40 resultados para University Modelling


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This paper is inspired by articles in the last decade or so that have argued for more attention to theory, and to empirical analysis, within the well-known, and long-lasting, contingency framework for explaining the organisational form of the firm. Its contribution is to extend contingency analysis in three ways: (a) by empirically testing it, using explicit econometric modelling (rather than case study evidence) involving estimation by ordered probit analysis; (b) by extending its scope from large firms to SMEs; (c) by extending its applications from Western economic contexts, to an emerging economy context, using field work evidence from China. It calibrates organizational form in a new way, as an ordinal dependent variable, and also utilises new measures of familiar contingency factors from the literature (i.e. Environment, Strategy, Size and Technology) as the independent variables. An ordered probit model of contingency was constructed, and estimated by maximum likelihood, using a cross section of 83 private Chinese firms. The probit was found to be a good fit to the data, and displayed significant coefficients with plausible interpretations for key variables under all the four categories of contingency analysis, namely Environment, Strategy, Size and Technology. Thus we have generalised the contingency model, in terms of specification, interpretation and applications area.

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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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In an input-output context the impact of any particular industrial sector is commonly measured in terms of the output multiplier for that industry. Although such measures are routinely calculated and often used to guide regional industrial policy the behaviour of such measures over time is an area that has attracted little academic study. The output multipliers derived from any one table will have a distribution; for some industries the multiplier will be relatively high, for some it will be relatively low. The recentpublication of consistent input-output tables for the Scottish economy makes it possible to examine trends in this mdistribution over the ten year period 1998-2007. This is done by comparing the means and other summary measures of the distributions, the histograms and the cumulative densities. The results indicate a tendency for the multipliers to increase over the period. A Markov chain modelling approach suggests that this drift is a slow but long term phenomenon which appears not to tend to an equilibrium state. The prime reason for the increase in the output multipliers is traced to a decline in the relative importance of imported (both from the rest of the UK and the rest of the world) intermediate inputs used by Scottish industries. This suggests that models calibrated on the set of tables might have to be interpreted with caution.

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This paper discusses the challenges faced by the empirical macroeconomist and methods for surmounting them. These challenges arise due to the fact that macroeconometric models potentially include a large number of variables and allow for time variation in parameters. These considerations lead to models which have a large number of parameters to estimate relative to the number of observations. A wide range of approaches are surveyed which aim to overcome the resulting problems. We stress the related themes of prior shrinkage, model averaging and model selection. Subsequently, we consider a particular modelling approach in detail. This involves the use of dynamic model selection methods with large TVP-VARs. A forecasting exercise involving a large US macroeconomic data set illustrates the practicality and empirical success of our approach.

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This paper examines how appropriately to attribute economic impact to consumption expenditures. Consumption expenditures are often treated as either wholly endogenous or wholly exogenous, following a distinction from Input-Output analysis. For many applications, such as those focusing on the impacts of tourism or benefits systems, such binomial assumptions are not satisfactory. We argue that consumption is neither wholly endogenous nor wholly exogenous but that the degree of this distinction is rather an empirical matter. We set out a general model for the treatment of consumption expenditures and illustrate its application through the case of university students. We examine individual student groups and how the impacts of students at particular institutions. Furthermore we take into account the binding budget constraint of public expenditures (as is the case for devolved regions in the UK)and examine how this affects the impact attributed to students' consumption expenditures.

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Econometric analysis has been inconclusive in determining the contribution that increased skills have on macroeconomic performance whilst conventional growth accounting approaches to the same problem rest on restrictive assumptions. We propose an alternative micro-to-macro method which combines elements of growth accounting and numerical general equilibrium modelling. The usefulness of this approach for applied education policy analysis is demonstrated by evaluating the macroeconomic impact on the Scottish economy of a single graduation cohort from further education colleges. We find the macroeconomic impact to be significant. From a policy point of view this supports a revival of interest in the conventional teaching role of education institutions.

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Genuine Savings has emerged as a widely-used indicator of sustainable development. In this paper, we use long-term data stretching back to 1870 to undertake empirical tests of the relationship between Genuine Savings (GS) and future well-being for three countries: Britain, the USA and Germany. Our tests are based on an underlying theoretical relationship between GS and changes in the present value of future consumption. Based on both single country and panel results, we find evidence supporting the existence of a cointegrating (long run equilibrium) relationship between GS and future well-being, and fail to reject the basic theoretical result on the relationship between these two macroeconomic variables. This provides some support for the GS measure of weak sustainability. We also show the effects of modelling shocks, such as World War Two and the Great Depression.

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Part of the local economic impact of a major sporting event comes from the associated temporary tourism expenditures. Typically demand-driven Input-Output (IO) methods are used to quantify the impacts of such expenditures. However, IO modelling has specific weaknesses when measuring temporary tourism impacts; particular problems lie in its treatment of factor supplies and its lack of dynamics. Recent work argues that Computable General Equilibrium (CGE) analysis is more appropriate and this has been widely applied. Neglected in this literature however is an understanding of the role that behavioural characteristics and factor supply assumptions play in determining the economic impact of tourist expenditures, particularly where expenditures are temporary (i.e. of limited duration) and anticipated (i.e. known in advance). This paper uses a CGE model for Scotland in which agents can have myopic- or forward-looking behaviours and shows how these alternative specifications affect the timing and scale of the economic impacts from anticipated and temporary tourism expenditure. The tourism shock analysed is of a scale expected for the Commonwealth Games to be held in Glasgow in 2014. The model shows how “pre-shock” and “legacy” effects – impacts before and after the shock – arise and their quantitative importance. Using the forward-looking model the paper calculates the optimal degree of pre-announcement.

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There is a vast literature that specifies Bayesian shrinkage priors for vector autoregressions (VARs) of possibly large dimensions. In this paper I argue that many of these priors are not appropriate for multi-country settings, which motivates me to develop priors for panel VARs (PVARs). The parametric and semi-parametric priors I suggest not only perform valuable shrinkage in large dimensions, but also allow for soft clustering of variables or countries which are homogeneous. I discuss the implications of these new priors for modelling interdependencies and heterogeneities among different countries in a panel VAR setting. Monte Carlo evidence and an empirical forecasting exercise show clear and important gains of the new priors compared to existing popular priors for VARs and PVARs.

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We investigate the dynamic and asymmetric dependence structure between equity portfolios from the US and UK. We demonstrate the statistical significance of dynamic asymmetric copula models in modelling and forecasting market risk. First, we construct “high-minus-low" equity portfolios sorted on beta, coskewness, and cokurtosis. We find substantial evidence of dynamic and asymmetric dependence between characteristic-sorted portfolios. Second, we consider a dynamic asymmetric copula model by combining the generalized hyperbolic skewed t copula with the generalized autoregressive score (GAS) model to capture both the multivariate non-normality and the dynamic and asymmetric dependence between equity portfolios. We demonstrate its usefulness by evaluating the forecasting performance of Value-at-Risk and Expected Shortfall for the high-minus-low portfolios. From back-testing, e find consistent and robust evidence that our dynamic asymmetric copula model provides the most accurate forecasts, indicating the importance of incorporating the dynamic and asymmetric dependence structure in risk management.