Intangible capital and stock market

This thesis contains two independent but related papers on intangible capital and stock market.; The first chapter, Intangible Capital and Stock Prices, develops a two-sector dynamic stochastic general equilibrium model to measure the intangible capital stock and studies the implied riskiness of the market value of capital. The equilibrium of the economy is characterized by a state-space representation of the dynamic system. A Kalman filter algorithm is used to produce an estimate of the value of intangible capital stock based on the observed data on macroeconomic variables and asset prices. With modest capital adjustment costs, the model implies that significant amount of intangible capital is accumulated during the past 50 years in the US economy but the growth of intangible capital in the last decade is not as fast as the estimates of Hall (2001). The variation in the intangible capital estimated from aggregate macroeconomic variables accounts for almost half of the variability in the market-to-book ratio of nonfinancial and nonfarm corporate firms.; The second chapter, Intangible Risk, is a joint paper with Lars Peter Hansen and John C. Heaton. In this paper we reviewed two findings pertinent for using asset market data to make inferences about the intangible capital stock. We presented evidence familiar from the empirical finance literature that returns are heterogeneous when firms are grouped according to their ratio of market equity to book equity. This evidence suggests that there are important differences in the riskiness of investment in measured capital vis. a. vis. intangible capital. This has potentially important ramifications for how to build explicit economic models to use in constructing measurements of the intangible capital stock. There has been much interest recently in the finance literature on using vector autoregressive (VAR) methods to understand riskiness of serially correlated cash flows or dividends. The discounted dividend risk-measures using VAR methods find that high-book-to-market portfolio returns have more economically relevant risk. Our results are sensitive to other specifications of the long run dynamics and to our identification of the shocks.