development control of the

planning authority over the land market. Limited empirical studies were

based on planning application data using statistical methods. Only Dobry

(1975) and Brothern (1992a, 1992b) had conducted some empirical work

based on the aggregate application data.

1 Town Planning Board (2003). Town Planning Board Guidelines For Development

within “Other Specified Uses (Business)” Zone (TPB PG-NO. 22B of 31-5-2004),

Hong Kong: Printing Department. 2 ibid.

- 3 -

Other than Willis (1995), Tang and Tang (1999), Tang and Choy (2000),

Tang et. al. (2000), Lai and Ho (2001a, 2001c, 2001d, 2002a, 2002b, 2002c,

2003), Yung (2001, 2004), Kwan (2002), Ngai (2002), Chan (2003), Wan

(2004) who used probit/logit modelling. Most studies relied heavily on

population, economic, environmental figures to investigate the strategic

policies. Examples were there of Abercrombie (1945, 1948), Abercrombie et.

al. (1945) and Abercrombie and Plumstead (1949).

But Dobry’s (1975) work was an exception. He conducted qualitative

analysis of the impact of planning process and concluded that any delay in

planning process was costly. After the publication of the Dobry’s Report,

better and other statistical methods had been applied by different researchers.

Examples were: Brotherton (1984, 1992a, 1992b), Gilg and Kelly (1996),

McNamara and Healey (1984), Preece (1990), Sellgren (1990) and Willis

(1995). The trend was for abandoning aggregate in favour of non-aggregate

data in development controls analysis.

In Hong Kong, qualitative analysis began with Staley’s monograph (1994).

Staley (1994) investigated the planning mechanism of cost delay in the

Review of the Town Planning Ordinance 1992. His study discovered that the

transaction costs of the development would be added by the proposed

- 4 -

“planning certificates”. Developing the idea of Staley, Chau, Lai and

Hammer (1996) and Lai (1997) further reviewed the Town Planning

Ordinance 1996, and concluded that the planning mechanisms would lead to

higher transaction costs for the development and rent-seeking activities. For

the change of the use of non-aggregate data, (a) Tang and Tang (1999), Tang

and Choy (2000), Tang et. al. (2000) with the Hong Kong Polytechnic

University and (b) Lai and Ho (2001a, 2001c, 2001d, 2002a, 2002b, 2002c,

2003) and Chau and Lai (2004) with the University of Hong Kong had made

contribution.

Different researchers had their own preferences and characteristics in testing

their hypotheses. Gilg and Kelly (1996, p.205) classified the research on

development control statistics into four different categories.

1. simple statistical and cartographic analysis;

2. power struggle in decision making process analysis;

3. logical positivism analysis (technical exercises within decision making

processes); and

4. postmodernism analysis3

(random but sequence of event within

decision making processes).

3 The postmodernism approach involves modifying behaviour, hermeneutic, humanistic

or case study approaches in order to build a “tale” of how “things really are” rather

than a “meta-narrative’ based on modernist concepts of “order and pattern”.

- 5 -

Willis (1995a, 1995b) could be regarded as the first person who used

non-aggregate planning data in statistical study of planning control.

Non-aggregate data4 meant disaggregate data. Willis (1995a) used a logit

function to investigate for the likelihood of planning applications in respect

of waste disposal to be approved. In the same year, Willis (1995b)

developed two models for the analysis of development control. They were

the “Cognitive Continuum” and “Lens” models. Willis (1995b, p.1070) used

the “Cognitive Continuum” model to study the ability of people in

performing different kinds of work and the knowledge that was employed on

the work. For the “Lens” model (Willis 1995b, p.1071), “there is some

actual, underlying, hidden condition or state – planning permission – which

the planning officer (or planning committee) was trying to identify and

classify, from observable signs, cues or indicators it produces”. Willis (1995,

p.1070) mentioned that the development applications could be imagined as

producing some messages or signals which were different in such forms as

strength, frequency. Willis (1995) pointed out that the planning officers or

committees would try to follow or identify the hints or signals from the

proposed development projects in order to judge the applications.

4 The definition of Carols reads, “If each observation in our data set consists of an

attribute vector (representing an individual how has been interviewed), and an observed

choice, we say that we have disaggregated data. If, on the other hand, the data include

information on groups of people, we call it aggregate data.” (Carols (1979, p.6))

- 6 -

Many empirical studies had been conducted by researchers following in the

footsteps of Willis (1995b, p.1072). The functional forms of the hints in such

studies were: how the decision makers assigned the importance of the hints,

how to organize the data of the hints, what the relationship between the hints

and the decisions was, and whether there was consistency for the decisions

made.

In Hong Kong, the study on the so-called “Two-tier Plot Ratio” system by

Tang and Tang (1999) was the first application of the logistic regression

model to study the impact of new zoning on the redevelopment of private

housing. They utilized 627 sets of observation data (non-aggregate sampling)

from 1986 to 1997 to test their hypothesis. The hypothesis was whether the

time waiting for the approval of building plan and the “Consents to

Commence Work” from the local authority (Building Authority) will

become longer if the site area of the proposed redevelopment on the

combined site is smaller. Tang and Tang (1999, p.42) found that in urban

Kowloon, planning applications for the larger site had a greater chance of

success in obtaining permissions for uses in Residential (Group A) Zones

from Town Planning Board.

