25 resultados para economic model of disability

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


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This paper provides a simple theoretical framework to discuss the relationship between assisted reproductive technologies and the microeconomics of fertility choice. Individuals make choices of education and work along with decisions about whether and when to have children. Decisions regarding fertility are influenced by policy and labor market factors that affect the earnings opportunities of mothers and the costs of raising children. We show how observed differences in these economic factors across countries explain observed different fertility and childbearing age patterns. We then use the model to predict behavioral responses to biomedical improvements in assisted reproductive technologies, and hence the impact of these technologies on fertility.

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In this paper we propose a novel empirical extension of the standard market microstructure order flow model. The main idea is that heterogeneity of beliefs in the foreign exchange market can cause model instability and such instability has not been fully accounted for in the existing empirical literature. We investigate this issue using two di¤erent data sets and focusing on out- of-sample forecasts. Forecasting power is measured using standard statistical tests and, additionally, using an alternative approach based on measuring the economic value of forecasts after building a portfolio of assets. We nd there is a substantial economic value on conditioning on the proposed models.

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This paper investigates underlying changes in the UK economy over the past thirtyfive years using a small open economy DSGE model. Using Bayesian analysis, we find UK monetary policy, nominal price rigidity and exogenous shocks, are all subject to regime shifting. A model incorporating these changes is used to estimate the realised monetary policy and derive the optimal monetary policy for the UK. This allows us to assess the effectiveness of the realised policy in terms of stabilising economic fluctuations, and, in turn, provide an indication of whether there is room for monetary authorities to further improve their policies.

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This paper examines both the in-sample and out-of-sample performance of three monetary fundamental models of exchange rates and compares their out-of-sample performance to that of a simple Random Walk model. Using a data-set consisting of five currencies at monthly frequency over the period January 1980 to December 2009 and a battery of newly developed performance measures, the paper shows that monetary models do better (in-sample and out-of-sample forecasting) than a simple Random Walk model.

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This paper presents a dynamic Overlapping Generations Computable General Equilibrium (OLG-CGE) model of Scotland. The model is used to examine the impact of population ageing on the labour market. More specifically, it is used to evaluate the effects of labour force decline and labour force ageing on key macro-economic variables. The second effect is assumed to operate through age-specific productivity and labour force participation. In the analysis, particular attention is paid to how population ageing impinges on the government expenditure constraint. The basic structure of the model follows in the Auerbach and Kotlikoff tradition. However, the model takes into consideration directly age-specific mortality. This is analogous to “building in” a cohort-component population projection structure to the model, which allows more complex and more realistic demographic scenarios to be considered.

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This paper presents a dynamic Overlapping Generations Computable General Equilibrium (OLG-CGE) model of Scotland. The model is used to examine the impact of population ageing on the labour market. More specifically, it is used to evaluate the effects of labour force decline and labour force ageing on key macro-economic variables. The second effect is assumed to operate through age-specific productivity and labour force participation. In the analysis, particular attention is paid to how population ageing impinges on the government expenditure constraint. The basic structure of the model follows in the Auerbach and Kotlikoff tradition. However, the model takes into consideration directly age-specific mortality. This is analogous to “building in” a cohort-component population projection structure to the model, which allows more complex and more realistic demographic scenarios to be considered.

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As demand for electricity from renewable energy sources grows, there is increasing interest, and public and financial support, for local communities to become involved in the development of renewable energy projects. In the UK, “Community Benefit” payments are the most common financial link between renewable energy projects and local communities. These are “goodwill” payments from the project developer for the community to spend as it wishes. However, if an ownership stake in the renewable energy project were possible, receipts to the local community would potentially be considerably higher. The local economic impacts of these receipts are difficult to quantify using traditional Input-Output techniques, but can be more appropriately handled within a Social Accounting Matrix (SAM) framework where income flows between agents can be traced in detail. We use a SAM for the Shetland Islands to evaluate the potential local economic and employment impact of a large onshore wind energy project proposed for the Islands. Sensitivity analysis is used to show how the local impact varies with: the level of Community Benefit payments; the portion of intermediate inputs being sourced from within the local economy; and the level of any local community ownership of the project. By a substantial margin, local ownership confers the greatest economic impacts for the local community.

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We study how the use of judgement or “add-factors” in forecasting may disturb the set of equilibrium outcomes when agents learn using recursive methods. We isolate conditions under which new phenomena, which we call exuberance equilibria, can exist in a standard self-referential environment. Local indeterminacy is not a requirement for existence. We construct a simple asset pricing example and find that exuberance equilibria, when they exist, can be extremely volatile relative to fundamental equilibria.

