ECONS507-21A (HAM)

Quantitative Skills for Finance and Economics

15 Points

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Division of Management
School of Accounting, Finance and Economics

Staff

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Convenor(s)

Lecturer(s)

Administrator(s)

: denise.martin@waikato.ac.nz

Placement/WIL Coordinator(s)

Tutor(s)

Student Representative(s)

Lab Technician(s)

Librarian(s)

: clive.wilkinson@waikato.ac.nz

You can contact staff by:

  • Calling +64 7 838 4466 select option 1, then enter the extension.
  • Extensions starting with 4, 5, 9 or 3 can also be direct dialled:
    • For extensions starting with 4: dial +64 7 838 extension.
    • For extensions starting with 5: dial +64 7 858 extension.
    • For extensions starting with 9: dial +64 7 837 extension.
    • For extensions starting with 3: dial +64 7 2620 + the last 3 digits of the extension e.g. 3123 = +64 7 262 0123.
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Paper Description

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The exponential growth in the availability of data requires that students are able to make informed decisions using data, and effectively communicate their data analyses.This course covers the analytical and statistical techniques that business and management students are most likely to use in their future courses and professional careers.

Students learn to apply skills in data analysis and applied regression methods to a broad range of topics including business applications, corporate and international finance, international economics and macroeconomics using time series and panel data at household, firm and country level. The topics covered include data analysis; correlation vs.causation; simple regression analysis; multiple regression analysis; regression diagnostics; regression with dummy variables; transformation of variables and econometric issues with time series and panel data. The skills acquired from the course can be applied to problems in accounting, economics, finance, marketing, and business in general.

This course uses a combination of lectures, case discussions, lab sessions and student presentations. Students will have hands-on work with data. Weekly computer-based workshops aim to enhance understanding of how the techniques introduced in lectures apply in a business context. Topics to be covered include presenting data using visual and descriptive statistics, measuring and understanding the relationship between variables, predictive analytics and prescriptive analytics tools. Empirical examples from economics, finance, accounting, and marketing will illustrate the material covered. Emphasis will be placed on understanding concepts and analysis of data.

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Paper Structure

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A two-hour lecture plus computer labs per week. Attendance at lectures and computer labs is strongly encouraged.

Lectures
The lectures will be focused on teaching quantitative methods to students who want to apply data and regression analysis techniques sensibly in the context of real-world empirical problems. They will also feature some discussion based on applied econometric theory, these will draw on practical examples that demonstrate the interpretation of results provided by various techniques.

Computer Labs
The main purpose of the computer classes will be to provide students with practical experience of using the econometric techniques covered in the lectures. In labs, you will be given a set of questions and exercises to complete using the software package STATA.T he computer classes will also be a forum for students to discuss the lecture material and attempt various problem-solving exercises that might be set over the weeks.

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Learning Outcomes

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Students who successfully complete the paper should be able to:

  • Interpret business and economic data
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  • Explain how data analytics theory applies to business decision making
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  • Identify and apply the appropriate data analytics methods to real world business issues and interpret the results, including analysis of random experiments and methods of comparing group
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  • Make inference on population means, difference between means for business decision making
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  • Use regression analysis and critically appraise the merits and shortcomings of using regression methods to analyse empirical data
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  • Evaluate evidence to inform decision making
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  • Demonstrate proficiency in using Microsoft Excel & STATA as a statistical and analytical tool
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Assessment

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Assessment Components

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The internal assessment/exam ratio (as stated in the University Calendar) is 100:0. There is no final exam. The final exam makes up 0% of the overall mark.

The internal assessment/exam ratio (as stated in the University Calendar) is 100:0 or 0:0, whichever is more favourable for the student. The final exam makes up either 0% or 0% of the overall mark.

Component DescriptionDue Date TimePercentage of overall markSubmission MethodCompulsory
1. Assignment I
12 Apr 2021
5:00 PM
20
  • Online: Submit through Moodle
2. Assignment II
19 May 2021
12:00 AM
20
  • Online: Submit through Moodle
3. Applied project
14 Jun 2021
10:00 AM
30
  • Online: Submit through Moodle
4. Final Test
31 May 2021
9:00 AM
30
  • Online: Submit through Moodle
Assessment Total:     100    
Failing to complete a compulsory assessment component of a paper will result in an IC grade
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Required and Recommended Readings

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Required Readings

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Introductory Econometrics: A Modern Approach by Jeffrey Wooldridge 6th Ed (Cengage)

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Recommended Readings

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The following three texts are available online from the library (link available in the reading list):

  • Forecasting: Principles and practice by R.J. Hyndman; G. Athanasopoulos 2018
  • Mostly harmless econometrics: An empiricist's companion by J.D. Angrist; J-S. Pischke 2009
  • Econometrics for dummies by R. Pedace 2013

FULL READING LISTS FOR ECONS507:

https://rl.talis.com/3/waikato/lists/B8BC90AF-E08C-84DD-226A-CEC5D0122C4F.html?lang=en-US&login=1

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Other Resources

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The following two texts are useful for excel based analytics:

Duignan, J. (2014) Quantitative Methods for Business Research Using Microsot Excel, Cengage Learning (On Course Reserve)

Hyndman, R. and Athanasopoulos, G. (2018) Forecasting: Principles and Practice, 2nd ed., OTexts: Melbourne, Australia (freely available online at https://otexts.com/fpp2)

In addition to the required textbook and those in the reading lists, students are encouraged to read widely including the business section of newspaper, the Economist magazine, and other similar sources. Additional paper resources will be made available on Moodle.

The following websites are examples of Data Analytics being used in practice:

http://fivethirtyeight.com/

https://www.gapminder.org/

Waikato University also has several databases available for students with interests in Finance, which include:

  • NZX Company Research(formerly NZX Deep Archive), which provides historical information on New Zealand Companies
  • Datastreamwhich provides key data sets from both developed and emerging markets. Current and historical data is available variables such as - equities, market indices, company accounts, economic indicators, bonds, foreign exchange, interest rates, commodities and derivatives.
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Online Support

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All course materials, plus other information of importance to students, are available via Moodle
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Workload

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According to the university points system, students are expected to spend 150 hours in total on a 15-point paper. 

Since you are taking a paper in Economics, we know that you will make rational and optimal (to you) decisions about the work you will put into the paper. Thus, the workload the paper places on you will depend on your preferences, what you want to achieve and the constraints you face. 

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Linkages to Other Papers

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Prerequisite(s)

Prerequisite papers: Acceptance into the MPAcct or MAppFin programme.

Corequisite(s)

Equivalent(s)

Restriction(s)

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