Friday, April 24, 2015

Manufacturing Up, Pollution Down: How?

From 1990 to 2008, US manufacturing output (measured in inflation-adjusted dollars) rose by about one-third. At the same time, emissions of six common air pollutants fell by about 60%. How did we pull this off?  Joseph S. Shapiro and Reed Walker tackle this question in "Why is Pollution from U.S. Manufacturing Declining? The Roles of Trade, Regulation, Productivity, and Preferences," which was published in January 2015 as a working paper for the Center for Economic Studies at the US Census Bureau.

Here's a figure showing the basic question. Real US manufacturing output is the solid blue line, where the 1990 level is set equal to 100, and changes are shown relative to that level. The air pollutants shown are carbon monoxide (CO), nitrogen oxides (NOx), particulate matter (PM2.5 and PM10 refer to particulate matter that is either less than 2.5 microns or less than 10 microns), sulfur dioxide (SO2), and volatile organic compounds (VOCs). 


How could this happen? Shapiro and Walker lay out the four most common hypotheses (citations omitted):
Research suggests at least four possible explanations of these substantial improvements in U.S. air quality. First, U.S. manufacturing trade has grown substantially. When dirty industries like steel or cement move abroad, total U.S. pollution emissions may fall. Second, federal and state agencies require firms to install increasingly stringent pollution abatement technologies. Some research, for example, directly attributes national changes in air quality to the Clean Air Act and to other environmental regulations. Third, ... Americans may gradually choose to spend less on heavy manufactured goods and more on services and cleaner goods. Finally, if manufacturers use fewer dirty inputs each year to produce the same outputs, then annual productivity growth could improve air quality.
The authors use plant-level data that includes the value of shipments, production costs, and pollutants emitted. They lay out a detailed industry-level model of firms and the choices they make about reducing pollution, and then use that estimate the model with data. As is standard for any exercise like this, the model is a useful (and indeed, an unavoidable) way of organizing the data and suggesting connections, and the detailed results will depend to some extent on the specific model chosen. They also do some specific analysis of  the extent to which emissions of specific pollutants changed when tighter rules were put into effect. Readers with the technical skills can dig through the paper and evaluate it for themselves. Here, I'll stick to some big-picture insights.

The decline in pollution from US manufacturing doesn't seem to be due to a change in what was produced: instead, it's mostly a case of lower pollution to produce specific products. They write: "[C]hanges in the scale of manufacturing output or changes to the composition of products produced cannot explain trends in pollution emissions from U.S. manufacturing between 1990 and 2008. Instead, changes in emissions over this time period were almost exclusively driven by decreased pollution per unit output for narrowly de fined products." This insight suggests that while it is certainly true that global supply chains are shifting parts of manufacturing around the world, and that American consumers are spending money on services, these factors are not causing the fall in pollution from US manufacturing production.

Instead, Shapiro and Walker find strong evidence that environmental regulations are what made most of the difference. "[W]e fi nd that the increasing stringency of environmental regulation explains 75 percent or more of the 1990-to-2008 decrease in pollution emissions from U.S. manufacturing. ... [W]e find that changes in U.S. productivity have had small e ffects on U.S. pollution emissions at the economy-wide level."

An obvious follow-up question here is: What about carbon dioxide and the potential effects on climate change? In their analysis of air pollution regulation, Shapiro and Walker estimate that the increase in regulatory costs on the six pollutants mentioned above were the equivalent of imposing a pollution tax that more than doubled between 1990 and 2008. However, we have not imposed either such rules or explicit taxes on carbon dioxide, and thus it's not a big surprise that CO2 have not dropped in synch with the other emissions. The authors write: "We also measure implicit tax rates for CO2 , a pollutant which largely has not been regulated. While our inferred tax rates for most pollutants more than doubled between 1990 and 2008, the implicit tax rate for CO2 
 hardly changed over this time period."

Of course, this sort of study doesn't analyze costs and benefits: that is, it doesn't show either that the costs of these new pollution rules were worthwhile, nor does it analyze whether some alternative form of regulation might been able to achieve the same reduction in pollution at lower cost. However, the fact that it is possible to substantially reduce air pollution while still having manufacturing output rise has broader implications for holding down pollution in the US and around the world. Readers might also be interested in earlier posts on "Costs of Air Pollution in the United States" (November 7, 2011), "Air Pollution: World Biggest Health Hazard" (April 1, 2014), and "Other Air Pollutants: Soot and Methane" (June 28, 2012).

