Coro Chasco

Building an environmental quality index for a big city: a spatial interpolation approach combined with a distance indicator

One of the main tasks of regional and environmental economics is to construct Environmental Quality Indexes for big cities. A standard method is to generate a single measure as a linear combination of several contaminants by applying Principal Component Analysis. Spatial interpolation is then carried out to determine pollution levels across the city. We innovate on this method and propose an alternative approach. First, we combine a set of noise and air pollutants measured at a number of monitoring stations with data available for each census tract. This yields a mixed environmental index that is socioeconomically more complete. We then apply kriging to match the monitoring station records to the census data. Finally, we construct a composite pollution index using the Pena Distance method (DP2), which proves more robust than traditional approaches.

Heterogeneity in Perceptions of Noise and Air Pollution: A Spatial Quantile Approach on the City of Madrid

Abstract In this paper, we apply a hedonic housing price model to estimate the willingness to pay for less air pollution and noise in the city of Madrid. Using subjective data on the perception of air pollution and noise by the Madrid residents, we apply a quantile conditionally parametric model that allows one to quantify the heterogeneity of this willingness to pay values across quantiles of the conditional distributions of housing prices and their spatial heterogeneity across the whole study area. The results show that implicit prices for clean and quiet environment differ substantially across the housing markets, depending on the perceived intensity of pollution, accessibility to jobs and leisure, and some socioeconomic characteristics of the population. In particular, in some areas, households seem to make a trade-off between improvements in communication and some worsening in environmental conditions.

Long-run determinants of economic growth in South America

Based on an annual historical database for South American countries from 1960 to 2008, we develop an empirical study to gain insight into the long-run determinants of economic growth using a two-equation framework. A system of two panel data models is estimated to identify the growth determinants and their connection with foreign direct investment. We find that economic growth is driven most strongly by physical and human capital accumulation, as well as by sectorial exports, and that institutions and policy have a substantial impact on economic growth and investment. Macroeconomic disturbances have a significant detrimental effect on long-run growth. Trade openness correlates positively with foreign investment, indicating that relatively closed countries stand to benefit most from opening up their economies. Our division of the sample into two sub-periods, 1960–1980 and 1981–2008, indicates a structural change.

Evolution of the Influence of Geography on the Location of Production in Spain (1930–2005)

In this paper, we investigate the relative importance of geographic features on the location of production in Spain. Specifically, we want to quantify how much of the spatial pattern of GDP can be attributed to only exoge-nous first nature elements (physical and political geography) and how much can be derived from endogenous second nature factors (man-made agglomeration economies). In order to disentangle both effects empiri-cally, and to learn how they are interrelated, we control for second nature. We use a methodology based on an analysis of variance (ANOVA), which is applied to a panel of 47 Spanish provinces in the period 1930-2005. We demonstrate that results can be biased if spatial autocorrelation and spatial heterogeneity, as well as multicollinearity and endogeneity, are not prop-erly taken into account. In the Spanish case, we detect strong spatial het-erogeneity in the form of two main clusters. As expected, gross second na-ture forces are more important than net natural advantages, though their effects range from about 55% in the hinterland to 80% in the coast.

Dealing with Data at Various Spatial Scales and Supports: An Application on Traffic Noise and Air Pollution Effects on Housing Prices with Multilevel Models

In empirical studies dealing with spatial data, researchers are frequently confronted with data available at different spatial scales. For instance, hedonic models on housing prices usually combine individual data pertaining to the price and structural characteristics of the dwelling and socio-economic neighbourhood characteristics that are available at some upper administrative levels. Another frequent issue is the change of support problem or misaligned regression problem (Gotway and Young 2002; Banerjee et al. 2004) when there is a spatial mismatch between the spatial supports of the variables. For instance, the measurement of air quality is based on regular sampling at a few stations in an area whereas socio-economic data are available for aggregate administrative.

A comparative analysis of the effect of aid and microfinance on growth

Abstract This paper investigates the effect of official development aid (ODA) and microfinance (MF) on economic growth and compares the results. We identify and analyse the transmission mechanisms from ODA and microfinance to growth. We then study the effects of ODA and microfinance on growth, using an unbalanced panel of 67 countries for the period 2001–2011. Accounting for country and time effects, our results show that microfinance has a positive and statistically significant effect on economic growth through private investment, while ODA has no effect on growth. This suggests that deploying resources in the microfinance industry will foster economic development in poor countries.

Spatial econometrics principles and challenges in Jean Paelinck's research

Abstract This special issue contains a selection of many excellent papers and posters presented at the Sixth ‘Jean Paelinck’ Seminar of Spatial Econometrics, which was held at the Universidad Autónoma de Madrid (UAM) in October, 2013. The collection of papers addresses some of the major concerns and progression lines proposed by professor Paelinck along his academic life for spatial econometrics: the treatment of spatial data and the need to specify and estimate appropriate econometric models in the realm of regional and urban science. The first two papers in this issue present two methods to detect spatial clusters (Rodero-Cosano, Salinas-Pérez, García-Alonso and Salvador-Carulla) and concentrations (Thomas-Agnan and Bonneu) using homogeneous micro-data and individual observations, respectively, to adequately deal with the Modifiable Areal Unit Problem. The following three articles focus on the specification of spatial effects—spatial autocorrelation and spatial heterogeneity—in more complex situations. Le Gallo and Chasco propose a non-parametric approach to deal with spatial effects when the models parametric structure is unknown, as it is the case in hedonic models with large databases. Ezcurra and Ríos derive a spatial Durbin panel data model from theory in order to model the spatio-temporal relationship between output volatility and regional growth. Finally, Díaz-Lanchas, Gallego, Llano and De la Mata take into account spatial complexity in trade flows introducing spatial dependence in a gravity model.

Spatial analysis of urban growth in Spain, 1900-2001

The purpose of this paper is to improve the knowledge of the Spanish urban system. We study the evolution of population growth among the group of 722 municipalities included in the Spanish urban areas over the period from 1900-2001. Urban population cross-sectional distribution is characterized by means of nonparametric estimations of density functions, and the growth process is modeled as a first-order stationary Markov chain. A spatial SUR model is also estimated for the Zipf’s law. Spatial effects are then introduced within the Markov chain framework using regional conditioning and spatial Markov chains.(This abstract was borrowed from another version of this item.)