III. Analyzing Country Results
Based on the empirical and benchmarking work of the Forum and its partners, over 140 quantitative indicators have been assembled to provide an illustration of enabling environment conditions and performance across 112 countries within each of the policy and institutional domains. These comparative profiles of institutional strength and use of policy space are intended to help spotlight and prioritize opportunities for improvement within countries and enable transfer of knowledge about best practices among them. By bringing a fuller spectrum of such opportunities into sharper relief on a country-by-country basis, the aim is to enable a more concrete and productive conversation within societies about how to achieve greater social inclusion along with stronger and more resilient growth.
Data are displayed within peer groups of countries at similar levels of development as defined by income. These four comparator groups of countries are: advanced, upper-middle income, lower-middle income and low-income. The first and last categories are based on IMF and World Bank classifications, respectively; and the threshold between upper- and lower-middle income countries is the same $6,000 per capita (GDP per capita) level utilized in the World Economic Forum’s Global Competitiveness Report.35 The categories also reflect differences in data sources – such as OECD and World Bank indicators – which limit comparisons between the advanced economies and those from developing regions.
Separate tables for each of the four groups of countries compare the pillar and sub-pillar scores of each country via a traffic-light shading scheme that ranks countries relative to their group. Red corresponds to the lowest relative performance within the group, yellow to the median, and dark green to the best performance.
Since this color scheme ranks countries only within each comparator group, colors are not comparable across income groups. However, the absolute numerical score values (on a scale of 1 to 7) that are displayed in each data field are largely comparable across the entire sample of 112 countries.36 When countries are missing data, this is indicated by white shading and a numerical value of N/A. If data is missing for more than 30% of indicators, the sub-pillar score is also left blank (see appendix for a full description of the methodology).
In addition to the cross-country sub-pillar tables presented in this Report, the online version includes full individual country profiles. These list the score for every indicator within every sub-pillar for each country covered by the Report. Readers should consult their country’s complete Inclusive Growth and Development Country Profile at http://wef.ch/igd15.
This Framework does not in any way suggest that there is a single, ideal policy or institutional mix for the pursuit of inclusive growth and development. The Forum’s view is very much to the contrary and it is for this reason that, in contrast to the Forum’s other benchmarking studies, an overall aggregate ranking or league table of countries has not been computed.
For the same reason, the Framework does not at this time assign different weights to the pillars, sub-pillars and indicators. This reflects the belief that no single pillar or individual factor is dispositive of inclusive growth and development. Rather, the indicators are taken to be simple proxies for prevailing conditions and the extent to which countries are using the available policy space. As such, scores at the pillar level should be interpreted merely as markers or signposts for where further investigation of the country’s policy or institutional framework might be warranted by virtue of a weak or strong score in that specific domain relative to its peer group. The underlying assumption is that different approaches and policy mixes will be appropriate to different countries depending on their historical, cultural, and political-economy circumstances. However, it warrants emphasis that what countries often do have in common is an unexploited opportunity to think more systematically about the full range of instruments and approaches available to address the problem.
Six significant findings emerge from an overview of the data:
1. All countries have room for improvement. There is considerable diversity in performance not only across but also within countries. No country is a top performer (appearing dark green) in every sub-pillar. Indeed, not a single country scores above average in all 15 sub-pillars. Only a handful come close: Australia, Canada, Finland, Norway, and Switzerland among advanced countries; and Hungary, Malaysia, and Mauritius among upper-middle income countries.
2. There is no inherent trade-off in economic policy-making between the promotion of social inclusion and that of economic growth and competitiveness; it is possible to be pro-equity and pro-growth at the same time. Several of the strongest performers in the Forum’s Global Competitiveness Index (GCI) also have a relatively strong inclusive growth and development profile. This is significant because, while there is some overlap in concepts, notably in the areas of education, infrastructure, and corruption, the two exercises examine different aspects of the economic enabling environment. For example, on education the GCI includes indicators measuring access and quality, while this database also includes measures of equity of outcomes; on labor markets, the GCI includes indicators on flexibility, while this exercise adds parameters relating to such matters as worker protection, working conditions, wages, and non-wage compensation.
3. Larger fiscal transfers are not necessarily incompatible with growth and competitiveness, but neither are they always the primary or most effective available option for broadening socioeconomic inclusion.34 Many of the world’s most competitive economies have high levels of social protection and the significant tax burdens these imply (e.g. the flexi-security model of Nordic economies). However, what is even more striking is the diverse experience in the use and impact of redistributive transfers depending upon the extent to which policy space in other areas is being exploited.
