The appointment of new federal chief information officer Steven VanRoekel comes at a challenging time for President Barack Obama. The national economy continues to be weak. Congress plans to cut trillions from the federal budget. And in the time leading up to the 2012 election, American voters remain cynical about the ability of the government to address important policy problems in an effective manner.

In an era of deficit reduction and public cynicism, the tasks facing federal officials are to determine how to do more with less and persuade voters the government can become smarter and more effective. There are going to be fewer dollars for virtually every federal program so it is important to figure how ways to innovate and perform more efficiently.

Former CIO Vivek Kundra sought to do this through encouraging agencies to move software applications to the cloud, consolidating federal data centers, improving transparency, and improving the information technology procurement process. It is important to continue this progress even as agencies are forced to downsize their operations.

As shown in the private sector, government administrators should use technology to cut costs, improve worker productivity, and streamline operations. This is not just a matter of using technology in more innovative ways, but changing the operations and culture of the public sector. Public officials must improve its data mining activities to identify fraud and abuse in Medicare, Medicaid, the Defense Department, and other domestic programs.

New software gives managers better tools to evaluate how money is being spent and whether it is fulfilling intended goals. If it is not, programs need to be modified or eliminated. The most important weapon in Mr. VanRoekel’s arsenal may be the scalpel as he goes through the federal government’s $80 billion IT budget.

Donald Trump has made waves during this year’s election cycle by taking a hard line on illegal immigration. This, however, builds on years of heated debate among policymakers. It is also an enduring hot-button issue in Arizona, which has passed several immigration laws over the years.  In 2010, the passage of SB 1070 brought national attention to this debate.  Deemed the strictest immigration law to date, SB 1070 sought to achieve “attrition [of illegal immigrants] through enforcement” by requiring law enforcement to detain any person whom they believed to be residing in the country illegally. Although SB 1070’s effects on individuals and families have been well documented, little is known about its impact on students and schools. To this end, we sought to estimate the relationship between the passage of SB 1070 and school-level student achievement.

We anticipated that anti-immigration policies would primarily affect children from the families of undocumented immigrants. Such effects could be observed in different ways. For instance, the emotional and psychological distress of these children could result in a decline in average test scores at the school-level. On the other hand, students might have left the country or the state under the threat of being deported in which case school-level test scores would rise (since these students often perform below their peers). To this end, we considered three scenarios: 

1. Immigrant children remain in the state but experience higher levels of stress.  As a result, average school-level test scores will drop while Hispanic enrollment remains the same.
2. Children of undocumented immigrants leave the state, which results in a drop in Hispanic enrollment accompanied by an increase in school-level test scores.
3. Or, the first two scenarios occur simultaneously and we do not observe any change in test scores since the two effects would cancel each other, but note a slight decrease in Hispanic enrollment.

In order to see which of these hypothetical scenarios is supported by the data, we first estimated the relationship between the passage of SB 1070 and average school-level reading test scores. We then attempted to unpack the mechanism through which such an effect might have taken place. To this end, we used publicly available data on school-level achievement and enrollment collected by the Arizona Department of Education (ADE). Given the targeted nature of the policy and the demographics of immigrants in Arizona, the majority of whom are of Hispanic or Mexican descent, we focused on schools that traditionally enroll large proportions of Hispanic students. We identified schools with high (more than 75 percent) shares of Hispanic students as those whose average achievement and student composition are most likely to be affected by immigration reform. We contrasted changes in school-level achievement and enrollment in those schools with schools that enroll less than 25 percent Hispanic students, as these schools are less likely to experience any changes as a result of tightening immigration laws.

Figures 1 and 2 show trends in the average percentage of students passing the state reading test and average Hispanic enrollment at these schools between 2006-2007 and 2011-2012.           

Figure 1. Average Percent of Students Passing AIMS Reading

Figure 2. Average Hispanic Student Enrollment

Clearly, the rate of growth in school-level reading scores was much higher for high Hispanic schools after the passage of SB 1070 in 2010 (Figure 1). At the same time, there was a significant decrease in Hispanic enrollment in these schools (Figure 2). Thus, it appears the second scenario is likely driving the patterns we observe.

The data also suggest that the trends for high Hispanic and low Hispanic schools started diverging before the passage of SB 1070 - after the 2007-2008 school year.  This happens to be the year that Arizona passed an even more restrictive, though less controversial, immigration law – the Legal Arizona Workers Act (LAWA). LAWA required Arizona business owners to verify the legal status of their employees using E-Verify, an online tool managed by the federal government. Although LAWA used a different mechanism, similar to SB 1070 it sought to achieve the attrition of undocumented immigrants from the state. 

