The possibility to measure the relative contribution of agents and exchanges to the price formation process in high-frequency financial markets acquired increasingly importance in the financial econometric literature. In this paper I propose to adopt fully data-driven approaches to identify...

The possibility to measure the relative contribution of agents and exchanges to the price formation process in high-frequency financial markets acquired increasingly importance in the financial econometric literature. In this paper I propose to adopt fully data-driven approaches to identify...

The size of the economy-wide rebound effect is crucial for estimating the contribution that energy efficiency improvements can make to reducing greenhouse gas emissions and for understanding the drivers of energy use. Existing estimates, which vary widely, are based on computable general...

This paper introduces a little known category of estimators - Linear Non-Gaussian vector autoregression models that are acyclic or cyclic - imported from the machine learning literature, to revisit a well-known debate. Does exporting increase firm productivity? Or is it only more productive...

The size of the economy-wide rebound effect is crucial for estimating the contribution that energy efficiency improvements can make to reducing greenhouse gas emissions and for understanding the drivers of energy use. Existing estimates, which vary widely, are based on computable general...

This paper introduces a little known category of estimators - Linear Non-Gaussian vector autoregression models that are acyclic or cyclic - imported from the machine learning literature, to revisit a well-known debate. Does exporting increase firm productivity? Or is it only more productive...