Sector-Specific Volatility Patterns in Investment
AbstractThis paper addresses the question if there are differences between time patterns in the volatility of investment across different industrial sectors. A competitive partial-equilibrium model with quadratic adjustment costs in investment and a GARCH demand shock is developed to predict aggregate investment in a sector. It is shown that under the assumptions made in the model, the GARCH property is inherited by the aggregate investment process in the rational-expectations equilibrium. The equation for investment from the model is estimated on quarterly time series from six industrial sectors in the UK. As conjectured, GARCH effects play an important role in some sectors but are not significant in others. Astonishingly, the volatility patterns are in general very different across sectors. This suggests that sector-specific factors are more important in determining investment volatility than the macroeconomic environment.
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Bibliographic InfoPaper provided by EconWPA in its series Macroeconomics with number 0501016.
Length: 15 pages
Date of creation: 12 Jan 2005
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investment; volatility; variance; GARCH; ARCH; sector;
Find related papers by JEL classification:
- E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Capital; Investment; Capacity
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-01-16 (All new papers)
- NEP-ETS-2005-01-16 (Econometric Time Series)
- NEP-MAC-2005-01-16 (Macroeconomics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Cevdet Denizer & Murat Iyigun & Ann Owen, 2000.
"Finance and Macroeconomic Volatility,"
- Denizer, Cevdet & Iyigun, Murat F. & Owen, Ann L., 2000. "Finance and macroeconomic volatility," Policy Research Working Paper Series 2487, The World Bank.
- Cevdet Denizer & Murat F. Lyigun & Ann L. Owen, 2000. "Finance and macroeconomic volatility," International Finance Discussion Papers 670, Board of Governors of the Federal Reserve System (U.S.).
- Tim Bollerslev, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
EERI Research Paper Series
EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
- n/a, 1999. "An Artificial Neural Network System of Leading Indicators," NIESR Discussion Papers 198, National Institute of Economic and Social Research.
- Lucas, Robert E, Jr & Prescott, Edward C, 1971. "Investment Under Uncertainty," Econometrica, Econometric Society, vol. 39(5), pages 659-81, September.
- Sean D. Campbell, 2004. "Macroeconomic volatility, predictability and uncertainty in the Great Moderation: evidence from the survey of professional forecasters," Finance and Economics Discussion Series 2004-52, Board of Governors of the Federal Reserve System (U.S.).
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