899 resultados para Cartels, Deterreneve, UK,


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The research reported here is an output of Karen Turner’s ESRC Climate Change Leadership Fellow project (Grant reference RES-066-27-0029). However, this research builds on previous work funded by the ESRC on modelling the economic and environmental impacts of technological improvement (Grant reference: RES-061-25-0010) and by the EPSRC through the SuperGen Marine Energy Research Consortium on accounting for and modeling environmental indicators (Grant reference: EP/E040136/1).

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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 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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The revival of support for a living wage has reopened a long-run debate over the extent to which active regulation of labour markets may be necessary to attain desired outcomes. Market failure is suggested to result in lower wages and remuneration for low skilled workers than might otherwise be expected from models of perfect competition. This paper examines the theoretical underpinning of living wage campaigns and demonstrates that once we move away from idealised models of perfect competition to one where employers retain power over the bargaining process, such as monopsony, it is readily understandable that low wages may be endemic in low skilled employment contracts. The paper then examines evidence, derived from the UK Quarterly Labour Force Survey, for the extent to which a living wage will address low pay within the labour force. We highlight the greater incidence of low pay within the private sector and then focus upon the public sector where the Living Wage demand has had most impact. We examine the extent to which addressing low pay within the public sector increases costs. We further highlight the evidence that a predominance of low pay exists among public sector young and women workers (and in particular lone parent women workers) but not, perhaps surprisingly, among workers from ethnic minority backgrounds. The paper then builds upon the results from the Quarterly Labour Force Survey with analysis of the British Household Panel Survey in order to examine the impact the introduction of a living wage, within the public sector, would have in reducing household inequality. The paper concludes that a living wage is indeed an appropriate regulatory response to market failure for low skilled workers and can act to reduce age and gender pay inequality, and reduce household income inequality among in-work households below average earnings.

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This paper disaggregates a UK Input-Output (IO) table for 2004 based on household income quintiles from published survey data. In addition to the Input-Output disaggregation, the household components of a UK Income Expenditure (I-E) account used to inform a Social Accounting Matrix (SAM),have also been disaggregated by household income quintile. The focus of this paper is on household expenditure on the UK energy sector.

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In this paper, we use CGE modelling techniques to identify the impact on energy use of an improvement in energy efficiency in the household sector. The main findings are that 1) when the price of energy is measured in natural units, the increase in efficiency yields only to a modification of tastes, changing as a result, the composition of household consumption; 2) when households internalize efficiency, the improvement in energy efficiency reduces the price of energy in efficiency units, providing a source of improved competitiveness as the nominal wage and the price level both fall; 3) the short-run rebound can be greater than the long run rebound if the household demand elasticity is the same for both time frames, however, the short run rebound is always lower than in the long-run if the demand for energy is relatively more elastic in the long-run; 4) the introduction of habit formation changes the composition of household consumption, modifying the magnitude of the household rebound only in the short-run. In this period, household and economy wide rebound are lowest for external habit formation and highest when consumers’ preferences are defined using a conventional utility function.

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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 model as evidence comes in about which has forecast well in the recent past. In an empirical study involving forecasting output 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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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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The eight years from 2000 to 2008 saw a rapid growth in the use of securitization by UK banks. We aim to identify the reasons that contributed to this rapid growth. The time period (2000 to 2010) covered by our study is noteworthy as it covers the pre- financial crisis credit-boom, the peak of the fi nancial crisis and its aftermath. In the wake of the financial crisis, many governments, regulators and political commentators have pointed an accusing finger at the securitization market - even in the absence of a detailed statistical and economic analysis. We contribute to the extant literature by performing such an analysis on UK banks, focussing principally on whether it is the need for liquidity (i.e. the funding of their balance sheets), or the desire to engage in regulatory capital arbitrage or the need for credit risk transfer that has led to UK banks securitizing their assets. We show that securitization has been signi ficantly driven by liquidity reasons. In addition, we observe a positive link between securitization and banks credit risk. We interpret these latter findings as evidence that UK banks which engaged in securitization did so, in part, to transfer credit risk and that, in comparison to UK banks which did not use securitization, they had more credit risk to transfer in the sense that they originated lower quality loans and held lower quality assets. We show that banks which issued more asset-backed securities before the financial crisis suffered more defaults after the financial crisis.

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The Conservative Party emerged from the 2010 United Kingdom General Election as the largest single party, but their support was not geographically uniform. In this paper, we estimate a hierarchical Bayesian spatial probit model that tests for the presence of regional voting effects. This model allows for the estimation of individual region-specic effects on the probability of Conservative Party success, incorporating information on the spatial relationships between the regions of the mainland United Kingdom. After controlling for a range of important covariates, we find that these spatial relationships are significant and that our individual region-specic effects estimates provide additional evidence of North-South variations in Conservative Party support.

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NORTH SEA STUDY OCCASIONAL PAPER No. 113

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NORTH SEA STUDY OCCASIONAL PAPER No. 116

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NORTH SEA STUDY OCCASIONAL PAPER No. 118