This article explores a new approach to identifying government spending shocks which avoids many of the shortcomings of existing approaches. The new approach is to identify government spending shocks with statistical innovations to the accumulated excess returns of large US military contractors. This strategy is used to estimate the dynamic responses of output, hours, consumption and real wages to a government spending shock. We find that positive government spending shocks are associated with increases in output, hours and consumption. Real wages initially decline after a government spending shock and then rise after a year. We estimate the government spending multiplier associated with increases in military spending to be about 1.5 over a horizon of 5 years. Disciplines Finance | Finance and Financial Management CommentsAt the time of publication, author Ryan Heath Peters was affiliated with the Federal Reserve Bank of Chicago. Currently, he is a faculty member at the Wharton School at the University of Pennsylvania. Abstract This paper explores a new approach to identifying government spending shocks which avoids many of the shortcomings of existing approaches. The new approach is to identify government spending shocks with statistical innovations to the accumulated excess returns of large US military contractors. This strategy is used to estimate the dynamic responses of output, hours, consumption and real wages to a government spending shock. We find that positive government spending shocks are associated with increases in output, hours, and consumption. Real wages initially decline after a government spending shock and then rise after a year. We estimate the government spending multiplier associated with increases in military spending to be about 1.5 over a horizon of 5 years. Journal of Economic Literature Classification Numbers: E0, E30, E60
This article explores a new approach to identifying government spending shocks which avoids many of the shortcomings of existing approaches. The new approach is to identify government spending shocks with statistical innovations to the accumulated excess returns of large US military contractors. This strategy is used to estimate the dynamic responses of output, hours, consumption and real wages to a government spending shock. We find that positive government spending shocks are associated with increases in output, hours and consumption. Real wages initially decline after a government spending shock and then rise after a year. We estimate the government spending multiplier associated with increases in military spending to be about 1.5 over a horizon of 5 years. Disciplines Finance | Finance and Financial Management CommentsAt the time of publication, author Ryan Heath Peters was affiliated with the Federal Reserve Bank of Chicago. Currently, he is a faculty member at the Wharton School at the University of Pennsylvania. Abstract This paper explores a new approach to identifying government spending shocks which avoids many of the shortcomings of existing approaches. The new approach is to identify government spending shocks with statistical innovations to the accumulated excess returns of large US military contractors. This strategy is used to estimate the dynamic responses of output, hours, consumption and real wages to a government spending shock. We find that positive government spending shocks are associated with increases in output, hours, and consumption. Real wages initially decline after a government spending shock and then rise after a year. We estimate the government spending multiplier associated with increases in military spending to be about 1.5 over a horizon of 5 years. Journal of Economic Literature Classification Numbers: E0, E30, E60
Current standards prohibit the capitalization of internally created intangibles, resulting in a downward bias of reported assets. We estimate a capitalization model using market prices of intangibles to estimate the parameters of the capital accumulation process. Two settings provide intangible asset values: publicly traded equity prices and exit prices. We use these parameters to estimate intangible capital stocks and subject them to an extensive set of validation tests that compare them with stocks estimated using existing parameters. Intangible stocks developed from exit price parameters outperform both stocks developed by publicly traded parameters and those stocks developed with existing estimates.
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