Luận án tiến sĩ kinh tế quản lý đề tải nghiên cứu một số yếu tố ảnh hưởng đến giá đất ở đô thị tại thành phố thái nguyên, tỉnh thái nguyên

V

MINISTRY OF EDUCATION AND TRAINING
THAI NGUYEN UNIVERSITY

NGUYEN NGOC ANH

RESEACH ON FACTORS AFFECTING PRICES OF URBAN
RESIDENTIAL LAND IN THAI NGUYEN CITY, THAI
NGUYEN PROVINCE

Speciality: Land Managerment
Code: 62.85.01.03

SUMMARY OF PHILOSOPHY
DOCTORAL DISSERTATION

Thai Nguyen, year 2017


The dissertation has been completed at:
College of Agriculture and Forestry - Thai Nguyen University

Scientific Supervisor:
Assoc. Prof. Nguyen The Hung, PhD

Reviewer 1: …………………………………………………………
Reviewer 2: …………………………………………………………
Reviewer 3: …………………………………………………………

PhD. Dissertation will be presented and defended at the College of

Agriculture and Forestry - Thai Nguyen University.
At

am/pm date

PhD. Dissertation would be found in:
- National Library
- Learning Resource Centre - TNU
- Library in College of Agriculture and Forestry

month

year 2017


LIST OF PUBLICATION
RELATED TO PhD. DISSERTATION

1. Nguyen Ngoc Anh, Nguyen The Hung, Phan Dinh Binh
(2016). The study of factors affecting urban land price in Thai
Nguyen city, Thai Nguyen province. Journal on Agriculture and
Rural Development, No. 12, 2016, pp. 26 - 33
2. Nguyen Ngoc Anh, Nguyen The Hung, Phan Dinh Binh
(2016). Study on the difference between land urban price on the
market and land price regulation in Thai Nguyen city, Thai Nguyen
province. Journal on Agriculture and Rural Development, No. 19,
2016, pp. 18 - 26.


INTRODUCTION

1. The necessity of the study
In fact, the land price market in Thai Nguyen city is a significant
fluctuations, price increases strongly and rapidly over the years.
Meanwhile, to ensure the stability of economic - social issues, the
land price of the State does not increase which causes a huge
difference level compared to the market. This leads to the number of
shortcomings in managing and using land. Background on the set for
the show to systematically review the rationale and practice of land
valuation, assessing the impact of factors to the value of land as a
basis for completion of management and valuation to apply in
Vietnam in the coming time is necessary, given both theoretical and
practical. Stemming from this reality, thesis: "Research on factors
affecting price of urban residential land in Thai Nguyen City, Thai
Nguyen Province" to contribute to the work gradually improved
valuation of land urban in Thai Nguyen city - Thai Nguyen province.
2. Research Objectives
- Research on the relationship and differences between land urban
prices in the market and land prices by state regulation in Thai
Nguyen city.
- Identify and analyze the influence of a number of factors
affecting the land urban price to building land valuation standards to
fit with the price index in the market of Thai Nguyen city.
- Preliminary research building modeling land urban valuation in
the Thai Nguyen city to make forecasts for the future in a scientific
way, help the State capture, management of land prices, study the
formation and development of the real estate market, therefrom
giving appropriate management measures.
1

3. The contributions of the thesis
3.1. Scientific significance
Contributing to clarify the scientific theory about the factors
affecting land urban prices and mass valuation of land urban in
Vietnam.
3.2. Practical significance
- Contribute to raising knowledge of land price management
system in the Thai Nguyen city about the factors affecting land urban
prices, creating conditions for raising the quality of land prices
management in the Thai Nguyen city.
- Create tools of mass land valuation, can be applied to improve
the process of building the State's land price in the Thai Nguyen city.
4. New scientific findings
(1) Identifying the most important factors affecting land prices,
level of their influence and factor ranking by their level affecting the
urban residential land price in the Thai Nguyen City. Those factors
are: location, infrastructure, environmental condition, legal policy,
individual characters of land parcels, economic and social condition.
(2) The study initially identified the equations describing
dependence of urban residential land price on above-mentioned
factors. This equation is a foundation for constructing Thai Nguyen
provincial urban residential land price and for consulting price for a
given specific urban residential land parcels in Estate Agent.
5. Thesis structure
The thesis includes 120 pages typed in A4 size divided in 3 chapters
excluding introduction, conclusion and recommendations (Chapter 1:
Document Overview, Chapter 2: Content and Reseach methods,
Chapter 3: Results of research).
The thesis has 22 tables and 08 figures (excluding the appendix for
illustration), gets reference from 86 documents, in which 64 documents

