3 resultados para RATE-CONSTANT METHOD

em Scottish Institute for Research in Economics (SIRE) (SIRE), United Kingdom


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Ukraine has a rapidly ageing and declining population. A dynamic forward-­looking Computable General Equilibrium (CGE) model with an explicitly modelled Pay‐As‐You-­Go pension scheme is constructed to perform simulations of different pension reform scenarios and investigate the impact of population ageing on a wide range of macroeconomic variables. It is shown that, changes in age structure will result in a significant negative impact on the economy and stability of the pension system. Analysis of the potential changes to the pension system is limited to modelling an increase of the pension age, keeping either the workers’ contribution rate or replacement rate constant.

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We study a business cycle model in which a benevolent fiscal authority must determine the optimal provision of government services, while lacking credibility, lump-sum taxes, and the ability to bond finance deficits. Households and the fiscal authority have risk sensitive preferences. We find that outcomes are affected importantly by the household's risk sensitivity, but not by the fiscal authority's. Further, while household risk-sensitivity induces a strong precautionary saving motive, which raises capital and lowers the return on assets, its effects on fluctuations and the business cycle are generally small, although more pronounced for negative shocks. Holding the stochastic steady state constant, increases in household risk-sensitivity lower the risk-free rate and raise the return on equity, increasing the equity premium. Finally, although risk-sensitivity has little effect on the provision of government services, it does cause the fiscal authority to lower the income tax rate. An additional contribution of this paper is to present a method for computing Markov-perfect equilibria in models where private agents and the government are risk-sensitive decisionmakers.

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An expanding literature articulates the view that Taylor rules are helpful in predicting exchange rates. In a changing world however, Taylor rule parameters may be subject to structural instabilities, for example during the Global Financial Crisis. This paper forecasts exchange rates using such Taylor rules with Time Varying Parameters (TVP) estimated by Bayesian methods. In core out-of-sample results, we improve upon a random walk benchmark for at least half, and for as many as eight out of ten, of the currencies considered. This contrasts with a constant parameter Taylor rule model that yields a more limited improvement upon the benchmark. In further results, Purchasing Power Parity and Uncovered Interest Rate Parity TVP models beat a random walk benchmark, implying our methods have some generality in exchange rate prediction.