8th Annual Conference of the International Association for Applied Econometrics (IAAE)



The mission of the IAAE is to advance knowledge of econometrics, as well as its application in economics. The annual conference brings together leading researchers in the field to discuss and debate all aspects of econometrics, covering both its theoretical development and applied uses. 

The conference is organised and will be hosted by King’s Business School in London from 21 June – 24 June, 2022. 

Platinum Sponsor : Qatar Centre for Global Banking & Finance / Gold Sponsor: King’s Business School



Further information on the conference can be found on the International Association for Applied Econometrics (IAAE) 2022 conference website.  


On June 24 at 10:00am CET, Emanuele ChiniPh.D. in Finance candidate, EDHEC Business School and teaching assistant EDHEC Risk Climate Impact Institute (ERCII), will participate in the Empirical Asset Pricing panel session, together with:

  • Session ProposerAna María Herrera Ph.D., Professor and Associate Chair, Gatton College of Business and Economics
  • Session Chair: Ambroglio Dalo, Assistant Professor, CEMLA and Manager, University of Groningen, Faculty of Economics

Emanuele Chini, EDHEC Risk teaching Assistant "Time-varying Environmental Betas and Latent Green Factors"




Emanuele will present his recent paper "Time-varying Environmental Betas and Latent Green Factors".

Is US stock market pricing exposures to climate risks?

In this paper he tries to answer this question through the lenses of a latent factor model. He extends the instrumented principal component analysis (IPCA) methodology of Kelly et al. (JFE 2019) to extract a green factor. IPCA allows to extract latent factors and their loadings from a panel of returns and a set of observable firm-level characteristics that instrument for the loadings. Indeed, loadings are assumed to be linear combination of the characteristics and this feature of the model helps to interpret the factors.

In his specification he uses both “financial” and “green” characteristics, and he extends the model to allow the presence of different sets of orthogonal factors driven by only one of the two types of characteristics. This methodological extension allows to interpret his factors as purely “green" or “financial" factors.

The main contribution of this paper is that we are able to identify and estimate latent green factors from a large panel of stock returns without defining (and constructing) them ex-ante, as typically done in the climate finance literature.