Tag Archives: World Bank

The Economics of Regulation Part 2: Quantifying Regulation

I recently wrote about a new study from economists John Dawson and John Seater that shows that federal regulations have slowed economic growth in the US by an average of 2% per year.  The study was novel and important enough from my perspective that it deserved some detailed coverage.  In this post, which is part two of a three part series (part one here), I go into some detail on the various ways that economists measure regulation.  This will help put into context the measure that Dawson and Seater used, which is the main innovation of their study.  The third part of the series will discuss the endogenous growth model in which they used their new measure of regulation to estimate its effect on economic growth.

From the macroeconomic perspective, the main policy interventions—that is, instruments wielded in a way to change individual or firm behavior—used by governments are taxes and regulations.  Others might include spending/deficit spending and monetary policy in that list, but a large percentage of economics studies on interventions intended to change behavior have focused on taxes, for one simple reason: taxes are relatively easy to quantify.  As a result, we know a lot more about taxes than we do about regulations, even if much of that knowledge is not well implemented.  Economists can calculate changes to marginal tax rates caused by specific policies, and by simultaneously tracking outcomes such as changes in tax revenue and the behavior of taxed and untaxed groups, deduce specific numbers with which to characterize the consequences of those taxation policies.  In short, with taxes, you have specific dollar values or percentages to work with. With regulations, not so much.

In fact, the actual burden of regulation is notoriously hidden, especially when directly compared to taxes that attempt to achieve the same policy objective.  For example, since fuel economy regulations (called Corporate Average Fuel Economy, or CAFE, standards) were first implemented in the 1970s, it has been broadly recognized that the goal of reducing gasoline consumption could be more efficiently achieved through a gasoline tax rather than vehicle design or performance standards.  However, it is much easier for a politician to tell her constituents that she will make auto manufacturers build more fuel-efficient cars than to tell constituents that they now face higher gasoline prices because of a fuel tax.  In econospeak, taxes are salient to voters—remembered as important and costly—whereas regulations are not. Even when comparing taxes to taxes, some, such as property taxes, are apparently more salient than others, such as payroll taxes, as this recent study shows.  If some taxes that workers pay on a regular basis are relatively unnoticed, how much easier is it to hide a tax in the form of a regulation?  Indeed, it is arguably because regulations are uniquely opaque as policy instruments that all presidents since Jimmy Carter have required some form of benefit-cost analysis on new regulations prior to their enactment (note, however, that the average quality of those analyses is astonishingly low).  Of course, it is for these same obfuscatory qualities that politicians seem to prefer regulations to taxes.

Despite the inherent difficulty, scholars have been analyzing the consequences of regulation for decades, leading to a fairly large literature. Studies typically examine the causal effect of a unique regulation or a small collection of related regulations, such as air quality standards stemming from the Clean Air Act.  Compared to the thousands of actual regulations that are in effect, the regulation typically studied is relatively limited in scope, even if its effects can be far-reaching.  Because most studies on regulation focus only on one or perhaps a few specific regulations, there is a lot of room for more research to be done.  Specifically, improved metrics of regulation, especially metrics that can be used either in multi-industry microeconomic studies or in macroeconomic contexts, could help advance our understanding of the overall effect of all regulations.

With that goal in mind, some attempts have been made to more comprehensively measure regulation through the use of surveys and legal studies.  The most famous example is probably the Doing Business index from the World Bank, while perhaps the most widely used in academic studies is the Indicators of Product Market Regulation from the OECD.  Since 2003, the World Bank has produced the Doing Business Index, which combines survey data with observational data into a single number designed to tell how much it would cost to “do business,” e.g. set up a company, get construction permits, get electricity, register property, etc., in set of 185 countries.  The Doing Business index is perhaps most useful for identifying good practices to follow in early to middle stages of economic development, when property rights and other beneficial institutions can be created and strengthened.

