Technology Shocks, Statistical Models, and The Great Moderation

Fuentes-Albero, Cristina (2007): Technology Shocks, Statistical Models, and The Great Moderation.

Abstract

In this paper we compare the cyclical features implied by an RBC model with two technology shocks under several statistical specifications for the stochastic processes governing technological change. We conclude that while a trend-stationary model accounts better for the observed volatilities, a difference-stationary model does a relatively better job of accounting for the correlation of the variables of interest with output. We also explore some counterfactuals to assess the ability of our model to replicate the volatility slowdown of the mid 1980s. First, we conclude that the stochastic growth model outperforms the deterministic growth model in accounting for the Great Moderation. Finally, we obtain that even though the neutral technology shock is the main driving force in the volatility slowdown, allowing for a larger financial flexibility in the form of a smaller volatility for the investment-specific innovation improves the ability of our model to account for the magnitude of the Great Moderation.

• Item Type: MPRA Paper
• Institution: University of Pennsylvania
• Language: English
• Keywords: Business Cycle; Aggregate fluctuations; Technology Shocks; Unit Roots
• Subjects: O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights > O30 - General; E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E32 - Business Fluctuations ; Cycles; C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models

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