Thursday, April 23, 2015

Americans, Led by Democrats, Get Friendlier With Free Trade

I've pointed out in the past that Americans tend to be less supportive of international trade than other high-income countries of the world, and high-income countries tend to be less supportive of trade than lower-income countries. Of course, foreign trade (as measured by export/GDP ratio, for example) is relatively less important in the US economy, with its enormous internal markets, than in most other countries around the world. Thus, a working hypothesis would be that countries with lower incomes and/or more exposure to foreign trade are more likely to see it in overall positive terms.

However, a recent Gallup poll conducted in February suggest that although Americans became more likely to see trade as a "threat" than as an "opportunity" from about 2001-2008, since the Great Recession of 2007-2009, a rising share of Americans have started to viewing foreign trade as an opportunity.  Here's a graph from Gallup:

Trend: What Americans Think Foreign Trade Means for the Country

Interestingly, the Gallup poll also suggests that the rise in Americans support for foreign trade has been driven mostly by a shift toward in the pro-trade beliefs of (self-described) Democrats and Independents, not a shift in the beliefs of Republicans. Indeed, Gallup finds that Republicans were more likely than Democrats to see trade as an opportunity in the early 2000s, but now Democrats are more likely to hold such beliefs. 


   Trend: View Foreign Trade Mainly as an Opportunity for the U.S. -- by Party ID 
I welcome the overall shift toward a more positive view of foreign trade among Americans. As I've argued on this blog before, the next few decades seem likely to be a time when the most rapid economic growth is happening outside the high-income countries of the world, and finding ways for the US economy to connect with and participate in that rapid growth could be an important driver of US economic growth in the decades ahead.  In a broad sense, US attitudes over foreign trade mirror the behavior of the US trade deficit: that is, when the US trade deficit was getting worse in the early 2000s, the share of those viewing trade as a "threat" was rising, but at about the same time that the US trade deficit started declining, the share of those viewing trade as an "opportunity" started to rise.

However, I feel considerable uncertainty over how to interpret these findings. For example, it's not clear to me why Democrats and Independents are shifting their opinions about trade more strongly than Republicans. This shift doesn't seem to reflect the political divisions in Congress, where it seems that Republicans are more often the ones to be pushing for agreements to reduce trade barriers and Democrats are more likely to be opposing them. 

Wednesday, April 22, 2015

What about the EU Single Market?

Discussions of the economic situation in Europe and the eurozone during the last few years have a heavy emphasis on government debt and central bank policy. But from the time when the Treaty of Rome back in 1957 created the European Economic Community, better known as the "Common Market," a primary goal of the European project has been to create a single market. The notion is that goods, services, people, and capital are supposed to be able to move freely across borders. Mario Mariniello, André Sapir and Alessio Terzi offer an overview of how far we have travelled on "The long road towards the European single market," published in March 2015 as Bruegel Working Paper 2015/01.

Back in 1993, the European Commission accounted the "completion" of the single market project. Economic theory suggests the single market should improve productivity and thus increase the standard of living. Here's a comparison between productivity in the EU-15 (which is the 15 countries that were in the EU through the 1990s, before the addition of a wave of new EU members in 2004) and US productivity. The vertical line in 1993 doesn't suggest that the SMP, the single market project, has given Europe much of a productivity boost.

Mariniello, Sapir, and Terzi rehearse the reasons why economic theory suggests a single market should help productivity growth. For example, a single market and lower barriers to trade means that firms face more competition, which should encourage innovation. The cross-fertilization of ideas and methods across Europe should also favor innovation. Firms would be operating in a larger European market rather than a smaller national market, so they can expand to take advantage of economies of scale.  Workers can move to regions where the economy is expanding and job opportunities are more plentiful. Financial integration would help to allocate investment capital to projects with higher rates of return and greater competitiveness.  However, they also point out that when empirical researchers tried to quantify these effects, they don't find much--as the figure above implies.