are in Vietnamese, and 22 documents are in foreign languages.
2


Chapter 1
DOCUMENT OVERVIEW
Through research and analysis of relevant issues in Vietnam and
other countries in the world, it shows that research results obtained
fairly systems in various fields:
- Concept of land market: There are many different concepts,
however, all most of them show that land market includes civil
transactions according to the law in an area and in a certain time. It
is active market for transactions such as: business, exchange, rent,
mortgage, demise,…
- Land prices, land valuation: In terms of overall, land price is the
selling price of land ownership, is the value of that land ownership in
space and determine time. Land valuation is an estimate of land
value in monetary form for an intended use has been identified, at a
determine time.
- Land valuation methods: To estimate value of real estate, can
use the methods of real estate valuation different. However, in the
operation valuation, we can not use a independently method which
between them have a relationship of mutual cross-checking.
- Experience management and valuation of countries in the
world: Synthesis and summarize the experience of countries in the
world in the use of land valuation methods, ways of organizing,
construction and public announced land price.
- Factors affecting land price: The study has shed light on the
factors affecting land price, On the basis of explaining to confirm the
reliability and effect of factors in calculation process of determining

land prices.
3


Chapter 2
CONTENT AND RESEACH METHODS
2.1. Object and scope of the study
The thesis research management, land valuation and the factors
affecting the land urban price in the Thai Nguyen city, Thai Nguyen
Province.
2.2. Contents of the study
2.2.1. Natural conditions, society-economic and land use situation in
Thai Nguyen city.
2.2.2. Evaluation of construction, management and land urban price
movements follow prescribed by state in the Thai Nguyen city.
2.2.3. The difference between the State’s land urban price and land
price market in the city.
2.2.4. Factors affecting the land urban price in the study area.
2.2.5. Preliminary studies modeling to determine land urban prices
in Thai Nguyen city.
2.2.6. Solutions proposed to effectively perform the valuation and
management of land urban in Thai Nguyen city.
2.3. Reseach methods
2.3.1. Methods of collecting secondary data
2.3.2. Research methods for selecting the location and route survey
Select areas, representative streets, reflect the economic
development, social of the city and land prices of the region, that
route is more movement.
2.3.3. Methods of survey sampling, interviews
1. Determine samples number of collecting

4


- To evaluate the factors affecting the land urban price in the Thai
Nguyen city, the study surveyed 300 sample includes objects that the
staff of Resources & Environment Department, officials of land
registration office, real estate investors, brokers, ...
- To build predictive models to determine land urban prices in
Thai Nguyen city, researchers surveyed 250 samples are successfully
transferred property in the city.
2. Building investigation form
On the basis of information to be collected, studied conducting
investigation form designed to collect information on factors affecting
land prices and investigation form to collect information on land
urban plots transferred success in the Thai Nguyen city.
3. Sampling methods
Conducting a surveys of 300 samples to collect information
investigate the factors affecting land urban prices in Thai Nguyen
city, of which 216 samples are individual stock investing and real
estate business in the 18 wards of Thai Nguyen city (12 samples per
ward); 70 samples is the staff of Resources and Environment
departments, officials land registration office, ... and 14 samples is
the teller at the real estate broker center in the Thai Nguyen city.
Conducting a survey of 250 samples are real estate successfully
transferred located on 27 selected routes (region I: 9 routes; region II:
9 routes and region III: 9 routes). In addition, there is the consultation
of cadastral officer and teller in the real estate brokers center in the
Thai Nguyen city to get information and more accurate judgment.
2.3.4. Statistical methods, described

2.3.5. Comparative method
2.3.6. Analytical methods determine the factors affecting land prices
5


1. Quy trình nghiên cứu

Figure 2.1: Process of researching factors effect
to land price
2. Scales design
Liker scale: level 1: Not important; level 2: Less important; level
3: Neutral (not identified important or not); level 4: Important; level
5: Very important.
3. Theories inspection and assessment
(1) Scale quality inspection:
According to Hoang Trong and Chu Nguyen Mong Ngoc (2005)
defined criteria Cronbach Alpha coefficients have values from 0,8 to
nearly 1 are possible scale; from 0,7 to 0,8 can be used. According to
Nunnally, J. C (1978) and Robert A. Peterson (1994), said that
Cronbach's alpha is 0,6 or higher can be used. In addition, to use
additional criteria total correlation coefficient (Corrected Item - Total
6


