It’s a classic case of over-promising and under-delivering.

First, it was the job numbers. Now comes the phantom Congressional districts.

Since much of the direct stimulus aid goes to state capitals, any attempt to analyze stimulus spending by Congressional district alone would skew the figures. In the chart below, about half of the stimulus awards in Oklahoma — $1.3 billion — is going to the 5th Congressional District, which includes Oklahoma City.

Source: Recovery.gov

After our story came out today, one reader e-mailed and said recipients could have entered their state House or Senate districts by mistake instead of the Congressional districts. For me, more troubling than the so-called “fake” Congressional districts is the fact that a good chunk of the data don’t include any Congressional district at all (the “Null” field above).

Still, in the wake of all the negative press about the Congressional districts, the officials behind Recovery.gov said they have updated the data on the site that erroneously placed stimulus awards in nonexistent districts.

If a recipient reported an incorrect or invalid congressional district, the code “ZZ” appears in the “Congressional District” field as a placeholder. The recipient will change  the report with the correct congressional district during the next reporting period, beginning January 1, 2010.

Also, the federal watchdogs in charge of stimulus spending were grilled on Capitol Hill this morning. In a related report, the Government Accountability Office had some interesting things to say about how stimulus transparency has fared so far. What I found interesting is its investigators started doing error analysis on the same day the data was released to the general public.

GAO performed an initial set of basic analyses on the final recipient report data that first became available at www.recovery.gov on October 30, 2009; reviewed documents; interviewed relevant state and federal officials; and conducted fieldwork in selected states, focusing on a sample of highway and education projects.

While much of the blame for erroneous or missing data is being placed at the recipients who filled out the Web forms on FederalReporting.gov, many are asking if there shouldn’t be some type of validation for the data before it’s released to the public.

The guidance released back in the summer by the Office of Management and Budget lays out who is responsible for data quality in stimulus reporting.

Data quality is an important responsibility of key stakeholders identified in the Recovery Act. Prime recipients, as owners of the data submitted, have the principal responsibility for the quality of the information submitted. Sub-recipients delegated to report on behalf of prime recipients share in this responsibility. Agencies funding Recovery Act projects and activities provide a layer of oversight that augments recipient data quality. Oversight authorities including the OMB, the Recovery Board, and Federal agency Inspectors General also have roles to play in data quality. The general public and non-governmental entities interested in “good government” can help with data quality, as well, by highlighting problems for correction.

To be fair, more than 100,000 reports on stimulus spending have been filed so far. Some data entry errors or miscategorizations were bound to happen when you have that many people filling in Web forms. Here’s what the GAO said it found:

Our review also identified a number of cases in which other anomalies suggest a need for review: discrepancies between award amounts and the amounts reported as received, implausible amounts, or misidentification of awarding agencies. While these occurred in a relatively small number of cases, they indicate the need for further data quality efforts.

Officials hope that future stimulus reports will contain fewer errors as recipients become more comfortable filling out the forms and the requirements are refined. In the meantime, Recovery.gov could make an easy fix by allowing users of the site to flag data that plainly looks wrong. It could function much like the “star ratings” systems on other sites, where users could “grade” their view of the data accuracy in a report.

For more on Recovery.gov data quality, check out the Sunlight Foundation and ProPublica. The White House also published a lengthy retort to critics earlier this week on its blog.

–Paul

UPDATE, 6:10 p.m., 11/19/09: From the prepared remarks of the Earl Devaney, chairman of the Recovery Accountability and Transparency Board:

These mistakes do not surprise me, however, and in a serendipitious way, they are not unequivocally bad. In reality, this data should serve in the long run as evidence of what transparency can achieve.

In the past, this data would have been scrubbed from top to bottom before its release, and the agencies would never have released the information until it was perfect. You — and the American public — are now seeing what agencies have seen, internally, in the past. And what we are all seeing, at least following this first reporting period, is not particularly pretty.

This raw-form, unsanitized data may cause embarrassment for some agencies and recipients, but my expectation is that any embarrassment suffered will encourage self-correcting behavior and lead to more accurate reporting in the future.

Do you count people who went without coverage for a week or a month as being uninsured? What about the ranks of the long-term uninsured? How many of them might qualify for government programs or subsidies but just haven’t signed up?

It’s not an easy task, which is why today’s story on the numbers of uninsured might shed some light on the issue. The Census Bureau’s American Community Survey, a wide-ranging sample of 3 million households each year, asked a health insurance coverage question for the first time last year. For a look at how the question was asked, check out page 8 of the survey form.

Our analysis of the Census’ ACS estimates showed that about 22 percent of Oklahomans under 65 went without health insurance coverage when they were surveyed last year. That put Oklahoma at No. 5 in the nation for the percentage of residents younger than 65 without health insurance.