What went wrong? The authors argue that the single market is far from complete along a number of dimensions. Here is their "non-exhaustive" list of remaining major barriers:

Insufficient mutual recognition. Official tariffs between EU countries are essentially zero. But even more than a half-century after the Treaty of Rome, regulations for products and services still vary considerably across EU countries, so the costs of doing business across borders remain high.

Poor quality of implementation of directives. An OECD report emphasized that efforts to harmonize regulations across Europe and promote competition have often been accompanied by "regulatory creep," adding to the costs of such regulation, as well as by "gold-plating," which is implementation that goes beyond the requirements and thus makes the business climate more complex rather than simpler.

Public Procurement. They cite evidence that public procurement is 16% of GDP in the EU countries, but only 3% of contracts are actually cross border, and only 20% of bids end up being published.

Service Sectors. National-level rules and regulations are especially strong in a number of service industries, including retail trade, professional services (doctors, lawyers, accountants), and network industries (telecommunications)

Infrastructure not integrated. Infrastructure is still planned and funded mostly a national level, including both infrastructure for transportation and for communication. The national emphasis tends to be on moving and communicating within the country, not across borders.

Free movement of people. Only about 3% of the EU workforce actually works in another country. Some of the issue is language, culture, and family ties. But another part is that countries often have rules that discourage working elsewhere, like a lack of eligibility for retirement and unemployment programs, lack of recognition of professional qualifications, and lack of coordination on personal taxes that can lead to being double-taxed in two countries on the same income.

Differences in regulation across countries. There is no common set of banking regulations across the EU countries. The 28 countries have  28 different tax codes. Environmental standards and consumer protection standards vary by country.

Of course, this outcome is unsurprising from a political economy viewpoint. On one side, EU countries make strong statements about their commitment to the European project, and at some level they mean it. But when push comes to shove in domestic politics, there remains a strong desire for national control over all sorts of regulations, prodded by national-level interest groups that like limited competition and public monopolies and also play a large role in the electoral fortunes of national politicians.

But as the EU economy staggers along with barely positive economic growth and an unemployment rate that has been above 10% for the last three years (and of course is much worse in certain countries), it's time to recognize that Europe's productivity problems are about more than government debt and managing the euro-zone. Indeed, even if the gains to European productivity are small in the short-term and only emerge over time, there is good reason to believe that moving toward a single market could help to ease some of the macroeconomic stresses created by having such different economies sharing the single euro currency.

Tuesday, April 21, 2015

Why Did Sweden, of All Places, Abolish Its Century-Old Inheritance Tax?

The US House of Representatives voted on April 16 to repeal the estate tax. The bill seems unlikely to become law. The US Senate seems unlikely to pass such legislation, because it would be filibustered by Democrats,and President Obama has said he would veto the measure if it passed through Congress. But did you know that Sweden, with its well-earned reputation for egalitarian social policy, abolished its century-old inheritance tax in 2004? Indeed, Portugal also abolished its inheritance tax in 2004, as did Austria in 2008 and Norway in 2014.

Why did Sweden abolish its inheritance tax? Magnus Henrekson and Daniel Waldenström provide background in "Inheritance Taxation in Sweden, 1885–2004:The Role of Ideology, Family Firms and TaxAvoidance,"  written as the Research Institute for Industrial Economics (IFN) Working Paper No. 1032 (October 27, 2014).

For context, here's a figure that offers an illustration of Sweden's inheritance tax over time. The top tax rate rose sharply through much of the 20th century, topping out at 65%. Perhaps more interesting, the horizontal axis gives a sense of the income level where those top rates kicked in. For example, in 1985, although the very top tax rate applied only to those with inheritance levels at roughly 30 times annual income of a worker, many of those with inheritances that were only 10 times the annual income of a worker or less also could end up paying inheritance tax.


Of course, Sweden is not extraordinary in having some high top-level inheritance taxes. Here's a figure with some international comparisons of countries, including the United States, where the top rate of inheritance taxes exceeded 60% over time. However, notice that in all of those countries the peak inheritance tax rates are in the past--often several decades in the past. Top rates for inheritance taxes have been coming down.
Of course, each country has its own distinctive politics and history that go into the decisions about inheritance taxes. What caused Sweden to abolish the tax in 2004? Here are some of the reasons from Henrekson and Waldenström, with my own thoughts about the arguments apply in a US context.

