Reseach on factors affecting prices of urban residential land in Thai Nguyen city, Thai Nguyen province

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)

pdf25 trang | Chia sẻ: tueminh09 | Ngày: 10/02/2022 | Lượt xem: 408 | Lượt tải: 0download
Bạn đang xem trước 20 trang tài liệu Reseach on factors affecting prices of urban residential land in Thai Nguyen city, Thai Nguyen province, để xem tài liệu hoàn chỉnh bạn click vào nút DOWNLOAD ở trên
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 month year 2017 PhD. Dissertation would be found in: - National Library - Learning Resource Centre - TNU - Library in College of Agriculture and Forestry 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. 1 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. 2 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. 3 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. 4 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 5 - 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 6 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 7 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. 8 - 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. 9 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 10 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. 11 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. 12 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 Factors affecting land price 1 Location factors - Distance to the Center - Distance to the Market - Distance to the School - Distance to the bus station - Distance to the Hospital 2 Economic factors - Economic growth rate - Supply - demand for land on the market - Incomes and expenditures of population - Volatility and Pricing - interest rate 3 Social factors - Urbanization - Land speculators - Population density - Medical and education - Education of the population - Vấn đề về phong thủy 4 Enviroment factors - Environmental Quality - Social Security - Business environment 5 Individual factors - Shape - Area - Depth - Width 6 Infrastructure factors - Water and electricity system - Communications system - Transport system 7 Legal policy factors - Legal status of land - Policies for land use - Planning limited 13 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 Numerical Scale Variables reliability Cronbach’s Alpha Variables unuse Number variable name Number variable name 1 Location factors 5 VT1; VT2; VT3; VT4; VT5 0 2 Economic factors 3 KT2; KT3; KT5 2 KT1; KT3 3 Social factors 4 XH1; XH3; XH4; XH5 2 XH2; XH6 4 Enviroment factors 3 MT1; MT2; MT3 0 5 Infrastructure factors 3 HT1; HT2; HT3 0 6 Individual factors 3 CB1; CB2; CB4 1 CB3 7 Legal policy factors 3 CS1; CS2; CS3 0 8 Affecting land price 7 AH1; AH2; AH3; AH4; AH5; AH6; AH7 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 14 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 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 Unstandardized regression Standardized regression t Sig. Collinearity statistics B coefficient Std.error Beta Tolerance VIF 1 Constant 0.041 .059 52.953 .000 x1 .450 .007 .450 48.603 .000 .992 1.008 x2 .085 .006 .085 -.922 .000 .948 1.055 x3 .027 .006 .027 -2.191 .000 .993 1.007 x4 .201 .007 .201 -10.804 .000 .946 1.057 x5 .296 .007 .296 1.580 .000 .983 1.017 x6 .105 .005 .105 -.159 .000 .988 1.012 x7 .153 .004 .153 -2.713 .000 .993 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: Numerical Factor group code Variables Factors Group name Cronbach's Alpha coefficient after correction 1 X1 VT1. VT2. VT3. VT4. VT5 Location 0.809 2 X2 KT2. KT4. KT5 Economic 0.849 3 X3 XH1. XH3. XH4. XH5 Social 0.942 4 X4 MT1. MT2. MT3 Enviroment 0.774 5 X5 HT1. HT2. HT3 Infrastructure 0.801 6 X6 CB1. CB2. CB4 Individual 0.873 7 X7 CS1. CS2. CS3 Legal policy 0.850 8 Y (Biến phụ thuộc) AH1. AH2. AH3. AH4. AH5. AH6. AH7 Affecting land price 0.888 15 Table 3:15. Infulence level of factors to land prices Factors affecting Group Unstandardized regression Percentage Affects order X1 - Location 0.450 34.17 1 X2 - Economic 0.085 6.45 6 X3 - Social 0.027 2.05 7 X4 - Enviroment 0.201 15.26 3 X5 - Infrastructure 0.296 22.48 2 X6 - Individual 0.105 7.97 5 X7 - Legal policy 0.153 11.62 4 Total 1.317 100.00 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 Variable code Description Types Unit Expected A Dependent variable 1 G_DAT Land price Quantitative Million VND /m2 B Biến độc lập 1 KC_TT Distance to the center Quantitative m - 2 KCTI_1 Distance to the utility (market, supermarkets, schools, hospitals, ...) dummy 1 = Distance to utility ranging from 0 - 1000m 0 = Distance to remaining utility + 3 KCTI_2 Distance to the utility (market, supermarkets, schools, hospitals, ...) dummy 1 = Distance to utility ranging from >1000 - 2000m 0 = Distance to remaining utility + 4 D_TICH Area Quantitative m2 + 5 H_THE Shape Qualitative 1 = square 0 = not square + 6 CR_MT Width Quantitative m + 7 CR_DUONG Width street Quantitative m + 8 CL_DUONG Quality street Qualitative 1 = Good 0 = Nomal + 9 TT_LL Communications Qualitative 1 = Good 0 = Nomal + 10 DIEN_NUOC