Department of Economics2024-11-1020099780-1917-1731-49780-1992-3719-710.1093/acprof:oso/9780199237197.003.00022-s2.0-84919696094http://dx.doi.org/10.1093/acprof:oso/9780199237197.003.0002https://hdl.handle.net/20.500.14288/16922The M2 monetary aggregate is monitored by the Federal Reserve, using a broad brush theoretical analysis and an informal empirical analysis. This chapter illustrates empirical identification of an eleven-variable system, in which M2 and the factors that the Fed regards as causes and effects are captured in a vector autoregression. Taking account of cointegration, the methodology combines recent developments in graph-theoretical causal search algorithms with a general-to-specific search algorithm to identify a fully specified structural vector autoregression (SVAR). The SVAR is used to examine the causes and effects of M2 in a variety of ways. The chapter concludes that while the Fed has rightly identified a number of special factors that influence M2 and while M2 detectably affects other important variables, there is 1) little support for the core quantity-theoretic approach to M2 used by the Fed; and 2) M2 is a trivial linkage in the transmission mechanism from monetary policy to real output and inflation.EconomicsEmpirical identification of the vector autoregression: the causes and effects of us M2Book Chapterhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84919696094anddoi=10.1093%2facprof%3aoso%2f9780199237197.003.0002andpartnerID=40andmd5=25b29236da8d7294b3c813ca840a1c6cN/A12901