- 7 -

Tang and Choy (2000) made another attempt to investigate the criteria

involved in the decision making process and whether these criteria actually

followed some planning policies and guidelines. Tang and Choy (2000)

utilized 162 sets of observation data from 186 and 1997 and selected nine

independent variables (some of them from written planning policies or

guidelines) as the factors for evaluating the planning decisions of the Town

Planning Board. The results were similar to those of in Tang and Tang’s

(1999) that the larger the site and scale of a proposed development enabled

easier permission from the Town Planning Board.

Tang et. al (2000) further examined the development control regimes in

Hong Kong. They pointed out that actually Hong Kong’s planning control

system is a “Hybrid System” (Tang et. al (2000), p.2465). A “Hybrid

System” means the decision making is governed by the discretionary

permission process and the zoning plan. They developed sixteen variables as

factors in a logistic regression model and examined whether the “Hybrid

System” can provide flexibility for development control and give certainty

for development application on office use in Hong Kong Island. Seven out

of sixteen were found to be significant and they hence argued that there were

flexibility and certainty in the planning decision (Tang et. al (2000), p.2481).

- 8 -

2. Controls on planning development and the Hypotheses

The most readily observable statutory controls in Hong Kong are those

under the Buildings Ordinance and Town Planning Ordinance. Both are

regulated by a group of professionals when applications are submitted. Lai

(2001b) pointed out that the planning authority had the role of rationing the

development rights and such rationing was controlled by government town

planners. The Buildings Ordinance clearly states that the duty of Building

Authority is to maintain the safety and hygienic of the buildings according to

the designs, structural and safety requirements of the building plans

submitted for approval under Cap.123, s.16 of the Buildings Ordinance.

The Town Planning Ordinance authorizes the Town Planning Board to

regulate the redevelopment of land use in Hong Kong. So if any developer

intends to redevelop or change the use of land, they must check the relevant

statutory plan (i.e. OZP or DPA Plan) no matter the proposed development

uses are permitted by the government lease or not. Lai (1997a & 2002)

complained that such measures actually attenuated the property rights of a

land owner as they attenuated without compensation the agreed terms in the

lease.

- 9 -

Although there are ordinances, development guidelines and other

publications governing town planning control, a clear set of rules for

deciding planning application cannot be found. The planning legislation

does not state that decisions made by government town planners should be

based on “public interest”. However, this expression is often used in making

decisions by the Town Planning Board. But what the exactly meaning of

“public interest” is not clear. Moreover, planning guidelines and publications

are not statutory, and each planning application is said to be decided on a

“case-by-case basis” or its individual merits. All these suggest that planning

decisions can be heavily influenced by planners’ own preferences in their

professional judgment. Therefore, the local planning permission system can

be described as “self-governing” and insensitive to external influenced. Due

to the “secret” and “black-box” nature of the Town Planning Board, it would

be interesting for us to analyze or discover the actual factors or variables that

affected the outcomes of the planning application.

Hypothesis I investigates if the chance of success in obtaining planning

permissions on applications for developments in OU (Business) Zones is

easier to be approved by the Town Planning Board than those in Industrial

Zones. This is set in the background that the government is relaxing the

criteria for considering applications in order to restructure the industrial

- 10 -

sector of Hong Kong. The intention for introducing the OU (Business) Zone

is to allow more flexibility in industrial or industrial-office buildings. If the

hypothesis is not refuted, this would mean that Town Planning Board is

really closely following the Town Planning Board’s guidelines.

Hypothesis II examines if the planning applications for particular uses in OU

(Business) Zones are associated with a greater likelihood of being approved

by the Town Planning Board than that in Industrial Zones. It is conducted to

find out whether the two different zones are “separable” or not (Lai and Ho

2002b).

Hypothesis III evaluates if the chance of success in obtaining planning

permission on applications for development in larger sites (measured in

terms of proposed gross floor area (GFA) of the building(s) or use) is easier

to be approved by the Town Planning Board than those in smaller site. It is

based on the appraisal used by Lai and Ho (2001a, 2001b, 2001c, 2002a,

2003) about rent-seeking activities involved in the planning process. It is

assumed that for a larger site, more capital is required and this can act as a

proxy for the involvement of a larger developer. If the hypothesis is not

refuted, this will indicate that Town Planning Board is indeed favouring

larger developers and the decisions for cases are not really based on a

- 11 -

case-by-case, individual merits basis or following the guidelines.

Hypothesis IV is to find out if the planning applications for development in

particular regions are really associated with a greater likelihood of being

approved by the Town Planning Board than those of other regions in OU

(Business) and Industrial Zones. It is to investigate whether there is any

preference for any particular proposed uses in OU (Business) or Industrial

Zones by Town Planning Board when considering the planning applications.

It is proposed for investigating whether Town Planning Board will prefer

some particular regions so that easier permissions for case therein can be

obtained. If the hypothesis is not refuted, this will mean that all the regions

are considered as being the same by the Town Planning Board.

Hypothesis V investigates if the chance of success in obtaining planning

permissions for developments after January 2001 was easier than those

before January 2001. It evaluates whether the approval rates will be higher

or not after the introduction of the new type of zones. In theory, as the Town

Planning Board has relaxed the criteria for deciding applications since

January 2001; the likelihood of success in obtaining planning permission

should be higher. If the hypothesis is not refuted, this will mean that the

government allows more flexibility for developments in industrial or

- 12 -

industrial-office buildings.