The OECD’s Indicators of Product Market Regulation database focuses more narrowly on types of regulation that are more relevant to developed economies.  Specifically, the original OECD data considered only product market and employment protection regulations, both of which are measured at “economy-wide” level—meaning the OECD measured whether those types of regulations existed in a given country, regardless of whether they were applicable to only certain individuals or particular industries.  The OECD later extended the data by adding barriers to entry, public ownership, vertical integration, market structure, and price controls for a small subset of broadly defined industries (gas, electricity, post, telecommunications, passenger air transport, railways, and road freight).  The OECD develops its database by surveying government officials in several countries and aggregating their responses, with weightings, into several indexes.

By design, the OECD and Doing Business approaches do a good job of relating obscure macroeconomic data to actual people and businesses.  Consider the chart below, taken from the OECD description of how the Product Market Regulation database is created.  As I wrote last week and as the chart shows, the rather sanitized term “product market regulation” actually consists of several components that are directly relevant to a would-be entrepreneur (such as the opacity of a country’s licenses and permits system and administrative burdens for sole proprietorships) and to a consumer (such as price controls and barriers to foreign direct investment).  You can click on the chart below to see some of the other components that are considered in OECD’s product market regulation indicator.

oecd product regulation tree structure

Still, there are two major shortcomings of the OECD data (shortcomings that are equally applicable to similar indexes produced by the World Bank and others).  First, they cover relatively short time spans.  Changes in regulatory policy often require several years, if not decades, to implement, so the results of these changes may not be reflected in short time frames (to a degree, this can be overcome by measuring regulation for several different countries or different industries, so that results of different policies can be compared across countries or industries).

Second, and in my mind, more importantly, the Doing Business Index is not comprehensive.  Instead, it is focused on a few areas of regulation, and then only on whether regulations exist—not how complex or burdensome they are.  As Dawson and Seater explain:

[M]easures of regulation [such as the Doing Business Index and the OECD Indicators] generally proceed by constructing indices based on binary indicators of whether or not various kinds of regulation exist, assigning a value of 1 to each type of regulation that exists and a 0 to those that do not exist.  The index then is constructed as a weighted sum of all the binary indicators.  Such measures capture the existence of given types of regulation but cannot capture their extent or complexity.

Dawson and Seater go out of their way to mention at least twice that the OECD dataset ignores environmental and occupational health and safety regulations.  Theirs is a good point – in the US, at least, environmental regulations from the EPA alone accounted for about 15% of all restrictions published in federal regulations in 2010, and that percentage has consistently grown for the past decade, as can be seen in the graph below (created using data from RegData).  Occupational health and safety regulations take up a significant portion of the regulatory code as well.

env regs as percentage of total

In contrast, one could measure all federal regulations, not just a few select types.  But then the process requires some usage of the actual legal texts containing regulations.  There have been a few attempts to create all-inclusive time series measures of regulation based on the voluminous legal documents detailing regulatory activity at the federal level.   For the most part, studies have relied on the Federal Register, the government’s daily journal of newly proposed and final regulations.  For example, many scholars have counted pages in the Federal Register to test for the existence of the midnight regulations phenomenon—the observation that the administrations of outgoing presidents seem to produce abnormally large numbers of regulations during the lame-duck period

There are problems with using the Federal Register to measure regulation (I say this despite having used it in some of my own papers).  First and foremost, the Federal Register includes deregulatory activity.  When a regulatory agency eliminates words, paragraphs, or even entire chapters from the CFR, the agency has to notify the public of the changes.  The agency does this by printing a notice of proposed rulemaking in the Federal Register that explains the agencies intentions.  Then, once the public has had adequate time to comment on the agencies proposed actions, the agency has to publish a final rule in the Federal Register—another set of pages that detail the final actions the agency is taking.  Obviously, if one is counting pages published in the Federal Register and using that as a proxy for the growth of regulation, deregulatory activity that produces positive page counts would lead to incorrect measurements.  

Furthermore, pages published in the Federal Register may be a biased measure because the number of pages associated with individual rulemakings has increased over time as acts of Congress or executive orders have required more analyses. In his Ten-Thousand Commandments series, Wayne Crews mitigates this drawback to some degree by focusing only on pages devoted to final rules.  The Ten-Thousand Commandments series keeps track of both the annual number of final regulations published in the Federal Register and the annual number of Federal Register pages devoted to final regulations.

