The Concept

The approach of the Benchmarking Framework and Key Performance Indicators presented in this Report is intended to be normative and primarily aimed at stimulating discussion on policy priorities, actions that could be taken by the private sector (alone or in concert with government), and further research endeavors. As outlined above, there is widespread agreement that the growth process must yield inclusive outcomes, and research on the factors that determine such outcomes is still going on and remains at a formative stage. Many determinants are thought to influence growth outcomes and the way in which they are distributed. The selection  of the pillars therefore represents a key assumption of the Framework. It is based on available research and best judgment based on historical experience. However, these domains have not yet been empirically proven to have a direct, causal link to increased growth or social equity, either individually or collectively.  

For practical reasons, the Policy and Institutional Indicator (PII) Framework separates the policy domains into seven distinct pillars, though the policy areas are interdependent and interconnected. They tend to reinforce each other, and a weakness in one area often has a negative impact on others. No single determinant can ensure inclusive growth, which  can only be achieved through a combination of factors.  For example, employment can only contribute to equitable growth if education is widely accessible and transmits skills  of relevance to the labor market. Private-sector investment will be higher and more efficient if government and business activity is transparent and ethical. Likewise, education is also linked to health outcomes – in advanced economies, those with the highest education can expect to live six years longer than their poorly educated peers. 

The appropriate mix of policies and institutions will depend on country circumstances and preferences. The Framework  does not intend to suggest that there is an ideal policy or institutional mix for the pursuit of inclusive growth and  development that will apply to all countries. For the same reason, the Benchmarking Framework and the Inclusive  Development Index do not assign different weights to the  pillars and sub-pillars. Given the data limitations, the  complexity of the topic, and the need for further research,  the individual indicators should be interpreted as simple  proxies for prevailing conditions and the extent to which countries are fully using their policy space. A weak or strong score in a specific domain relative to its peer group should thus be seen as a marker or signpost of where a country might explore policy changes or other actions.

It is important to note that in a number of instances, data had to be adjusted to take into account both equity and growth considerations. Although equity remains a principal focus when assigning rank direction, a cut-off has been applied  at the point where these policies might dampen growth. These trade-offs are visible in the case of labor market and tax-related indicators, where a higher degree of protection  or higher taxes can support social inclusion but also dampen growth. For example, a higher degree of collective bargaining supports redistribution of income toward employment, but it limits the ability of businesses to adjust wages to their needs. Along similar lines, while trade unions are key for protecting workers’ rights, a very high degree of unionization can  create constraints on decisions critical for a company’s future economic viability. For the same conceptual reasons, some tax data were adjusted. Other adjustments were undertaken if the relationship between the indicator and inclusive growth is not linear. For example, paid maternity leave is beneficial to female inclusion until it begins to adversely affect wages and (re)integration into the labor market. Similarly, financial market indicators, such as domestic credit to the private sector or share turnover, can indicate instabilities in financial markets once a certain level is reached, as was so poignantly demonstrated during the financial crisis of the last decade. Specific adjustments were based upon available literature and the authors’ interpretation of the data.

Data and Aggregation Methods 

The Benchmarking Framework includes two types of data. The first category is quantitative data collected from leading international organizations and other respected sources.  The second category of data is derived from the World Economic Forum’s Executive Opinion Survey, which assesses the perspectives of more than 14,000 business leaders about their countries’ business and political environment (between February and June 2016). The questions from the survey are on a 1-to-7 scale, with 1 representing the worst case, and  7 the best. 

If quantitative data presents outliers, data thresholds are introduced to reduce the bias in the distribution of the data. The same thresholds are applied across the full sample of countries where data is available to allow for some degree of comparability (at indicator level and across some sub-pillars).

The computation is based on successive aggregations of scores from the indicator level to the sub-pillar and pillar level. Unless noted otherwise, an arithmetic mean is used to  aggregate individual indicators within a category. For  quantitative data, to make aggregation possible, indicators are converted to a 1-to-7 scale (worst to best) in order to  align them with the Survey results. A linear min-max  transformation is applied, which preserves the order of, and the relative distance between, country scores. 

a. Formally, for a category [i]i[i] composed of [i]K[i] indicators, there is:

b. Formally, the equation is:

The [i]sample minimum[i] and [i]sample maximum[i] are, respectively, the lowest and highest country scores in the sample of economies covered by the benchmarking tool. In some instances, adjustments were made to account for extreme outliers. For those indicators for which a higher value indicates a worse outcome, the transformation formula takes the following form, thus ensuring that 1 and 7 still correspond to the worst and best possible outcomes, respectively:

Data Presentation 

In order to facilitate peer-group comparisons for countries, the results are grouped into the four broad categories of countries based on a combination of the World Economic Forum’s Global Competitiveness Index methodology and the World Bank’s income classifications that were available at the time the last Report was drafted: advanced, upper-middle, lower-middle and low income.¹ This classification also reflects somewhat different available data sets and policy challenges for each group. The income thresholds presented in the table below are based on GDP per capita in current US dollars. 

