Virginia’s Regions: Northern Virginia is Different

This week, the Demographics Research Group updated its profile of Virginia’s regions. The eight regions of the Commonwealth were identified by the Demographics Research Group based on proximity, geography, demographic characteristics and shared socioeconomic conditions. While there are many shared characteristics across Virginia’s regions, our profile shows that a number of differences exist as well.


Northern Virginia stands out the most among Virginia’s regions, but this is not a new trend as Charles Grymes notes on Virginia Places:

“Northern Virginia has been “different” ever since Lord Fairfax established a land office issuing Northern Neck deeds independently from the colonial government in Williamsburg” Continue reading

Fostering a Better Future

Presentation1May 2014 is National Foster Care Month and provides an excellent opportunity to recognize the important role of foster care in the lives of so many children and youth across the country as well as in the Commonwealth. In 2013, Governor Bob McDonnell launched his “Virginia Adopts: Campaign for 1,000” initiative to match 1,000 children in foster care to 1,000 adoptive families, the target was successfully exceeded by finding permanent homes for 1,008 children. This year, Governor Terry McAuliffe also recognized May as Foster Care Month for the Commonwealth of Virginia and emphasized that “every child and youth in foster care deserves the security and opportunity for growth that a family can provide”.

Continue reading

Virginia’s immigrants: Where do they come from and where are they now?

The foreign-born, or immigrants, comprise more than 10% of the Commonwealth’s population.  Most of them are between 25 and 44 years of age. This young cohort is highly active both in terms of production (working) and reproduction (having children). The adult foreign-born, for example, make up 15% of the Commonwealth’s workforce; and a fifth of all native-born children below the age of 18 have at least one foreign-born parent. More details are available here.

Contributions of the foreign-born population to multicultural diversity can be explored in several ways; where they come from and where they stay plays a key role in this story. A hundred years ago, most foreign-born people were from European nations; today almost 80% of immigrants to Virginia originate form Asia or Latin America. The top five countries of birth for the contemporary foreign-born population are El Salvador, India, Mexico, Philippines and Korea.  What is also of significance is where these immigrants choose to live within Virginia.

Slide2The distribution of foreign-born people among Virginia’s 11 metropolitan areas (MSAs) can be seen in the map above. Close to 70% of immigrants can be found in Northern Virginia alone, with Hampton Roads and Richmond hosting about 10% each. Among the smaller MSAs, Charlottesville leads the pack with nearly 20,000 foreign-born individuals, many of whom are students, faculty or staff at the University of Virginia.  The non-metro, mostly rural areas are home to less than 3 percent of the foreign-born.

The map below shows the percentage of each MSA population that is foreign-born. Again, Northern Virginia leads the way, with nearly a quarter of its population being immigrants. Harrisonburg and Charlottesville MSAs have a high proportion (nearly 9%) of foreign-born people, closely followed by Winchester and Richmond (7%), and Virginia Beach and Blacksburg (6%).


A quick glance at School Enrollment Projections

Being primarily an Economist, and the newest member of the group, I still have a lot to learn about the demographic changes affecting Virginia and the US. So attending the Applied Demography Conference 2014 was a very educative experience for me. One of the subjects I found particularly interesting was school level projections, so here are some thoughts on the subject.

School enrollment projections are crucial for staffing, budgeting and classroom allocations as school districts rely on these numbers to anticipate future needs and plan accordingly. It is reasonable to assume that number of students in a particular grade will depend upon the class-size of this cohort when they were in the immediately preceding grade. Consider a batch of students moving from 9th to 10th grade between 2012 and 2013.


If everything remained constant, all 110 9th graders from 2012 should progress to 10th grade in 2013 and so forth. However the numbers are not always the same which could be due to several reasons. As we go from 9th to 10th grade, 5 more students could have joined the cohort in 2013 so the class-size would grow to 115 as some new children may have moved into the school district from elsewhere. Alternatively in 2013 when we follow these 9th graders into 10th grade there may be 5 fewer students, making the class size 105 for the next year. Some of these children could have remained in the previous grade to repeat a year, they may have left to join a different school or may have dropped out of school altogether causing the class-size to shrink. Hence all students from a grade may not automatically advance to the next higher grade and we need a method for estimating future class-sizes. Grade Progression Ratio (GPR) is the standard go-to for forecasting school enrollment. To see how this works, suppose you are a school administrator who needs to know how many students to expect in the 10th grade in 2014.

From the example above we find that GPR9th-10th  = 10th grade Enrollment in 2013/9th grade Enrollment in 2012 = 105/110 = 0.95, which implies that we expect 95% of students in 9th grade to move on to 10th grade. To calculate the current enrollment for grade 10 in 2014, we can apply the progression rate from last year: 10th grade Enrollment in 2014 = 0.95 * 97 = 92.59. Therefore approximately 93 students are projected for the upcoming year. This is a simplified illustration of how we may predict the expected number of students in different grades in the future.  In practice, we use data from multiple years to build ratios in order to minimize randomness and several other elements must be incorporated into the calculations to get greater reliability.