Hypothesis VI examines if the planning applications for particular uses in

OU (Business) and Industrial Zones are associated with a greater likelihood

of being approved by the Town Planning Board than those of other uses in

OU (Business) and Industrial Zones. It investigates whether there is any

preference for proposed uses of Town Planning Board when considering the

planning applications.

Hypothesis VII evaluates if the chance of success in obtaining planning

permissions for developments for planning review under s.17(1) or planning

appeal under s.17(B) using the same proposal that fails in the s.16 process is

lower than that for planning application under s.16. The chance for obtaining

planning permission under s.17(1) or s.17(B) is very important for the

developers. If the probability of success on review or appeal is low,

developers may decide not to continue with the same application in order to

reduce further loss.

- 13 -

3. Probit Model

The Probit model was first utilized to study the effect of insecticides on the

insects in order to find out the critical dosage of the insecticides. Individual

insects were tested by applying an insecticide until the amount of insecticide

had reached a critical dosage and the insects all died after the critical limit.

Theil (1971) assumed that the proportion of insects killed was p, a probit

transformation was applied as y=F-1

(p), where y was the linear function to

the dosage of insecticides used. Lee and Trost (1978) followed the idea of

Probit Model and tried to use the model to investigate housing economics.

They criticized that many researchers or scholars had not fully utilized the

advantages of Probit Model. As the model could admit binary dependent

variables, many variables could be analyzed at the same time. Many earlier

works were only concerned with the expenditure of owners or renters. Lee

and Trost (1978) posed the hypothesis as to whether consumers would own

or rent their flats and the amount they would spend. This approach was for

the simultaneous determination of two factors. Since then, many research

projects based on simultaneous equations had been carried out. Examples

were the work of Goodman (1988) and Goodman and Kawai (1988), who

concluded that the choice of tenure (own/rent) and the housing decisions

were significant at the same time. They also mentioned that the income of

- 14 -

consumers was a significant variable for housing decision. One year later,

Potepan (1989) suggested that an increase in current interest rate could have

a positive effect on the improvement of housing. But an increase in income

would discourage the probability of housing improvement. Bourassa (1995)

used economic and demographic variables in a Probit Model to study their

effects on user costs and homeownership. The result was positive, which

meant that the variation in user cost could have a significant effect on the

probability of homeownership. Hsueh and Chen (1999) also applied the

Probit Model to examine the choice of tenure in Taiwan.

In Hong Kong, Lai and Ho (2001a, 2001c, 2001d, 2002a, 2002b, 2003), and

Chau & Lai (2004) evaluated different variables (such as proposed

development uses, site area, application time) using the Probit Model in

order to make predictions about the planning decisions. Their raw statistics

were obtained from the Town Planning Board files kept by Planning

Department. Lai and Ho (2001c) evaluated hypotheses about “zone

separation” in Hong Kong. In the work of Lai and Ho (2001d), 379 sets of

data from 1975 to 1998 were used to examine whether the likelihood of

obtaining planning permissions in Green Belt Zones by the Town Planning

Board in the proposed housing development project was greater or not.

Moreover, some evidence of rent seeking activities favouring larger

- 15 -

developers could also been found in the work of Lai and Ho (2001a, 2001b,

2001d & 2003), Kwan (2002), Ngai (2002), Chan (2003), Chau and Lai

(2004) and Wan (2004).

4. Modelling Planning Applications

Lai and Ho (2001c) mentioned that the Probit Model could be used to

identify the determinants of the choice between the two discrete alternatives

which was 1, 0 (it was convenient to identify “1” as approval and “0” as

rejection).

A univariate binary qualitative response model was expressed as Equation 1:

[Equation 1]

p(ai = 1) = f (xiββββ0) i ε {1, n}

where {ai} was a series of independent binary random variables in either 0

or 1; xi was the K-vector of known constants; and ββββ0 was the K-vector of

unknown parameters; f was a certain known function (Finney (1977)).

Ameniya (1986) suggested that it was more common to express the

probability in f(xi , ββββ0), but Equation 1 could be said as the most specification.

Moreover, specifying f as xiββββ0 was a more general approach in linear

regression model as xi could become the transformation of original

- 16 -

independent variables. f was just a distribution function and xi ββββ0 could also

approximated regarded as general transformation of non-linear function of

independent variables.

f could be used as function form in such statistic model as Probit Model,

Logit Model and Linear Probability Model. Equation 2 showed the Probit

Model for the planning applications.

[Equation 2]

p( xα1, xα2, …xαk) = f (β0 + β1xα1+β2xα2+…+ βk xαk)

Or equivalently be expressed as

[Equation 3]

f-1

[p( xα1, xα2, …,xαk)]= (β0 + β1xα1+β2xα2+…+ βkxαk)

The probability of successful planning application was modelled as a

function of particular development or use such as a resident use, commercial

use, office, hotel, bank, church, etc; the development size (measured in

=

- 17 -

terms of gross floor area); location as well as time. Let xα1, xα2,…, xαk be the

value taken by each of these k variables for αth planning application.

In order to estimate the parameters of β0, β1, β2,… and βk, the

maximum-likelihood model was used. The observation of the decisions was

defined in such a way that the first j’ applications were approved by the

Town Planning Board and the sequent j – j’ applications were rejected.

