Prof. vibhuti patel gender responsive budgets in india pragati, vol. 1, issue...
Thesis abstract
1. Research fields: extensive studies in human development shows that achieving
stable human development without considering the social and economical
development of women in different aspects of life will not be possible. Regarding
the situation of women in different societies, the importance of the issue appears to
be highlighted in developing countries. Considering the important role of
governments in promoting the development of their community, the impact of
government fiscal policy on economic and social development of women will have
a positive influence for the development and advancement of women in developing
countries, Empirical studies in different countries shows the accuracy of this
subject for developing countries. The purpose of this study is to evaluate the
impact of fiscal policy on women's social and economic development of the
selected developing countries in Asia, such as iran during the years 2013-1980.
Method: Theoretical studies show that government fiscal policy through social
expenditures is One of the major factors affecting the women's development
indexes. hence this study evaluates the government social expenditures on the two
key and basic factors of health and education of women’s development And for
achieving this purpose, For this purpose, the ordinary least squares estimation
method (OLS) regression equations using Eviews software all Sion selection of
Asian developing countries is estimated.
Results: The findings reveal that the social expenditures of the governments can
positively impact on both the health and education factors of women in developing
countries also the results indicate that the impact of government social
expenditures on health factors is more highlighted in the developing countries,
which have a lower human development index.
Keywords: fiscal policy, government social expenditures, economical development
of women, human development index, Asian developing countries, the ordinary
least squares estimator (OLS).