A closer look at Gini coefficients for inequality in both market income (pre-taxes and transfers) and net income (after taxes and transfers) is revealing in this respect. Figures 3 and 4 illustrate the importance of redistribution as a policy lever. However, they also reveal that social inequality (as measured by the Gini after taxes and transfers) is influenced just as much by the level of inequality prevailing before fiscal transfers as by the size of such transfers. Some countries start from a relatively high level of inequality from market activity but compensate through aggressive use of fiscal transfers to achieve a moderate level of inequality (for example Ireland, Hungary, Poland, Latvia, and the Nordics). Others achieve moderate or low Ginis mainly because their pre-transfer level of inequality is comparatively modest to begin with rather than due to the significance of their transfers (e.g. Republic of Korea, Japan, Switzerland, Ukraine and, to a lesser extent, Slovak Republic, and Slovenia). Even within the Nordic countries there is considerable variation. Countries like Sweden and Denmark redistribute more than Finland and Norway, which redistribute more than Iceland, indicating there are many different ways of achieving inclusive growth. (See Figure 3)
4. Policies and institutions supporting social inclusion are not solely a luxury of high-income countries. While the absolute scores within some sub-pillars are correlated with income (particularly those for Social Protection, Wage and Non-Wage Compensation, Heath Services and Infrastructure, and Home and Financial Asset Ownership), many are not. There is extensive overlap in absolute scores across at least three of the four income groups of countries in the sub-pillars of Business and Political Ethics, Tax Code, Financial System Inclusion, Intermediation of Business Investment, Productive Employment, Concentration of Rents, and Educational Quality and Equity. Even in sub-pillars in which absolute scores are correlated with income across the four peer groups, there are typically significant variations in scores within peer groups, and the income ranges within these groups are very large indeed. The wealthiest countries in each peer group typically enjoy levels of GDP per capita three or four times above those of the poorest members of the group.
This suggests there is much that countries at all levels of economic development can do to improve their inclusive growth and development model. There is also much they can learn from each other, including from those outside their peer group, whether at higher or lower levels of overall economic development.
5. There are, however, significant regional or cultural similarities. Regional clustering of relatively weak sub-pillar scores includes Eastern European countries on Tax Systems, East Asian countries on Social Protection, and Latin American countries on Educational Equity. Regional clustering of relatively strong scores includes Eastern Europe on Education and Skills, and Northern European countries on Employment and Compensation as well as Education and Skills. This suggests that there are shared historical traditions and political-economy reflexes that are more deeply rooted than the particular acts or omissions of policy in these individual countries. These merit further investigation.
6. Seen from a practical, evidence-based perspective, the current debate on inequality and social inclusion is unduly narrow and unnecessarily polemicized. It is possible, indeed essential, to be pro-labor and pro-business, to advocate a strengthening of both social inclusion and the efficiency of markets. The inequality debate focuses almost exclusively on up-skilling of labor and redistribution – when it moves beyond problem identification. For many countries, these may be among the most appropriate responses to widening dispersion of incomes, but they represent only a minority of the policy options available. To focus only on them is to miss the fuller opportunity to adapt or “structurally adjust” one’s economy to the challenge of strengthening the contribution of economic growth to broad-based progress in living standards, in the face of forces such as technological change and global economic integration that can pull in the opposite direction.
Some other actionable options are not traditionally thought of as equity-enhancing because they concern strengthening of the enabling environment for business entrepreneurship and investment. But these can be just as critical to a country’s success in advancing living standards. As further explored in Box 4, digitization will continue to create enormous challenges for employment in manufacturing in many industries and countries. However, it also has the potential to create extensive opportunities for new entrepreneurs and small businesses by reducing barriers to entry and scale, while dis-intermediating and unbundling existing activities performed by larger organizations, including in international trade. As manufacturing productivity improves and societies age, the market for services – many of which are less tradable across borders than goods – will expand, creating further opportunities for employment, small-business ownership, and asset building. While wider markets and lower transaction costs driven by the scaling and leveling effects of technology and integration are increasing the returns to capital and innovation, the creation of a conducive regulatory and financial environment for running and investing in small businesses can help a larger proportion of the working population to capture a larger share of these gains through the profits and equity appreciation that can accompany ownership of a small business.
