<p>Agglomeration economies is a large concept that includes any effect that increases firms' and workers' income when the size of the local economy grows.</p>
<p>The general idea is to estimate the overall impact of density on a local characteristic, such as the impact of local employment density on local productivity. The density estimate captures the agglomeration effect.</p>
<p>As a naive example <strong>to operationalize the concept of agglomeration economies</strong>, consider the following specification:
<span class="math-container">$$Y_c = \alpha Density_c + \beta Skills_c + \epsilon_c$$</span>
where <span class="math-container">$Y_c$</span> is a measure of the local outcome in a city <span class="math-container">$c$</span>, say the logarithm of local wage, <span class="math-container">$Density_c$</span> is the logarithm of density, <span class="math-container">$Skills_c$</span> captures local skills and <span class="math-container">$\epsilon_c$</span> is the error term. If there is no correlation between the random component and explanatory variables, then the ordinary least squares estimate of the elasticity of productivity with respect to density (<span class="math-container">$\beta$</span>) is a consistent measure of total net agglomeration economies. For instance, a value for the elasticity of the local outcome with respect to density of 0.03 means that a city twice as large (knowing that a factor of 10 is often obtained for the interquartile
of local density in many countries) has <span class="math-container">$2^{0.03} - 1 = 2.1\%$</span> greater productivity,
because of either pure local externalities or market agglomeration effects that dominate dispersion effects of any kind.</p>
<p>You will find much more, including a discussion of the mechanisms, in Chapter 5 of the Handbook of Urban and Regional Economics, <a href="https://www.elsevier.com/books/handbook-of-regional-and-urban-economics/duranton/978-0-444-59517-1" rel="nofollow noreferrer">The Empirics of Agglomeration</a>.</p>

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2021-01-03T09:23:06.550Z
2021-01-03T20:40:17.963Z
2021-01-03T20:40:17.963Z
emeryville
<p>How most common way to operationalize the concept of agglomeration economies? I am new in research field. I even don't know what conceptual definition means.</p>

CC BY-SA 4.0
2020-11-24T18:13:53.490Z
It means that the whole is greater than the sum of its parts. Something happens when individuals or firms come together. There are examples everywhere, New York City; London; Silicon Valley. Typically the argument stands that there is something like increasing returns to scale. Therefore you'll often see someone like Paul Romer link his work on endogenous growth to agglomeration.
EB3112
<urban-economics>
How to operationalize agglomeration economies?
Anonymous M
# How to operationalize agglomeration economies?

(Asked by: username_0 on 2020-11-24)

How most common way to operationalize the concept of agglomeration economies? I am new in research field. I even don't know what conceptual definition means.

**Tags:** urban-economics
> **Comments:**
> **username_1**: It means that the whole is greater than the sum of its parts. Something happens when individuals or firms come together. There are examples everywhere, New York City; London; Silicon Valley. Typically the argument stands that there is something like increasing returns to scale. Therefore you'll often see someone like Paul Romer link his work on endogenous growth to agglomeration.  

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## 1 answers

### Answer by username_2 on 2021-01-03. Score: 3 | Accepted answer

Agglomeration economies is a large concept that includes any effect that increases firms' and workers' income when the size of the local economy grows.

The general idea is to estimate the overall impact of density on a local characteristic, such as the impact of local employment density on local productivity. The density estimate captures the agglomeration effect.

As a naive example **to operationalize the concept of agglomeration economies**, consider the following specification:
$$Y\_c = \alpha Density\_c + \beta Skills\_c + \epsilon\_c$$
where $Y\_c$ is a measure of the local outcome in a city $c$, say the logarithm of local wage, $Density\_c$ is the logarithm of density, $Skills\_c$ captures local skills and $\epsilon\_c$ is the error term. If there is no correlation between the random component and explanatory variables, then the ordinary least squares estimate of the elasticity of productivity with respect to density ($\beta$) is a consistent measure of total net agglomeration economies. For instance, a value for the elasticity of the local outcome with respect to density of 0.03 means that a city twice as large (knowing that a factor of 10 is often obtained for the interquartile
of local density in many countries) has $2^{0.03} - 1 = 2.1\%$ greater productivity,
because of either pure local externalities or market agglomeration effects that dominate dispersion effects of any kind.

You will find much more, including a discussion of the mechanisms, in Chapter 5 of the Handbook of Urban and Regional Economics, [The Empirics of Agglomeration](https://www.elsevier.com/books/handbook-of-regional-and-urban-economics/duranton/978-0-444-59517-1).


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