The Use of Instruments in Demand Estimation

See my earlier article on demand estimation for background.

There are two broad approaches to estimating aggregate-level demand: product-space approaches and characteristics-space approaches. Product-space approaches, such as Price Invariant Generalised Logarithmic models and Almost Ideal Demand Systems, treat individual products as the unit of analysis and endeavour to estimate demand functions using restrictions from economic theory. However, these approaches need to estimate N^2 elasticities (considering both own-price and cross-price elasticities), where N is the number of products, hence, even for a modest market with (e.g.) 20 products, over 400 parameters need to be estimated. This is computationally difficult, leading to the curse of dimensionality, and poses a key downside to product-space approaches, along with the detraction that such methods do not allow for the counterfactual estimation of new products being introduced. [...]

How to Estimate Demand

I recently attended a fantastic workshop on demand estimation and have been doing a lot of reading around this topic recently, so wanted to share an outline of the IO story on demand estimation.

Estimating underlying demand functions – that illustrate what happens to quantity purchased when prices change – is useful for a variety of policy analyses, such as estimation of merger control, the introduction of tariffs, welfare effects, product entry etc. In essence, we want to calculate the elasticities which exist between varying products. However, this is not easy, both conceptually and computationally.

To begin with, there is a fundamental problem of endogeneity. [...]