Crime Along the Mexican Border Is Lower Than in the Rest of the Country

Crime along the border and national security will be major themes in President Trump’s upcoming address where he will likely make the case for declaring a national emergency to build his wall.  Shocking images and anecdotes of crime along the border fuel this narrative, but rarely are facts deployed to make the case.  We’ve addressed the terrorism and crime arguments frequently, but only rarely touch on border crime.  Border counties have far less crime per capita than American counties that are not along the border. 

If the entire United States in 2017 had crime rates identical to those in counties along the U.S.-Mexico border, there would have been 5,720 fewer homicides, 159,036 fewer property crimes, and 99,205 fewer violent crimes across the entire country.  If the entire United States had crime rates as low as those along the border in 2017, then the number of homicides would have been 33.8 percent lower, property crimes would have been 2.1 percent lower, and violent crimes would have dropped 8 percent.

Table 1

Crime Rates by Counties in 2017, per 100,000

  Violent Crime Rate Property Crime Rate Homicide Rate
Border counties 347.8 2,207.1 3.4
Non-border counties 378.6 2,256.4 5.2
United States 377.8 2,255.2 5.1

Source: FBI Uniform Crime Reports 2017.

The numbers in Table 1 come from the FBI’s Uniform Crime Reports for 2017 that we obtained via a special request from the FBI.  The crime rates are organized by county, with all crimes reported to sub-county agencies added up using county codes from the FBI’s 2012 Law Enforcement Agency Identifiers Crosswalk.  The population figures also come from the FBI and are based on the intercensal reports obtained by the FBI from the Census Bureau.  The 23 border counties are lumped together as one and compared to the non-border counties. The numbers for the entire United States are in the last row. 

Sheriff Ronny Dodson of Brewster County Texas said, “A lot of politicians are running on securing the border.  One’s got a six point plan, one’s got a nine point plan. They’re throwing tons of money at this border. I wish they’d just shut up about it.”  Dodson went on to say, “I think they’re [politicians] just throwing money at the border for nothing. I think people on the interior see all these shows about the border where there’s violence.” 

Although Dodson’s comment is just rhetoric, there is a lot more empirical support for his claims than there is for those who claim that there is a border crime crisis.

A Sea-Surface Temperature Picture Worth a Few Hundred Words!

On January 7 a paper by Veronika Eyring and 28 coauthors, titled “Taking Climate Model Evaluation to the Next Level” appeared in Nature Climate Change, Nature’s  journal devoted exclusively to this one obviously under-researched subject.

For years, you dear readers have been subject to our railing about the unscientific way in which we forecast this century’s climate: we take 29 groups of models and average them. Anyone, we repeatedly point out, who knows weather forecasting realizes that such an activity is foolhardy. Some models are better than others in certain situations, and others may perform better under different conditions. Consequently, the daily forecast is usually a blend of a subset of available models, or, perhaps (as can be the case for winter storms) only one might be relied upon.

Finally the modelling community (as represented by the football team of authors) gets it. The second sentence of the paper’s abstract says “there is now evidence that giving equal weight to each available model projection is suboptimal.”

A map of sea-surface temperature errors calculated when all the models are averaged up shows the problem writ large:

Annual sea-surface temperature error (modelled minus observed) averaged over the current family of climate models. From Eyring et al.

Annual sea-surface temperature error (modelled minus observed) averaged over the current family of climate models. From Eyring et al.

First, the integrated “redness” of the map appears to be a bit larger than the integrated “blueness,” which would be consistent with the oft-repeated (here) observation that the models are predicting more warming than is being observed. But, more important, the biggest errors are over some of the most climatically critical places on earth.

Start with the Southern Ocean. The models have almost the entire circumpolar sea too warm, much of it off more than 1.5°C. Down around 60°S (the bottom of the map) water temperatures get down to near 0°C (because of its salinity, sea water freezes at around -2.0°C). Making errors in this range means making errors in ice formation. Further, all the moisture that lies upon Antarctica originates in this ocean, and simulating an ocean 1.5° too warm is going to inject an enormous amount of nonexistent moisture into the atmosphere, which will be precipitated over the continent in nonexistent snow.

The problem is, down there, the models are making error about massive zones of whiteness, which by their nature absorb very little solar radiation. Where it’s not white, the surface warms up quicker.

(To appreciate that, sit outside on a sunny but calm winters day, changing your khakis from light to dark, the latter being much warmer)

There are two other error fields that merit special attention: the hot blobs off the coasts of western South America and Africa. These are regions where relatively cool water upwells to the surface, driven in large part by the trade winds that blow into the earth’s thermal equator. For not-completely known reasons, these sometimes slow or even reverse, upwelling is suppressed, and the warm anomaly known as El Niño emerges (there is a similar, but much more muted version that sometimes appears off Africa).

