Consumption growth and spatial poverty traps : an analysis of the effect of social services and community infrastructures on living standards in rural Peru.

Why are there areas with persistenly low levels of income or consumption? This could result from the concentration of households with a low capital endowment or from variations in households’ environment. Peru is a country with a very much fragmented topography and climate, that combines dry deserts, high mountains and rain forest. One important question is to assess the weight of the geographic endowment in the growth process. If differences in geographic endowment matter more than those in households’ characteristics, then encouraging migration to better endowed regions might be a good development policy whereas, in the opposite, it might be better to invest in households’ capital. Of course several factors, either geographic or not, can combine to explain persistent poverty in a given area. In this chapter we test the effect of local geographic endowment of capital on household growth in living standards in rural Peru, using a four years unbalanced panel data set. Our theoretical model of household consumption growth allows for the effect of community variables to modify the returns to augmented capital in the household production function. Three different sources of data are used: the ENAHO 1997-2000 households surveys, the population census of 1993 and the district infrastructure census of 1997. Altogether the addition of these different data sources makes an unusually rich data set, at least when considered with developing country standards. As in Jalan and Ravallion (2002), we use a quasi-differencing method to identify the impact of locally determined geographic and socioeconomic variables, while removing unobserved household and community level fixed effects. GMM are then used to estimate the model parameters. Several significant interesting results appear, showing that private consumption growth depends on local geographic variables, but more on local endowments of private and public assets than on pure geographic characteristics. This suggests to combine policies focused on private and public asset endowments that will reinforce local positive externalities, with infrastructure investments that will help poor households to take advantage of growth opportunities, offered by more dynamic markets across local communities.Pauvreté; Développement; Inégalités spatiales;

Openness and Growth: The Long Shadow of the Berlin Wall

The question whether international openness causes higher domestic growth has been subject to intense discussions in the empirical growth literature. This paper addresses this issue using the fall of the Berlin wall in 1990 as a natural experiment. We analyze whether the slow-down in convergence in per capita income between East and West Germany since the mid-1990s and the lower international openness of East Germany are linked. We address the endogeneity of openness by adapting the methodology proposed by Frankel and Romer (1999) in a panel framework. We instrument openness with time-invariant exogenous geographic variables and time-varying exogenous policy variables. We also distinguish different channels of integration. Our paper has three main findings. First, geographic variables have a significant impact on regional openness. Second, controlling for geography, East German states are less integrated into international markets along all dimensions of integration considered. Third, the degree of openness for trade has a positive impact on regional income per capita.openness, growth, German re-unification

Spatial poverty traps?

Can place of residence make the difference between growth and contraction in living standards for otherwise identical households? The authors test for the existence of spatial poverty traps, using a micro model of consumption growth incorporating geographic externalities, whereby neighborhood endowments of physical and human capital influence the productivity of a household's own capital. By allowing for nonstationary but unobserved individual effects on growth rates, they are able to deal with latent heterogeneity (whereby hidden factors entail that seemingly identical households see different consumption gains over time), yet identify the effects of stationary geographic variables. They estimate the model using farm-household panel data from post-reform rural China. They find strong evidence of spatial poverty traps. Their results strengthen the case -- both for efficiency and equity -- for investing in the geographic capital of poor people.Environmental Economics&Policies,Economic Theory&Research,Public Health Promotion,Health Monitoring&Evaluation,Economic Conditions and Volatility,Achieving Shared Growth,Economic Theory&Research,Environmental Economics&Policies,Inequality,Health Monitoring&Evaluation

THE CONTRIBUTION OF ENVIRONMENTAL AMENITIES TO AGRICULTURAL LAND VALUES: HEDONIC MODELLING USING GEOGRAPHIC INFORMATION SYSTEMS DATA

Geographic Information Systems (GIS) data are used in a hedonic model to measure the impact of recreational and scenic amenities on agricultural land values. Results indicate agricultural land values are determined by environmental amenities as well as production attributes. Significant amenity variables included scenic view, elk habitat and fishery productivity.Environmental Economics and Policy, Land Economics/Use,

Applications of Geographic Information Systems for the Analysis of Apartment Rents

This study is the first to incorporate comprehensive regional factors into the analysis of the variations of apartment rent in a particular metropolitan area. A Geographic Information Systems (GIS) procedure is developed to generate regional variables for the analysis. Results show that not only the individual apartment's characteristics, but also the regional factors are important in determining apartment rents.

