House Market Study in Boston
Urban House Market in Boston
The target of Boston municipality is to accommodate the increasing population in Boston despite the forces of the market. Recently the initiative to change the housing situation in the region has been established, and it targets to be accomplished in 2030. Housing a Changing City: Boston 2030 is a comprehensive plan to address the future housing requirements effectively in the city that will increase accommodation of residents and reflect differences demographically in profound ways from the present situation. In the achievement of this analysis, econometrics is vital in enhancing effective strategies and policies that will guide the municipality of Boston in dealing with the spontaneous changes in age and structures of house distribution.
The inadequate houses in Boston have directly influenced the affordability of houses negatively due to high prices in the region. Moreover, the available houses in the region are not effectively distributed in terms of demographic. In this case, the population in the region does not meet the demands of the types of the available and the dominating houses in the region. This pertains to prices and the rooms of the apartment and thus the strategies being stipulated need to consider the population age in the region effectively. The distribution of houses through a strategic plan will consider the demand in the market that revolves around young millennial, working families, aging population and the low-income households. Moreover, there exist the challenge of matching the housing supply to the changing house demand in terms of the structures and the plans of the houses in order to enhance affordability. The undersupplies of the mismatch of the houses in the region need to be focussed comprehensively in order to facilitate effective accommodation and availability of the houses depending on the economic status and utility of an individual in the population.
In strategizing on the effective policies to be adopted in dealing with the urban housing market in Boston econometric tools are vital in analysing the situation and assisting in the stipulation of policies and strategies to be enacted. Econometric enhances the collection of empirical content in terms of economic relations. Moreover, it facilitates testing of economic theories and the decision-making pertaining to policies through evaluation. In this case, the situation of Boston house market needs the evaluation in order for effective strategies to be developed in curbing the undersupply, consideration of age of the population in the region and the planning of the town as per the municipalities laws.
The methodological issues pertaining to Boston housing market revolves around the population number of people in a family, structure and age of the building and the value of the houses pertaining to the quality in the region. The econometric tools that were effective in the analysis of the situation of the urban housing market in Boston depended on the variables being considered in the study. The necessity of focusing on timely and appropriate economic and business questions is provided by the adoption of econometrics tools that enhance the reflection of the empirical side of economics. Mean and standard deviation were adopted in the study due to the ability of the tools to effectively reflect the needs in the housing market. Quantifying economic relationship, enhancing evaluation of the policies, forecasting and developing an economic model that accurately explains the need of the study facilitated the usage of the tools. Moreover, the tools rely on available data to enhance the relationship between the variables, the forecast of values and enhancing hypothesis test through a framework that enables analysis of the data collected. The econometric tools were supported by the research that enhanced collections of data in order for the analysis to be derived from tools application reflecting the situation of the market of housing in Boston. The applications adopted in the study analysis were determined by the variables in the study in order to reflect the relationship and provide the answers to the questions of the study.
The adoption of standard deviation, mean and regression analysis in this study enhanced the reflection of descriptive analysis through the basis of qualitative analysis of data. This mainly assists in the calculation of descriptive statistic and inclusion of graph in the analysis of data. Indeed, it embraces describing the fundamental features of data in the study and provides the summaries pertaining to sample and measures in an attempt to present the results in a qualitative description. Moreover, the data is presented in a manageable form for easy understanding and inference making. For instance, the mean enhances attainment of the averages of the samples while the standard deviation reflects the dispersion of the population. In this case, the study of the housing market in Boston can be easily be attained through the adoption of the tools and lead to the accurate results that will enhance the development of the effective policies and plans.
The study relied on a sample of the population and thus the sample statistic calculation through the tools will be effective in estimating accurately. The estimation depends on the tools and meets the properties that substantiate the distribution that produce the data. The best properties of a good estimator revolve around un-biases, efficiency on comparing sampling variance, consistency pertaining to large sample and sufficiency of the estimator in capturing the vital information in the sample. Basically, the house market study in Boston required this kind of estimator and the econometric tools adopted reflected the reliable data.
Pertaining to linear regression it effectively reflects an estimation approach in economic that reflect implementation and easy relative result interpretation. In this consideration, it effectively matches with the house market study in Boston in terms of predicting and difference explanation pertaining to the value of the variable outcome. Additionally, it enhances potential relationship explanation between two or more variable. Typically, it forms a relationship with explanatory variable and outcome, the direction of the strength of relationship, important variables and predicting values or set of values pertaining to outcome variables of the explanatory variables.