Therefore, the logarithmic form of the likelihood function could be

expressed as:

[Equation 4]

where p( xα1, xα2,…,xαk) was in form of Equation 2 and also the function of

β0, β1, β2,… and βk.

Thei (1971) and Tobin (1975) mentioned that by applying differentiation in

Equation 4 with respect to the above parameters and setting the derivatives

to zero, one could obtain a non-linear equation so that the estimates could be

derived numerically by an iterative procedure.

- 18 -

Amemyia (1981) pointed out that in a Log Likelihood Equation; there was

only 1 maximum, which meant that the equation was concave in nature. So

by applying an iterative procedure, our estimation could be converged into

one single maximum. And Long (1997) explained that the iterative

procedure should be started initially with a value and adding vectors of

adjustment in attempts afterwards could help improve the guess work. This

process would continue to run until convergence was found.

5. Data Description

From the planning statistics collected, there are 180 sets of planning

application data for the Other Specified annotated Business Zones from

2001 to 2004, while there are 1,951 sets of planning applications for

Industrial Zones from the period 1975 to 2004. Due to the missing of such

information as the proposed gross floor area, planning decision etc, some

sets of applications are excluded from the analysis. So, only 97 sets of

observations are used in Other Specified annotated Business Zones and

1,799 observations in Industrial Zones.

The dependent variable in the research is the “Decision” for the planning

applications from the Town Planning Board. The variable “Decision” equals

- 19 -

to 1 if the planning application is approved by the Town Planning Board. In

this dissertation, there are 25 of variables to be investigated compared with

the dependent variable. Each variable is the key factor postulated to have

affected the results of the application. The gross floor area variable, “GFA”,

is the proxy for the scale and size of the development. It is measured in

square meters. According to Lai and Ho (2001c), “GFA” was a much more

meaningful and reliable variable than “GSA” (used by Tang & Tang (1999),

Tang & Choi (2000)) in Model as the Accommodation Value (AV) of the

proposed development could be estimated on the basis of GFA. Moreover,

Lai and Ho (2001c) also pointed out that a larger value of “GFA” would

require greater capital investment, so this could act as a proxy for a larger

developer. This in turn throws light on the presence of rent-seeking

activities.

There are two zoning types or classes in this study: “Other Specified

annotated Business Zone” and “Industrial Zone”. So, a variable “OUB” for

the zoning area is assumed to equal 1 if the proposed development is located

in an OU (Business) Zone.

There are several common use variables which indicate the types of

proposed development applied for. They include: Residential (RES);

- 20 -

Commercial (COM); Office (OFF); Bank (BANK); Industrial-office (IO);

Showroom (SR); Hotel (HOTEL); Restaurant (REST) and other uses.

Moreover, in order to test the separation between the OU (Business) and

Industrial Zones, two new variables, “OUBCOM” and “OUBOFF”, are

defined. “OUBCOM” indicates the planning applications for commercial

uses in OU (Business) Zones. It is obtained by multiplying the two variables

of “OUB” and “COM”. “OUBOFF” represents planning applications for

office uses in OU (Business) Zones and is obtained by multiplying the

variables of “OUB” and “OFF”.

Geographic factors are also investigated under the Model. For broad regional

division, Hong Kong Island; Kowloon Peninsula (KLN) and the New

Territories (NT) are analyzed in the research. “KLN” equals 1 if the

proposed development is located in the Kowloon Peninsula and “NT” equals

1 if the proposed development is located in the New Territories.

For district division: Aberdeen & Ap Lei Chau (ABERDEEN); Chai Wan

(CW); Kwun Tong (KT); Ngau Tau Kok & Kowloon Bay (NTK); Cheung

Sha Wan (CSW); Tsz Wan Shan, Diamond Hill & San Po Kong (TWS); Sha

Tin (ST); Kwai Chung (KW); Tsuen Wan (TW) are differentiated.

- 21 -

The variable “S16” is used to identify the stage of an application. From the

collected data, there are 1741 observations on applications under s.16 and

155 observations under s.17(1) or s.17(B). “S16” equals 1 if no further

review or appeal cases arose after decisions were made by Town Planning

Board to reject approval under s.16.

Since 19 January 2001, OU (Business) Zones have been designated in order

to restructure industrial sector in Hong Kong. “AFTER01” equals 1 if the

planning decision is made after January 2001.

6. DISSUSSION

Table 5 in Appendix I presents the final linear form of Probit results of

independent variables. The variable “OUB” is significant at 0.90% level and

has a positive coefficient. This means that getting planning permissions in

OU (Business) Zones from Town Planning Board is easier than in the

Industrial Zones. Therefore, Hypothesis I is not refuted. It reveals that the

Town Planning Board has actually followed its own guidelines of relaxing

the development criteria for restructuring the industrial area.

“OUBCOM” and “OUBOFF” are two independent variables which are used

to evaluate Hypothesis II. Table 6 in Appendix I shows the Probit results of

- 22 -

the two independent variables, “OUBCOM” and “OUBOFF”, are 100% not

significant. This means that the commercial and office uses in OU (Business)

Zones are not associated with a higher chance to obtain planning

permissions. So, the two zoning classes (OU (Business) and Industrial Zones)

can be concluded as “inseparable” in respect of commercial and office uses.

Therefore, Hypothesis II is refuted.

