Approach

Economic Freedom of the World
Economic Freedom of North America

For technical details on variables, see:
https://www.fraserinstitute.org/sites/default/files/uploaded/2022/economic-freedom-of-the-world-2022-appendix.pdf

For technical details on the Gender Disparity Adjustment, see:
https://www.fraserinstitute.org/sites/default/files/womens-economic-rights.pdf

The index measures the degree of economic freedom present in five major areas: [1] Size of Government; [2] Legal System and Security of Property Rights; [3] Sound Money; [4] Freedom to Trade Internationally; [5] Regulation. Comprehensive data are available only with a two-year lag, so the index itself has a two-year lag.

Within the five major areas, there are 26 components in the index. Many of those components are themselves made up of several sub-components. In total, the index comprises 44 distinct variables. All variables come from third party sources, such as the International Country Risk Guide, the Global Competitiveness Report, and the World Bank’s Doing Business project, so that the subjective judgments of the authors do not influence the index. This also creates transparency and allows researchers to replicate the index. The index for past years is updated with each new edition to take account of revisions in the underlying data.

Each component and sub-component is placed on a scale from 0 to 10 that reflects the distribution of the underlying data. When subcomponents are present, the sub-component ratings are averaged to derive the component rating. The component ratings within each area are then averaged to derive ratings for each of the five areas. In turn, the five area ratings are averaged to derive the summary rating for each country. The following section provides an overview of the five major areas.

The Gender Disparity Index (GDI) measures the degree to which women around the world have the same legal rights as men and is used to adjust the EFW index scores to account for any differences in access to economic rights. The Gender Disparity Index includes measures selected from the World Bank’s Women, Business, and the Law report (WB&L) which tracks gender inequality in the legal and regulatory code for 189 countries. The GDI only includes a subset of what is included in the WB&L report, specifically laws and regulations directly related to their economic rights. The Gender Disparity Index includes 42 variables contained in 2018’s Women Business and the Law report, which provides a snapshot of the laws for 2017/2018.

1. Size of Government

A. Government consumption

B. Transfers and subsidies

C. Government enterprises and investment

D. Top marginal tax rate

(i) Top marginal income tax rate

(ii) Top marginal income and payroll tax rate

E. State ownership of assets

The five components of Area 1 indicate the extent to which countries rely on the political process to allocate resources and goods and services. When government spending increases relative to spending by individuals, households, and businesses, government decision-making is substituted for personal choice and economic freedom is reduced. The first two components address this issue. Government consumption as a share of total consumption (1A) and transfers and subsidies as a share of GDP (1B) are indicators of the size of government. When government consumption is a larger share of the total, political choice is substituted for personal choice. Similarly, when governments tax some people in order to provide transfers to others, they reduce the freedom of individuals to keep what they earn.

The third and fifth components (1C and 1E) in this area measures the extent to which countries use private investment and enterprises rather than government investment and firms to direct resources. Governments and state-owned enterprises play by rules that are different from those to which private enterprises are subject. They are not dependent on consumers for their revenue or on investors for capital. They often operate in protected markets. Thus, economic freedom is reduced as government enterprises produce a larger share of total output.

The fourth component (1D) is based on (1Di) the top marginal income tax rate and (1Dii) the top marginal income and payroll tax rate and the income threshold at which these rates begin to apply. These two sub-components are averaged to calculate the top marginal tax rate (1D). High marginal tax rates that apply at relatively low income levels are also indicative of reliance upon government. Such rates deny individuals the fruits of their labor. Thus, countries with high marginal tax rates and low income thresholds are rated lower.

Taken together, the four components of Area 1 measure the degree to which a country relies on personal choice and markets rather than government budgets and political decision-making. Therefore, countries with low levels of government spending as a share of the total, a smaller government enterprise sector, and lower marginal tax rates earn the highest ratings in this area.

