The following list provides the full list of my past courses and teaching activities since 2010 (PhD graduation). Most of the courses have been given by multiple times. Details on the same course units are provided in the list when mentioned the first time. If not otherwise mentioned, the course is organized at the Department of Mathematics and Statistics (University of Turku)

Spring 2021 - present (incl. season 2022 - 2023) (my role: Associate Professor and Head of Statistics, Statistics, University of Turku)

• Statistics and Data (6 ECTS, undergraduate level) [2022]

• Time Series Analysis (6 ECTS, since 2022 only undergraduate level) [2022]

• Nonlinear Time Series Analysis (6 ECTS, Master's level, available also for PhD students in economics and finance) [2022]

• Multiple Time Series Analysis (6 ECTS, Master's level, available also for PhD students in economics and finance) [2021]

• Macroeconometrics (5 - 6 ECTS, Master's level, a joint course with the University of Helsinki & Helsinki GSE & FDPE) [2022, 2023]

• Linear and Generalized Linear Models (8 ECTS, Undergraduate level) [2021, 2022, 2023]

• Advanced Regression Analysis and Statistical Learning (6 ECTS, undergraduate level and available also students at the UTUGS) [2021]

• Advanced Statistical Learning (6 ECTS, Master's level) [2022]

• Statistical Learning: Boot Camp (1 ECTS, PhD level, UTU Graduate School) [2021]

• Master’s degree seminar in Statistics & supervision of Master’s degree students (4 ECTS, Master level) [continuous]

• Internship (Statistics) (5 ECTS, Master's level) [continuous]

• History of Statistics (2-6 ECTS, Master's level) [continuous]

• Discrete Data Analysis (6 ECTS, Undergraduate level) [continuous]

• Mathematics and Statistics in Working Life (2 ECTS, with Vesa Halava and Marko Mäkelä) [2023]

In addition, invited/visiting lecturer:

• Advanced Econometrics 3: Macroeconometrics (5 ECTS, University of Helsinki: Master’s Programme in Economics (Research track, advanced studies) and Doctoral students in economics (Helsinki Graduate School of Economics)) [2021]

2020 (Associate Professor, Statistics, University of Turku)

• Linear and Generalized Linear Models (8 ECTS, Undergraduate level) [2020]

• Nonlinear Time Series Analysis (6 ECTS, Master's level, available also for PhD students in economics and finance) [2020]

• Advanced Statistical Learning (6 ECTS, Master's level) [2020]

• Master’s degree seminar in Statistics & supervision of Master’s degree students (4 ECTS, Master level) [continuous]

• Bachelor’s degree seminar and general responsibility of Bachelor’s theses in Statistics (spring 2020, with Jouko Katajisto and Pekka Nieminen)

• Graduate Econometrics (2 - 6 ECTS, only for PhD students in econometrics, can be included in UTUGS studies)

2018 (autumn) - 2019 (autumn) (University lecturer (Statistics, University of Turku)) and part-time fixed term Professor (Economics, University of Tampere)

• Time Series Analysis (6 ECTS, since 2022 only undergraduate level) [2018]

• Nonlinear Time Series Analysis (6 ECTS, Master's level, available also for PhD students in economics and finance) [2019]

• Multiple Time Series Analysis (6 ECTS, Master's level, available also for PhD students in economics and finance) [2019]

• Linear and Generalized Linear Models (8 ECTS, Undergraduate level) [2019]

• Advanced Regression Analysis and Statistical Learning (6 ECTS, undergraduate level and available also students at the UTUGS) [2019]

• Matrices for Statistics (2 ECTS, undergraduate level) [2019, spring and autumn 2019]

• Bachelor’s degree seminar and general responsibility of Bachelor’s theses in Statistics (with Jouko Katajisto) [2018]

• Sampling and Study Design (5 ECTS, undergraduate level, with Jouko Katajisto) [2018, 2019]

• Master’s degree seminar in Statistics & supervision of Master’s degree students (4 ECTS, Master level) [continuous]

Teaching and supervision, Economics (University of Tampere, Faculty of Management and Business), autumn 2018 - spring 2019:

• Empirical Macroeconomics (5 ECTS, Master's special course level) [2019]

• Advanced Econometrics (Ekonometrian jatkokurssi) (10 ECTS, Master's level course) [2018]

• Supervision of Master’s degree students in Economics (2018 - 2019) [2018, 2019]

2016 - 2018 (University lecturer (Statistics, University of Turku))

• Sampling and Study Design (5 ECTS, undergraduate level, with Jouko Katajisto and Maiju Pesonen) [2016, 2017]

• Time Series Analysis (6 ECTS) [2016, 2017]

• Multiple Time Series Analysis (6 ECTS, Master's level, available also for PhD students in economics and finance) [2017]

• Advanced Regression Analysis and Statistical Learning (6 ECTS) [2017]

• Advanced Statistical Learning (6 ECTS, Master's level) [2018]

• Theory of linear models (Lineaariset mallit) (8 ECTS, undergraduate level) [2016, 2017, 2018]

• Financial and Time Series Econometrics (6 ECTS credit points, PhD/Master's level, with Heikki Kauppi) [2016]

