Technology Shocks, Structural Breaks and the Effects On the Business Cycle

Abstract In this paper, we analyse the volatility of US GDP growth using quarterly series starting in 1875. We find structural breaks in volatility at the end of World War II and at the beginning of the Great Moderation period. We show that the Great Moderation volatility reduction is only linked to changes in expansions, whereas that after World War II is due to changes in both expansions and recessions. We also propose several methodologies to date the US business cycle in this long period. We find that taking volatility into account improves the characterization of the business cycle.

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IMPERFECT TRANSMISSION OF TECHNOLOGY SHOCKS AND THE BUSINESS CYCLE CONSEQUENCES

Macroeconomic Dynamics ◽

10.1017/s1365100512000454 ◽

2012 ◽

Vol 18 (2) ◽

pp. 418-437 ◽

Cited By ~ 3

Author(s):

Hamilton B. Fout ◽

Neville R. Francis

Keyword(s):

Business Cycle ◽

American Economic Review ◽

Two Dimensions ◽

Adjustment Cost ◽

Temporary Increase ◽

Technology Shocks ◽

Initial Wealth ◽

Technology Shock ◽

The Business Cycle ◽

Sustained Increase

We investigate the business cycle effects of imperfect transmission of technology shocks within a basic real business cycle (RBC) model along two dimensions. First, we assume that agents cannot distinguish a temporary increase in productivity growth from a sustained increase in the underlying growth rate of productivity and instead must conduct signal extraction exercises and update beliefs about the source of aggregated shocks. Second, we propose a technology adjustment cost resulting in the slow diffusion of technological innovations into the production process. Both of these impediments to the transmission of technology result in a large initial wealth effect, increasing investment and hours less, relative to the usual RBC model without these frictions. Furthermore, each of these features is capable of producing a decline in hours on impact of the technology shock matching the negative response in hours found in the data by such works as Gali [American Economic Review89(1), 249–271 (1999)].

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Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?

The American Economic Review ◽

10.1257/aer.89.1.249 ◽

1999 ◽

Vol 89 (1) ◽

pp. 249-271 ◽

Cited By ~ 782

Author(s):

Jordi Galí

Keyword(s):

Simple Model ◽

Business Cycles ◽

Business Cycle ◽

Monopolistic Competition ◽

Real Business Cycle ◽

Technology Shocks ◽

Aggregate Fluctuations ◽

G7 Countries ◽

Technology Shock ◽

The Business Cycle

I estimate a decomposition of productivity and hours into technology and non-technology components. Two results stand out: (a) the estimated conditional correlations of hours and productivity are negative for technology shocks, positive for nontechnology shocks; (b) hours show a persistent decline in response to a positive technology shock. Most of the results hold for a variety of model specifications, and for the majority of G7 countries. The picture that emerges is hard to reconcile with a conventional real-business-cycle interpretation of business cycles, but is shown to be consistent with a simple model with monopolistic competition and sticky prices. (JEL E32, E24)

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Decomposition of the Business Cycle Shock and the Default Rate of SMEs in Korea

Journal of Derivatives and Quantitative Studies ◽

10.1108/jdqs-04-2019-b0002 ◽

2019 ◽

Vol 27 (4) ◽

pp. 401-423

Author(s):

Jaesung James Park ◽

Joonkyo Hong ◽

Sumi Na

Keyword(s):

Business Cycle ◽

Capital Accumulation ◽

Structural Var ◽

Technology Shocks ◽

Empirical Results ◽

Long Run ◽

Default Rate ◽

Technology Shock ◽

The Business Cycle ◽

The Impact

This paper, through a structural VAR identified by a long-run restriction which is imposed by a neoclassical growth model, decomposes the real price index of capital accumulation (= deflator for fixed capital accumulations/consumption expenditure deflator), labor productivity (= real GDP/total employee hours), and total employee hours into three business cycle shocks: (i) investment-specific technology shock, (ii) neutral technology shock, and (iii) non-technology shock, and explores which shock has played a significant role in contributing to decreases in the default rate of SMEs. Empirical results drawn from Korean data spanning from 2000:Q1 to 2016:Q2 indicate that when the two technology shocks arise by 1%p, the default rate decreases by 0.03%p to 0.05%p permanently. In contrast, the impact of the non-technology shock on the default rate is highly transitory : the default rate decreases by 0.02%p in response to the 1%p increment in non-technology shock but turns back to its initial level after about three quarters. These imply the technology shocks could account for the most of variations in the default rate of SMEs. Our empirical results, therefore, deliver the policy implication that SME financing should focus on innovative firms with aggressive funding.

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