What is that extra bathroom worth?

The scenario is all too familiar- searching the web listings you come across the seemingly perfect 2- bedroom row house –it’s in the right location, close to public transit and good schools, not next to the fire station, it’s more than 12 feet wide so the stairs don’t eat up all the space, it has a decent size garden and a finished basement, it’s under $1 million.  Then it all comes crashing down -it only has one bathroom!

Even the prospective single buyer knows that while one bathroom might be perfectly suitable for her/his living arrangements, on resale this is likely to affect value and narrow the field of prospective buyers.

In this post we crunched the numbers to see how much an extra bathroom is worth and the difference with respect to a half-bathroom.

Here’s what we found based on an analysis of market values for over 15,000 2-bedroom single family homes.

Average value of a an additional full and a half bathroom in a 2 bedroom home in DC  


Difference in value compared to a 2 bedroom- 2 bath

2 Highlights:

On average, the extra full bathroom results in a difference in value of about 15 percent, or almost $60,000.

The average figure masks significant differences among neighborhoods.  In Georgetown, the differential between a one bathroom and 2 bathroom property was almost 25 percent.  Some of the differential is due to the fact that a 2 bedroom 2 bath house is simply larger- larger bedrooms, a larger living room- so that not all of the incremental value is due to the extra bathroom. We estimate that about 1/3 of the additional value or about $75,000 is due to the extra bathroom. (See graph below for a comparison of select neighborhoods)

In less expensive neighborhoods, like Trinidad and Brookland, the difference was less pronounced, only about 15 and 11 percent respectively.

Having 1.5 baths narrows the differential in value with respect to a full 2 bathroom considerably. The average difference in value compared to a full 2 bathroom is $23,000, or about 6 percent.

Comparison of values of 2 bedroom homes by number of bathrooms and neighborhood 


The upshot

The large premium that a 2 bedroom 2 bath row house commands over a house with only a single bathroom  makes it worthwhile to ask an architect friend if she/he can squeeze in at least a half bath. Perhaps they can combine the hallway closet with the kitchen pantry. This is certainly the case in neighborhoods like Georgetown where the increase in value from having the extra full or half bathroom would compensate for the cost.

What exactly is the data?

Data on property values were obtained from the Office of Tax and Revenue and refer to values in 2015. As noted above these are average differences.  Values will vary considerably based on others factors such as the condition of the home, square footage, the presence of other amenities like fireplaces, garages, etc.

Bob Zuraski contributed to this post


DC’s startup economy- How much does it pay to work at a startup in DC compared to other companies and other cities?

Start-up companies play a vital role in the economy, fostering innovation and providing job opportunities for those who want to go at it on their own and/or prefer to work in what is typically a less hierarchical environment.  In the digital information era, the glorified image of young entrepreneurs and workers who start hugely successful companies masks some of the risks associated with working at startup companies. Typically these companies do not have the deep pockets to pay salaries comparable to established companies and failure rates among startups tend to be higher than for established companies.  This may be a risk worth undertaking as the payoffs for working at start-up companies that eventually become successful can be significant, particularly in high tech companies that go public. For younger individuals, job security and pay related to seniority and tenure can be less of a factor than for older individuals, making the risk of working at a startup less severe.

In this post we examine how average salaries for startup companies compare to salaries across companies in DC and other cities. We use industry-wide data for all age groups and then show this separately for 25-34 year olds.

Table 1: Average Salaries for Startups vs All Companies, All Age Groups


Source: US Census Bureau, DistrictMeasured.com

  • As shown above, for all age groups, salaries at startups ranged between 56 percent and 76 percent of salaries at all companies among the comparison cities.
  • DC was at the lower end of the range at 61.2 percent exceeding only NYC at 56.2 percent.

Table 2: Average Salaries for Startups vs All Companies, 25-34 year olds



Source: US Census Bureau, DistrictMeasured.com

  • For the 25-34 year old age group the ratio of start-up salaries compared to all salaries was higher than the average for all age groups shown in Table 1. This is likely related to the fact that salaries for younger individuals are typically lower and more compressed to begin with.
  • The ratio of pay varied considerably among cities.
  • In San Francisco and Austin, the pay for young individuals working for startups was comparable to the pay at more established companies.
  • In San Francisco the pay for 25-34 year at startups exceeded pay for all other age groups.
  • DC and New York were at the lower end of the scale again. Pay at startups was, respectively, 72.7 percent and 68.5 percent of the pay at more established companies.