Interpretation and discussion
The regression model offers the explanation pertaining to the behaviour of the dependent variable (y) facilitated by the existence of information contained in the explanatory variable (X). Moreover, there exist the perturbance term (U) depicting all other factors. The explanatory variable explains the results influenced by the behaviour of the dependent variable. The regression analysis aims to estimate a and b using an estimation method. Obtaining the values of a and b enables explanation of the behaviour of the dependent variable with the information on the explanatory variable through finding effective linear approximation with few errors.
In our case study our dependent variable (Y) is the log house and other factors the explanatory variables which is 0.42 as the determinant coefficient. Pertaining to the summary of the statistic carried out on the mean and the average of the samples the results reflects relationship and influence of the dummy variables.
The dummy variable mean are vital in ensuring qualitative relationship through the assignation of numerical values facilitating answering of either both/one the question. For effective performance of regression method in estimation the mean and the standard deviation of the statistics in the study enhanced the definition of the qualitative factor through enhancement of the attributes qualitative explanatory variable. This is achieved due to assigning numerical values to the categories of the explanatory variables. In the study the validation of the statistical significance was analysed through the calculation of the t-test that involves the slope of the estimated coefficient. Basically, the results of the t-test enhance decision making of the estimation which may either reject or accept depending on the hypothesis being investigated. Additionally, the adoption of the t-test in the study was determining which explanatory variable should be included in the specification of the inferences and regression model.
Adoption of the t-test is essential since it utilizes the degree of freedoms in finding the critical value to be used in decision making after the hypothesis process. In the interpretation of the hypothesis, explanatory variables included in the regression model were vital in joint explanation of the dependent variable.
The case study is vital in cases where the holistic in-depth investigation is required. In the case of house market in Boston, it has been influenced by various factors and thus it was effective to adopt the strategy in the study. However, despite this there are prevalent problems revolving around the method of study and it influences the results of the house market study in Boston. Basically, the researchers may fail to follow the designed method in the collection of the data and data analysis leading to inconsistencies in inferences made from the data collected from the study. This arises since the case studies are designed to bring out the viewpoint of the participant into details due to consideration of multiple sources of data.
Case study generally does not capitalize on sampling and stress on studying the whole population but in the real sense sampling is essential in order to complete the task within ultimatum. In this case, the case study of the housing market in Boston utilized the sample in order to understand the entire market of urban houses in Boston. This would pose the problem of the study if the population were to be studied holistically within the ultimatum given. Moreover, the case study is a selective system that focuses only on issues that facilitates the understanding of the issues being investigated posing the problem of ignoring other factors that could influence the study objective in future. Additionally, the case study reflects generalization in developing the theories and models after the study that poses difficulty in explaining and comparing the results of the empirical results.
The applicability of the case study should revolve around the explanation of causal links in the real life, describing the real life context where the intervention has occurred and describing intervention itself. The problem sets in where compromise of the accuracy in data collection will lead to ineffective policies development. In the case of studying the urban house market generalization and relying on questionnaires may have compromised the accuracy of the data posing the problem to the case study.
Limitation of the case study
The study incorporated single case study that disadvantages the results due to validity issues. It should have involved various studies for comparison since the study explicitly acknowledged the interpretative basis for the meanings, understanding and the reasons for the urban house market. The study was objective only if the question of how and where the data was gathered is spared. Moreover, the external reliability of the single study carried out is not effective on issues of validity and generalization since it cannot offer results beyond the obvious. For effective generalization, case study needs explicit research in order to deal with uncertainty degrees that accompany prediction.
Using case study it leads to access to large data for an easy and simple analysis which lead to difficulty in representing it in a simple way. Additionally, time-consuming and expensive when done on large scale and impossibility of generalising in the conventional sense. Indeed, the case study uses specific cases in studying the intended objective and thus cross-check of information is not applicable if not in the cases of study.
The future work on the study of the urban house market in Boston needs to accommodate various case studies for accuracy and effective generalization. Moreover narrowing the case of study is vital in order to achieve the proponents of the goal of the study. In this case, overcoming dichotomies that exist between generalizing, particularizing, quantitative and qualitative research should be guided by methodological choices rather than narrow and preconceived dogmatic approaches. Adherence to this will facilitate a study that reflects the real issues that exist in the house market in Boston and the effective strategies to be upheld in defining the policies to deal with the undersupply of the houses in the market.