A recent IMF staff discussion note has received a lot of attention for claiming that a smaller income share of the poor lowers economic growth (see also here and here). This piece in the FT is fairly typical, arguing that the paper “establishes a direct link between how income is distributed and national growth.”
It quotes Nicolas Mombrial, head of Oxfam International’s office in Washington DC, saying that (my emphasis): “the IMF proves that making the rich richer does not work for growth, while focusing on the poor and the middle class does” and that “the IMF has shown that `trickle down’ economics is dead; you cannot rely on the spoils of the extremely wealthy to benefit the rest of us.”
The aim of this blog post is to clarify that the results in Table 1 of the paper, which are based on system GMM estimation, rely on assumptions that are not spelled out explicitly and whose validity is therefore very difficult to assess. In not reporting this and other relevant information, the paper’s application of system GMM falls short of current best practices. As a result, without this additional information, I would be wary to update my prior on the effect of inequality on growth based on the new results reported in this paper.
The paper attempts to establish the causal effect of various income quintiles (the share of income accruing to the bottom 20%, the next 20% etc.) on economic growth. It finds that a country will grow faster if the share of income held by the bottom three quintiles increases. In contrast, a higher income share for the richest 20% reduces growth. As you can imagine, establishing such a causal effect is difficult: growth might affect how income is distributed, and numerous other variables (openness to trade, institutions, policy choices…) might affect both growth and the distribution of income. Clearly, this implies that any association found between the income distribution and growth might reflect things other than just the causal effect of the former on the latter.
To try to get around this problem, the authors use a system GMM estimator. This estimator consists of (i) differenced equations where the changes in the variables are instrumented by their lagged levels and (ii) equations in levels where the levels of variables are instrumented by their lagged differences (Bond, 2002, is an excellent introduction). Roughly speaking, the hope is that these lagged levels and differences isolate bits of variation in income share quintiles that are not affected by growth or any of the omitted variables. These bits of variation can then be used to identify the causal effect of the income distribution on growth. The problem with the IMF paper is that it does not tell you exactly which lagged levels and differences it uses as instruments, making it hard for readers to assess how plausible it is that the paper has identified a causal effects.