Here are some other updates and advances about enrollment projections:

  • One way to calculate future student enrollment in rapidly expanding areas is to track new residential developments (historical trends, current construction, home sales etc. are indicators of single-family and multi-family presence in the school districts) for creating different area-specific yield factors.
  • For each new house that is constructed, there are several pre-existing homes that exchange hands; so neighborhoods could evolve even though number of housing units remains steady. New families come into ownership of these resold properties changing the population composition which in turn may change the demand for schooling.
  • Migration alters the prevailing age structure and family type of a locality which will determine schooling needs. Number of school age children in a household fluctuates over time and migrating households could contain elderly individuals with adult offspring or they may be young families planning for or already with children. For example, a 3rd grader moves with the whole household while a college student moves alone and movement of empty-nesters will not add new students to an area.
  • Geo-spatial analysis has become an indispensable tool for understanding modern demography. Families move and household composition changes, therefore the geographic distribution is useful for identifying trends in student yield with variation in housing tenure. Plotting child-densities on a map helps to visualize concentration of students in a school district and could improve the accuracy of projections.
  • Public school enrollment rates may be affected by presence of private schools among others; the odds of attending a private school significantly depend upon household income, race and neighborhood of residence. The economic climate also plays a significant role as in times of prosperity more families can afford to send their children to private institutions. Public schools will receive more funding during economic booms as opposed to times of recession when the financial downturn percolates into both household and administrative schooling decisions.

All trend projections and estimates are speculative in nature which means that there is a constant need for dynamically updating the statistics. Here at the Weldon Cooper Center, every year we conduct school enrollment projections under contract with individual school divisions. We apply Grade Progression Rates for general analyses and implicitly take account of net effect from migration, dropout, deaths, retention, and school transfers. For more customized analyses, we include further nuances into the methodological design such as housing development, family structure, differential fertility rates by race and ethnicity etc. to incorporate location specific characteristics. For more details please visit our School Enrollment Projections page.

Crime Statistics in 2012: Where does Virginia stand?

Have you noticed how many television channels currently have programs with story-lines woven around crime or law enforcement? With so many police dramas and crime series floating around the pool of broadcasting networks, I couldn’t help but wonder what the recent crime statistics looked like in the real world. These numbers are quite important because not only do they reflect the current state of security, but they help criminal justice agencies make informed decisions about how to manage and allocate their limited resources towards keeping our communities and its residents safer.

The FBI’s annual report Crime in the United States 2012  provides a snapshot of some facts and trends regarding criminal activity. Their estimates indicate that over the past year number of violent crimes has increased by 0.7% while the number of property crimes declined by 0.9%. Violent crimes (murder/non-negligent manslaughter, forcible rape, robbery and aggravated assault) which involve some form of force or threat of force against a victim had rates ranging from 123 in Maine to 1244 per 100,000 people in Washington D.C. Property crimes (burglary, larceny, motor vehicle theft and arson) on the other hand, are those where there is a loss of money or property and ranged from a rate of 1922 in the state of New York to 4861 per 100,000 for Washington D.C.



A glance at the maps above shows us that Virginia fares quite well compared to other states. But is this true of all regions in the Commonwealth? The recent Crime in Virginia 2012 report released by the Virginia Uniform Crime Reporting Program from the Department of State Police demonstrates an uneven distribution for estimated adult and juvenile arrests across the state. It is evident that there are some pockets that report higher number of arrests but these figures need to be understood in light of the area’s unique circumstances and characteristics. Several factors affect crime like population size, density and composition; socioeconomic conditions like employment and education; degree of urbanization etc. hence any insights we draw must be contingent upon the distinctive conditions affecting each locality. So if you are interested in knowing how your own county or city fared in terms of crime over 2012, take a look at the report here.

To gauge the frequency of all the offenses reported for the entire state, consider the following time-clock: approximately one crime against a person was reported every 5 minutes while a crime against property was committed every 2 minutes and a crime against society was recorded to occur once every 8 minutes. To wrap it up, here is a quick look at what kinds of criminal activity were most prevalent within Virginia over the course of 2012.



[1] The maps reflect the number of crimes per 100,000 people. Rates of Property Crime do not include arson data due to reporting discrepancies between agencies.

[2] Ranking the states on the national maps should be approached with caution as local law enforcement jurisdictions may report their data with varying levels of assessment or accuracy.

[3] At the state level, comparing different cities and counties on the basis of these reported crime statistics could also be misleading as there may be discrepancies in the data with respect to the categories or number of offenses estimated by different reporting agencies.