18
on equity is negative, but small and not significant. The overall effect on inclusive growth of
moving towards the 2 percent target is therefore positive. Various measures of the
contribution of regressors to explaining the variability of dependent variables also suggest
that inflation is the most important regressors in explaining variation of equity (see Appendix
E).
One concern is the direction of causality between growth and inflation. To address this
potential endogeneity issue, we also carried out a causality test and instrumental variable
estimation, using lagged inflation as an instrument. The results, presented in Appendix D, are
broadly in line with the ones in our benchmark model, confirming that inflation affects
growth.
Labor market duality – measured by the ratio between the numbers of new offers for part-
time and regular employment – has a negative and significant impact on inclusive growth,
through its negative impact on average income growth. As the scale of labor input is
accounted for by the growth in man-hour labor input, the composition of the labor force as
proxied by the duality variable captures the utilization of input and the efficiency. The
duality measure has a negative marginal effect on the rate of income growth at a similar
magnitude for the all sample and working-age sub-sample. A negative effect of labor market
duality on average income growth is consistent with the idea, discussed in Aoyagi and
Ganelli (2013), that Japan’s excessive duality reduces productivity through a “training
channel”, because non-regular workers receive less training than regular ones, and an “effort
channel”, because non-regular workers tend to be less motivated and therefore less
productive than regular ones. Aoyagi and Ganelli (2013) underscore the importance of
reforming Japan’s labor market through contract reform to increase productivity by reducing
labor market duality. While no concrete measure has been taken in terms of contract reform
so far, the idea has been discussed at the technical level in various working group and
committees, and the government has expressed its intention to improve working conditions
of non-regular workers. In this paper, we therefore assume that a “complete” Abenomics
package will, at some point, include measures to reduce labor market duality. Our results
show that this will have a positive effect on inclusive growth. Moreover, as expected, such an
effect is stronger when we include in the regression only working-age households.
Our results also suggest that a higher female participation rate has a positive effect on
inclusive growth by increasing average income growth. Furthermore, this variable has
positive and sizable effects both on average income and equity index growth, when using the
working-age household sample. Considering that female labor participation is a form of
inclusiveness (in process), it is not surprising that the working-age population is affected
more strongly. In other words, the results for the estimation with all households are mitigated
by the inclusion of the retirement-age female population. Increasing female labor
participation is one of the key objectives of Abenomics, on which measures (e.g. increasing
availability of child care) have already started to be implemented. Our results suggest that, in
19
addition to its positive impact on potential growth (as estimated for example by Steinberg
and Nakane 2012), this policy is also good for inclusiveness.
Another important objective of Abenomics is that of countering the aging of the population
by increasing labor supply not only of women, but of the overall population. While male
labor participation is already high in Japan, there is some scope for increasing overall labor
supply, for example by increasing participation of foreigners and older workers. Some of the
initiatives which have been announced in Special Economic Zones seem to go in this
direction. Our results show that increasing labor input would boost inclusive growth by
increasing both average income and equity (although only the effect on the former is
significant).
Our control variables for the size of the prefectural economy and demographic characteristics
show expected signs and reasonable magnitudes of estimated coefficients. Initial GDP per
capita — accounting for the level of income of each prefecture — is a negative and
significant determinant of inclusive growth (and its components) for the all household sample
and the working-age sub-sample, largely due to increasing inequality. The negative signs are
consistent with classic theories on growth and inequality: the rate of growth falls as the
(average) income level rises (Solow, 1956); and income tends to be unequal at a higher
average income level (Kuznets, 1955).
The elderly index — accounting for the aging of the society — has an insignificant effect on
inclusive growth when using the all-household sample, and a significant and positive effect
when using only the working-age household sample. Since the elderly index is actually a
dependency ratio, measured by the ratio of elderly population to the working-age population,
we can say that a higher dependency ratio affects the income distribution through the overall
productivity of the prefectural economy, rather than through distributional changes. The
marginally positive effect of aging on inclusive growth is rather surprising, but can be
explained by wealth distribution. In particular, while our income measure is before tax and
redistribution (and thus retired households have less or no income flows), it also accounts for
interest and rent payments (i.e. returns on assets).
Overall, policy variables affect inclusive growth mostly through growth in average income.
Our result suggests that the potential impact of a complete Abenomics package on income
equality is relatively small. We also carried out some robustness checks using alternatives
weights on the equity index and different assumptions on income distribution.
6
These checks,
not reported here but available upon request, confirm the robustness of our results.
6
Data of income distribution, disaggregated to the prefectural level, are limited to values at first and ninth
deciles and the mean. In order to construct our dependent variable, we therefore needed to make some
assumptions to estimate an income distribution, given all the available information. In the benchmark estimated
income distribution, we assume that: the lowest income is zero; the income distribution between observed
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