We then would anticipate both laws to have similar effects on school-level achievement and Hispanic enrollment. Indeed, we estimated that LAWA likely led to an average increase of roughly 4 percent of students passing the state reading test at high Hispanic schools. This was accompanied by an average loss of 38 Hispanic students per school. Because the passage of SB 1070 was preceded by the passage LAWA as well as a language policy that would have affected treatment schools, disentangling the effects of these two policies is not straightforward. However, based on our analysis, we estimate that SB 1070 is associated with an average increase of between 1.5 percent and 4.5 percent of students passing the state reading test at the school-level accompanied by an average loss of between 14 and 40 Hispanic students. 

Despite the fact that we cannot pin down the exact magnitude of SB 1070’s effect on school-level achievement, our analysis shows that when Arizona passed restrictive immigration laws in 2008 and 2010, it looked as if the state’s lowest performing schools were improving rapidly. This, however, likely had more to do with the changing composition of schools as an indirect though anticipated effect of immigration policies than with policies aimed at improving student achievement. 

Despite this, the Arizona Department of Education took credit for these gains. Similarly, Arizona was recently recognized as one of the nation’s leaders in growth on the National Assessment of Educational Progress (NAEP) over the last ten years. Although wrongly attributing these gains may seem harmless at first glance, it is important to remember that Arizona is viewed by many as a model for controversial education reforms like school choice and high-stakes accountability. It is easy to imagine how policymakers might look at increasing test scores in Arizona and wrongly attribute them to these kinds of reforms. That’s not to say that these policies don’t have merit. However, if other states adopt education policy reforms under the assumption that they worked in Arizona, then they might find that these policies fail to deliver.

Although a few political analysts have been focusing on the white working class for years, it is only in response to the rise of Donald Trump that this large group of Americans has begun to receive the attention it deserves. Now, thanks to a comprehensive survey that the Public Religion Research Institute (PRRI) undertook in collaboration with the Brookings Institution, we can speak with some precision about the distinctive attitudes and preferences of these voters.

There are different ways of defining the white working class. Along with several other survey researchers, PRRI defines this group as non-Hispanic whites with less than a college degree, with the additional qualification of being paid by the hour or by the job rather than receiving a salary. No definition is perfect, but this one works pretty well. Most working-class whites have incomes below $50,000; most whites with BAs or more have incomes above $50,000. Most working-class whites rate their financial circumstances as only fair or poor; most college educated whites rate their financial circumstances as good or excellent. Fifty-four percent of working-class whites think of themselves as working class or lower class, compared to only 18 percent of better-educated whites.

The PRRI/Brookings study finds that in many respects, these two groups of white voters see the world very differently. For example, 54 percent of college-educated whites think that America’s culture and way of life have improved since the 1950s; 62 percent of white working-class Americans think that it has changed for the worse. Sixty-eight percent of working-class whites, but only 47 percent of college-educated whites, believe that the American way of life needs to be protected against foreign influences. Sixty-six percent of working-class whites, but only 43 percent of college-educated whites, say that discrimination against whites has become as big a problem as discrimination against blacks and other minorities. In a similar vein, 62 percent of working-class whites believe that discrimination against Christians has become as big a problem as discrimination against other groups, a proposition only 38 percent of college educated whites endorse.

This brings us to the issue of immigration. By a margin of 52 to 35 percent, college-educated whites affirm that today’s immigrants strengthen our country through their talent and hard work. Conversely, 61 percent of white working-class voters say that immigrants weaken us by taking jobs, housing, and health care. Seventy-one percent of working-class whites think that immigrants mostly hurt the economy by driving down wages, a belief endorsed by only 44 percent of college-educated whites. Fifty-nine percent of working-class whites believe that we should make a serious effort to deport all illegal immigrants back to their home countries; only 33 percent of college-educated whites agree. Fifty-five percent of working-class whites think we should build a wall along our border with Mexico, while 61 percent of whites with BAs or more think we should not. Majorities of working-class whites believe that we should make the entry of Syrian refugees into the United States illegal and temporarily ban the entrance of non-American Muslims into our country; about two-thirds of college-educated whites oppose each of these proposals.