Correlation), in which the variables has total correlated variables
<0,3 will be removed.
(2) Analysis of EFA explored factors
- Suitability inspection of EFA: Standard: 0,5 ≤ KMO ≤ 1,0 and
Sig. <0,05; If KMO <0,5, factor analysis is not appropriate for data.
- Correlation inspection of observed variables: Use Bartlet test to

evaluate observed variables are correlated with each other in a scale
(factor). When significance level Sig. of Bartlet test ≤ 0,05 =>
observed variables are correlated linearly with representative factors.
- Interpretation inspection of observed variables with factor: Use
extracting factors standard including Eigenvalue index (representing
variation is explained by factors) and Total Varicance Explained
index (total variance extracted show that factors explain how much
percent). According to, Eigenvalue ≥1 and total variance ≥ 50%.
- Standard of factor loading: Factor loading is an indication to
ensure practical significance of EFA (Ensuring practical-significance),
indicates single correlation between variables with factors, is used to
assess EFA significance. According to Hair & ctg (1998), said that:
Factor Loading ≥ 0,55 if 100 ≤ sample size <350 samples.
(3) Inspections of multivariate regression analysis:
- Partial correlation inspection of regression coefficients: When
Sig. significance of regression coefficient less than 0,05 (Sig. <0,05),
which of reliability significance is 95%, will be concluded correlated
with statistically significant between independent variables and
dependent variables.
- Suitability inspection of model: Using analysis of ANOVA
variance (Analysis of variance) to test. If level of significance to
ensure reliability of at least 95% (Sig.<0,05), reject H0 hypothesis
and H1 hypothesis be accepted => model considered appropriate.
7


- Testing of multi-collinear phenomenon: When VIF coefficient
<10, model not multi-collinearity phenomenon.
- Inspection of constant residual variance: In this case, using
Spearman test: If level of significance (Sig.) of Spearman correlation

coefficient assurance greater 0,05 (Sig.> 0,05); accept H0 and reject
H1, and conclude that model has constant residual variance.
2.3.7. Construction method of land price regression model
1. Research model
Regression model used by author is multivariate regression
model, which forms of general formula:
Yi = β0+ β1 X1 + β2X2+ β3X3 + ... + βnXn + ei
2. Research process

Figure 2.2: Analysis diagram of Regression process

3. Hypotheses testing and model evaluation
Regression model to ensure reliability and efficiency to
implement inspection as described in content (3) Section 2.3.6.
8


Chapter 3
RESULTS OF RESEACH
3.1. Natural conditions, social-economic and land use situation in
Thai Nguyen city
3.1.1. Natural conditions
Thai Nguyen city is grade I urban, located in mountainous of
Northern center region, Northeast Hanoi capital about 80km and is
surrounded by 5 districts of Thai Nguyen province, with 18.630,56ha
total area. Thai Nguyen city bearing same features of Vietnam
Northeast climate, under denatured monsoon tropical, climate has 2
distinct seasons.
3.1.2. Economic and social conditions
Although Thai Nguyen city is a center of Thai Nguyen province,

but agricultural land still accounts for 65,15% of total natural land.
Agricultural production has been positive change in both quantity and
quality, development of commodity production, farming practices,
technical, productivity, output has been enhanced over the years.
3.1.3. Lan use and management
3.1.3.1. Land use
As result of land inventory on 01.01.2015, natural area of Thai
Nguyen city is 18.630,56 ha, by using the following purposes:
Farmland: 12.138,87 ha; Non-agricultural land: 6.122,94 ha. Unused
land: 368,75 ha.
3.1.3.2. Land management
Since 1993, land law was enacted with provisions for land
allocation stable, long-term users are tied to land use rights extend
close to ownership, management state of land use rights with
variables important change in terms of both quantity and quality. The
9


