The idea that certain economic variables are roughly constant in the long-run is an old one. Kaldor described them as stylized facts, whereas Klein and Kosobud labelled them great ratios. While such ratios are widely adopted in theoretical models in economics as conditions for balanced growth,...

Economics places a high premium on completeness of explanation. Typical general-equilibrium accounts of economic phenomena are preferred to partial equilibrium accounts on the ground that important interactions are necessarily omitted in the latter. A similar preference for microfoundational...

On December 5th and 6th 2014, the Stanford Graduate School of Business hosted the Causality in the Social Sciences Conference. The conference brought together several distinguished speakers from philosophy, economics, finance, accounting and marketing with the bold mission of debating scientific...

This study uses firm level data from two detailed surveys of Italian manufacturing firms to study the relationship between R&D expenditures and productivity growth. The analysis considers the different contributions of various forms of R&D (product, process, internal, external in collaboration...

The COVID-19 crisis has been accompanied by an extensive use of indicators, such as those related to COVID infections and deaths but also a good number of COVID policy indicators. This paper discusses these indicators from the perspective of a legal scholar with an interest (and some expertise)...

This paper proposes a new strategy to identify causal effects. Instead of finding a conventional instrumental variable correlated with the treatment but not with the confounding effects, we propose an approach which employs an instrument correlated with the confounders, but which itself is not...

It is well known that efficient estimation of average treatment effects can be obtained by the method of inverse propensity score weighting, using the estimated propensity score, even when the true one is known. When the true propensity score is unknown but parametric, it is conjectured from the...

It is customary to assume that an indicator of a latent variable is driven by the latent variable and some random noise. In contrast, a background indicator is also systematically influenced by variables outside the structural model of interest. Background indicators deserve attention because in...

Randomised controlled or clinical trials (RCTs) are generally viewed as the most reliable method to draw causal inference as to the effects of a treatment, as they should guarantee that the individuals being compared differ only in terms of their exposure to the treatment of interest. This...