While cross-border investment flows are surging to levels not witnessed since before the Great Depression, the evaluation of political risk inherent in these projects has changed little since the 1960s. Since 1983, foreign direct investment inflows to developing countries have increased five-fold. From 1989 to 1992, the stock of American affiliates infrastructure assets grew by 153% leading to the share of total assets invested in infrastructure doubling from 1.6% to 3.0%. While this is but a fraction of the peak of 22% reached in 1940, recent research by the World Bank suggests that more than $2.0 trillion of new infrastructure will be required in East Asia and Latin America alone during the next ten years 1 . As developing countries have increasingly reopened their doors to foreign capital for such projects, multinational corporations need to carefully weigh the potential costs and benefits of reentering markets in which previous waves of investments were expropriated.
This paper addresses the contradictory results obtained by Segal (1997) and Spiller and Gely (1992) concerning the impact of institutional constraints on the U.S. Supreme Court's decision making. By adapting the Spiller and Gely maximum likelihood model to the Segal dataset, we find support for the hypothesis that the Court adjusts its decisions to presidential and congressional preferences. Data from 1947 to 1992 indicate that the average probability of the Court being constrained has been approximately one-third. Further, we show that the results obtained by Segal are the product of biases introduced by a misspecified econometric model. We also discuss how our estimation highlights the usefulness of Krehbiel's model of legislative decision making.
A good government implies two things: first, fidelity to the object of government, which is the happiness of the people; secondly, a knowledge of the means by which the object can best be obtained.
This paper addresses the contradictory results obtained by Segal (1997) and Spiller and Gely (1992) concerning the impact of institutional constraints on the U.S. Supreme Court's decision making. By adapting the Spiller and Gely maximum likelihood model to the Segal dataset, we find support for the hypothesis that the Court adjusts its decisions to presidential and congressional preferences. Data from 1947 to 1992 indicate that the average probability of the Court being constrained has been approximately one-third. Further, we show that the results obtained by Segal are the product of biases introduced by a misspecified econometric model. We also discuss how our estimation highlights the usefulness of Krehbiel's model of legislative decision making.
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