Introduction - The Agricultural Economics of the 21st Century - page 2

and salaries, number of people employed per enterprise, share of employment in
manufacturing total, investment per person employed, and the share of R&D
employment in the number of people), from 1996 to 2008, and with data which
was obtained from Eurostat.
The fifth chapter aims to analyze some economic, social, and environmental
causes of the agricultural output in some European Union countries, analyzing data
from the World Bank and considering time series econometric instruments. Some
influential countries, such as Spain, France, Italy, Germany, and UK were also
considered along with the three countries (Portugal, Ireland, and Greece) that have
received financial assistance from International Institutions.
Not forgetting the emerging economies, with data from the World Bank, for the
period 1961-2012, and considering the traditional function of production, the
contextual agricultural economics within BRICS countries were also analyzed in
the sixth chapter through time series econometric techniques.
In the seventh chapter the objective was to analyze the demographic, scientific,
and social sustainability of the economic growth in Portuguese sectors, with data
for the Portuguese NUTs II (seven), obtained via Eurostat for the period 1995-2010
and with panel data econometric instruments, based on the Keynesian models.
Considering the period 2004-2011, in the eighth chapter we investigated the
influence of the environmental variables within Portuguese economic growth,
specifically in the manufacturing sector, including those having the agricultural
sector as a base, taking into account the Keynesian models, for the Portuguese
regions (NUTs III), and the data (in panel) available for the Statistics of Portugal.
In the ninth chapter we analyzed the influence of other sectors related to the
farming sector in the performance of some indicators in agriculture, namely the
output, using statistical information from the Statistics of Portugal for the year of
2009 and considering cross-sectional estimations through several tests and tech-
niques, including those related to spatial econometrics.
The tenth chapter intends to identify and find the objectives and priorities of the
Azorean dairy farmer's decision making. The proposed methodology is based on
multicriteria models, by simulation of the dairy farmers' behavior through data of
the Farm Accountancy Data Network.