This component considers the level of government expenditures as a percentage of GDP. Government expenditures, including consumption and transfers, account for the entire score.

No attempt has been made to identify an optimal level of government expenditures. The ideal level will vary from country to country, depending on factors ranging from culture to geography to level of development. However, volumes of research have shown that excessive government spending that causes chronic budget deficits and the accumulation of sovereign debt is one of the most serious drags on economic dynamism.

The methodology treats zero government spending as the benchmark, and underdeveloped countries with little government capacity may receive artificially high scores as a result. However, such governments, which can provide few if any public goods, are likely to receive lower scores on some of the other components of economic freedom (such as property rights, financial freedom, and investment freedom) that reflect government effectiveness.

The scale for scoring government spending is non-linear, which means that government spending that is close to zero is lightly penalized, while levels of government spending that exceed 30 percent of GDP lead to much worse scores in a quadratic fashion (for example, doubling spending yields four times less freedom). Only extraordinarily large levels of government spending—for example, over 58 percent of GDP—receive a score of zero.

The expenditure equation used is:

GE_i = 100 – α (Expenditures_i)²

where GE_i represents the government expenditure score in country i; Expenditures_i represents the total amount of government spending at all levels as a portion of GDP (between 0 and 100); and α is a coefficient to control for variation among scores (set at 0.03). The minimum component score is zero.

In most cases, general government expenditure data include all levels of government such as federal, state, and local. In cases where general government spending data are not available, data on central government expenditures are used instead.

Business Freedom

• Starting a business—procedures (number);
• Starting a business—time (days);
• Starting a business—cost (% of income per capita);
• Starting a business—minimum capital (% of income per capita);
• Obtaining a license—procedures (number);
  
• Obtaining a license—time (days);
• Obtaining a license—cost (% of income per capita);
• Closing a business—time (years);
• Closing a business—cost (% of estate); and
• Closing a business—recovery rate (cents on the dollar).
  

Each of these raw factors is converted to a scale of 0 to 100, after which the average of the converted values is computed. The result represents the country’s business freedom score. For example, even if a country requires the highest number of procedures for starting a business, which yields a score of zero in that factor, it could still receive a score as high as 90 based on scores in the other nine factors. Canada, for instance, receives scores of 100 in nine of these 10 factors, but the 14 licensing procedures required by the government equate to a score of 64.5 for that factor.

Each factor is converted to a scale of 0 to 100 using the following equation:

Factor Score_i = 50 factor_average/factor_i

which is based on the ratio of the country data for each factor relative to the world average, multiplied by 50. For example, on average worldwide, it takes 18 procedures to get necessary licenses. Canada’s 14 licensing procedures are a factor value better than the average, resulting in a ratio of 1.29. That ratio multiplied by 50 equals the final factor score of 64.5.

For the six countries that are not covered by the World Bank’s Doing Business report, business freedom is scored by analyzing business regulations based on qualitative information from reliable and internationally recognized sources.

Monetary Freedom

The score for the monetary freedom component is based on two factors:

• The weighted average inflation rate for the most recent three years and
• Price controls.

The weighted average inflation rate for the most recent three years serves as the primary input into an equation that generates the base score for monetary freedom. The extent of price controls is then assessed as a penalty of up to 20 points subtracted from the base score. The two equations used to convert inflation rates into the monetary freedom score are:

Weighted Avg. Inflation_i = θ₁ Inflation_it + θ₂Inflation_it–1 + θ₃ Inflation_it–2

Monetary Freedom_i = 100 – α √Weighted Avg. Inflation_i – PC penalty_i

where θ₁ through θ₃ (thetas 1–3) represent three numbers that sum to 1 and are exponentially smaller in sequence (in this case, values of 0.665, 0.245, and 0.090, respectively); Inflation_it is the absolute value of the annual inflation rate in country i during year t as measured by the consumer price index; α represents a coefficient that stabilizes the variance of scores; and the price control (PC) penalty is an assigned value of 0–20 points based on the extent of price controls.

