Decoding Economic Consulting: The work we do on a daily basis

Economic consulting work makes use of academic literature and microeconomic theory extensively quite a lot in their work. It is one of those rare fields of work where you actually get to use what you learnt in the university very often, even on a day-to-day basis. Industrial organization is the most applied stream of microeconomics in these jobs, but wider microeconomic theory as well as game theory is also used for different projects as required. And econometrics is of course the bread and butter for economic consulting jobs, and is extensively used for quantitative analysis. And along with application of economic theories and methodologies, a lot of data processing is involved in the job as well. We will try and get into the details of each here.

Theoretical Components

For most of the reports that we make (including expert testimony reports, merger reports, market research and many others), theoretical foundations are what decides the arguments, structure and methodologies. Crucial areas that constitute the theoretical framework include market definition, scoping out the competitive landscape of the industry and also coming up with a sound theory of harm.

There are many different theoretical frameworks for solving the same problem, and the choice of the framework depends on the problem at hand, the industry, the competitive landscape in the industry etc. The availability of data can also be a crucial concern while building these theoretical foundations, as an empirical model of the theoretical argument is often helpful and even seen as necessary in some cases. These empirical models are usually very simple at the beginning stages of the projects, but as the project evolves, and more data becomes available (through production by the opposition, or data from entities for a merger for example) which allows for more elaborate theoretical models which can be empirically modelled as well. But crucially, all the empirical models including analysis methodologies for identifying counterfactuals and calculation of damages must be supported by solid theoretical arguments.

Quantitative Work: Data

Often during these engagements, by the time the law firm or the client approaches an economic consultant, they would have already made an initial hypothesis on the problem at hand, and also would have already made a hopeful prediction on the issue. For example, when a law firm is arguing for the final consumers at the plaintiff side against a cartel formed by a group of companies - in this example, the law firm has already made a hypothesis and prediction that the implementation of the cartel has increased prices for the consumers, and thus caused harm to these consumers. The role of the economists at that stage is usually to formalize this hypothesis using theoretical frameworks, supported by proper research and test that hypothesis with available data using the most appropriate quantitative methods to solve that problem.

In doing that, identifying the data sources you need to solve that problem is the first step. This is especially crucial and complicated when you are requesting the data from the opposition side (or any external non-participant in the case). These data exchanges are rarely generous, as it is often an expensive process for the opposition or non-participant to produce this data especially to the requirements made in the such requests. So as an economist, you need to make sure that you make the right asks from the start itself, and be aware of what compromises can be made if the data request process is subject to negotiations by the providing entity. And once these data is produced by them, it is very difficult to go back and ask for more especially if these have not been laid out to them in the requests made in the beginning itself.

Data cleaning is also a large step in this data side of things. The cleanliness of the data provided can vary largely between entities. Some data might be easy and clean to use straight away, while some others might need extensive careful scrutinization, followed by complicated data cleaning pipelines. So data cleaning is an extremely important skill for any economic consultant who has to work with any form of data.

Quantitative Work: Methodologies and Analysis

Using the data, the next step is evaluating the effects of the implications laid out in the theoretical economic arguments. This could include implications on the market, the competitive landscape or damages resulting from the harm caused by the anticompetitive conduct.

In most cases, finding a counterfactual or what is commonly referred to as the "but-for" world is a key component in most of such analysis. The idea is to identify a world where the conduct under scrutiny did not happen, and what such a world would look like in terms of the economic arguments made compared to the real world. Different methods are used for this including comparative methods, cost-basis methods and theoretical simulation models.

1. Comparative methods - For a simplistic explanation, comparative methods are comparing the real world to a but-for world, which is actually present in the real world in some shape or form. For example, to see the effect of a conduct in one country, a comparison can be made between that country and a "similar" country where such a conduct has not happened. This is one of the most intuitive methods, but also one of the most difficult to justify.
2. Cost-Basis methods - This usually deals with the idea of a "reasonable margin" that an organization should be getting compared to the actual margin that the company under scrutiny gets. This reasonable margin can be obtained by understanding the costs of production, and the general margin levels in the industry derived by other potentially competing companies.
3. Theoretical Simulations - This method deals with making theoretical simulations of the "ideal" market with the support of supply and demand models using observed data on prices, volume and costs to predict market outcomes.

Econometric models applied on available data is the main tool of analysis for most of these cases. Many econometric models are used, including regression analysis, difference-in-differences and instrumental variables. The simpler the model is, the better as these models need to by understood by judges deciding on these cases who even though understands the basic concepts of economics, might not have knowledge of more nuanced analysis methods with less interpretability.

Quantitative Work: Programs Used

The programs used to perform the econometric analysis has seen some change over the past few decades. But in most cases, the adoption of newer technologies or more complicated or streamlined software is not that quick in the field of economic consulting compared to other technology applications.

The early 2000s used SAS as their primary program for analysis which was later overtaken by Stata to become the primary software for most economic analysis by professionals and academics. Now R and Python are also used across the industry, and excel still remains an indispensable tool for a lot of the data work. While programming skills required for an economic consultant is not at the level as required by the tech industry jobs, most new recruits become good coders for quantitative data analysis in the first two years of their jobs.

SQL is also a prominent language used especially when dealing with large terabytes sized datasets - although this is very rare. I've had to learn SQL for such massive projects, so it does happen even though rarely.

Qualitative Work: Research and Expert Reports

All the quantitative work that we discussed above needs to be backed by solid theoretical and research foundations. Extensive research is required in all cases before putting pen to the paper to formulate theoretical and empirical methodologies. This is especially important in the qualitative elements such as understanding the technicalities and unique aspects of specific markets that the case relates to. Most of this information is available from public sources and services like Bloomberg and S&P which are commonly used by economic consultants. Bloomberg is especially used in securities and financial litigation projects. Research is also important in collecting public data where the opposition data is not available yet, especially in the earlier stages of the engagement.

The quantitative analysis and research needs to be finally put into a report to be presented to the clients and the court. If it is a litigation case that is in court to be decided by a judge, the economist submits an expert report with detailed report of their data, research, methodologies and findings. In most cases the opposition also submits such a report in support of the opposition's claims. And in most cases these reports will be subject to scrutiny by the opposition during the course of the engagement, and we will also do the same with the opposition report.

Well, hopefully that gives you a general idea of what the day-to-day work looks like for an economic consultant. While there can be deviations from this, especially in niche consulting engagements, most of these work stages are still applicable generally throughout the industry. Hope you learned something about the work-life of an economic consultant from this!

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