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Course Description Course Name : Limited Dependent Variables Models II Course Code : IEM 722 Course Type : Optional Level of Course : Second Cycle Year of Study : 1 Course Semester : Spring (16 Weeks) ECTS : 6 Name of Lecturer(s) : Prof.Dr. SEDA ŞENGÜL Learning Outcomes of the Course : Acquires truncated and censored distributions. Applies the goodness of fit tests for limited dependent variable models. Acquires and applies limited variable models Has the ability to apply limited dependent variable models in a suitable programming language Interprets the results obtained Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : This course is the second part of a two semester sequence designed to provide students with basic concepts and methods in limited dependent variable models.The aim of this course to teach the problem of censoring, censored and truncated distributions, Sample selection, Tobit, Heckman, Double Hurdle models .By the end of the semester students are expected to have a working knowledge of limited dependent variable models and to be able to apply them in a suitable programming language.Students are also expected to be able to interpret the result. obtained. Course Contents : Censored and truncated distributions, truncated and censored samples, truncated regression, censored regression, tobit model, heckman model, double hurdle model Language of Instruction : Turkish Work Place : Class   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 The problem of censored data Reading related sources Lecture 2 Truncated and censored distributions Reading related sources Lecture 3 Truncated regression Reading related sources Lecture 4 Censored regression Reading related sources Lecture 5 Tobit model Reading related sources Lecture 6 Tobit model Reading related sources , problem set and application Lecture and application 7 Midterm exam 8 The Characteristics of Double Hurdle Model Reading related sources Lecture 9 To compare Double Hurdle model with Tobit Model Reading related sources Lecture 10 Independent and dependent Double Hurdle Models Reading related sources, problem set and application Lecture and application 11 Independent and dependent Double Hurdle Models Reading related sources, problem set and application Lecture and application 12 Infrequency of purchase model Reading related sources, problem set and application Lecture and application 13 Heckman Model Reading related sources, problem set and application Lecture and application 14 Heckman model Reading related sources, problem set and application Lecture and application 15 Review of Limited Dependent Variable models Reading related sources, problem set and application Lecture and application 16/17 Final exam   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  Maddala, G.S (1988), Limited Dependent and Qualitative Variables in Econometrics  Cameron C.A., Trivedi P, K, (2005). Microeconometrics Methods and Applications. Cambridge University Press.  J. Scott Long, Regression Models for Categorical and Limited Dependent Variables, 1997, Sage Publications; Required Course Material(s)   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 75     Homeworks/Projects/Others 6 25 Total 100 Rate of Semester/Year Assessments to Success 40   Final Assessments 100 Rate of Final Assessments to Success 60 Total 100   Contribution of the Course to Key Learning Outcomes # Key Learning Outcome Contribution* 1 Explains Econometric concepts 4 2 Equipped with the foundations of Economics, develops Economic models 4 3 Models problems using the knowledge of Mathematics, Statistics, and Econometrics 4 4 Acquires the ability to analyze, benchmark, evaluate and interpret at conceptual levels to develop solutions to problems 4 5 Collects, edits, and analyzes data 5 6 Uses advanced software packages concerning Econometrics, Statistics, and Operation Research 4 7 Develops the ability to use different resources in an area which has not been studied in the scope of academic rules, synthesizes the information gathered, and gives effective presentations 3 8 Speaks Turkish and at least one other foreign language in accordance with the requirements of academic and business life. 3 9 Questions traditional approaches and their implementation and develops alternative study programs when required 2 10 Recognizes and implements social, scientific, and professional ethic values 3 11 Gives a consistent estimate for the model and analyzes and interprets its results 5 12 Takes responsibility individually and/or as a member of a team; leads a team and works effectively 3 13 Defines the concepts of statistics, operations research and mathematics. 3 14 Knowing the necessity of life-long learning, follows the latest developments in the field of study and improves himself continiously 0 15 Follows the current issues, and interprets the data about economic and social events. 2 16 Understands and interprets the feelings, thoughts and behaviours of people and expresses himself/herself orally and in written form efficiently 3 * Contribution levels are between 0 (not) and 5 (maximum).   Student Workload - ECTS Works Number Time (Hour) Total Workload (Hour) Course Related Works     Class Time (Exam weeks are excluded) 14 3 42     Out of Class Study (Preliminary Work, Practice) 14 4 56 Assesment Related Works     Homeworks, Projects, Others 6 8 48     Mid-term Exams (Written, Oral, etc.) 1 5 5     Final Exam 1 5 5 Total Workload: 156 Total Workload / 25 (h): 6.24 ECTS Credit: 6