Paul Gomme () (Department of Economics, Concordia University) B. Ravikumar () (Department of Economics, University of Iowa) Peter Rupert () (Department of Economics, University of California, Santa Barbara)
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We measure the return to capital directly from the NIPA and BEA data and examine the return implications of the real business cycle model. Specifically, we construct a quarterly time series of the after-tax return to business capital. The business cycle properties of this return differs considerably from those of the S&P 500 returns. First, its volatility is considerably smaller than that of S\&P 500 returns. Second, our measured return is procyclical and leads output by one quarter; S&P 500 returns are countercyclical and lead the cycle by four quarters. The standard business cycle model captures almost 50% of the volatility in the return to capital (relative to the volatility of output), and does well in capturing the lead-lag pattern. We consider several departures from the benchmark model; the model with stochastic taxes captures nearly 85% of the relative volatility in the return to capital and the model with high risk aversion captures 80% of the relative volatility. We then include capital gains in our measurement and use a model with investment specific technological change to address the higher volatility in the return to capital. This model accounts for more than 80% of the return volatility, and essentially all of the relative volatility.
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Paper provided by Concordia University, Department of Economics in its series Working Papers with number
08002.
Find related papers by JEL classification: E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles E13 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Neoclassical
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