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The Business Cycles Implications of Fluctuating Long Run Expectations

Daniel Tortorice ()

No 100, Working Papers from Brandeis University, Department of Economics and International Businesss School

Abstract: I consider a real-business cycle, DSGE model where consumption is a function of the present discounted value of wage and capital income. The agent is uncertain if these income variables are stationary or non-stationary and puts positive probability on both representations. The agent uses Bayesian learning to update his probability weights on each model and these weights vary over time according to how well each model ts the data. The model exhibits an improved t to the data relative to the rational expectations benchmark. The model requires half the level of exogenous shocks to match the volatility of output and still matches the relative volatilities of key business cycle variables. The model lowers the contemporaneous correlation of consumption and wages with output and generates positive autocorrelation in model growth rates. Impulse responses exhibit persistent responses and consistent with survey evidence forecast errors are positively serially correlated. Finally, in contrast to the existing literature, the model endogenously generates observed time varying volatility and long run predictability of business cycle variables, especially for investment.

Keywords: Business Cycles; Investment; Learning (search for similar items in EconPapers)
JEL-codes: D83 E22 E32 (search for similar items in EconPapers)
Pages: 50 pages
Date: 2016-01
New Economics Papers: this item is included in nep-dge and nep-mac
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http://www.brandeis.edu/economics/RePEc/brd/doc/Brandeis_WP100.pdf (application/pdf)

Related works:
Journal Article: The business cycle implications of fluctuating long run expectations (2018) Downloads
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