State has issued many legal documents specifying Land law, which
recognizes land valuable and is a special commodity, whereby the
transfer relations, trade ... more common place, but management to
more difficult and complicated.
3.2. Evaluation of construction, management and land urban price
movements follow prescribed by state in the Thai Nguyen city.
3.2.1. Management of land prices
To carry out construction of land price and land price announced,
Committee of Thai Nguyen Province are issued document: Designation
1365/2004/QD-UB in 21/06/2004; Designation 498/2007/QD-UB in
03/23/2007; Designation 03/2012/QD-UB in 21/02/2012 and
Designation 13/2015/QD-UB in 15/6/2015 of Committee, promulgating

regulations to order and procedures for determining land price and
specific land valuation in Thai Nguyen province.
3.2.2. Construction of land price
Process of building land prices in Thai Nguyen province with
Designation 03/2012/QD-UB in 21/02/2012 of Committee of Thai
Nguyen province.
3.2.3. Land urban price movements of State in the Thai Nguyen
city period 2010 - 2014
In recent years, land price in Thai Nguyen city is fluctuated. To
explore and evaluate factors affecting land prices in the city, the
study conducts genaral land prices in some road represent 03 streets
types of city from 2010 to 2014. The results showed that, land urban
price was also rised significantly, but it was not constant and strong
fluctuation through the years. Land prices was defined in routes of
center city, near the center and outlying routes tended to increase
from 2010 to 2011, from 2012 to 2014, land prices was stable.

10


3.3. The difference between the State’s land urban price and land
price market in the city

Figure 3.3 and 3.4: Land price regulations and actual price at I area
and II area

Figure 3.5: Land price regulations and actual price at III area

3.3.4. General assessment
We can say that the annual land valuation is still heavily form

without close to reality, because since the collection of data to build
land price until the list issued, the actual transfer price in the market
has a lot of volatility. There are also other factors such as the:
infrastructure, individual elements of land, land speculation, policies,
market information,...
* The difference between land price in the market and land prices
regulation in Thai Nguyen city may consider some basic reasons as follows:
The Land price list current of the State regulations only divided
city roads, no specific price list.
11


Valuation is not concerned with individual factors such as the area of
land plots, the shape, the width of the facade, environmental quality, ...
The State are still not institutions tracking systems land price on
the market as a basis for appropriate valuation.
Infrastructure is the foundation for development of the region, so
when the residential area is construction of infrastructure systems
well, where land values are rising.
Speculative factors governing the land market has created extreme
volatility of prices, land prices in the market at very high levels.
3.4. Factors affecting the land urban price in the study area.
3.4.1. Factors affecting
Table 3.9: Factors affecting land price
Numerical

Group factors affecting land prices

1

Location factors

2

Economic factors

3

Social factors

4

Enviroment factors

5

Individual factors

6

Infrastructure factors

7

Legal policy factors

12

Factors affecting land price
- Distance to the Center

- Distance to the Market
- Distance to the School
- Distance to the bus station
- Distance to the Hospital
- Economic growth rate
- Supply - demand for land on the market
- Incomes and expenditures of population
- Volatility and Pricing
- interest rate
- Urbanization
- Land speculators
- Population density
- Medical and education
- Education of the population
- Vấn đề về phong thủy
- Environmental Quality
- Social Security
- Business environment
- Shape
- Area
- Depth
- Width
- Water and electricity system
- Communications system
- Transport system
- Legal status of land
- Policies for land use
- Planning limited

3.4.2. Analyze and evaluate affecting of these factors
3.4.2.1 Research model

Figure 3.6: Reseach model of factors affecting land price

3.4.2.2. Cronbach's Alpha coefficient test
According to analytical scales testing, scales ensure standards
with Cronbach's Alpha > 0,6 and scale has total variable correlation
coefficient with standard <0,3 to be removed.
Table 3.11: Scale of factors influence Cronbach's Alpha analysis later
Variables reliability
Numerical

Scale

1
2
3
4
5
6
7

Location factors
Economic factors
Social factors
Enviroment factors
Infrastructure factors
Individual factors
Legal policy factors

Number
5
3
4
3
3
3
3

8

Affecting land price

7

Cronbach’s Alpha
variable name
VT1; VT2; VT3; VT4; VT5
KT2; KT3; KT5
XH1; XH3; XH4; XH5
MT1; MT2; MT3
HT1; HT2; HT3
CB1; CB2; CB4
CS1; CS2; CS3
AH1; AH2; AH3; AH4;
AH5; AH6; AH7

