The Relative Efficiency of Automatic and Discretionary Industrial Aid

For the last two decades, the primary instruments for UK regional policy have been discretionary subsidies. Such aid is targeted at “additional” projects - projects that would not have been implemented without the subsidy - and the subsidy should be the minimum necessary for the project to proceed. Discretionary subsidies are thought to be more efficient than automatic subsidies, where many of the aided projects are non-additional and all projects receive the same subsidy rate. The present paper builds on Swales (1995) and Wren (2007a) to compare three subsidy schemes: an automatic scheme and two types of discretionary scheme, one with accurate appraisal and the other with appraisal error. These schemes are assessed on their expected welfare impacts. The particular focus is the reduction in welfare gain imposed by the interaction of appraisal error and the requirements for accountability. This is substantial and difficult to detect with conventional evaluation techniques.

Industrial Structure, Trade and Regional Economics : Market Segmentation

We consider a general equilibrium model a la Bhaskar (Review of Economic Studies 2002): there are complementarities across sectors, each of which comprise (many) heterogenous monopolistically competitive firms. Bhaskar's model is extended in two directions: production requires capital, and labour markets are segmented. Labour market segmentation models the difficulties of labour migrating across international barriers (in a trade context) or from a poor region to a richer one (in a regional context), whilst the assumption of a single capital market means that capital flows freely between countries or regions. The model is solved analytically and a closed form solution is provided. Adding labour market segmentation to Bhaskar's two-tier industrial structure allows us to study, inter alia, the impact of competition regulations on wages and - financial flows both in the regional and international context, and the output, welfare and financial implications of relaxing immigration laws. The analytical approach adopted allows us, not only to sign the effect of policies, but also to quantify their effects. Introducing capital as a factor of production improves the realism of the model and refi nes its empirically testable implications.

Financial liberalisation and industrial development in Malawi

It has been suggested that financial liberalisation may be a key policy to promote industrialisation as it removes the credit access constraint on firms, especially small and medium ones. We investigate the effect of credit expansion in the wake of liberalisation on the structure of the industrial sectors in Malawi and find that, in contrast to the hypothesis above, it resulted in an increase in industrial concentration and a decrease in net firm entry, especially in sectors that are more finance dependent. The case of Malawi is interesting because financial liberalisation has been justified precisely as a means for industrial development and because the implementation of the policy has been regarded as relatively successful.

Infrastructure Finance and Industrial Takeoff in England

That financial matters did not constrain industrial takeoff in the UK is generally accepted in the historical literature; in contrast, contemporary empirical analyses have found evidence that financial development can be a causal determinant of economic growth. We look to reconcile these findings by concentrating on a particular aspect of industrialising UK where inefficiencies in finance could have had bite: The finance of physical infrastructures. We document the historical record and develop the importance of spatial disaggregation and spillovers in both technological and financial development. We develop a simple model that captures the nature of infrastructure finance within a theory of endogenous growth where financial costs are endogenous. We argue that the conception of the finance-growth nexus as a largely static, aggregative phenomenon misses out a good deal of complexity and we relate that complexity to a number of implications for regulation of both financial systems and the emergence of infrastructures

The Significance of Identifying Industrial clusters The Case of Scotland

Industrial clustering policy is now an integral part of economic development planning in most advanced economies. However, there have been concerns in some quarters over the ability of an industrial cluster-based development strategy to deliver its promised economic benefits and this has been increasingly been blamed on the failure by governments to identify industrial clusters. In a study published in 2001, the DTI identified clusters across the UK based on the comparative scale and significance of industrial sectors. The study identified thirteen industrial clusters in Scotland. However the clusters identified are not a homogeneous set and they seem to vary in terms of their geographic concentration within Scotland. This paper examines the spatial distribution of industries within Scotland, thereby identifying more localised clusters. The study follows as closely as possible the DTI methodology which was used to identify such concentrations of economic activity with particular attention directed towards the thirteen clusters identified by the DTI. The paper concludes with some remarks of the general problem of identifying the existence of industrial clusters.

Volatility of Housing

The aim of the project is to develop a theoretical framework where homelessness arises due to various economic and social factors that vary over time. The ultimate goal is i) to understand whether homelessness spells, entrances and exits could be predicted and if so what information is necessary; and ii) to design and evaluate a homelessness prevention programme in a changing and uncertain environment. Examples of the questions we want to answer are: Should it be made easier for people to borrow money so that they can get out of homelessness, or will such borrowing allow people to over-consume today and so fall into homelessness tomorrow? Should precautionary savings be encouraged so that people have cushions to withstand future shocks, or will savings just delay entry into homelessness? What interventions will affect the probability of becoming homeless and how will they affect behaviour? How will interventions affect incentives to save and to consume before homelessness prevention programmes kick in?

