(Optimal) Spatial Aggregation in the Determinants of Industrial Location

Empirical studies on the determinants of industrial location typically use variables measured at the available administrative level (municipalities, counties, etc.). However, this amounts to assuming that the effects these determinants may have on the location process do not extent beyond the geographical limits of the selected site. We address the validity of this assumption by comparing results from standard count data models with those obtained by calculating the geographical scope of the spatially varying explanatory variables using a wide range of distances and alternative spatial autocorrelation measures. Our results reject the usual practice of using administrative records as covariates without making some kind of spatial correction. Keywords: industrial location, count data models, spatial statistics JEL classification: C25, C52, R11, R30

Indirect likelihood inference

Given a sample from a fully specified parametric model, let Zn be a given finite-dimensional statistic - for example, an initial estimator or a set of sample moments. We propose to (re-)estimate the parameters of the model by maximizing the likelihood of Zn. We call this the maximum indirect likelihood (MIL) estimator. We also propose a computationally tractable Bayesian version of the estimator which we refer to as a Bayesian Indirect Likelihood (BIL) estimator. In most cases, the density of the statistic will be of unknown form, and we develop simulated versions of the MIL and BIL estimators. We show that the indirect likelihood estimators are consistent and asymptotically normally distributed, with the same asymptotic variance as that of the corresponding efficient two-step GMM estimator based on the same statistic. However, our likelihood-based estimators, by taking into account the full finite-sample distribution of the statistic, are higher order efficient relative to GMM-type estimators. Furthermore, in many cases they enjoy a bias reduction property similar to that of the indirect inference estimator. Monte Carlo results for a number of applications including dynamic and nonlinear panel data models, a structural auction model and two DSGE models show that the proposed estimators indeed have attractive finite sample properties.

Location Determinants of New Firms: Does Skill Level of Human Capital Really Matter?

This paper is about the role played by stock of human capital on location decisions of new manufacturing plants. We analyse the effect of several skill levels (from basic school to PhD) on decisions about the location of plants in various industries and, therefore, of different technological levels. We also test whether spatial aggregation level biases the results and determine the most appropriate areas to be considered in analyses of these phenomena. Our main statistical source is the Register of Manufacturing Establishments of Catalonia (REIC), which has plant-level microdata on the locations of new manufacturing plants. Keywords: agglomeration economies, industrial location, human capital, count-data models, spatial econometrics.

Industrial Location and Space: New Insights

This paper tries to resolve some of the main shortcomings in the empirical literature of location decisions for new plants, i.e. spatial effects and overdispersion. Spatial effects are omnipresent, being a source of overdispersion in the data as well as a factor shaping the functional relationship between the variables that explain a firm’s location decisions. Using Count Data models, empirical researchers have dealt with overdispersion and excess zeros by developments of the Poisson regression model. This study aims to take this a step further, by adopting Bayesian methods and models in order to tackle the excess of zeros, spatial and non-spatial overdispersion and spatial dependence simultaneously. Data for Catalonia is used and location determinants are analysed to that end. The results show that spatial effects are determinant. Additionally, overdispersion is descomposed into an unstructured iid effect and a spatially structured effect. Keywords: Bayesian Analysis, Spatial Models, Firm Location. JEL Classification: C11, C21, R30.

Nonclassical measurement error with applications to labor and development issues

Zero correlation between measurement error and model error has been assumed in existing panel data models dealing specifically with measurement error. We extend this literature and propose a simple model where one regressor is mismeasured, allowing the measurement error to correlate with model error. Zero correlation between measurement error and model error is a special case in our model where correlated measurement error equals zero. We ask two research questions. First, we wonder if the correlated measurement error can be identified in the context of panel data. Second, we wonder if classical instrumental variables in panel data need to be adjusted when correlation between measurement error and model error cannot be ignored. Under some regularity conditions the answer is yes to both questions. We then propose a two-step estimation corresponding to the two questions. The first step estimates correlated measurement error from a reverse regression; and the second step estimates usual coefficients of interest using adjusted instruments.

Generació de codi amb WebRatio

L'objectiu d'aquest PFC és la implementació d'una eina que s'encarregui de transformar un model de dades en un model de navegació complet i correcte. Per fer-ho, el programa WebRatio suporta completament el llenguatge WebML i s'utilitzarà com a dissenyador dels models de dades i també com a eina per comprovar els models de navegació generats.