Dawson and Seater instead rely on the Code of Federal Regulations, another set of legal documents related to federal regulationsActually, the CFR would be better described as the books that contain the actual text of regulations in effect each year.  When a regulatory agency creates new regulations, or alters existing regulations, those changes are reflected in the next publication of the CFR.  Dawson and Seater collected data on the total number of pages in the CFR in each year from 1949 to 2005. I’ve graphed their data below.

dawson and seater cfr pages

*Dawson and Seater exclude Titles 1 – 3 and 32 from their total page counts because they argue that those Titles do not contain regulation, so comparing this graph with page count graphs produced elsewhere will show some discrepancies.

Perhaps the most significant advantage of the CFR over counting pages in the Federal Register is that it allows for decreases in regulations. However, using the CFR arguably has several advantages over indexes like the OECD product market regulation index and the World Bank Doing Business index.  First, using the CFR captures all federal regulation, not just a select few types.  Dawson and Seater point out:

Incomplete coverage leads to two problems: (1) omitted variables bias, and, in any time series study, (2) divergence between the time series behavior of subsets of regulation on the one hand and of total regulation on the other.

In other words, ignoring potentially important variables (such as environmental regulations) can cause estimates of the effect of regulation to be wrong.

Second, the number of pages in the CFR may reflect the complexity of regulations to some degree.  In contrast, the index metrics of regulation typically only consider whether a regulation exists—a binary variable equal to 1 or 0, with nothing in between.  Third, the CFR offers a long time series – almost three times as long as the OECD index, although it is shorter than the Federal Register time series.

Of course, there are downsides to using the CFR.  For one, it is possible that legal drafting standards and language norms have changed over the 57 years, which could introduce bias to their measure (Dawson and Seater brush this concern aside, but not convincingly in my opinion).  Second, the CFR is limited to only one country—the United States—whereas the OECD and World Bank products cover many countries.  Data on multiple countries (or multiple industries within a country, like RegData offers) allow comparisons of real-world outcomes and how they respond to different regulatory treatments.  In contrast, Dawson and Seater are limited to constructing a “counterfactual” economy – one that their model predicts would exist had regulations stayed at the level they were in 1949.  In my next post, I’ll go into more detail on the model they use to do this.

If You Are Successful, Did You Do It On Your Own?

A lot of people are upset with the President’s remarks from last weekend. Here is what the President said:

[L]ook, if you’ve been successful, you didn’t get there on your own. You didn’t get there on your own. I’m always struck by people who think, well, it must be because I was just so smart. There are a lot of smart people out there. It must be because I worked harder than everybody else. Let me tell you something — there are a whole bunch of hardworking people out there. (Applause.)

If you were successful, somebody along the line gave you some help. There was a great teacher somewhere in your life. Somebody helped to create this unbelievable American system that we have that allowed you to thrive. Somebody invested in roads and bridges. If you’ve got a business — you didn’t build that. Somebody else made that happen. The Internet didn’t get invented on its own. Government research created the Internet so that all the companies could make money off the Internet.

I agree with those who believe the remarks seem to completely dismiss the role of the entrepreneur. I also agree with those who think the president is exaggerating the role of government. But in two important respects, I think it would be a mistake for free market advocates to dismiss the entire statement. In fact, we should embrace some of it.

First, the president is absolutely right to note that intelligence is not the only determinant of success. In fact, I expressed a very similar sentiment in my SPN piece:

What allows me and my fellow countrymen to command such salaries? I’d like to think work ethic or intelligence has something to do with it. But the truth is that those things can explain only so much. There are plenty in the bottom 99 percent with better work ethics and more intel­ligence than I. Most of the world’s unemployed and underemployed—the ones with nowhere to go and nothing to do—would jump at the opportu­nity to work hard and would excel if given the opportunity to do so.

Second, the president is absolutely correct that a person’s productivity is crucially dependent upon the “system” in which he or she operates. Too many free-market advocates get hung up on the ‘pull yourself up by your bootstraps’ mentality and miss this point. There is a reason more successful businesses are started in the U.S. than in Zimbabwe. It has nothing to do with the inherent business acumen of Americans and everything to do with our “system.”

