| Course | ECON 1002 Microeconomics |
|---|---|
| Week | Week 10 |
| Paper type | Assumption audit |
| Length | About 880 words, 6 pages |
| Format | APA 7 student paper |
| School | Walden University |
| Program | BS in Business Administration |
| Updated | October 2026 |
Free sample paper for ECON 1002 Week 10
Five Assumptions Behind the Week 2 Used-Bicycle Prediction, Rated Against How Secondhand Sales Actually Work, With Loss Aversion Named as the One That Bends the Prediction Most
Student Name
Walden University
ECON 1002: Microeconomics
Instructor Name
Month Day, Year
Five Assumptions Behind the Week 2 Used-Bicycle Prediction, Rated Against How Secondhand Sales Actually Work, With Loss Aversion Named as the One That Bends the Prediction Most
The Analysis Being Audited
In Week 2 I predicted that when about 6,000 students and new staff arrive in a composite college town in late August, the demand curve for secondhand commuter bikes moves to the right while supply barely moves, so the price rises from about $150 to about $175 and weekly sales rise from forty to about forty-five. That prediction used the standard supply and demand model. Like any model, it rested on assumptions I did not state at the time. This audit lists five, rates how well each holds for secondhand bicycles and says what changes if it fails.
The Audit Table
Table 1
Five Assumptions Behind the Used-Bicycle Prediction
| Assumption | What it says | How well it holds here | What changes if it fails | |
|---|---|---|---|
| Ceteris paribus | Only the arrivals change; everything else stays fixed | Weak: the start of term, autumn weather and a new bike lane arrived together | The price change cannot be attributed to the arrivals alone | |
| Rational choice | Buyers and sellers weigh costs and benefits consistently | Moderate: most buyers compare listings, but many decide in a hurry | Some trades happen at prices the model would not predict | |
| Full information | Buyers know the quality of what they buy | Weak: worn chains and bearings cannot be seen in a photograph | Buyers discount all used bicycles, and good ones are underpriced | |
| Identical goods | All used commuter bicycles are the same product | Weak on paper, but differences average out | Little change to the market price; wide spread of individual prices | |
| Sellers price by value, not history | A seller asks what the bicycle is worth now | Weak: many sellers price against what they paid | Listings sit unsold above the market price; quantity falls short of prediction | |
Ratings are the author's judgment, based on the Week 2 market as described.
Ceteris Paribus
The model asks what happens when one thing changes and everything else stays the same. In late August, several things changed at once: the arrivals, the start of term, autumn weather and a new protected bike lane on the main road to campus. The lane probably raised demand on its own. So the price rise I predicted may be partly correct for the wrong reason, and the size of the rise cannot be pinned on the arrivals alone (Greenlaw et al., 2022).
Rational Choice and Full Information
Most buyers compare a few listings before buying, which roughly fits the rational-choice assumption. Newcomers in a hurry may pay more than they would with time to search, which slightly strengthens the predicted price rise. Full information is the weaker assumption. A buyer cannot see a worn chain, a cracked frame under the paint or a failing bearing from a photograph. Akerlof (1970) showed that when buyers cannot tell good used goods from bad ones, they offer a price reflecting average quality, which drives owners of good goods out of the market. For bicycles, this means the market price may be lower, and the quality of what sells worse, than the model assumes. The refurbishing shop's warranty partly solves this, which helps explain why its bicycles sell at a premium.
Identical Goods
On paper, used bicycles are far from identical: brands, sizes, frame materials and condition all differ. But the prediction was about the market price, and the differences tend to average out across forty sales a week. This assumption is the weakest in description but the least damaging in practice.
Loss Aversion
The standard model assumes that a seller asks what a bicycle is worth today. Many do not. Kahneman and Tversky (1979) found that people feel a loss more strongly than a gain of the same size. A seller who paid $400 for a bicycle three years ago may feel that selling it for $150 is a $250 loss and hold out for $250, even though $150 is what the market will pay. Kahneman et al. (1990) found the same pattern in experiments: people who owned an item demanded about twice as much to give it up as others would pay to acquire it. In the bicycle market this means many listings sit unsold above the market price for weeks.
That changes the prediction. Supply in August is less responsive than the model assumed, because some potential sellers will not lower their asking prices even when the market moves against them, and others who might sell refuse to list at all. So the price could rise a bit more than predicted, and the quantity sold would rise less than five a week. Of the five assumptions, this one bends the prediction most because it affects exactly the side of the market, supply, that the prediction relied on being stable.