Table 2 and Table 3 in Appendix I show that both the variables of “GFA”

and “1/GFA” are not significant. This result implies that gross floor area is

not a major factor governing the final decision of Town Planning Board.

This appears to contradict previous findings of Staley (1994), Hammer

(1996), Lai (1997), Lai and Ho (2001a), Kwan (2002), Chan (2003), Wan

(2004). Scale of proposed development is not significant in obtaining

planning permission for the types of used examined. Therefore, Hypothesis

III is refuted. There is no prima facie evidence is to support the argument

that development scale is affecting the decision of the Town Planning Board.

Therefore, no any rent-seeking activities have taken place to favour the large

developers in the types of uses examined.

For the investigation on districts, Kwai Chung is selected as the basis for

evaluating Hypothesis IV. From Table 5 in Appendix I, “ABERDEEN” and

- 23 -

“ST” are significant, respectively, at 3.26% and 0.63% levels. “ST”

possesses a positive coefficient, but the coefficient for “ABERDEEN” is

negative. This means that it is easier for developers to obtaining planning

permissions in Sha Tin. However, it is difficult for developers to getting

planning approvals in Aberdeen & Ap Lei Chau. Therefore, Hypothesis IV

is not refuted.

From Table 7 in Appendix I, the variable “AFTER01” is significant at

1.46% level and has a positive coefficient. This means that a higher chance

of success in planning application is associated with a proposed

development after January 2001. Therefore, Hypothesis V is not refuted.

Greater flexibility has apparently been granted for redeveloping the

industrial areas in order to suit the changing of manufacturing sector to

service-oriented sector in Hong Kong.

Besides “RES”, “OFF”, “BANK”, other uses’ variables (“COM”, “IO”,

“SR”, “HOTEL” and “REST”) are shown to be insignificant in the model.

From Table 6 in Appendix I, we can see that “RES” and “OFF” are

significant, respectively, at level of 3.49% and 5.78%, both with positive

coefficients. This means that it is easier to obtain planning permissions for

- 24 -

residential and office uses in OU (Business) and Industrial Zones than other

uses in the zones. Therefore, Hypothesis VI is not refuted.

Although the variable “BANK” is significant at level of 11.69%, it has a

negative coefficient. This means that getting planning approvals for bank

uses in OU (Business) and Industrial Zones is more difficult than other uses.

This result can provide some guidance for developers who are interest in

such uses in Industrial or OU (Business) Zones.

That “Office” uses stood a higher chance of success is logical because Hong

Kong’s resources are shifting from the industrial to serviced-oriented sector.

So the demand for office uses has increased. According to the guidelines, the

Town Planning Board should allow more flexibility in re-development and

facilitate the restructuring the industrial areas in Hong Kong. Therefore, it is

reasonable for Town Planning Board to have relaxed the criteria for

approving the office uses.

However, it is surprising to find that residential uses are associated with a

higher chance of success both in OU (Business) and Industrial Zones. Since

the OU (Business) and Industrial Zones are located in industrial areas, it is

not common to have residential uses in there. There are two possibilities for

this strange result. One is that the Town Planning Board does not closely

- 25 -

follow its own guidelines or instructions when making decision. The other is

that amount of applications is limited, thus reducing the significance of the

results.

The stage variable “S16”, as shown in Table 6 in Appendix I, is highly

significant and has a positive coefficient. This can reveal that if a planning

application made under s.16 is rejected, the success rate in a planning review

or an appeal will be very low consequently. Therefore, Hypothesis VII is

not refuted.

- 26 -

- 27 -

7. Conclusion

Zone separation is the focus of this dissertation. Even the label of a use in

Column 2 is identical in two zoning classes, the planning intention and thus

the decision criteria should be different. Otherwise, the two zones will

become inseparable, and the zoning regimes become meaningless in real

terms. In the hypotheses, commercial and offices uses are selected for

investigating the actual “separation” of the OU (Business) and Industrial

Zones. The result is surprising: there is no difference between the two

classes of zones. This means that make the introduction of newly designated

OU (Business) Zones is redundant as the planning intentions of the Town

Planning Board for them are actually the same regarding the proposed uses

in the two zoning classes.

No evidence is found supporting a large scale or small scale of proposed

development can affect the chance of success in planning application.

From the view of developers, the location of the proposed development will

directly affect the economic value. So, Sha Tin is the district that can have a

higher chance of success and may act as a reference for developers to invest.

And Aberdeen & Ap Lei Chau is a place in which it is difficult to apply for

planning approvals and this lower the incentive of developers.

- 28 -

Since January 2001, the planning applications have been more easily be

approved by the Town Planning Board due to the relaxation of the

development criteria. This may encourage developer to make more

proposals for development, so that the process of industrial area

restructuring can be speeded up.

Residential and office uses are the two popular uses from the view of Town

Planning Board as the approving rates are very high for both uses. But the

question is whether it is suitable to allow more residential uses in industrial

areas.

If an application fails under s.16, then the chance for success under s.17(1)

or s.17(B) would be much lower. This is normal since the Town Planning

Board is following the same principles when reviewing the case. Except

where the developers can provide new and strong evidence to prove that

their proposed developments are suitable to locate on the land, the chance of

rejection or dismissal is very high.

- 29 -

8. Limitations

The major limitation of the research is the restrictions in information

collected. Firstly, the OU (Business) Zones have only been introduced for 3

years. Therefore, the number of applications is quite small compared with

Industrial Zones. The great difference in the number of application

observations will definitely affect the results of the analysis.