Variables unuse
Number

0
2
2
0
0
1
0

variable name
KT1; KT3
XH2; XH6

CB3

0

Source: General results

3.4.2.3. Inspection of EFA explore factors
Through analysis, scale quality inspection and testing of EFA
models, give new model includes 24 variasbles characterizing 7
13


representative elements groups and results are aggregated together
with factors affecting one group land prices as table 3.13.
Table 3.13: Model adjusted through Cronbanh's Alpha testing and EFA
Numerical
1
2

3
4
5
6
7
8

Factor
group code

Variables

X1
X2
X3
X4
X5
X6
X7
Y (Biến phụ
thuộc)

VT1. VT2. VT3. VT4. VT5
KT2. KT4. KT5
XH1. XH3. XH4. XH5
MT1. MT2. MT3
HT1. HT2. HT3
CB1. CB2. CB4
CS1. CS2. CS3
AH1. AH2. AH3. AH4.

AH5. AH6. AH7

Cronbach's
Alpha coefficient
after correction
0.809
0.849
0.942
0.774
0.801
0.873
0.850

Factors Group
name
Location
Economic
Social
Enviroment
Infrastructure
Individual
Legal policy
Affecting land price

0.888

Source: General results

3.4.2.4. Evaluate affect of factors by regression model
From table 3.14, shows that βi regression coefficients. Consider

unstandardized regression coefficients in column B. We can to
estimate temporarily sample regression models prior to testing, the
model is expressed as follows:
Y = 0,041 + 0,450X1 + 0,085X2 + 0,027X3 + 0,201X4 + 0,296X5
+ 0,105X6 + 0,153X7
Table 3.14: Results of regression coefficients
Model

1

Constant
x1
x2
x3
x4
x5
x6
x7

Unstandardized
regression
B coefficient Std.error
0.041
.059
.450
.007
.085
.006
.027
.006

.201
.007
.296
.007
.105
.005
.153
.004

Standardized
regression
Beta
.450
.085
.027
.201
.296
.105
.153

t

Sig.

Collinearity statistics
Tolerance

52.953
48.603
-.922

-2.191
-10.804
1.580
-.159
-2.713

.000
.000
.000
.000
.000
.000
.000
.000

.992
.948
.993
.946
.983
.988
.993

VIF
1.008
1.055
1.007
1.057
1.017
1.012

1.007

Source: Analysis results

Based on standardized regression coefficient, can be converted
into a percentage and sorted by priority order from high to low as the
following table:
14


Table 3:15. Infulence level of factors to land prices
Factors affecting Group
X1 - Location
X2 - Economic
X3 - Social
X4 - Enviroment
X5 - Infrastructure
X6 - Individual
X7 - Legal policy
Total

Unstandardized
regression
0.450
0.085
0.027
0.201
0.296
0.105
0.153

1.317

Percentage
34.17
6.45
2.05
15.26
22.48
7.97
11.62
100.00

Affects
order
1
6
7
3
2
5
4

Source: Analysis results

3.5. Preliminary studies modeling to determine land urban prices
in Thai Nguyen city
3.5.1. Selection and variable format for research models
Table 3.16: Variable format for land price regression model
Numerical
A

1
B
1

4

Variable code
Description
Dependent variable
G_DAT
Land price
Biến độc lập
KC_TT
Distance to the center
Distance to the utility
KCTI_1
(market, supermarkets,
schools, hospitals, ...)
Distance to the utility
KCTI_2
(market, supermarkets,
schools, hospitals, ...)
D_TICH
Area

5

H_THE

Shape

Qualitative

6
7

CR_MT
CR_DUONG

Width
Width street

Quantitative
Quantitative

8

CL_DUONG

Quality street

Qualitative

9

TT_LL

Communications

Qualitative

10

DIEN_NUOC

Water and electricity
system

Qualitative

11

MTST_TOT

Good environment

dummy

12

MTST_BT

Normal environment

dummy

13

AN_TOT

Good security

dummy

14

AN_BT

Nomal security

dummy

15

MTKD_TOT

Good business
environment

dummy

16

MTKD_KHA

Nomal business
environment

dummy

17

P_LY

Legal of land

dummy

18

Q_HOACH

Pland

dummy

2

3

Types

Unit

Expected
2

Quantitative

Million VND /m

Quantitative

m
1 = Distance to utility ranging
from 0 - 1000m
0 = Distance to remaining utility
1 = Distance to utility ranging
from >1000 - 2000m
0 = Distance to remaining utility
m2
1 = square
0 = not square
m
m
1 = Good
0 = Nomal
1 = Good
0 = Nomal
1 = Good
0 = Nomal
1 = Good environment
0 = Remaining environment
1 = Normal environment
0 = Remaining environment
1 = Good security
0 = Remaining security
1 = Nomal security
0 = Remaining security
1 = Good business environment

