This course deals with the application of statistical models and theories for modeling and analyzing economic problems. The purpose of the course is to train students in the quantitative modeling approaches to understanding and  analyzing  economic  phenomena.  Economic  events  and  outcomes  often  show  considerable  level  of uncertainties. As a result, a government planner or a business executive often has to take recourse to conjectures in making policy decisions. This course will give students exposure to how decisions based on conjectures are formally tested  and  substantiated, using statistical body of knowledge.  Economic uncertainties often have a complex blend of certain (deterministic) and random (probabilistic) components. Application of economic and statistical tools helps us separate out the deterministic features of an economic phenomenon from the probabilistic features. This is done by using existing quantitative information (data) on an economic event.

The primary objective of this course is to learn how to apply statistical and econometric tools to address              numerous economic issues within the abovementioned framework. For instance, we may be interested to know the expected rate of return on a common stockor to formally verify if the risk associated with an investment is   within acceptable level. We may also want to see how a price of a product affects the volume of sales of a          company; we may be interested to investigate what contributes the most in determining house price. We may   want to know how elastic the demand for gasoline is, or we may want to forecast the likely sales of smart        phones ten years from now. Addressing these issues require availability of quantitative economic information    commonly called data. A portion of this course will help students learn how to gather and use relevant economic data and make them suitable for statistical and econometric applications using computer and statistical          software, primarily STATA and EXCEL.

Prerequisites

• Economics 301 (Intermediate Microeconomics)

• Economics 311 (Introductory Statistics)

• Math 226 (calculus)

• Working knowledge of Microsoft EXCEL

Course Organization

The course will be offered online synchronously via ZOOM for Econ 312 (1989, synchronous) students. Each video lecture will be recorded and posted on iLearn on a daily basis. For students enrolled in the Econ 312-3Z (2555, asynchronous) class, each video lecture from the Econ 312 (1989, Synchronous) class will be posted on iLearn on a daily basis. Each course (both synchronous and asynchronous) will be divided into two parts. Although the two parts are inextricably linked, to distinguish one from the other, students must note that Part 1 will be primarily based on class lectures via zoom (or via video in the case of the asynchronous class) when we learn how to apply statistical and econometric tools in addressing economic problems. Part 2 is a natural continuation ofPart 1  and  will  involve  learning  computer-based statistical packages. In this course EXCEL, and a statistical software, called STATA, will be the primary statistical packages to be used for data organization and analysis. There will be three homework assignments. Homework  1 and 2 will be due right before exams 1 and 2, respectively. Homework 3 will be due during week 5 of class. Homework (three in number) will not be graded. Instead of a final exam, every student will carry out an INDEPENDENT MODELING PROJECT, which will be due for evaluation on the last day of class.

Grading Weights and Letter Grades

• Regular class attendance and watching recorded video lectures are the most important factors in

the overall performance and course grade.

Required Text and Course Material

Required Text: Author: Christopher Dougherty, Introduction to Econometrics, Fifth Edition or later,

Oxford University Press

Course Material: Handouts and  lecture  notes  will be  posted on iLearn for this course on a weekly basis. Homework exercises, data sets for homework assignments and for class discussion purposes will be put up on the iLearn website  on a weekly basis. Students are required to download the data set for their work from the iLearn website or from the Textbook website at

https://global.oup.com/uk/orc/busecon/economics/dougherty5e/student/datasets/

Course Outline, Assignments, Exams, and Modeling Project

Disability access

Students with disabilities who need reasonable accommodations are encouraged to contact the instructor. The         [Disability Programs and Resource Center (DPRC)] is available to facilitate the reasonable accommodations           process. The [DPRC] is located in the [Student Service Building and can be reached by telephone (voice/TTY 415- 338-2472) or by email ([email protected]).” (http://www.sfsu.edu/~dprc)]

Student disclosures of sexual violence.

SF State fosters a campus free of sexual violence including sexual harassment, domestic violence, dating violence, stalking, and/or any form of sex or gender discrimination. If you disclose a personal experience as an SF State       student, the course instructor is required to notify the [Dean of Students]. To disclose any such violence                 confidentially, contact:

[The SAFE Place - (415) 338-2208; http://www.sfsu.edu/~safe_plc/]

[Counseling and Psychological Services Center - (415) 338-2208; http://psyservs.sfsu.edu/] San Francisco State University College of Business Undergraduate Academic Standards

San Francisco State University College of Business Undergraduate Academic Standards San Francisco State       University College of Business (SF State CoB) regards incidents of academic misconduct as serious matters. The following explains what academic misconduct is and outlines the consequences of academic misconduct.

A. Academic Misconduct

Academic misconduct is defined as follows:

1. Cheating: Any unauthorized attempt to offer or obtain assistance in a formal academic exercise (e.g., an     examination or class exercise); assuming another student's identity with intent to provide an advantage for the student; copying, in part or in whole, from another's test or other evaluation instrument; submitting work        previously presented in another course, if contrary to the rules of either course.

2. Plagiarism: The unauthorized use (i.e., representing as one’s own work) or reproduction or close imitation of original creations (ideas, words, sentences, paragraphs, or parts thereof; or artistic/scholarly works such as        computer programs, photographs, or similar works) of another author (person, group, organization, including    anonymous authors) without due acknowledgment (accepted standards of citation or reference of the original    source of the used or quoted content).

3. Fabrication: The distortion of data, information, or citations in any formal academic exercise or altering grading or grading instructions. 4. Deception: Providing false information to an instructor concerning a formal academic     exercise—e.g., giving a false excuse for missing a deadline, falsely claiming to have submitted work, or submitting false information regarding internships.

4. Deception: Providing false information to an instructor concerning a formal academic exercise—e.g., giving a false excuse for missing a deadline, falsely claiming to have submitted work, or submitting false information      regarding internships.

B. Disciplinary Sanctions

Two major types of sanctions may be imposed for any academic misconduct: Academic and Administrative.