Three essays on policy evaluation and analysis
|Author:||Vědunka Kopečná (9.3.2022)|
|Year:||2022 - summer|
|Leaders:|| PhDr. Jaromír Baxa Ph.D.
|Consultants:|| Mgr. Milan Ščasný PhD.
|Work type:|| Dissertations
|Awards and prizes:|
|Abstract:||This thesis consists of three articles sharing the main theme -
evaluation of policies related to current issues both from micro and
macroeconomic perspectives. The dissertation aims at the central
The first article presents a novel methodology of a hybrid
dynamic computable general equilibrium model used to quantify
socio-economic impacts of an emission abatement driven policy
focused on adoption of electric vehicles in personal transport on the
example of Austria. Heterogeneous micro-founded preferences are
integrated into a dynamic computational general equilibrium model
which is further linked to a bottom-up technology-rich electricity
model and a stock-flow vehicle accounting model. Endogenously
determined emissions from vehicle use, electricity generation, and
production provide an input to quantify external costs attributable to
air quality and carbon emissions using the Impact Pathway Analysis.
The second article estimates the elasticity of substitution between
capital, labour, energy and materials in the constant elasticity of
substitution production function, which is being used in a majority of
general equilibrium models. We use a non-linear estimation technique
to derive these elasticities for the whole economy and for five different
sectors, for the EU as a whole and for its two sub-regions - Western
and Central and East European countries.
The third article evaluates the public sector employment policy
from a microeconomic perspective, and focuses on the project
Internships for Young Job Seekers, as part of the program Youth
Guarantee, which was intended as a help for students with
transitioning from schools to the labour market thanks to internships
in companies. The counterfactual evaluation quantifies the impacts of
internships on personal income and economic status of trainees by
using the propensity score matching, difference-in-differences
estimation and two complementary methods – ordinary least squares
and multinomial logit model.