Results are displayed by pillar as well as by country (scorecards). The former is intended to enable the reader to benchmark a given score against a peer group of countries in a given policy domain and across other policy domains. The latter is intended to provide a comprehensive picture of a country’s performance and enabling environment conditions across the full spectrum of policy domains covered by the Benchmarking Framework. In addition to numerical values, a five-color system of color shading is applied to ease interpretation of the data and comparisons across countries and indicators, with darkest green representing the best performance in a pillar, shades of yellow standing for average performance, and deepest red displaying the poorest performance. The same color palette has been used for the icons on the country  profiles showing the individual country performances as well as in the aggregated pillar result tables for each income group. This allows both an internal comparison for individual countries (by showing in which pillars they perform more or less well) as well as a cross-country comparison (how the countries compare to their peers in the various pillars and sub-pillars).

It is important to note that in order to facilitate the comparison of countries with their peers – those with similar resources at their disposal – the color palette has been based on results by income group. Thus, caution must be taken in comparing color results across income groups, as they are not directly comparable. Specifically, the range of colors shown for advanced, upper-middle and lower middle income economies are each based on the results of the specific income group and only comparable to the countries within their group. For the low-income countries, a single color calibration has been performed based on the range in scores of the lower-middle income countries. This has been done to highlight the still significant room for improvement even for the best performers within the low income group.² 

Country Coverage

The Report covers 109 countries representing all regions. Country coverage has mainly been driven by data availability – all but 12 countries have full coverage on all pillars, and no countries have more than a third of missing data in a given  pillar. Likewise, all but 2 countries have sufficient data to calculate the IDI scores for the most recent year and 6 countries are missing IDI scores in 2011 (used to calculate 5-year trends). In most cases, missing values do not exceed 25%. If the overall results of more than two pillars could not be properly calculated, the country has not been included. The Forum will strive to expand coverage as more comparable data becomes available, especially for low income countries. For this reason, for some variables two distinct data sets have been used (one for advanced and upper-middle income economies and another for lower-middle income and low income economies) in order to capture a wide array of concepts and to use the best data available for a large range of countries. For example, for advanced and upper-middle income countries, data from the OECD’s PISA assessment has been included, while for lower-middle income and low income countries UNESCO’s WIDE Database on Educational Inequality has been used due to the lack of comparable data by income quintile across the whole sample. This is also the case for a few other indicators that are available for higher income economies but not available for some of the other country groupings. As a result, pillar level scores are not strictly comparable between income groups. The table below indicates the specific variables that are available only for certain income groups. 

Strengthening the World Economic Forum’s Framework for Inclusive Growth

Some key concepts that are important for inclusive growth could not be captured due to gaps in available data – for example, discrimination against the disabled, migrants, and ethnic minorities. Data is especially scarce for low income countries and capturing the distribution of outcomes by income groups. Going forward, in order to make progress in this area, countries and international organizations will need to regularly collect better data in these critical areas especially through the use of household surveys. It is very hard to fix what you cannot measure. 

It bears mention that measures of social mobility and real economy investment, or productive uses of capital, are a relatively underexplored area with important implications for inclusive growth. For this pillar, comparable data for a large number of countries is limited, necessitating the use of  several different variables or proxies in order to capture this complex concept. For example, it is difficult to capture net  equity issuance (taking into account share buybacks) in a  single measure due to poor country coverage; these  indicators could not be combined and have been presented separately in this Report. Likewise, private investment in infrastructure data is only available for developing countries as data for many advanced economies also includes public investment. The Forum’s goal is to provide a more complete breakdown of this concept in the next Report. 

This Report should be seen as marking the start of an  ongoing process. Empirical research on the topic of inclusive growth is still emerging. As it evolves, the Forum intends to use it to explore the relationships and relative importance of the different pillars. A ‘Build Your Own Index’ tool is also  available online, which features alternative weightings of the IDI sub-components (with the default reflecting equal  weightings). It intends to stimulate discussion around different ways of measuring and tracking progress. Work will also be done to incorporate new countries and indicators into the analysis and to test the robustness of the Framework. This work on further refining and upgrading the methodology will inform the next edition of the Report. 