Secondly, the missing of such information as “planning decision”, “gross

floor area” and “existing gross floor area” would make many data

inapplicable. The limited amount of the data reduces the significance and the

accuracy of the Probit Results.

Thirdly, there is the problem with the time horizons between OU (Business)

and Industrial Zones. The time period for OU (Business) Zones ranges from

2001 to 2004, but the time period for Industrial Zones from 1975 to 2004.

The difference in the time horizons may have affected the results. However,

if the same time horizon (from 2001 to 2004) is used, the available

observations would become too small for comparison, so it is worthwhile

compare the two zones according to different time horizons.

- 30 -

9. Further Research

Many interesting questions have been encountered during the research. The

guidelines published by the Town Planning Board have clearly stated that

the OU (Business) Zones can be perceived as a combination of commercial

and industrial zones. But why some of the industrial zones have been

changed to OU (Business) Zones, but no commercial zone changed to OU

(Business) Zones? And not all the industrial zones have been changed to OU

(Business) Zones. Just only some of them have been changed. Based on

what criteria or reasons for selecting the place or district to rezone? Further

analysis and research should be done in order to clarify the “actual” planning

criteria and intention of the Town Planning Board.

- 31 -

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i

Appendix I

Table 2: First Linear form of Probit Results of independent variables

Dependent Variable: DECISION Method: ML - Binary Probit Date: 12/27/04 Time: 23:15 Sample(adjusted): 5 1896 Included observations: 1886 Excluded observations: 6 after adjusting endpoints Convergence achieved after 9 iterations Covariance matrix computed using second derivatives

Variable Coefficient Std. Error z-Statistic Prob.

C 0.164809 0.157332 1.047524 0.2949

GFA -1.23E-07 1.30E-06 -0.094916 0.9244 OUB 0.198681 0.295064 0.673348 0.5007 RES 0.564583 0.294169 1.919246 0.0550 COM 0.040897 0.092628 0.441518 0.6588 OFF 0.122335 0.084764 1.443230 0.1490

BANK -0.191394 0.125480 -1.525293 0.1272 IO -0.052168 0.104579 -0.498837 0.6179 SR -0.051346 0.111217 -0.461670 0.6443

HOTEL 0.444570 0.369069 1.204571 0.2284 REST 0.084101 0.131637 0.638885 0.5229 S16 0.537224 0.111688 4.810042 0.0000

AFTER01 0.128933 0.192783 0.668799 0.5036 KLN 0.055124 0.103342 0.533408 0.5938 NT 0.050894 0.105672 0.481617 0.6301

ABERDEEN -0.299571 0.143646 -2.085481 0.0370 KT 0.042544 0.100060 0.425186 0.6707

CSW -0.078886 0.100259 -0.786824 0.4314 ST 0.265174 0.114105 2.323952 0.0201

TWS -0.000825 0.158823 -0.005194 0.9959 NTK 0.056670 0.361326 0.156839 0.8754 TW 0.238020 0.166217 1.431981 0.1521 CW 0.177554 0.214087 0.829351 0.4069

Mean dependent var 0.780488 S.D. dependent var 0.414026 S.E. of regression 0.407981 Akaike info criterion 1.039807 Sum squared resid 310.0935 Schwarz criterion 1.107395 Log likelihood -957.5377 Hannan-Quinn criter. 1.064697 Restr. log likelihood -992.5827 Avg. log likelihood -0.507708 LR statistic (22 df) 70.08992 McFadden R-squared 0.035307 Probability(LR stat) 6.40E-07

Obs with Dep=0 414 Total obs 1886 Obs with Dep=1 1472

ii

The McFadden R-squared value (the percentage that the independent

variables can explain the dependent variable) is 0.035307. And it is

surprising that the “GFA” variable is highly insignificant at 92.44%. This

shows that the probability of linear relationship between “GFA” and the

Decision of the planning application is low. In order to reduce the problem

of heteroscedasticity, the variable “GFA” is reciprocated into “1/GFA” in

Table 3.

In the model, only 3 variables: “RES” (5.50%), “ABERDEEN” (3.70%) &

“ST” (2.01%) are significant in the first linear test. All other variables are

shown insignificant in the result.

iii

Table 3: Second Linear form of Probit Results of independent variables

excluding “SR”, “AFTER01”, “KT”, “TWS”, “NTK”

