Christian Ochsner, Ph.D.
Did you know that men who shave their beards every day live longer? This statement is true in terms of correlation, but there is no causal relationship at all. In fact, empirical research in economics and social sciences faces the challenge of distinguishing correlation from causation. The course introduces concepts of causal analysis in a non-technical way. These concepts were awarded the 2021 Nobel Prize in Economics. The focus will be on research settings and designs. Figures and graphs will help to train students to understand the intuition behind the respective concepts. We will read and understand research papers in the field of long-run development and political economy that focus on specific concepts of causal empirical analysis.
Silvester van Koten, Ph.D.
Climate change, in the form of global warming, affects lives, societies, and economies. At the same time, energy remains a basic necessity of daily life and a vital input to industry in society. New climate policies seek to address these tensions and now exert a strong and growing influence on how economies and energy systems operate.
First, this course gives a brief overview of the present and expected future state of global warming and its economic consequences. Second, it offers clear theoretical insight into the economics of externalities, of which global warming is a prime example. It introduces key economic policy tools, such as Pigovean taxes, emission trading systems (also known as cap-and-trade), subsidies, and mandates. The theory has wide applications, including in public finance and public policy. Third, new technologies, from renewables such as wind, biofuels, and solar to the renewed interest in nuclear power, are reshaping the energy industry. Fourth, the course examines the main elements of the EU’s climate strategies and assesses the degree to which they align with economic theory and cost-benefit logic. Where possible, we highlight the relevance of climate change and the course concepts for participants’ local context.
Gabriela Kuvíková, Ph.D.
This course aims to provide a basic understanding of today’s changing landscape of financial markets and institutions with a broad scope and emphasis on general principles. Students will study the key fundamentals of financial markets and learn how financial markets and financial institutions work. We will discuss interest rates and their role in valuation, learn about efficient market hypothesis and exchange rate determination, explore money and capital markets, identify various players in the financial institutions industry, and take a closer look at central banking and the conduct of monetary policy.
Eva Hromadkova, Ph.D.
This Health Economics course aims to show students how economic principles can be used to understand health, healthcare demand and supply, and the organization and financing of health systems. It combines microeconomic theory with empirical methods to teach students how to model health and healthcare choices and how to evaluate policy using data. Core topics include the demand for health, health insurance and information problems (moral hazard, adverse selection), and public versus private financing arrangements. Further modules cover provider and pharmaceutical markets, long-term care, risky health behaviors, and international or regional comparisons of health systems.
Aizhamal Rakhmetova, PhD candidate
The course aims to provide students with basic knowledge in the main areas of behavioral economics by focusing on the behavioral implications of theoretical models and experimental evidence in economics. The list of topics includes bounded rationality, decision-making under risk and uncertainty, preferences, intertemporal decision-making, attention and information acquisition, and other behavioral heuristics and biases. Upon successfully completing this course, students should be able to understand the conceptual framework of behavioral economics and its tools, recognize behavioral biases, and apply insights from psychology when predicting or analyzing economic decision-making.
Ella Sargsyan, Ph.D.
The course will introduce regression analysis and cover some of the most recent econometric techniques central to modern econometric practice. Successful students will gain a deeper understanding of the material discussed in other Distance Learning Program courses. They will be up to speed with Western European students at the same education level, making them more competitive in their further studies and on the labor market. At the end of this course students will understand basic econometric concepts, basic estimation methods, and methods for testing statistical hypotheses. They will be able to apply standard methods of constructing econometric models, process statistical information, obtain statistically sound conclusions, and give meaningful interpretation to the results of the estimated econometric models. In addition, students will gain real data processing skills, using econometric packages for building and estimating econometric models in R.
Taras Hrendash, Ph.D.
Technology advances rapidly and affects us all, as new products and production methods continually replace old ones. Technological progress is a key driver of long-term economic growth, constantly improving living standards, health, and quality of life worldwide.
But do we fully understand the mechanisms behind these processes? Why do firms innovate and race to be first in research and development? Can free markets efficiently handle the creation and diffusion of new ideas and technologies? How can creativity, knowledge production, and risky exploration be incentivized? Does knowledge travel freely across borders, and why do innovation clusters emerge? These and many other questions surrounding innovation are highly debated and often lead to controversial conclusions. A scientific approach is therefore essential to provide the theoretical foundations needed to understand the economics of innovation. The awarding of the 2025 Nobel Prize in Economics for research in innovation economics underscores the societal importance of uncovering how innovation works, recognizing its costs and benefits, and fostering openness to new ideas and change.
This course combines solid theoretical foundations from leading economic research with real-world cases and anecdotes that stimulate discussion and learning.
Vilém Semerák, Ph.D.
This is a course about international trade, its determinants and its consequences. We study the ways that the patterns of international trade might be shaped by (and might in turn re-shape) a country’s available resource endowments, its technology, income distribution, economic growth and politics.
The course starts with the concept of comparative advantage and the gains from trade and the determinants of the patterns of trade. We will further explore the costs, benefits, and impact on the income distribution of different instruments of trade protection; the effects of free trade areas (trade creation and trade diversion), and of factor mobility. Students will learn to apply the analytical toolbox of trade theory to real-world situations in order to make qualitative predictions of the effects of measures such as tariffs or export subsidies. Students will not only learn the theory, but they will have a chance to use and analyze actual trade data.
Furthermore, due to the turbulent development of international trade relations in 2025, more space will be dedicated to trade policy issues – with attempts to provide insight into the dynamics of trade relations and negotiations between the USA, the EU, and China.
Daniil Kashkarov, Ph.D.
The aim of the course is to acquaint students with the general ideas behind structural macroeconomic modelling and how it can be applied to better understand real-world data, whether GDP fluctuations, evolution of lifetime income, or the decision of household to spend monetary transfers on consumption. We will cover several classical and widely used macro models focusing on economic growth, the development of income and consumption inequality over the lifetime of individuals, and on the differences in behavior of poor vs. wealthy households. For each model, we will acquire basic intuition on how a model works, and then describe how a model is calibrated to real data. The study of each model will conclude with a discussion on how the model helps us to understand the real world and what it fails to explain.