Here is a summary graph of the pay ratios for all ages and the 25-34 year old age group.

Graph 1: Ratio of Salaries at Startups Compared to all Companies, Ages 25-34 and All Ages   3

Source: US Census Bureau, DistrictMeasured.com

Finally we looked to see if there was considerable variation among select industries that could explain some of the differences in pay at startups in DC compared to San Francisco for instance.

Here’s what we found:

Table 3: Startup pay to ratio to all companies among industries in San Francisco and DC, Ages 25-34


Source: US Census Bureau, DistrictMeasured.com

Notably, in San Francisco the pay ratio for Professional Scientific and Technical Services, one of the largest industries for tech startups, far exceeded that in DC, almost 100 percent compared to 78 percent.

With the exception of Health Care and Social Services, pay ratios in the other industries also exceeded or were similar to DC.


The difference in pay ratios for start-up pay likely reflects a more vibrant start up economy in San Francisco and Austin, compared to more traditional career paths in established financial and legal services firms in DC and NYC. The causes for this could include- stronger ties to venture capital funding that provide greater financing to startups , or simply stronger competition for young talent among startups in San Francisco and Austin.

What exactly is the data?     Data on wages is from the U.S. Census Bureau, Local Employment Dynamics Data for 2014. Start-up companies are defined as firms that are less than 4 years old.

Bob Zuraski contributed to this report         

How can the rent be so high in DC when almost two-thirds of all rental units in the District are subject to rent control? A small number of “spoiler “units with high turnover may be the reason.

The District, along with a few other housing major markets in the nation, has rent control laws that were enacted to protect tenants against unreasonable rent increases. The laws governing rent control in these markets generally stipulate that rent increases are bound by the Consumer Price Index or other cost of living measures. These laws also allow for larger increases when units become vacant (we will return to this point later).

If rent increases are generally constrained by the cost of living, how could the median rent in the District over the 2005-2014 period have grown by 65 percent, or nearly 6 percent annually, when the DC consumer price index over the same period grew by only 30 percent, or just under 3 percent per year? In addition, as shown below, growth in median rents in DC has outpaced other markets where rent control laws are also in place.

Median Contract Rent: 2005-2014


Source: U.S Census Bureau, American Community Survey, DISTRICTMEASURED.COM

One possibility is that most units are not subject to rent control and must pay what the market will bear. To analyze this, we looked at data on the number of rental units subject to rent control in the District. Under DC laws most rental units with more than 5 units and built prior to 1975 are subject to rent control.

Here’s what we found in terms of the number of units subject to rent control



Source DC Office of Tax and Revenue, DC ORA, DISTRICTMEASURED.COM

This is what the data looks like by Ward


Source: DC Office of Tax and Revenue, DC ORA, DISTRICTMEASURED.COM


  • Almost two thirds of all rental units are potentially subject to rent control or other restrictions. This is a significant share of the entire rental stock.
  • The highest concentration of rent control units was located in Wards 3 and 4 with over 80 percent of all units potentially subject to rent control.
  • Wards 5, 6 and 7 had the lowest overall share of rent controlled units. In Ward 6, less than a third of all units are subject to rent control.
  • These overall findings are largely consistent with the results of a prior study from the Urban Institute, “A Rent Control Report for the District of Columbia” by Peter A. Tatian, Ashley Williams, June 17, 2011 which can be accessed by clicking here


To put these statistics further into perspective we looked at the share of rent regulated apartments in New York City.

This is what we found for New York City’s Boroughs


 Source: 2014 New York City Housing Vacancy Survey, U.S. Census Bureau

DC ‘s overall share of rent regulated units is comparable to New York City’s, although certain DC Wards have an even higher share of regulated units than in the Bronx or Manhattan.

