Identification in Macroeconomics

My proposed thesis focuses on estimating the causal effects of
macroeconomic policies, particularly monetary policy. This question is central
to the study of modern dynamic macroeconomics and has direct relevance for
policy making. The literature to-date has been heavily influenced by a
particular conceptual framework, under which the notion of a "causal effect" is
explicitly defined in terms of the effect of a "shock" - that is, an unanticipated,
autonomous change linked to some specific source. My thesis would seek to
challenge this conceptual framework, taking inspiration instead from
frameworks typically used in other areas of economics and social sciences
where causality is defined in terms of counterfactuals. I plan to do this through
a combination of statistical theory to prove the deficiencies in the
"shock-based" conception of causality, as well as through various effective
empirical applications highlighting the insights that can be gained through
conceiving of causality as counterfactuals.
My research work to-date has already sought to do just that. In particular, as
part of an ongoing project, I have developed a number of proofs to highlight the
problems associated with a specific application of the "shock-based" approach
in which one attempts to estimate the causal effect of policy by controlling for
confounding factors that simultaneously drive policy decisions and outcome
variables of interest. I plan to build on this work for the DPhil.
First, I plan to develop similar proofs to highlight that similar issues arise with
the "shock-based" approach in other settings (i.e. other than ones in which
practitioners attempt to control for confounding factors). Second, I plan to
demonstrate insights that can be garnered through alternate approaches
through applied work with a focus on estimating the effect of monetary policy (a
defining challenge in the literature to-date). For example, I hope to revisit
estimates of the extent to which central banks...