Opinions on trade follow a similar pattern. By a narrow margin of 48 to 46 percent, college-educated whites endorse the view that trade agreements are mostly helpful to the United States because they open up overseas markets while 62 percent of working-class whites believe that they are harmful because they send jobs overseas and drive down wages.

It is understandable that working-class whites are more worried that they or their families will become victims of violent crime than are whites with more education. After all, they are more likely to live in neighborhoods with higher levels of social disorder and criminal behavior. It is harder to explain why they are also much more likely to believe that their families will fall victim to terrorism. To be sure, homegrown terrorist massacres of recent years have driven home the message that it can happen to anyone, anywhere. We still need to explain why working-class whites have interpreted this message in more personal terms.

The most plausible interpretation is that working-class whites are experiencing a pervasive sense of vulnerability. On every front—economic, cultural, personal security—they feel threatened and beleaguered. They seek protection against all the forces they perceive as hostile to their cherished way of life—foreign people, foreign goods, foreign ideas, aided and abetted by a government they no longer believe cares about them. Perhaps this is why fully 60 percent of them are willing to endorse a proposition that in previous periods would be viewed as extreme: the country has gotten so far off track that we need a leader who is prepared to break so rules if that is what it takes to set things right.

Last month, we experienced yet another breakthrough in the epic battle of man against machine. Google’s AlphaGo won against the reigning Go champion Lee Sedol. This success, however, was different than that of IBM’s Deep Blue against Gary Kasparov in 1987. While Deep Blue still applied “brute force” to calculate all possible options ahead, AlphaGo was learning as the game progressed. And through this computing breakthrough that we can learn how to better leverage the data revolution.

In the game of Go, brute-force strategies don’t help because the total number of possible combinations exceeds the number of atoms in the universe. Some games, including some we played since childhood, were immune to computing “firepower” for a long time. For example, Connect Four wasn’t solved until 1995 with the conclusion being the first player can force a win. And checkers wasn’t until 2007, when Jonathan Schaeffer determined that in a perfect game, both sides could force a draw. For chess, a safe strategy has yet to be developed, meaning that we don’t know yet if white could force a win or, like in checkers, black could manage to hold on to a draw.

But most real-life situations are more complicated than chess, precisely because the universe of options is unlimited and solving them requires learning. If computers are to help, beyond their use as glorified calculators, they need to be able to learn. This is the starting point of the artificial intelligence movement.  In a world where perfection is impossible, you need well-informed intuition in order to advance. The first breakthrough in this space occurred when IBM’s Watson beat America’s Jeopardy! champions in 2011. These new intelligent machines operate in probabilities, not in certainty.

That being said, perfection remains important, especially when it comes to matters of life and death such as flying airplanes, constructing houses, or conducting heart surgery, as these areas require as much attention to detail as possible. At the same time, in many realms of life and policymaking we fall into a perfection trap. We often generate obsolete knowledge by attempting to explain things perfectly, when effective problem solving would have been better served by real-time estimates. We strive for exactitude when rough results, more often than not, are good enough.

By contrast, some of today’s breakthroughs are based on approximation. Think of Google Translate and Google’s search engine itself. The results are typically quite bad, but compared to the alternative of not having them at all, or spending hours leafing through an encyclopedia, they are wonderful. Moreover, once these imperfect breakthroughs are available, one can improve them iteratively. Only once the first IBM and Apple PCs were put on the market in the 1980s did the cycle of upgrading start, which still continues today.

In the realm of social and economic data, we have yet to reach this stage of “managed imperfection” and continuous upgrading. We are producing social and economic forecasts with solid 20th century methods. With extreme care we conduct poverty assessments and maps, usually taking at least a year to produce as they involve hundreds of enumerators, lengthy interviews and laborious data entry. Through these methods we are able to perfectly explain past events, but we fail to estimate current trends—even imperfectly.

The paradox of today’s big data era is that most of that data is poor and messy, even though the possibilities for improving it are unlimited. Almost every report from development institutions starts with a disclaimer highlighting “severe data limitations.” This is because only 0.5 percent of all the available data is actually being curated to be made usable. If data is the oil of the 21st century, we need data refineries to convert the raw product into something that can be consumed by the average person.

Thanks to the prevalence of mobile device and rapid advances in satellite technology, it is possible to produce more data faster, better, and cheaper. High-frequency data also makes it possible to make big data personal, which also increases the likelihood that people act on it. Ultimately, the breakthroughs in big data for development will be driven by managerial cultures, as has been the case with other successful ventures. Risk averse cultures pay great attention to perfection. They nurture the fear of mistakes and losing. Modern management accepts failure, encourages trial and error, and reaches progress through interaction and continuous upgrading.