• Bachelor’s degree seminar and general responsibility of Bachelor’s theses in Statistics (with Jouko Katajisto) [continuous]

2015 (Post-doc researcher (University of Helsinki) and University lecturer (Statistics, University of Turku)

Topics in Macroeconometrics (6 ECTS credit points, PhD/Master's level, with Markku Lanne (course website)) [2015]

• Department of Political and Economic Studies (University of Helsinki) & HECER & Finnish Doctoral Programme in Economics (FDPE)

• Overview, Part II: The course consists of two parts. The latter part considers models for time series whose range is limited. In a number of macroeconomic and financial applications involving such time series, the usual assumption of a continuous, real-valued dependent variable underlying linear models is inappropriate, and an alternative class of models needs to be entertained instead. In that class, this course concentrates on discrete (binary and multinomial), censored (positive-valued) and duration time series data. The main objective is to introduce the properties and major applications of econometric models specified for such data.

Basic Course on Regression Modelling (5 ECTS, PhD level, practical sessions, with Mervi Eerola and Jouko Katajisto) [2015]

• University of Turku Graduate School (UTUGS)

• This intensive course starts with a short overview of the principles of statistical analysis. It does not replace an elementary course in statistics but helps by examples to understand how relationships between phenomena can be investigated and their significance assessed by simple statistical models. The course is especially intended to those wishing to improve their understanding of statistical inference and modelling.

Tilastotiede tutuksi ("Introduction to Statistics applications") (5 ECTS , undergraduate level, one invited lecture) [2015]

• Department of Mathematics and Statistics, University of Helsinki

Advanced Econometrics I: Principles of Econometrics (2015) (6 ECTS, Master's level) [2015]

• Department of Political and Economic Studies, University of Helsinki & HECER Master's Programme & Economics (Aalto University & Hanken)

• Overview: The course builds upon the introductory course in econometrics (TA9). After the course, the students should be familiar with the interpretation and statistical inference in the linear regression model and binary response models in the cross-sectional context. To the extent covered in the course, they should also understand the basic properties of the maximum likelihood estimator and the related tests, and be able to implement the central models and methods in practical research work. Moreover, they should be able to critically read empirical economic research reports employing methods covered in the course, to identify their potential methodological problems, to compare alternative econometric model specifications, and to assess the adequacy of empirical results.

2010 - 2014 (Post-doc researcher, University lecturer 2010-2011 (Economics, University of Helsinki))

KT043022 KTS24 Advanced Econometrics (2014) (10 ECTS, Master's level) [2014]

• Invited lecturer

• Turku School of Economics, Economics, University of Turku

• Overview: The regression framework and the underlying statistical theory are introduced at a fairly general level. The basic asymptotic (large sample) theory and its application to ordinary least squares estimation are treated under the random sampling assumption, common in empirical analyses of cross-sectional data. Problems related to multicollinearity, heteroscedasticity, omitted variable bias and simultaneity are covered. Instrumental variable estimation and related techniques are studied carefully. Other topics include panel regressions, binary response regressions and some time series models. Theoretical problem sets and empirical demonstrations with econometric software are an important part of the course

Advanced Econometrics I: Principles of Econometrics (6 ECTS, Master's level) [2012, 2014]

• Department of Political and Economic Studies, University of Helsinki & HECER Master's Programme & Economics (Aalto University & Hanken)

• Overview: The course builds upon the introductory course in econometrics (TA9). After the course, the students should be familiar with the interpretation and statistical inference in the linear regression model and binary response models in the cross-sectional context. To the extent covered in the course, they should also understand the basic properties of the maximum likelihood estimator and the related tests, and be able to implement the central models and methods in practical research work. Moreover, they should be able to critically read empirical economic research reports employing methods covered in the course, to identify their potential methodological problems, to compare alternative econometric model specifications, and to assess the adequacy of empirical results.

Taloudelliset termit tutuiksi ("Introduction to economic terms and applications") (5 ECTS, undergraduate level, an invited lecture) [2011 - 2015]

• Department of Political and Economic Studies, University of Helsinki

Advanced Econometrics (2010 - 2011) (10 ECTS credit points, Master's level) [2010 - 2011]

• Department of Political and Economic Studies, University of Helsinki & Aalto University & Hanken

• Overview: After the course, the students should be very familiar with the interpretation of and statistical inference in the linear regression model in the time series contexts and know its basics in the panel data context. They should also understand the basic properties of linear time series models, and be able to implement the central models and methods in practical research work. Moreover, they should be able to critically read empirical economic research reports employing the methods covered in the course, to identify their potential methodological problems, to compare alternative econometric model specifications, and to assess the adequacy of empirical results.

Empirical Macroeconomics (5 ECTS, Master's level) [2010, 2013]

• Department of Political and Economic Studies, University of Helsinki

• Overview: The goal of the course is to provide an introduction to business cycle analysis and the methods of modern empirical macroeconomics. The topics include the measurement of the business cycle, dating and predicting business cycle turning points and structural change in business cycles characteristics. Econometric models suitable for capturing the behaviour of macroeconomic time series are introduced. Issues relating to the construction of macroeconomic data are also covered. In particular, many macroeconomic variables are subject to revisions that must be taken into account in empirical work, and the properties of revisions as well as methods to deal with them are discussed.