Description of Framework Pillars (PII)

This section describes the types of indicators contained in each pillar and their importance for delivering inclusive outcomes from growth. A full description of indicators and sources can be found in the Technical Notes and Sources section. 

Labor is the primary, and in most cases, exclusive, source of income for citizens of rich and poor countries alike. Strong and rising labor productivity across different sectors and geographies is therefore an important cornerstone of any strategy to strengthen broad-based progress in living  standards and reduce social marginalization. This is all the more important in the presence of rapid technological change that is automating, dis-intermediating, and enabling remote performance of many functions. Such change both disrupts existing jobs and creates new opportunities for labor income at every stage of economic development, in both cases  favoring workers who are able to acquire and adapt skills.  The challenge to societies is to create an enabling environment for widespread access to, and steady improvement in, skills acquisition.  

As such, the Framework includes indicators that gauge the breadth of enrollment in early, basic, vocational, and tertiary education as well as the availability of training services  (Access Sub-pillar). It includes measures of educational system quality such as the proficiency of secondary students, pupil-teacher ratio, internet access, public expenditure levels, and employer perceptions (Quality Sub-pillar). It also  incorporates information on preprimary, primary, and secondary completion rates, basic reading and math proficiency by quintile of parental income, as well as other measures of the equity of educational opportunity in a society, reflecting a view that education is the main vehicle for disrupting the  transmission of inequality in life chances from one generation to the next (Equity Sub-pillar).

The common availability of basic services and infrastructure underpins equality of economic opportunity. For example, a well-developed transport infrastructure network is a prerequisite for less-developed communities to access core economic activities and services. Investment in the provision of health services, clean water, and sanitation is critical economically as well as morally. A healthy workforce is vital to a country’s competitiveness, productivity, and inclusivity, as workers who are ill cannot function to their full potential. Exclusion from physical networks (water, power, telecommunications, transportation, logistics, solid waste disposal, etc.) constrains productivity and keeps people poor. Markets often do not naturally extend these networks to encompass the entire population, as it may not be cost-effective to connect poor people because the fixed costs cannot be recouped. The Basic and Digital Infrastructure Sub-pillar includes indicators that gauge the quality of overall infrastructure and domestic transport network, transport infrastructure investment as a proportion of GDP, overall access to electricity, inequality in access to electricity, proportion of urban population living in slums, pollution, dwellings without basic facilities, and a number of measures of access to and affordability of information and communications technology (ICT). The Health-related Services and Infrastructure Sub-pillar gauges perceptions of the quality and accessibility of healthcare services, extent of out-of-pocket health expenses, access to improved drinking water and sanitation, undernourishment, particulate matter concentration, inequality-adjusted life expectancy and gender-gap health measures like sex ratio at birth and female healthy-life expectancy as compared to male.

Corruption has a chilling effect on personal initiative and entrepreneurship, and hence, on investment, job creation, and purchasing power. Its effects, both direct and indirect, are borne most heavily by ordinary citizens. It is corrosive, even antithetical, to social inclusion and economic growth, as it represents the exploitation of power by the haves against the have-nots. This sub-pillar gauges perceptions of the ethical behavior of firms, efficacy of measures to combat corruption and bribery, diversion of public funds, irregular payments in tax collection, and public trust in politicians (Business and Political Ethics Sub-pillar). Undue concentration of wealth  and market power and high barriers to entry discourage entrepreneurial initiative and the recycling of resources toward uses that have the most potential to contribute to productivity gains. As such, they also suppress economic growth and progress in living standards. This sub-pillar includes indicators measuring perceptions of the extent of market dominance, intensity of local competition, regulatory protection of  incumbents as well as the concentration of land ownership, and banking-sector assets (Concentration of Rents  Sub-pillar).

Access to credit is a key link between economic opportunity and outcomes. By empowering individuals to cultivate  opportunity, financial inclusion can be a powerful agent for inclusive growth. This sub-pillar measures access and  affordability of financial services with particular emphasis on banking for the poorest and most marginalized (the bottom 40%). An account at a formal financial institution generally  reduces the cost of engaging in financial transactions,  provides a ready vehicle for savings and access to funds, and serves as a reference for individuals wishing to obtain credit for small business development. With improved financial access, families can smooth out consumption and increase investment, including in education and health. They can also insure against unfavorable events, and therefore avoid falling deeper into poverty. Indicators are also included on prevalence of accounts used for business purposes, ease of access to credit, and depth of credit information (Financial Inclusion Sub-pillar).

