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In recent years, interest in rigorous impact evaluation has grown
tremendously in policy-making, economics, public health, social
sciences and international relations. Evidence-based policy-making
has become a recurring theme in public policy, alongside greater
demands for accountability in public policies and public spending,
and requests for independent and rigorous impact evaluations for
policy evidence. Froelich and Sperlich offer a comprehensive and
up-to-date approach to quantitative impact evaluation analysis,
also known as causal inference or treatment effect analysis,
illustrating the main approaches for identification and estimation:
experimental studies, randomization inference and randomized
control trials (RCTs), matching and propensity score matching and
weighting, instrumental variable estimation,
difference-in-differences, regression discontinuity designs,
quantile treatment effects, and evaluation of dynamic treatments.
The book is designed for economics graduate courses but can also
serve as a manual for professionals in research institutes,
governments, and international organizations, evaluating the impact
of a wide range of public policies in health, environment,
transport and economic development.
Policy evaluation and programme choice are important tools for informed decision-making, for the administration of active labour market programmes, training programmes, tuition subsidies, rehabilitation programmes etc. Whereas the evaluation of programmes and policies is mainly concerned with an overall assessment of impact, benefits and costs, programme choice considers an optimal allocation of individuals to the programmes. This book surveys potential evaluation strategies for policies with multiple programmes and discusses evaluation and treatment choice in a coherent framework. Recommendations for choosing appropriate evaluation estimators are derived. Furthermore, a semiparametric estimator of optimal treatment choice is developed to assist in the optimal allocation of participants.
Most countries implement social protection programs to help
individuals manage risks such as unemployment, disability, illness,
longevity or death. In many middle income countries, these are
often based on a 'Bismarckian model' (named after Otto von
Bismarck), where benefits are financed by contributions levied on
salaried employment. In countries with a large informal sector,
however, only a fraction of the population is covered by this
system and non-contributory programs have been added or are planned
to increase coverage. This can create distortions in the labor
market, and the book is about policies to expand the coverage of
social insurance programs to all workers, without reducing
incentives to job creation and formal work. While few would argue
against the need and social merits of social insurance and social
assistance programs there are growing concerns about their
unintended consequences on labor markets because of poor design.
The programs can distort incentives and individual behaviors in
ways that either reduce employment levels and/or promote
informality, ultimately affecting productivity and economic
performance. For instance, high social security contribution rates
can reduce formal employment; badly designed unemployment benefits
can reduce incentives to keep, search, and take jobs; and
fragmented social assistance programs can become a tax on formal
labor and encourage informality. The book reviews the evidence
regarding the effects of social insurance and social assistance
programs on labor market outcomes and discusses options to improve
their design and implementation. The book focuses particularly on
middle income countries in Latin America and Asia with a large
informal sector and suggests ways to reduce these distortions and
better manage and finance the subsidies to make coverage universal,
while creating good jobs. The book compiles expert papers from the
joint conferences of the World Bank (WB), the Institute for the
Study of Labor (IZA) and the Inter-American Development Bank (IDB)
on Employment and Development.
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