1) In Sweden, a relatively large share of inheritances owed some inheritance tax. The authors report: "In the last year of the tax, the exemption level was a mere one-quarter of an annual production worker’s income (SEK 70,000), and the top marginal rate was reached at an inherited amount of just over two times the annual income of a production worker." This is probably the main difference with US inheritance tax, which has high exemptions. For example, in 2015 only estates of more than $5.4 million will even potentially need to pay any estate tax at all. Historically, only about 1 in 700 deaths in the US results in paying any estate tax.

2) Sweden had built a number of "safety valves" into its inheritance tax. For example, "owners of unlisted business equity"--often those inheriting a family business--had strict limits on what they would pay. Apparently, someone inheriting a family business in Sweden under no circumstances paid an inheritance tax of more than 9%. There were prominent examples of how wealthy Swedish families (Wallenberg, Söderberg) had created foundations to shield family wealth from the inheritance tax. There were a variety of ways to reduce the estate tax owed: for example, family holdings could be loaded up with debt, to reduce their current value. Money could be passed between generations through real estate holdings, which faced different tax rules, or buy purchasing large life insurance policies, because in Sweden life insurance payments were tax-free for the beneficiary. Of course, one of the easiest ways to pass wealth between generations is to do so before death, by hiring the next generation into the family business at an exorbitant salary. Obviously, when those with high wealth levels have many ways to find ways to avoid or minimize an estate tax, while still passing along wealth to future generations, such a tax ends up looking unfair and pointlessly symbolic. A globalizing economy surely adds to the ways in which wealth can be accumulated and passed on in other nations, where the estate tax rules may be more lenient.

3) The authors point out that in Sweden and in other countries, the tax funds raised by estate taxes are are often around 1-2% or even less of total government revenues. Thus, whether you think that  dropping the estate and inheritance tax is wise or unwise, it makes much less difference to the government bottom line than many other tax changes.

As regular readers know, I'm concerned about the extent to which economic inequality is transmitted between generations. But in the modern US economy, inherited fortunes don't matter in the same way that they did, say, back in 19th century Europe. Instead, I think the transmission of economic inequality in the modern economy happens primarily because of parents who have the resources to do so provide all kinds of extra support and opportunities to their children. I find it hard to get much excited over the current debates about the US estate tax, which are essentially arguments over whether the labyrinthine rules of the tax code will make it harder or easier for a tiny slice of the very wealthiest households--together with their high-priced estate lawyers--to pass along resources after death. I worry a lot more about all the children growing up whose families don't have the resources and connections to provide a special added turbo-boost to their development, and how their life opportunities are being shaped and determined.

Monday, April 20, 2015

The Data Revolution and Economic Research

Empirical research in economic is being revolutionized (and no, that word is not too strong) by two major new sources of data: administrative data and private sector data. Liran Einav and Jonathan Levin explain in "Economics in the age of big data," which appears in Science magazine, November 7, 2014 (vol 346, iossue 6210; the "Review Summary" is p. 715 and the "Review" article itself is pp. 1243089-1 to 12403089-6). Science is not freely available online, but many readers will have access through library subscriptions.

To grasp the magnitude of the change, you need to know that a two or more decades ago, economists had only a few main sources of data: there was data produced by the government for public consumption like all the economic statistics from the Bureau of Economic or the Bureau of Labor, the surveys from the US Census, and a few other major surveys. Sometimes, economists also constructed their own data by working in library archives or carrying out their own surveys. For example, I remember as an undergraduate back around 1980 I remember doing basic empirical exercises where you wrote programs (stored on punch cards!) to find correlations between GDP, unemployment, interest rates, and car sales. I remember as a graduate student in the early 1980s compiling data on the miles-per-gallon of new cars, which involved collecting the annual paper brochures from the US Department of Transportation and then inputting the date to a computer file (no more punchcards by then!).  As Einav and Levin put it: "Even 15 or 20 years ago, interesting and unstudied data sets were a scarce resource."