Another important factor that influences employment and wage levels is the extent to which a country’s financial system efficiently intermediates the flow of private savings to  profitable business investment opportunities, as opposed to financial assets or real estate which result in little net new capital formation. Such real economy business investment typically requires a medium- to long-term investment horizon to support investment in infrastructure, equipment, workforce skills, and innovation, which are crucial for firm competitiveness and growth.  Accordingly, this sub-pillar includes indicators illustrating the extent to which the financial system is geared toward non-residential private investment and business capital formation. These include the extent of local equity market access, venture capital availability, domestic credit to firms by banks, private investment in infrastructure, non-residential private investment, private R&D expenditures, share turnover, bank lending to non-financial corporations, IPO issuances for both small- and large-cap firms, follow-on equity issuances, and share buybacks in order to provide an integrated picture of the how well the financial system mobilizes risk capital (Intermediation of Business Investment Sub-pillar).

Small business entrepreneurship and home ownership are typically the first means by which working families accumulate wealth beyond savings from wages and pension contributions. For many, they provide the primary ladder to the middle class and beyond. This pillar includes a range of indicators  assessing the ease of starting and running a business with  respect to regulatory and cultural factors, which is an  important enabler of business and hence employment  creation. These include density of new business registrations and patent applications; attitudes toward entrepreneurial failure; cost of and time required to start a business, resolve insolvency, and enforce a contract; and the time required to prepare and pay taxes (Small Business Sub-pillar). Several additional indicators measure levels of and enabling  environmental conditions relating to home ownership and private savings. These include the perceived strength of  property rights protection, home ownership rate, house  price-to-income ratio, housing loan penetration and, for  advanced countries, employee stock ownership, profit  sharing, and private pension asset accumulation (Home and Financial Asset Ownership Sub-pillar).

This pillar continues the theme that productive employment is central to achieving inclusive growth. It includes indicators measuring the extent of labor force participation (including  for women) and unemployment (including for youth);  underemployment and vulnerable, temporary, and informal sector employment; employer perceptions of the ease of retaining skilled employees; measures of social mobility; and strictness of employment protection. Other indicators capture the quality of working conditions through indicators like  excessive working hours (Employment Sub-pillar). 

Pillar 6 also measures enabling environment factors that can influence the pace and distribution of wage and non-wage labor compensation (Wage and Non-wage Labor Compensation Sub-pillar). For example, it includes indicators measuring wage dispersion (ratio of median to minimum wages), low pay (below two-thirds of the median), trade union density, collective bargaining coverage, cooperation in labor-employer relations, gender pay gap, and violations of worker’s rights. Finally, it incorporates measures of key aspects of non-wage compensation such as child care costs and maternal and parental leave.

A nation’s fiscal policy – the way governments collect and spend public resources – can play a major role in reducing poverty and inequality. Taxation is an important source of revenue to fund social protection programs and provides a means of directly redressing market inequalities. However, taxes must be designed well to minimize loopholes and ensure progressivity (that they are levied more strongly on those best able to afford them) without dampening incentives to work, save, and invest. This sub-pillar includes indicators measuring total tax revenue, total tax wedge as a percentage of labor costs, the incidence of taxes on capital, property, inheritance, and consumption, as well as the overall  progressivity of the tax system and perceptions of its impact on incentives to work and invest (Tax Code Sub-pillar).  

Social safety nets of various sorts can help societies mitigate the effects of external and transitory livelihood shocks as well as to meet the minimum needs of the chronically poor so that they too can participate in and benefit from growth. These include policies and programs to reduce the risks of  unemployment, underemployment, or low wages resulting from inappropriate skills or poorly functioning labor markets. Other social insurance programs are designed to cushion risks associated with ill health, disability, work-related injuries, and old age. Social assistance and welfare schemes such as cash or in-kind transfers are intended for the most vulnerable groups that have no other means of adequate support. 

This sub-pillar includes indicators that comparatively assess: the total social expenditures as a proportion of GDP;  coverage, adequacy and progressivity of public pensions; coverage and adequacy of unemployment benefits;  coverage of disability and health benefits; perceived  effectiveness of government in reducing poverty and inequality; perceived wastefulness of government spending; and  adequacy of social assistance and insurance (Social Protection Sub-pillar).