Of course, it didn’t help matters that the Census just two weeks ago put out another survey that had information on the uninsured from its long-running Current Population Survey. That survey showed an estimated 15.9 percent of Oklahomans of all ages were without health insurance in the CPS’ 2-year average from 2007 to 2008. (For more discussion of that survey data, see the Oklahoma Policy Institute posting here, and the thoughts from our editorial page here. The journal Health Affairs also has a more detailed discussion of the CPS health insurance estimates here.)

David Blatt, policy director for the Oklahoma Policy Institute, said that no matter which Census survey policymakers use, “I think the true numbers lie somewhere between those estimates. Whatever the number, we have a heck of a lot of Oklahomans without health insurance coverage.”

Researchers are hopeful that the bigger survey sample of the American Community Survey will provide more accurate figures in the future. Here’s how the University of Minnesota’s State Health Access Data Assistance Center, or SHADAC, puts it:

The ACS is a great development for health services researchers, but as with all surveys, it will have its problems. In summary, the greatest advantage is that the ACS will be a regular source of health insurance coverage for local areas. The timely releases will fill a significant information void. The biggest limitation is format of the health insurance item is and the ability of respondents to recognize what type of health insurance coverage they have. Some error is always expected in survey research, and we have yet to see how it will compare to other surveys.

In the meantime, here’s a look at some of the latest uninsured estimates from the Census’ American Community Survey for the Oklahoma counties and Congressional districts covered under the latest 2008 survey data:

Finally, NPR has a nice set of interactive maps using the same data:

–Paul

Apparently, it takes the average American almost four years to earn $100,000. But for NBA superstar LeBron James, all it takes is 21 minutes of playing time in an NBA game. Tiger Woods? Just 11 holes on the links. The New York Yankees’ Alex Rodriguez earns $100,000 for every six pitches he sees at the plate. More from the story:

Ben Roethlisberger of the Pittsburgh Steelers may have him beat. If you include his signing bonus, Mr. Roethlisberger brought in 100 grand for every 3.6 snaps he took in 2008 (many of which were hand-offs). But at least he helped his team win a Super Bowl.

–Paul

Yesterday, the U.S. Department of Agriculture released its annual report on the estimated costs of raising a child to adulthood. The 2008 estimate for a middle-income family clocks in at $221,190. (Read the AP story here.)

Before you wonder why the government is in the child-care expenditure business, here’s why the figures are important:

Issued by USDA each year since 1960, the report is a valuable resource to courts and state governments in determining child support guidelines and foster care payments. For the year 2008, annual child-rearing expenses for a middle-income, two-parent family ranges from $11,610 to $13,480, depending on the age of the child.

For the typical family in Oklahoma, the costs are slightly lower than the total estimates, most likely reflecting our lower costs of living. To raise a child to age 17, the USDA estimates that families in our region will spend between $149,610 to $346,320, depending on family income.

Here’s what the USDA estimates a typical family will spend their money on during the first 17 years:

The numbers also differ by income level. This chart shows that the highest-income families spend more than twice as much as the lowest-income families on child-rearing expenses:

In a somewhat understated aside, the report notes that it excludes expenses after age 17, with the largest being college or university education:

The expenditures also exclude costs made on children after age 17. One of the largest of these expenses is the cost of a college education. The College Board (2009) estimated that in 2008-2009, annual average (enrollment-weighted) tuition and fees were $6,585 at 4-year public colleges (in-State tuition) and $25,143 at 4-year private (nonprofit) colleges; annual room and board was $7,748 at 4-year public colleges and $8,989 at 4-year private colleges. For 2-year colleges in 2008-2009, annual average tuition and fees were $2,402 at public colleges.

Of course, the naked economics of quantifying a child’s life is alternately alarming and distasteful. So I’ll leave you with a few links to some recent psychological studies of how much children enrich their parents’ lives.

This report from a pair of British psychologists looks at the pleasures and rewards of time spent on daily activities:

In terms of pleasure, the results confirmed earlier findings, suggesting that we spend an awful lot of time doing things we don’t find pleasurable, including “work” and “shopping”. Out of 18 key activities, “time with children” and “sex” both came in around mid-table, far below “outdoor activities” and “watching TV”. However, consideration of the ratings for “reward” (as opposed to pleasure) told a rather different story, with “work” now the top scorer, and “time with children” not far behind.

Meanwhile, this report attempts to explain why children bring happiness even though everyone knows being a parent is hard work:

It is, on the other hand, much more likely that we as parents will end up spending a large chunk of our time attending to the very core process of child care such as ‘Am I going to be able to pick up David from his school in time?’ or ‘How do I stop Sarah from crying?’ Most of these negative experiences are a lot less salient than the positive experiences we have with our kids, which is probably why we tend not to think about them when prompted with a question of whether or not children bring us happiness. Nevertheless, it is these small but more frequent negative experiences, rather than the less frequent but meaningful experiences, that take up most of our attention in a day. It should therefore come to no surprise to us that these negative experiences that come with parenthood will show up much more often in our subjective experiences, including happiness and life satisfaction, than activities that are, although rewarding, relatively rare.