The convex (square root) functional form was chosen to create separation among countries with low inflation rates. A concave functional form would essentially treat all hyperinflations as equally bad, whether they were 100 percent price increases annually or 100,000 percent, whereas the square root provides much more gradation. The α coefficient is set to equal 6.333, which converts a 10 percent inflation rate into a freedom score of 80.0 and a 2 percent inflation rate into a score of 91.0.

Trade Freedom

Trade freedom is a composite measure of the absence of tariff and non-tariff barriers that affect imports and exports of goods and services. The trade freedom score is based on two inputs:

• The trade-weighted average tariff rate and
• Non-tariff barriers (NTBs).

Different imports entering a country can, and often do, face different tariffs. The weighted average tariff uses weights for each tariff based on the share of imports for each good. Weighted average tariffs are a purely quantitative measure and account for the basic calculation of the score using the following equation:

Trade Freedom_i = (((Tariff_max–Tariff_i )/(Tariff_max–Tariff_min )) * 100) – NTB_i

where Trade Freedom_i represents the trade freedom in country i; Tariff_max and Tariff_min represent the upper and lower bounds for tariff rates (%); and Tariff_i represents the weighted average tariff rate (%) in country i. The minimum tariff is naturally zero percent, and the upper bound was set as 50 percent. An NTB penalty is then subtracted from the base score. The penalty of 5, 10, 15, or 20 points is assigned according to the following scale:

• 20—NTBs are used extensively across many goods and services and/or act to effectively impede a significant amount of international trade.
• 15—NTBs are widespread across many goods and services and/or act to impede a majority of potential international trade.
• 10—NTBs are used to protect certain goods and services and impede some international trade.
• 5—NTBs are uncommon, protecting few goods and services, and/or have very limited impact on international trade.
• 0—NTBs are not used to limit international trade.

We determine the extent of NTBs in a country’s trade policy regime using both qualitative and quantitative information. Restrictive rules that hinder trade vary widely, and their overlapping and shifting nature makes their complexity difficult to gauge. The categories of NTBs considered in our penalty include:

• Quantity restrictions—import quotas; export limitations; voluntary export restraints; import–export embargoes and bans; countertrade, etc.
• Price restrictions—antidumping duties; countervailing duties; border tax adjustments; variable levies/tariff rate quotas.
• Regulatory restrictions—licensing; domestic content and mixing requirements; sanitary and phytosanitary standards (SPSs); safety and industrial standards regulations; packaging, labeling, and trademark regulations; advertising and media regulations.
• Investment restrictions—exchange and other financial controls.
• Customs restrictions—advance deposit requirements; customs valuation procedures; customs classification procedures; customs clearance procedures.
• Direct government intervention—subsidies and other aid; government industrial policy and regional development measures; government-financed research and other technology policies; national taxes and social insurance; competition policies; immigration policies; government procurement policies; state trading, government monopolies, and exclusive franchises.

As an example, Botswana received a trade freedom score of 79.7. By itself, Botswana’s weighted average tariff of 5.2 percent would have yielded a score of 89.7, but the existence of NTBs in Botswana reduced the score by 10 points.

Gathering tariff statistics to make a consistent cross-country comparison is a challenging task. Unlike data on inflation, for instance, countries do not report their weighted average tariff rate or simple average tariff rate every year; in some cases, the most recent year for which a country reported its tariff data could be as far back as 2002. To preserve consistency in grading the trade policy component, the Index uses the most recently reported weighted average tariff rate for a country from our primary source. If another reliable source reports more updated information on the country’s tariff rate, this fact is noted, and the grading of this component may be reviewed if there is strong evidence that the most recently reported weighted average tariff rate is outdated.

The World Bank publishes the most comprehensive and consistent information on weighted average applied tariff rates. When the weighted average applied tariff rate is not available, the Index uses the country’s average applied tariff rate; and when the country’s average applied tariff rate is not available, the weighted average or the simple average of most favored nation (MFN) tariff rates is used. In the very few cases where data on duties and customs revenues are not available, data on international trade taxes or an estimated effective tariff rate are used instead. In all cases, an effort is made to clarify the type of data used and the different sources for those data in the corresponding write-up for the trade policy component.