Browse
RECENT EMPIRICAL STUDIES of the demand for money have - applied distributed lag models to specifications of monetary behavior. One such study by Joseph Adekunle 1 focused on the manner in which adaptive expectations affect portfolio behavior. The present paper is a further investigation into the adaptive expectation model of the demand for money.
When the top personal tax rates are above the corporate rate, high income individuals have an incentive to reclassify their earnings as corporate rather than personal income for tax purposes. At least U.S. tax law imposes strict limits on the extent to which employees in publicly traded corporations can engage in such income shifting. However, entrepreneurs setting up new firms can easily reclassify their income for tax purposes. This tax incentive therefore favors entrepreneurial activity. In the United States, these tax incentives were huge during the 1950s and 1960s, though they have been much smaller since then.
This paper surveys the literature on the effects of capital account openness and stock market liberalization on economic growth and provides a synthesis in which we reconcile some of the different results presented in the literature. Various empirical measures used to gauge the presence of controls on capital account transactions and the liberalization of equity markets are discussed. We compare detailed measures of capital account controls that attempt to capture the intensity of enforcement with other indicators that simply capture whether controls are present. A detailed review of the literature is followed by an empirical section in which we trace the divergence in published results to differences in country coverage, sample periods, indicators of liberalization, and control variables across studies. Specifically, we show that when an institutional variable such as government reputation is added to the specification, the significance of capital account openness vanishes. Also, we demonstrate that enriching the specification by allowing for nonlinearities helps explain why different studies that ignore the nonlinear nature of the relationship find different results. [JEL. F32, F33, F36]