List of References
Collecchia, A. and P. Schreyer, 2001, “ICT Investment and Economic Growth in the 1990s: Is the United States a Unique Case? A Comparative Study of Nine OECD Countries,” STI Working Paper, DSTI/DOC(2001)/7, 25 October 2001 (Paris: OECD).
Caballero, R., 1999, “Aggregate Investment,” in Handbook of Economics, Taylor, J.B. and M. Woodford, eds. (New York: NorthHolland).
Fraumeni, B., 1997, “The Measurement of Depreciation in the U.S. National Income and Product Accounts,” Survey of Current Business, July (Washington, D.C.: Department of Commerce) 7-23.
Hubbard, R.G., 1998, “Capital-Market Imperfections and Investment,” Journal of Economic Literature, March (Nashville, TN) 193-225.
Kirova, M. and R. Lipsey, 1998, “Measuring Real Investment: Trends in the United States and International Comparisons,” Federal Reserve Bank of St. Louis Review, January/February (St. Louis, MO: Federal Reserve) 3-18.
Kopcke, R., 1993, “The Determinants of Business Investment: Has Capital Spending Been Surprisingly Low?” New England Economic Review, January/February (Boston: Federal Reserve) 3-31.
Lum, S. and B. Moyer, 2001, “Gross Domestic Product by Industry for 1998-2000,” Survey of Current Business, November (Washington, D.C.: Department of Commerce) 17-33.
Oliner, S., G. Rudebusch, and D. Sichel, 1995, “New and Old Models of Business Investment: A Comparison of Forecasting Performance,” Journal of Money, Credit and Banking, Vol. 27, No. 3, August, 806-826.
Plegrin, F. S. Schich, and A. de Serres, 2002, “Increases in Business Investment Rates in OECD Countries in the 1990s: How much can be explained by Fundamentals?,” Working Paper ECO/WKP(2002)13 (Paris: OECD).
Tevlin, S. and K. Whelan, 2000, “Explaining the Investment Boom of the 1990s,” mimeo. (Washington, D.C.: Federal Reserve Board of Governors).
Whelan, K., 2001, “A Two-Sector Approach to Modeling U.S. NIPA Data,” Finance and Economics Discussion Series, Working Paper 2001-4 (Washington, D.C.: Federal Reserve Board of Governors) January.
Whelan, K., 2000, “A Guide to the Use of Chain Aggregated NIPA Data” Finance and Economics Discussion Series, Working Paper 2000-35 (Washington, D.C.: Federal Reserve Board of Governors) June.
Prepared by Christopher MacDonagh-Dumler.
The balance was largely due to higher investment spending on: communications equipment, industrial machinery, and trucks (which together accounted for 40 percent of the increase) and office building and other commercial, nonfarm, and natural gas structures (20 percent of the increase).
A slowdown in structures investment—as reflected in rising vacancy rates in office building and other commercial and nonfarm structures—accounted for 35 percent of the decline in the investment rate (0.2 percentage point of GDP).
As a share of the capital stock, depreciation has steadily increased, however. In 1980, BEA’s measure of depreciation in the capital stock data was about 6¼ percent of the capital stock. By 2000, it reached 8 percent.
The industries were: industrial machinery and equipment; electronic equipment, motor vehicles; petroleum and coal products; telephone and telegraph; electric, gas and sanitary services (public utilities); wholesale trade; retail trade, and business services.
As Figure 5 indicates, and Kirova and Lipsey (1998) note, the United States has had a relatively lower investment rate through much of the post-war period. OECD (2001) and Pelgrin, Schich, and de Serres (2002) note that the recent increase in investment is largely in line with fundamentals.
Collecchia and Schreyer (2001) illustrate that although high-technology investment provided a boost to growth in all countries, the United States benefited the most, followed by Australia, Finland, and Canada. Technology contributed the least to economic growth in Germany, France, Italy, and Japan. Prices of high-technology goods declined most rapidly in the United States, although after accounting for different statistical methodologies, the U.S. decline is not as pronounced.
See Caballero (1999). By including a cointegrating term, this model differs from many traditional models Oliner, Rudebusch, and Sichel (1995) provide a comprehensive survey of the performance of common investment models, all of which fit the data poorly, and most of which suffer from theoretical and methodological problems. Tevlin and Whelan (2000) show that the perpetual inventory method used to derive the traditional estimating equation is not valid because of the chain-weighting methodology used by BEA to aggregate the capital-stock data.
Pelgrin, Schich, and de Serres (2002) estimate a cointegrating relationship between investment, output, and the cost of capital in nine OECD countries and find some support for cointegration.
In contrast to the overall capital-stock equation, the fit of the cointegrating relationship in the computer equipment model is significantly better, and the coefficient on the cost of capital is negative, significant, and appropriately close to -1.
These results are similar to recent research by Macroeconomic Advisers (2002) that estimates a capital overhang in the technology sector (computers and software) of about $55 billion by the end of 2000, declining to $25 billion by the end of 2001.
BEA data cover 62 types of capital (equipment, software, and structures) for 58 industries and include the average age of capital, real capital stocks (in 1996 chain-weighted dollars), and nominal capital stocks and are combined with industry output data from Lum and Moyer (2001). Both data sets are available on BEA’s website http://www.bea.gov).
Specifically, industries and capital types were selected as follows: industries were ranked by the ratio of the nominal stock of capital (for each asset type) to nominal industry output, and by the growth rate of the real stock of capital (for each type) between 1995 and 2000. Individual asset types in an industry were selected if: (i) the change in the capital-output ratio between 1995 and 2000 was disproportionately large (that is, the change in the ratio was in the lowest or highest 2½ percentile, measuring extreme changes), and (ii) if the real stock of capital grew by more than the industry average (to measure rapid capital accumulation). Attention was focused on only types of capital that grew significantly faster in the late 1990s than the early 1990s (the annual growth rate of real capital was more than 5 percentage points higher in the latter 1990s than in the early 1990s).