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Register a new userA Mathematical Model of Foreign Capital Inflow
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The paper models foreign capital inflow from the developed to the developing countries in a stochastic dynamic programming (SDP) framework. Under some regularity conditions, the existence of the solutions to the SDP problem is proved and they are then obtained by numerical technique because of the non-linearity of the related functions. A number of comparative dynamic analyses explore the impact of parameters of the model on dynamic paths of capital inflow, interest rate in the international loan market and the exchange rate.
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The major perspective of this paper is to provide more evidence into the empirical determinants of capital structure adjustment in different macroeconomics states by focusing and discussing the relative importance of firm-specific and macroeconomic characteristics from an alternative scope in U.S. This study extends the empirical research on the topic of capital structure by focusing on a quantile regression method to investigate the behavior of firm-specific characteristics and macroeconomic variables across all quantiles of distribution of leverage (total debt, long-terms debt and short-terms debt). Thus, based on a partial adjustment model, we find that long-term and short-term debt ratios varying regarding their partial adjustment speeds; the short-term debt raises up while the long-term debt ratio slows down for same periods.
Capital usually leads to income, and income is more accurately and easily measured. Thus we summarize income distributions in USA, Germany, etc.
In this paper, we formulate a method for minimising the expectation value of the procurement cost of electricity in two popular spot markets: {it day-ahead} and {it intra-day}, under the assumption that expectation value of unit prices and the distributions of prediction errors for the electricity demand traded in two markets are known. The expectation value of the total electricity cost is minimised over two parameters that change the amounts of electricity. Two parameters depend only on the expected unit prices of electricity and the distributions of prediction errors for the electricity demand traded in two markets. That is, even if we do not know the predictions for the electricity demand, we can determine the values of two parameters that minimise the expectation value of the procurement cost of electricity in two popular spot markets. We demonstrate numerically that the estimate of two parameters often results in a small variance of the total electricity cost, and illustrate the usefulness of the proposed procurement method through the analysis of actual data.
This paper outlines a critical gap in the assessment methodology used to estimate the macroeconomic costs and benefits of climate policy. It shows that the vast majority of models used for assessing climate policy use assumptions about the financial system that sit at odds with the observed reality. In particular, the models assumptions lead to `crowding out of capital, which cause them to show negative impacts from climate policy in virtually all cases. We compare this approach with that of the E3ME model, which follows non-equilibrium economic theory and adopts a more empirical approach. While the non-equilibrium model also has limitations, its treatment of the financial system is more consistent with reality and it shows that green investment need not crowd out investment in other parts of the economy -- and may therefore offer an economic stimulus. The implication of this finding is that standard CGE models consistently over-estimate the costs of climate policy in terms of GDP and welfare, potentially by a substantial amount. These findings overly restrict the range of possible emission pathways accessible using climate policy from the viewpoint of the decision-maker, and may also lead to misleading information used for policy making. Improvements in both modelling approaches should be sought with some urgency -- both to provide a better assessment of potential climate policy and to improve understanding of the dynamics of the global financial system more generally.
The number of Italian firms in function of the number of workers is well approximated by an inverse power law up to 15 workers but shows a clear downward deflection beyond this point, both when using old pre-1999 data and when using recent (2014) data. This phenomenon could be associated with employent protection legislation which applies to companies with more than 15 workers (the Statuto dei Lavoratori). The deflection disappears for agriculture firms, for which the protection legislation applies already above 5 workers. In this note it is estimated that a correction of this deflection could bring an increase from 3.9 to 5.8% in new jobs in firms with a workforce between 5 to 25 workers.
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