Although a few political analysts have been focusing on the white working class for years, it is only in response to the rise of Donald Trump that this large group of Americans has begun to receive the attention it deserves. Now, thanks to a comprehensive survey that the Public Religion Research Institute (PRRI) undertook in collaboration with the Brookings Institution, we can speak with some precision about the distinctive attitudes and preferences of these voters.

There are different ways of defining the white working class. Along with several other survey researchers, PRRI defines this group as non-Hispanic whites with less than a college degree, with the additional qualification of being paid by the hour or by the job rather than receiving a salary. No definition is perfect, but this one works pretty well. Most working-class whites have incomes below $50,000; most whites with BAs or more have incomes above $50,000. Most working-class whites rate their financial circumstances as only fair or poor; most college educated whites rate their financial circumstances as good or excellent. Fifty-four percent of working-class whites think of themselves as working class or lower class, compared to only 18 percent of better-educated whites.

The PRRI/Brookings study finds that in many respects, these two groups of white voters see the world very differently. For example, 54 percent of college-educated whites think that America’s culture and way of life have improved since the 1950s; 62 percent of white working-class Americans think that it has changed for the worse. Sixty-eight percent of working-class whites, but only 47 percent of college-educated whites, believe that the American way of life needs to be protected against foreign influences. Sixty-six percent of working-class whites, but only 43 percent of college-educated whites, say that discrimination against whites has become as big a problem as discrimination against blacks and other minorities. In a similar vein, 62 percent of working-class whites believe that discrimination against Christians has become as big a problem as discrimination against other groups, a proposition only 38 percent of college educated whites endorse.

This brings us to the issue of immigration. By a margin of 52 to 35 percent, college-educated whites affirm that today’s immigrants strengthen our country through their talent and hard work. Conversely, 61 percent of white working-class voters say that immigrants weaken us by taking jobs, housing, and health care. Seventy-one percent of working-class whites think that immigrants mostly hurt the economy by driving down wages, a belief endorsed by only 44 percent of college-educated whites. Fifty-nine percent of working-class whites believe that we should make a serious effort to deport all illegal immigrants back to their home countries; only 33 percent of college-educated whites agree. Fifty-five percent of working-class whites think we should build a wall along our border with Mexico, while 61 percent of whites with BAs or more think we should not. Majorities of working-class whites believe that we should make the entry of Syrian refugees into the United States illegal and temporarily ban the entrance of non-American Muslims into our country; about two-thirds of college-educated whites oppose each of these proposals.

Opinions on trade follow a similar pattern. By a narrow margin of 48 to 46 percent, college-educated whites endorse the view that trade agreements are mostly helpful to the United States because they open up overseas markets while 62 percent of working-class whites believe that they are harmful because they send jobs overseas and drive down wages.

It is understandable that working-class whites are more worried that they or their families will become victims of violent crime than are whites with more education. After all, they are more likely to live in neighborhoods with higher levels of social disorder and criminal behavior. It is harder to explain why they are also much more likely to believe that their families will fall victim to terrorism. To be sure, homegrown terrorist massacres of recent years have driven home the message that it can happen to anyone, anywhere. We still need to explain why working-class whites have interpreted this message in more personal terms.

The most plausible interpretation is that working-class whites are experiencing a pervasive sense of vulnerability. On every front—economic, cultural, personal security—they feel threatened and beleaguered. They seek protection against all the forces they perceive as hostile to their cherished way of life—foreign people, foreign goods, foreign ideas, aided and abetted by a government they no longer believe cares about them. Perhaps this is why fully 60 percent of them are willing to endorse a proposition that in previous periods would be viewed as extreme: the country has gotten so far off track that we need a leader who is prepared to break so rules if that is what it takes to set things right.

June’s jobs gains, released this morning, show that 287,000 new jobs were added in June, an impressive rebound after only 11,000 new jobs were added in May (revised down from from 38,000 at the time of the release).

This year’s monthly job gains and losses can indicate how the economy is doing once they are corrected to account for the pattern we already expect in a process called seasonal adjustment. The approach for this seasonal adjustment that is presently used by the Bureau of Labor Statistics (BLS) puts very heavy weight on the current and last two years of data in assessing what are the typical patterns for each month.