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This paper attempts to extend existing models of political agency to an environment in which voting may be divided between informed and instrumental, informed and ‘expressive’ (Brennan and Lomasky (1993)) and uninformed due to ‘rational irrationality’ (Caplan (2007)). It constructs a model where politicians may be good, bad or populist. Populists are more willing than good politicians to pander to voters who may choose inferior policies in a large-group electoral setting because their vote is insignificant compared with those that voters would choose were their vote decisive in determining the electoral outcome. Bad politicians would ideally like to extract tax revenue for their own ends. Initially we assume the existence of only good and populist politicians. The paper investigates the incentives for good politicians to pool with or separate from populists and focuses on three key issues – (1) how far the majority of voter’s preferences are from those held by the better informed incumbent politician (2) the extent to which the population exhibits rational irrationality and expressiveness (jointly labelled as emotional) and (3) the cost involved in persuading uninformed voters to change their views in terms of composing messages and spreading them. This paper goes on to consider how the inclusion of bad politicians may affect the behaviour of good politicians and suggests that a small amount of potential corruption may be socially useful. It is also argued that where bad politicians have an incentive to mimic the behaviour of good and populist politicians, the latter types of politician may have an incentive to separate from bad politicians by investing in costly public education signals. The paper also discusses the implications of the model for whether fiscal restraints should be soft or hard.

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This paper develops methods for Stochastic Search Variable Selection (currently popular with regression and Vector Autoregressive models) for Vector Error Correction models where there are many possible restrictions on the cointegration space. We show how this allows the researcher to begin with a single unrestricted model and either do model selection or model averaging in an automatic and computationally efficient manner. We apply our methods to a large UK macroeconomic model.

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Iodine deficiency is the leading cause of preventable mental retardation in the world today. Iodine deficiency was common in the developed world until the introduction of iodized salt in the 1920’s. The incidence of iodine deficiency is connected to low iodine levels in the soil and water. We examine the impact of salt iodization in the US by taking advantage of this natural geographic variation. Areas with high pre-treatment levels of iodine deficiency provide a treatment group which we can compare to a control group of low iodine deficiency areas. In the US, salt was iodized over a very short period of time around 1924. We use previously unused data collected during WWI and WWII to compare outcomes of cohorts born before and after iodization, in localities that were naturally poor and rich in iodine. We find evidence of the beneficial effects of iodization on the cognitive abilities of the cohorts exposed to it.

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This paper demonstrates that an asset pricing model with least-squares learning can lead to bubbles and crashes as endogenous responses to the fundamentals driving asset prices. When agents are risk-averse they need to make forecasts of the conditional variance of a stock’s return. Recursive updating of both the conditional variance and the expected return implies several mechanisms through which learning impacts stock prices. Extended periods of excess volatility, bubbles and crashes arise with a frequency that depends on the extent to which past data is discounted. A central role is played by changes over time in agents’ estimates of risk.

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Untreated wastewater being directly discharged into rivers is a very harmful environmental hazard that needs to be tackled urgently in many countries. In order to safeguard the river ecosystem and reduce water pollution, it is important to have an effluent charge policy that promotes the investment of wastewater treatment technology by domestic firms. This paper considers the strategic interaction between the government and the domestic firms regarding the investment in the wastewater treatment technology and the design of optimal e­ffluent charge policy that should be implemented. In this model, the higher is the proportion of non-investing firms, the higher would be the probability of having to incur an e­ffluent charge and the higher would be that charge. On one hand the government needs to impose a sufficiently strict policy to ensure that firms have strong incentive to invest. On the other hand, it cannot be too strict that it drives out firms which cannot afford to invest in such expensive technology. The paper analyses the factors that affect the probability of investment in this technology. It also explains the difficulty of imposing a strict environment policy in countries that have too many small firms which cannot afford to invest unless subsidised.

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UK regional policy has been advocated as a means of reducing regional disparities and stimulating national growth. However, there is limited understanding of the interregional and national effects of such a policy. This paper uses an interregional computable general equilibrium model to identify the national impact of a policy-induced regional demand shock under alternative labour market closures. Our simulation results suggest that regional policy operating solely on the demand side has significant national impacts. Furthermore, the effects on the non-target region are particularly sensitive to the treatment of the regional labour market.

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This paper introduces a new model of trend (or underlying) inflation. In contrast to many earlier approaches, which allow for trend inflation to evolve according to a random walk, ours is a bounded model which ensures that trend inflation is constrained to lie in an interval. The bounds of this interval can either be fixed or estimated from the data. Our model also allows for a time-varying degree of persistence in the transitory component of inflation. The bounds placed on trend inflation mean that standard econometric methods for estimating linear Gaussian state space models cannot be used and we develop a posterior simulation algorithm for estimating the bounded trend inflation model. In an empirical exercise with CPI inflation we find the model to work well, yielding more sensible measures of trend inflation and forecasting better than popular alternatives such as the unobserved components stochastic volatility model.