Efficiency effects of quality of service and environmental factors: experience from Norwegian electricity distribution

Since the 1990s, efficiency and benchmarking analysis has increasingly been used in network utilities research and regulation. A recurrent concern is the effect of environmental factors that are beyond the influence of firms (observable heterogeneity) and factors that are not identifiable (unobserved heterogeneity) on measured cost and quality performance of firms. This paper analyses the effect of geographic and weather factors and unobserved heterogeneity on a set of 128 Norwegian electricity distribution utilities for the 2001-2004 period. We utilize data on almost 100 geographic and weather variables to identify real economic inefficiency while controlling for observable and unobserved heterogeneity. We use the factor analysis technique to reduce the number of environmental factors into few composite variables and to avoid the problem of multicollinearity. We then estimate the established stochastic frontier models of Battese and Coelli (1992; 1995) and the recent true fixed effects models of Greene (2004; 2005) without and with environmental variables. In the former models some composite environmental variables have a significant effect on the performance of utilities. These effects vanish in the true fixed effects models. However, the latter models capture the entire unobserved heterogeneity and therefore show significantly higher average efficiency scores.Efficiency; Quality of service; Input distance function; Stochastic frontier analysis

How perilous are broad-scale correlations with environmental variables?

Many studies correlate geographic variation of biotic variables (e.g., species ranges, species richness, etc.) with variation in environmental variables (climate, topography, history). Often, the resulting correlations are interpreted as evidence of causal links. However, both the dependent and independent variables in these analyses are strongly spatially structured. Several studies have suggested that spatially structured variables may be significantly correlated with one another despite the absence of a causal link between them. In this study we ask: if two variables are spatially structured, but causally unrelated, how strong is the expected correlation between them? As a specific example, we consider the correlations between broad-scale variation in gamma species richness and climatic variables. Are these correlations likely to be statistical artefacts? To answer these questions, we randomly generated pseudo-climatic variables that have the same range and spatial autocorrelation as temperature and precipitation in the Americas. We related mammal and bird species richness both to the real and the pseudo-climatic variables. We also observed the correlations among pseudo-climate simulations. Correlations among randomly generated, spatially unstructured, variables are very small. In contrast, the median correlations between spatially structured variables are near r2=0.1 – 0.3, and the 95% confidence limits extend to r2=0.6 – 0.7. Viewing this as a null expectation, given spatially structured variables, it is worth nothing that published richness–climate correlations are typically marginally stronger than these values. However, many other published richness–environment correlations would fail this test. Tests of the “predictive ability” of a correlation cannot reliably distinguish correlations due to spatial structure from causal relationships. Our results suggest a three-part update of Tobler’s “First Law of Geography”: #1) Everything in geography that is spatially structured will be collinear. #2) Near things are more related than distant things. #3) The more strongly spatially structured two variables are, the stronger the collinearity between them will be

Hotel Location in Tourism Cities: Madrid 1936-1998.

To determine how the positioning of new hotels is affected by the distribution of similar incumbent competitors, this paper investigates geographic location, price, size, and services. With data on all 240 hotels operating in the city of Madrid between 1936 and 1998, a model of geographic and product location at the time of the hotels’ foundings is estimated based on the above mentioned variables. These are simultaneously determined and contingent upon the changing socioeconomic and urban circumstances of the city. The findings suggest that agglomeration occurs only among differentiated establishments. In the balance between agglomeration and differentiation strategies, particularly significant is the trade-off between price and geographic dimensions.Emplacement des hôtels dans les villes touristiques: Madrid 1936–1998. Pour déterminer comment le positionnement des nouveaux hôtels est affecté par la distribution des concurrents similaires et déjà établis, cet article examine situation géographique, prix, grandeur et services. Avec des données sur tous les 240 hôtels en opération à Madrid entre 1936 et 1998, on calcule un modèle de la situation géographique et des services au moment de la fondation des hôtels, en se basant sur les variables surmentionnées. Celles-ci dépendent au même temps des circonstances urbaines et socioéconomiques changeantes de la ville. Les résultats suggèrent que l’agglomération a lieu seulement parmi les établissements différenciés. Dans l’équilibre entre les stratégies d’agglomération et de différentiation, le compromis entre prix et situation est particulièrement significatif.Hotels; Location; Madrid; Hotels; Situation;

Growth, History, or Institutions? What Explains State Fragility in Sub-Saharan Africa

We explore the determinants of state fragility in sub-Saharan Africa. Controlling for a wide range of economic, demographic, geographic and istitutional regressors, we find that institutions, and in particular the civil liberties index and the number of revolutions, are the main determinants of fragility, even taking into account their potential endogeneity. Economic factors such as income growth and investment display a non robust impact after controlling for omitted variables and reverse causality. Colonial variables reflecting the history of the region display a marginal impact on fragility once institutions are accounted for.State fragility, Africa, institutions, colonial history