58 resultados para Dynamic programming (DP)


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This paper studies the quantitative implications of changes in the composition of taxes for long-run growth and expected lifetime utility in the UK economy over 1970-2005. Our setup is a dynamic stochastic general equilibrium model incorporating a detailed scal policy struc- ture, and where the engine of endogenous growth is human capital accumulation. The government s spending instruments include pub- lic consumption, investment and education spending. On the revenue side, labour, capital and consumption taxes are employed. Our results suggest that if the goal of tax policy is to promote long-run growth by altering relative tax rates, then it should reduce labour taxes while simultaneously increasing capital or consumption taxes to make up for the loss in labour tax revenue. In contrast, a welfare promoting policy would be to cut capital taxes, while concurrently increasing labour or consumption taxes to make up for the loss in capital tax revenue.

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The effect of mortality reductions on fertility is one of the main mechanisms stressed by the recent growth literature in order to explain demographic transitions. We analyze the empirical relevance of this mechanism based on the experience of all countries since 1960. We distinguish between the effects on gross and net fertility, take into account the dynamic nature of the relationship and control for alternative explanatory factors and for endogeneity. Our results show that mortality plays a large role in fertility reductions, that the change in fertility behavior comes with a lag of about 10 years and that both net and gross fertility are affected. We find comparatively little support for explanations of the demographic transition based on economic development or technological change.

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This paper uses a unique individual level administrative data set to analyse the participation of health professionals in the NHS after training. The data set contains information on over 1,000 dentists who received Dental Vocational Training in Scotland between 1995 and 2006. Using a dynamic nonlinear panel data model, we estimate the determinants of post-training participation. We nd there is signi cant persistence in these data and are able to show that the persistence arises from state dependence and individual heterogeneity. This finding has implications for the structure of policies designed to increase participation rates. We apply this empirical framework to assess the accuracy of predictions for workforce forecasting, and to provide a preliminary estimate of the impact of one of the recruitment and retention policies available to dentists in Scotland.

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In this paper, we quantitatively assess the welfare implications of alternative public education spending rules. To this end, we employ a dynamic stochastic general equilibrium model in which human capital externalities and public education expenditures, nanced by distorting taxes, enhance the productivity of private education choices. We allow public education spending, as share of output, to respond to various aggregate indicators in an attempt to minimize the market imperfection due to human capital externalities. We also expose the economy to varying degrees of uncertainty via changes in the variance of total factor productivity shocks. Our results indicate that, in the face of increasing aggregate uncertainty, active policy can signi cantly outperform passive policy (i.e. maintaining a constant public education to output ratio) but only when the policy instrument is successful in smoothing the growth rate of human capital.

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We consider optimal monetary and scal policies in a New Keynesian model of a small open economy with sticky prices and wages. In this benchmark setting monetary policy is all we need - analytical results demonstrate that variations in government spending should play no role in the stabilization of shocks. In extensions we show, rstly, that this is even when true when allowing for in ation inertia through backward-looking rule-of-thumb price and wage-setting, as long as there is no discrepancy between the private and social evaluation of the marginal rate of substitution between consumption and leisure. Secondly, the optimal neutrality of government spending is robust to the issuance of public debt. In the presence of debt government spending will deviate from the optimal steady-state but only to the extent required to cover the deficit, not to provide any additional macroeconomic stabilization. However, unlike government spending variations in tax rates can play a complementary role to monetary policy, as they change relative prices rather than demand.

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Block factor methods offer an attractive approach to forecasting with many predictors. These extract the information in these predictors into factors reflecting different blocks of variables (e.g. a price block, a housing block, a financial block, etc.). However, a forecasting model which simply includes all blocks as predictors risks being over-parameterized. Thus, it is desirable to use a methodology which allows for different parsimonious forecasting models to hold at different points in time. In this paper, we use dynamic model averaging and dynamic model selection to achieve this goal. These methods automatically alter the weights attached to different forecasting models as evidence comes in about which has forecast well in the recent past. In an empirical study involving forecasting output growth and inflation using 139 UK monthly time series variables, we find that the set of predictors changes substantially over time. Furthermore, our results show that dynamic model averaging and model selection can greatly improve forecast performance relative to traditional forecasting methods.

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This paper proposes a bootstrap artificial neural network based panel unit root test in a dynamic heterogeneous panel context. An application to a panel of bilateral real exchange rate series with the US Dollar from the 20 major OECD countries is provided to investigate the Purchase Power Parity (PPP). The combination of neural network and bootstrapping significantly changes the findings of the economic study in favour of PPP.

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The measurement of inter-connectedness in an economy using input-output tables is not new, however much of the previous literature has not had any explicit dynamic dimension. Studies have tried to estimate the degree of inter-relatedness for an economy at a given point in time using one inputoutput table, some have compared different economies at a point in time but few have looked at the question of how inter-connectedness within an economy changes over time. The publication in 2009 of a consistent series of inputoutput tables for Scotland offers the researcher the opportunity to track changes in the degree of inter-connectedness over the seven year period 1998 to 2004. The paper is in two parts. A simple measure of inter-connectedness is introduced in the first part of the paper and applied to the Scottish tables. It is shown that although the aggregate results might appear to indicate a degree of import substitution was taking place this result is not robust to industrial disaggregation. In the second part of the paper an extraction method is applied to an eleven sector disaggregation of the Scottish economy in order to estimate how interconnectedness has changed over time for each industrial sector. It is shown that for the majority of sectors the degree of interconnectedness with the rest of the Scottish economy has grown for others, in particular Financial Services and Energy and Water Supply it has not.

