The theory of internal capital markets offers diverging views on the efficiency of resource distribution across a firm’s operating units. The efficient hypothesis posits that internal capital markets benefit from stronger control rights and superior information quality, which enable the CEO to make better allocation decisions.
The alternative hypothesis states that internal capital markets suffer from multi-layered agency motives of divisional managers and the CEO, who pursue their private interests via rent-seeking, empire building, or entrenching. Despite the key role of divisional executives in the theory of internal capital markets, there is little empirical evidence on what influence, if any, they have on capital budgeting and firm value of conglomerates.
Volatility forecasting is central to financial decision making. To assess the tradeoffs between risk and return, investors need forecasts of average return and volatility of different assets. Similarly, for the pricing of options and other derivative securities with non-linear payoffs, investors not only need to estimate current volatility, but also need to forecast it up to the maturity of the options. Forecasts of covariances across assets are as invaluable for basic needs in finance, such as the efficient diversification of risks, or the valuation of convertible securities that can either become into stocks or bonds in the future. Motivated by recent economic models of time varying volatilities, in this paper we show that empirical measures of economic uncertainty predict future volatility above and beyond traditional lagged-based forecasts.
Most financial economists today believe that asset price volatilities and cross covariances change over time, and that the movements are persistent. Starting with the seminal work on auto regressive conditional heteroskedasticity in asset prices (Engle 1982), a family of models emerged in the time series literature that generalized this important finding, tested alternative specifications, and added information in economic variables (see, e.g., Bollerslev, Chou and Kroner 1992 for a survey). Despite its success in fitting volatility processes, the ARCH family of models has had only limited success in forecasting (Figlewski 1997). While Anderson and Bollerslev (1998) show that GARCH models do provide accurate one-week-ahead forecasts, Diebold and Christoffersen (2000) show that the forecasting power of these models declines quite rapidly with the time horizon. In this paper we augment these lag-based forecasts of variances and covariances with empirical measures of uncertainty that investors have over future inflation and earnings growth, and find quite remarkably that for forecast horizons of one and two years, the proportion of explained future variation increases from about a fourth to a half.
This article reports on tests of rational political business cycle (PBC) models using an extensive new data set covering all Portuguese mainland municipalities. With a panel of observations for budget balances and expenditure items over the 1979-2000 periods, it is possible to examine the fiscal choices of local governments over a number of electoral cycles.
