Over the past decade, both investors and the general public have paid increasingly close attention to the benefits of environmentally conscious buildings. We want to examine commercial real-estate market data to determine if tenants are willing to pay a premium for rental space in green buildings.
An Austin real-estate developer is interested in the possible economic impact of “going green” in her latest project: a new 15-story mixed-use building on East Cesar Chavez, just across I-35 from downtown. Will investing in a green building be worth it, from an economic perspective? The baseline construction costs are $100 million, with a 5% expected premium for green certification.
The developer has had someone on her staff offer a preliminary reccomendation:
I began by cleaning the data a little bit. In particular, I noticed that a handful of the buildings in the data set had very low occupancy rates (less than 10% of available space occupied). I decided to remove these buildings from consideration, on the theory that these buildings might have something weird going on with them, and could potentially distort the analysis. Once I scrubbed these low-occupancy buildings from the data set, I looked at the green buildings and non-green buildings separately. The median market rent in the non-green buildings was $25 per square foot per year, while the median market rent in the green buildings was $27.60 per square foot per year: about $2.60 more per square foot. (I used the median rather than the mean, because there were still some outliers in the data, and the median is a lot more robust to outliers.) Because our building would be 250,000 square feet, this would translate into an additional $250000 x 2.6 = $650000 of extra revenue per year if we build the green building.
Our expected baseline construction costs are $100 million, with a 5% expected premium for green certification. Thus we should expect to spend an extra $5 million on the green building. Based on the extra revenue we would make, we would recuperate these costs in $5000000/650000 = 7.7 years. Even if our occupancy rate were only 90%, we would still recuperate the costs in a little over 8 years. Thus from year 9 onwards, we would be making an extra $650,000 per year in profit. Since the building will be earning rents for 30 years or more, it seems like a good financial move to build the green building.
The file greenbuildings.csv contains data on 7,894 commercial rental properties from across the United States constructed by real-estate economists. Of these, 685 properties have been awarded either LEED or EnergyStar certification as a green building (find out more about this certification at www.usgbc.org).
Each of these 685 buildings was matched to a cluster of nearby commercial buildings. Each small cluster contains one green-certified building, and all non-rated buildings within a quarter-mile radius of the certified building. On average, each of the 685 clusters contains roughly 12 buildings.
For each building, we have information on their:
- size: the total square footage of available rental space in the building.
- empl.gr: the year-on-year growth rate in employment in the building’s geographic region.
- rent: the rent charged to tenants in the building, in dollars per square foot per calendar year.
- leasing.rate: a measure of occupancy; the fraction of the building’s available space currently under lease.
- stories: the height of the building in stories.
- age: the age of the building in years.
- renovated: whether the building has undergone substantial renovations during its lifetime.
- class: an indicator of building quality; A is highest, B is reasonable, and C is lowest quality.
- green.rating: an indicator for whether the building is either LEED- or EnergyStar-certified.
- LEED, Energystar: indicators for the two specific kinds of green certifications.
- net: an indicator as to whether the rent is quoted on a “net contract” basis. Tenants with net-rental contracts pay their own utility costs, which are otherwise included in the quoted rental price.
- amenities: an indicator of whether at least one of the following amenities is available on-site: bank, convenience store, dry cleaner, restaurant, retail shops, fitness center.
- cd.total.07: number of cooling degree days in the building’s region in 2007. A degree day is a measure of demand for energy; higher values mean greater demand. Cooling degree days are measured relative to a baseline outdoor temperature, below which a building needs no cooling.
- hd.total07: number of heating degree days in the building’s region in 2007. Heating degree days are also measured relative to a baseline outdoor temperature, above which a building needs no heating.
- total.dd.07: the total number of degree days (either heating or cooling) in the building’s region in 2007.
- Precipitation: annual precipitation in inches in the building’s geographic region.
- Gas.Costs: a measure of how much natural gas costs in the building’s geographic region.
- Electricity.Costs: a measure of how much electricity costs in the building’s geographic region.
- cluster.rent: a measure of average rent per square-foot per calendar year in the building’s local market.
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The Austin-based real estate developer is seeking to understand the financial returns to green certification for her new building. Construction of the building is priced at $100 million, with an expected $5 million premium for green certification. An analyst on the developer’s staff estimated that green certification for the building will result in an additional $650,000 of yearly revenue and that it will take 7.7 years to recuperate the premium, considering the building has an occupancy rate of 100%. The analyst calculated his estimates by looking at all buildings with leasing rates greater than 10%. The goal of our analysis is to revisit the analyst’s estimates, using the same data set containing statistics on 7,894 buildings, and determine if the presented returns to green certification are accurate.
The developer’s building is 15 stories tall, 250,000 square feet, and has an age of 0. To evaluate if the analyst should have accounted for our building’s physical features, the below plots reveal the general relationships between Rent and each of these features. The gray shading around the line represents our margin of error for this estimate and the vertical red line represents our building.
The building is located on East Cesar Chavez in Austin, Texas. Using outside sources, we were able to identify the local employment growth rate (2.5% as of March 31, 2020: source), average annual rainfall (34 inches: source), and the number of degree days (2,248 heating days, 2,862 cooling days, and 5,110 total degree days: source). The data set measured the values for degree days in 2007 however, as the 2007 estimates were unavailable, we used the 2018 values as they are likely a close estimate. We were unable to find information on the other location-based variables present in the data set.
The below plots investigate whether these geographical characteristics have any affect on a building’s rent. The red dashed line represents the data set’s mean rent. While the direct relationship between the following location-based features and rent may not be clear, they help us understand where the rental market is inflated.
The left plot indicates how rent is only stable for regions with positive employment growth rates. Otherwise, rent greatly varies for different levels of employment growth rates. The right plot reveals how rent spikes for regions with greater precipitation. This graph may be capturing the high rental rates for cities that receive high rainfall, such as San Francisco and the Pacific Northwest region.
The relationship between rent and regional variables is complicated. Ultimately, it is best to account for as many physical and regional features as possible when estimating returns to green certification.
We obtained a subset of the buildings data set that contained buildings within +/- 1 standard deviations of our building’s size, stories, age, regional employment growth rate, regional annual rainfall, and regional degree days. We dropped buildings that had less than 10% occupancy to avoid outliers. This data set contained information on 314 buildings, 73 of which were green and 241 of which were non-green.
Looking only at similar buildings, the median rent for a green building is $22 while the median rent for a non-green building is $20.25.
Green buildings also have a higher median leasing rate of 91.43% compared with the non-green leasing rate of 88.49%.
The building’s quality is measured in the data set by standards of high (class a), average (class b), or low (class c). The below plots reveal how the quality of the building has a significant association with higher rent per sq foot for buildings similar to ours. One would expect green certified buildings to be of higher quality however, these variables have a fairly low correlation of 0.248.
The analyst’s conclusion that a green certification yields a greater return was accurate however, his analysis was quite faulty. He greatly overestimated the degree of the return in yearly rent per square foot as he did not account for the building’s characteristics. The analyst focused on the number of years it would take to recuperate the initial premium. As it is almost impossible that every individual square foot of a building could be rented out, these estimates are irrelevant.
Our analysis concluded that green certification is worth the extra premium. Green buildings offer an additional $1.75 in yearly rent per square foot, on average. Based upon higher average occupancy rates, it is more likely that green buildings will have a higher total level of income than non-green buildings. However, it is essential that the developer ensure her building is of high quality as this variable leads to a greater difference in rent for buildings similar to ours.