Productivity, Preferences and UIP deviations in an Open Economy Business Cycle Model

We show that a flex-price two-sector open economy DSGE model can explain the poor degree of international risk sharing and exchange rate disconnect. We use a suite of model evaluation measures and examine the role of (i) traded and non-traded sectors; (ii) financial market incompleteness; (iii) preference shocks; (iv) deviations from UIP condition for the exchange rates; and (v) creditor status in net foreign assets. We find that there is a good case for both traded and non-traded productivity shocks as well as UIP deviations in explaining the puzzles.

The Timing of Asset Trade and Optimal Policy in Dynamic Open Economies

Using a standard open economy DSGE model, it is shown that the timing of asset trade relative to policy decisions has a potentially important impact on the welfare evaluation of monetary policy at the individual country level. If asset trade in the initial period takes place before the announcement of policy, a national policymaker can choose a policy rule which reduces the work effort of households in the policymaker’s country in the knowledge that consumption is fully insured by optimally chosen international portfolio positions. But if asset trade takes place after the policy announcement, this insurance is absent and households in the policymaker’s country bear the full consumption consequences of the chosen policy rule. The welfare incentives faced by national policymakers are very different between the two cases. Numerical examples confirm that asset market timing has a significant impact on the optimal policy rule.

Balanced Budget Government Spending in a Small Open Regional Economy

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.

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.

How much does a single graduation cohort from further education colleges contribute to an open regional economy?

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.

An investigation of the determinants of household demand for bushmeat in the Serengeti using an open-ended choice experiment

Illegal hunting for bushmeat is regarded as an important cause of biodiversity decline in Africa. We use a stated preferences method to obtain information on determinants of demand for bushmeat in villages around the Serengeti National Park, Tanzania. We estimate the effects of changes in the own price of bushmeat and in the prices of two substitute protein sources – fish and chicken. Promoting the availability of protein substitutes at lower prices would be effective at reducing pressures on wildlife. Supply-side measures that raise the price of bushmeat would also be effective.

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.