There’s a current theory that El Niños are one mechanism that contributes to atmospheric warming, which holds that the temperature tends to jump in steps that occur after each big one. It’s not hard to see that systematically creating these conditions more persistently than they occur could put more nonexistent warming into the forecast.

Finally, to beat ever more manfully on the dead horse—averaging up all the models and making a forecast—we again note that of all the models, one, the Russian INM-CM4 has actually tracked the observed climate quite well. It is by far the best of the lot. Eyring et al. also examined the models’ independence from each other—a measure of which are (and which are not) making (or not making) the same systematic errors. And amongst the most independent, not surprisingly, is INM-CM4.

(It’s update, INM-CM5, is slowly being leaked into the literature, but we don’t have the all-important climate sensitivity figures in print yet.)

The Eyring et al. study is a step forward. It brings climate model application into the 20th century.

Border Patrol Agents Dealt with More Children Under Pres. Bush

The deaths of two children in custody in recent weeks have led to a justifiable focus on the numbers of children who enter Border Patrol custody every year. The Department of Homeland Security told Congress this week that “more children and families are being apprehended between the ports of entry than ever before.” While the large numbers of children are certainly alarming, it is incorrect that it is the largest number ever. President Bush’s administration apprehended more children with far fewer resources.

Figure 1 shows the number of children who Border Patrol apprehended from Fiscal Year (FY) 2001 to 2018. In FY 2005, Border Patrol brought into their custody 114,222 people under the age of 18. The number of minors proceeded to nosedive, bottoming out 23,089 in FY 2011, before rising again to 107,613 in FY 2014. Under President Trump, the agency arrested 82,769 in FY 2017 and about 109,000 in FY 2018, which is still below the peak.

Figure 1: Apprehensions of Juveniles By Border Patrol

Moreover, as Figure 1 also shows, Border Patrol made those apprehensions in the early 2000s with a far smaller force than under Presidents Obama or Trump. That means that President Bush had fewer resources to deal with the issue. Three times under President Bush, the average Border Patrol agent apprehended 10 children per year. Under President Trump, the average Border Patrol agent has brought in 32 percent fewer children per year as under President Bush (Figure 2). This is greater than the average for President Obama’s presidency, but still far from the most ever. 

Figure 2: Apprehensions of Juveniles Per Border Patrol Agent

What has changed in recent years is the share of apprehensions who were juveniles. As Figure 3 shows, the number of children largely moved in tandem with the number of adults prior to FY 2014, but after FY 2014, the number of children returned to the early 2000s norm, while the number of adults remained low. From FY 2001 to 2013, 9 percent of apprehensions were minors—since FY 2014, they were 24 percent of apprehensions. 

Figure 3: Apprehensions – Juvenile and Adult – and Juvenile Share of Apprehensions

The shift to a more child-heavy flow with lower overall numbers coincided with a substantial decline in apprehensions of Mexicans, and an increase in arrivals from non-Mexican countries, 90 percent of whom were from Central America’s Northern Triangle—Guatemala, Honduras, and El Salvador.

Figure 4: All Apprehensions by Border Patrol by Nationality and Juvenile Share

From the standpoint of the Trump administration, Central American children are much more difficult to deal with for several reasons. If deported, they need to be flown back to Central America, which takes more time and resources than simply putting children back in Mexico. Unaccompanied children from Mexico are afforded fewer protections and can be deported without a process to protect them, while Central American unaccompanied minors cannot are subject to procedures intended to make sure that, if they were trafficked, fled persecution, or were abandoned, they receive protection in America.

From a security perspective, however, the shift to a majority child-family flow is a blessing because children and families overwhelmingly turn themselves in to Border Patrol rather than attempt to sneak into the country. According to a DHS-commissioned report last year, nearly all families and children turn themselves in rather than seek to evade detection. This allows the U.S. government the opportunity to check them for diseases and conduct background checks.  

In the period between 2005 and 2014, the government constructed hundreds of miles of fences near urban areas, which has led to an influx of migrants in remote areas of the border. This increased the risks to child migrants trying to cross and turn themselves in for asylum, and it contributed to the deaths of the two children who ended up in Border Patrol custody. The Trump administration has aggravated this problem by institutionalizing a practice of turning away asylum seekers at ports of entry and firing tear gas at people who try to scale the fence to let themselves be caught. 

The point is not that there is not a real humanitarian crisis at the border, but it is one primarily driven by government policies, not the unprecedented number of children.

This post was updated 1/11/2019 with an improved estimate of children who came in FY 2018 to account for the fact that unaccompanied children didn’t track total children in FY 2018 for the first time. The update accounts for the increase in family units, which include children. This increases the estimated number of children from about 85,000 to 109,000. Thanks to Aaron Reichlin-Melnick for improving the methodology. 

