Structural Interactions in Spatial Panels

Until recently, much effort has been devoted to the estimation of panel data regression models without adequate attention being paid to the drivers of diffusion and interaction across cross section and spatial units. We discuss some new methodologies in this emerging area and demonstrate their use in measurement and inferences on cross section and spatial interactions. Specifically, we highlight the important distinction between spatial dependence driven by unobserved common factors and those based on a spatial weights matrix. We argue that, purely factor driven models of spatial dependence may be somewhat inadequate because of their connection with the exchangeability assumption. Limitations and potential enhancements of the existing methods are discussed, and several directions for new research are highlighted.

Understanding Interactions in Social Networks and Committees

While much of the literature on cross section dependence has focused mainly on estimation of the regression coefficients in the underlying model, estimation and inferences on the magnitude and strength of spill-overs and interactions has been largely ignored. At the same time, such inferences are important in many applications, not least because they have structural interpretations and provide useful interpretation and structural explanation for the strength of any interactions. In this paper we propose GMM methods designed to uncover underlying (hidden) interactions in social networks and committees. Special attention is paid to the interval censored regression model. Our methods are applied to a study of committee decision making within the Bank of England’s monetary policy committee.

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.

Inequalities in Child Mortality in India: A District-Level Analysis

This paper measures the degree of inequality in child mortality rates across districts in India, using data from the 1981, 1991 and 2001 Indian population censuses. The results show that child mortality is more concentrated in less developed districts in all three census years. Further, between 1981 and 2001, the inequality in child mortality seems to have increased to the advantage of the more developed districts (i.e., there was an increasing concentration of child mortality in less developed districts). However, the inequality in female child mortality rates seems to have declined between 1991 and 2001, even as it increased – albeit at a slower rate than before – for male child mortality rates. In the decomposition analysis, it is found that while a more equitable distribution of medical facilities and safe drinking water across districts did contribute towards reducing inequality in child mortality between 1981 and 1991, different levels of structural change among districts were responsible for a very large part of the inequality in child mortality to the advantage of the more developed districts in all three census years. Other variables which played important roles in increasing inequality included a measure of infrastructure development, female literacy, and a social group status variable. The paper concludes with some brief comments on the policy implications of the findings.

Ecological-economic modelling of interactions between wild and commercial bees and pesticide use

The decline in extent of wild pollinators in recent years has been partly associated with changing farm practices and in particular with increase of pesticide use. In this paper we combine ecological modelling with economic analysis of a single farm output under the assumption that both pollination and pest control are essential inputs. We show that the drive to increase farm output can lead to a local decline in the wild bee population. Commercial bees are often considered an alternative to wild pollinators, but we show that their introduction can lead to further decline and finally local extinction of wild bees. The transitions between different outcomes are characterised by threshold behaviour and are potentially difficult to predict and detect in advance. Small changes in economic (input prices) and ecological (wild bees carrying capacity and effect of pesticides on bees) can move the economic-ecological system beyond the extinction threshold. We also show that increasing the pesticide price or decreasing the commercial bee price might lead to reestablishment of wild bees following their local extinction. Thus, we demonstrate the importance of combining ecological modelling with economics to study the provision of ecosystem services and to inform sustainable management of ecosystem service providers.

Educational spillovers and parental migration

Impacts of parental emigration on educational outcomes of children and, in turn, the children’s influence on peers are theoretically ambiguous. Using novel data I collected on migration experiences and timing, family background and school performance of lower secondary pupils in Poland, I analyse empirically whether children with parents working abroad (PWA) influence school performance of their classmates. Migration is mostly temporary in nature, with one parent engaging in employment abroad. As many as 63% of migrant parents have vocational qualifications, 29% graduated from high school, 4% have no qualifications and the remaining 4% graduated from university. Almost 18% of all children are affected by parental migration and, on average, 6.5% of pupils in a class have a parent abroad. Perhaps surprisingly, estimates suggest that pupils benefit from the presence of PWA classmates. PWA pupils whose parents graduated from high school exert the biggest positive impact on their classroom peers. Further, classmates are differently affected by PWA children; those who themselves experienced migration within the family benefit most. This positive effect is likely driven by the student level interactions or increased teachers’ commitment to classes with students from migrant families.