ASSESSMENT EXEMPLAR WITH GUIDE FOR INSTRUCTORS:
REGRESSION ANALYSIS
Topic:
☐ Microeconomics
☐ Macroeconomics
☒ Statistics/Econometrics
Level:
☐ Bachelors
☐ Masters
☒ Both/Either
Core concepts:
Regression analysis, including omitted variable bias (ceteris paribus); crosssectional empirical modelling in line with tenets of economic theory
Learning domains:
☒ Knowledge
☒ Application
☒ Data analysis
☒ Communication
☒ Reflection
Type(s) of task (can be more than one)
☒ Constructed response given stimulus material
(clip/narrative/etc.)
☐ Constructed response with no stimulus material
☒ Quantitative analysis
☐ Independent data sourcing
☐ Independent research (not data sourcing)
☒ Written presentation
☒ Oral presentation
☐ Group collaboration
☐ Use of nominated maths/stats software (specify):
☐ Use of other technology (specify):
☐ Other (specify):
________________________________________
The core statistical concept underpinning this assessment item is regression, and in particular the concept of “ceteris paribus” that is featured in any multiple regression exercise where factors other than the focal variable are held constant. Students are asked to apply analytical techniques to interpret the estimation results from a model of economic variables, and to explain how that model itself reflects economic concepts and principles. The item loads strongly onto students’ interpretational and evaluative skills and also tests their ability to decode the output of a standard statistical package. In discussing weaknesses of the model and the limitations of the conclusions that can be reached confidently based on its results, students are reflecting on the use and power of the model and of the entire exercise. Situating students’ results within the problem of health policy then gives rise to some more reflection-oriented components, and a clear direction to extend the item for Masters students.
The callouts to the learning standards assessed by different components of the items appear in square brackets within the items, and should be removed before the items are used.
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Bachelors level task:
Suppose you have access to data on the birth weights (in ounces) of 1,388 babies born to a sample of American mothers, matched to data on how many cigarettes each mother smoked on average per day during her pregnancy. You use these data to run a regression in Excel of birth weight on cigarettes smoked per day, and you obtain the following results:
(i) Interpret the estimated coefficient on cigarettes smoked. [ KB1 , DB2 ]
(ii) Interpret the intercept in this equation. [ KB1 , DB2 ]
(iii) Suppose that your sister, who lives in Sydney and is going into labour right now, smoked 5 cigarettes per day during her pregnancy. What would you predict her baby’s birth weight to
be based on the above equation? [ DB2 ]
(iv) Suppose tha t your sister is an advocate for smokers’ rights, and believes that in reality there is no effect of maternal smoking on birth weight – or if there is an effect, then it is tiny compared with the effects of many other factors. Can you express tests of these beliefs
using these data? Why or why not? [ AB1 , AB2 , RB1 , CB1 ]
(v) Suppose you also had data on how much the baby’s father smoked during the mother’s pregnancy. Do you think a variable constructed from these data belongs in the equation
above? Why or why not? [ KB1 , AB1 , AB2 , RB1 , CB1 ]
(vi) What caveats apply to your interpretations in parts (a) through (d)? [ RB1 , RB2 , CB1 ]
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Masters level task:
Suppose you have access to data on the birth weights (in ounces) of 1,388 babies born to a sample of American mothers, matched to data on how many cigarettes each mother smoked on average per day during her pregnancy. You use these data to run a regression in Excel of birth weight on cigarettes smoked per day, and you obtain the following results:
(i) Describe how this empirical model relates to the concept of elasticity. [ KM1 , AM1 , CM1 ]
(ii) Suppose that your sister, who lives in Sydney and is going into labour right now, smoked 5 cigarettes per day during her pregnancy. What would you predict her baby’s birth weight to be based on the above equation? How confident are you of this prediction, and why?
