993 resultados para Glasgow (GB)


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This paper attempts to estimate the impact of population ageing on house prices. There is considerable debate about whether population ageing puts downwards or upwards pressure on house prices. The empirical approach differs from earlier studies of this relationship, which are mainly regression analyses of macro time-series data. A micro-simulation methodology is adopted that combines a macro-level house price model with a micro-level household formation model. The case study is Scotland, a country that is expected to age rapidly in the future. The parameters of the household formation model are estimated with panel data from the British Household Panel Survey covering the period 1999-2008. The estimates are then used to carry out a set of simulations. The simulations are based on a set of population projections that represent a considerable range in the rate of population ageing. The main finding from the simulations is that population ageing—or more generally changes in age structure—is not likely a main determinant of house prices, at least in Scotland.

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Traditionally, it is assumed that the population size of cities in a country follows a Pareto distribution. This assumption is typically supported by nding evidence of Zipf's Law. Recent studies question this nding, highlighting that, while the Pareto distribution may t reasonably well when the data is truncated at the upper tail, i.e. for the largest cities of a country, the log-normal distribution may apply when all cities are considered. Moreover, conclusions may be sensitive to the choice of a particular truncation threshold, a yet overlooked issue in the literature. In this paper, then, we reassess the city size distribution in relation to its sensitivity to the choice of truncation point. In particular, we look at US Census data and apply a recursive-truncation approach to estimate Zipf's Law and a non-parametric alternative test where we consider each possible truncation point of the distribution of all cities. Results con rm the sensitivity of results to the truncation point. Moreover, repeating the analysis over simulated data con rms the di culty of distinguishing a Pareto tail from the tail of a log-normal and, in turn, identifying the city size distribution as a false or a weak Pareto law.

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An extensive economics and regional science literature has discussed the importance of social capital for economic growth and development. Yet, what social capital is and how it is formed are elusive issues, which require further investigation. Here, we refer to social capital in terms of civic capital and good culture , as rephrased by Guiso, Sapienza and Zingales (2010) and Tabellini (2010). The accumulation of this kind of capital allows the emerging of regional informal institutions, which may help explaining diff erences in regional development. In this paper, we take a regional perspective and use exploratory space and space-time methods to assess whether geography, via proximity, contributes to the formation of social capital across European regions. In particular, we ask whether generalized trust, a fundamental constituent of social capital and an ingredient of economic development, tends to be clustered across space and over time. From the policy standpoint, the spatial hysteresis of regional trust may contribute to the formation of spatial traps of social capital and act as a further barrier to regional economic development and convergence.

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We use a panel of euro area countries to assess the determinants of long-term sovereign bond yield spreads over the period 1999.01-2010.12. We find that, unlike the period preceding the global financial crisis, European government bond yield spreads are wellexplained by macro- and fiscal fundamentals over the crisis period. We also find that the menu of macro and fiscal risks priced by markets has been significantly enriched since March 2009, including the risk of the crisis’ transmission among EMU member states, international risk and liquidity risk. Finally, we find that sovereign credit ratings are statistically significant in explaining spreads, yet compared to macro- and fiscal fundamentals their role is limited.

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We use firm level data to assess the role of exporting in the link between financial health and rm survival. The data are for the UK and France. We examine whether fi rms at diff erent stages of export activity (starters, exiters, continuers, switchers) react di fferently to changes in financial variables. In general, export starters and exiters experience much stronger adverse e ffects of fi nancial constraints for their survival prospects. By contrast, the exit probability of continuous exporters and export switchers is less negatively a ffected by financial characteristics. These relationships between exporting, finance and survival are broadly similar in the British and French sub-samples.

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Recent work on optimal monetary and fiscal policy in New Keynesian models suggests that it is optimal to allow steady-state debt to follow a random walk. Leith and Wren-Lewis (2012) consider the nature of the timeinconsistency involved in such a policy and its implication for discretionary policy-making. We show that governments are tempted, given inflationary expectations, to utilize their monetary and fiscal instruments in the initial period to change the ultimate debt burden they need to service. We demonstrate that this temptation is only eliminated if following shocks, the new steady-state debt is equal to the original (efficient) debt level even though there is no explicit debt target in the government’s objective function. Analytically and in a series of numerical simulations we show which instrument is used to stabilize the debt depends crucially on the degree of nominal inertia and the size of the debt-stock. We also show that the welfare consequences of introducing debt are negligible for precommitment policies, but can be significant for discretionary policy. Finally, we assess the credibility of commitment policy by considering a quasi-commitment policy which allows for different probabilities of reneging on past promises. This on-line Appendix extends the results of this paper.

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This paper examines the impact of Federal Funds rate (FFR) surprises on stock returns in the United States over the period 1989-2009, focusing on the impact of the recent financial crisis. We find that prior to the crisis, stock prices increased as a response to unexpected FFR cuts. State dependence is also identified with stocks exhibiting larger increases when interest rate easing coincided with recessions, bear stock markets, and tightening credit market conditions. However, an important structural shift took place during the financial crisis, which changed the stock market response to FFR shocks, as well as the nature of state dependence. Specifically, during the crisis period stock market participants did not react positively to unexpected FFR cuts. Our results highlight the severity of the recent financial turmoil episode and the ineffectiveness of conventional monetary policy close to the zero lower bound for nominal interest rates.