Similarly, in today’s more internationally competitive and technologically dynamic environment, the effectiveness of business investment is a critical determinant of a country’s ability to support productive industrial employment. Other critical determinants of the number and quality of employment opportunities are the quality and cost of infrastructure and basic services that link goods to markets and equip people for jobs; the cost and patience of capital available for long-term investment in industrial production and productivity improvements; and the extent of deadweight losses to economic efficiency and innovation in the form of corruption and rents. These must be considered just as critical to inclusive growth as efforts to improve skills or fiscal transfers.
In this sense, an inclusive growth and development model is one that is inherently pro-labor and pro-business. Political myths and polemics to the contrary serve only to distract attention from the practical work of governments to assess their strengths and weaknesses and then marshal the imagination and coalitions necessary to construct a coherent and durable national strategy – all based on an understanding that wide-spectrum economic institution building is just as important for the promotion of broad-based progress in living standards as the maintenance of sound macroeconomic policy and competitive product, labor, and capital markets is for expanding GDP.
Box 6: Use of Policy Space: Market Levers versus Fiscal Transfers
Figure 4 aggregates the results of pillars 1 – 6 to illustrate the relative emphasis laid by countries on market policy and institutional levers, and plots this score against pillar 7, which measures the extent of countries’ use of fiscal transfers. Countries appearing in the upper right quadrant are making the greatest use of both sets of policy and institutional levers, whereas countries appearing in the bottom left quadrant are making the least use of either strategy (implying that they have the most unexploited policy space relative to the experience of their peers, which is to say that their economies have the weakest inclusive growth and development institutional profile in their peer group). Countries in the upper left quadrant are making comparatively good use of fiscal transfers but have significant unexploited policy space relative to the experience of their peers in the areas affecting pre-transfer inequality. The opposite is the case for countries appearing in the bottom right quadrant.
Advanced Economies make the most use of the two different sets of policy levers, but even top performers have room for improvement – no country comes close to the maximum (score of 7) in either of these areas. Countries that have the most conducive enabling environment across market-related and fiscal-transfer institutions include Norway, New Zealand, Switzerland, Denmark, Canada, and the UK. Countries lagging the most in this group include Greece, Czech Republic, Italy, Portugal, Spain, and Estonia. Singapore relies most disproportionately on pre-transfer mechanisms to achieve on fiscal transfers.
In the Upper-Middle Income group, Panama, Hungary, Malaysia, and Poland take greatest advantage of both market related institutions and fiscal transfers, whereas Venezuela, Peru, Mexico, Colombia, and Azerbaijan make comparatively limited use of either mechanism. China, Lithuania, and Chile disproportionately emphasize pre-transfer institutions and policy incentives In fact, Bulgaria, China and Peru are the only countries among all 112 whose post-transfer Gini is higher than their pre-transfer Gini, suggesting that their fiscal systems may have a net regressive effect and therefore particularly merit strengthening.1-6 Kazakhstan also makes little use of fiscal transfers evident from the very negligible difference between its pre- and post-transfer Gini coefficients (less than 1 point change). South Africa, by contrast, makes relatively expansive use of fiscal transfers in relation to its use of policy and institutional levers supporting more equal market outcomes.
Lower-Middle Income countries fall just slightly behind upper-middle income countries in their overall performance in these two domains, with Macedonia, Mongolia, Ukraine, Thailand, Georgia, and Armenia taking the greatest advantage of both areas of policy space, and India, Pakistan, and Senegal taking the least. India’s use and targeting of fiscal transfers in particular could merit strengthening as evident from the very negligible difference between their pre- and post-transfer Gini coefficients. Lesotho relies most disproportionately on institutions acting through the market, whereas Sri Lanka relies most disproportionately on fiscal transfers.
Low-Income countries struggle the most overall to provide institutional support for social inclusion. Yet, given the limited resources at their disposal, countries like Rwanda and Kenya manage to make good use of a mixture of tools, while Chad, Burundi, and Burkina Faso have the weakest institutions across the two dimensions. Madagascar relies most disproportionately on pre-transfer institutions, whereas Tanzania relies more heavily on transfers than other countries in its group.
An important caveat regarding fiscal transfers: efficiency of spending is also important. More transfers are not necessarily better, if resources are not targeted and channeled efficiently to where they are most needed. With progressive taxation and targeted programs, countries like Australia and New Zealand show it is possible to achieve more with less. Clarifying the relationship between fiscal transfers (taxation and social protection) and market-based policy levers represents an important area for future research.
effort has been made to use the same indicators across all groups or the best available proxy. See methodology section of the appendix.