In previous work, we estimated a dynamic model of the Italian economy, showing that its weakness in the past two decades is mainly due to the slowdown in total factor productivity growth. In those models, two parameters play a key role: technological progress and the elasticity of substitution. Recent estimates of those parameters are affected, in our opinion, by a specification problem: technological parameters are inherently long-run but their estimates are based on short-run data. Looking deeply into the estimation procedure, we show that the misspecification issue present in the estimates gives rise to a spurious regression bias (high Rquadro, low DW), because the standard approach does not incorporate frictions and rigidities. Our modeling strategy takes account of them. Although we cannot in general say that our framework gets rid of the serial correlation problem, the statistics for our model do show that residuals are not serially correlated.

Elasticity of substitution and technical progress: Is there a misspecification problem?

FEDERICI, Daniela;
2016-01-01

Abstract

In previous work, we estimated a dynamic model of the Italian economy, showing that its weakness in the past two decades is mainly due to the slowdown in total factor productivity growth. In those models, two parameters play a key role: technological progress and the elasticity of substitution. Recent estimates of those parameters are affected, in our opinion, by a specification problem: technological parameters are inherently long-run but their estimates are based on short-run data. Looking deeply into the estimation procedure, we show that the misspecification issue present in the estimates gives rise to a spurious regression bias (high Rquadro, low DW), because the standard approach does not incorporate frictions and rigidities. Our modeling strategy takes account of them. Although we cannot in general say that our framework gets rid of the serial correlation problem, the statistics for our model do show that residuals are not serially correlated.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11580/59116
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