Water and electricity system Qualitative 1 = Good 0 = Nomal + 11 MTST_TOT Good environment dummy 1 = Good environment 0 = Remaining environment + 12 MTST_BT Normal environment dummy 1 = Normal environment 0 = Remaining environment + 13 AN_TOT Good security dummy 1 = Good security 0 = Remaining security + 14 AN_BT Nomal security dummy 1 = Nomal security 0 = Remaining security + 15 MTKD_TOT Good business environment dummy 1 = Good business environment 0 = Remaining business environment + 16 MTKD_KHA Nomal business environment dummy 1 = Nomal business environment 0 = Remaining business environment + 17 P_LY Legal of land dummy 1 = Full legal papers 0 = Not enough legal papers + 18 Q_HOACH Pland dummy 1 = Not frozen plans 0 = frozen plans + Source: Reseach results 16 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 Unstandardized regression Standardized regression t Sig. Collinearity statistics B coefficient Std.error Beta Tolerance VIF 1 (Constant) 1917.864 1550.739 1.237 .217 KCTT -.725 .085 -.248 -8.518 .000 .491 2.038 KCTI_1 2201.828 669.507 .126 3.289 .001 .285 3.514 KCTI_2 763.867 537.032 .044 1.422 .156 .428 2.338 CR_DUONG 241.873 37.649 .169 6.424 .000 .598 1.672 CL_DUONG 2401.187 590.931 .139 4.063 .000 .356 2.808 TT_LL -165.813 1196.882 -.004 -.139 .890 .403 2.482 DIEN_NUOC 389.288 588.962 .015 .661 .509 .768 1.303 D_TICH -11.219 7.647 -.072 -1.467 .144 .170 5.873 H_THE 2117.450 509.722 .104 4.154 .000 .667 1.499 CR_MT 241.896 247.026 .050 .979 .328 .159 6.270 MTST_TOT 7966.060 762.546 .357 10.447 .000 .355 2.813 MTST_BT 2276.749 625.489 .121 3.640 .000 .377 2.651 AN_TOT 388.813 1180.560 .023 .329 .742 .088 11.419 AN_BT -984.817 1021.522 -.056 -.964 .336 .121 8.286 MTKD_TOT 15076.707 1046.562 .327 14.406 .000 .803 1.246 MTKD_KHA 3968.087 400.862 .226 9.899 .000 .794 1.260 P_LY -1702.722 403.110 -.097 -4.224 .000 .785 1.274 Q_HOACH 1344.354 453.689 .066 2.963 .003 .832 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. 17 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 Model Unstandardized regression Standardized regression t Sig. Collinearity statistics B coefficient Std.error Beta Tolerance VIF 1 (Constant) 306.452 1086.522 .282 .778 KCTT -.767 .072 -.262 -10.617 .000 .747 1.339 KCTI_1 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) + 18 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 auto- correlation 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) 19 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 Addresses Land price Difference (times) Regression model Compare method 1 Located on CMT8 street from Loang Bridge to railway into 3 roof storage 12,315.62 11,500 816 2 Located on Hoang Van Thu street From Dong Quang circle to Ha Thai railway 28,584.37 30,500 1,916 3 Located on Thong Nhat Street from Bac Nam intersection to Ha Thai railway 15,960.03 16,500 540 4 Located on Luong Ngoc Quyen street from Thai Nguyen bus station to Dong Quang circle (meet Hoang Van Thu street) 31,552.19 33,000 1,448 5 Located on CMT8 street from Xuong Rong crossroads to Gia Sang intersection (meet Bac Nam street) 20,422.94 19,500 923 6 Located on Hoang Ngan street 24,281.18 23,000 1,281 7 Located on Hoang Van Thu street from center circle to Nguyen Hue crossroads and Chu Van An street 40,870.05 43,500 2,630 8 Located on CMT8 street from railway into 3 roof storage to Kep railway 9,961.40 9,500 461 9 Located on 3/2 street from Phu Xa street to Secondary School Tich Luong 11,923.65 11,000 924 10 Nằm trên Đường Dương Tự Minh Từ băng tải than Núi Hồng đến cầu Tân Long 14,119.23 15,500 1,381 11 Located on Quang Trung Street: Ha Thai railway to Z159 intersection 19,353.47 18,500 853 12 Located on Hoang Van Thu street: From Dong Quang circle to Ha Thai railway 31,168.69 32,500 1,331 13 Located on Duong Tu Minh street from Mo Bach Bridge to side entrance Cao Ngan thermal power Company 12,270.32 11,500 770 14 Located on 3/2 street from Thong Nhat street (Tuberculosis and Lung Diseases Hospital) to College of Financial Economics crossroads 9,605.24 9,000 605 15 Located on Thong Nhat street: Ha Thai railway to the end of Viet - Thai garment factory 14,414.46 15,000 586 16 Located on Duong Tu Minh street from Nui Hong coal conveyor belt to Tan Long bridge 11,552.95 10,800 753 17 Located on Z115 street from Quang Trung street to the end of student dormitory 10,510.15 11,200 690 18 Located on Quang Trung street: from Dan overpass to Dan intersection go to Nui Coc + 100m (Dan Market) 17,512.67 16,500 1,013 19 Located on 3/2 street from Phu Xa street to Secondary School Tich Luong 7,672.64 7,500 173 20 Located on CMT8 street from Street Thai Nguyen Power Company - Thai Nguyen city branch to Phan Dinh Phung street 22,543.48 25,000 2,457 Source: Calculated results and investigation 20 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. 21 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%. 22 (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.

Các file đính kèm theo tài liệu này:

  • pdfreseach_on_factors_affecting_prices_of_urban_residential_lan.pdf
Luận văn liên quan