So what accounts for the large increases in rents given that two thirds of DC rental units are subject to rent control?

Two provisions of the law are likely to account for this:

When a DC tenant vacates a rental unit the amount of rent charged may, at the election of the housing provider, be increased:

(1) By 10% of the current allowable amount of rent charged for the vacant unit; or

(2) To the amount of rent charged for a substantially identical rental unit in the same housing accommodation; provided that the increase shall not exceed 30% of the current rent charged for the vacant unit.

It is easy to see how the combination of these two provisions can result in substantial price increases. This is what could happen to rents in a building where one unit (Unit 1) has a relatively high turnover. We assumed a turnover of once every three years for this unit, which is not unusual given DC’s high mobility. The other units have no or limited turnover. We assumed all comparable units started with a rent of $1,000 in 2004.

Rent simulation given turnover


Source: DC Office of Revenue Analysis, Cells highlighted in orange indicate a vacancy rent increase of 10%, and red denotes up to a 30% percent increase based on a comparable unit

Turnover in one “spoiler” unit can cause rents to increase for all comparable units in the building.

Even the third unit in this hypothetical building, which turns over only once in ten years, has seen its potential rent increase by 58 percent. Only the fourth unit, that has seen no turnover, has a rent that remains below $1500.

As shown above, given allowable vacancy increases and comparability under DC law, even one comparable unit with a high turnover can cause rents to increase substantially for many units. Higher turnover, which may be due to changing demographics (more married couples and fewer singles remaining in the same unit for many years) or a spoiler unit, which may be the substantially identical unit on the same floor but close to the garbage room or near the garage exit, could cause rents to increase significantly even with rent control.

What exactly is the data?

To determine units potentially subject to rent control we looked at the year built and number of units for the following building codes for rental properties (21, 22, 25, 28,216 and 217) from the DC Office of Tax and Revenue Real Property Tax Database. The New York City Housing and Vacancy Survey (NYCHVS), sponsored by the New York City Department of Housing Preservation and Development, is conducted every 3 years to comply with New York state and New York City’s rent regulation laws. The Census Bureau has conducted the survey for the City since 1965. The 2014 NYCHVS is the 16th such survey. No similar study exists for DC.

Bob Zuraski contributed to this post

Depending on Bonuses- Why the news on a $1 billion payout creates dependency for bonus recipients, residential brokers, luxury retailers, policymakers, the taxman….

For many employees in the District this is an important time of the year when decisions regarding their bonuses are made.  Employees typically receive their bonuses in their paychecks during the months of December through February.

Bonus pay (also called variable compensation or incentive pay) is a significant part of overall pay, particularly for certain sectors like finance, legal and management consulting.  Proponents of bonus pay argue that it is an effective management tool to tie pay to performance and one that affords firms greater flexibility during downturns to trim pay rather than payroll. Others argue that incentive pay is the reason for rising income inequality and that it is often determined in a subjective way by a supervisor or a friendly board, rather than tied to concrete measures of performance. There is evidence to support both sides of the debate.

The focus here is on measuring this important economic indicator and why it matters to so many people.

The large sums of money that are often involved are closely watched by high-end retailers and residential brokers as leading indicators for their industries.  Decisions on whether to sell, upgrade or renovate a home, or to purchase a luxury car or other high ticket items are often tied to bonuses.

For tax revenue forecasting purposes, bonuses can be a significant, yet highly volatile, source for income taxes and other taxes (the impact on DC sales taxes depends on whether bonus recipients purchase a new vehicle or decide to spend their bonus on a winter getaway).

Here’s what the data show for bonuses in DC for the lucky 50,000 employees in finance, legal services and consulting.

Bonus and Base Pay, 2006-2014.


Source: U.S. Census Bureau, DISTRICTMEASURED.COM

As shown above, bonus compensation in 2014 averaged about $21,000 for employees in these industries, or nearly 15 percent of their base pay.

Using a 15 percent ratio, and assuming a two-earner bonus household making $500,000, this would imply a bonus check of $75,000.