2. Legal System and Property Rights

A. Judicial independence

B. Impartial courts

C. Protection of property rights

D. Military interference in rule of law and politics

E. Integrity of the legal system

F. Legal enforcement of contracts

G. Regulatory costs of the sale of real property

H. Reliability of police

I. Business costs of crime

J. Gender Disparity Adjustment

Protection of persons and their rightfully acquired property is a central element of economic freedom and a civil society. Indeed, it is the most important function of government. Area 2 focuses on this issue. The key ingredients of a legal system consistent with economic freedom are rule of law, security of property rights, an independent and unbiased judiciary, and impartial and effective enforcement of the law. The nine components in this area are indicators of how effectively the protective functions of government are performed. These components are from three primary sources.

Security of property rights, protected by the rule of law, provides the foundation for both economic freedom and the efficient operation of markets. Freedom to exchange, for example, is fatally weakened if individuals do not have secure rights to property, including the fruits of their labor. When individuals and businesses lack confidence that contracts will be enforced and the fruits of their productive efforts protected, their incentive to engage in productive activity is eroded. Perhaps more than any other area, this area is essential for the efficient allocation of resources. Countries with major deficiencies in this area are unlikely to prosper regardless of their policies in the other four areas.

3. Sound Money

A. Money growth

B. Standard deviation of inflation

C. Inflation: most recent year

D. Freedom to own foreign currency bank accounts

Money oils the wheels of exchange. An absence of sound money undermines gains from trade. As Milton Friedman informed us long ago, inflation is a monetary phenomenon, caused by too much money chasing too few goods. Similarly, when the rate of inflation increases, it also tends to become more volatile. High and volatile rates of inflation distort relative prices, alter the fundamental terms of long-term contracts, and make it virtually impossible for individuals and businesses to plan sensibly for the future. Sound money is essential to protect property rights and, thus, economic freedom. Inflation erodes the value of property held in monetary instruments. When governments finance their expenditures by creating money, they are, in effect, expropriating the property and violating the economic freedom of their citizens.

The important thing is that individuals have access to sound money: who provides it makes little difference. Thus, in addition to data on a country’s rate of inflation and its government’s monetary policy, it is important to consider how difficult it is to use alternative, more credible, currencies. If bankers can offer saving and checking accounts in other currencies or if citizens can open foreign bank accounts, then access to sound money is increased and economic freedom expanded.

There are four components to the EFW index in Area 3. All of them are objective and relatively easy to obtain and all have been included in the earlier editions of the index. The first three are designed to measure the consistency of monetary policy (or institutions) with long-term price stability. Component 3D is designed to measure the ease with which other currencies can be used via domestic and foreign bank accounts. In order to earn a high rating in this area, a country must follow policies and adopt institutions that lead to low (and stable) rates of inflation and avoid regulations that limit the ability to use alternative currencies.

4. Freedom to Trade Internationally

A. Tariffs

(i) Revenue from trade taxes (% of trade sector)

(ii) Mean tariff rate

(iii) Standard deviation of tariff rates

B. Regulatory trade barriers

(i) Non-tariff trade barriers

(ii) Compliance costs of importing and exporting

C. Black-market exchange rates

D. Controls of the movement of capital and people

(i) Foreign ownership / investment restrictions

(ii) Capital controls

(iii) Freedom of foreigners to visit

In the world of high technology and low costs for communication and transportation, freedom of exchange across national boundaries is a key ingredient of economic freedom. Many goods and services are now either produced abroad or contain resources supplied from abroad. Voluntary exchange is a positive-sum activity: both trading partners gain and the pursuit of the gain provides the motivation for the exchange. Thus, freedom to trade internationally contributes substantially to our modern living standards.

At the urging of protectionist critics and special-interest groups, virtually all countries adopt trade restrictions of various types. Tariffs and quotas are obvious examples of roadblocks that limit international trade. Because they reduce the convertibility of currencies, controls on the exchange rate also hinder international trade. The volume of trade is also reduced if the passage of goods through customs is onerous and time consuming. Sometimes these delays are the result of administrative inefficiency while in other instances they reflect the actions of corrupt officials seeking to extract bribes. In both cases, economic freedom is reduced.

