Ashley Hodgson · Economics Explained
Search Costs in Economics
Finding a match in a market takes time, effort, and money — and those search costs shape everything from hiring decisions to how long a job sits unfilled. Ashley Hodgson explains why the friction of finding is itself an economic force.
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The problem
Markets don’t self-assemble — buyers and sellers must find each other, and that search costs real resources
Standard price theory talks about supply and demand meeting at a clearing price, but it largely skips over the messy question of how suppliers and demanders actually find each other in the first place. In the real world, workers spend weeks sending applications; employers post job ads and run interviews for months. None of that is free. Search costs — the time, money, and effort spent locating the right match — are a genuine economic variable that affects how markets work and how resources get allocated.
Hodgson introduces search costs through the labour market, the canonical example. Workers are searching for jobs. Employers are searching for workers. Both sides want the optimal match: the worker who fits the role, the firm that fits the career. The friction between the two sides — resumes sent, interviews run, positions left open — is not a rounding error. It is a real cost embedded in every hire.
“who is searching for what — the suppliers and demanders searching for each other”
“what are search costs in economics like who is searching for what what are we talking about and who is doing the searching is the suppliers and the demanders in some market who are searching for each other they’re searching for some kind of match that is the optimal match for them and the classic example of course is workers searching for jobs where the workers are on one side and the firms are on the other side.”
What makes this framework useful is that it applies far beyond hiring. Dating markets, housing markets, online platforms matching buyers and sellers — anywhere one side of a market must search for the other, these costs appear. The structure is always the same: a searcher evaluates options sequentially or in batches, each evaluation costs something, and stopping too soon or too late both carry a price.
How they solve it
The optimal stopping problem: search until the marginal cost of one more interview equals the marginal benefit
Hodgson walks through a hiring scenario to make the economics precise. An employer has interviewed three candidates and found a good one. Should they interview a fourth? The cost of interviewing a fourth is real — the recruiter’s time, any productivity lost from keeping the position open another week, and the administrative overhead of an additional evaluation. The benefit is the probability that candidate four is better than the best of the first three, multiplied by how much better they might be.
“what kinds of productivity is lost from keeping that job open”
“not having the position filled and what kinds of productivity is lost from keeping that job open but there’s a benefit to interviewing a fourth and that could be well we could find someone who’s better than the first three so even though the chances that number four is better than the best of the first three that’s going to be less than um the certainly than interviewing the... so there’s a tradeoff.”
As the number of interviews grows, the probability of finding someone meaningfully better than the current best candidate drops. At some point — the economically optimal stopping point — the expected gain from another interview falls below its cost, and the rational employer should stop and hire. This is not a formula with a universal answer; the optimal number of searches (economists call it n*) depends on the specific costs and potential gains in each situation. But the framework tells you what to measure and where the tradeoff lives.
Hodgson also addresses how technology reshapes these costs. Online marketplaces compress search costs significantly: a job board lets an employer see hundreds of applicants in the time it used to take to collect a handful of paper resumes. But technology helps more with quantitative matching than qualitative. When what you need is legible — a specific certification, a years-of-experience threshold — search costs fall sharply. When the match is qualitative — cultural fit, creative judgment, collaborative style — the search remains expensive and uncertain regardless of the platform.
“the more qualitative and unmeasurable something is, the more difficult”
“super expensive ideally you can go online and get ideally good information from the online marketplace and similarly with job searches having online tools that help match resumes to open jobs can help with that process but the more qualitative and unmeasurable something is in terms of what you’re looking for in a good match um the more difficult and more uncertainty you’re going to have to build into your models.”
The broader insight is that search costs are not just a tax on transactions — they are a structural feature of markets that affects prices, wages, and how long resources sit idle. A worker willing to accept a lower wage at the first offer rather than keep searching is making a rational choice given high search costs. An employer who leaves a position open for six months is betting that the eventual match will justify the ongoing vacancy cost. Neither is irrational; both are responding to the same underlying friction.
Takeaway
The quick version
- Search costs — time, effort, and money spent finding a match — are real economic variables, not background noise.
- The optimal stopping point (n*) is where the expected benefit of one more search equals its cost; that number varies by context.
- Technology compresses search costs for quantifiable matches but does little for qualitative ones.
- Unresolved search costs show up as wages below potential, vacancies held open too long, and inefficient resource allocation.
“The more qualitative and unmeasurable something is in terms of what you’re looking for in a good match, the more difficult and more uncertainty you’re going to have to build into your models.”— Ashley Hodgson, Ashley Hodgson YouTube
Search costs are invisible on a balance sheet but present in every hire, every unfilled role, and every candidate who settles too soon. Knowing they exist — and that they have an optimal stopping point — is the first step to managing them deliberately.