0 = Remaining business
environment
1 = Nomal business environment
0 = Remaining business
environment
1 = Full legal papers
0 = Not enough legal papers
1 = Not frozen plans
0 = frozen plans

dummy

dummy
Quantitative

+

+
+
+
+
+
+
+
+
+
+
+
+
+

+
+
+

Source: Reseach results
15


3.5.2. Construction and model selection
3.5.2.1. Statistics describing variables in the model
To conduct regression, study used 250 sample properties located
frontage on main roads in Thai Nguyen city and distributed them to
ward in the city.
3.5.2.2. Land price regression model
1. Land price regression model for first time
Running first regression model with all 18 independent variables,
the results as:
Table 3.18: Results of the first regression model
Model

1

(Constant)
KCTT
KCTI_1
KCTI_2
CR_DUONG
CL_DUONG
TT_LL

DIEN_NUOC
D_TICH
H_THE
CR_MT
MTST_TOT
MTST_BT
AN_TOT
AN_BT
MTKD_TOT
MTKD_KHA
P_LY
Q_HOACH

Unstandardized
regression
B coefficient Std.error
1917.864 1550.739
-.725
.085
2201.828
669.507
763.867
537.032
241.873
37.649
2401.187
590.931
-165.813 1196.882
389.288
588.962

-11.219
7.647
2117.450
509.722
241.896
247.026
7966.060
762.546
2276.749
625.489
388.813 1180.560
-984.817 1021.522
15076.707 1046.562
3968.087
400.862
-1702.722
403.110
1344.354
453.689

Standardized
regression
Beta
-.248
.126
.044
.169
.139
-.004
.015

-.072
.104
.050
.357
.121
.023
-.056
.327
.226
-.097
.066

t

Sig.

Collinearity statistics
Tolerance

1.237
-8.518
3.289
1.422
6.424
4.063
-.139
.661
-1.467
4.154
.979

10.447
3.640
.329
-.964
14.406
9.899
-4.224
2.963

.217
.000
.001
.156
.000
.000
.890
.509
.144
.000
.328
.000
.000
.742
.336
.000
.000
.000
.003

.491

.285
.428
.598
.356
.403
.768
.170
.667
.159
.355
.377
.088
.121
.803
.794
.785
.832

VIF
2.038
3.514
2.338
1.672
2.808
2.482
1.303
5.873
1.499
6.270
2.813

2.651
11.419
8.286
1.246
1.260
1.274
1.202

Source: Analysis results

Through analysis results in table 3.18, show that most of the
observed variables as expected and coefficient R2 = 0,897, variation
TT_LL, AN_BT, P_LY has reverse expectations. sig. value of
variables KCTI_2, TT_LL, DIEN_NUOC, D_TICH, CR_MT,
AN_TOT and AN_BT bigger 5% significance.
16


2. Land price regression model for second time
After removing variables P_LY, KCTI_2, TT_LL, DIEN_NUOC,
D_TICH, CR_MT, AN_TOT and AN_BT from model and again
running model with 10 remaining variables. We get following
results:
Table 3.20: Results of regression models for second time
Unstandardized

Standardized

regression

regression

Collinearity statistics
Model

B coefficient
(Constant)
KCTT
KCTI_1

1

Std.error

t

Sig.

Beta

Tolerance

VIF

306.452

1086.522

.282

.778

-.767

.072

-.262 -10.617

.000

.747

1.339

1967.134

568.678

.112

3.459

.001

.433

2.310

CR_DUONG

260.701

38.477

.182

6.775

.000

.628

1.591

CL_DUONG

2230.503

593.437

.129

3.759

.000

.388

2.580

H_THE

2737.723

456.343

.134

5.999

.000

.914

1.095

MTST_TOT

9155.560

752.149

.410

12.173

.000

.401

2.493

MTST_BT

2720.909

615.392

.144

4.421

.000

.428

2.338

MTKD_TOT

16164.243

1066.450

.351

15.157

.000

.848

1.179

MTKD_KHA

4425.717

385.573

.252

11.478

.000

.942

1.062

Q_HOACH

1101.007

454.518

.054

2.422

.016

.910

1.099

Source: Analysis results

Final result show that model is consonant, all of 10 variables are
statistically significant (Sig. <= 0,05). Research model has R2
coefficient is 0,887, It mean 88,7% change in GIA_DAT dependent
variable is explained by independent variables of model. then,
research give land urban price regression model for the main roads in
Thai Nguyen city as follows:
GIA_DAT