One of the major new sources of data is "administrative data," which is data collected by the government in course of administering various programs. As Einav and Levin point out, some of the most prominent results in empirical economics in recent years are based on administrative data.

For example, the evidence that most of the rise in income inequality is at the very top of the income distribution is based on IRS tax data. Evidence on wide variation in health care spending, how people and providers react to different health insurance provisions, and the use of certain health care treatments across states (thus implying that some health care providers in some states may be overdiagnosing or underdiagnosing) is often based on administrative data from Medicare and Medicaid. Evidence on how teachers can affect student academic achievement is based on a combination of student test scores and the patterns of how teachers are assigned to classrooms.

Of course, the use of administrative data for research raises legitimate privacy issues. But  just to be clear, it's the existence of this data in government hands that raises the privacy concerns in the first place. Before the administrative data is received by researchers, it is "anonymized" so that it should be impossible to identify individuals. Einav and Levin sum up:
The potential of administrative data for academic research is just starting to be realized, and substantial challenges remain. This is particularly true in the United States,where confidentiality and privacy concerns, as well as bureaucratic hurdles, have made accessing administrative data sets and linking records between these data sets relatively cumbersome. European countries such as Norway, Sweden, and Denmark have gone much farther to merge distinct administrative records and facilitate research. ... However, even with today’s somewhat piecemeal access to administrative records, it seems clear that these data will play a defining role in economic research over the coming years.
The other major source of new data comes from private efforts, either by firms or by researchers. Your credit card company, your insurance company, your cable access provider, and many other firms have a lot of information about your life and your preferences. They are already doing in-house research on this data, but in some cases, they are pairing with research economists to work on anonymized forms of the data. For example, Einav and Levin have done research with eBay data on how Internet sales taxes affect online shopping.


Some companies are taking the next step and publishing data. Einav and Levin write:
Already the payroll service company ADP publishes monthly employment statistics in advance of the Bureau of Labor Statistics, MasterCard makes available retail sales numbers, and Zillow generates house price indices at the county level. These data may be less definitive than the eventual government statistics, but in principle they can be provided faster and perhaps at a more granular level, making them useful complements to traditional economic statistics. 

Similarly, Google publishes a "Flu Trends" list which seeks to provide early warning of flu outbreaks, faster than the Center for Disease Control statistics, by using data from search queries.

 Researchers can create their own data sets by "scraping" the web: that is, by writing programs that will download data from various websites at regular intervals. One of the best-known of these projects is the Billion Prices Project run by Alberto Cavallo and Roberto Rigobon at MIT. Their program downloads detailed data on prices and product characteristics from websites all over the world every day on hundreds of thousands of products. For a sense of the findings that can emerge from this kind of study, here's one graph showing the US price level as measured by the Billion Prices Project and the official Consumer Price Index. They are fairly close. Next  look at the price level from the Billion Prices Project and the official measure of inflation in Argentina. It's strong publicly available evidence that the government in Argentina is gaming its inflation statistics.


Finally, many more economists are creating their own data by carrying out their own social experiments and surveys.

The new sources of data are changing the emphasis of published economic research. If you go back about 30 years, the majority of papers appearing in top research journals were theoretical--that is, they contained either no data or a few bits of illustrative data. Now, about 70% of the papers in top economics journals are primarily empirical and data-based. Einav and Levin offer evidence that for empirical papers (not including experiments designed by the researcher), only about 5-10% of the papers used administrative or private data back in 2006-2008, but by 2013 and 2014, the share of empirical papers using administrative and private data was nearly half. The tools for collecting and using this administrative and private-sector data are different in many ways from what economists have traditionally done. Careers, reputations, and eventually even Nobel prizes will be built on this body of work.


Friday, April 17, 2015

Snapshots of Global Military Spending

For an overview of patterns of global military spending, my go-to source is the Stockholm International Peace Research Institute. SIPRI has just published "Trends in World Military Expenditure, 2014," by Sam Perlo-Freeman, Aude Fleurant, Pieter D. Wezeman and Siemon T. Wezeman. Here are some patterns that jumped out at me.

As a starter, here's the overall pattern of global military spending since the late 1980s. Since the Great Recession hit, global military spending has dropped a bit (as measured in inflation-adjusted dollars).

