年齢構成と貿易開放度に関する地域別分析
The effects of age structure on trade openness by geographic region
衣笠智子（神戸大学）・福本幸男（大阪経済大学）
Tomoko Kinugasa (Kobe University) and Yukio Fukumoto (Osaka University of Economics)
kinugasa@econ.kobe-u.ac.jp

In this research, we investigate how age structure influences trade openness (i.e.,
the ratio of trade to GDP) by geographic region. Not all tradable goods are imported orexported, but an increase in the demand and supply for tradable goods will increaseimports and exports. Based on previous studies, especially Braude (2000) and Fukumoto
and Kinugasa (2017), we hypothesize that there exist differences in demand between
tradable and non-tradable goods by age groups. Compared with working-age individuals,
dependent individuals tend to consume more non-tradable goods such as education andmedical services; this suggests that an increase in the share of the working-age population
will increase the demand and supply for tradable goods relative to non-tradable goods andthus increase trade openness.
We empirically examine the relationship between trade openness and age structureusing panel data. We conduct empirical analysis not only for the whole world but also for
the following four regions of the world: Africa, Asia and Oceania, Europe, and North andSouth America. We deal with a sample period of 1951–2010 and 92 countries are
considered to represent the whole world sample. We calculate five-year average data from1951 to 2010 and create panel data for 12 periods: 1951–1955, 1956–1960, 1961–1965,1966–1970, 1971–1975, 1976–1980, 1981–1985, 1986–1990, 1991–1995, 1996–2000,2001–2005, and 2006–2010. In our empirical model, the dependent variable is trade
openness. Independent variables are the variables for age structure, the government
consumption share of GDP, population and period dummies. We use two kinds of agestructure variables: share of working-age population in total population and dependency
ratio (the ratio of young and old dependent populations to working age population).
We estimate the following three equations by region: Africa, Asia and Oceania,Europe, and North and South America.
/ββββ1956 1960
1971 19751986 1990
2001 2005

ββββ1961 1965
1976 1980
1991 1995
2006 2010

ββ1966 1970
1981 1985
β1996 2000

for n = 1, 2, 3. The dependent variable Opennessit represents trade openness of country iat period t. is a country dummy variable. Let1be the share ofworking-age population,2
be the dependency ratio, and3 ≡ 0.
denotes the government consumption share of GDP,

denotes population, and/is the real GDP per capita. D(XXXX-YYYY)it areperiod dummies.
We consider factors other than age structure as follows. Government consumption
share of GDP is defined as the variable of government size. High government size mightmean strong government intervention, and we expect that government size has a negativeeffect on trade openness. Population is considered as the variable of economy size. We
expect that the economy size has a negative effect on trade openness because smaller
countries tend to need to trade more than larger countries. Real GDP per capita is used
for the variable of economic development. It is expected that increases in demand for
luxury non-tradable goods due to economic development would reduce trade openness.
We use period dummies as proxy variables for the trade barriers and foreign outsourcing
because of data restriction. Above all, declining trade barriers and increasing foreign
outsourcing could be important reasons for the upward trend of trade openness over
several decades. Development of regional economic integration would influence trade
openness for many countries in the same region during the same period, and so we believethat it comprises a part of the period dummy variables. Therefore, it is possible that theeffects of period dummies on trade openness are different by region.
Our empirical results show that the share of working-age population has
significantly positive effects and the dependency ratio has significantly negative effects
on trade openness in the three regions except Africa. The absolute values of thecoefficients are the largest for Asia and Oceania and second largest for Europe. Since
intra-regional trade is actually vigorous in both regions, this would be consistent with ourhypothesis. In Europe, the dispersions of trade openness and the share of working-age
population are small, therefore, the similarity of age structure might influence similarityof trade openness. The absolute values of the coefficients for North and South America
are smaller than those for Asia and Oceania and Europe. Because North and SouthAmerica is quite a long region, it is possible that intra-regional trade of North and SouthAmerica has not been developed. In addition, shift to trade liberalization was delayed inSouth American countries compared with Asian countries because trade policies based on
infant industry argument were predominant. Manufacturing protection under importsubstituting industrialization decreases the share of trade of tradable goods. As a result,trade openness might be less sensitive to age structure. In many African countries, goods
and labor markets are not prepared enough, and non-tradable goods such as education andmedical services may not be sufficiently supplied. Therefore, it is possible that age
structure does not influence trade openness in Africa.
To sum up our empirical results, it is possible that demographic change has
influenced trade openness. Moreover, it is suggested that the similarity of trade openness
among countries in the same region may occur not only because of regional economic
integration but also because of similarity of age structure.