–Paul

Not so fast, said the Agriculture Department, as it swatted down Drudge’s reports with a rare rebuttal.

Now, all this back-and-forth might seem a bit excessive for a few pounds of sliced ham, but it illustrates one of the perils of transparency without context. Our government spends billions each year to collect, maintain and analyze all kinds of data. But it’s collected by humans, who make mistakes.

Take the ham fiasco. Everything appears above board in the original description on Recovery.gov. But because of the “Description of Work/Service Performed” field, it looks like we paid a bunch of money for some pork. That’s not necessarily an error, but it’s definitely not clear to most readers. (I probably would have drawn the same conclusion, although I would check it out first before writing a story.)

The people who deal with government data on a regular basis know all too well the problems associated with collecting and disseminating data. In the field of computer-assisted reporting, we call it “dirty data,” and we’re on guard for it all the time. (A chunk of my time as Database Editor is spent cleaning up data we get from various local, state and federal sources.)

Here’s how the folks at the Institute for Analytic Journalism put it in 2006:

An uncountable number of public agency databases have been created in the past 30 years. More and more, public and private decision-makers draw on this collected, digital data to make decisions about everything from disciplining doctors to zoning decisions to law enforcement to deciding who gets to vote. The often-unquestioned assumption is that the data, as found, analyzed and presented by a government or quasi-government agency, is valid. Increasingly, anecdotal evidence indicates that data is riddled with serious errors. Often, if initial investigations indicate the data is too suspect — and the cost to clean the data by hand or automatically too high — then good and important analysis and investigations are put aside.

The Government Accountability Office recently put out its own report on the subject of government data. The report is mainly a guide for government auditors, but they recognized the problems of all these disparate sources of data, and the public’s appetite to put it all online.

While this guide focuses only on the reliability of data in terms of completeness and accuracy, other data quality considerations are just as important. In particular, consider validity. Validity (as used here) refers to whether the data actually represent what you think is being measured. For example, if we are interested in analyzing job performance and a field in the database is labeled “annual evaluation score,” we need to know whether that field seems like a reasonable way to gain information on a person’s job performance or whether it represents another kind of evaluation score.

In journalism, we try to follow the age-old advice of, “If your Mother says she loves you, check it out.” Maybe Drudge should do the same thing?

–Paul

The U.S. Debt Clock, a real-time counter of debt, taxes and other economic indicators.

Now, you might want to take this with a grain of salt, because they don’t reveal their sources, but it’s a fun thing to look at.

The U.S. Treasury releases its own debt figures, “down to the penny,” here.

If you want a good visualization of federal government spending (with sources), then slide on over here to the Wall Stats site. Their “Death & Taxes 2009” poster is simply amazing.

–Paul

Overall, reported crime was down 2.5 percent from 2007. But in Oklahoma City and Tulsa, the incidents of violent crime rose.

Much of the conventional wisdom out there holds that when the economy sours, crime rises. But how does that explain the increase in Oklahoma City and Tulsa, both of which have been fairly insulated from the worsening economy in other parts of the country? (For what it’s worth, business magazine Forbes last year declared Oklahoma City as one of the nation’s most “recession-proof” cities.)

I came across a recent series put out by the Federal Reserve Bank in Minneapolis. In the March issue of their FedGazette,  bank researchers and economists looked into the relationship between the economy and crime:

The matter is complicated, at least somewhat, by findings from economic theory and empirical research. Though some research supports the conventional view of rising crime during economic downturns, a closer look at theory finds a more complex story, and empirical studies over the years haven’t found as solid a relationship as one might think between economic downturns and criminal activity. Many other factors are at play, from demographic changes and shifting cultural norms to legislative initiatives and technological innovation. Thus, forecasting crime trends—like predicting the weather or the economy—is an uncertain venture.

Researchers have different theories on the links between crime and the economy:

… Similarly, economist Philip Cook at Duke University recently examined the course of crime rates in urban areas of the United States in recent decades and concluded that “the statistical evidence presented here indicates that [the 1990s crime rate] decline, like the crime surge that preceded it, has been largely uncorrelated with changes in socioeconomic conditions.”

Others, like University of Missouri-St. Louis sociologist Richard Rosenfeld, future president of the American Society of Criminology, continue to hold that macroeconomic conditions do indeed have a strong influence on crime rates. “Crime rates are likely to increase as the economy sours,” Rosenfeld wrote in a Los Angeles Times opinion piece in March 2008, which warned Angelenos “to brace themselves for more crime to come.”

