Climate Change Impact and Structural Reforms in Kiribati
KIRIBATI
6. The regression sample consists of 115 low-income and developing countries, emerging
markets, and advanced economies covering the period 1995 to 2014. The following equation is
estimated:
Yi = B1+ B2iXi + εt
in which y is the GDP per capita growth, Xi captures the aforementioned explanatory variables, and ε+
is the error term. A robust two-step GMM methodology could control for endogeneity issues. The
estimation uses the coefficients from this regression to decompose the differences in average real
GDP per capita growth rates in Kiribati and a benchmark group of countries in the bottom
30 percent of the global income distribution based on data from 2010 through 2018.
7. The results from this exercise help illustrate the potential GDP growth losses from
Kiribati's higher level of legal barriers than those found in the peer group (Figure 2). The figure
shows that Kiribati's relatively higher level of schooling and their overall lower level of gender
inequality are positively associated with GDP growth. However, the level of female legal equity had a
negative impact on the country's growth relative to the peer countries.
Figure 2. Kiribati: Results of Growth Decomposition Model
Bottom 30 Percent of Income
Gender inequality
Initial income (catching up)
Dependent population
Schooling (years)
High inflation
Change in terms of trade
Female legal equity (hypothetical)
Female legal equity
Source: IMF staff calculations.
-0.8
-0.6
-0.4
-0.2
0.0
0.2
0.4
8.
The better-than-average GII in Kiribati however masks a significant heterogeneity
among its sub-components (text chart). A comparison of the sub-components of the Gll that
Kiribati has actual data reveals that Kiribati fares far better than peers in the health indicators, with
both maternal mortality ratio and adolescent birth rate much lower in Kiribati than those of the
benchmark group. Meanwhile, women empowerment is relatively weak in Kiribati with lower
parliament seats held by women and lower female labor force participation rate. Thus, while the
7
A common issue with growth regressions is endogeneity. Instrumental variable techniques can be challenging due
to the difficulty in finding acceptable instruments; that is, variables that are uncorrelated with the error term but
partially and sufficiently associated with GDP growth. The GMM method is used for this analysis to addresses
endogeneity issues.
8 Note that Figure 2 only includes variables for which data are available for Kiribati.
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