The Urban Housing Market

The Urban housing Market
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The Context of the case study: Boston, urban housing market, econometrics.
Most Millennials are drifting towards urban housing each custom-made to fit the different segments of the population. Annual reports have indicated an annual surge in the cost of housing and the demand for housing simultaneously. This means that families are fighting for the available housing units and this leads to diversification of the amenities provided by these housing units. Considering the economic importance of Boston, the number of its inhabitants will continue to increase. Therefore, families will continue being squeezed in the housing market because the number of units available is not enough to sustain the current and future capacities.
The urban housing market will, therefore, continue to grow beyond its limits and the prices would vary depending on the packages offered by the housing facility. The price of the housing facility is mainly determined by these set of variables: age of the structure, house value, number of rooms, adherence of a garage unit, the proximity of its location to the central City and also the demand for the housing unit bat a particular area and time.
Econometrics analyses the characteristics of the urban housing market, its dynamics and the growth value in the near future. Various tools are utilized in this analysis including the type and size of the population involved in the study constituting the urban housing market. Tools such as frequency distribution, regression analysis and the statistical inferences would correctly describe the urban housing market in Boston.
Methodological issues in the case study: the use of econometric tools in this specific case
Considering the current urban housing market in Boston, economic tools like the mean, standard deviation and the regression analysis describe the situation adequately. The variables used in this study included the housing value, number of bathrooms, number of bedrooms, garage inclusion, age of the structure, whether the unit is single-family attached, the surrounding neighborhood and the proximity of the structure to the central City. The mean presents the most likely value of the variables constituted like the most likely value of the house, the most likely number of bedrooms/bathrooms and if it is most likely within the central City proximity.
Regression analysis, on the other hand, presents the relationship between the variables involved. In this case, the house value in the Boston market would be the dependent variable while the variables stated earlier would be the in...