The Geographical Scope of Industrial Location Determinants: An Alternative Approach

This paper considers the estimation of the geographical scope of industrial location determinants. While previous studies impose strong assumptions on the weighting scheme of the spatial neighbour matrix, we propose a exible parametrisation that allows for di fferent (distance-based) de finitions of neighbourhood and di fferent weights to the neighbours. In particular, we estimate how far can reach indirect marginal e ffects and discuss how to report them. We also show that the use of smooth transition functions provides tools for policy analysis that are not available in the traditional threshold modelling. Keywords: count data models, industrial location, smooth transition functions, threshold models. JEL-Codes: C25, C52, R11, R30.

Final Report for the Iowa Livestock Industry Waste Characterization and Methane Recovery Information Dissemination Project, 2003

The Iowa livestock industry generates large quantities of manure and other organic residues; composed of feces, urine, bedding material, waste feed, dilution water, and mortalities. Often viewed as a waste material, little has been done to characterize and determine the usefulness of this resource. The Iowa Department of Natural Resources initiated the process to assess in detail the manure resource and the potential utilization of this resource through anaerobic digestion coupled with energy recovery. Many of the pieces required to assess the manure resource already exist, albeit in disparate forms and locations. This study began by interpreting and integrating existing Federal, State, ISU studies, and other sources of livestock numbers, housing, and management information. With these data, models were analyzed to determine energy production and economic feasibility of energy recovery using anaerobic digestion facilities on livestock faxms. Having these data individual facilities and clusters that appear economically feasible can be identified specifically through the use of a GIs system for further investigation. Also livestock facilities and clusters of facilities with high methane recovery potential can be the focus of targeted educational programs through Cooperative Extension network and other outreach networks, providing a more intensive counterpoint to broadly based educational efforts.

Informal care and labour force participation among middle-aged women in Spain

Informal care is today the form of support most commonly used by those who need other peoplein order to carry out certain activities that are considered basic (eating, dressing, taking a shower,etc.), in Spain and in most other countries in the region. The possible labour opportunity costsincurred by these informal carers, the vast majority of whom are middle-aged women, have not asyet been properly quantified in Spain. It is, however, crucially important to know these quantities ata time when public authorities appear to be determined to extend the coverage offered up to nowas regards long-term care.In this context, we use the Spanish subsample of the European Community Household Panel (1994-2001) to estimate a dynamic ordered probit and so attempt to examine the effects of various typesof informal care on labour behaviour. The results obtained indicate the existence of labouropportunity costs for those women who live with the dependent person they care for, but not forthose who care for someone outside the household. Furthermore, whereas caregiving for morethan a year has negative effects on labour force participation, the same cannot be said of those who start caregiving and stop caregiving .

Quantitative antibiogram as a typing method for the prospective epidemiological surveillance and control of MRSA: comparison with molecular typing.

OBJECTIVE: Evaluation of the quantitative antibiogram as an epidemiological tool for the prospective typing of methicillin-resistant Staphylococcus aureus (MRSA), and comparison with ribotyping. METHODS: The method is based on the multivariate analysis of inhibition zone diameters of antibiotics in disk diffusion tests. Five antibiotics were used (erythromycin, clindamycin, cotrimoxazole, gentamicin, and ciprofloxacin). Ribotyping was performed using seven restriction enzymes (EcoRV, HindIII, KpnI, PstI, EcoRI, SfuI, and BamHI). SETTING: 1,000-bed tertiary university medical center. RESULTS: During a 1-year period, 31 patients were found to be infected or colonized with MRSA. Cluster analysis of antibiogram data showed nine distinct antibiotypes. Four antibiotypes were isolated from multiple patients (2, 4, 7, and 13, respectively). Five additional antibiotypes were isolated from the remaining five patients. When analyzed with respect to the epidemiological data, the method was found to be equivalent to ribotyping. Among 206 staff members who were screened, six were carriers of MRSA. Both typing methods identified concordant of MRSA types in staff members and in the patients under their care. CONCLUSIONS: The quantitative antibiogram was found to be equivalent to ribotyping as an epidemiological tool for typing of MRSA in our setting. Thus, this simple, rapid, and readily available method appears to be suitable for the prospective surveillance and control of MRSA for hospitals that do not have molecular typing facilities and in which MRSA isolates are not uniformly resistant or susceptible to the antibiotics tested.

