Most of Dickenson County‘s residents live along the many river valleys that flow down into the Russell Fork which cuts through Virginia’s Cumberland Mountains to create the largest gorge east of the Mississippi. Yet despite its many scenic attractions and the bonus of a low cost of living, Dickenson has been steadily shedding its population, declining by over a third since 1950.Rural counties in Virginia, like Dickenson, have been slowly losing their young adult population for decades as many have moved elsewhere to seek more education and work opportunities. But often rural counties have been able to continue growing by attracting older migrants who are nearing retirement or have already established their careers elsewhere. However, these two migration trends are now creating a new problem for most of Virginia’s counties; the gradual hollowing out of their young adult populations from decades of out-migration combined with a growing retiree age population means that in an increasing number of counties, there are no longer enough families with children to replace the rising number of deaths. Read Full Article →
In my last post, I began a series focused on the gender wage gap, and discussed why demonstrating its existence is not always a simple proposition. Most importantly, I argued, it is not enough to simply look at the difference between men’s and women’s median wages. Not only do these estimates tell us less than we might like (recall those overlapping margins of error), but their analysis also often ends up oversimplifying the conversation by providing only a comparison between all working men to all working women—not, ultimately, the comparison we really want to make.This is because human capital—the abilities people bring with them into the workplace—and wage structure—the amount we compensate various jobs relative to others—affect how much we can reasonably expect people to be paid, as do some outside factors, such as when and where a worker is hired. In other words, there are plenty of reasons other than gender that could explain why two individuals working full time earn different amounts of money. In order to investigate the extent to which a worker’s gender influences his or her wages, we need to make sure we’re comparing workers who are similar in as many other ways as possible. Read Full Article →
Farming has a semi-mythological status unlike any other industry or occupation. In few places is this more true than Virginia, which was founded on farming and particularly tobacco farming. For much of Virginia’s history, its population was shaped by agriculture. Most early Virginians came to the state as either indentured servants or slaves to work in its tobacco and wheat fields. As recently as 1940, farming was still the largest employer in Virginia, with 180,000 farms taking up two-thirds of the state’s land area. Read Full Article →
A couple of weeks back, I attended the 2015 ACS Data Users Conference and heard a lot of concerned researchers discussing the impact of losing the 3-year estimates from the American Community Survey. In the past, the Census Bureau provided separate 1-year, 3-year, and 5-year estimates – but funding constraints have resulted in the discontinuation of the 3-year statistical product which covered communities with a population size of 20,000 or more. Each set of estimates have their relative merits, as explained in detail on their website. The 3 and 5-year estimates are period estimates constructed as a rolling average, these are different from the 1-year values which capture the data collected during the annual cycle. Choice of the data-set and the timeline depends on the goal of the analysis, and it usually involves some tradeoff between currency and precision. Read Full Article →
April 14 of this year marked what is known as Equal Pay Day, the representing “how far into the year women must work to earn what men earned in the previous year.” The choice of date is based on research demonstrating that women earn approximately 77 cents for every dollar earned by their male counterparts. Whether it is 77, 84, or 93 cents on the dollar, there is reason to believe that women earn less than men in this country—but it takes a lot of careful work to meaningfully demonstrate it.Recently, I have been asked for data on men’s versus women’s wages in Virginia, overall, as well as within smaller regions, such as particular localities or zip codes. Each time, the asker—a journalist—has explained that his goal is to find quantitative data addressing the topic of gender wage equity in the workplace. I’m thrilled that journalists are not only interested in asking these questions, but also looking for high-quality data to use as they write about this complex topic. But while comparing wages might appear to be the most obvious way to get at the answer, careful consideration of the data reveals why this task is not as straightforward as it may appear. Read Full Article →
Everyday, medical professionals diagnose and treat cancer patients, clinical researchers look for ways to prevent and cure cancer, and policy makers allocate resources for advancement of cancer programs. With the Commonwealth’s population growing and aging, we, as demographers, attempted to see how many people may be diagnosed with cancer over the next few decades. Earlier this week, the Demographics Research Group released its report on “Projecting Cancer Incidence in Virginia” along with a detailed data set, background methodology, and a set of interactive maps, all of which are available here.
During most of the 20th century, the neighborhoods where people lived and worked in Richmond — even the boundaries of the city — were shaped by race. For decades after WWII, the city’s leaders fought a well-publicized battle to maintain this system and prevent the city’s population from becoming majority black. In recent years, Richmond has experienced its most significant demographic transformation since the post-war era, but this time the change has occurred much more quietly. Why?
For many of us, the morning commute is often not the best part of the day; however some may actually enjoy this time, managing to find peace and productivity during the trip into their workplace. Countless articles discuss the impact of commuting on the average person’s quality of life, with the costs – time lost in transit, stress from the daily commute, financial expenses – usually outweighing the benefits. People sometimes do not realize how much their commute is costing them, how their overall health and wellness is affected, or how it may be correlated with unhappiness and dissatisfaction.
“529,000 Americans ages 25 to 29 moved from cities out to the suburbs in 2014; only 426,000 moved in the other direction. Among younger millennials, those in their early 20s, the trend was even starker: 721,000 moved out of the city, compared with 554,000 who moved in.”
This is wrong, but it’s not Casselman’s fault. He’s reading the table correctly. The problem is with the way the CPS migration data is tabulated and presented. Other data journalists have made similar points about migration, relying on the same bad data. To demographers who work with population data every day, these articles make no sense. That’s just not how it works. There is always a steady churn of people into and out of central cities, with cities gaining young adults (and suburbs and rural areas losing them), followed by cities losing families as they have children (and suburbs gaining them). It’s the variations in this pattern which are newsworthy, not the pattern itself.The truth is harder to nail down, but based on population distributions from the same survey, it looks like over the past 5 years about 3 million more Americans age 20-29 moved from suburbs to principal cities than from cities to suburbs, with last year being the largest net gain for cities yet.That’s an error several orders of magnitude in the wrong direction and should be a little startling. Proving it is fairly easy. Explaining it is more difficult. Read Full Article →
When it comes to the social safety net, myths and half-truths, rather than reality, often shape our conception of who depends on the net and the value of these programs. It is easy to lose sight of what these programs do for families, especially if one lives in a household that has never qualified for a program. Mitt Romney, a smart and well-informed person, infamously stated that 47 percent of Americans “believe the government has the responsibility to care for them, who believe that they are entitled to health care, to food, to housing, to you-name-it.” But the reality isn’t so simple. Advocates of the social safety net countered Romney’s argument by highlighting that many of those people were seniors who had paid into the system, or individuals who are currently working, but needed help to make ends meet.When our understanding of the social safety net relies on myths and incomplete truths, it distorts our public conversation about the place of these programs in our society, and our obligation—or lack of obligation—to those households using the programs.In an attempt to provide a better picture of the social safety net I graphed median annual benefits for 12 social safety programs against a household’s resources or wages. Read Full Article →
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