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Cấu trúc

  • Introduction 3

  • Methodolody 4

  • Econometrics Model

    • I. Model 4

    • II. Variables meaning

      • 1. Specific explanations of variables 4

      • 2. Data descriptions 5

    • III. Results

      • 1. Running Model 7

      • 2. Testing Model 7

      • a. Testing Normality 7

      • b. Testing Multicollinearity 8

      • c. Testing Heteroskedasticity 9

      • d. Testing Autocorrelation 11

      • e. Testing Specification Bias 11

    • IV. Conclusions

      • 1. Final Regression Model 12

      • 2. Explanation 12

    • V. Sugesstions 13

  • Appendix 14

Nội dung

FOREIGN TRADE UNIVERSITY ECONOMETRICS ASSIGNMENT What affects people’s choices of purchasing apartment? Page | Table of Contents Introduction Methodolody Econometrics Model I Model II Variables meaning Specific explanations of variables Data descriptions III Results Running Model Testing Model a Testing Normality b Testing Multicollinearity .8 c Testing Heteroskedasticity d Testing Autocorrelation 11 e Testing Specification Bias 11 IV Conclusions Final Regression Model 12 Explanation 12 V Sugesstions .13 Appendix .14 INTRODUCTION Housing nowadays seems to be a never-ending problem of society due to the rapid growth of population while lands are limited It leads to an obvious result that the Page | prices of real estate, especially in big cities like Ho Chi Minh City or Hanoi, go up and down unstably The fluctuation of real estate price confuses customers, who are largely newly married couples seeking for their own nests Since the scarcity of usable areas are still questioning land planners, a lot of sensitive investors start investing in apartments, which seems to be the best solution to housing problems at the moment Apartment brings a lot of advantages to both contractors and customers: modest area required, cheaper cost, more people contracting at the same time, better security…… To figure out what affects the price of an apartment, we have done a research on which factors the price is dependent to bring a clearer view and support to everyone who is planning to buy an apartment The question given is: “Which elements affecting Hanoi’s apartment price?” A METHODOLOGY So far we have collected date from some reliable internet sources like www.nhadatvideo.com, www.nhadat24h.net as well as consulted some assignments of senior students to clarify what we should implement and develop and continue researching We have found that due to the result of model testing, our seniors have removed “direction” variable- which Gretl has listed as insignificant Though in reality, most Hanoi people when deciding to buy a house or an apartment usually care whether its direction is suitable to the owner’s lunar age Page | We collected about 120 reliable observations and then chose the most sufficient once again Our group ended up with 86 observations We built multiple regression model with some assumed variables which we suppose may have direct effect on Hanoi apartment’s price per square, constructing process, floor or square… Our group has tested assumptions of the model that are normality, multicollinearity, heteroscedascity, autocorrelation and specification bias B ECONOMICTRICS MODEL I MODEL Prps = ß1 + ß2 *area + ß3*pro + ß4*flr + ß5*sqr + ß6*dir + ui II VARIABLES MEANING Specific explanation of variables - Prps: price per square (million VND/ m2) - Area: whether that apartment is close to city center or convenient or not ( if - yes = 1, if no =1) Pro : constructing process – whether the building is completed or not ( if - yes = 1, if no = 0) Flr : floor – where the apartment is located Sqr : square (in m2) Dir : direction ( if the direction is south, south east or south west => =1; if the direction is north, north east , north west, west =>0)1 Expectation in signs - ß1 : it depends - ß2 : positive ( apartments near city center tend to be more expensive than - those in suburb ) ß3 : positive ( people prefer building that has been finished so that they can - directly judge if the apartment they are going to buy is beautiful or not) ß4 : it depends ( some people like low floor so that it would be more convenient for them to go around, some like higher floor in order to avoid - noise and city pollution) ß5 : negative ( the larger the apartment is, the less expensive per square) ß6 : positive ( if the apartment faces good direction, its price will be raised higher) Data description This direction is only based on the weather, not referring to owner’s lunar age Page | a Price per square Summary statistics, using the observations 1950/01/02 - 1951/08/20 for the variable 'prps' (86 valid observations) Summary Statistics, using the observations 1950/01/02 - 1951/08/20 for the variable prps (86 valid observations) Mean Median Minimum Maximum 30,5070 28,2500 11,5000 64,7000 Std Dev C.V Skewness Ex kurtosis 11,1527 0,365578 0,805264 0,129277 b Area Summary Statistics, using the observations 1950/01/02 - 1951/08/20 for the variable area (86 valid observations) Mean Median Minimum Maximum 0,569767 1,00000 0,000000 1,00000 Std Dev C.V Skewness Ex kurtosis 0,498012 0,874063 -0,281827 -1,92057 c d Process Completed: 61/86 Uncompleted: 25/86 Floor Summary Statistics, using the observations 1950/01/02 - 1951/08/20 for the variable floor (86 valid observations) Mean Median Minimum Maximum 9,15116 6,00000 1,00000 33,0000 Std Dev C.V Skewness Ex kurtosis 7,24450 0,791648 0,994216 0,228333 e Square Summary Statistics, using the observations 1950/01/02 - 1951/08/20 for the variable sqr (86 valid observations) Mean Median Minimum Maximum 76,2855 67,0000 36,0000 156,000 Std Dev C.V Skewness Ex kurtosis 29,4782 0,386420 0,738389 -0,379040 f Direction - Good direction: 48/86 - Bad direction: 38/86 Page | Page | III RESULTS: Running Model: Using Gretl, we have the result as above As it