The ViRVIG Institute

In this paper we present the ViRVIG Institute, a recently created institution that joins two well-known research groups: MOVING in Barcelona, and GGG in Girona. Our main research topics are Virtual Reality devices and interaction techniques, complex data models, realistic materials and lighting, geometry processing, and medical image visualization. We briefly introduce the history of both research groups and present some representative projects. Finally, we sketch our lines for future research

The Determinants of Exit in Argentina: Core and Peripheral Regions

This paper analyses the regional determinants of exit in Argentina. We find evidence of a dynamic revolving door by which past entrants increase current exits, particularly in the peripheral regions. In the central regions, current and past incumbents cause an analogous displacement effect. Also, exit shows a U-shaped relationship with respect to the informal economy, although the positive effect is weaker in the central regions. These findings point to the existence of a core-periphery structure in the spatial distribution of exits. Key words: firm exit, count data models, Argentina JEL: R12; R30; C33

Regional determinants of firm entry in a developing country

We analyse the determinants of firm entry in developing countries using Argentina as an illustrative case. Our main finding is that although most of the regional determinants used in previous studies analysing developed countries are also relevant here, there is a need for additional explanatory variables that proxy for the specificities of developing economies (e.g., poverty, informal economy and idle capacity).We also find evidence of a core-periphery pattern in the spatial structure of entry that seems to be mostly driven by differences in agglomeration economies. Since regional policies aiming to attract new firms are largely based on evidence from developed countries, our results raise doubts about the usefulness of such policies when applied to developing economies. JEL classification: R12, R30, C33. Key words: Firm entry, Argentina, count data models.

Oliorelaatiotietokannan käyttö energianhallintajärjestelmässä

Empower Oy on energia-alan palveluja tarjoava yritys. Energianhallintajärjestelmää käytetään energiatietojen hallintaan ja ylläpitoon sekä tietojen esittämiseen loppukäyttäjille. Palvelun näytöt ja raportit on toteutettu web-pohjaisen käyttöliittymän kautta. Yhtiössä käynnistyi suurprojekti vanhan energianhallintajärjestelmän korvaamiseksi. Vanha järjestelmä otettiin käyttöön vuonna 1995 ja EMS-projekti käynnistettiin vuonna 2001. Diplomityö tehtiin osana EMS-projektia ja työn tavoitteina oli selvittää perusjärjestelmän käyttämän tietokantaratkaisun toimivuutta ja soveltuvuutta tehtävään sekä tutkailla eri tietokantamalleja teoreettisesti. Lisäksi työhön kuului erillisten haku- ja muutoskomponenttien ja rajapintojen toteuttaminen. Näiden avulla voidaan hakea ja muuttaa tietoa perusjärjestelmän pohjalla toimivasta oliorelaatiotietokannasta. Perusjärjestelmän DOR-tietokannaksi (Domain Object Repository) kutsuttu kokonaisuus on olioläheinen tietovarasto, josta tietoa haetaan ilmoittamalla haettavan olion tyyppi ja siihen liitoksissa olevat tyypit. Hakutulokseen mukaan haluttavat ominaisuudet ilmoitetaan kultakin tyypiltä erikseen. Haettaessa ja muutettaessa oliopohjaista DOR-tietoa, tulee noudattaa järjestelmän käyttämiä tietomalleja. Haku- ja muutoskomponentit toteutettiin Microsoftin kehittämällä .NET-teknologialla. Tietokantamallien teoreettinen tarkastelu auttoi ymmärtämään järjestelmän pohjalla toimivaa tietokantaratkaisua. Työssä selvisi, että perusjärjestelmän hyödyntämä oliorelaatiotietokanta soveltuu varsin hyvin tarkoitukseensa. Haku- ja muutoskomponenttien toteutus onnistui ja ne toimivat helppokäyttöisenä rajapintana energianhallintajärjestelmän tietokantaan.

Accelerated Microstructure Imaging via Convex Optimisation for regions with multiple fibres (AMICOx)

This paper reviews and extends our previous work to enable fast axonal diameter mapping from diffusion MRI data in the presence of multiple fibre populations within a voxel. Most of the existing mi-crostructure imaging techniques use non-linear algorithms to fit their data models and consequently, they are computationally expensive and usually slow. Moreover, most of them assume a single axon orientation while numerous regions of the brain actually present more complex configurations, e.g. fiber crossing. We present a flexible framework, based on convex optimisation, that enables fast and accurate reconstructions of the microstructure organisation, not limited to areas where the white matter is coherently oriented. We show through numerical simulations the ability of our method to correctly estimate the microstructure features (mean axon diameter and intra-cellular volume fraction) in crossing regions.