The components in this area are designed to measure a wide variety of restraints that affect international exchange: tariffs, quotas, hidden administrative restraints, and controls on exchange rates and the movement of capital. In order to get a high rating in this area, a country must have low tariffs, easy clearance and efficient administration of customs, a freely convertible currency, and few controls on the movement of physical and human capital.

5. Regulation

A. Credit market regulations

(i) Ownership of banks

(ii) Private sector credit

(iii) Interest rate controls / negative real interest rates

B. Labor market regulations

(i) Hiring regulations and minimum wage

(ii) Hiring and firing regulations

(iii) Centralized collective bargaining

(iv) Hours regulations

(v) Mandated cost of worker dismissal

(vi) Conscription

C. Business regulations

(i) Administrative requirements

(ii) Bureaucracy costs

(iii) Starting a business

(iv) Extra payments / bribes / favoritism

(v) Licensing restrictions

(vi) Cost of tax compliance

When regulations restrict entry into markets and interfere with the freedom to engage in voluntary exchange, they reduce economic freedom. The fifth area of the index focuses on regulatory restraints that limit the freedom of exchange in credit, labor, and product markets. The first component (5A) reflects conditions in the domestic credit market. Sub-component 5Ai provides evidence on the extent to which the banking industry is privately owned. The final two sub-components indicate the extent to which credit is supplied to the private sector and whether controls on interest rates interfere with the market in credit. Countries that use a private banking system to allocate credit to private parties and refrain from controlling interest rates receive higher ratings for this regulatory component.

Many types of labor-market regulation infringe on the economic freedom of employees and employers. Among the more prominent are minimum wages, dismissal regulations, centralized wage setting, extension of union contracts to nonparticipating parties, and conscription. The labor-market component (5B) is designed to measure the extent to which these restraints upon economic freedom are present. In order to earn high marks in the component rating regulation of the labor market, a country must allow market forces to determine wages and establish the conditions of hiring and firing, and refrain from the use of conscription.

Like the regulation of credit and labor markets, the regulation of business activities (component 5C) inhibits economic freedom. The sub-components of 5C are designed to identify the extent to which regulations and bureaucratic procedures restrain entry and reduce competition. In order to score high in this portion of the index, countries must allow markets to determine prices and refrain from regulatory activities that retard entry into business and increase the cost of producing products. They also must refrain from “playing favorites,” that is, from using their power to extract financial payments and reward some businesses at the expense of others.

Construction of Area and Summary ratings

Theory provides some direction regarding elements that should be included in the five areas and the summary index, but it does not indicate what weights should be attached to the components within the areas or among the areas in the construction of the summary index. It would be nice if these factors were independent of each other and the appropriate weight could be attached to each of them. In the past, we investigated several methods of weighting the various components, including principle component analysis and a survey of economists. We invite others to use their own weighting structure if they believe that it is preferable. Our experience indicates that the summary index is not very sensitive to alternative weighting methods.

Furthermore, there is reason to question whether the areas (and components) are independent or work together like the wheels, motor, transmission, driveshaft, and frame of a car. Just as these interconnected parts provide for the mobility of an automobile, it may be the combination of interrelated factors that brings about economic freedom. Which is more important for the mobility of an automobile: the motor, wheels, or transmission? The question cannot be easily answered because the parts work together. If any of these key parts break down, the car is immobile. Institutional quality may be much the same. If any of the key parts are absent, the overall effectiveness is undermined.

As the result of these two considerations, we organize the elements of the index in a manner that seems sensible to us but we make no attempt to weight the components in any special way when deriving either area or summary ratings. The various components and areas of the index are now weighted equally for transparency and simplicity. Of course, the component and sub-component data are available to researchers who would like to consider alternative weighting schemes and we encourage them to do so.