=

306,452

-

0,767*(KCTT)

+

1967,134*(KCTI_1)

+

260,701*(CR_DUONG) + 2230,503*(CL_DUONG) + 2737,723*(H_THE) +

17


9155,560*(MTST_TOT) + 2720,909*(MTST_BT) + 16164,243*(MTKD_TOT) +
4425,717*(MTKD_KHA) + 1101,007*(QH)

3.5.2.3. Reviews and model testing
* Testing of multicollinearity phenomenon: In the table 3:20,
columns Variance Inflation Factor values (magnification variance)
VIF <10. Besides, VIF = 1 / (1 - R2) = 1 / (1-0,887) = 8,45 <10.
Thus, no phenomenon of multi-collinearity in model.
* Testing of auto-correlation phenomenon
- Based on experience: according to regression results, we have d
= 1,886 value of about conditions 1 < d <3 so this regression model
not phenomena occur of auto-correlation.
- Based on Durbin-Watson testing: The results of statistical
analysis d = 1,886, with 250 sample observers; parameters k = 10;
Durbin - Watson statistical table has dL = 1,665 (statistical values
below) and dU = 1,874 statistical values over). Thus, dU = 1,874 < d
= 1,886 < (4 - dU = 2,126), there is no phenomenon of residual autocorrelation in model, model is signification.
* Testing of variance change phenomenon
As result we know, all the sig. (2-tailed) of independent variables
were > 0,05, which means that no residual variance. Thence, show
that model is stable, reasonable data. Thus, Spearman testing said
that residual variance unchanged.
Conclusion: Model is selected:
GIA_DAT

=

306,452

-

0,767*(KCTT)

+

1967,134*(KCTI_1)

+

260,701*(CR_DUONG) + 2230,503*(CL_DUONG) + 2737,723*(H_THE) +
9155,560*(MTST_TOT) + 2720,909*(MTST_BT) + 16164,243*(MTKD_TOT) +
4425,717*(MTKD_KHA) + 1101,007*(QH)

18


3.5.3. Application models to estimate urban land
Table 3:22: Results checking the accuracy of the estimated land urban
price in the Thai Nguyen city by regression models
Unit: 1000 VND/m2
Numerical
1
2
3
4

5
6
7
8
9
10
11
12
13

14
15
16
17
18
19
20

Land price
Regression
Compare
model
method

Addresses
Located on CMT8 street from Loang Bridge to
railway into 3 roof storage
Located on Hoang Van Thu street From Dong
Quang circle to Ha Thai railway

Located on Thong Nhat Street from Bac Nam
intersection to Ha Thai railway
Located on Luong Ngoc Quyen street from Thai
Nguyen bus station to Dong Quang circle (meet
Hoang Van Thu street)
Located on CMT8 street from Xuong Rong
crossroads to Gia Sang intersection (meet Bac
Nam street)
Located on Hoang Ngan street
Located on Hoang Van Thu street from center
circle to Nguyen Hue crossroads and Chu Van
An street
Located on CMT8 street from railway into 3 roof
storage to Kep railway
Located on 3/2 street from Phu Xa street to
Secondary School Tich Luong
Nằm trên Đường Dương Tự Minh Từ băng tải
than Núi Hồng đến cầu Tân Long
Located on Quang Trung Street: Ha Thai railway
to Z159 intersection
Located on Hoang Van Thu street: From Dong
Quang circle to Ha Thai railway
Located on Duong Tu Minh street from Mo
Bach Bridge to side entrance Cao Ngan thermal
power Company
Located on 3/2 street from Thong Nhat street
(Tuberculosis and Lung Diseases Hospital) to
College of Financial Economics crossroads
Located on Thong Nhat street: Ha Thai railway
to the end of Viet - Thai garment factory