As I point out in my SPN piece, those who move just a short distance across the border from Mexico into the U.S. increase their salaries more than 415 percent. What could possibly account for such a dramatic improvement?

Physical capital is surely part of it. Once on the American side of the border, the typical worker is more likely to work with machines that enhance her productivity. But an important World Bank study demonstrates that these differences in physical capital only account for a small fraction of the differences in productivity around the world.

Much more important are differences in “intangible assets.” These are factors that cannot be seen but nevertheless help determine our productivity. When a worker produces a good or a service, he uses more than the physical tools in his hand. As I wrote in the piece:

He also uses a legal system, which (ideally) ensures his contracts are honored. He uses a police force, which (hopefully) protects his property. He uses a curren­cy, which either affords him a reliable means of exchange or one that may lose its value at any moment. He depends on the honesty of government officials as they judge his compliance with the laws. Since governments require resources, he relies on the incentives of his country’s tax regime as it encourages or discourages him (and those with whom he does busi­ness) to work, save, invest, and consume. A worker even relies on the culture of his countrymen. Are they disposed to praise him for his hard work and business acumen? Or—like the Romans in their decline—will his countrymen save their plaudits for those who destroy goods in armed conflict rather than sell them in the marketplace?

It turns out that the U.S. has a much larger stock of such intangible capital than Mexico (the World Bank estimates it at $420,000 per capita in the U.S. compared with only about $34,000 per capita in Mexico). And this helps make a Mexican immigrant to the U.S. far more productive than he would be in his home country.

But here is the irony in the President’s statement: the enormous stock of intangible capital in the U.S. is mostly due to the country’s economic freedom, not its active government. Historically speaking, people in the United States have been some of the most-productive on the planet because they have been the most-free. Compared with citizens elsewhere, Americans have enjoyed better protection of their property, lower taxes, fewer and lighter regulations, greater ability to trade with foreigners, and more-sound monetary policy. Historically, business decisions in the U.S. have been more likely to be driven by consumer interests than by political considerations. Our culture has tended to celebrate entrepreneurship and risk-taking and we have been more willing to trust one another. I put all of this in the past tense because there is evidence that many of these things are less true now than they were twelve years ago.

But the basic point is that, historically, the “unbelievable American system” has indeed allowed Americans to thrive.

But the president is mistaken to imply that our “system” is superior because we spend more on roads or bridges, or because we invest more public capital in private R&D, or because we make more grants to start-up businesses like Solyndra. To the extent our system has succeeded, it is because it has allowed Americans more freedom.

It takes a village. A free one.

Trust Me On This One

Think about how often you depend on the kindness trust of strangers. You can walk into a restaurant, order the most expensive item on the menu and leisurely eat it without offering up any sort of collateral. The restaurateur may not know you, but he trusts you. Similarly, you can walk into a New York City hotel, put down a credit card and spend a week in the lap of luxury. The hotel doesn’t know you, but they know your credit card and extend their trust in Visa to you.

Like money, trust lubricates the wheels of commerce. It allows us to do business with people we’ve never met, expanding the “extent of the market,” and our standard of living. Indeed, as Steve Knack, senior economist at the World Bank, sees it: “If you take a broad enough definition of trust, then it would explain basically all the difference between the per capita income of the United States and Somalia.”

Why is it that strangers in the United States are so much more willing to trust one another compared with strangers in Somalia? More importantly: how can we build trust in places where it is lacking? Studies have found that humans have some rather ugly rules of thumb when it comes to trust. They are more likely to trust others if they are perceived as high status or if they are of the same race. That doesn’t offer much in the way of helpful policy advice for building trust.

But new research by Omar Al-Ubaydli, Daniel Houser, John V. Nye, Maria Pia Paganelli and Xiaofei Pan points to another trust-builder: experience with markets. They write:

In randomized control laboratory experiments, we find that those primed to think about markets exhibit more trusting behavior. We randomly and unconsciously prime experimental participants to think about markets and trade. We then ask them to play a trust game involving an anonymous stranger. We compare the behavior of these individuals with that of a group who are not primed to think about anything in particular. Priming for market participation affects positively the beliefs about the trustworthiness of anonymous strangers, increasing trust.