What the Audit Means for the Week 2 Prediction
The direction of the prediction survives: the price still rises. Its size is less certain. The rise may partly reflect the bike lane, buyers may face hidden quality problems that hold prices down and sellers anchored to what they paid may hold quantity down. A better prediction would state the direction with confidence and offer a band of likely prices instead of one number.
References
Akerlof, G. A. (1970). The market for "lemons": Quality uncertainty and the market mechanism. Quarterly Journal of Economics, 84(3), 488-500. https://doi.org/10.2307/1879431
Greenlaw, S. A., Shapiro, D., & MacDonald, D. (2022). Principles of microeconomics (3rd ed.). OpenStax. https://openstax.org/details/books/principles-microeconomics-3e
Kahneman, D., Knetsch, J. L., & Thaler, R. H. (1990). Experimental tests of the endowment effect and the Coase theorem. Journal of Political Economy, 98(6), 1325-1348. https://doi.org/10.1086/261737
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291. https://doi.org/10.2307/1914185
The Walden ECON 1002 Week 10 instructions
In Week 10 you audit the assumptions behind an analysis you made earlier in the course. Restate the earlier prediction briefly. Identify at least five assumptions the model relied on, including any you did not state at the time. For each, say what it requires, rate how well it holds in your market and explain what changes if it fails. A table is the clearest format. Then discuss the most important assumptions in more depth, using research where it applies, such as behavioral economics. Close by saying how the original prediction should be revised in light of the audit.
Inside the ECON 1002 Week 10 example
The audit restates the Week 2 prediction. A five-row table rates each assumption and states the consequence of failure. The ceteris paribus section notes that the start of term, the weather and a new bike lane arrived together, citing OpenStax. The section on rational choice and full information explains how hidden wear on chains and bearings leads buyers to discount all used bicycles, citing Akerlof. A short section explains why differences between bicycles average out. The loss aversion section, the longest, applies Kahneman and Tversky and the endowment effect experiments to sellers who hold out above the market price, then explains how this changes supply. The conclusion keeps the direction and widens the range.
Where the marks sit in the ECON 1002 Week 10 rubric
Assumption audits are judged on whether the student identifies the assumptions that matter and assesses them honestly. Listing textbook assumptions without applying them to the market earns little. Each rating should be supported by a feature of the actual market, and each consequence should say how the prediction would change, not just that it might. Strong audits rank the assumptions by their effect on the prediction and spend the most space on the one that matters most. Using research, such as behavioral findings, to support a rating shows depth. The revised prediction should follow from the audit and be more cautious where warranted. The audit should also be honest about the earlier work: admitting that a prediction leaned on a weak assumption is the point of the exercise, not a sign of failure.
ECON 1002 Week 10 help: mistakes that cost marks
Go back to your earlier analysis and, for each step, ask what condition it quietly relied on. Did anything else change at the same time? Could buyers judge quality? Did sellers price by today's value? Write each as an assumption, then ask how well it fits the real market. The assumption that would change the prediction most deserves the longest discussion. Loss aversion and hidden quality are common culprits in used-goods markets. Weak audits copy the textbook list or rate every assumption the same. Send us the analysis you are auditing, and we can identify its key assumptions with you.
Get a ECON 1002 Week 10 example written to your instructions
Send the audit prompt and rubric together with the earlier analysis you are auditing, and the assumptions are drawn from that paper and rated against your market, 24 to 48 hours, the first free. Every seller and buyer in this audit is a composite, and no asking price came from an actual listing.
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ECON 1002 Week 10 questions, answered
Where can I find a free ECON 1002 Week 10 sample paper?
The audit table and every section that follows it are on this page to read freely.
Which assumptions does the ECON 1002 Week 10 audit test?
Ceteris paribus, rational choice, full information, identical goods and sellers pricing by current value rather than what they paid.
Which assumption matters least?
Identical goods: bicycles differ widely, but the differences average out across many sales and barely affect the market price.
Why does loss aversion matter most?
Sellers anchored to what they paid hold listings above the market price, so supply responds less than the model assumed.
How does the audit revise the prediction?
The price still rises, but the size is uncertain and is better given as a band of prices than as one number.