Economics researchers awarded 2023 SSHRC Insight Grants

Bertille Antoine

Identification, estimation, and inference of dynamic causal effects in macroeconomics

Dynamic causal effects are traditionally understood as the effects, over time, of an intervention - or unexpected shock - that spread through the economy: quantities of interest include impulse responses as well as various measures of causality. 

Accurately identifying and estimating these dynamic causal effects is important as they are often used to evaluate the effectiveness of interventions such as, for example, a given monetary policy.

Following an approach that has proven highly productive in modern micro-econometrics, the use of "external instruments" has opened a rapidly growing research avenue in macro-econometrics. In this approach, dynamic causal effects are identified using as-if random variation in the shock of interest in local projection models. Such constructed measures hold out the potential for more credible identification than provided in standard models. However, they are also associated with new challenges which we aim to tackle here.

In this project we aim to develop new econometric frameworks and methods designed to target key quantities relevant for macro-economic policy work. We build on the features of local projection models that have led to their popularity while avoiding reliance on others that are unnecessarily restrictive.

Our key technical innovations will exploit the validity of the instrument in a flexible way to enhance the extent and quality of information that can be extracted from the data.

Lucas Herrenbrueck

Crypto 'Money': Medium of Exchange, Store of Value, or Object of Speculation?

This joint project with Zijian Wang (Wilfrid Laurier University) aims to improve our understanding of cryptocurrencies by focusing on an understudied but increasingly important phenomenon, their financialization. Although cryptocurrencies are designed to be decentralized in nature, the vast majority of actual transactions are conducted through large, centralized trading platforms such as Coinbase and Binance.

The goal of Herrenbrueck and Wang’s project is to better understand the impact of these exchanges on cryptoasset prices (and price volatility), the adoption of cryptoassets as payment instruments and financial stability.

To achieve this they will develop mathematical and computational models and calibrate them to generate price dynamics similar to those found in data. This will help determine the relative importance of fundamental shocks, heterogeneous beliefs, and limited rationality and provide insights into what kinds of government intervention could be helpful or harmful.