Located on Duong Tu Minh street from Nui
Hong coal conveyor belt to Tan Long bridge
Located on Z115 street from Quang Trung street
to the end of student dormitory
Located on Quang Trung street: from Dan
overpass to Dan intersection go to Nui Coc +
100m (Dan Market)
Located on 3/2 street from Phu Xa street to
Secondary School Tich Luong
Located on CMT8 street from Street Thai
Nguyen Power Company - Thai Nguyen city
branch to Phan Dinh Phung street

Difference
(times)

12,315.62

11,500

816

28,584.37

30,500

1,916

15,960.03

16,500

540

31,552.19

33,000

1,448

20,422.94

19,500

923

24,281.18

23,000

1,281

40,870.05

43,500

2,630

9,961.40

9,500

461

11,923.65

11,000

924

14,119.23

15,500

1,381

19,353.47

18,500

853

31,168.69

32,500

1,331

12,270.32

11,500

770

9,605.24

9,000

605

14,414.46

15,000

586

11,552.95

10,800

753

10,510.15

11,200

690

17,512.67

16,500

1,013

7,672.64

7,500

173

22,543.48

25,000

2,457

Source: Calculated results and investigation

19


3.6. Solutions proposed to effectively perform the valuation and
management of land urban in Thai Nguyen city.
3.6.1. Facility proposed solutions
3.6.2. Solutions to implement management and land valuation
3.6.2.1. Capacity building awareness and computerization for the
organization of land prices management and valuation.
3.6.2.2. Building procedures to be applied the mass land price for
construction of land price list or land prices map of Provincial
People's Committees.

20


CONCLUSIONS AND RECOMMENDATIONS
1. Conclusions
(1). Basically land prices to be constructed have ensured the
difference between the street has the advantage for the business,
close to downtown, public works,... with the price higher of
streets in remote region central and not convenient for business,
trade and activities of the people (in the center and suburban
areas, the level of land price regulation difference between the
highest and lowest price is 13,33 times, the difference average
land price in the market is 8,9 times, differences between land
prices highest and lowest on the market is 39,75 times).
(2). Land prices on the same street in convenient location for the
business, trade will higher in less favorable locations. However, land
price regulation lower than land price in the market (the gap ranging
from 1,71 to 2,69 times), the price difference also decreases by
region and type of street.
(3). Group factors affecting land urban prices in Thai Nguyen city
includes 7 group factors: (1) X1 (Position), (2) X2 (Economics), (3)
X3 (Social), (4) X4 (Environment), (5) X5 (Individual), (6) X6
(Infrastructure) and (7) X7 (legal policy of the State). Relations
between the factors with land prices is shown by the model: Y =
0,041 + 0,450 * X1 + 0,085 * X2 + 0,027 * X3 + 0,201 * X4 + 0,296 *
X5 + 0,105 * X6 + 0,153 * X7. Therein, Location factors contributing
34,17%; Economic factors contributing 6,45%; Social factors
contribute 2,05%; Environmental factors contributing 15,26%;
Infrastructure

factors

contribute

22,48%;

Individual

factors

contributed 7,97% and Legal policy factors contributed 11,62%.
21


(4). Building land urban valuation modeling in Thai Nguyen city
for property located on main road in Thai Nguyen city, the following
models: GIA_DAT = 306,452 - 0,767 * (KCTT) + 1967,134 *
(KCTI_1) + 260,701 * (CR_DUONG) + 2230,503 * (CL_DUONG)
+ 2737,723 * (H_THE) + 9155,560 * (MTST_TOT) + 2720,909 *
(MTST_BT) + 16164,243 * (MTKD_TOT) + 4425,717 *
(MTKD_KHA) + 1101,007 * (QH). To apply results regression
model, the study conduct mass land valuation some real estate
representative for Thai Nguyen city.
(5). Propose some possibility solution to fulfill good management
and land urban valuation in Thai Nguyen city, Solution is: (1)
Capacity

building

awareness

and

computerization

for

the

organization of land prices management and valuation; (2) Building
procedures to be applied the mass land price for construction of land
price list or land prices map of Provincial People's Committees.
2. Recommendations
(1). Must being further study, expanded scope of the survey over
all districts, towns and cities in order to more accurately assess the
impact of these factors in a comprehensive manner, which can give
the annual land price close to more reality.
(2). Further researching on the land urban valuation model and
expand, additional land valuation model for other purposes used
such as the land of non-agricultural production business, land of
agricultural and forestry, ...
(3). Do not give fully the land valuation for administrative
agencies that need the combination between administrative agencies
and the independent valuation organization to build the land price
list market proximity.
22