Dependent Variable: DECISION

Method: ML - Binary Probit

Date: 12/27/04 Time: 23:18

Sample(adjusted): 5 1896

Included observations: 1887

Excluded observations: 5 after adjusting endpoints

Convergence achieved after 4 iterations

Covariance matrix computed using second derivatives


C 0.158148 0.149031 1.061175 0.2886

1/GFA 0.161176 0.603195 0.267204 0.7893

OUB 0.336421 0.228931 1.469529 0.1417

RES 0.563647 0.290954 1.937236 0.0527

COM 0.042319 0.090564 0.467285 0.6403

OFF 0.138081 0.081116 1.702270 0.0887

BANK -0.181282 0.121689 -1.489719 0.1363

IO -0.029324 0.096815 -0.302883 0.7620

HOTEL 0.459435 0.364650 1.259935 0.2077

REST 0.102220 0.129431 0.789765 0.4297

S16 0.533835 0.111353 4.794088 0.0000

KLN 0.058608 0.101103 0.579688 0.5621

NT 0.059787 0.104252 0.573491 0.5663

ABERDEEN -0.315850 0.138558 -2.279552 0.0226

CSW -0.101254 0.091600 -1.105400 0.2690

ST 0.256517 0.108526 2.363653 0.0181

TW 0.230376 0.161524 1.426270 0.1538

CW 0.113444 0.205327 0.552501 0.5806

Mean dependent var 0.780074 S.D. dependent var 0.414306

S.E. of regression 0.407872 Akaike info criterion 1.036163

Sum squared resid 310.9263 Schwarz criterion 1.089035

Log likelihood -959.6202 Hannan-Quinn criter. 1.055634

Restr. log likelihood -994.0981 Avg. log likelihood -0.508543

LR statistic (17 df) 68.95581 McFadden R-squared 0.034683

Probability(LR stat) 3.26E-08

Obs with Dep=0 415 Total obs 1887

Obs with Dep=1 1472

iv

The McFadden R-squared value is changed from 0.035307 to 0.034683; this

indicates that the effect of exclusion is little. After the reciprocal of the

variable of “GFA”, the value is still insignificant at 78.93%; this can prove

that the size of the proposed development does not affect much of the

decision for the planning permission of the Town Planning Board.

v

Table 4: Third Linear form of Probit Results of independent variables

excluding “1/GFA”, “COM”, “IO”, “KLN”, “NT”, “CW”



Date: 12/27/04 Time: 23:20







C 0.222815 0.117465 1.896853 0.0578

OUB 0.352840 0.224417 1.572249 0.1159

RES 0.583800 0.283461 2.059539 0.0394

OFF 0.138498 0.073060 1.895675 0.0580

BANK -0.187993 0.116746 -1.610274 0.1073

HOTEL 0.210204 0.324907 0.646967 0.5177

REST 0.107872 0.126817 0.850614 0.3950

S16 0.526542 0.110415 4.768740 0.0000

ABERDEEN -0.314072 0.137006 -2.292392 0.0219

CSW -0.102906 0.090385 -1.138525 0.2549

ST 0.267453 0.105485 2.535469 0.0112

TW 0.223629 0.160056 1.397197 0.1624







Probability(LR stat) 1.38E-09


Obs with Dep=1 1477

vi

Table 5: Final Linear form of Probit Results of independent variables

excluding “HOTEL”, “REST”, “CSW”

In the final results, nearly all the variables are significant. “OUB”, “RES”,

“OFF”, “BANK”, “ABEDEEN” and “ST” are significant at 0.90%, 3.49%,

5.78%, 11.69%, 3.26% and 0.63% levels respectively.



Date: 12/27/04 Time: 23:21







C 0.203654 0.112141 1.816047 0.0694

OUB 0.444329 0.170039 2.613109 0.0090

RES 0.596750 0.282895 2.109439 0.0349

OFF 0.136440 0.071920 1.897112 0.0578

BANK -0.182854 0.116625 -1.567886 0.1169

S16 0.531834 0.109911 4.838781 0.0000

ABERDEEN -0.288833 0.135189 -2.136516 0.0326

ST 0.280650 0.102767 2.730925 0.0063

TW 0.243893 0.158585 1.537936 0.1241






LR statistic (8 df) 61.21854 McFadden R-squared 0.030613 Probability(LR stat) 2.69E-10


Obs with Dep=1 1477

vii

Table 6: Probit Results of independent variables to investigate whether

OU (Business) Zones and Industrial Zones can be distinguished

as separate



Date: 12/27/04 Time: 22:58







C 0.685146 0.043865 15.61944 0.0000

1/GFA 0.422657 0.643613 0.656694 0.5114

OUB 0.389106 0.187398 2.076355 0.0379

COM 0.062083 0.085617 0.725121 0.4684

OUBCOM 6.287131 143156.7 4.39E-05 1.0000

OFF 0.144096 0.069545 2.071970 0.0383

OUBOFF -0.132368 608531.7 -2.18E-07 1.0000






LR statistic (6 df) 18.19340 McFadden R-squared 0.009132 Probability(LR stat) 0.005767


Obs with Dep=1 1474

From the results, the two variables “OUBCOM” and “OUBOFF” are 100%

not significant. This can indicate that the application uses of commercial and

office uses in OU (Business) Zones do not have a higher chance to be

approved by the Town Planning Board. Therefore, the two zoning classes

(OU (Business) and Industrial Zones) can be regarded as “inseparable” on

the commercial and office uses.

viii

Table 7: Probit Results of independent variable, “AFTER01”



Date: 12/27/04 Time: 23:22


Included observations: 1896 after adjusting endpoints




C 0.747163 0.033379 22.38455 0.0000

AFTER01 0.305092 0.124887 2.442932 0.0146







Probability(LR stat) 0.012379


Obs with Dep=1 1478

The variable of “AFTER01” is significant at 1.46%. But the McFadden

R-squared is quite low which is only 0.003128. This may be resulted of the

limited amount of planning application data after January 2001.

ix

Appendix II

Fig. 1 (Photograph taken on 20-3-2005)