The Cost of the Border Wall Keeps Climbing and It’s Becoming Less of a Wall

Social scientist Bent Flyvbjerg described the selection of government-funded infrastructure projects as “survival of the unfittest” because proponents of those projects systematically exaggerate the benefits and underestimate the costs.  President Trump’s proposed border wall with Mexico provides a striking example of this: A wall along the border with Mexico will likely cost about $59.8 billion to construct.

The Office of Management and Budget (OMB) recently sent a letter to Congress where it argued that $5.7 billion would pay for approximately 234 miles of a new physical steel barrier along the border.  That new estimate comes to about $24.4 million per mile.  This new OMB estimate is 41 percent more costly than the approximately $17.3 million per mile construction costs that the Department of Homeland Security (DHS) estimated just a few years ago, 2.7 times as expensive as Mitch McConnell and Paul Ryan estimated, and 5 times as expensive as Trump’s lowest estimate

Even worse, the $24.4 million per mile estimate does not include the large cost overruns for government construction projects.  Applying a conservative 50 percent cost overrun estimate to building the border fence brings the total price tag to approximately $36.6 million per mile.  Building a steel fence along the remaining 1,637 miles of Mexican border not covered by pedestrian fencing would cost approximately $59.8 billion, excluding any maintenance costs. 

There are a few caveats about the above estimate.

First, the 50 percent cost overrun estimate is conservative.  A small sample of large construction projects selected by my colleague Chris Edwards shows that cost overruns boost total project costs by an average of 3.3 fold.  The cost of the border fence is thus very likely to be more than double what I estimate above.

Second, this estimate is for the steel bollard barrier and not a concrete wall.  In other words, the currently proposed steel border fence is far cheaper than the concrete and steel wall originally proposed by President Trump.  Making it out of concrete could more than double the price.

Third, our cost estimate does not include the low-ball $864,353 annual per mile cost of maintaining the current border fence – which is likely a lot less expensive than repairing the barrier that has been proposed by Trump. 

Fourth, the OMB’s cost estimate per wall is more in line with previous Trump administration requests than estimates made by organizations that are ideologically committed to building a wall regardless of the cost to taxpayers.    

Since 2017, administration officials at the OMB have been relatively consistent in estimating that the government cost of building a border wall is around $24 million per mile.  However, the incentives for and history of government agencies systematically underestimating the costs of government construction projects makes this the lowest possible estimate.  If it is built for about $24.3 million per mile than it would be the first time that a large government construction project has come in at or below cost in a very long time.

The cost of the border wall keeps getting higher, the border wall keeps becoming less of a wall, and the administration keeps promising that it will cover less and less of the border.  At this rate, President Trump might end his administration with less fencing than he began it. 

High Tax Rates Won’t Work in Today’s Economy

Rep. Alexandria Ocasio-Cortez is making headlines calling for raising the top individual income tax rate to 70 percent to fund a Green New Deal. Sympathetic commentators are saying that such a high rate on the wealthy is no big deal because the top tax rate used to be 70 percent and above. Noah Smith at Bloomberg says the congresswomen’s plan would be “a return to the 20th century norm.”

The problem is that globalization has dramatically changed the economy over recent decades. High tax rates were not a good idea back then, but they would be disastrous now.

Before the 1980s, capital controls under fixed currency exchange rate regimes kept money bottled up within countries, keeping taxpayers in national economic prisons. That regime broke down, and today trillions of dollars flows over borders under flexible exchange rate systems, while industries and entrepreneurs have become highly mobile. Tax bases are far too movable these days for governments to sustain yesteryear’s excessive tax rates, as I discuss in Global Tax Revolution.

Every industrial country has figured that out, and their policy decisions refute the soak-the-rich tax dreaming of Rep. Ocasio-Cortez. Top income rates have plunged around the world since 1980 under governments of both the political left and right.

The chart shows the average top federal-state income tax rate for 26 core OECD countries that have good data back to 1980. The average top rate among these high-income nations fell from 68 percent in 1980 to 47 percent today. The average rate for all 35 OECD countries today is 43 percent. The top U.S. federal-state tax rate at 46 percent in 2017 was above the OECD average. The recent GOP tax cut dropped the top federal rate a few points, but raised the effective state rate by capping deductibility. On individual income taxes, America is not a low rate country.

 

The 26 countries are Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Portugal, Spain, Sweden, Switzerland, Turkey, United Kingdom, and United States. Data for 2000-2017 from the OECD. Data for 1980-1995 from Global Tax Revolution.