Spatial Interactions in Hedonic Pricing Models: The Urban Housing Market of Aveiro, Portugal

Spatial heterogeneity, spatial dependence and spatial scale constitute key features of spatial analysis of housing markets. However, the common practice of modelling spatial dependence as being generated by spatial interactions through a known spatial weights matrix is often not satisfactory. While existing estimators of spatial weights matrices are based on repeat sales or panel data, this paper takes this approach to a cross-section setting. Specifically, based on an a priori definition of housing submarkets and the assumption of a multifactor model, we develop maximum likelihood methodology to estimate hedonic models that facilitate understanding of both spatial heterogeneity and spatial interactions. The methodology, based on statistical orthogonal factor analysis, is applied to the urban housing market of Aveiro, Portugal at two different spatial scales.

Social Housing Policies in Latin America and Singapore: Lessons for China

This paper addresses the challenges facing China in accelerating the pace of rural-urban migration as part of its on-going economic development programme. It explains the push and pull influences on migration and in particular explains why a continuing focus on urbanisation is justified by the very large gap between rural and urban incomes and the relatively higher income elasticity of demand for urban-based goods and services. The provision of affordable housing is an integral part of this structural shift programme. The paper thus considers the most appropriate ways in which housing finance can be mobilised, and thence how both the quality and the affordability of the housing stock can be increased. Positive and negative lessons for China are offered from the different urbanisation experiences of Latin America (especially Colombia) and Singapore.

An Investigation of Housing Affordability in the UK Regions

The housing market has been extensively investigated in the literature; however there is a lack of understanding of the fundamentals a ffecting housing affordability across UK regions as measured by the price to income ratio. The aim of this paper is twofold; fi rstly we calculate the a ffordability ratio based on individuals' incomes. Second we set o f to ask which socio-economic factors could a affect this ratio. The analysis finds a strong influence coming from the mortgage rate, the residents' age and academic quali fications. We also report a positive and signifi cant e ffect from foreign capital coming to the UK. Finally, we record a non-negligible degree of heterogeneity across the twelve regions.

Spatial Takeoff in the First Industrial Revolution

Using the framework of Desmet and Rossi-Hansberg (forthcoming), we present a model of spatial takeoff that is calibrated using spatially-disaggregated occupational data for England in c.1710. The model predicts changes in the spatial distribution of agricultural and manufacturing employment which match data for c.1817 and 1861. The model also matches a number of aggregate changes that characterise the first industrial revolution. Using counterfactual geographical distributions, we show that the initial concentration of productivity can matter for whether and when an industrial takeoff occurs. Subsidies to innovation in either sector can bring forward the date of takeoff while subsidies to the use of land by manufacturing firms can significantly delay a takeoff because it decreases spatial concentration of activity.

Spatial Takeoff in the First Industrial Revolution

Using the framework of Desmet and Rossi-Hansberg (forthcoming), we present a model of spatial takeoff that is calibrated using spatially-disaggregated occupational data for England in c.1710. The model predicts changes in the spatial distribution of agricultural and manufacturing employment which match data for c.1817 and 1861. The model also matches a number of aggregate changes that characterise the first industrial revolution. Using counterfactual geographical distributions, we show that the initial concentration of productivity can matter for whether and when an industrial takeoff occurs. Subsidies to innovation in either sector can bring forward the date of takeoff while subsidies to the use of land by manufacturing firms can significantly delay a takeoff because it decreases spatial concentration of activity.

Modelling Housing Prices using a Present Value State Space Model

This paper introduces a State Space approach to explain the dynamics of rent growth, expected returns and Price-Rent ratio in housing markets. According to the present value model, movements in price to rent ratio should be matched by movements in expected returns and expected rent growth. The state space framework assume that both variables follow an autoregressive process of order one. The model is applied to the US and UK housing market, which yields series of the latent variables given the behaviour of the Price-Rent ratio. Resampling techniques and bootstrapped likelihood ratios show that expected returns tend to be highly persistent compared to rent growth. The Öltered expected returns is considered in a simple predictability of excess returns model with high statistical predictability evidenced for the UK. Overall, it is found that the present value model tends to have strong statistical predictability in the UK housing markets.

Modelling Housing Prices using a Present Value State Space Model

This paper introduces a State Space approach to explain the dynamics of rent growth, expected returns and Price-Rent ratio in housing markets. According to the present value model, movements in price to rent ratio should be matched by movements in expected returns and expected rent growth. The state space framework assume that both variables follow an autoregression process of order one. The model is applied to the US and UK housing market, which yields series of the latent variables given the behaviour of the Price-Rent ratio. Resampling techniques and bootstrapped likelihood ratios show that expected returns tend to be highly persistent compared to rent growth. The filtered expected returns is considered in a simple predictability of excess returns model with high statistical predictability evidence for the UK. Overall, it is found that the present value model tends to have strong statistical predictability in the UK housing markets.