[ AM2 , DM2 , RM1 , CM1 ]
(iii) Suppose that your sister is an advocate for smokers’ rights, and believes that in reality there is no effect of maternal smoking on birth weight – or if there is an effect, then it is tiny compared with the effects of many other factors. Can you express tests of these beliefs using these data? If so, state and describe those tests; if not, why not? Based on the
results above, how might you respond to your sister? [ AM2 , DM2 , CM1 , RM1 ]
(iv) Suppose you also had data on the average number of cigarettes smoked per day by the baby’s father during the mother’s pregnancy. If you added this variable to the regression above, what would you predict would happen to the estimated coefficient on mothers’
cigarettes smoked? Why? [ KM1 , AM2 , DM2 , CM1 , RM2 , CM1 ]
(v) Suppose you are developing a policy brief for the state health department that aims to provide an estimate of the total social cost of adult smoking. Based in part on what you have thought about in this question: a. Describe a data collection plan that would yield data you need for this report
[ DM1 , CM1 ]; and
b. Present a research plan in which you describe how you would use these data to
develop an estimate of the total social cost of smoking. [ AM3 , DM1 , CM1 ]
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Advice to assessors
The type of communication used to express the answer to part (v) in the Masters item can be written, which is the default, but could also be oral. Masters students could use part (v) at the basis for a debate about Australian health policy, possibly incorporating a collaborative component if debate preparation occurs within teams, or a role-playing game where different students play the role of The
Economist, The Head of the Health Department, The Smoking Citizen, The Non-Smoking Citizen, and The Tobacco Company Lobby Representative.
Masters students may be given reading material about existing policies in regard to tobacco in order to respond knowledgably to part (v). Such material should be current and drawn from ongoing debates on issues relating to the costs of smoking (e.g., op-eds from The Australian or articles from
The Conversation), and could also include historical reports or articles about smoking prevalence over time or across countries. They could be asked to compare the model or its results to other recent work, in particular to comparable analyses using Australian data (note that the assessment item uses American data) or data from other countries, and reflect upon likely causes for any differences found. For a further extension, they could be tasked with finding Australian data sources that could be used as input into statistical analyses that would help inform policy-setting in this area.
The question frame can be used as a graft for other questions that query students’ skills in evaluating the results of simple regressions for purposes of health policy-setting – for example, an examination of the individual-level association between health measures and exercise, sleep, stress, or other factors, or an examination of the country-level association between health measures and pollution, smoking, democracy, inequality, or other factors.
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Learning domain
Learning outcomes
Bachelor Degree Masters Degree
Knowledge
Application
Data analysis
KB1 Bachelor graduates will be able to identify, coherently explain and synthesise core economic concepts
Bachelor graduates will be able to:
AB1 • frame problems in terms of core economic concepts and principles
AB2 • apply economic reasoning and analytical skills, in order to make informed judgments and decisions
KM1 Masters graduates will be able to identify, coherently explain and synthesise core and advanced economic concepts , including recent developments in the discipline
Masters graduates will be able to:
AM1 • frame and critically analyse problems in terms of core and advanced economic concepts and principles
AM2 • apply advanced economic reasoning and analytical skills, including quantitative techniques where appropriate, in order to make informed judgments and decisions
AM3 • p lan and execute a research-based project
Bachelor graduates will be:
DB1 • able to use economic data to address typical problems faced by economists
DB2 • aware of, and able to implement, basic empirical techniques and interpret the results
Masters graduates will be able to:
DM 1• select and apply an appropriate empirical method to address typical problems faced by economists
DM2
• critically evaluate the results
CM1 Masters graduates will be able to communicate complex ideas clearly and coherently, in written form and interactive oral form to expert and non-expert audiences, individually or in collaborative contexts
Communication CB1 Bachelor graduates will be able to present a clear and coherent exposition of economic knowledge, ideas and empirical evidence both orally and in writing, individually or in collaborative contexts
Reflection Bachelor graduates will be able to reflect on:
RB1 • the nature and implications of assumptions and value judgments in economic analysis and policy
RB2
• interactions between economic thinking and economic events, both historical and contemporary
RB3
• the responsibilities of economists and their role in society
Masters graduates will be able to reflect on and evaluate:
RM 1• the nature and implications of assumptions and value judgments in economic analysis and policy
RM2
• interactions between economic thinking and economic events, both historical and contemporary
RM3
• the responsibilities of economists and their role in society
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