Methodology

Calculating the scores
To avoid subjective judgments, objective methods were used to calculate and weight the components. For all components, each observation was transformed into a number from zero to 10 using the following formula: (V_max − V_i)/(V_max − V_min) × 10, where (unless otherwise stated) V_max is the largest value found within a component, V_min is the smallest, and V_i is the observation to be transformed. The 2005 data were used to derive the maximum and minimum values for each variable. In some cases, there were severe outliers that skewed the scores substantially, so we chose a lower maximum or higher minimum, typically the mean plus or minus between one and four standard deviations (see Appendix B and Economic Freedom of the World, which uses a similar approach). When an observation equals or exceeds the 2005 maximum, it is given a score of 0; when it equals or falls below the 2005 minimum, it is given a score 10. For each component, the calculation was performed for all data for all years to allow comparisons over time.

To transform the individual components into specific areas and the overall summary index, multiple categories were created. In the subnational index, Areas 1, 2, and 3 were equally weighted, and each of the components within each area was equally weighted. For example, the weight for Area 1 was 33.3%. Area 1 has three components, each of which received equal weight in calculating Area 1, or 11.1% in calculating the overall index. The all-government index adds the following:

one additional component to Area 1—1D: Government Investment (the country score for variable 1C in Economic Freedom of the World: 2022 Annual Report [EFW]);
one additional component to Area 2B—2Bii: Top marginal income and payroll tax rate (the country score for variable 1Dii in EFW);
eight additional components to Area 3—
- 3Aiv–ix: the six components of Labor market regulation (variable 5B in EFW),
- 3B: Credit Market Regulations (variable 5A in EFW), and
- 3C: Business Regulations (variable 5C in EFW);
Area 4: Legal System and Property Rights (Area 2 in the EFW);
Area 5: Sound Money (Area 3 in the EFW); and
Area 6: Freedom to Trade Internationally (Area 4 in the EFW).

Thus, it has six areas. Each area was equally weighted and each of the components within each area was equally weighted. More details on the calculations and data sources for the adjusted index can be found in Appendix B.

Fiscal variables
In order to produce comparable tax and spending data for jurisdictions that are of widely different sizes and income levels, all such variables are measured as a percentage of income, as is the minimum wage variable. In Canada and Mexico, we use “household income”. In the United States, the comparable concept is called “personal income”.

Income tax
Calculating the income-tax component was more complicated. The component examining the top marginal income-tax rate and the income threshold at which it applies was transformed into a score from zero to 10 using Matrix 1, Matrix 2a, and Matrix 2b. Canadian nominal thresholds were first converted into constant 2020 Canadian dollars by using the Consumer Price Index and then converted into US dollars using the Purchasing Power Parity between Canada and the United States for each year. US nominal thresholds were converted into real 2020 US dollars using the Consumer Price Index. Mexican nominal thresholds were first converted into constant 2020 Mexican Pesos by using the Indice Nacional de Precios al Consumidor (National Consumer Price Index) and then converted into US dollars using the Purchasing Power Parity between Mexico and the United States for each year. This procedure is based on the transformation system found in Economic Freedom of the World: 1975–1995 (Gwartney, Lawson, and Block, 1996), modified for this study to take into account a different range of top marginal tax rates and income thresholds. Matrix 1 was used in calculating the score for Component 2Bi, Top Marginal Income Tax Rate and the Income Threshold at Which It Applies, at the all-government level; Matrix 2a was used to calculate the score for Component 2B at the subnational level for Canada, and Matrix 2b was used for the United States. Since there are no subnational income taxes in Mexico, this variable was not included in the Mexican subnational index.

In setting the threshold levels for income taxes at the subnational level, we faced an interesting quandary. In the United States, most state thresholds were below US federal thresholds in the 1980s and 1990s. In Canada, provincial thresholds were frequently higher than federal thresholds. Whenever the provincial or state threshold was higher than the federal threshold, the federal threshold was used at the sub-national level since, when a provincial threshold is above the national level, the cause is typically the imposition of a relatively small surcharge on those earning high incomes. Because of the structure of these matrixes, this can produce perverse scoring results. For example, in Matrix 2b a jurisdiction gets a score of 2.5 if it has a top marginal income-tax rate of, say, 12.5% for incomes over $66,260. Let us say the jurisdiction imposes a surcharge for income earners above $132,520, increasing the top marginal income-tax rate to 13%. In Matrix 2b, even though additional taxes in the form of a surcharge have been imposed, the state’s score perversely increases to 3.0 because of the increase in the threshold level.