U.S. Trade Policy Agenda in 2019? Fixing What’s Been Breaking Since January 20, 2017

Upon taking office in 2017, President Trump accused trade partners of underhandedness, demonized U.S. companies with foreign supply chains, and perpetuated the false narrative that trade is a zero-sum game requiring an “America First” agenda. He withdrew the United States from the Trans-Pacific Partnership, threatened to pull out of North American Free Trade Agreement and the Korea-U.S. Free Trade Agreement, and initiated a war of attrition against the World Trade Organization by refusing to endorse any new Appellate Body judges until his unspecified demands were met. Yet, those were still the halcyon days of trade.

In 2018, straining all credulity, the Trump administration dusted off a seldom-used law (Section 232 of the Trade Expansion Act of 1962) to impose tariffs on imported steel and aluminum from most countries on the basis that national security is threatened by U.S. dependence on foreign sources of these widely available commodities.

Later in the year, invoking another controversial U.S. trade statute (Section 301 of the Trade Act of 1974), which is widely considered an act of vigilantism under WTO rules, the administration announced tariffs on $50 billion worth of imports from China for alleged unfair practices, such as forced technology transfer and intellectual property theft. When Beijing retaliated with tariffs on U.S. agricultural products, Trump announced that he would hit another $200 billion of imports from China with tariffs. Once again, Beijing responded by broadening its list of targeted U.S. products and the president subsequently threatened to apply U.S. levies to all imports from China (over $500 billion in 2017).

To be fair, U.S. trade policy in 2018 wasn’t only rancor, hostage-taking, and trade war. Juxtaposed against this contentious, grievance-based, enforcement-oriented U.S. posture was some “trade liberalization.” Instead of withdrawing from NAFTA and KORUS, the Trump administration renegotiated both. Both included some liberalizing provisions, but also some lamentable, protectionist retrogression, which wasn’t totally unexpected given that, in both cases, U.S. insistence on renegotiation was motivated less by an interest in updating, expanding, and modernizing the agreements than by a desire to revise provisions that would—at least nominally—tilt the playing field in favor of U.S. workers and certain manufacturers.

As 2019 begins, five major issues cast long shadows over the trade policy landscape. First is whether and how the U.S.-China trade war will be contained, scaled back, and ultimately ended. Second is the looming possibility that the Trump administration will invoke national security to impose sweeping new tariffs on automobile imports. Third is the question of whether and when Congress will pass the implementing legislation for the new NAFTA (the United States-Mexico-Canada Agreement or USMCA). Fourth is whether, when, and how the crisis at the WTO will be resolved. And fifth concerns whether the Trump administration has the wherewithal to make good on its stated intentions of negotiating new trade agreements with Japan, the European Union, the Philippines, possibly the United Kingdom, and other countries. With much of the rest of the world moving forward with a slew of new trade agreements and the United States stuck on revamping old deals, the real and opportunity costs to U.S. businesses, consumers, and taxpayers continue to mount.

Throughout the year ahead, these major issues will be the predominant focus of the research and writing of the Cato Institute’s Herbert A. Stiefel Center for Trade Policy Studies.

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Illegal Immigrant Conviction Rates Are Low, Even When Factoring in Recidivism

 Over the last two years, Cato has published three Immigration Research and Policy Briefs on illegal immigrant criminality.  In each one, we found that illegal immigrants have lower criminal conviction rates in the state of Texas and lower nationwide incarceration rates relative to native-born Americans.  Although nobody has criticized our methods or the data, we answer other criticisms that arise.

The best recent criticism is that illegal immigrant conviction rates are low because they are deported after they serve their sentences, which reduces their recidivism rates relative to native-born Americans who cannot be deported after being released from prison.  Thus, the illegal immigrant incarceration or conviction rates are lower than those of native-born Americans because it is more difficult for them to recidivate as they would have to enter the country illegally again to do so.  This has been a difficult criticism to address as data limitations are severe, but we attempted to do so after making some assumptions.  We focused on comparing first-time criminal conviction rates.

We estimate that native-born Texans had a first-time criminal conviction rate of 683 per 100,000 natives in 2016.  In the same year, we estimate that illegal immigrants had a first-time criminal conviction rate of 462 per 100,000 illegal immigrants – 32 percent below that of native-born Americans.  Thus, about 36 percent of the gap that we observed in criminal conviction rates between illegal immigrants and native-born Americans can be explained by lower illegal immigrant recidivism that is likely due to their deportation. 

This question could have been easily resolved by comparing the immigration statuses of first-time offenders.  Of course, such data do not exist.  Regardless, this is still an important question even if our estimate results from a back of the envelope estimate.  You can judge for yourself how we came to this estimate.  This is how we did it. 

First, we used the Arizona state prison data from 2016 for those admitted to state prison that year.  Of U.S. citizens sent to prison that year, 58 percent had previously been to prison at some point since 1984.  The subpopulation of deportable non-citizens, which includes illegal immigrants but is not limited to them, had a recidivism rate of 47 percent – below those of U.S. citizens, but not that much below.