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This paper considers Bayesian variable selection in regressions with a large number of possibly highly correlated macroeconomic predictors. I show that by acknowledging the correlation structure in the predictors can improve forecasts over existing popular Bayesian variable selection algorithms.

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Recent work on optimal monetary and fiscal policy in New Keynesian models suggests that it is optimal to allow steady-state debt to follow a random walk. Leith and Wren-Lewis (2012) consider the nature of the timeinconsistency involved in such a policy and its implication for discretionary policy-making. We show that governments are tempted, given inflationary expectations, to utilize their monetary and fiscal instruments in the initial period to change the ultimate debt burden they need to service. We demonstrate that this temptation is only eliminated if following shocks, the new steady-state debt is equal to the original (efficient) debt level even though there is no explicit debt target in the government’s objective function. Analytically and in a series of numerical simulations we show which instrument is used to stabilize the debt depends crucially on the degree of nominal inertia and the size of the debt-stock. We also show that the welfare consequences of introducing debt are negligible for precommitment policies, but can be significant for discretionary policy. Finally, we assess the credibility of commitment policy by considering a quasi-commitment policy which allows for different probabilities of reneging on past promises. This on-line Appendix extends the results of this paper.

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This paper offers an integrated analysis of the forces shaping the emergence of the African slave trade over the early modern period. We focus our attention on two questions. First, why most of the increase in the demand for slaves during this period came exclusively from western Europeans. Second, and of most relevance for present-day development outcomes, why was the overwhelming majority of slaves of African origin. Technological differences in manufacturing technology, the specificities of sugar (and other crops’) production, and the cultural fragmentation of the African continent all play a role in the analysis. Supporting evidence for each of our claims is provided from a broad corpus of relevant literature.

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This paper studies discretionary non-cooperative monetary and fiscal policy stabilization in a New Keynesian model, where the fiscal policymaker uses a distortionary taxe as the policy instrument and operates with long periods between optimal time-consistent adjustments of the instrument. We demonstrate that longer fiscal cycles result in stronger complementarities between the optimal actions of the monetary and fiscal policymakers. When the fiscal cycle is not very long, the complementarities lead to expectation traps. However, with a sufficiently long fiscal cycle — one year in our model — no learnable time-consistent equilibrium exists. Constraining the fiscal policymaker in its actions may help to avoid these adverse effects.

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Discretionary policymakers cannot manage private-sector expectations and cannot coordinate the actions of future policymakers. As a consequence, expectations traps and coordination failures can occur and multiple equilibria can arise. To utilize the explanatory power of models with multiple equilibria it is first necessary to understand how an economy arrives to a particular equilibrium. In this paper we employ notions of learnability and self-enforceability to motivate and identify equilibria of particular interest. Central among these criteria are whether the equilibrium is learnable by private agents and jointly learnable by private agents and the policymaker. We use two New Keynesian policy models to identify the strategic interactions that give rise to multiple equilibria and to illustrate our methods for identifying equilibria of interest. Importantly, unless the Pareto-preferred equilibrium is learnable by private agents, we find little reason to expect coordination on that equilibrium.

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This paper presents a DSGE model in which long run inflation risk matters for social welfare. Aggregate and welfare effects of long run inflation risk are assessed under two monetary regimes: inflation targeting (IT) and price-level targeting (PT). These effects differ because IT implies base-level drift in the price level, while PT makes the price level stationary around a target price path. Under IT, the welfare cost of long run inflation risk is equal to 0.35 percent of aggregate consumption. Under PT, where long run inflation risk is largely eliminated, it is lowered to only 0.01 per cent. There are welfare gains from PT because it raises average consumption for the young and lowers consumption risk substantially for the old. These results are strongly robust to changes in the PT target horizon and fairly robust to imperfect credibility, fiscal policy, and model calibration. While the distributional effects of an unexpected transition to PT are sizeable, they are short-lived and not welfare-reducing.

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Faced with the problem of pricing complex contingent claims, an investor seeks to make his valuations robust to model uncertainty. We construct a notion of a model- uncertainty-induced utility function and show that model uncertainty increases the investor's eff ective risk aversion. Using the model-uncertainty-induced utility function, we extend the \No Good Deals" methodology of Cochrane and Sa a-Requejo [2000] to compute lower and upper good deal bounds in the presence of model uncertainty. We illustrate the methodology using some numerical examples.

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It is a well-established fact in the literature on simulating Input-Output tables that mechanical methods for estimating intermediate trade lead to biased results where cross-hauling is underestimated and Type-I multipliers are overstated. Repeated findings to this effect have led to a primary emphasis on advocating the accurate estimation of intermediate trade flows. This paper reviews previous research and argues for a qualification of the consensus view: When simulating IO tables, construction approaches need to consider spill-over effects driven by wage and consumption flows. In particular, for the case of metropolitan economies, wage and consumption flows are important if accurate Type-II multipliers are to be obtained. This is demonstrated by constructing an interregional Input-Output table, which captures interdependencies between a city and its commuter belt, nested within the wider regional economy. In addition to identifying interdependencies caused by interregional intermediate purchases, data on subregional household incomes and commuter flows are used to identify interdependencies from wage payments and household consumption. The construction of the table is varied around a range of assumptions on intermediate trade and household consumption to capture the sensitivity of multipliers.