Here's a table showing the 15 countries with the highest level of military spending. US is one-third of all global military spending, or to put it another way, US military spending is roughly equal to the next seven nations on the list combined. Of course, it's worth remembering that military spending doesn't buy the same outcomes in all countries; for example, the pay of a soldier in India or China is considerably lower than that in the United States. It's also interesting to me that US military spending as a share of GDP is higher than for  most of the other countries in the top 15, with the exception of Russia, Saudi Arabia, and UAE. And it's thought-provoking to compare, say, military spending in China to that in Japan and South Korea, or military spending in Russia to that in Germany and France.

Finally, here's a list of the countries where military spending is more than 4% of their GDP.
As the report notes: "A total of 20 countries—concentrated in Africa, Eastern Europe and the Middle East—spent more than 4 per cent of their GDP on the military in 2014, compared to 15 in 2013.
Only 3 of the 20 countries are functioning democracies, and the majority were involved in armed conflict in 2013–14 or had a recent history of armed conflict."
I won't editorialize here, except to note that when countries devote very high levels of GDP to military spending, they are putting their money behind a belief that using or threatening military force is in their near future.


Thursday, April 16, 2015

Natural Disasters: Insurance Costs vs. Deaths

The natural disasters that cause the highest levels of insurance losses are only rarely the same as the natural disasters that cause the greatest loss of life. Why should that be? Shouldn't a bigger disaster affect both property and lives? The economics of natural disasters (and yes, there is such a subject) offers and answer. But first, here are two lists from the Sigma report recently published by Swiss Re (No 2, 2015).

The first list shows the 40 disasters that caused the highest insurance losses from 1970 to 2014 (where the size of losses has been adjusted for inflation and converted into 2014 US dollars). The top four items on the list are: Hurricane Katrina that hit the New Orleans area in 2005 (by far the largest in terms of insurance losses), the 2011 Japanese earthquake and tsunami; Hurricane Sandy that hit the New York City area in 2012; and Hurricane Andrew that blasted Florida in 1992. The fifth item is the only disaster on the list that wasn't natural: the terrorist attacks of September 11, 2001.


Now consider a list of the top 40 disasters over the same time period from 1970 to 2014, but this time they are ranked by the number of dead and missing victims. The top five on this list are the Bangladesh storm and flood of 1970 (300,000 dead and missing); China's 1976 earthquake (255,000 dead and missing),  Haiti's 2010 earthquake (222,570 dead and missing), the 2004 earthquake and tsunami that hit Indonesia and Thailand (220,000 dead and missing), and the 2008 tropical cyclone Nargis that hit the area around Myanmar (138,300 dead and missing). Only two disasters make the top 40 on both lists: the 2011 Japanese earthquake and tsunami, and Japan's Great Hanshin earthquake of 1995.


The reason why there is so little overlap between the two lists is of course clear enough: the effects of a given natural disaster on people and property will depend to a substantial extent on what happens before and after the event. Are most of the people living in structures that comply with an appropriate building code? Have civil engineers thought about issues like flood protection? Is there an early warning system so that people have as much advance warning of the disaster as possible? How resilient is the infrastucture for electricity, communications, and transportation in the face of the disaster? Was there an advance plan before the disaster on how support services would be mobilized?

In countries with high levels of per capita income, many of these investments are already in place, and so natural disasters have the highest costs in terms of property, but relatively lower costs in terms of life. In countries with low levels of per capita income, these investments in health and safety are often not in place, and much of the property that is in place is uninsured. Thus, a 7.0 earthquake hits Haiti in 2010, and 225,000 die. A 9.0 earthquake/tsunami combination hits Japan in 2011--and remember, earthquakes are measured on a base-10 exponential scale, so a 9.0 earthquake has 100 times the shaking power of a 7.0 quake--and less than one-tenth as many people die as in Haiti.

Natural disasters will never go away, but with well-chosen advance planning, their costs to life and property can be dramatically reduced, even (or perhaps especially) in low-income countries. For an overview of some economy thinking in this area, a starting point is my post on "Economics and Natural Disasters," published November 2, 2012, in the aftermath of Hurricane Sandy.