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Regular distribution (economics)

Regular distribution (economics) is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Regular distribution (economics) rather than just read about it. In short: Regularity, sometimes called Myerson's regularity, is a property of probability distributions used in auction theory and revenue management. Examples of distributions that satisfy this condition include Gaussian, uniform, and exponential; some power law distributions also satisfy regularity.

Key takeaways

  • Regular distribution (economics) belongs to mathematics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Regular distribution (economics) to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Regular distribution (economics) from memory before moving on to harder problems.

Reference excerpt

Regularity, sometimes called Myerson's regularity, is a property of probability distributions used in auction theory and revenue management. Examples of distributions that satisfy this condition include Gaussian, uniform, and exponential; some power law distributions also satisfy regularity. Distributions that satisfy the regularity condition are often referred to as "regular distributions".

Definitions Two equivalent definitions of regularity appear in the literature. Both are defined for continuous distributions, although analogs for discrete distributions have also been considered.

Concavity of revenue in quantile space Consider a seller auctioning a single item to a buyer with random value v {\displaystyle v} . For any price p {\displaystyle p} set by the seller, the buyer will buy the item if v ≥ p {\displaystyle v\geq p} . The seller's expected revenue is p ⋅ Pr [ v ≥ p ] {\displaystyle p\cdot \Pr[v\geq p]} . We define the revenue function R : [ 0 , 1 ] → R {\displaystyle R:[0,1]\rightarrow \mathbb {R} } as follows:

R ( q ) {\displaystyle R(q)} is the expected revenue the seller would obtain by choosing p {\displaystyle p} such that Pr [ v ≥ p ] = q {\displaystyle \Pr[v\geq p]=q} . In other words, R ( q ) {\displaystyle R(q)} is the revenue that can be obtained by selling the item with (ex-ante) probability q {\displaystyle q} . Finally, we say that a distribution is regular if R {\displaystyle R} is a concave function.

Monotone virtual valuation

For a cumulative distribution function F ( v ) {\displaystyle F(v)} and corresponding probability density function f ( v ) := F ′ ( v ) {\displaystyle f(v):=F'(v)} , the virtual valuation of the agent is defined as

w ( v ) := v − 1 − F ( v ) f ( v ) {\displaystyle w(v):=v-{\frac {1-F(v)}{f(v)}}}

The valuation distribution is said to be regular if w {\displaystyle w} is a monotone non-decreasing function.

Applications

Myerson's auction

An important special case considered by Myerson (1981) is the problem of a seller auctioning a single item to one or more buyers whose valuations for the item are drawn from independent distributions. Myerson showed that the problem of the seller truthfully maximizing her profit is equivalent to maximizing the "virtual social welfare", i.e. the expected virtual valuation of the bidder who receives the item. When the bidders valuations distributions are regular, the virtual valuations are monotone in the real valuations, which implies that the transformation to virtual valuations is incentive compatible. Thus a Vickrey auction can be used to maximize the virtual social welfare (with additional reserve prices to guarantee non-negative virtual valuations). When the distributions are irregular, a more complicated ironing procedure is used to transform them into regular distributions.

Prior-independent mechanism design

Myerson's auction mentioned above is optimal if the seller has an accurate prior, i.e. a good estimate of the distribution of valuations that bidders can have for the item. Obtaining such a good prior may be highly non-trivial, or even impossible. Prior-independent mechanism design seeks to design mechanisms for sellers (and agents in general) who do not have access to such a prior. Regular distributions are a common assumption in prior-independent mechanism design. For example, the seminal Bulow & Klemperer (1996) proved that if bidders valuations for a single item are regular and i.i.d. (or identical and affiliated), the revenue obtained from selling with an English auction to n + 1 {\displaystyle n+1} bidders dominates the revenue obtained from selling with any mechanism (in particular, Myerson's optimal mechanism) to n {\displaystyle n} bidders.

Notes

References

Sources Bulow, Jeremy; Klemperer, Paul (March 1996). "Auctions Versus Negotiations". The American Economic Review. 86 (1). American Economic Association: 180–194.

Worked examples

Example 1 — a first encounter with Regular distribution (economics)

Start with the simplest possible case. Write down what Regular distribution (economics) claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Regular distribution (economics) before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Regular distribution (economics) ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Regular distribution (economics)

In research
Regular distribution (economics) appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Regular distribution (economics) in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Regular distribution (economics) is common in secondary-school and first-year university syllabi. It links to neighbouring topics Auction theory, Mathematical finance, Probability distributions, so understanding it makes those chapters shorter.
In everyday life
Look for Regular distribution (economics) outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Regular distribution (economics) in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Regular distribution (economics) means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Regular distribution (economics) out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Regular distribution (economics) in simple terms?

Regularity, sometimes called Myerson's regularity, is a property of probability distributions used in auction theory and revenue management. Examples of distributions that satisfy this condition include Gaussian, uniform, and exponential; some power law distributions also satisfy regularity.

Why does Regular distribution (economics) matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Regular distribution (economics)?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Regular distribution (economics).

Tags

  • Auction theory
  • Mathematical finance
  • Probability distributions

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