1.4 Measuring inclusive growth
IG began in leading multilateral financial institutions, like the World Bank and the International Monetary Fund. As such, it has always been led by a practical agenda of how to develop policy interventions that will drive more participatory economies. Before one can consider how to devise these purposive actions, it is important to be able to analyse and measure the process of growth. Here, you will look at some examples of frameworks that have been developed for this aim.
In the first few years following the emergence of the IG agenda, there appeared to be little attempt to systematically or empirically bound IG. Ranieri and Ramos (2013) stated that ‘the few existing analyses mirror the conceptual debate’, lacking cohesion and clarity behind the framing. The landscape has since changed dramatically, and there are as many analytical frameworks as there are organisations working on the topic.
Activity 1.5: Comparing IG frameworks and indicators
Two of the most prominent frameworks have been developed by the OECD and the African Development Bank (Table 1.2). Look at both of them, and then note down any similarities and differences.
| OECD category/indicator | AfDB dimension/indicator |
|---|---|
|
|
| Similarities | Differences |
Discussion
The conceptualisation of the high-level component dimensions might be couched in very different language:
- AfDB uses broad categorisations such as ‘social’ and ‘environmental’.
- OECD uses ‘firms, people and places’.
The logics sitting behind them, once you delve into the disaggregated indicator sets, are not dissimilar. Although a plethora of these analytical tools exist, there are some surprisingly similar trends across them. For example:
- Analyses tend to take a national-level perspective in assessing how far a particular country has achieved some measure of IG.
- Within the nationally centred framework, there are few attempts to apply IG to particular economic sectors or social groups.
- Dependence on composite indicators and sets as the way to measure and track IG. What is interesting to note is that while the ‘pillared’ categorisation in the OECD framework is a favoured organising principle, there are few attempts to triangulate between indicators within the same, or across different, sets.
A reliance on macro-economic datasets that are often incomplete or unreliable. Few studies on IG use mixed methods and qualitative data. One issue of using secondary datasets is that it means any causality between different factors of growth can only be inferred. This is problematic when trying to unpack complex economies and, particularly, when it comes to non-income-related outcomes.
The indicator framework that MIAG created ended up containing 37 different indicators – too many too list here – and was developed with those wider trends in mind, as the team did an extensive review of existing models.
The OECD framework was chosen as as a good basis, structurally, to build around the same four categories. This is because Category 1 (growth and ensuring equitable sharing of benefits from growth) included a detailed set of composite economic growth factors, but Categories 2, 3 and 4 spoke much more broadly to the social and policitical dimensions of IG that MIAG wanted to thoroughly explore. The team removed one or two of the OECD’s indicators that were not relevant to the project’s focus on SMEs, but largely kept the set as it was.
The additional indicators incorporated measures that the team could use to assess the influence and impact of migration on growth. Indicators looking at remittance flows were introduced to Category 1, and levels of corruption and political stability were added to governance as factors that may affect attracting and operating migrant business, for instance.
One of the main disadvantages of secondary quantitative data in these IG frameworks is the limitation of being able to make causal connections across indicators, as mentioned above. To get around this, MIAG used two other data collection methods, surveying and semi-structured interviews, which you will learn more about in the coming weeks.
1.3 Why does growth need to be more inclusive?