The first data set was from Real Estate Business Intelligence (RBI), formerly the custom solutions branch of the Mid-Atlantic Multiple Listing Service (MLS)/Metropolitan Regional Information Systems (MRIS). RBI provided a custom dataset for all 366,542 recorded homes sales in the state of Maryland from January 1, 2010 to March 1, 2016 and their corresponding home characteristics. The home characteristics were chosen based on the generally perceived impact on property value, completeness of information, and feasibility of analysis. For example, characteristics like “Type of Body of Water” which allows a broad range of responses such as “Bay, Canal, Creek, Lagoon, Lake, etc…” would be difficult to analyze due to the inconsistent response …show more content…
Therefore, the ENERGY STAR New Homes data was used to determine if a home in the MLS data is an ENERGY STAR certified home (ES Home). ENERGY STAR New Homes Population Data The second data set was obtained from the Maryland ENERGY STAR New Homes Program’s internal records. As a part of the program’s rebate process, participants are required to register each ENERGY STAR home in the program database. The home-level data from this database was aggregated into an ENERGY STAR Report (ES Report) with the addresses of all home submitted for rebate payment since 2010 . The presence of a financial incentive for constructing ENERGY STAR homes across almost the entire state of Maryland ensures that the number of homes in the ES Report represents the majority of all ENERGY STAR New Homes built in the state of Maryland since 2010 . The ES Report contains 17,860 registered homes throughout the five Maryland utility (BGE, Delmarva, Pepco, Potomac Edison, and
Throughout the process of showing clients houses, the agent discusses not many things about the property itself. Because the agent must be aware of the neighborhood the property is in, they often use their knowledge of the landscape to further convince clients as to why they should make the investment. Some main points discussed are, distance from the nearest shopping, size of the rooms, and various features of the house. Such things as, the fireplace, pools, the size of the garage and even the gardens are discussed when overviewing the
The significance of the housing market and it's importance to this economy cannot be overstated. There is a wealth of quality information about real-time
1. I have experienced high rates first hand. It’s never fun paying $700 for one month of energy when your home claims to be energy efficient.
In 2007, Canada’s industries saved 2.1 billion U.S. dollars of energy costs (2007). All these numbers show Canada’s efforts in general public utilities.
Protecting our environment and promoting energy efficiency is a priority of Realtors® in Massachusetts. Our Association supports policies and programs aimed at encouraging homeowners to make energy efficiency improvements to their home. We
An extensive description of these programs includes HUD that deals with the development of affordable housing in urban area for low-income individuals. Lack of housing options have driven fissure in education, health and economic opportunities, in fact, the Mississippi Delta has the state’s average home value standing at 50 percent lower than the national average, making the state the second lowest in the country. The goal of the Department of Housing and Urban Development was to focus on insuring mortgages for single-family and multifamily dwellings and extending loans for home improvements and for the purchase of mobile homes; channeling funds from investors into the mortgage industry through the Government National Mortgage Association; and making loans for the construction or rehabilitation of housing projects for older and handicapped persons.
The social housing program will be a means tested program. Families with an annual household income of $30,000 or less will be eligible for affordable housing. This requirement is set for the possibility of reducing racial inequality since Hispanics and African-Americans are disproportionately ranked the poorest in the United States (Halfmann 2017). I also aim to narrow the gap of these racial disparities by proposing that these new apartments and houses be as eco-friendly as possible. This can be achieved by installing solar panels and energy efficient appliances. These adjustments will lower utility costs tremendously for the household while simultaneously reducing the transmission of greenhouse gases
Each year the cost of designing, building, and maintaining renewable energy infrastructure and technology decreases. This trend is most prominently visible in the solar and wind industries which have both “seen stock prices jump since Congress approved an extension of tax credits for renewables” in late 2015 (Warrick). One cause for the renewable industry’s growth is the influx of investors. In November 2015, Goldman Sachs “quadruple[d] its investments in renewables to $150 billion,” a trend that has only become more prevalent in 2017 (Warrick). Part of the strong appeal of renewable energy is that it pays itself off over time. Instead of paying an electric bill every month, year after year, one can pay to have solar panels installed, that while initially expensive, never require additional payments. Not only are they free after the initial payment, some electric companies pay customers for installing panels and investing in clean energy. Many people complain that renewables produce far less power per dollar than coal, natural gas, and oil. While this may be true, the gap is quickly closing as renewable technology improves and prices drop. The convenience of only needing to pay once for renewable infrastructure far outweighs the greater power output that non-renewables provide for
The energy-efficient appliance credit has been available for companies which produce high-efficiency appliances such as dishwashers, washers and refrigerators for home use. In general, this credit applies only to the number of those appliances made in the US during the tax year, which exceeds the average number produced in the previous two years. There is a maximum total of $75 million for this credit. In addition, each appliance type has energy saving requirements which determine the specific allowed credit for that
By comparing census data from the Toronto CMA and specific census tracts (e.g. 5350037) in Table 1, stores like Lowe’s would be able to create a qualitative profile of the market and explore in deep tentative sites for future stores. In fact, the comparison and analysis of the following variables would allow Lowe’s to understand the type of market in the census tract with respect to Toronto. First, the Toronto CMA presents an average of 2.8 persons per private household, which is relatively higher compared to an average of 2.1 persons for the census tract 5350037. By analysing the market, an average of 2.1 people is more likely to require a service focused on interior living spaces than outdoor home improvements, reducing the demand and therefore
The Department of Housing and Urban Developments (HUD) self-sufficiency programs were developed in an effort to break the cycle of poverty, empowering people to undergo training or education, leading to employment, economic independence and potentially home ownership. In addition, HUD or agencies such as Home Forward liaise with outside agencies providing alternative types of self-sufficiency programs.
Zillow is the dominance force in the real estate market. Though there’s other companies in these filed, such as homegain.com and Market Leader.
Numerous energy and water efficiency measures have been completed or committed saving approximately $870,000/year at 2011/12
In traditional real estate industry, property information had the characteristics of localization, asymmetry, and low transparency. Home information was held by real estate brokerages and websites like MLS that restricted the access to only licensed agents. Before Zillow, consumers lacked the professional knowledge and had few access to comprehensive, timely and accurate data, they could only get the listings through buyer’s agents.
According to the case study written by Jurek, Bras, Guldberg, D’Arcy, Oh, and Biller, energy costs were steadily rising and were predicted to continue this trend going into the future. At the same time, utility companies were beginning to implement Smart Grid technologies to increase the efficiency of energy distribution. One resulting program to emerge from