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Lectures in open economy macroeconomics, (2009)

by M Uríbe
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Robustness, Information-Processing Constraints, and the Current Account in

by Yulei Luo , Jun Nie , Eric R Young , Paul Bergin , Larry Qiu , Kevin Salyer , Tom Sargent , Ulf Söderström , Lars Svensson - Small Open Economies,” Journal of International Economics , 2012
"... Abstract We examine the effects of two types of informational frictions, robustness (RB) and finite information-processing capacity (called rational inattention or RI) on the current account, in an otherwise standard intertemporal current account (ICA) model. We show that the interaction of RB and ..."
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Abstract We examine the effects of two types of informational frictions, robustness (RB) and finite information-processing capacity (called rational inattention or RI) on the current account, in an otherwise standard intertemporal current account (ICA) model. We show that the interaction of RB and RI has the potential to improve the model's predictions on the joint dynamics of the current account and income: (i) the contemporaneous correlation between the current account and income, (ii) the volatility and persistence of the current account in small open emerging and developed economies. In addition, we show that the two informational frictions could also better explain consumption dynamics in small open economies: the impulse responses of consumption to income shocks and the relative volatility of consumption growth to income growth. Calibrated versions using detection probabilities fit the data better along these dimensions than the standard model does. JEL Classification Numbers: C61, D81, E21.

Federal Reserve Bank of Kansas City

by Yulei Luo, Eric R. Young , 2014
"... This paper studies the aggregate dynamics of durable and nondurable consumption under slow information diffusion (SID) due to noisy observations and learning within the permanent income framework. We show that SID can significantly improve the model’s predictions on the joint behavior of income, dur ..."
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This paper studies the aggregate dynamics of durable and nondurable consumption under slow information diffusion (SID) due to noisy observations and learning within the permanent income framework. We show that SID can significantly improve the model’s predictions on the joint behavior of income, durable consumption, and nondurable consumption at the ag-gregate level. Specifically, we find that SID can significantly improve the model’s predictions for: (i) smoothness in durable and nondurable consumption, (ii) autocorrelation of durable con-sumption, and (iii) contemporaneous correlation between durable and nondurable consump-tion. Furthermore, we discuss that incorporating a fixed cost into our SID model does a better job of reproducing the infrequent adjustments of durable consumption at the individual level and the slow adjustments at the aggregate level.

Robustness, information–processing constra open economies☆

by Yulei Luo A, Jun Nie B, Eric R. Young C
"... e e inty e c the contemporaneous correlation between the current account and income and response of consumption to income and the relative volatility of consumption to income growth. © 2012 Elsevier B.V. All rights reserved. he inte nant of national saving, and the balance of national saving in exce ..."
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e e inty e c the contemporaneous correlation between the current account and income and response of consumption to income and the relative volatility of consumption to income growth. © 2012 Elsevier B.V. All rights reserved. he inte nant of national saving, and the balance of national saving in excess of capital market and optimal consumption is determined by permanent
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...d.6 Note that in the data the current account is countercyclical with real GDP and more countercyclical in the emerging economy. (For example, see Neumeyer and Perri, 2005; Aguiar and Gopinath, 2007; =-=Uríbe, 2009-=-). Second, they cannot generate low persistence of the current account.7 The standard RE models predict that the current account and net income have the same degree of persistence, whereas in the data...

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