سیاست های پولی همراه با سیگنال از بازار اوراق قرضه

Monetary policy is conducted in an environment of uncertainty. This paper presents a model where the central bank uses real time data from the bond market together with standard macroeconomic indicators to infer the current state of the economy more efficiently, while taking into account that its own actions influence the bond market and therefore what it observes. That the central bank uses the information in the term structure to set policy creates a link between the bond market and the macroeconomy that is novel to the literature. The estimated model suggests that there is some information in US yields of maturities of less than 1 year that can help the Federal Reserve to identify shocks to the economy on a timely basis.

Hayek (1945) famously argued that market economies are more efficient than planned economies because of markets’ ability to efficiently use information dispersed among market participants. In most western economies there is now little planning and almost all prices are determined by market forces without interference from any central authority. However, there is one important exception: the market for short term nominal debt where central banks control interest rates. In the presence of nominal frictions in product or wage markets, this practise can improve welfare by reducing the volatility of inflation and output. Hayek's insight, though formulated in a more general setting of a planned economy, was that even a central bank that shares the objective of the representative agent may not be able to implement an optimal stabilizing policy due to incomplete information. In this paper, the central bank would implement an optimal stabilizing policy if it knew the state of the economy with certainty, and any deviation from optimal policy is due only to information imperfections. Under this assumption this paper demonstrates how the central bank can make use of Hayek's insight and use the market for debt of longer maturities as a source of information that makes a more efficient estimation of the state of the business cycle possible, and thus reduces deviations from optimal policy. That this is close to how some central banks think about and use the term structure is illustrated by a quote by the Chairman (then Governor) of the Federal Reserve Board, Ben Bernanke:

This paper has presented a general equilibrium model of monetary policy where the central bank operates in an uncertain environment and uses information contained in the term structure to estimate the underlying state of the economy more efficiently. This set up creates a link between the term structure and the macroeconomy that is novel to the literature. A movement in the term structure signals that a change in the short term interest rate set by the central bank may be desirable, which when implemented in turn affects aggregate demand. Söderlind and Svensson (1997) warn that “central banks should not react mechanically to [market expectations]” since this may lead to a situation of “the central bank chasing the market, and the market simultaneously chasing the central bank”. This argument is formalized in Bernanke and Woodford (1997) where the authors show that if central banks react to market expectations, a situation with a multiplicity of equilibria or where no equilibrium exists may arise. This paper argues that there may be benefits from systematic reactions to market expectations, but with some important qualifications. The non-existence of equilibria arises in the model of Bernanke and Woodford because the central bank can extract the underlying state perfectly from observing the expectations of the private sector. Inflation will thus always be on target. But if inflation is always on target and private agents only care about accurate inflation forecasts there is no incentive for the private sector to pay a cost to be informed about the underlying shock, and observing expectations will not reveal any information. The model here differs because, to the extent that there is noise in the bond market, the central bank cannot extract the underlying shock perfectly. Thus there will always exist a cost of information gathering that is small enough to make it profitable for the private sector to acquire information about the underlying shock, even if private agents only cared about having accurate inflation forecasts. Additionally, in this model the forecasting problem of private agents involves more than accurately forecasting inflation since bond prices depend on real factors through the stochastic discount factor as well as the price level. In so far as the real discount factor is affected by the underlying state, agents will have an incentive to collect information about it, regardless of the behavior of inflation. Ultimately, the informational content of the term structure is an empirical question. The model presented here provides a coherent framework within which any information about the state of the economy that is contained in the term structure can be quantified in a general equilibrium setting. The model explicitly takes into account that the central bank may use the information in the term structure to set policy and therefore influences what it observes. The model was estimated on US data using Bayesian methods. The empirical exercise suggests that there is some information in the US term structure that allow the Federal Reserve to respond to shocks in a timely manner. Most of the information in the US term structure about the state of the business cycle could be found in yields with maturities of less than one year. That longer maturity bonds are uninformative about the state of the economy is a consequence of the fact that the standard macromodels are not very good at explaining movements in long maturity yields (see for instance Gürkaynak et al., 2005). If a business cycle model is not very good at explaining long yields, then movements in long yields will not be very informative about the current state of the business cycle as defined by the model at hand. There is reduced form evidence that long maturity yields are correlated with the business cycle, with perhaps the most famous link being between an inverted yield curve and the onset of a recession (Harvey, 1993) which suggest that there may be potentially useful information also in the long end of the term structure. However, the link between long term interest rates and optimizing behavior by individual investors is still quite poorly understood. Until a better understanding of what drives long rates is achieved, we may have to settle for looking at the short end of the yield curve to find clues about the current state of the business cycle that we can interpret using structural microfounded models.