For the very highest earners, (above $ 1 million) bonus payouts are likely to take on a more complicated structure than just wage compensation and include stock options and other deferred compensation forms which have a favorable carried interest tax treatment.

To get the total bonus payout in 2014 we multiplied the average bonus for all employee, $21,000, by the total number of employees in these sectors, about 50,000, to get $1.1 billion.

We also looked to see how bonuses vary by age groups.

Bonus Payout by Age Group, 2014


Source: U.S. Census Bureau, DISTRICTMEASURED.COM

As expected, bonus pay generally grows with work experience. On average, senior employees (ages 45+) earned about $25,000 compared to $ 18,000 for junior employees (ages 25 to 44).

Finally we looked to see how bonus payments fluctuated from year to year, an issue that is clearly of importance to bonus recipients, but is also a complicating factor for tax revenue forecasters.

Annual Growth in Bonus Pay vs. Base Pay


Source: U.S. Census Bureau, DISTRICTMEASURED.COM


Base pay grew on average by 4 percent over the 2006 to 2014 period, with growth varying from a low of zero in 2012 to a high of 5.8 percent in 2008. In contrast, bonus pay fluctuated considerably ranging from -28.5 percent in 2008 to +20.0 percent in 2014.

Other considerations:

In addition to studies that have linked bonus pay to increasing income inequality, the reliance on incentive pay as a part of overall compensation also helps to explain other changes in the economy.  A fascinating study by Peter Kuhn and Fernando Lozano,  “The Expanding Workweek? Understanding Trends in Long Work Hours Among U.S. Men, 1979-2004” explains how work hours, in certain industries where pay is linked to job performance, have increased.

One possible behavioral implication of overall pay being linked so much to incentive pay is that with so much at stake bonus recipients “cannot afford” to take time off or work less.

Betty Alleyne and Bob Zuraski contributed to this post

What exactly is the data?

Data on bonuses is imputed by computing the difference in pay during bonus quarters ( Q4, Q1) compared to base pay ( Q2,Q3). As noted, wage and employment data is for the following 4-digit NAICS sectors (legal services, securities and commodity brokers and management, scientific, and technical consulting services).

DC’s Residential Property Market –$2 Million may be the new $1 Million for the Luxury Market

Many reports have focused on the rapid pace of price appreciation and sales volumes of luxury homes valued more than $1 million. Year to date, sales of homes with prices exceeding  $1 million account for more than 18 percent of all single family home sales in DC.  With sales of $1 million becoming more and more “commonplace”, it may be time to set the bar higher in terms of what constitutes luxury.  This redefinition would also better align the DC market with other expensive housing markets in the nation where $1 million no longer carries the same cachet and exclusivity that it did ten years ago.

Here’s data that shows the share of overall sales of single family homes valued more than $1 million. These are broken out in three ranges: 1) $1-1.5 Million 2) $1.5-$2 Million and 3) $2 Million and greater

Share of Overall Sales of Single Family Homes Valued more than $1 Million, 2001-2015



  • The share of overall sales of single family homes valued more than $1 million has risen from only 3 percent of all home sales in 2001 to over 18 percent in 2015.
  • Sales of homes valued more than $1 million broke the ten percent barrier of overall sales in 2006.
  • Sales of homes valued more than $2 million now account for more than 4 percent of all sales.
  • Given the upward trend in prices, it may not be too long before 5 percent of all homes sold in the District top $2.0 million.

Shown below are the main neighborhoods where the majority of transactions valued more than $2 million has occurred.

Number of Sales of Homes Valued More than $2 Million by Major Neighborhoods: 2001-2015


  • In most of these neighborhoods, and in particular the bellwether neighborhood of Georgetown, sales of homes valued more than $2 million jumped beginning in 2014.
  • Georgetown accounts for almost one-third of all single family homes sold valued more than $2 million.
  • Altogether, the neighborhoods shown above account for almost 75 percent of all sales valued $2 million and over.

What exactly is the data?

Data on sales is from the DC Recorder of Deeds and the DC Office of Tax and Revenue. Building codes 11-13 were used to identify single family homes.  Only arm’s length transactions were considered.