shown from the result, we have some initial conclusions: - R- squared is 0.600373 meaning that approximately 60% of the variables can be explained by the model There are five independent variables which can explain the dependent variable All of these five independent variables are statistically significant The initial Regression Model can be defined as: Prps = 31.2517 + 7.67236*area + 5.04203*Pro – 0.285302*Flr – 0.107574*Sqr + 3.80662*Dir + ui Testing Model: a Testing normality: From the model, we test normality by using command Tests residuals in Gretl The result is: Normality of Page | The p-value from the result is 0.0718 > 0.05 distributed The residuals are normally Page | b Testing Multicollinearity: There are two ways to test Multicollinearity by using Gretl First of which is using the VIF ( variance inflating factor) : From the result, we can see that VIF < 10 Model is free from Multicollinearity Or we can use the Correlation Matrix: The correlation between the variables is smaller than 0.8 not exist in the model Multicollinearity does Page | c Testing Heteroskedasticity: Using White test in Gretl, we can see if the Model is suffered from Heteroskedasticity or not The result is: As can be inferred from the result, the p-value is 0.203444 > 0.05 not suffer from heteroskedasticity The Model does Page | 10 d Testing autocorrelation: The p- value in this result is 0.951 > 0.05 model There is no autocorrelation in this e Testing Specification bias: Using Ramsey’s RESET test, we will have the result as below: Page | 11 The p-value is 0.143 which is greater than 0.05 Model is adequately specificated IV CONCLUSION: Final Regression Model: Prps = 31.2517 + 7.67236*area + 5.04203*Pro – 0.285302*Flr – 0.107574*Sqr + 3.80662*Dir Explanation: - R- squared is 0.600373 meaning that approximately 60% of the variables can be explained by the model Remarks on variables: Variable name Conjecture of Trend of impact True Trend of impact Explanation ß1 It depends Positive if other factors are not taken into consideration, the dependent variable reaches the estimated value of 31.2517 Area Positive Positive One m2 of an apartment in city center will be 7.67236 million VND more expensive than that in the suburb Page | 12 Process (Pro) Positive Positive Floor (Flr) It depends Negative Square (Sqr) Negative Negative Direction (Dir) Positive Positive People have a tendency to prefer completed apartment to unfinished ones A m2 of a finished one will be 5.04203 million VND more expensive than that of unfinished one Lower floor seems to beat higher floor in terms of safety in people’s thinking For one extra floor will cost you 0.285302 million VND less One extra m2 will safe you 0.107574 million VND In reality, for Asian people, direction will always sit on top of other problems when it comes to purchasing estate And a m2 of an apartment facing good direction will take 3.80662 millionVND more out of your wallet in comparison with that which faces bad direction V SUGGESTIONS:  To buy a good apartment, customer should have a close enough check on main elements : contractor's reputation, products' quality and contract in order for you to make a right purchase  Firstly, contractor's reputation plays a very important role in your decision making It is better if you have a basic understanding about his/her ability or financial statement to avoid being tricked or waiting continuously without knowing when you can get your apartment  Secondly, product's quality is also very essential Since real estate is a kind of special products, it involves with many external factors: legal base, certificate, neighboring areas, surrounding environment The more you have knowledge Page | 13 of your about-to-buy apartment, the more advantages you have when negotiating about pricing  Last but not least, contract matters are always one of the most concerns to customers You should carefully check all the terms before signing Process delayed is the most popular risk when you buy an apartment which has not been finished, so in this situation, fine is the best way to urge the contractor to complete the contract on time Also, you should check the bias between the apartment's are in reality with that in contract to avoid future complaints APPENDIX Customers and the taste of apartments, together with the price Prps area Pro Flr Sqr Dir 30 65 45 1 47.5 28.3 1 11 53 27 0 132 22 0 84 21 0 98 24.5 1 119 23.4 1 76 22 84 28.2 1 47 25 146 26 1 62 34.5 1 63.49 30 1 13 110 19 11 132 17.5 0 22 109 20 25 95 27 56 30 18 54 Page | 14 29 14 69 20 0 11 156 17 20 111 20 0 12 95 18 33 106 32 17 121 25 22 67 15 17 122 30.7 0 14 64 26 1 16 62 30 1 21 89.5 23 19 78 23.5 23 75 29 1 25 54 27.8 22 111 34 1 16 37 37.3 1 17 65 15.5 0 120 16.3 0 15 115 27.5 0 53 17 0 111 21.5 0 23 87 27 13 56 18 106 23 15 78 29.4 1 41 48.3 1 64 42.5 1 36 23.6 75 33.2 1 45 27 56 41.5 1 56.76 48.2 1 52 38 48.56 Page | 15 43.5 40 39 1 56.76 51 1 11 62.5 22 84 16.5 0 114 64.7 1 41 33.8 1 43 55.9 1 67.72 49.2 1 37.5 30.8 1 67 28.2 59 52.8 1 15 49 45.4 1 75 56.2 1 81 15 0 122 48.3 1 39 27.6 55 31.4 1 12 37.6 32.6 1 71.17 25 67 25.7 1 11 64 31.5 1 45 29.2 1 42 11.5 0 18 142 19.7 0 96 40.8 1 60 31 123 47 1 57 31.6 1 58 22 84 47.5 1 60 41.4 1 68.89 40.6 1 75.6 Page | 16 ... Since the scarcity of usable areas are still questioning land planners, a lot of sensitive investors start investing in apartments, which seems to be the best solution to housing problems at the... as consulted some assignments of senior students to clarify what we should implement and develop and continue researching We have found that due to the result of model testing, our seniors have... pricing  Last but not least, contract matters are always one of the most concerns to customers You should carefully check all the terms before signing Process delayed is the most popular risk when

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