Figs. 1 & 2 show the proposed fast food development in Unit A8, G/F,

Koon Wah Mirror Group Building, 2 Yuen Shun Circuit, Siu

Lek Yuen, Sha Tin (File Reference: A/ST/603)

x



Figs. 3 & 4 show the proposed office development in Unit 1-7, 20/F, Chai

Wan Industrial City Phase I, Chai Wan (File Reference:

A/H20/129)

xi



Figs. 5 & 6 show the proposed development of temporary showroom

(display of autoparts) for a period of 3 years in Unit 1(Part),

G/F, Topsail Plaza, 11 On Sum Street, Sha Tin (File reference:

A/ST/585)

xii



Figs. 7 & 8 show the proposed development of temporary office (estate

agency) for a period of 3 years in Unit 2(Part), G/F, Topsail

Plaza, 11 On Sum Street, Sha Tin (File reference: A/ST/587)

xiii



Figs. 9 & 10 show the proposed development of temporary retail shop (toy

shop) for a period of 3 years in Unit 3(Part), G/F, Topsail Plaza,

11 On Sum Street, Sha Tin (File reference: A/ST/586)

xiv



Figs. 11 & 12 show the proposed hotel development in 24 Lee Chung Street,

Chai Wan (File reference: A/H20/126. The application was

rejected under s.16)

xv



Figs. 13 & 14 show the wholesale (stationery) development in Unit 9B,

Level 1, Wah Yiu Industrial Centre, 30-32 Au Pui Wan

Street, Sha Tin (File reference: A/ST/588)

xvi

Index of Names

Abercrombie……………………………… 3, 31

Abercrombie and Plumstead……………... 3, 31

Abercrombie et. al............................... …... 3, 31

Ameniya...................................................... 15, 31

Bourassa……………………………... …... 14, 32

Brothern……………………………........... 2, 32

Brotherton………………………….... …... 3, 32, 38

Chan…………………………………. …... 3, 15, 22, 33

Chau, Hammer and Lai…………………... 4, 33

Dobry………………………………........... 2, 3, 34

Finney…………………………………….. 15, 34

Gilg and Kelly…………………………..... 3, 4, 34

Goodman………………………………….13, 34

Goodman and Kawai………………........... 13, 34

Hsueh and Chen …………………………. 14, 35

Kwan……………………………………... 3, 15, 22, 35

Lai………………………………………… 3, 4, 8, 14, 22, 36

Lai and Ho………………………………... 3, 4, 10, 14, 15, 19, 22, 37

Lee and Trost……………………………... 13, 38

Long……………………………………… 18, 38

McNamara and Healey…………………… 3, 32

Ngai…………………………………......... 3, 15, 39

Potepan…………………………………… 14, 39

Preece…………………………………….. 3, 39

Sellgren………………………………........ 3, 40

Staley…………………………………....... 3, 4, 22, 40

Tang and Choy…………………………… 3, 4, 7, 19, 40

Tang and Tang……………………………. 3, 4, 6, 7, 19, 40

Tang et. al.………………………………... 3, 4, 7, 40

Theil……………………………………… 13, 40

Tobin…………………………………....... 17, 41

Wan………………………………………. 3, 15, 22, 41

Willis…………………………………....... 3, 5, 6, 42

Yung……………………………………… 3, 42

xvii

Index of Terms

Aggregate…………………………………………. 2, 3, 40

Case-by-case……………………………………… 9, 11

Column 2………………………………………….. 27

Development control(s)…………………………… 2, 3, 4, 5, 7, 31, 32, 33,

34, 37, 38, 39, 40, 41, 42

District(s)…………………………………………..20, 22, 27, 30

GFA………………………………………………..10, 19, 22

Hypothesis(es)……………………………………..6, 9, 10, 11, 12, 13, 21,

22, 23, 25

Industrial Zone(s)…………………………………. 1, 9, 10, 11, 12, 18, 19,

20, 21, 22, 23, 24, 27, 29,

30

Non-aggregate……………………………………..1, 3, 4, 5, 6

Other Specified Uses annotated Business Zone(s)... 1, 2, 18, 19, 41

OU (Business) Zone(s)……………………………. 1, 2, 9, 10, 11, 12, 19, 20,

21, 22, 23, 24, 27, 29, 30

Planning application(s)……………………………. 1, 2, 5, 6, 9, 10, 11, 12,

15, 16, 17, 18, 19, 20, 23,

25, 27, 28, 32, 33, 35, 37,

38, 41

Planning permission(s)…………………………….1, 5, 9, 10, 11, 12, 14, 21,

22, 23

Probit Model………………………………………. 1, 13, 14, 15, 16, 31, 37

Public interest……………………………………...9

Region(s)…………………………………………..11

Rent-seeking……………………………………….1, 4, 10, 19, 22

Statutory plan(s)……………………………….......8, 41

s.16 ………………………………………………... 1, 8, 12, 21, 25, 28

s.17(1)……………………………………………... 12, 21, 28

s.17(B)…………………………………………….. 12, 21, 28

Town Planning Board……………………………...1, 2, 6, 7, 8, 9, 10, 11, 12,

14, 17, 18, 19, 21, 22, 24,

27, 28, 30, 41

Zone Separation……………………………………1, 14, 27, 35, 37, 38, 42

Zoning……………………………………………...6, 19, 22, 27, 36, 39, 40

Documents

Probit analysis of planning statistics on case study zone Author(s ... · to 2004). For the selected zones, it is found that getting planning permissions in OU (Business) Zones from