Our decision to use the federal threshold as the default threshold when the provincial threshold was higher is, frankly, a matter of judgment. Thus, it was important to understand whether this would affect the results significantly. To see whether this was so, we calculated the overall index both ways and found that changes were small and that the overall results were not significantly affected.

Adjustment factors
We faced a common problem in comparing statistics across time, changes in the structure of some series over time. Similarly, some Canadian spending categories were not strictly comparable to those in the United States. This required the use of judgment in some cases. Spending on medical care, for example, is structured as government consumption in Canada and as a set of transfer programs in the United States. Given that the index captures the impact of both government consumption and of transfer programs, we decided the most accurate method of accounting was to reflect the actual nature of the spending, a transfer program in the United States and government consumption in Canada, rather than artificially include one or other in an inappropriate component. The same phenomenon occurs on the revenue side where the entire US Social Security program is funded by a dedicated payroll tax, whereas in Canada part of the similar program, Old Age Security, is funded by general tax revenues. Those revenues are included in variable 2A for US states and in variable 2C for Canadian provinces.

Other adjustments
Our earlier source of government finance data in Canada was discontinued in 2010, with the last year of data being 2009. As a result, in recent years we had used the change in overall aggregates in spending and revenue to produce estimates for the government finance variables in Area 1 and Area 2. The new data series became available in 2015, after the 2015 edition had gone to print. That new data was first incorporated into the 2016 edition. It goes back to 2007. To smooth the transition between the two series, for 2006 we used the average of that new 2007 data and the 2005 data from the previous data series. The two data series are not identical.

There were changes in the way that spending and revenue categories were defined. However, this did not create any major changes in the relative rankings of the provinces.

The fiscal data for the US states comes from the US Census Bureau.
The Tax Foundation calculated the federal tax burden by US state up to the year 2005 using sophisticated techniques but has not issued updates in recent years. As several years of data are missing, we use data on federal tax collections within each state directly from the US Internal Revenue Service.
The historical data for federal spending in the US states comes from the Consolidated Federal Funds Report, which has been discontinued. The last year available is 2010. We used the annual percentage increases in the subnational amounts for the years since 2010 to calculate annual estimates for the federal amounts for both 1A and 1B for those years.
Variable 1C measures insurance and retirement payments as a percentage of income. Because there are several US states where retirees form an abnormally large percentage of the population, using federal spending in each state skews the scores on this variable in a way that does not reflect differences in economic freedom (but rather reflects differences in demographics). In the US states, the US total for this variable, as a percentage of total US income, was used as the federal component for this variable (and simply added to the subnational spending for each state as a percentage of their state income). Since that phenomenon does not exist in Canada and Mexico, this adjustment was not made for the Canadian provinces and Mexican states.
There is a similar issue in the all-government index with regard to Variable 2A, which measures income and payroll taxes. Because states with low corporate income-tax (CIT) burdens tend to attract corporate relocations, those states may tend to have inordinately large revenue from corporate income tax. At the state level, when a corporation has operations in multiple states, taxable corporate income is apportioned based on activity within each state. At the federal level, there are wide disparities in federal CIT revenue collected in the various states (measured as a percentage of personal income) that cannot be driven by differences in state policy. For that reason, we have used the national average in each country for the federal CIT portion of 2A in each state or province.
Variable 2D measures sales and gross receipts taxes. Several Mexican states with large ports have abnormally high values for this variable, in some cases exceeding 100% of personal income. Because that revenue goes to the federal government, we have instead used the same national total for this variable, as a percentage of personal income, for the federal component of this variable for each Mexican state. This adjustment was not necessary for Canada or the United States.