Question

4. Give an example of one of the ways we can empirically measure agglomeration. What does that measure tell us, and why might it be problematic?

Answer 1

Agglomeration in dictionary terms mean merging of things . One of the common example of this is when two firms cluster together . This clustering of firms (or industries) result into reduction in transportation costs, coordination in sales , ease in product design etc. Also ,helping clustered firms to share knowledge and ideas more easily hence optimizing each labor's (working in these firms) efficiency as well as productivity . But the effects of agglomeration ultimately depends upon the extent of agglomeration. And this is where ,the concept of agglomeration index comes into the picture. This index is used to measure these returns which are expected from agglomeration of industries. However.it has been identified that such measurement is difficult to find and if found then it must have properties like -it should be comparable across industries; it should control for overall agglomeration across industries ; should be justified by a suitable model etc.

Empirically, the effect of agglomeration on technology spillover,transport cost ,labour correlation can be shown using the following equations: (Equations are there in the image attached)

The Equation1 represents EG index. Here the dependent variable is 'Y' measures the extent of agglomeration of two firms.(This index is based on the physical location of the firms)

Accordingly,equation 2 gives the colocation index which tells us the extent to which two sectors say sector 1 and sector 2 are located.It ranges between 0 & 1 .

Equation 3 measures the absolute colocation.This equation calculates the count of number of firms located in sector 1 that are located in same area as firms in sector 2.

It should be noted that above three equations are from the theory point of view , These measures the EG index .Result from which can be compared with the result obtained from equation 4(explained below)

Hence the empirical model is represented by equation 4 : All the variables used in equation 4 will be transformed to same unit .Using this euation we can find the coefficients for each of the independent variable ,giving us the relative importance of each independent variable in explaining agglomeration patterns.

And from the results obtained from econometric modelling,we can conclude that out of these four independent variables( Input-ouput linkages,costcolocation,technology transfers, skills enhancement etc.) which are significant and which are not with respect to agglomeration.

CHALLENGES: The above empirical method is taking into account only four measures .Understanding the driving factors behind agglomeration is a challenging task.Also the result for developed countries would differ when comapred to developing countries.