Progress depends on the extent of the market, the extent of the market depends on trust, and trust can be facilitated with familiarity with markets.

Economic Freedom In Decline

Today, the Fraser Institute released the 2011 version of the Economic Freedom of the World report. Authored by James Gwartney of Florida State University, Robert Lawson of Southern Methodist University, and Joshua Hall of Beloit College, the index is an annual measure of economic freedom. Drawing on 42 data points gathered from each of 141 countries, it assigns each nation an economic freedom score. The score reflects the degree to which citizens in the nation enjoy economic freedom as characterized by “personal choice, voluntary exchange coordinated by markets, freedom to enter and compete in markets, and protection of persons and their property from aggression by others.”

Chapter 3 of the new report features an essay by Jean-Pierre Chauffour, lead economist of the World Bank’s Middle East and North Africa Region. In Figure 3.1, reproduced below, Chauffour shows the relationship between economic freedom and the log of per capita income (adjusting for purchasing power parity).

But economic freedom seems to be about more than just per capita income. Readers of Neighborhood Effects know that scores of peer-reviewed studies have examined the relationship between economic freedom and all sorts of measures of well being. The overwhelming evidence is that economic freedom is positively related to things humans like (per capita income of the poor, life expectancy, access to clean water, etc.) and negative related to things humans don’t like (poverty, child labor, etc.). Some of the most sophisticated studies have even tried to disentangle cause and effect.

So where do we stand? The data are lagged, so this year’s report now calculates economic freedom through 2009. There are some bright spots. For example:

The chain-linked summary ratings of Uganda, Zambia, Nicaragua, Albania, and Peru have improved by three or more points since 1990.

There is also some bad news:

 ….In contrast, the summary ratings of Venezuela, Zimbabwe, United States, and Malaysia fell by eight tenths of a point or more between 1990 and 2009, causing their rankings to slip.

In fact, those countries that slipped the most since 2000 were: Argentina, Iceland, Ireland, the United States, and Venezuela.

To see just how far the U.S. has fallen, consider the graph below. The first phase shows the U.S. (chain-linked) economic freedom score from 1970 through 2000. It is slow and steady progress the whole way. The second phase shows the U.S. score from 2000 onward. It is a dramatic and precipitous drop. Notice, by the way, that the ascendant periods lasts through three presidents of two different parties. The descent also seems to have persisted irrespective of the party in office. It seems that the policies that impact economic freedom are not strongly related to partisanship.

Mercatus has its own state-level measure of economic freedom, developed by Jason Sorens of the University of Buffalo (SUNY) and William Ruger of Texas State University.

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Addendum: Here is Arnold Kling on the report. Here is David Henderson. Here is Mark Steyn. Here is Robert Lawson.

Economic Freedom, Economic Growth, and Freedom in the 50 States

Today, Mercatus released a new edition of William Ruger and Jason Sorens’s Freedom in the 50 States. To my knowledge, it is the most-comprehensive analysis of freedom at the state level, covering both economic freedoms and personal freedoms. The authors explain their study in this pretty awesome video:

Vero offers some interesting analysis over at The Corner.

The timing is excellent, as the World Bank recently released a new study of the impact of economic freedom on economic performance (HT to Robert Lawson). They conclude:   

Reviewing the economic performance—good and bad— of more than 100 countries over the past 30 years, this paper finds new empirical evidence supporting the idea that economic freedom and civil and political liberties are the root causes of why some countries achieve and sustain better economic outcomes. For instance, a one unit change in the initial level of economic freedom between two countries (on a scale of 1 to 10) is associated with an almost 1 percentage point differential in their average long-run economic growth rates.

To put the numbers in perspective, what if, in 1975 (the first year for which they have data), the US level of economic freedom had been 1 unit lower? This would have put us in the neighborhood of Canada or Panama at the time. Then, other things being equal, the World Bank study suggests that we’d expect today’s economy to be about 30 percent smaller than it actually is. What if we’d had 1 unit less freedom in 1945? Then we’d expect today’s economy to be about half its current size.   

 As I have mentioned elsewhere, state-level studies corroborate the international evidence on the importance of economic freedom. I hope decision makers at the state level are reading Ruger and Sorens’s new study.