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Moving Endpoints in Macrofinance

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Author Info
Sharon Kozicki (Federal Reserve Bank of Kansas City, 925 Grand Boulevard)
Peter A. Tinsley () (Federal Reserve Board, Washington)

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Abstract

Much of macroeconomics and finance employs stochastic difference equation descriptions of no-arbitrage or first-order conditions. A problem with empirical implementations of resulting present-values in the intertemporal decision rules and asset valuations of agents is that long-horizon forecasts are heavily influenced by postulated transversality or endpoint conditions. Unfortunately, the short data samples characteristic of macrofinance are unable to empirically reject quite different characterizations of long-run behavior so assumptions about long-run behavior dominate long-term forecasts. Whereas the terminal conditions imposed on real and nominal interest rates in finance typically imply fixed endpoints, those selected in many macrofinance analyses of the term structure are moving endpoints with random walk components. The strong influence of endpoint assumptions is demonstrated for a single state-variable model of bond rates.

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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 1996 with number _058.

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Handle: RePEc:sce:scecf6:_058

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