In my paper “Unseasonal Seasonals?” I argue that a longer window should be used to estimate seasonal effects. I found that using a different seasonal filter, known as the 3x9 filter, produces better results and more accurate forecasts by emphasizing more years of data. The 3x9 filter spreads weight over the most recent six years in estimating seasonal patterns, which makes them more stable over time than in the current BLS seasonal adjustment method.

I calculate the month-over-month change in total nonfarm payrolls, seasonally adjusted by the 3x9 filter, for the most recent month. The corresponding data as published by the BLS are shown for comparison purposes. According to the alternative seasonal adjustment, the economy added 286,000 jobs in June (column Wright SA), almost identical to the official BLS total of 287,000 (column BLS Official).

Data updates released today for prior months also reveal some differences between my figure and the official jobs gains from prior months. The official BLS numbers for May were revised down from 38,000 new jobs to a dismal 11,000. My alternative adjustment shows that the economy actually lost 6,000 jobs in May, down from 17,000 jobs gained at the time of the release. [i] The discrepancies between the two series are explained in my paper.

In addition to seasonal effects, abnormal weather can also affect month-to-month fluctuations in job growth. In my paper “Weather-Adjusting Economic Data” I and my coauthor Michael Boldin implement a statistical methodology for adjusting employment data for the effects of deviations in weather from seasonal norms. This is distinct from seasonal adjustment, which only controls for the normal variation in weather across the year. We use several indicators of weather, including temperature and snowfall.

We calculate that weather in June brought up the total by 25,000 jobs (column Weather Effect), but this should be considered a transient effect. Our weather-adjusted total, therefore, is 262,000 jobs added for June (column Boldin-Wright SWA). This is not surprising, given that weather in June was in line with seasonal norms.

It’s good to see the jobs numbers rebounding this month. The May number was somewhat affected by the Verizon strike. Also, it is important to remember that pure sampling error in any one month’s data is large, and that could explain part of the weak employment report for May. Averaging over the last three months, employment is expanding by about 150,000 jobs per month—a healthy pace, although a bit of a step down from last year.

a. Applies a longer window estimate of seasonal effects (see Wright 2013). The June 2015 to May 2016 values in this column have been corrected to remove a coding error that affected the previously reported values.

b. Includes seasonal and weather adjustments, where seasonal adjustments are estimated using the BLS window specifications (see Boldin & Wright 2015). The incremental weather effect in the last column is the BLS official number less the SWA number.

[i] Note that, due to a small coding error, my alternative seasonal adjustment for May, at the time of the release, should have been 17,000 new jobs, not -4,000, as was reported in my previous post. In addition to the underlying data revisions, and correcting for this error, the revised alternative seasonal adjustment for May is -6,000 jobs added (second row of column Wright SA).

Also in this podcast: Russ Whitehurst discusses the cost of universal education for preschool, and David Wessel comments on the current state of the economy

"To use some of the time honored clichés, 'The enemy may get a vote too.' Or the Bolshevik line, 'You may not have an interest in war, but war may have an interest in you' I paraphrase that to say we may not, at the moment, have an interest in counterinsurgency and stabilization missions, but they may have an interest in us… we can't be like the ostrich putting our head in the sand just because we're tired of these kinds of wars. They might come back, whether we like it or not." says Senior Fellow Michael O'Hanlon about his new book, "The Future of Land Warfare."

After learning about the various scenarios that might necessitate land warfare, we'll hear Russ Whitehurst, senior fellow in Economic Studies and Editor of the Evidence Speaks project, discuss the cost of universal Pre-K. "The question is: what should the nation or states do to increase participation rates to a universal level?" Whitehurst asks in this project. "And what I've found by looking at the evidence is that actually people haven't provided very good evidence on how many children are presently served."

Also, stay tuned to hear expert David Wessel update us on one of the nation's most alarming economic problems – wage stagnation.

Show Notes:

• Read more about O'Hanlon's book, "The Future of Land Warfare"
• The future of the U.S. army
• Toward a "Reaganov" Russia: Russian Security Policy after Putin
• Obama the Carpenter: The President's National Security Legacy
• What role will evidence play in the 2016 election?
• Do we already have universal preschool?
• Why public school vouchers could have bi-partisan appeal
• Hutchins Roundup: wealth inequality, student borrowing, and more

Subscribe to the Brookings Cafeteria on iTunes, listen on Stitcher, and send feedback email to BCP@Brookings.edu.