Difference-in-discontinuities method

This post will review the econometric method of difference-in-discontinuities design, outlining the technical details, the strength and weaknesses, and provide an intuitive explanation for how this method can be used to identify causal effects of a treatment policy. In doing so, we will refer to its application in Ferguson and Kim (2023). Firstly, we outline the empirical question posed by Ferguson and Kim (2023) and discuss some potential ways of answering this question, to then motivate the use of the difference-in-discontinuities design approach.

Ferguson and Kim (2023) apply the difference-in-discontinuities technique to answer the question of whether a policy of decentralised agricultural production (called the Household Responsibility System or HRS) can causally explain the increase in agricultural yields seen in China in the late 1970s and 1980s. [...]

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. [...]

The Difference-in-Difference Revolution

I don’t often post about econometric topics, as I am not an econometrician, but as an applied microeconomist, I have been reading a lot about the difference-in-difference revolution and the new approaches taken to deal with staggered adoption. As the best way to learn something is to teach it, I thought I’d write a blog post explaining my understanding of the problem and the various solutions available. As I am not an econometrician, I will be mainly explaining this through intuition and will add links to the various sources for those interested in a deeper dive on the technical details.

The Problem

For a long time, empiricists would use the two-way fixed effects estimator to estimate linear regressions of interest on a panel dataset of interest. [...]

Interpreting regression coefficients

In this article I will explain how to interpret regression coefficients when dealing with variables that have been logged.

Why would we work with logged variables? Firstly, we might take the log of a non-linear model, to make it linear in parameters, to satisfy the Gauss-Markov assumptions (these are required for the OLS method of estimation to be the BLUE – the best linear unbiased estimator). Secondly, as we will see below, it can sometimes be easier to interpret coefficients which have been logged, as we can talk about percentage changes, which might make more sense than talking about unit changes, in some contexts. [...]