Betty Alleyne contributed to this post





Turnover in DC’s residential property market-Who sold in 2015 and who were the biggest winners?

The real estate market is characterized by a constant churn of activity that results from residents who for various reasons –job relocations, a desire to upsize or downsize, move to a different part of the City or elsewhere–sell their homes in any given year. This normal churn of activity can be influenced as well by economic and market conditions that can make it more difficult or less advantageous to sell.

In this post we examine sales of single family homes in the District to see how long sellers in the District held on to their property before selling and whether the gains realized by sellers depend on how long they held their property.

Here’s what the data shows for single family home sellers in fiscal year 2015.

Median Gains Realized by Sellers in FY 2015 by Length of Time Property Was Held



  • The highest median appreciation was for those who had been holding on to their properties for over 14 years, these sellers realized median gains of over $324,000.
  • The lowest gains realized were for those who purchased their homes 8 to 9 years ago at the height of the previous housing boom. For these sellers the median gain was only $46,000.
  • Sellers who bought their homes recently, less than 5 years ago, also realized substantial gains exceeding $100,000.
  • The median gain for all sellers was $108,000.
  • There were 185 properties with gains that exceeded $500,000- Thirty-one sellers realized gains exceeding $1,000,000.

Share of Properties Sold in FY 2015 by Length of Time Property Was Heldpic3

  • More than half of the sellers held on to their homes for less than 7 years, with a median hold time of just over 6 years.
  • The data indicates  high turnover among sellers who hold on to their homes for less than 3 years. This is consistent with other data that we have analyzed on mobility in the District.
  • Data from the National Association of Homebuilders indicates an average hold time of 10 years for the nation, another indication of the higher housing mobility in the District.

Peter Johansson and Bob Zuraski contributed to this post

What exactly is the data?

Data was compiled using information from the DC Office of Tax and Revenue and the DC Recorder of Deeds. The data focused on market rate transactions of single family homes, excluding non-arm’s length transactions. Sales of single family homes in FY 2015 totaled  3,674 based on preliminary data.

How many businesses and which types of businesses are owned by women? DC compared to the nation.

The U.S. Census Bureau released preliminary figures today on the characteristics of businesses ownership in the nation based on 2012 data from the Survey of Business Owners. In this post we examine how many businesses are owned by women, comparing DC to the nation and examining how these figures have changed over time. Though women comprise the majority of the nation’s (and the District’s) population, women are still a minority in terms of owning a business.

Here’s what the data show for DC, the nation and the four largest states.

Business Ownership by Gender, DC and the Nation


Key Highlights

  • In the District, almost 45 percent of non-publicly owned businesses are owned by women. This is significantly higher than the nationwide average of 36 percent.
  • If these preliminary estimates hold up, this represents a considerable increase in female ownership since 2007, when 37.5 percent of businesses in the District were owned by women.
  • Even taking into account the fact that the District has the highest female to male population ratio among states, almost 53 percent versus 51 percent in the nation overall, the female ownership ratio in DC still stands out.
  • Interestingly when it comes to joint female/male owned ownership, the District share is considerable lower than the nationwide average and the other states. This may have to do with the relatively low presence of smaller mom and pop shops in denser urban areas like DC.
  • Looking at what types of business women tend to own, among the major sectors, health and education topped the list. For these types of businesses, women-owned businesses actually represented the majority.
  • Ownership of management holding companies, construction and transportation tended to be male dominated.
  • The sectoral composition of DC’s economy, towards service sectors where women are more likely to own businesses, also explains why female ownership is higher in the District compared to the nation.

Business Ownership by Gender and Sector:5Source: U.S. Census Bureau, DISTRICTMEASURED.COM

We will provide further updates on this data including characteristics of minority owner businesses and metro level data.

What exactly is the data?

Data are based on the 2012 Economic Census, and the estimates of business ownership by gender, ethnicity, race, and veteran status are from the 2012 Survey of Business Owners. Detail categories will not sum to the total because the ‘publically held and other firms not classifiable by gender, ethnicity, race, and veteran status’ category is not included in the preliminary tables. For further details on methodology and data issues click here. These data are preliminary and are subject to revisions.