But other scholars, including political scientist James Q. Wilson, former chair of the White House Task Force on Crime, are less certain. Almost a year after Rosenfeld predicted a rise in L.A. crime, Wilson wrote an editorial for the Los Angeles Times, noting that during 2008, crime had fallen in the city “at a time when the economy was reeling and unemployment was rising.”

Whatever the case, it helps to put the most recent FBI stats in context. The FBI itself cautions about drawing comparisons among cities:

Figures used in this Report are submitted voluntarily by law enforcement agencies throughout the country. Individuals using these tabulations are cautioned against drawing conclusions by making direct comparisons between cities. Comparisons lead to simplistic and/or incomplete analyses that often create misleading perceptions adversely affecting communities and their residents. Valid assessments are possible only with careful study and analysis of the range of unique conditions affecting each local law enforcement jurisdiction. It is important to remember that crime is a social problem and, therefore, a concern of the entire community. The efforts of law enforcement are limited to factors within its control. The data user is, therefore, cautioned against comparing statistical data of individual agencies.

Here’s the FBI preliminary stats for Oklahoma City, Tulsa and Norman. The full report, along with the stats of other Oklahoma cities, will be out later this year.

And if you’re still curious, another source of crime information is the National Crime Victimization Survey by the federal Bureau of Justice Statistics. It surveys people (rather than police departments), and its numbers are usually higher than the FBI’s Uniform Crime Reports. That’s because residents sometimes don’t report crimes to their local police departments.

–Paul

And then the president’s budget comes out today, with its talk of trillions.

How do you begin to put those kind of numbers into context? We’ll get to that in a minute. But first, a few more numbers to boggle your mind:

$5.7 million: University of Oklahoma football coach Bob Stoops’ total pay in 2008.

$7.1 billion: Gov. Brad Henry’s proposed budget for fiscal year 2010.

$11.6 billion: Chesapeake Energy Corp.’s revenue in 2008.

$378 billion: Wal-Mart Stores Inc. revenue in 2008.

$14.2 trillion: The gross domestic product (GDP) of the United States in 2008.

The reporters at Politico have a good roundup of the problems of understanding the federal budget and large numbers in general.

Here’s a recent clip from The Daily Show of Sen. Mitch McConnell, R-Kentucky, trying to explain $1 trillion.

Other senators got into the act earlier this month during the same debate about the federal stimulus package before Congress.

Generally, experts said it helps to put such large numbers in terms people can grasp, such as their own salaries or time. I’m intrigued by the MegaPenny Project, which has been around for a few years.

This is one trillion pennies (the tiny dot below the big block is supposed to be a person). That’s equal to about $10 billion.

Meanwhile, the guys at WallStats also have some useful charts on visualizing $1 billion if you’re a “average person”:

Since we’re talking about the federal budget, WallStats also has a nifty chart on their site that shows where federal money went in the last budget.

Finally, this interview with the authors of the recent book, The Numbers Game, sheds more light on the tricky business of understanding large numbers:

Imagine those numbers instead as seconds: A million seconds is 11.5 days; a billion seconds is nearly 32 years.

–Paul

You can see more of their effort at ReadtheStimulus.org. They include links to the bill itself, committee reports, amendments and other stimulus-related documents.

The Congressional Budget Office also released its analysis of the stimulus plan here. (PDF link)

A few of the highlights: On highway and transit spending, “concerns exist about how quickly state and local governments can adjust their contracting procedures to accommodate the significant increase in the amount of funding.” The bill also includes about $39.5 billion in 2009 and again in 2010 for the State Fiscal Stabilization Fund. The CBO estimates 61 percent of those funds for the states would go to education, with the remainder going to general government.

Meanwhile, Mark Zandi, an economist at Moody’s Economy.com, provided his own analysis of the stimulus plan in testimony to the House Budget Committee today. (PDF link)

Zandi noted that the $825 billion plan ($550 billion in spending with $275 billion in tax cuts) represents about 5.5 percent of the nation’s gross domestic product. That puts it below the massive public works program to combat the Great Depression, but higher than the stimulus plans unveiled during the recessions of the early 1980s:

(The $825 billion) is large enough to provide a substantive near-term boost to the economy, but not so large as to result in measurably higher interest rates.

Of particular interest to us in Oklahoma, Zandi also said, “The benefits of a fiscal stimulus are less pronounced in the nation’s agricultural and energy-producing regions.”

For more analysis of the ins and outs of tax cuts and spending, go to the Tax Policy Center.

–Paul

Well, how about checking out this super-massive widget machine from phone company Sprint. Just open your browser to its fullest extent and bask in the data–everything to the number of bicycles and cars being built to top YouTube videos and headlines from Fox Sports.

And my favorite–a mini version of the classic video game Pong.

–Paul