Course catalog

WiSe 22/23  
 School of Busin...  
 Econometrics  
 Course

WiSe 22/23: Module offerings

Econometrics

0190d_m30

  • Mathematics (for Students of Business and Economics)

    0171dA1.5

    learning objectives:
     Students learn the essential mathematical methods they need in order to understand the formalized economic relationships that they will encounter during their studies. The methods will also enable them to develop solutions to problems related to these economic relationships. The methods include a fundamental understanding of linear algebra and analysis as well as how to apply that to economic problems. In addition, the module treats the students’ individual and cultural diversity as a positive contribution that supports student and teacher success.

    course content:
     Vectors, matrices, determinants, linear systems of equations, functions of one or more variables, ordinary and partial derivatives, extreme values of functions with and without constraints, integral calculus.

    language of instruction:
     German / English

    workload
     180 hours (6 ECTS)

    duration / frequency
    one semester / every winter semester

    close
    • 10120301 Lecture
      Mathematics for Economists (V) (Dieter Nautz)
      Schedule: Mo 10:00-12:00 (Class starts on: 2022-10-17)
      Location: Hs 101 Hörsaal (Garystr. 21)
    • 10120302 Practice seminar
      Mathematics for Economists (Ü) (Dieter Nautz)
      Schedule: Di 10:00-12:00 (Class starts on: 2022-10-18)
      Location: Hs 101 Hörsaal (Garystr. 21)
    • 10120305 Tutorial
      Mathematics for Economists (T) (Lea Sieckmann)
      Schedule: Mi 08:00-10:00, Mi 10:00-12:00, Mi 12:00-14:00, Mi 16:00-18:00, Do 12:00-14:00, Do 14:00-16:00, Do 16:00-18:00, Fr 14:00-16:00, zusätzliche Termine siehe LV-Details (Class starts on: 2022-10-19)
      Location: 328 Hörsaal (Boltzmannstr. 16-20)

  • Schließende Statistik (Inferential Statistics)

    0171dA1.7

    learning objectives:
     Students learn to make decisions based on statistical data and assess the quality of these decisions. They learn how to solve three central types of statistical problems: Estimating unknown parameters of a distribution (point estimation), determining the confidence interval for an unknown parameter (confidence interval), making statements about the equality or inequality of distributions (tests). Students learn to apply these techniques themselves using empirical data and with the help of computer technology. The diversity of perspectives, experiences, and skills that the students bring with them to the group is treated as a positive contribution to the quality of research they produce and entails great benefits.

    course content:
     Continuous distribution models, sampling functions, parameter estimation, confidence intervals, hypothesis testing, regression analysis.

    language of instruction:
     German / English

    workload
     180 hours (6 ECTS)

    duration / frequency
    one semester / every winter semester

    close
    • 10120501 Lecture
      Inferential Statistics (V) (Jan Marcus)
      Schedule: Di 12:00-14:00, zusätzliche Termine siehe LV-Details (Class starts on: 2022-10-18)
      Location: HFB/A Hörsaal (Garystr. 35-37)
    • 10120502 Practice seminar
      Inferential Statistics (T) (Jan Marcus)
      Schedule: Do 10:00-12:00 (Class starts on: 2022-10-20)
      Location: Hs 107 Hörsaal (Garystr. 21)
    • 10120505 Tutorial
      Inferential Statistics (T) (N.N.)
      Schedule: Mi 14:00-16:00, Do 08:30-10:00, Fr 10:00-12:00 (Class starts on: 2022-10-26)
      Location: HFB/B Hörsaal (Garystr. 35-37)

  • Introduction to Time-Series Analysis

    0171dB2.3

  • Einführung in die Mikroökonometrie (Introduction to Microeconometrics)

    0171dB2.4

    learning objectives:
     Students expand their knowledge of basic econometrics to include important questions and approaches in applied microeconometrics. This includes learning about which methods to use to analyze consumer and producer behavior in product and factor markets. Students learn about the most significant microeconometric models and gain practical knowledge about how to perform empirical studies themselves. They learn to use statistics software to work on topics with empirical data. Furthermore, students learn to apply modern microeconometric methods to practical problems and are able to conduct empirical analyses independently.

    course content:
     Panel data models, discrete choice models, limited-dependent variable models.

    language of instruction:
     German / English

    workload
     180 hours (6 ECTS)

    duration / frequency
    one semester / irregular

    close

Subjects A - Z