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This paper investigates the impact of a balanced budget fiscal policy expansion in a regional context within a numerical dynamic general equilibrium model. We take Scotland as an example where, recently, there has been extensive debate on greater fiscal autonomy. In response to a balanced budget fiscal expansion the model suggests that: an increase in current government purchase in goods and services has negative multiplier effects only if the elasticity of substitution between private and public consumption is high enough to move downward the marginal utility of private consumers; public capital expenditure crowds in consumption and investment even with a high level of congestion; but crowding out effects might arise in the short-run if agents are myopic.

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This paper investigates the extent of disparities amongst the provinces of China since the economic reform in 1978 up to the most recent year for which data is available. After a brief review of theoretical and in particular recent empirical literature on regional inequality in China it investigates whether or not the dynamic economic growth in China has been coupled with increasing disparities amongst the Chinese provinces. The paper utilises a few models of convergence along the lines of those hypothesised by neoclassical economists. It employs per capita income and per capita consumption to identify the possible absolute and conditional convergence since the economic reforms. The coverage and impact of the disparities in terms of the relative size of population affected are then taken into account in the analysis of inequality in income and consumption.

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Robust decision making implies welfare costs or robustness premia when the approximating model is the true data generating process. To examine the importance of these premia at the aggregate level we employ a simple two-sector dynamic general equilibrium model with human capital and introduce an additional form of precautionary behavior. The latter arises from the robust decision maker s ability to reduce the effects of model misspecification through allocating time and existing human capital to this end. We find that the extent of the robustness premia critically depends on the productivity of time relative to that of human capital. When the relative efficiency of time is low, despite transitory welfare costs, there are gains from following robust policies in the long-run. In contrast, high relative productivity of time implies misallocation costs that remain even in the long-run. Finally, depending on the technology used to reduce model uncertainty, we fi nd that while increasing the fear of model misspecfi cation leads to a net increase in precautionary behavior, investment and output can fall.

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In many decentralised markets, the traders who benefit most from an exchange do not employ intermediaries even though they could easily afford them. At the same time, employing intermediaries is not worthwhile for traders who benefit little from trade. Together, these decisions amount to non-monotone participation choices in intermediation: only traders of middle “type” employ intermediaries, while the rest, the high and the low types, prefer to search for a trading partner directly. We provide a theoretical foundation for this, hitherto unexplained, phenomenon. We build a dynamic matching model, where a trader’s equilibrium bargaining share is a convex increasing function of her type. We also show that this is indeed a necessary condition for the existence of non-monotone equilibria.

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In recent years there has been increasing concern about the identification of parameters in dynamic stochastic general equilibrium (DSGE) models. Given the structure of DSGE models it may be difficult to determine whether a parameter is identified. For the researcher using Bayesian methods, a lack of identification may not be evident since the posterior of a parameter of interest may differ from its prior even if the parameter is unidentified. We show that this can even be the case even if the priors assumed on the structural parameters are independent. We suggest two Bayesian identification indicators that do not suffer from this difficulty and are relatively easy to compute. The first applies to DSGE models where the parameters can be partitioned into those that are known to be identified and the rest where it is not known whether they are identified. In such cases the marginal posterior of an unidentified parameter will equal the posterior expectation of the prior for that parameter conditional on the identified parameters. The second indicator is more generally applicable and considers the rate at which the posterior precision gets updated as the sample size (T) is increased. For identified parameters the posterior precision rises with T, whilst for an unidentified parameter its posterior precision may be updated but its rate of update will be slower than T. This result assumes that the identified parameters are pT-consistent, but similar differential rates of updates for identified and unidentified parameters can be established in the case of super consistent estimators. These results are illustrated by means of simple DSGE models.

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This paper uses forecasts from the European Central Bank's Survey of Professional Forecasters to investigate the relationship between inflation and inflation expectations in the euro area. We use theoretical structures based on the New Keynesian and Neoclassical Phillips curves to inform our empirical work. Given the relatively short data span of the Survey of Professional Forecasters and the need to control for many explanatory variables, we use dynamic model averaging in order to ensure a parsimonious econometric speci cation. We use both regression-based and VAR-based methods. We find no support for the backward looking behavior embedded in the Neo-classical Phillips curve. Much more support is found for the forward looking behavior of the New Keynesian Phillips curve, but most of this support is found after the beginning of the financial crisis.

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In an effort to meet its obligations under the Kyoto Protocol, in 2005 the European Union introduced a cap-and-trade scheme where mandated installations are allocated permits to emit CO2. Financial markets have developed that allow companies to trade these carbon permits. For the EU to achieve reductions in CO2 emissions at a minimum cost, it is necessary that companies make appropriate investments and policymakers design optimal policies. In an effort to clarify the workings of the carbon market, several recent papers have attempted to statistically model it. However, the European carbon market (EU ETS) has many institutional features that potentially impact on daily carbon prices (and associated nancial futures). As a consequence, the carbon market has properties that are quite different from conventional financial assets traded in mature markets. In this paper, we use dynamic model averaging (DMA) in order to forecast in this newly-developing market. DMA is a recently-developed statistical method which has three advantages over conventional approaches. First, it allows the coefficients on the predictors in a forecasting model to change over time. Second, it allows for the entire fore- casting model to change over time. Third, it surmounts statistical problems which arise from the large number of potential predictors that can explain carbon prices. Our empirical results indicate that there are both important policy and statistical bene ts with our approach. Statistically, we present strong evidence that there is substantial turbulence and change in the EU ETS market, and that DMA can model these features and forecast accurately compared to conventional approaches. From a policy perspective, we discuss the relative and changing role of different price drivers in the EU ETS. Finally, we document the forecast performance of DMA and discuss how this relates to the efficiency and maturity of this market.